+
+You can **register for free** on our [Quant Platform](http://py4at.pqp.io) to make easy use of the Python codes in the cloud.
+
+## Copyright & Disclaimer
+
+© Dr. Yves J. Hilpisch | The Python Quants GmbH | November 2020
+
+All code and Jupyter Notebooks come without representations or warranties, to the extent permitted by applicable law. They are intended for personal use only and do not represent any investment advice or recommendation of any form.
+
+
+
+http://tpq.io | training@tpq.io | http://twitter.com/dyjh
+
diff --git a/ch01/01_pyalgo.ipynb b/ch01/01_pyalgo.ipynb
new file mode 100644
index 0000000..4fb6145
--- /dev/null
+++ b/ch01/01_pyalgo.ipynb
@@ -0,0 +1 @@
+{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" Value SMA\n", "Date \n", "2020-04-29 7790.66 7990.4138\n", "2020-04-30 7765.33 7981.0335\n", "2020-05-01 8777.63 7982.5451\n", "2020-05-02 8628.77 7981.6102\n", "2020-05-03 8824.66 7983.2674"]}, "execution_count": 6, "metadata": {}, "output_type": "execute_result"}], "source": ["d.tail()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["| \n", " | Value | \n", "SMA | \n", "
|---|---|---|
| Date | \n", "\n", " | \n", " |
| 2020-04-29 | \n", "7790.66 | \n", "7990.4138 | \n", "
| 2020-04-30 | \n", "7765.33 | \n", "7981.0335 | \n", "
| 2020-05-01 | \n", "8777.63 | \n", "7982.5451 | \n", "
| 2020-05-02 | \n", "8628.77 | \n", "7981.6102 | \n", "
| 2020-05-03 | \n", "8824.66 | \n", "7983.2674 | \n", "
![\"The](\"http://hilpisch.com/tpq_logo.png\"){kind=logo}
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"anaconda-cloud": {}, "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch02/Docker/Dockerfile b/ch02/Docker/Dockerfile new file mode 100644 index 0000000..c76ed6d --- /dev/null +++ b/ch02/Docker/Dockerfile @@ -0,0 +1,27 @@ +# +# Building a Docker Image with +# the Latest Ubuntu Version and +# Basic Python Install +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# + +# latest Ubuntu version +FROM ubuntu:latest + +# information about maintainer +MAINTAINER yves + +# add the bash script +ADD install.sh / +# change rights for the script +RUN chmod u+x /install.sh +# run the bash script +RUN /install.sh +# prepend the new path +ENV PATH /root/miniconda3/bin:$PATH + +# execute IPython when container is run +CMD ["ipython"] diff --git a/ch02/Docker/install.sh b/ch02/Docker/install.sh new file mode 100644 index 0000000..21147b7 --- /dev/null +++ b/ch02/Docker/install.sh @@ -0,0 +1,33 @@ +#!/bin/bash +# +# Script to Install +# Linux System Tools and +# Basic Python Components +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +# GENERAL LINUX +apt-get update # updates the package index cache +apt-get upgrade -y # updates packages +# installs system tools +apt-get install -y bzip2 gcc git # system tools +apt-get install -y htop screen vim wget # system tools +apt-get upgrade -y bash # upgrades bash if necessary +apt-get clean # cleans up the package index cache + +# INSTALL MINICONDA +# downloads Miniconda +wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O Miniconda.sh +bash Miniconda.sh -b # installs it +rm -rf Miniconda.sh # removes the installer +export PATH="/root/miniconda3/bin:$PATH" # prepends the new path + +# INSTALL PYTHON LIBRARIES +conda install -y pandas # installs pandas +conda install -y ipython # installs IPython shell + +# CUSTOMIZATION +cd /root/ +wget http://hilpisch.com/.vimrc # Vim configuration diff --git a/ch02/cloud/install.sh b/ch02/cloud/install.sh new file mode 100644 index 0000000..1887a10 --- /dev/null +++ b/ch02/cloud/install.sh @@ -0,0 +1,69 @@ +#!/bin/bash +# +# Script to Install +# Linux System Tools and Basic Python Components +# as well as to +# Start Jupyter Lab Server +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +# GENERAL LINUX +apt-get update # updates the package index cache +apt-get upgrade -y # updates packages +# install system tools +apt-get install -y gcc git htop # system tools +apt-get install -y screen htop vim wget # system tools +apt-get upgrade -y bash # upgrades bash if necessary +apt-get clean # cleans up the package index cache + +# INSTALLING MINICONDA +wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \ + -O Miniconda.sh +bash Miniconda.sh -b # installs Miniconda +rm -rf Miniconda.sh # removes the installer +# prepends the new path for current session +export PATH="/root/miniconda3/bin:$PATH" +# prepends the new path in the shell configuration +cat >> ~/.profile <
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading"]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Chapter 03 — Working with Financial Data**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Sample Data Set from Eikon"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Reading Financial Data From Different Sources"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### The Data Set"]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["fn = '../data/AAPL.csv'"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Date,HIGH,CLOSE,LOW,OPEN,COUNT,VOLUME\n", "2020-04-01,248.72,240.91,239.13,246.5,460606.0,44054638.0\n", "2020-04-02,245.15,244.93,236.9,240.34,380294.0,41483493.0\n", "2020-04-03,245.7,241.41,238.9741,242.8,293699.0,32470017.0\n", "2020-04-06,263.11,262.47,249.38,250.9,486681.0,50455071.0\n"]}], "source": ["with open(fn, 'r') as f:\n", " for _ in range(5):\n", " print(f.readline(), end='')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Reading from a CSV File with Python"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": ["import csv"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": ["csv_reader = csv.reader(open(fn, 'r'))"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": ["data = [l for l in csv_reader]"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [{"data": {"text/plain": ["[['Date', 'HIGH', 'CLOSE', 'LOW', 'OPEN', 'COUNT', 'VOLUME'],\n", " ['2020-04-01',\n", " '248.72',\n", " '240.91',\n", " '239.13',\n", " '246.5',\n", " '460606.0',\n", " '44054638.0'],\n", " ['2020-04-02',\n", " '245.15',\n", " '244.93',\n", " '236.9',\n", " '240.34',\n", " '380294.0',\n", " '41483493.0'],\n", " ['2020-04-03',\n", " '245.7',\n", " '241.41',\n", " '238.9741',\n", " '242.8',\n", " '293699.0',\n", " '32470017.0'],\n", " ['2020-04-06',\n", " '263.11',\n", " '262.47',\n", " '249.38',\n", " '250.9',\n", " '486681.0',\n", " '50455071.0']]"]}, "execution_count": 6, "metadata": {}, "output_type": "execute_result"}], "source": ["data[:5]"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": ["csv_reader = csv.DictReader(open(fn, 'r'))"]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": ["data = [l for l in csv_reader]"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [{"data": {"text/plain": ["[OrderedDict([('Date', '2020-04-01'),\n", " ('HIGH', '248.72'),\n", " ('CLOSE', '240.91'),\n", " ('LOW', '239.13'),\n", " ('OPEN', '246.5'),\n", " ('COUNT', '460606.0'),\n", " ('VOLUME', '44054638.0')]),\n", " OrderedDict([('Date', '2020-04-02'),\n", " ('HIGH', '245.15'),\n", " ('CLOSE', '244.93'),\n", " ('LOW', '236.9'),\n", " ('OPEN', '240.34'),\n", " ('COUNT', '380294.0'),\n", " ('VOLUME', '41483493.0')]),\n", " OrderedDict([('Date', '2020-04-03'),\n", " ('HIGH', '245.7'),\n", " ('CLOSE', '241.41'),\n", " ('LOW', '238.9741'),\n", " ('OPEN', '242.8'),\n", " ('COUNT', '293699.0'),\n", " ('VOLUME', '32470017.0')])]"]}, "execution_count": 9, "metadata": {}, "output_type": "execute_result"}], "source": ["data[:3]"]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"data": {"text/plain": ["272.38619047619045"]}, "execution_count": 10, "metadata": {}, "output_type": "execute_result"}], "source": ["sum([float(l['CLOSE']) for l in data]) / len(data)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Reading from a CSV File with pandas"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": ["import pandas as pd"]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": ["data = pd.read_csv(fn, index_col=0,\n", " parse_dates=True)"]}, {"cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" HIGH CLOSE LOW OPEN COUNT VOLUME\n", "Date \n", "2020-04-24 283.01 282.97 277.00 277.20 306176.0 31627183.0\n", "2020-04-27 284.54 283.17 279.95 281.80 300771.0 29271893.0\n", "2020-04-28 285.83 278.58 278.20 285.08 285384.0 28001187.0\n", "2020-04-29 289.67 287.73 283.89 284.73 324890.0 34320204.0\n", "2020-04-30 294.53 293.80 288.35 289.96 471129.0 45765968.0"]}, "execution_count": 14, "metadata": {}, "output_type": "execute_result"}], "source": ["data.tail()"]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [{"data": {"text/plain": ["272.38619047619056"]}, "execution_count": 15, "metadata": {}, "output_type": "execute_result"}], "source": ["data['CLOSE'].mean()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Exporting to Excel and JSON"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Create the local `data` folder if necessary via\n", "\n", " !mkdir data"]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": ["data.to_excel('data/aapl.xls', 'AAPL')"]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": ["data.to_json('data/aapl.json')"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["total 24\n", "-rw-r--r-- 1 501 20 3067 May 7 11:15 aapl.json\n", "-rw-r--r-- 1 501 20 5632 May 7 11:15 aapl.xls\n"]}], "source": ["ls -n data/"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Reading from Excel and JSON"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": ["data_copy_1 = pd.read_excel('data/aapl.xls', 'AAPL',\n", " index_col=0)"]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | HIGH | \n", "CLOSE | \n", "LOW | \n", "OPEN | \n", "COUNT | \n", "VOLUME | \n", "
|---|---|---|---|---|---|---|
| Date | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
| 2020-04-24 | \n", "283.01 | \n", "282.97 | \n", "277.00 | \n", "277.20 | \n", "306176.0 | \n", "31627183.0 | \n", "
| 2020-04-27 | \n", "284.54 | \n", "283.17 | \n", "279.95 | \n", "281.80 | \n", "300771.0 | \n", "29271893.0 | \n", "
| 2020-04-28 | \n", "285.83 | \n", "278.58 | \n", "278.20 | \n", "285.08 | \n", "285384.0 | \n", "28001187.0 | \n", "
| 2020-04-29 | \n", "289.67 | \n", "287.73 | \n", "283.89 | \n", "284.73 | \n", "324890.0 | \n", "34320204.0 | \n", "
| 2020-04-30 | \n", "294.53 | \n", "293.80 | \n", "288.35 | \n", "289.96 | \n", "471129.0 | \n", "45765968.0 | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" HIGH CLOSE LOW OPEN COUNT VOLUME\n", "Date \n", "2020-04-01 248.72 240.91 239.1300 246.50 460606 44054638\n", "2020-04-02 245.15 244.93 236.9000 240.34 380294 41483493\n", "2020-04-03 245.70 241.41 238.9741 242.80 293699 32470017\n", "2020-04-06 263.11 262.47 249.3800 250.90 486681 50455071\n", "2020-04-07 271.70 259.43 259.0000 270.80 467375 50721831"]}, "execution_count": 20, "metadata": {}, "output_type": "execute_result"}], "source": ["data_copy_1.head()"]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": ["data_copy_2 = pd.read_json('data/aapl.json')"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | HIGH | \n", "CLOSE | \n", "LOW | \n", "OPEN | \n", "COUNT | \n", "VOLUME | \n", "
|---|---|---|---|---|---|---|
| Date | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
| 2020-04-01 | \n", "248.72 | \n", "240.91 | \n", "239.1300 | \n", "246.50 | \n", "460606 | \n", "44054638 | \n", "
| 2020-04-02 | \n", "245.15 | \n", "244.93 | \n", "236.9000 | \n", "240.34 | \n", "380294 | \n", "41483493 | \n", "
| 2020-04-03 | \n", "245.70 | \n", "241.41 | \n", "238.9741 | \n", "242.80 | \n", "293699 | \n", "32470017 | \n", "
| 2020-04-06 | \n", "263.11 | \n", "262.47 | \n", "249.3800 | \n", "250.90 | \n", "486681 | \n", "50455071 | \n", "
| 2020-04-07 | \n", "271.70 | \n", "259.43 | \n", "259.0000 | \n", "270.80 | \n", "467375 | \n", "50721831 | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" HIGH CLOSE LOW OPEN COUNT VOLUME\n", "2020-04-01 248.72 240.91 239.1300 246.50 460606 44054638\n", "2020-04-02 245.15 244.93 236.9000 240.34 380294 41483493\n", "2020-04-03 245.70 241.41 238.9741 242.80 293699 32470017\n", "2020-04-06 263.11 262.47 249.3800 250.90 486681 50455071\n", "2020-04-07 271.70 259.43 259.0000 270.80 467375 50721831"]}, "execution_count": 22, "metadata": {}, "output_type": "execute_result"}], "source": ["data_copy_2.head()"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": ["!rm data/*"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Working with Open Data Sources"]}, {"cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [{"data": {"text/plain": ["['../pyalgo.cfg']"]}, "execution_count": 24, "metadata": {}, "output_type": "execute_result"}], "source": ["import configparser\n", "config = configparser.ConfigParser()\n", "config.read('../pyalgo.cfg')"]}, {"cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": ["import quandl as q"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": ["data = q.get('BCHAIN/MKPRU', api_key=config['quandl']['api_key'])"]}, {"cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["| \n", " | HIGH | \n", "CLOSE | \n", "LOW | \n", "OPEN | \n", "COUNT | \n", "VOLUME | \n", "
|---|---|---|---|---|---|---|
| 2020-04-01 | \n", "248.72 | \n", "240.91 | \n", "239.1300 | \n", "246.50 | \n", "460606 | \n", "44054638 | \n", "
| 2020-04-02 | \n", "245.15 | \n", "244.93 | \n", "236.9000 | \n", "240.34 | \n", "380294 | \n", "41483493 | \n", "
| 2020-04-03 | \n", "245.70 | \n", "241.41 | \n", "238.9741 | \n", "242.80 | \n", "293699 | \n", "32470017 | \n", "
| 2020-04-06 | \n", "263.11 | \n", "262.47 | \n", "249.3800 | \n", "250.90 | \n", "486681 | \n", "50455071 | \n", "
| 2020-04-07 | \n", "271.70 | \n", "259.43 | \n", "259.0000 | \n", "270.80 | \n", "467375 | \n", "50721831 | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" IvMean30 IvMean60 IvMean90\n", "Date \n", "2018-12-24 0.4310 0.4112 0.3829\n", "2018-12-26 0.4059 0.3844 0.3587\n", "2018-12-27 0.3918 0.3879 0.3618\n", "2018-12-28 0.3940 0.3736 0.3482\n", "2018-12-31 0.3760 0.3519 0.3310"]}, "execution_count": 34, "metadata": {}, "output_type": "execute_result"}], "source": ["vol[['IvMean30', 'IvMean60', 'IvMean90']].tail()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Refinitiv Eikon Data API"]}, {"cell_type": "markdown", "metadata": {}, "source": ["`pip install eikon` — Requires a paid subscription."]}, {"cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": ["import eikon as ek"]}, {"cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["2020-05-07 11:15:56,323 P[87076] [MainThread 4326989248] Error on handshake port 9000 : ReadTimeout(ReadTimeout())\n"]}], "source": ["ek.set_app_key(config['eikon']['app_key'])"]}, {"cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Help on package eikon:\n", "\n", "NAME\n", " eikon - # coding: utf-8\n", "\n", "PACKAGE CONTENTS\n", " Profile\n", " data_grid\n", " eikonError\n", " json_requests\n", " news_request\n", " streaming_session (package)\n", " symbology\n", " time_series\n", " tools\n", "\n", "SUBMODULES\n", " cache\n", " desktop_session\n", " istream_callback\n", " itemstream\n", " session\n", " stream\n", " stream_connection\n", " streamingprice\n", " streamingprice_callback\n", " streamingprices\n", "\n", "VERSION\n", " 1.1.2\n", "\n", "FILE\n", " /Users/yves/Python/lib/python3.7/site-packages/eikon/__init__.py\n", "\n", "\n"]}], "source": ["help(ek)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Retrieving Historical Structured Data"]}, {"cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [], "source": ["import warnings; warnings.simplefilter('ignore')"]}, {"cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [], "source": ["symbols = ['AAPL.O', 'MSFT.O', 'GOOG.O']"]}, {"cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": ["data = ek.get_timeseries(symbols,\n", " start_date='2020-01-01',\n", " end_date='2020-05-01',\n", " interval='daily',\n", " fields=['*'])"]}, {"cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [{"data": {"text/plain": ["MultiIndex([('AAPL.O', 'HIGH'),\n", " ('AAPL.O', 'CLOSE'),\n", " ('AAPL.O', 'LOW'),\n", " ('AAPL.O', 'OPEN'),\n", " ('AAPL.O', 'COUNT'),\n", " ('AAPL.O', 'VOLUME'),\n", " ('MSFT.O', 'HIGH'),\n", " ('MSFT.O', 'CLOSE'),\n", " ('MSFT.O', 'LOW'),\n", " ('MSFT.O', 'OPEN'),\n", " ('MSFT.O', 'COUNT'),\n", " ('MSFT.O', 'VOLUME'),\n", " ('GOOG.O', 'HIGH'),\n", " ('GOOG.O', 'CLOSE'),\n", " ('GOOG.O', 'LOW'),\n", " ('GOOG.O', 'OPEN'),\n", " ('GOOG.O', 'COUNT'),\n", " ('GOOG.O', 'VOLUME')],\n", " names=['Security', 'Field'])"]}, "execution_count": 41, "metadata": {}, "output_type": "execute_result"}], "source": ["data.keys()"]}, {"cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [{"data": {"text/plain": ["pandas.core.frame.DataFrame"]}, "execution_count": 42, "metadata": {}, "output_type": "execute_result"}], "source": ["type(data['AAPL.O'])"]}, {"cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["| \n", " | IvMean30 | \n", "IvMean60 | \n", "IvMean90 | \n", "
|---|---|---|---|
| Date | \n", "\n", " | \n", " | \n", " |
| 2018-12-24 | \n", "0.4310 | \n", "0.4112 | \n", "0.3829 | \n", "
| 2018-12-26 | \n", "0.4059 | \n", "0.3844 | \n", "0.3587 | \n", "
| 2018-12-27 | \n", "0.3918 | \n", "0.3879 | \n", "0.3618 | \n", "
| 2018-12-28 | \n", "0.3940 | \n", "0.3736 | \n", "0.3482 | \n", "
| 2018-12-31 | \n", "0.3760 | \n", "0.3519 | \n", "0.3310 | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": ["Field HIGH CLOSE LOW OPEN COUNT VOLUME\n", "Date \n", "2020-04-27 284.54 283.17 279.95 281.80 300771.0 29271893.0\n", "2020-04-28 285.83 278.58 278.20 285.08 285384.0 28001187.0\n", "2020-04-29 289.67 287.73 283.89 284.73 324890.0 34320204.0\n", "2020-04-30 294.53 293.80 288.35 289.96 471129.0 45765968.0\n", "2020-05-01 299.00 289.07 285.85 286.25 558319.0 60154175.0"]}, "execution_count": 44, "metadata": {}, "output_type": "execute_result"}], "source": ["data['AAPL.O'].tail()"]}, {"cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["CPU times: user 44.2 ms, sys: 2.87 ms, total: 47.1 ms\n", "Wall time: 10.7 s\n"]}], "source": ["%%time\n", "data = ek.get_timeseries(symbols,\n", " start_date='2020-05-05',\n", " end_date='2020-05-06',\n", " interval='minute',\n", " fields='*')"]}, {"cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Field HIGH LOW OPEN CLOSE COUNT VOLUME\n", "Date \n", "2020-05-05 16:00:00 1367.4 1366.1 1366.4 1367.2 82.0 3308.0\n", "2020-05-05 16:01:00 1369.0 1367.2 1367.4 1368.8 210.0 5455.0\n", "2020-05-05 16:02:00 1369.5 1368.4 1368.8 1368.9 176.0 4900.0\n", "2020-05-05 16:03:00 1369.8 1368.4 1369.2 1368.4 162.0 6133.0\n", "2020-05-05 16:04:00 1369.3 1367.9 1368.4 1368.6 140.0 5080.0\n"]}], "source": ["print(data['GOOG.O'].loc['2020-05-05 16:00:00':\n", " '2020-05-05 16:04:00'].round(1))"]}, {"cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "AAPL.O\n", " Field HIGH LOW OPEN CLOSE COUNT VOLUME\n", "Date \n", "2020-05-05 19:01:00 300.9 300.7 300.9 300.7 917.0 88059.0\n", "2020-05-05 19:02:00 300.9 300.7 300.7 300.8 634.0 60998.0\n", "2020-05-05 19:03:00 300.8 300.6 300.8 300.7 733.0 75349.0\n", "2020-05-05 19:04:00 300.8 300.6 300.7 300.8 632.0 56220.0\n", "2020-05-05 19:05:00 300.9 300.8 300.8 300.9 522.0 51194.0\n", "\n", "MSFT.O\n", " Field HIGH LOW OPEN CLOSE COUNT VOLUME\n", "Date \n", "2020-05-05 19:01:00 183.6 183.5 183.6 183.5 679.0 73198.0\n", "2020-05-05 19:02:00 183.6 183.5 183.5 183.6 595.0 79593.0\n", "2020-05-05 19:03:00 183.6 183.5 183.6 183.6 505.0 61200.0\n", "2020-05-05 19:04:00 183.6 183.5 183.6 183.6 357.0 27781.0\n", "2020-05-05 19:05:00 183.6 183.6 183.6 183.6 592.0 54057.0\n", "\n", "GOOG.O\n", " Field HIGH LOW OPEN CLOSE COUNT VOLUME\n", "Date \n", "2020-05-05 19:01:00 1369.8 1368.7 1369.5 1369.0 158.0 5056.0\n", "2020-05-05 19:02:00 1369.6 1368.7 1368.9 1368.9 32.0 950.0\n", "2020-05-05 19:03:00 1369.5 1367.9 1369.3 1368.4 174.0 5186.0\n", "2020-05-05 19:04:00 1369.2 1368.0 1368.8 1368.7 76.0 2809.0\n", "2020-05-05 19:05:00 1369.6 1368.7 1368.7 1369.0 46.0 1186.0\n"]}], "source": ["for sym in symbols:\n", " print('\\n' + sym + '\\n', data[sym].iloc[-300:-295].round(1))"]}, {"cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["CPU times: user 219 ms, sys: 16.1 ms, total: 235 ms\n", "Wall time: 7.34 s\n"]}], "source": ["%%time\n", "data = ek.get_timeseries(symbols[0],\n", " start_date='2020-05-05 15:00:00',\n", " end_date='2020-05-05 16:00:00',\n", " interval='tick',\n", " fields=['*'])"]}, {"cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["| Field | \n", "HIGH | \n", "CLOSE | \n", "LOW | \n", "OPEN | \n", "COUNT | \n", "VOLUME | \n", "
|---|---|---|---|---|---|---|
| Date | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
| 2020-04-27 | \n", "284.54 | \n", "283.17 | \n", "279.95 | \n", "281.80 | \n", "300771.0 | \n", "29271893.0 | \n", "
| 2020-04-28 | \n", "285.83 | \n", "278.58 | \n", "278.20 | \n", "285.08 | \n", "285384.0 | \n", "28001187.0 | \n", "
| 2020-04-29 | \n", "289.67 | \n", "287.73 | \n", "283.89 | \n", "284.73 | \n", "324890.0 | \n", "34320204.0 | \n", "
| 2020-04-30 | \n", "294.53 | \n", "293.80 | \n", "288.35 | \n", "289.96 | \n", "471129.0 | \n", "45765968.0 | \n", "
| 2020-05-01 | \n", "299.00 | \n", "289.07 | \n", "285.85 | \n", "286.25 | \n", "558319.0 | \n", "60154175.0 | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": ["AAPL.O VALUE VOLUME\n", "Date \n", "2020-05-05 15:00:00.012 298.05 100.0\n", "2020-05-05 15:00:00.013 298.05 100.0\n", "2020-05-05 15:00:00.013 298.05 60.0\n", "2020-05-05 15:00:00.013 298.05 40.0\n", "2020-05-05 15:00:00.013 298.05 56.0"]}, "execution_count": 50, "metadata": {}, "output_type": "execute_result"}], "source": ["data.head()"]}, {"cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [], "source": ["resampled = data.resample('30s', label='right').agg(\n", " {'VALUE': 'last', 'VOLUME': 'sum'}) # <6>"]}, {"cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [{"data": {"text/html": ["| AAPL.O | \n", "VALUE | \n", "VOLUME | \n", "
|---|---|---|
| Date | \n", "\n", " | \n", " |
| 2020-05-05 15:00:00.012 | \n", "298.05 | \n", "100.0 | \n", "
| 2020-05-05 15:00:00.013 | \n", "298.05 | \n", "100.0 | \n", "
| 2020-05-05 15:00:00.013 | \n", "298.05 | \n", "60.0 | \n", "
| 2020-05-05 15:00:00.013 | \n", "298.05 | \n", "40.0 | \n", "
| 2020-05-05 15:00:00.013 | \n", "298.05 | \n", "56.0 | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" VALUE VOLUME\n", "Date \n", "2020-05-05 15:58:00 298.8750 11129.0\n", "2020-05-05 15:58:30 298.9601 19818.0\n", "2020-05-05 15:59:00 298.9000 18750.0\n", "2020-05-05 15:59:30 298.9700 28733.0\n", "2020-05-05 16:00:00 298.8900 24757.0"]}, "execution_count": 52, "metadata": {}, "output_type": "execute_result"}], "source": ["resampled.tail()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Retrieving Historical Unstructured Data"]}, {"cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [], "source": ["headlines = ek.get_news_headlines(query='R:AAPL.O macbook',\n", " count=5,\n", " date_from='2020-4-1',\n", " date_to='2020-5-1')"]}, {"cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | VALUE | \n", "VOLUME | \n", "
|---|---|---|
| Date | \n", "\n", " | \n", " |
| 2020-05-05 15:58:00 | \n", "298.8750 | \n", "11129.0 | \n", "
| 2020-05-05 15:58:30 | \n", "298.9601 | \n", "19818.0 | \n", "
| 2020-05-05 15:59:00 | \n", "298.9000 | \n", "18750.0 | \n", "
| 2020-05-05 15:59:30 | \n", "298.9700 | \n", "28733.0 | \n", "
| 2020-05-05 16:00:00 | \n", "298.8900 | \n", "24757.0 | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" versionCreated \\\n", "2020-04-20 21:33:37.332 2020-04-20 21:33:37.332000+00:00 \n", "2020-04-20 10:20:23.201 2020-04-20 10:20:23.201000+00:00 \n", "2020-04-20 02:32:27.721 2020-04-20 02:32:27.721000+00:00 \n", "2020-04-15 12:06:58.693 2020-04-15 12:06:58.693000+00:00 \n", "2020-04-09 21:34:08.671 2020-04-09 21:34:08.671000+00:00 \n", "\n", " text \\\n", "2020-04-20 21:33:37.332 Apple said to launch new AirPods, MacBook Pro ... \n", "2020-04-20 10:20:23.201 Apple might launch upgraded AirPods, 13-inch M... \n", "2020-04-20 02:32:27.721 Apple to reportedly launch new AirPods alongsi... \n", "2020-04-15 12:06:58.693 Apple files a patent for iPhones, MacBook indu... \n", "2020-04-09 21:34:08.671 Apple rolls out new software update for MacBoo... \n", "\n", " storyId \\\n", "2020-04-20 21:33:37.332 urn:newsml:reuters.com:20200420:nNRAble9rq:1 \n", "2020-04-20 10:20:23.201 urn:newsml:reuters.com:20200420:nNRAbl8eob:1 \n", "2020-04-20 02:32:27.721 urn:newsml:reuters.com:20200420:nNRAbl4mfz:1 \n", "2020-04-15 12:06:58.693 urn:newsml:reuters.com:20200415:nNRAbjvsix:1 \n", "2020-04-09 21:34:08.671 urn:newsml:reuters.com:20200409:nNRAbi2nbb:1 \n", "\n", " sourceCode \n", "2020-04-20 21:33:37.332 NS:TIMIND \n", "2020-04-20 10:20:23.201 NS:BUSSTA \n", "2020-04-20 02:32:27.721 NS:HINDUT \n", "2020-04-15 12:06:58.693 NS:HINDUT \n", "2020-04-09 21:34:08.671 NS:TIMIND "]}, "execution_count": 54, "metadata": {}, "output_type": "execute_result"}], "source": ["headlines"]}, {"cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [], "source": ["story = headlines.iloc[0]"]}, {"cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [{"data": {"text/plain": ["versionCreated 2020-04-20 21:33:37.332000+00:00\n", "text Apple said to launch new AirPods, MacBook Pro ...\n", "storyId urn:newsml:reuters.com:20200420:nNRAble9rq:1\n", "sourceCode NS:TIMIND\n", "Name: 2020-04-20 21:33:37.332000, dtype: object"]}, "execution_count": 56, "metadata": {}, "output_type": "execute_result"}], "source": ["story"]}, {"cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [], "source": ["news_text = ek.get_news_story(story['storyId'])"]}, {"cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [], "source": ["from IPython.display import HTML"]}, {"cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | versionCreated | \n", "text | \n", "storyId | \n", "sourceCode | \n", "
|---|---|---|---|---|
| 2020-04-20 21:33:37.332 | \n", "2020-04-20 21:33:37.332000+00:00 | \n", "Apple said to launch new AirPods, MacBook Pro ... | \n", "urn:newsml:reuters.com:20200420:nNRAble9rq:1 | \n", "NS:TIMIND | \n", "
| 2020-04-20 10:20:23.201 | \n", "2020-04-20 10:20:23.201000+00:00 | \n", "Apple might launch upgraded AirPods, 13-inch M... | \n", "urn:newsml:reuters.com:20200420:nNRAbl8eob:1 | \n", "NS:BUSSTA | \n", "
| 2020-04-20 02:32:27.721 | \n", "2020-04-20 02:32:27.721000+00:00 | \n", "Apple to reportedly launch new AirPods alongsi... | \n", "urn:newsml:reuters.com:20200420:nNRAbl4mfz:1 | \n", "NS:HINDUT | \n", "
| 2020-04-15 12:06:58.693 | \n", "2020-04-15 12:06:58.693000+00:00 | \n", "Apple files a patent for iPhones, MacBook indu... | \n", "urn:newsml:reuters.com:20200415:nNRAbjvsix:1 | \n", "NS:HINDUT | \n", "
| 2020-04-09 21:34:08.671 | \n", "2020-04-09 21:34:08.671000+00:00 | \n", "Apple rolls out new software update for MacBoo... | \n", "urn:newsml:reuters.com:20200409:nNRAbi2nbb:1 | \n", "NS:TIMIND | \n", "
NEW DELHI: Apple recently launched its much-awaited affordable smartphone iPhone SE. Now it seems that the company is gearing up for another launch. Apple is said to launch the next generation of AirPods and the all-new 13-inch MacBook Pro next month.
In February an online report revealed that the Cupertino-based tech giant is working on AirPods Pro Lite. Now a tweet by tipster Job Posser has revealed that Apple will soon come up with new AirPods and MacBook Pro. Jon Posser tweeted, \"New AirPods (which were supposed to be at the March Event) is now ready to go.
Probably alongside the MacBook Pro next month.\" However, not many details about the upcoming products are available right now. The company was supposed to launch these products at the March event along with the iPhone SE.
But due to the ongoing pandemic coronavirus, the event got cancelled. It is expected that Apple will launch the AirPods Pro Lite and the 13-inch MacBook Pro just like the way it launched the iPhone SE. Meanwhile, Apple has scheduled its annual developer conference WWDC to take place in June.
This year the company has decided to hold an online-only event due to the outbreak of coronavirus. Reports suggest that this year the company is planning to launch the all-new AirTags and a premium pair of over-ear Bluetooth headphones at the event. Using the Apple AirTags users will be able to locate real-world items such as keys or suitcase in the Find My app.
The AirTags will also have offline finding capabilities that the company introduced in the core of iOS 13.Apart from this, Apple is also said to unveil its high-end Bluetooth headphones. It is expected that the Bluetooth headphones will offer better sound quality and battery backup as compared to the AirPods.
For Reprint Rights: timescontent.com
Copyright (c) 2020 BENNETT,COLEMAN & CO.LTD.
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"anaconda-cloud": {}, "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch03/sample_data.py b/ch03/sample_data.py new file mode 100644 index 0000000..338df40 --- /dev/null +++ b/ch03/sample_data.py @@ -0,0 +1,57 @@ +# +# Python Module to Generate a +# Sample Financial Data Set +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import numpy as np +import pandas as pd + +r = 0.05 # constant short rate +sigma = 0.5 # volatility factor + + +def generate_sample_data(rows, cols, freq='1min'): + ''' + Function to generate sample financial data. + + Parameters + ========== + rows: int + number of rows to generate + cols: int + number of columns to generate + freq: str + frequency string for DatetimeIndex + + Returns + ======= + df: DataFrame + DataFrame object with the sample data + ''' + rows = int(rows) + cols = int(cols) + # generate a DatetimeIndex object given the frequency + index = pd.date_range('2021-1-1', periods=rows, freq=freq) + # determine time delta in year fractions + dt = (index[1] - index[0]) / pd.Timedelta(value='365D') + # generate column names + columns = ['No%d' % i for i in range(cols)] + # generate sample paths for geometric Brownian motion + raw = np.exp(np.cumsum((r - 0.5 * sigma ** 2) * dt + + sigma * np.sqrt(dt) * + np.random.standard_normal((rows, cols)), axis=0)) + # normalize the data to start at 100 + raw = raw / raw[0] * 100 + # generate the DataFrame object + df = pd.DataFrame(raw, index=index, columns=columns) + return df + + +if __name__ == '__main__': + rows = 5 # number of rows + columns = 3 # number of columns + freq = 'D' # daily frequency + print(generate_sample_data(rows, columns, freq)) diff --git a/ch04/04_pyalgo.ipynb b/ch04/04_pyalgo.ipynb new file mode 100644 index 0000000..ff883a1 --- /dev/null +++ b/ch04/04_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading"]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Chapter 04 — Vectorized Backtesting**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Making Use of Vectorization"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Vectorization with NumPy "]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["v = [1, 2, 3, 4, 5]"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["sm = [2 * i for i in v]"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [{"data": {"text/plain": ["[2, 4, 6, 8, 10]"]}, "execution_count": 3, "metadata": {}, "output_type": "execute_result"}], "source": ["sm"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [{"data": {"text/plain": ["[1, 2, 3, 4, 5, 1, 2, 3, 4, 5]"]}, "execution_count": 4, "metadata": {}, "output_type": "execute_result"}], "source": ["2 * v"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": ["import numpy as np"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": ["a = np.array(v)"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([1, 2, 3, 4, 5])"]}, "execution_count": 7, "metadata": {}, "output_type": "execute_result"}], "source": ["a"]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [{"data": {"text/plain": ["numpy.ndarray"]}, "execution_count": 8, "metadata": {}, "output_type": "execute_result"}], "source": ["type(a)"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 2, 4, 6, 8, 10])"]}, "execution_count": 9, "metadata": {}, "output_type": "execute_result"}], "source": ["2 * a"]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([2.5, 3. , 3.5, 4. , 4.5])"]}, "execution_count": 10, "metadata": {}, "output_type": "execute_result"}], "source": ["0.5 * a + 2"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": ["a = np.arange(12).reshape((4, 3))"]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0, 1, 2],\n", " [ 3, 4, 5],\n", " [ 6, 7, 8],\n", " [ 9, 10, 11]])"]}, "execution_count": 12, "metadata": {}, "output_type": "execute_result"}], "source": ["a"]}, {"cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0, 2, 4],\n", " [ 6, 8, 10],\n", " [12, 14, 16],\n", " [18, 20, 22]])"]}, "execution_count": 13, "metadata": {}, "output_type": "execute_result"}], "source": ["2 * a"]}, {"cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0, 1, 4],\n", " [ 9, 16, 25],\n", " [ 36, 49, 64],\n", " [ 81, 100, 121]])"]}, "execution_count": 14, "metadata": {}, "output_type": "execute_result"}], "source": ["a ** 2"]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [{"data": {"text/plain": ["5.5"]}, "execution_count": 15, "metadata": {}, "output_type": "execute_result"}], "source": ["a.mean()"]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [{"data": {"text/plain": ["5.5"]}, "execution_count": 16, "metadata": {}, "output_type": "execute_result"}], "source": ["np.mean(a)"]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([4.5, 5.5, 6.5])"]}, "execution_count": 17, "metadata": {}, "output_type": "execute_result"}], "source": ["a.mean(axis=0)"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 1., 4., 7., 10.])"]}, "execution_count": 18, "metadata": {}, "output_type": "execute_result"}], "source": ["np.mean(a, axis=1)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Vectorization with pandas"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": ["a = np.arange(15).reshape(5, 3)"]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0, 1, 2],\n", " [ 3, 4, 5],\n", " [ 6, 7, 8],\n", " [ 9, 10, 11],\n", " [12, 13, 14]])"]}, "execution_count": 20, "metadata": {}, "output_type": "execute_result"}], "source": ["a"]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": ["import pandas as pd"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": ["columns = list('abc')"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [{"data": {"text/plain": ["['a', 'b', 'c']"]}, "execution_count": 23, "metadata": {}, "output_type": "execute_result"}], "source": ["columns"]}, {"cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": ["index = pd.date_range('2021-7-1', periods=5, freq='B')"]}, {"cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [{"data": {"text/plain": ["DatetimeIndex(['2021-07-01', '2021-07-02', '2021-07-05', '2021-07-06',\n", " '2021-07-07'],\n", " dtype='datetime64[ns]', freq='B')"]}, "execution_count": 25, "metadata": {}, "output_type": "execute_result"}], "source": ["index"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": ["df = pd.DataFrame(a, columns=columns, index=index)"]}, {"cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [{"data": {"text/html": ["
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"], "text/plain": [" a b c\n", "2021-07-01 0 2 4\n", "2021-07-02 6 8 10\n", "2021-07-05 12 14 16\n", "2021-07-06 18 20 22\n", "2021-07-07 24 26 28"]}, "execution_count": 28, "metadata": {}, "output_type": "execute_result"}], "source": ["2 * df"]}, {"cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [{"data": {"text/plain": ["a 30\n", "b 35\n", "c 40\n", "dtype: int64"]}, "execution_count": 29, "metadata": {}, "output_type": "execute_result"}], "source": ["df.sum()"]}, {"cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [{"data": {"text/plain": ["a 6.0\n", "b 7.0\n", "c 8.0\n", "dtype: float64"]}, "execution_count": 30, "metadata": {}, "output_type": "execute_result"}], "source": ["np.mean(df)"]}, {"cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [{"data": {"text/plain": ["2021-07-01 2\n", "2021-07-02 8\n", "2021-07-05 14\n", "2021-07-06 20\n", "2021-07-07 26\n", "Freq: B, dtype: int64"]}, "execution_count": 31, "metadata": {}, "output_type": "execute_result"}], "source": ["df['a'] + df['c']"]}, {"cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [{"data": {"text/plain": ["2021-07-01 0.0\n", "2021-07-02 4.5\n", "2021-07-05 9.0\n", "2021-07-06 13.5\n", "2021-07-07 18.0\n", "Freq: B, dtype: float64"]}, "execution_count": 32, "metadata": {}, "output_type": "execute_result"}], "source": ["0.5 * df.a + 2 * df.b - df.c"]}, {"cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [{"data": {"text/plain": ["2021-07-01 False\n", "2021-07-02 False\n", "2021-07-05 True\n", "2021-07-06 True\n", "2021-07-07 True\n", "Freq: B, Name: a, dtype: bool"]}, "execution_count": 33, "metadata": {}, "output_type": "execute_result"}], "source": ["df['a'] > 5"]}, {"cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | a | \n", "b | \n", "c | \n", "
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| 2021-07-06 | \n", "18 | \n", "20 | \n", "22 | \n", "
| 2021-07-07 | \n", "24 | \n", "26 | \n", "28 | \n", "
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"], "text/plain": [" a b c\n", "2021-07-05 6 7 8\n", "2021-07-06 9 10 11\n", "2021-07-07 12 13 14"]}, "execution_count": 34, "metadata": {}, "output_type": "execute_result"}], "source": ["df[df['a'] > 5]"]}, {"cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [{"data": {"text/plain": ["2021-07-01 True\n", "2021-07-02 True\n", "2021-07-05 True\n", "2021-07-06 True\n", "2021-07-07 True\n", "Freq: B, dtype: bool"]}, "execution_count": 35, "metadata": {}, "output_type": "execute_result"}], "source": ["df['c'] > df['b']"]}, {"cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [{"data": {"text/plain": ["2021-07-01 False\n", "2021-07-02 False\n", "2021-07-05 False\n", "2021-07-06 True\n", "2021-07-07 True\n", "Freq: B, dtype: bool"]}, "execution_count": 36, "metadata": {}, "output_type": "execute_result"}], "source": ["0.15 * df.a + df.b > df.c"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Strategies based on Simple Moving Averages"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Getting into the Basics "]}, {"cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": ["raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv',\n", " index_col=0, parse_dates=True).dropna()"]}, {"cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["| \n", " | a | \n", "b | \n", "c | \n", "
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| 2021-07-07 | \n", "12 | \n", "13 | \n", "14 | \n", "
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"], "text/plain": [" price SMA1 SMA2\n", "Date \n", "2019-12-24 1.1087 1.107698 1.119630\n", "2019-12-26 1.1096 1.107740 1.119529\n", "2019-12-27 1.1175 1.107924 1.119428\n", "2019-12-30 1.1197 1.108131 1.119333\n", "2019-12-31 1.1210 1.108279 1.119231"]}, "execution_count": 44, "metadata": {}, "output_type": "execute_result"}], "source": ["data.tail()"]}, {"cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": ["%matplotlib inline\n", "from pylab import mpl, plt\n", "plt.style.use('seaborn')\n", "mpl.rcParams['font.family'] = 'serif'"]}, {"cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["| \n", " | price | \n", "SMA1 | \n", "SMA2 | \n", "
|---|---|---|---|
| Date | \n", "\n", " | \n", " | \n", " |
| 2019-12-24 | \n", "1.1087 | \n", "1.107698 | \n", "1.119630 | \n", "
| 2019-12-26 | \n", "1.1096 | \n", "1.107740 | \n", "1.119529 | \n", "
| 2019-12-27 | \n", "1.1175 | \n", "1.107924 | \n", "1.119428 | \n", "
| 2019-12-30 | \n", "1.1197 | \n", "1.108131 | \n", "1.119333 | \n", "
| 2019-12-31 | \n", "1.1210 | \n", "1.108279 | \n", "1.119231 | \n", "
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data.plot(title='AAPL stock price | 42 & 252 days SMAs',\n", " figsize=(10, 6));\n", "# plt.savefig('../../images/ch04/sma_plot_1.png')"]}, {"cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [], "source": ["data['position'] = np.where(data['SMA1'] > data['SMA2'],\n", " 1, -1)"]}, {"cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": ["data.dropna(inplace=True)"]}, {"cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data['position'].plot(ylim=[-1.1, 1.1],\n", " title='Market Positioning',\n", " figsize=(10, 6));\n", "# plt.savefig('../../images/ch04/sma_plot_2.png')"]}, {"cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [], "source": ["data['returns'] = np.log(data['price'] / data['price'].shift(1))"]}, {"cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [{"data": {"image/png": "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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data['returns'].hist(bins=35, figsize=(10, 6));\n", "# plt.savefig('../../images/ch04/sma_plot_3.png')"]}, {"cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [], "source": ["data['strategy'] = data['position'].shift(1) * data['returns']"]}, {"cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [{"data": {"text/plain": ["returns -0.176731\n", "strategy 0.253121\n", "dtype: float64"]}, "execution_count": 53, "metadata": {}, "output_type": "execute_result"}], "source": ["data[['returns', 'strategy']].sum()"]}, {"cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [{"data": {"text/plain": ["returns 0.838006\n", "strategy 1.288039\n", "dtype: float64"]}, "execution_count": 54, "metadata": {}, "output_type": "execute_result"}], "source": ["data[['returns', 'strategy']].sum().apply(np.exp)"]}, {"cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[['returns', 'strategy']].dropna().cumsum(\n", " ).apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch04/sma_plot_4.png')"]}, {"cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [{"data": {"text/plain": ["returns -0.019671\n", "strategy 0.028174\n", "dtype: float64"]}, "execution_count": 56, "metadata": {}, "output_type": "execute_result"}], "source": ["data[['returns', 'strategy']].mean() * 252"]}, {"cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [{"data": {"text/plain": ["returns 0.085414\n", "strategy 0.085405\n", "dtype: float64"]}, "execution_count": 57, "metadata": {}, "output_type": "execute_result"}], "source": ["data[['returns', 'strategy']].std() * 252 ** 0.5"]}, {"cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [], "source": ["data['cumret'] = data['strategy'].cumsum().apply(np.exp)"]}, {"cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [], "source": ["data['cummax'] = data['cumret'].cummax()"]}, {"cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[['cumret', 'cummax']].dropna().plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch04/sma_plot_5.png')"]}, {"cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [], "source": ["drawdown = data['cummax'] - data['cumret']"]}, {"cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.17779367070195917"]}, "execution_count": 62, "metadata": {}, "output_type": "execute_result"}], "source": ["drawdown.max()"]}, {"cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": ["temp = drawdown[drawdown == 0]"]}, {"cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [], "source": ["periods = (temp.index[1:].to_pydatetime() -\n", " temp.index[:-1].to_pydatetime())"]}, {"cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([datetime.timedelta(days=1), datetime.timedelta(days=1),\n", " datetime.timedelta(days=10)], dtype=object)"]}, "execution_count": 65, "metadata": {}, "output_type": "execute_result"}], "source": ["periods[12:15]"]}, {"cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [{"data": {"text/plain": ["datetime.timedelta(days=596)"]}, "execution_count": 66, "metadata": {}, "output_type": "execute_result"}], "source": ["periods.max()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Generalizing the Approach"]}, {"cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": ["import SMAVectorBacktester as SMA"]}, {"cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [], "source": ["smabt = SMA.SMAVectorBacktester('EUR=', 42, 252,\n", " '2010-1-1', '2019-12-31') "]}, {"cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [{"data": {"text/plain": ["(1.24, 0.36)"]}, "execution_count": 69, "metadata": {}, "output_type": "execute_result"}], "source": ["smabt.run_strategy()"]}, {"cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["CPU times: user 3.92 s, sys: 14.8 ms, total: 3.94 s\n", "Wall time: 3.94 s\n"]}, {"data": {"text/plain": ["(array([ 48., 238.]), 1.44)"]}, "execution_count": 70, "metadata": {}, "output_type": "execute_result"}], "source": ["%%time\n", "smabt.optimize_parameters((30, 50, 2),\n", " (200, 300, 2))"]}, {"cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["smabt.plot_results()\n", "# plt.savefig('../../images/ch04/sma_plot_6.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Strategies based on Momentum"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Getting into the Basics"]}, {"cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [], "source": ["data = pd.DataFrame(raw['XAU='])"]}, {"cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [], "source": ["data.rename(columns={'XAU=': 'price'}, inplace=True)"]}, {"cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [], "source": ["data['returns'] = np.log(data['price'] / data['price'].shift(1))"]}, {"cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [], "source": ["data['position'] = np.sign(data['returns'])"]}, {"cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [], "source": ["data['strategy'] = data['position'].shift(1) * data['returns']"]}, {"cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", 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"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[['returns', 'strategy']].dropna().cumsum(\n", " ).apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch04/mom_plot_1.png')"]}, {"cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [], "source": ["data['position'] = np.sign(data['returns'].rolling(3).mean())"]}, {"cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [], "source": ["data['strategy'] = data['position'].shift(1) * data['returns']"]}, {"cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[['returns', 'strategy']].dropna().cumsum(\n", " ).apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch04/mom_plot_2.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["#### Intraday Data from Eikon"]}, {"cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [], "source": ["fn = '../data/AAPL_1min_05052020.csv'\n", "# fn = '../data/SPX_1min_05052020.csv'"]}, {"cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [], "source": ["data = pd.read_csv(fn, index_col=0, parse_dates=True)"]}, {"cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "DatetimeIndex: 241 entries, 2020-05-05 16:00:00 to 2020-05-05 20:00:00\n", "Data columns (total 6 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 HIGH 241 non-null float64\n", " 1 LOW 241 non-null float64\n", " 2 OPEN 241 non-null float64\n", " 3 CLOSE 241 non-null float64\n", " 4 COUNT 241 non-null float64\n", " 5 VOLUME 241 non-null float64\n", "dtypes: float64(6)\n", "memory usage: 13.2 KB\n"]}], "source": ["data.info()"]}, {"cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [], "source": ["data['returns'] = np.log(data['CLOSE'] /\n", " data['CLOSE'].shift(1))"]}, {"cell_type": "code", "execution_count": 85, "metadata": {}, "outputs": [], "source": ["to_plot = ['returns']"]}, {"cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [], "source": ["for m in [1, 3, 5, 7, 9]:\n", " data['position_%d' % m] = np.sign(data['returns'].rolling(m).mean())\n", " data['strategy_%d' % m] = (data['position_%d' % m].shift(1) *\n", " data['returns'])\n", " to_plot.append('strategy_%d' % m) "]}, {"cell_type": "code", "execution_count": 87, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[to_plot].dropna().cumsum().apply(np.exp).plot(\n", " title='AAPL intraday 05. May 2020',\n", " figsize=(10, 6), style=['-', '--', '--', '--', '--', '--']);\n", "# plt.savefig('../../images/ch04/mom_plot_4.png')\n", "# plt.savefig('../../images/ch04/mom_plot_5.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Generalizing the Approach"]}, {"cell_type": "code", "execution_count": 88, "metadata": {}, "outputs": [], "source": ["import MomVectorBacktester as Mom"]}, {"cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [], "source": ["mombt = Mom.MomVectorBacktester('XAU=', '2010-1-1',\n", " '2019-12-31', 10000, 0.0)"]}, {"cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [{"data": {"text/plain": ["(21202.37, 10139.12)"]}, "execution_count": 90, "metadata": {}, "output_type": "execute_result"}], "source": ["mombt.run_strategy(momentum=3)"]}, {"cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["mombt.plot_results()\n", "# plt.savefig('../../images/ch04/mom_plot_6.png')"]}, {"cell_type": "code", "execution_count": 92, "metadata": {}, "outputs": [], "source": ["mombt = Mom.MomVectorBacktester('XAU=', '2010-1-1',\n", " '2019-12-31', 10000, 0.001)"]}, {"cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [{"data": {"text/plain": ["(12196.06, 1132.8)"]}, "execution_count": 93, "metadata": {}, "output_type": "execute_result"}], "source": ["mombt.run_strategy(momentum=3)"]}, {"cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [{"data": {"image/png": 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s3Pgv3HzzrzB06HDRc9PS0qFUKqFUKtGzZwSqqiqxcePriImJxaVLl9Cv3wDJex45chinTp2ETqdFeHgYAODSpSKkp6cDAHr0SOWOT01NQ3JyDxw9mo1Tp07gzjvv9sizkxgj/BIpMaYzUGSMIAgiGMnK6oft2z/n1nfu3I6YmBg8//xKtLe344EHFuCmm2ZBoVCAYRhotRpUVlZApVLbXeu555bh3Xc/RnJyMtraWrntcrm5VL6pqRFtbe3IyuqHqVNnICurL3Q6Hfbv3wsA6NUrE8XFxRgyZCjKyq4Krj1//t2W1GZfxMXFeeTZSYwRfolRomasnWZTEgRBBCXjxk3ApUv5eOutDVCr1YiJicEvv5xBQcEFyGQyTJ06HdHRMejdOxPV1VV44411mDx5Cs6cyUFlZQV27tyOOXNuAwDcfvs8rF27GsOGDcfZs6dRXHwZEydeh0GDBmPPnt2orKzAnXfeheXL/4pPPvkAKSk9UFVViZtu+hUA4Omn/4JNm97CoEGDoVKpIJPJuHGOHTser7/+Gh577HGPPbuMkZq25ud4u6t7MHeOF8PfnremoR3PvHVIdN9/ls/o9PX97Xm9DT1vcEPPG9xcS8/rL8964UIeMjJ6IyQkBKdOncC33+7C8uV/hU6ng1qtxquvvow//3m5W9dMTIyS3EeRMcIvkUpTEgRBEIS3uXixCF9++Tl69sxASUkxHnrodwCAVateQLduiZg580aP3o/EGOGXGEiMEQRBED7illtm45ZbZtttf/75lV65H5m+En6JVM0YQRAEQQQbTiNj1dXVWL9+PfLy8rBt2zYAgE6nw5YtWxAWFobCwkLExcXhiSeeAABs3rwZLS0taGpqwuTJkzFz5kwAQG5uLj788EOkpaWhtrYWy5Ytg1KphFarxerVq5GUlITLly9j8eLF6N27txcfmQgETIFZykgQBEEQbuNUjB0/fhwzZ85Ebm4ut23Tpk0YN24cxo4dCwDIy8sDAOTk5CA7OxubNm2CXq/H7NmzMXbsWERFReHpp5/Gli1bkJiYiJdffhlfffUV5s+fj61btyIlJQW/+93vkJ+fj2effRYfffSRlx6XCBSMEqavgLlVEn9mC0EQBEEEMk7TlLfccgsiIiIE23bu3InS0lK8++67WL9+PRITEwEAe/fuxYgRIwAAKpUKmZmZOHr0KEpKSqDRaLjjRo0ahZ9++gkAsG/fPowcORIA0L9/f+Tl5aGlpcVzT0gEJLYF/AMzrF4udU3arh4OQRAEQXiNDhXwX716FTKZDA8++CB++eUXLF26FO+//z7q6uqQmZnJHRcZGYm6ujrU1tYKBF1kZCRqa2sBQHJfZGSkwzHExYVDqVR0ZPgu42gaajDiT89b3qgRrA/u0w25V+oBADsPF+PP94/u9D386Xm7Anre4IaeN7i5lp73WnpWlg6JscjISAwbNgwAMHr0aBw7dgxGoxHx8fFobbU63ba0tCA+Ph4JCQl22xMSEgDA4T5H1Ne3dWToLuMvXiddhb89b21dq2C9sckqzn46WYrf3NyvU9f3t+f1NvS8wQ09b3BzLT1vMD+rI5HZodmUEydORElJCQBzlKxnz55QKBSYPn06Tp06BQAwGAwoKirC2LFjkZ6ejtDQUFRXVwMATpw4galTpwIApk2bhpMnTwIA8vPzMWDAAKdRMSL4sa0ZM9DsSoIgCCJIcRoZO3LkCLZv347q6mps3LgRDz/8MJ555hm8/vrryMvLQ1FREdasWQMAGD58OMaPH4+1a9eisbERy5cvR3R0NABgzZo1WLduHXr06AGj0Yi5c+cCABYuXIjVq1dj48aNKC4uxsqV3vHwIAIHk4lBRZ0w8qk3CMWYVBF/QWkD1EoFMpKvvTA3QRAEEZhQOyQJgjlUKoY/Pe+7u3OxP6dcsG3CoCQcPl/Jrb/952lQKe0Duw+//CMA5y2T/Ol5uwJ63uCGnje4uZaeN5if1eNpSoLwJrZCDLCPjDlLWza36Tw6Jl/T1KrDniPFMFFnAoIgiKCDxBgREMRGhqB/eiy3rhcRY3yj2JXvH+/U/RpbtPj4fwVo8hNR98aXp/HJj4X44USpr4dCEARBeBgSY4TfIRepBZs7JRN/nDeMWxczhdXpjdxyVX17p8aw9dt8fH+sBJ/vLezUdTxFSZXZe6/WxvKDIAiCCHxIjBF+h1zkVRkeqkRoiNVXTiwyptULt3VUuFQ1tONUYQ0AoLXd0KFreJKmVh10lmfT6Hw/HoIgCMKzkBgj/A65XLzVET9ixojUTml5kTEAaNd2TLgcOG2tWVOKTBLoav753jFu+WpNq4MjCYIgiECkQ6avBOFNxNKULCP7dsPJghrRRuI6GzEmFj1zhRCVVYApJYRhV7Dr0GVs++miYFt5jXfNjgmCIIiux/c/+wnCBkdiLDYyBABEZxXaRsZsZ2C6iorXZksqStcV2AoxAGjTGlBeS9ExgiCIYILEGOF3OBJA7D4xh4fmNr1gvaORMb3B6PwgH/LW9nO+HgJBEAThQUiMEX6Ho2AUGzUTi4y9/sVpwbo7kbHGFi3yLI3I+ef1SY1x+Rpdhe9idQRBEIQ3IDFG+B0yh5Ex879iNWO2iNlfSLFi02G88vFJ1DdrhSLOjxpULJo9EAAwuHe8j0dCEARBeBISY4TfoXAkxhxExmxxp9NXu9acmtToDIJZmL6UYgq5DH1So7n1tMRIAIBR5NlNDIPD5yrI+oIgCCIAITFG+B1iYoPFWjNmfwwr4vqmxTi9jhQKhRxtfDHmIzXGMAyMJgYK3mSGsFDz5Oc9R0vsOgOcLqzFv785j5c/ONGl4yQIgiA6D4kxwu9o4RXiD+4dj6fvGcmtO4qMDc/qBgAY1ifBfAzDIPdKPeqaXDd//TmnDG0aqxhzJR3qDdjbyuUyLL9vFB6bOwQx4Wpu/5c/FQmOb7dExIotTv0EQRBE4EA+Y4Tf0SslCkVXm3Dd0BQ8bKmTYuEiYzZi7PO9hThxoRoAoFaZrSnqmjTY9M15AMC//nQdonhiRopdh66gd4o1NeirPCUb1VMo5OjH68nJ0tRqM3OUV+em1RkRolbYnkIQBEH4KRQZI/yOaItoumtmlt0+tpzMNjC2O7uYWw6xiDG+1cXS1w9I3q+6QdjHUpim9I0aY8WmVP2cbQpWwxtzS7ve9nCCIAjCjyExRvgdrNBQijSpZCNjjurBVJYWRnyfMUeSatUHxwXrLbx6rA6UnXmEL/ebDV+lDHBtN2t4hrcd9VcjCIIgfAOJMcLvMFjEhEJhL0QcFfCzsNEkvd41UdLYIiyGb9X4fkbi98dKAACNrVrBdtbWIjzEXGHQ0q7H2Uu1yD5fyR1j6GDnAYIgCMI3kBgj/A6DUTpFJ2MtTx1ErNhoks4DTvq+SlOylNcKe1E+NGsAAODw+Upo9Ub8Z1cu1n6aIzjOYCIxRhAEEUiQGCP8DqPJBIVcBplIio7VZ45EEhs9c9WBX6xAnsVXsylZBvUSGrwqlda37JmiWuQV19udU93g+uxRgiAIwveQGCP8DoOREU1RAuAEmqNaLp2lfupkQY1L9zP6cSRpwfQ+gnWVwvqWrW3ScDNH+fzf12e9Pi6CIAjCc5AYI/wOo9EkWrwPgGvM6CgyVlLtnteWTqS2bMrwFMl9XYFMBmSlxaB7XLhgu1pl/X/59MdCNLXqbE8lCIIgAgwSY4Tf4SgyJjW7kM9NY9LttiVEh0ge36YxICE6BEvnD0OfHtFYeHN/jMhKBAB888tlNLRoJc/1BiaGAcMASpGaOYVcjhtFng+wtksCrJMgCIIgCP+HxBjhd+gNJqiV4i9NGeczxohu7x4bhqgIe3PX2iZpQdWmNSAsRIVhfbrh2YVjMG1kKrQ8q4gnNxzs0lQm6zEml/AYS4oPE91+8zirSFu8Zh8On6/w/OAIgiAIj0NijPA79AYjVEpxB3m2Zsw2S6lWKhAeosTfHhwLuUzGeY3xaZRI6ekNRoSohMfbii9HYs7TGJ2IMb5QBIBxA7tj+X2jMGlIMqaO6MFt37TjvPcGSRAEQXgMEmOE36FzITJmWzNmNDFIig9HuKWZdohIYbutiGExmQCZjfBh7TVYquqFFhPehHPflzJ8hXC70tIySSaTCQr8R/VL9N4gCYIgCI9BYozwO/QGk2hkC7DWjNlGxkwmYZ0ZP6rUp4e516ROSowxjF0tmq3Df3W9sGWSN3EWGUtJEBb1S7VM8rUtB0F0JVdbyrGv9KCvh0EQHYLEGOFXGE0mGE2MpBhjZQdfaDAMAxPDCCJJ/FmGsZHm4n2xmZHsdWz1jNGmAF4qxekN2D6TYRaXfVuGZ3XDY3OHcOsKXjSsmdeX8mRBDQqvNnpplAThX6w6sg6fX9iOqy3lvh4KQbgNiTHCr2CNWsX8swDwrC2smzhBJREhYsWYXsSRX6ohd0ykcPalo16YnmbX4SsAgNpGafPW0f27cylbqXQmABSUNgjWDUYTzl2u83lnAYLwFs0696xtCMIfIDFG+BU6ixjj1z7xsaYprWLC6KB9EgDERJpnV2rFImMWkWVbMza6fyIG9LQ68xtNDHYfvuL1GYoGowk/nSoDAEwfler4YMt/AT89O39aH/RPj8WYAd0B2Ddbf2v7Obz2ySkcz6/23KAJwo/Qm/TODyIIP0M8D0IQPoJtcq1SOSng521zVmMVqjZH2cRqxqxpSuG5cpkME4ckI6+4gRvX5/uKAAATBiW78CQdQ6Mzj3FUv0SMG5jk8Fj2/4AvQuOjQ7HsvlE4VVCDY3lVMJoY/HC8FCXVrZg+ogdOXDCLsKqGrquBI4iuRGckI2Qi8CAxRvgVbGRMejalfWSMFVRSkTE25SnWOJx1sBAzk+XPqGzVdM2vbaNE2tQRCpEootISLTMYTfhsbyEAIDzEmvo1dWHalSC6Ep3J4OshEITbkBgj/Ao2eqVSSPmMmf9ltdiHey5AozN/+EqLMbnl2g4K+EXONfAajTe3WcVYZX0bkmzaFHkKqRo2R2QkRdptY8/n17rxr1nT2I6q+jaEhSgRFW5vkksQgYreSGlKIvCgmjHCr9AbHacp+TVjx/Or8cOJUhw8a67j4guqFxeNQ3x0CB69bTBClNJpyrwr9QDApe/48FsK8cXYX94+jPe+y0dRmednKrKzOKVSrnzYFk/9e8bZ7WOjZfxn2HXoCre8P6ccy98+jKfeJCsAIrjQmShNSQQeFBkj/Aq93rU0pYkB3vzqjGAfP/KTmhiJV38/GQBw7lIdAEBrsI+M7c6+YreNJTHW2naouV34Ab/v5FXsO3kV/1k+Q/J8dzExDPJLzDVqroixZxeOQUubHpFhKrt9bFF/S7vjKIGtuS1BBDoUGSMCEYqMEX4FN5vSic+YmDWDlICxpintI2NVDsxcR/dPxAM39wcgjIx5i1MFNXhnVy4A8SbhtsRGhiCtu32KErDORq1xoVCfbC6IYEAus7zPaTYlEYCQGCP8Cj0nxlyrGeMjWTNmuZZYO6RWjXSxr0wmw1iLRYReJKoGmAXeNwcveaRdUg3PV6y0urVT1+oWY47qnbtc7/RYZ9EzgggE1HJz7SNFxohAhMQY4VecLqoB4DxNebXG3thRIRc/h51ZaLRJyfEjQotmDxQ911kh/Xvf5eOrny/h658vOTzOJXjjaWrrXN1LWIiEaa4I9c1d1wSdILyFWmFO11NkjAhESIwRfsXPp82tTKSiNWxkbH+OfcsTqTQlW8xu66JfVmuNZk0emiJ6rlLhWIwVV5pFoSfaJekkom8dQSbhyv/4ncO4ZVbwNrSQGCMCH5XcIsYoMkYEICTGCL9Eqsm1lMgApKNYcs7mQSh2xNoj2V9T+BaxjTix12TNWjsDX4wN79Ot09cTo1+6tatAn9QYABQZI4IDlSUypqfZlEQAQmKM8EukTEnD1NLpN4VEFIvt3Wh7zV2/mGdS3nZdb8lr2kbbQtXCCcjlluiaJ0xhWXE4dUQP/GpCz05fj2VghtX6IixEib/+ZgyG9I7H1BE9AAA7Dl722L0IwleoLZExLTnwEwEIiTHCL4kItbdrAMxiQgq2aN0WVqTx05Qllc04bvEWS4wNdXlcIRINzKUK/N2BjYzNHJ1m16i8M/HfzP8AACAASURBVPxx3lDBeu+UaDx51whkUWSMCCKUcvN7M7fuAs0QJgIO8hkj/JJpI3uIbg93IMaS48TFmFzEjb6VV5OW3j3K5XFJRezqm7UwMYxoWyVXceax5i63TuoFvdGEULUS4wcnI9wmqhgfbRah7ohRgvBX+Pqrqr0GSeGJvhsMQbgJiTHCr4iNVEOtVEhaW4SHSr9kk+LFWxSxnl18IcXvU5mS4FprI4Vchp5JkZJNtg+cLseU4eIi0hXYMUk9u7vMnZLJLT/38HhUVzfbHdOjWwQaqYCfCAJMsEanZej4jyKC8AUkxgi/wsQ4dp8PdRAZiwoXT22KRcb4BfdKkUbbfNb+YTKUCjkiw1R479s8yeNOFdR0SoyxqU61RCsobxAZqkR5TStMJsYl13+C8Ff4qUkSY0SgQTVjhF/hTBTYpgFH9rXOOlRIiCqxptlaixi73UHxPktsZAjXcqjZkt6Mjw7BK0smYnT/RG6GpdQMUFdha8Y8laZ0hYgwFRgAbVpp81uCCAQYWN9/Rqbzs5sJoishMUb4FUaTe3VXsVHWQnep8+QiaUpWjMVFu1coX1pl9hXrlRyNbjFheGzuUKxZYu6BKSbGjCYTfjlb7pKXl97SIcBZpM6TsG2n+A3FCSIQMZqsAozEGBFoUJqS8BvOXqxFu9aAqgbXWwupXBAuchFrC7Y+S+1mfRab3uSnREPUFlNZnsP/+9/lIykuDCVVLTh4tgI3j0vHXTP6Cq7FMAwYXlpWZzBBpZQ79FLzNKyPmm13AoIINCraqrhlEmNEoEFijPAbPthzAQCg0zuO0kSFq7jG3ckuFN/LZOYKErampKFFi//bdhqA+/VZYo3MFXI5ZDJAz4su7T15FYDVJLaW13eSZfPOXBSUNuBvD46FXCaD3mDq0hQlYO0wYDBRZIwIXBq0jTAx1tcwf5kgAgFKUxJ+g9QsRVvSEiO55SnDXCuYl8lkYANjB89YWympJXzDpEhPjAAAJMUJRaBSIYdRJNXXrpX+hX7oXAVqGjV4fssR/GH9flytaUWoA1Nbb8CmRA0UGSMCmHpNg2D9XG2+j0ZCEB2DxBjhF2j1VtEycXCyw2PbNOZi82F9EiCXyzB7YgZmjXfsWC+XA4VXG/HR/y4IBFiIm2nKJbcPwT0z+3Lu9SxKhYwTNGKGk+06I47kVuKzvYV2++uarPVkg3snuDWezsIa4tY1aXC5oonb/s3BS1zTdoLwdzQGYU3mfy9976OREETHIDFG+AUNPBf4RbMHOjy2TWtOUbIGsPOm9sH86VkOz2Hrxv53rBQ6nvCTufkOiIkMwY1j0+2K7JUKOVcELxZj0ugMeGv7OXybXYxWjfTMxTEDutaokn2OdZ/l4B/vHoNWZ8S5y3X46udLWP/56S4dC0EAwOWmYhypOOHWOa36VgBAelQqAGBK6kSPj4sgvAnVjBF+QZ1FjLHRLkewFhURYeK+YmLwi+L5kageCRHuDFMSc5rSPC4xl36+r1ljq86u4ThLnAfbILmC7QQIjc6AnAJrRMxoMtk1SycIb7L+xFvQmwzIjMlATXsdMmMyoFaoHZ7TYjBP+hnWbRBKmq/CSDVjRIBBn7KEzzEYTXh3dy4AYATPN0yK398+FAN6xuLWSb1cvgdfT7DF9cvvG+Ww16U7KOQyrghezG5Mw6sda2zRSk5SsG1E7m1s/7/ZGZ0si9fs69LxEITeZI4c7ys5iDdObcJHeducntOqN4uxbmHmNH+7wbX6U4LwF0iMET5n+4FLqG4wzzaMj3IeGcrsEY1n7h2F6AjHv5b5iDlyO+pz6S7mNKV0zRh/tmJTm04w81IwJgftnrxB75RodIux9qbU6oyCKCLDkAcZ4RvO1pp/oOVUn3V6LCvGEi1irE1PYowILEiMET7ncoW1Z2Ksl9J0Yg7znhQ+/NmUYpGxxhYdt6w3mGAwiAscT0Xq3IEfCdPojXazWr/6+WJXD4nwMnqjHierzvi1BUR1ey0AuJRy1BjMP+ai1VFQypVoN9hbyRCEP0M1Y4TPqeZ9+bsT7eosnhQ+pdVmZ/5ThTVI51lviGEwMpxfGcvjdw7zWQSKX6PX0qbHsbwqwezQksoWn4yL8B6fF2zHwbIjmJs1Gzf0nOqVexypOIF+cX0QGxLTqeu4YuCqN5kn9agUKoQrwyhNSQQcTr+NqqursX79euTl5WHbNmHufuPGjdi6dSuys7O5bZs3b0ZLSwuampowefJkzJw5EwCQm5uLDz/8EGlpaaitrcWyZcugVCqh1WqxevVqJCUl4fLly1i8eDF693beL5AIHqrqrR+cEV2YpgvxgqfX61/Yz0BMS4xAaXUrt559roJrq8QyPMt5rZy34Kdwt35nboRuMDJ47bHJeOrNg13ufUZ4n6LGKwCAi5Z/PU1xcym2nv8EarkK66atdPm8/LrCDt3PYGmFpJQpEaYM5dKWBBEoOE1THj9+HDNnzrSrg8nOzkZTU5NgW05ODrKzs7F06VL85S9/werVq9HU1ASGYfD000/j8ccfx6OPPgqFQoGvvvoKALB161akpKTgkUcewYMPPohnn33Wg49HBBoqN32/3CXB0otSIZe51QOzM9g2ML9Q2shNIgDMM0h9SatGzy3z06khFj+2qzWtKK5stjuPCFzUcvNMZJ1R5+TIjmG01EjqTHonRwo5VH6sQ/djI2NKuRJKuZLaIREBh1MxdssttyAiQjj9v6amBrt27cL9998v2L53716MGDECAKBSqZCZmYmjR4+ipKQEGo0GiYlmD6VRo0bhp59+AgDs27cPI0eOBAD0798feXl5aGmhtMi1BOt1tfjWQV6/F2v4Gurh2qw5IjM7eyZFYv2frnOYfvz15F5YOn+4R8fiLvXN9k3MF986iKslK69tw/Nbjnb1sAgvouLEmHtiyVX4Ymj3pf9h58XvcN6JK/6p6rM4WumevxiLwTIDUylXQClTcpEygggU3P5GMplMWLt2LZYtW4bmZuGv5bq6OmRmZnLrkZGRqKurQ21trUDQRUZGorbWXJwptS8y0nHdTVxcOJRejqIkJkZ59fr+hi+eV28wwWA0YUTfRNw6ra/zEzpJWKj5SyhUrfDo8yZ1s3+9pidHo09GAuqapIuJo6NDu+z/3Z37DO2fhJRk4fGB9n4ItPF2FreeV2H+gRAWovbK/1O50eoBuPPSHm75vTvWIVQVKnYKdmT/V3R7t/B40THyt8kUgEKuQFL3GISGqGFoMQTd3z/YnscR19Kzsrgtxs6dOwelUolPP/0UjY2N0Gq1+Pe//42bbroJ8fHxaG211sa0tLQgPj4eCQkJdtsTEsypGUf7HFFf792agMTEKFRXXzupGV89b0u7+Ze5XIauub8l3R6qVnr0fka9/WxNvc6A6upmh/0pa+vbuuS53f37hsmBmhphhDqQ3g/0/nVMU7v5b1vb2uCV/6faevFrLvzyCfxz0grEhcba7UuLSEVlaw16RqWiuNmaxk8OSxKMsby1Em+f2YLqtjr8dsgDGNl9KNq1Gqhk5vc0YzDby1RWNULubosNP+Vaej0H87M6Epluv1KHDh2Kf/zjH1i8eDHuuecehISEYPHixejVqxemT5+OU6dOAQAMBgOKioowduxYpKenIzQ0FNXV1QCAEydOYOpU8wyeadOm4eTJkwCA/Px8DBgwwGlUjAgeNBbLibAuKhJn3fFDJRzwO0pEqH03AFdq0qaNSPXoODzBi78d77QLAhG4bD7zPmcbUd5aiWad58tCWONWMbIrjotuVynM76HfDLobMepobrut/ca2gm9Q3VYHANh89n3z/RgjlHJzbEEhN7+3vVUPRxDewKkYO3LkCLZv347q6mps3LgRGo055XLlyhV8+OGH0Gq12LhxI9ra2jB8+HCMHz8ea9euxYsvvojly5cjOjoaMpkMa9aswbp167BhwwYYjUbMnTsXALBw4UKUlZVh48aN2LJlC1audH3mDRH4tFvaBHWV8zzbSsnT94sMs7+eMy329wfHIjE2zKPj6Azzp/XB728fgtRu4i2ixNo8EYHHyeozgvUmneejEHoHhftlLRWi29m6rxBFCJ4e8wc8MHABAHsxxta7sZyvzUdNey0nxnLrLgAAdlz8rmODJwgf4PQbady4cRg3bpzd9oyMDCxbtgzLli0TbP/tb38rep2BAwdi1apVdttDQ0Px97//3dXxEn6O3mDC8QtVGDugu0s9DTU68wewpyNVtrz8yARU1LVzBqaeNlcVi4zJHKixxbcOQkayf9VFDMlMQHp36ai0wWiCWk42F4HMhlOb7baJdafoLI4K6KXEH2dPIVciSh2Jccmj8H7uZ3YzI8OVwh8wb+a8w53HJ6f6LBb0u83tsROELwiOhDrhN2z7qQj/3nEeX+2/5NLxbD2Vt72suseFY1ifBOj05vupVZ596Ys1Lb9Q0gAAuO06q29emsUQdmCveI/e3xM483jT6mmGWqDDRo0Aa+sgAyOdUuwoBgeRMSnXf/6MSACQy+SQQWZ3fJRa/AcDK8a6hZrfW+lRPdwbNEH4EBJjhEcpsZiZskLEGWxkrKvaALFpSqXCw2JMRMjUNJpT+nwxdsv4dLyzbDpiurDTgDOW3TsS86ZmIj5afJYby5Hcqi4aEdEVhCnNf+8Pcj/3eFskVlglRyTZ7ZPyHmsztEEuk0Mtt7435DK5SJpS/LOC3X7PgHkAgNRIEmNE4EBijPAobISrXefar22NrmsiYyxGS4sfhYcL1Fn/Mj6ThiTbbTOZHKcvfUH/nnGYPbGX0+OS4vynvo1wH6NN6jDUku672lKO0pYyj96LLeCf3ftGu30aib6RjdomRKujuAJ8wCzGbNOUBglDV6XMLMZClWZjZ72XPNQIwhtQb0rCo7CF8RoHdg58GlvMhqORYV0TKTJZrC28OVvwd7cOQmVdm6gRrKdFoLfpFhPKRfj8TUQS7tGsF86aZCNjgNUx31OwYixSFYH7BtyJ5IgkvHb8TQCQbOKtM+oRrhIK/lBliN3xBomZmkbGOgEAADRGezNjwv85djUHSl0YUiNTfD2ULoUiY4RHCbMU4mscRMYq6tpw6GwFGIZBRZ3ZLy45IbxLxse2+HFVLHaE7nFhuP36TEEq9LmFYzB5aDLGDOjutft6g+cfGosJg8ypJtuWaERg8XWh0FQ1Wm2dQNLmwcbah8uPYffl/wEw13FN6jEOmTEZ3H6pyJjeZLArwo9QRQj6TO4vPYQfS34GAPSNzRQc22I5LlJlng1cr23Ae+c/RW17fSefiOgq9CYDXjnwFlYdWYdGbTMqWqsEdY7BDEXGCI/CzqC0NTo1mRj8492jCA9VorK+HfXNWqQmRqC8tg1KhRzdnNQreYobx6Th/T0XMHmY9+pJxPzFMntEI7OH99s9eZrwUBVSE81fbiTFApsWvdlcO0IZjlZDmyBt2e5BMfZ+7mfcMr++a8W4J/DGqU1o1rWAYRi7SKvBpLezrYhQhqOytQomxgS5TI4vC7/h9vWNzURBw0VuvdXyfOxsS7b9UnbFcbw54xUPPR3hTYqbSrnlD/M+x7naPADA69NeEqSvgxESY4RHYfswmmyiKL99Za/dsRqdEdUN7UiMDe0yk9Hpo9IwPKsb+vdJ9JrLsy7IZh2y4pIiY4GN0VIIv+q65wAAv5QdBcrN+9r0nhNjfPhiLDUyBT0ikpGvK4SJMUEhs365mhgTDIzRrjg/UhUOBgx2FH2LWzNvFpjJhiqFP+C0FpPXYP/S9iVHKk6gUduEG3pO9UrZwnu5n3LLrBADzH/bcHlw16xSmpLwKHqDfe1JWU2ryJHmY9s0BkSFd+3MQmezBjtKdLj5V31XzQztKtgPXfJ8DWxMlsJ3hUwBpVyJ61MnYFLKWACeTVPysU07sgLMrijfIrJsI2PlbZUAgO+L9+HJ/X8V7GML9VlGJA7t/IAJSZp1Ldh6/hN8XfRflLaUe+UecgnPu+r2GrToW7Hs5xewt+SAV+7ta0iMER5Fb7SKMTZK9saXZ0SPbWrVgYFzf6tA4e8PjcNjc4egZ5J/mbl2FvYHMEXGAhsTw5i9uyx/UJlMhkk9zIbe31z8FvUa1+xopKhorUJhg9BfkB/9AsD1ijTa2FXoOTEm/Cyoaqvhlm0L90N4FhhLRz6ChYPuEh3XtVYI7g0atc1YfuAf3Hqdxjt1eGJWKACw58o+5NcVoEXfii8Kdnjl3r6GxBjhUfiRMXa5TSM+xbyx1ZxWEDNMDUTiokIwun9gFei7AvtblbRYYMPWXfHhu9lvPvtBp67/YvarWHfi/wTbYkNiBOtsCtE2Msa2T7KNpN3Qc6rk/XpGp3HLfeP6IERhFWf85TTyG+s0V22sT6rbaySO7By1mjrR7QmhcZDLgjv9TGKM8Ch8MWYwmmAwmtDcpodcJsPcKcLZTw2srYVIKyHCf5BxNWM+HgjRKUyM0S4NpOaJlstNxR2+dnVbLbfMRqLenPGKXV0RKwZZI1d2EgGXplQIPwt+nXkLRkqkHxPDumFU92GYkjrRbl8YT2RKWWEQrqO1abr+VeEubrmqrQa7Lu6x87FzF4ZhUNtej/QYe/H8Q8l+OwEfbARHfojwG/QG6xvGYGRwusj8IW1iGKTEC+0rrJExehn6M5SmDA7MaUphdMG2RqsjMAyD5w+v5tYbtU2cvYQtCjZNaTKiuLkUq4++jnv7z0NmbC/R8SjkCoFgBIC7+t2OqKgwyGQyLBpyv+h9QhXWejLblCjhPjsu7rbbpjPqoFaosfns+7jaUo5QZShm9pzS4XvoTQZojBrEh8WipNHehJjvNycW5Q10gutpCJ/DrxnTG4yobbK+geKihQW3rOGrWJNtwn/gImM+HgfROcwzGIUf+baRqI7A9wEDzBYacTbpSRa2hszEmHCq6iwA4KP8bdAYzJ8FYq2OsmJ7C9anpE3CTVmOv/TVvOcyeqH35rUGv3aPpaTZLJgatU0AgMq2zrVLazOYX0cR6nD8ZtDddrV+DdpGblmq2XwgQ2KM8Cj8NOXqj06ivsn8ISuXyRAfJZzF2NASXDVjwYqcImMBz6XGKyhrrbBLG/LFT6gitEN/4/z6QrttsaGxosdykTHGiAiVNVJ+sfEyACAhLN7unKHdrP58S4Y95NKYlLwIm95IYqwzFNQXccujuw/nlpstgoiNWGmNOhwqO4oWnfjseWew9ioRqjCMSx6FP41cjFCF9TujQWMVY9nlxzt0D3+GxBjhUfhirL5Zi2+PFEOpkOONpdcjJlKN3inRSLOYiLLu+5FBMpsyWLFaW5AYC0TqNQ141dKKSAbxGi4A0Bg1dlEuV/jPuQ/ttsVLiDG2QF9vMgjSj18W7gQAJIUn2p3DF4wD4vu6NCZ+ZC6vvgA/FO936TzCHr6NxeCEAdwy226KreU6VnkKH+R9jjdOberQfVhRF6E2i/RIVQTWTHket/WZBQA4XHGMO3bHxW87dA9/hsQY4VHEfMbSu0cgLEQJuUyGv/5mDO6cliXYT5ExP4eLjPl2GIT7MAyD535Zxa3b9qcEgDXXv4DrLUXwlW3Vbt+jW6h9NCsuRFyMsUatGoNWtCBbXIxZPx9sZ1tKcWe/X+O6HuO59W+C8Mu7q9DyenyOSRqBOb1vAmAWY2LN2DvadJ5LU/IipnKZXBAd42MKslpAEmOEx6isa+NmSPJRKW2KhhXCX+dUM+bfcO2dSIwFHFJNufmEq8KQHmWewVbVATE2JmkEAGBe1hxum1TNWJjli7Xd0C46yzFGHW23jbXDiA+Nc3lM0eoo3DNgnvW6EuMhnMPW841IHAqFXIGe0ekAAK1Bi+r2WkenugVbBxYTKvRplBLgHRV9/grlhwiP8fEPBTAYGcREqLmZkgCgUgo1v0IhXKfZlP4NK50pTRl4VLW7Jq5YEcT2r3QHncUjrHdML25bpDpS9NhwldlyolXfJirGpFoZrbn+hU5NNhATeYRrfF+8DwAwJ9McEWNnqmqMWlR0smifT0Wr+VrJkcLoqO2kjnHJo3Ck4gQuN5agZ1QaggWKjBEe43RRLeKiQjColzBtobTpOxkTIZyqHqIKbjO/QId8xgKXN06a63fClWHoE9NbsgCe9eXqSFsk1j2fb7Rqa0fBEqU2Rz0+zt/mluN/uCpMdKalq8SGkBjrLGzqmW1DpTVqOxRJleJi4xXIZXL0jusp2M7/u983YD5GdR8GANCZhN5ngQ6JMcIjXK0216LUN2vR1CpMVeYUCUPZSTZ+Y95oOEt4DvIZC1zYIuvkiCQ8OXoJhnQbKHpcGFfL5TytaQtbN6RWqPDU6MdwS8YM9I7uKXpstCVipjcZcKAs2+17dZQwpXf60XYl52rz8L/in7r0nvz3PCvCQtjImEErWWOoN+qRW3cBH+V94ZIZrM6oQ0nzVaRHpSJEKRTy/DTlwPi+XA1haXMZmnX2NZCBCokxwiMUlZm9ZkJUCtEiflsevW2wt4dEeAgqGQtMGIZB31hz14tFQ+5zeCwbybJ1WncFNkKhkquRGZOBW/vcIvkDi42MscSoo/H8hGVu39NV2C/uYEixb8z5D74q3AWdSNG8t2CL9wfF9+e2sWnK7IrjnN1E9/BugvOadM3YcGozDpYdQZ6I9QmfZl0LSprLYGSMSBdpXRXOK+gPUYRw4uxo5UmsOPjPDjyVf0JijPAI1Q3m9Maf7hwGk83n3tgB9v0aM3tQ2iBQsKYpA/8L7VriQFk2ChouAnBeM8WmGLMr3PdvYvtKqhXO04hRNrVkGdHpSAxPwK9634hHhz3o9r2d8dz4pwAE18w79v+7K7jYeAUA0CMymdsWorSad19oMHuQze51o+C8Nl6EtcFBOtpoMmL5gX9g7YmNAIAIkc4N6VGp1nsr1FDzZtcG09+VxBjhEVjPsJSEcLtfoSOyutkdr6Y6sYBBRtYWAcnuS99zy85KAfj2EXync1dgTVVdaa0UYlNLxoqz2b1vFJi7egrWZPZU9VnsubzX49fvKgy8VN/Zmtwuuef+0l/wZs47AIABcVZ/N9vaPRlk3CQOFgNvvUHXJHmPvaUHBOti6WSVXIne0T0RpYqEQq4Q9B0NJkiMER6hXWv+QI4MU8FkCY0N6hWHp+8ZiQmDk+yOjw5X46m7RmD1o/ZNfgn/Qm4TGQuGlM+1QJgq3PlBFvjtg1gndFfRmXSQy+RcqyN3cNU3rKOwprYaowbbL+7GpcaON0P3JfXt1ujSe7mfeuy6v5QdxbGKk9y6xqBBcXMpGIYRCKUYBxMgGDBIiRB+xutNei71Xa9pgMFkwHvnP+U6LbDwG44DwigYnydGLcGq654DACSGJwj27by4R3JsgQSJMcIjaPVGKOQyKBVy7starVRgYEac5K/ywb3jkRgbnL9yggmrAz9wJLcSj63bj6Kr7kVPiK5H70b9F9+J3900mN6oh0qu7NBEHGUHBJw72DaT5ru4BxK1bfVeue6HeZ9jy/mPufVP8r/G6qOvI7viuKAfpW1E848jfidY7x2TgRXjnsCvepvTlTqjHjrL6+9Q+VG8mP0asiuO47XjGwXnDbWZUMJPh/JRyBWCv2X/OKtx+PHKU06fMxAgMUZ0mtc+PYWiq01c6tFkSePTJMnggHUmMZkYbPrmPLQ6I1a+fxyHz1f4dmCEQ1i3e6mZjVK4YhTLR2cyQC0Xt7IQ465+t3PLZa3efQ0pbXzLOto30dfUtNVxy+HKMLTp2/DYj89gW8E3dscaTUZsL9qNGieGrPx6K3b5aOUJAMD7uZ8JjrW1KukX14dbvrPvrwEAqZEpCLekEG37lUqNRc4T44lhCYi2meAhxUOD7+UmFTTomlyasenvkBgjOs25S+YPCjaNNWdSBgBgxqjgMeS7lpFb1JjRxMDIm53x7x3nfTUkwgkXG6/gqqWn4IOD73Hr3DM17v1ddUadW4as/BmVV3l9D71BqCJUENUxMoHZNLyGFxlrM7TjUlMJAODHkp/tjj1aeRJ7ruzFmmMbHF6Tb2OiFzHg5cPaWbDwo1RRvKJ7tp5MbFxi8I1/0yRSlGJEqSPx2IhFGJ44BDqjDseCIDpGYozwGBqd+dfJuIFJ2PTMNAzubd+zjgg8FBYxdrFcuhCX8C8uN1lroyJV4m74UuwrPSi5T28ycG1rrNv0LhXvsyh4X+SMlw1TZDIZEni9Mw0BGkFh05RsS6h9JQckj2X/R511U6jnTdTQGXWSxz81+jFBTaEt/G4Lzl4HtulOvgickDza4blisJHO93I/xXMHVwX07EoSY4RXUMjppRUssAX89c3uG4ISviGW14sxVBni4EgrM9OnOD3m8wtf4y8HXhSknXQmvcMva1sUvKL9Md1HuHxeR4kPtTYtF2vBFAiwYqxOY/73fF2+6HFnas7jA5sUoxg6ox6rjqzj1r+5+C1q2+vsjntw0D3IjMlweC1+Y2/bCKltuyKdUS9IKbKzLv824WlJQ2JHFDVe4pbrtQ0d8snzF+gbk+gU5D0V/LBpylA19RANFEyWL7yJKWNdPicpItHpMQfLjgAA9lzZB41Bg4uNVywF/K6LMf6X+9ys2S6f11H4TcKNTGBGxuo1jVDKFFxNlhgX6ovw1ul3BdukDGLbDG2C9YNlR1DeWglAGL3K5PUbtSXU0vQ9UiRNyfLU6N/jb+P/jEeHPYhR3YeBAYP3cj/F9qLdAICqthokhMYhKdz5a0+MJ0YtEay3d6Cdl79An65EpyirCcyCWMJ12MiYK50VCP/AaEnXOItq8GF7D7rCwbJsHKk4zqWZ1G6IsTBlKP4x8S/QGDWSjcE9Cd+WIVAjY42aZkSpoyCXyQX9Q0N5tVw/iLRKqmmvFZ2hKIP97Cq2aD8zphdy6y4AACJU0uLvrxOeQk17HeJ4kUe+KH9+wjIo5UokRXRHUkR35NeZi/rZ+q5wZRha9K127v3ukBXbG1GqSDTrzW2R3J18EGKoJgAAIABJREFU4k9QZIzoFK0a64fbGBGnfSLwYSNjBqP5C54myfo/rBhzx/trYHw/t+7Br/dxp4AfABLC4pAameLWOR0lhjdhIBBrxtoN7ahpq0N0SBT3w4jFwBi5OqmUCHvRdcVS6G+LowjhkARrutC2cJ9PbEgMsmJ7C7bxU+K2fmB1WqET/9dF/3V6D3cJVLENkBgjOkmbxex1xqhULL7V8w7ahO9hxRgbGbvteusHMKWp/ROT5cvW1mfLETKZDD2jUu1sDFgqWqskz41Qum4w29UIImMBOJty+YEXAQBhilDMsKnrM4hMqOBj63DPYjRZo9w39pwm2Dc5dTy37K53nCN3/HqNuFeaOyluMfiTQAI1DQ2QGCM6icYixtISI6FU0MspGFHYiDG1UoGRfc2pBX5klPAf2GiJO2IMMEfSxDybGIbBi9mvSp5n23PSn2BnIAIISD8qNtoToQrHlLSJmJIq7FrCmrPy66XYzgZKmXglEt/ig1/ndUPPqVDJlXhh4jL8bcLTbo81KTwRd/Wbi+VjH7fbd++A+aLnJITFiW53Ff4PQoqMEdcsbBuksBAqPwxWbGvG5HIZYqPMqYX6Zq3PxkVIY01TuvcRX9pSDiNjFMxKMzEmbD77gcPzov1YjKVGpuCOrDkAgFqJ6EwgkBBmtuiQ2fxNq9tZMWatl0qJSIJSppCMbLH+blNSJwkiU6xY7RaW0OGi+ilpE0XbGiVHiJex3JQxvUP3YeEb++oDUGyzkBgjXKaxVYeWdvPsnOqGdry7Ow8NLeYP7bAQavwdrHBpSkvNmEIuQ2wkiTF/ho2MuVsgz7ZC+qn0IGrb67Dz4nf4497lOFV9hjvmrn5z7c5TSaQ2/YWZPa3pvdzaCz4cScdhfbhsZwxWt5ltRtqNVjGmlqsRpgwTnV14qfEK/nPuIwBmIcOPahq8mOZTyZWY1/dWwba+sZkuu+5LMc/SAQAQNihnCZRSChJjhEsYjCY88cYB/OlfPyP3ch3e2HYa+3PK8M0vlwEAcVGhvh0g4TW4An6DVYzFWcRYQwuJMX+ErZ0RmzXnCmUtlfjboZex+/IPdvumpE3koiZscbxtIbc/syFns6+H4BapkSkIVYYgyRJZYptyD+1mrtGttni+teutYuymjGkIU4WKNn0vqL/ILSvlSoxLHoWxSaMAABNTxnjnISxMT7sO1/Ww1qQ9PvKRTl9zdNJw/KrXDQCAIxUnBPu2nv8Ea45tCAgzWMotES7RxqsNWvPJKUSFC4sue3Tz3wJeonOwvSnZyJhcLkOcJU3ZQJExv6RVb/aRCle5976ckDIGh8uPobDhouh+1tfpqdGPoUXfim6h8WjRtyEmpHPRDUIag8koMNW9oedUxIbEYEjCAKw4+E/Uasxmre1GDSJU4Xhp8l+hkCuw+/IPqGqrMfvAWc5nGAYHyg5z14pQhUMhV+DBwXdj4aAFbtcYuotMJsPA+H44UJaNQfH9O9RcXgzWD00GGY5UnEDv6Awkhidw4qxe09jp2jRvQ5ExwiVYWwOW5jZhOJgc94MX2wJ+lUKO2EhzWqqeImN+CTvDzt0U0Py+twEwu5mLwUbAIlThSApPhEKuCEghJmWG6o/ojDrBDFe5TI5xyaMQrgpHtDoKzboWmBgT6jX1iFFHc6npOIvZ7bO/rOTOLW+tFNTNxaqjBdftCkZ0H4olwx7Cw0Pu9dg1s+IyAQAnq89g6/lP8I/sNYL9zXrpGaf+An2DXmOYGAZ/3ngQn/xQ4NZ5eqN0mPeGMdQQPJhh05QsGp0BUeHmLwe2hpDwH74u/C8XEQhTulc+EKoMkTRw7Rfbp9Nj8yXLxv6JW37ip2cDopboaMVJ1GsbEBcaLbo/Sh2FBm0jChsuQWvUcSlMwJrGZKOkgLDIPzMmA8MSh3hp5I4Z0m2gQxsMd7F1/rdNS9ZpxH9c+BMkxq4xKmrbUNekxZ6jVjPADV+ewQubDzs4CzAYpT+44qleLKixNZpkACgU5m0mU+e+0K5Wt+B4fnWnrkFYeev0u/i+eB+3btuY2RVso2lquQorJz+LJcMf7uzwfIptn8RGnf83vn/3/McAgB7R9oaugLVm718n3zYfxzPSHZc8iqsZZBvHsxM0Zve+EU+O+r1bPUUDjf9e+p5b3nLuI+j9PBpKYuwa43KF/QfQiQvVOJZb6bAY2+CgFU5slH/PpCI6h8ImMmYyMZxAM5oYGIwmFFc2o6ymFSY3ow1/fecI3vzqDDS6wPUH8ifO1JwXrCvl7pcFp0X1EKxHqCIQGxITdF/cGkPgpNgHdxfvjjA9/TrBOt9SQiaT4ZZeMwEAP189jL0lB/DGqU0AzEarnqrX8ld28cSYiTGhvK3Sh6NxDomxIIdhGIHbclV9u91+lsLSRsnr5F6x9+eZNzUTi389COMHJomcQQQLMhsxplTIoVRYxdgnPxTg+S1H8dzmbGz/+VKH7vHyBycCIm3UldS212H3pR8Enl+O8NSMsahOWg34M/yon87F/9euQu/AsHRgYpbo9r5xwtRxbIgwnXm9xSD2TPV5fFGwg9vubvuqQOCp0b8X3d7HUtzfpPXvujESY0HOlt15+N0r+/B/X58FYP7y5HPwTAW3LFUX1q414LO95iavt11nncIeFa7GhEHJQf8L61rHNjI2aUgyN2HDaDTh0DnrL85j+dItcxxRXNUCnd7/p593JVvPf4qdl77DwauOSwhYWCf2zmJbZ3Z3f3tfsUClf5xV1LgqcruCY5WnsHTfClxsvCy6PynSNQNW29ZCrCFqq6FNsN2dxu6BQq/onqLbJ1jsOpr1rV05HLchMRbkHDhtdlo+mmf+kjTa1H6VVLVwy1L1P6zLPgDcOqkXt6xW0cvnWoBfMzZpSDLUKgXYTSYTI3jduNMSy/b1ZjCRGONT2nIVAFCvlY5Y86ls65gQtoXf32/Z2D9hSLeBDo4OLPgF7DqT/4ixz/K/BgDsLzULb4ZhwDAMFDIFekuIDDFsU8lSjeI72w/SH5HL5EgKt3f5Z01tW3Qtdvv8Cfo2vcaw/cJj/aIA+6gZi45XL8afWReiJNf9awH+3zwi1PwhLpPJoJDLYDQxgteNO5nGqgZhytxRXeK1iLtJ28pWz0yEmJk+lVtODEvwyDX9hUEJ/bllf4qMmSx/7aOVJ9Cib8Uf9i7D5wU7YGSMTuv+/jz6MW45VBEi2Gc7y5DbHoRpSsD84yGGl4q+LnUCIlVmMebqjxpfQaav1xj8L86iq42S+/hIFVfHR9MsymsBfpoyVK0QbGcL+Fm6x7k+Xd329efIPuWaxKJsXXXRr7CJjMVafKbche8bJpeIrAQqU1InoknXjG8v/+BXNWNxITFc66KrzeZsxk+lBwEAMSHithYsvWMy8PyEZajR1CLUJsUs5R0WjJExwDx7OEIVgUaLz96sXjMRrgyHWqFGbm0+GIbx27IaiowFMTq9fZ8xfppy5fvH0arR8/aJfxlW1JrrDfgpSsC9L14icOGnKUN4Ykwml+FyhbAoNsmN10R5rbCOxTaFfq3D/W9Y/vtPVZ/FjyU/Sx5fZ9MEO41nc+Auc7NmY0jCgKCrLZLJZOhh8eLyJzHGb3ZtK6B6x2Q4PT8xPAED4+1nXEoJD5WbPUsDiQhe14kwZRjUChUyozNQ1V7jV9FQW0iMBTHFlfY5cqPJ1knf+uKUqhkrKjPbYQztY05Z3HNDX0wd0QNhIRRYvRbgf56HqKwf4lqdvdjfnV2MfSevunRdvU1acq8L55kYE36+egiNfj4zyjOY349yy8f0pjPvYVvBN5JHG0zCv8c9A+Z1+M439JyKJcMf9tsoQmdg3ex1Ik2lfQX/b6c1Ci03RiYO7dS1Z/acggFxfQEAY5JG4PrUiegd7VzgBSr8xuHsj4kQpTl9y9ZDGhzMXPUV9G0axGgN1jc4W1jNnz0JAPtzyrnlg2crkJwQgWF9hHUiF8saoZDLkJFkzr3fOCbdW0Mm/BD+FzI/TSnFe9/lY8qIHnZmsbbYpiX3HC3B3TP7OjznSMUJfJL/FT7J/wqLhy7EcB85iHcFrNVHk64Z24t2c9uNJiPX8oaPkTFAKVdyXzQdTVMGO6wRrj9FSYw8W5Iztbnc8ujuw52mKZ1xR9YcAEBVWzUSw7oFpcDmkx7VAwqZAkbGyD2r0pJuN5iM+Kn0F3x24Wv0j8vCXf1uR2J4N5yqPouh3QZJ1th1BRQZC0JY401+pCsrNdqpj1NJVQvWf55jt72qvh3d48KgooL9ax5+ZMzRR3qJSFTWFrZgnx9hte2Baku9xlpn9u8z76FOU483Tm7C6qP/cno/MRiGwYkL1YIZw/6CwfIrPrviOPZc2ctt10tEdIyMyadfJoECGxn776Xv/cbbjj+D9YDFymR6+nV4eMh9HrtH9/DEoBdiLOum/hP/mraKW2d/vHxz8Vt8dsE8czW/vhCfXdiOvSUH8M7ZD7gZrb6CxFiQ8e7uPPx29V4YjCaBGDPZzHpzFb3BhFaNAbGRIc4PJoIefs2Yo1dTi8Z5CogVXiql3G6bFLYN6ctaKpBXX4DiZtdSo7acLKjBhi/P4I1tpzt0vi+QSq8ZTEYoZArc0/8O/G7IA108qsBBLbd2DPGHlkgF9UWoaa+1294tyGaydiUKuUIwC5WNjB0qPyo4rrKtGiXNZQCAC/WFXTdAEUiMBRn7c8wvrKZWnaA1TZvWgCWv/QQA6JsWg3EDrX4sd88Qd3dmrwMAMZHU8ogQRsb4TBvRAw/OGsCt650YuOYU1uDwebNZrEph/bXuqAcqYF/cfNqm/Y+71DSafafyiv2rkTC/ubMtUj32jIxZjF2XOgEjuneuziiY6R7ejVtu07f7vJB/89kPRLcH2+QJX6KwiRhHKM1F/vXaBs6bbXrP67t8XHxIjAUptpGxspo2LjIWE6Hm6nniokIwY7SwgS4/dF9ea3YtpmbgBCBdM3bvjf0wZXgP3HejeUaXzmBf3M/nX19YI1H89LfTyJiN1cLBsmxuuSPtgFypgfMF5a3SffQk05Qmo2BWHiGOUq7EtLTJAID1J9/CU/v/hhYfurPz7Si6hcZzyx3pK0qIo7T53LiXN7nlaou5bnpw/AD4EhJjQcq2ny6Cn5XkR8lUSjmXYkqMDbNzTX/ijQPcMhs5SE2M8NpYicAhREK8sF5kakvK0XampKvXdGT8yjAMfik7Irm/IzOknIk/X1HbXie5T+ckMkY4h60ba9W3wcSYkFN11qXztCJ2QZ2FNSn944jfYfGw33Dbg9ULzBdEqKzfXxNTxmJE96EY1m0wAKBRa05Vs079vsKp9K6ursb69euRl5eHbdu2AQBWrVqFsLAwhIeHIy8vDytWrEBiorl31ubNm9HS0oKmpiZMnjwZM2eau8bn5ubi/9k778C46fv9P9JN2+d13nbs2M5wnOXsBAhZ7LJ+YbSUAmUmUKDsVb4tpRRKymwpKYWyS0uhlNGymx0ge5vYmZ6J9zjfPt3p94fWRzrd9Lb1+ic5nXSnO+ukt97jed555x2MGTMG7e3teOCBB6DX6+HxeLBq1Srk5OSgpqYGK1asQElJScj90YiO5g5nSKkKHU3j8sWlYJgAfnwmN7122bIJ+NfawwAAm5M72bu9DPYd5XoZhmoGQWNgCVWmFBqDDbxFljeGYGx8fipqeb2yZ97bi5UXTUZxbvAE2buHPsQJR1PQcgEmwIgX2WghG/eHkiBkOKueUD1jftYPWsuMRQXZNwZwE6uR+Gb/Sbz66UHcunwqZpdxbR5tXS5YU80RJ4dDUdfTgKO8H+Uk6wS0OqXeMW0Yo+84p3gpNjR+gx6vHafmzwUAZCSkA+BKlRQomPWD2xcdMTO2c+dOnHHGGbLSVUJCAu666y6sXLkS5eXleOmllwAAe/fuxdatW3HnnXfioYcewqpVq2Cz2cCyLO677z7ccccduPnmm6HT6fDhhx8CAN58803k5eVh5cqVuPbaa/Hwww/300cdHQj2RkkJhpDB2IIpOUizmHDrJdNEFf2fnj9ZpifFsiw+21KLPUc482GzUTsxaKgHYysunCz+36DjnvdFyCCMyeLuQicXp+OypePE5c0dTjz/XvBEry/AiFNmofDFkRlzE1ppsQSQ/Y1SM4wkbJlSy4xFhdLDMRoT6Vc/5SQn3l3DNXofrOnA/S99h1Xv7Ip7P9bUbZQ9tprTxP+T2RyN3kFTNJ5c+Cv8aekqlKYWA5C3POTxQsCDScRg7Nxzz0VSkvyguOuuu8T/syyLxESuGW7dunWYMWMGAMBgMKC0tBTbt29HfX093G63mD2bNWsWNmzgmsnXr1+PmTNnAgDKyspQVVUFu31oG3oOZYSyS2uXC6/8l2tuTkmUTjw3nF+OycVW1W2vOlvybfMHWBxpkGQEslK1njEN9WCMLDMao8yM6WgKJoMO914xEyaDDpcvHQfK5IBxwk7YvMEXRjdh8ByKuIIxj5/4f+zbH+uuxa1r78fL+96MedtwhAq4AK1M2RewillgwXooFvYf40rJhxvi9zxU9gbqaB3OKFqEZIMFeUnBptejjY17T+DNL6r67PXIzDd547KSKA8PFr1Kd9hsNmzevBkvvPACAKCjowOlpaXi8xaLBR0dHWhvb5cFdBaLBe3tXDo21HMWS/j6bXp6IvT9rHuVlZUceaUhRg9fYhR6vQCp7AgAp88uREaqumXND8+ehIN1XdhxsBmpaYnotEulkvIJI+/EMBz/vr2hLz5vTo5UPnz8llPx9bY6LJtfLPYdZtk49XCDUR/2/ViKC9yEdfKzk2GctB20yQ29+1jQtv6eyMFYSpoJWSnSdtF8Xpb03Uwyxfwd/fPoDgDA3rZKdFKtmJhZGmGL6DC1hD63JVh0qvvJsH6YTcZRc1z35nMeOnA45tdLTzahs8eDVAt3nBQQpfTMTEtcJW6LORGwAzPzpojvvyLzCqzAFUGvN1r+roD0Wd/4nAvEbvvRTJiNeuyqbkFJXgrSFb7ILZ1OdNs9mFCYjqqaDuRnWZCSFL5lIaVFsk0qLyru2w8QB3EHYz09PXj00UfxxBNPIC2NS61arVY4HNJdrd1uh9VqRUZGRtDyjAxOQyXcc+Ho7Aw9+t0XZGUlo7V1eFmuVNaEbvoV8Ht8aG0NzgAInzfAZ9Y+XHsYzR3cd7zyoinD7ruIxHD8+/aGvvq85GvkpZpxzVkT0dkh/X6ddi4Y67a5w76f282ApilxHbvdA9rEB1yMQbatzenFw2+tAYKt92Q0t3XD6OFu7KL5vKs/OoAdVZK5dkurHaYYr6epunTx//+35im8uOz3sb1ACLp6grODmWYr2twd+GD/F5hgLpNdrDMyksCyLAIMOyqO694ez/nmfFTikPiYAhX29XxMAN38zWm3nTu29x+Wjp1n39mJ9bsb8ee7F8MfYHHsZDemlkS+jgUYLkN3XdlVYd9/KJ+vAgEWdpcvYvATLWqfdX91M1gWeOzNHSjMtuDR6+fJnr/hybUAgCdWLMAvXt4Ck0GHZ287Laxln8cpZcUH6rsNF1DHNU3Z0dGBRx99FPfffz8KCwvx5ZdfAgCWLl2KPXv2AAAYhsHRo0cxd+5cFBYWwmw2o7W1FQCwa9cuLF68GACwZMkS7N69GwBQXV2NSZMmRcyKaQQTYFk88+6eiOtFunvT85pP3x2QGqWnlKiXNTVGD7++bi4evmZ2xPWE40dpdbT7UCuef3+vWEb3+QMwEFO8LCWtz/rkd70n2xxw+uR+fWq9UbFMU9ocXlkgBsQ3WSlMwvU1ap/lonHnAQAa7CdwrLtWdX1NDiE6lhbKNaVYsGGlUZo6nOJEuo/XwhOGmwCIfqwdPW786d/78Ow/9+LA8WAhVyV+NgCaolXtrYYLn3xzHHe+sBlHGuMv10biN2/sEL1r61vkbUx2l1T5aeCf8/j8eDrC9XBqZjlmZk3Dg3Pv6OO9jY+Iwdi2bdvw8ccfo7W1FatXr4bb7cYNN9yA6upq3Hvvvbj66qvFZvyKigrMnz8fzz77LB577DE8+OCDSElJAUVReOqpp/Dcc8/hT3/6E/x+P5YvXw4AuOaaa3DixAmsXr0ar7/+Oh5//PH+/cQjlHD9LhcvjH46VVBDr23m7hQmFaXBkqCNWI92inKSMS4/stehOFWmmB154d/7se9oOw7Vc+KqjD8gU96v8xB9Iaz8hsHpZmAYI2Uxyq0T8ezi3waN/jMxGD87VX4v/giCs2ooL+Dx9K2poQzGDLRB1nTe6mqD0+fC9qbdYFkW/z20BgBwsOMQNCJj1AUHrUqDbpLGNikAsDm8YFkWXhVhY68vIAoIn2iLXL0J8MHYcOar7fUAgO8qQ0869wV7DrepLj/RJmWRe4jA7PjJ8O4K+ZZc3DjtahQmF/TNDvaSiLdR8+bNw7x58pSgEHypceONN6ouLy8vxxNPPBG03Gw245FHHom0GxoRsLvVLwI3XTg55FSlGtlp8n6yZbPGhFhTQyMYIRYLhDBLEvTIGH9Apm/HgAikKPm2a6sqoUvlSvDlibPxs4rLuWwCpYOP2C7cBCIJy7J48/PgpuB4MmMBcNuYdEZ4/F7UdtejJHVskG1TrCiDsdtn3CRr6rd5enDfJu68mWy0YFNtaP01jWD0VPClz8W4kaBX76dtapcHVvuPdci0GwXabVJvYzTn3QDrH/bBmPA9xDMAEwqXhxFv3ATIDFggwILmzyWkwPTbX1bLthlKcjWRGN5HgYaIx6t+IaKo2GQpJhamyR43tg2eMrXG8EM48YXyX9bpaDD+AFwevyz4SdGTxx0rKwEdbJDKiX6/ZIk0JYOb/s3lx9LDTSCSdNm9qK4Ptj9iAnEEY/wH9fCWOn/Y8TpueubrmG6A1PApAssCS54sM9bpkUpCXr8X2Umcxc+tFTf06n1HC2rlXJdiYtfj9+IPu1/GrpZ9MgkUAHj+/WD5FQD49DupfGx3+fCXTypx8zPrsbO6VXV9PxuAbpgHY0KGUPkd9YY3Pq+SuXQo6XZIw2XhBKb7Q6S3vxjeR4GGSKi7epYFpo+zYvq4DNx88ZSIrzOuQF6KOn16Xp/sn8boQKxShojGth9swb83HAMAnCSyDbKbV4rF8+/vhY+/46VMRFYiIJ2yriq/HCum/RSLCk4BEH2JsLXLJXs8cwIXyPxr/dGoticRypQL8+dzj3VuJMxeA6cn+pIpADh9TrgZqUwmlFxPy5+HsSmFMCnEbDc2fiuty/rR1NOCJEMiJmeUQSMyFEWhwCI/tzkVfqC7WvbhUOcRvHrgb0E9kKEQ7OMATjNv6/fN8PoCOHpCvZ9quJcpySRAbyQ+lJDBlhr3vPgNrn9yLf780QF09oQuLztcfZet62+G71GgISNUvwvLsjDodbjz8grMK48sbKe0RrKmjB59sVABhEb0CD1joTJDX++oxzGVXg5KVprk/l/fwl3YjCWSGXgBKxlgG3VGVGRNEZXKv6hZg2anegaChAzGFk7LE7XT6pq5viCWZfHdie1hLYkA4IS9Cf86/AkAoChZXs7vdsWWUb5v06/xf99K/bIMy11Elo+/APfPuR0URamWxQBOq+qkvQX+ODJ7o5nilCLZY6ciM9bukrKzXkY9OFhUkYfrfjAJq24+BeMLUmXZoaYOKbgjS2wkwz0YO0EEn3aXD22KG514IZML584vCrne9qoW/O2r4D7J+ZO5a92z70UeahsqDN+jQEOGcPBecGqxzLoonvhCaNivGBd5NHuk8K/Dn+Dn6x+C1x/+jkwjPFJmLPQ6R1WmrmQinPxr1DXLx8199RMQYILLS0LJ6YSjCU9uez7iPrZ0SheMkvwUTC2VTwvvbNqPv1W9j2d3vBL2db47uV38/45KG1ivZKfS7Y79ouRi3GBZFn87+D72t3Fq72Q5LScxS3W7z45/DQBw+yNrsWlIKCdhXQz3N7N5e/Dx0c9xuOuY+Nwu89sAgHuumCHbpiQvBadPz0dWWoIoeCxAtng4VIKxgx2H0OxsHdZCvQ2t8snGl//zfYg1Y4McjvjBgrFYVBFbhaasiGt7ONnevxJYfYkWjI0Q/HwmwqCnUTE+U1wu2M7EgpAhykxTb2Ydiayr34wAG0CHu3Owd2VYI/WMhY7G/CpZs24HWWrgnt+07yQ6iIZo1m9Q7QEhAxZvwIcvataEfG+WZWV9PbPLsnDKlFwAkpXYp4c4i5ouXzue2vGnkJ+FnObcf7wVnoPzxcc97ugzY+REZqurTRbkkRIeyUYLHj3lgahfVyM86WZ5f6yTcaHJ0YyHNj+Gr2rX4UjX8aBtChXnU7KSYAwjQu5QDFj5Agz+tOevADiNs+FKY6v8OO8JkQGMFpZl8cjL34lB3hVnTIAlwRBWL0zJTRdMRn6GJCTv8fqx53Bbr/s4+xstGBshCL0Keh2Fa84pw4M/mYXf3jgfY3Nj10ESjtlhMoTSp2g6Tb1DLFNGcd4jT7A6HXGw8SXL4ydtuHf1t2AZLujxt47B+t2NsDnl2UulofJ/jn0Z8j3fXXNELPe9+sBSpCQaQVEU8jISxexyi79OXL/GVocPj3wa9DofH/0cX9aulXZZ7wXrkUr6x1uiD+r9RLP+esKWR0/rgybBNL/CvmNe7iwsyJuDC0vPAQB8cPg/OKGwJ1JiMuqQky7dpJLyLMV5oc+1ja12WVDvILww9cNYY0wo+Z89txAAMJNIBMSDzeHFrmppYEd4XZLFM/JVt73otGI8f/tCnDI1VzaIducLm/HHD/bhvXVHerVv/Y0WjI0Q/v4/zt7D4WKQYNJjYmEa8jPjO3ELJw16FEZj/ijlETTUkWTGpAtPqMzSb2+UMknjCqQLWY5VnpFl3YlgAzTA0mAB/EExyaYWQAdC9E+t39NI7Kt0fCeZDXC4GNV9XVO/Ec0O6QLR6mzHV7XrZOtQOj8AGr76CQCAdce2i3finT2esBNfDCsdcxsaiMbLABJOAAAgAElEQVR8lYGEcCUtrXk/NvS0HleX/xCzsivEZZH6BE0GncyflbyhOG/+WPH/ZYqpdIebkTWaO31SGXs496oKPXILp3FlRLu7d5mxN7+oVl2emiS1ACxfJFmOka00Z8weo+oCIGTTN+w50at962+0YGyEURxHJkzJMD43xMUJuyRWKFwYnT5nWEVuDXXUpC0E03DyRJmcaBDLgtx2xGuQ/WN6L2hLNyjiVHX8pLyXTE0zyu5T7xUJdYNh0NMIsCxsLvW+q79X/Vv8f3Wn3Ncw4LSAaSvABacWY/pEbhpZn1uL7yqbUFnTgXte/AYrn16PL7bWQY1YSuOkDMLUjEmy5y4oOTvq19GQyDBLllZNzpYwa3Jcf345AK5EOZ6YPiezZLPKpP6+zFQuY7q9qgWHOo/iV98+KTMI98YgVjzU6OADzBwr5/O4ed/JkJOj0VDfIv22yZ/qOfMK8cOl4/HbG+cjJdGI639QjmvOKcP4MdL3rxw++93KBbLHHp9/SA+5aMHYCEDoq6Eo+UkgXgTF/rmTRp45uBrP7Fwt/t/P+lHX04D7Nv0aa+o2DuJeDU9oFWkL4c6UzCIIJ28BPxH4koKxxpL9/AszuOi0YgBcIEdiUFFTt3nUveYELVahT0zgYC0XEH22K1gMFgCOdB8TP8dxmzyo8hxYiOvOmo5LFpXCpJf27dVPD2Lr99JFd+2uBtXXfmX/W6rLVfefCMZKU4tlz6X0kzXTSIe0Ivq+XT0zAwA/WjYeAOdG8dqDy/DyfUtC9jIlEstvu4SbAK5t6sEblX9Hu7sDr1W+Iz5v8w5Nz8lIdNk9on8xGYg+/tZO0ZYoVoQe55K8ZDx6nSQ2T1EUzp1fJFZ7Fk7Pw5KZBVg6U5piVg5Q5KTLzzEA4PFqwZhGPyJ4gk0vzeiT0uK584vw0j2LgzTHRirkFJrD58S+1koAwEdHPxusXRq2UCo9Y4IWUWleirjMpVDrbnVJVicTC6XjjjJKf5uz53Ij7kpbJrXMWI9H/WLg9QUwLj8FN104Wbb8rDlcb0q1a6dsebJe2ufbX/wKB2s70eGSMlkJNHfxEO7KDYom7s37TkrrmvT44PB/8M9qycGkzdWBVpe6h+H9c24PWkaWVk16k+w5LRjrPeECo0UV6r1KJPf/eCbKx6Zj5oQs/Ob6eXjsxvliRtgLJ7qHaeClhtKVgMTm9OL7mg68/WV1TNmoli4XLAkG/N81czAmO/LwWaJZj7/cuxgv3rUorOuFEOT97etq7D4cWf5mMNCCsRGAcMc+u6zvMllGw/BtKo0VUvzxr/vfDmmJohEZNdFXKTOmwznzuKCnmdBg6vbYZD1YrT4pgPHbuJ6QiwsvgUGvbkKelRjcNNzjCZ5mZPwB+AOs6rE9jZe3aNVJmkWsX4e2AxOlfdG58NQ/duOEgytrp5lSMcbAPS9Ys6SapOBNSaf1W6yt34SNjd/B5/fBzbjxyHdPBq33wNyf457Zt2JsSnDzMonP74ORmOjU0Tqs2dmAt74Mnd3RUEdZ8lUjmhvdSWPTcd+PZyLRrMeYbAsKMpNA0xSohB4ctLzfF7s6ZOjiJ6CvOpv7DZxH6IHRFIWn392Ddbsb8X1NdGX4AMuipdOF/KykmCyMDHpdyAyl0Mifm8FlybZUNuOFD/ZjZ3ULHn19O65/cu2QUenXgrERwOF6LjOmTNNqRAd5QXP7PTIl9053sG2ORmiEkyhp6itkxkxGnVjOEG6W/QE/3j74nuw1yEyXIAabZc4Us0+MohnepDMiP0ledlQrU3r5k65JJRgzG/WgU6R9Djgt8FbPAXTSsUBRAYAKwO5zYGL6eDx+2sOYZl4IQArG5mTNCnptADAYWPhTpAbiTk8XjnbXqq47xpKP0tSxqs+RePwe3DvnNtmyd74+hPW7G0X3Ao3ouKXieiQZgstaJPEWHWiKgmnS9pDP3zc7OAM6HLDZualmobmebD0g/SKVjhehcLoZ+AMs0pP7Tmj8jsum4493nC7T3gSAFz88gFpex7C1s2+EanuLdvUe5gRYFpv3c5kEtYuMRmScjEvsxclNypEJv3Z5+s7iYzQg9IyRWmLCFBl5fArTli/ufRUHO+QK2mT/mCBzodPpQFEU9DpK1Zrmthk3Yk7ODPxo4nIAgE2lTOnhhSRNxuDficmogz5b6gXzVM9BwJ6OQDeRdaMDgJ47NpJ5iQlhYlLImpgNBvi7uSybPu8ooPPCOH43xo2TX8m7PN2o7pAGAS6bcJH0NhEU2c8euxQAMMk6EdkJ3P4tHDtPptB/om34iF0OJtsONmPdbm7C1kgHT+L1BTqaAqA+FeXacSYyjbmqzw0kew63hexpDIVgWZRq4cuwRIbJQ4i2tnXLh2L+/vUh/OaN7bjrhc3YdlDqqRRcCtQmIuMlwaSHJcEQ1NxPMlREA7RgbJhT2yRlAIpytJ6RSLgZD76qXSezN7F7HaK6eZOjGe1uabw9WvNpDQ6yvOD2clml1R8dAAAkkIb1/LWpujNY+yfAklkdXsyYl3Qw6GkcO2HDN/tPyrZJNaXguilXYmwK19BrVylTCr2Var0uOpoCZZSkBy6Yy5etAnr46njJCDoAysAdNxY+GBOCTqFdJSPFjNRELkNgKDwM44Td0FmbUZvyhez9Ot3dWFMvDYicmj8PTy78Ff645HdB+6bkwtJz8PhpD2N8WgkMOgP+uOR3uH3+tTK18UffCJ2J0ZB46eNKvP1lNbZ836Sq9yVo3AEARcc3Zk5TFAJOrnx98/RrcVbREu61AxQQ0KPH2f+uH7VNPaiuC10u/OMH+/C3rw5FJYza0GpHZU0HPueng1P54EnIDgNcYCYEQMop4v/tbEBNUw+6HV68Qij290cwJhAu3mJCWAkONFowNswR/M/OnlsokwrQUOedqvfx8dHP8e6B/4jLPH4PzDrpu6skJqq8fi0YiwXyLrPD5pE173JldF76IsxryDwY+cyYXscHY/wJ/tVPD8ruxAWEv+ORjpogzTghOEyzBJ/sM9OMoC1SFpQUm2R5c3LTxF1i9sxEJ8r2VcdfiGiaQlkBYSMWkF/gBcskUtz1l/PvhUlnRLLRIpvsCwVN0UgzSUMMOprLGp5oi80PU0Pi5U++B80H/OS5wFc/MdQmUUPTFCi9F2BpTMucDLMweMFwx2GPs3/PMV9srcOjb2zHqr/vjriu0xPeWJvxB/CrV7fhmXclz8c0C/d5Tp+eJ7YhfL2jXuYvKYiSk72iAHfzItCfwZhgjwQAv/zpHFyyqFTURmOiNIHvb7RgbJgj/JAnjBkdk4+9pcZWDwDodktm1X42IJ6IAcmjDhjeGkCDgZAZM5ZtxxuH3sB/v5X6ovQ6WgygjHo6pI6b0cBHdAY39NkN/Lbc36eYmMjssnuCtjXruZN7VdtRrK3fJHtOiPHmqEi2dHikbKhr9xLRnxUAWJ90cRb2RxfglinLlNz/iYBKEYwFnFz2uq5HKgmFa/qPhUaFT6ByYlUjPB4+W56RYMWl4y9AOpUPf3se/N18cE0BB9oO4lPeCzRaaBqgzE4YGO5vvyBvDnINY+GpngOg/4Oxj7+RbJ0qa8KL2kbK0nX0BP/mhADMoNfh/AVcr2Nds/xYrG+xY9/Rdjz08hbZcrKXq50vZ1pT+36Aal55Dl59YClee3AZSvJScMGpxbCmcL9hLRjT6BOEH09yYv/0O4xUJAmGAFiwMjFNEp+WGYsJoVKhS21Ho7tWZsqtoylk8AKY08ZlhJR0AO3HzLOPIWPGfnGRgQ/GppRIpt4dttDBGADU9sh7YAQVfLVpSobPogXcCchJ5t5jUUUekhMNKE2aoLKLimCMKNEsLJCcBcgBAADwd+YEvZZJ1ze/3UZFZuwf/zscYk0NAVIfq8vLDevMzZmJZUWLMNZ+NhDQA6wgZBzAn/e9js+Of431Dd9E7dZBUxRAsaBY7rhLM6VinulCsC4uOGvp6t/+vnSLdDPxEt8yQEJmVO0RvCWFYRyBxwgXDSB0VuvtL6vxvMI5AwDqWuyivZnQRlCa3zc3J0qUE5o6Psuu7GkbLLRgbBjDsiw28TpGSiFMDXUE42Xx4stnZ2iKVjVhZsMW1DSCkZ/wyPOfXkfjjFljcOMF5SiY2ojfbHlKtq4w1Xqk6ziqug7BSUnBmiUh+CRf0xQ8MUlOxjq88uBEmPAiL8ACHn5ow9+RhwtP5e7urz2vHH/4+en4xVVzg8ycAz4jWrpc+Ggzl3XQEcHY+LQS8f+6VHnA6e+SZ+XOKloSsWE/Wnoc8qzG97XhsyAa6s3bU3iZi5ZOIUjiViIHS94/9DHWNWyO8j2EBn7hBpDFN/sl14/31x2Neb9jgZysTTQHS0DsOyodo7EEY0lmPQoUlnunV+TJHi+ZWQAg2Cid5JPNxxFgWXxf04E0ixGFA9T7PIbf9017h4ZNkhaMDWO+r+mEjT8BZ6Vp2ljRIPTkMH7u5CAGYzSNzIQMTEgrla0/nH3jBgODnsYZsyVVbLIEUJqfApqmcOrUPHxdvzZo23vn3BYyMBHskPxEs+1nW4KlIci7306PXJbEyV8Q1KaO3X4uy7b8tAk4dWpe0PM/mXSZ7LHfa8D6XZLPZVKC/GboF/PuUv0c8Mn7OuflqkthxAMTYGVTY2qZw9HGofou0aFEDYaRjiemjfu75yRmgWVZnOD7nCgT9+87B+U6YYc7j0W9HxTNihm2D9YfRUNrfAr18eDxBZBrTURmqln8DcifJ6YgveGzfeS6ZDZYQEfTKCTEWgUNMiXlYyULqs4eD1o7Xehx+jBpbHpMGmO9YcaETGSmmlE/gH+LcKgrpWkMC3bxSsLzyrPDju5qSAjNuW6Gu1AJd7uCAXNmQgYOd0knWS0zFjuLK/LxLV8NEUqDT91yKqwp4fWDzDozaCq4lyyFzkSykbuLJYM7oeQZik5PN9weBq9/XoUcawKO8mWQMVlJQetub+Kam0169TLLKflz4fK78cFhbvDD69JDr5cuGlaFNhIpJAwAS8csxCTrBCSU5ePJr2pgHMvZLiUZgvclXhh/AHodBVJizO1lYDaOztO83eXDk+/sAgC89uCyoOcDAVY2LOI7VgHfsenQLdPB6Wbg8viRnmyCO4HLkO1u3S/bPtpzg3A8syyFuuYecQpRYFxB/5TlBHxMACajDj1dXjjcDDpsbvG3yLIsdh+SFOndIQRQnW4GL318AAeOS9nWpXzWS0nF+AzU83ZINEXBZNDJgjjhb3Gy3YGHX9kKt9cvliqVv6P+hKIoWBIMaOt2o7HNEZTlG2i0K/gwZj+fXp4xIViBXEMdoafI5eN6mRhe4FXQFpuZPV22vpYZix2KuGMWNMEsisyRsuwHAHpar5oZu3/BCnH52FyphGENMT3821N/gcKUPDABBl9ur8H2qhb899taVNV1IceaiOREI76sWSubmt3ezF20k/ShhT+Xjlko/t/lokSfuxsvKFct/5BcNO48TM0sR5rFBNYrZbGTDH2X0fb72aCbMqEPZzTyu7/tDPu8uk0Pd1wKvbh5GaGPh1ADKKHW8zPAXz6pFJenJBlhMuhk2bm+hmVZeBk/jHpaLBXeu/pb8fnPttSijvCR/GTzcdXv5diJblkgdt6CIly0sCRoPQA4f0Gx7DF58/PgT6RMcF5GEgx6Gk43IwrDKs8T/Y2Q3fuDSj/bQKMFY8OYYv7CNHFMWoQ1NQSEZmkXnxn7vOZ/ACS9qykZZbhh6lWiCGcAQ2PSZjhB9k8JavlkFgkAipLHQImB1sl6vqTl0rKpJVbcd8UMAJLGl83plQUd6eY0ZFu4GxSnT95HlZVqRrenB58c+wKr974qLi+3cuWUGdnTQn4uiqLw8KyH4N6zCD1OH2qauIlcpVemkolp42DUcZ8hPdkE1iPd/evpvstaMf4AdDr59+zzjc7j92S7Q6a79tYXwQbwgr6UatmaL9flZybB1xA8wAEADl90UiJC9s3HsKImFwD84qpZMOhpVRHjvoLxs2BZ9aGVQ/Vd+GCDvNTaZfeisTX4czUpJCkKsy0h7aFMRh2e/tmpeP527ubltkun48dnTsBfH1gq2hMJ5KQn4mS7A5V8oDd+gP2QBRP3dpt70G+8tWBsCNDZ44lrDF04dNQakjXUEb6zBttJMAEGu1v2B60zK3u6aLo82D/Q4YhM/JHhSmdKE1+GDT7e9bQeM7KmBi036AjhTYrCeP7mw89fxB59fTueeHunrDdICOBMiuSZ2aSXmZIf6eIa8J0+F/S0XjUYJMlJSQW8iehxeMWMgrJfTOCRBffj3LHL8POZK8RlNE2B9XDZFort298t42ehD2OWPJpQCvuu3yM1aVfWdGDL901iEDS11IoziT5HlmXFsprZqAdzQt5HKlDX04i19ZvgYsJP40kixhSq6rg+xgd/MgvZ6Ykw6GlVvbxY8Pr8OH7Spv4cI0nJPLFigbjc6ZZKuABw5ZkTcMUZXNBZVdsJh1veyP93xWRuQoTStzXFLE5WpiYZcdacQtXgzZKgh5cJYN/RdiSYdCjKiWwO3pekWUyYMT4TLBt+yGAg0H65g4zX58c9L36DW5/biA17GiNvwPPltjrsrOZq/Vq/WGTsPgdOOppl6u7vVn8Imzd4Ig+QLGkCWs9YzOiIk67d7VPNPJDOBteU/wgXlJwDo86IGVnBmSmDInskZH98fGZDsFsiNZCEJuCN9Vtl2za22tHqlIKxFif3G3L4HEjSJ0ZsHtbRNKwpZhxq6BabnUOVVrITM3HhuHODXvPx6xfCc3gG3Idmhn2vWGECXOCbQkxW+6NQVB+JqJWNhRurZ97dg5c/+R52Xt/LoKNx5VkTMZNv9+h2eMXMGKeDRcHfwzWcp5vScNesW8TX/ODwf3Dvxl+F3RexL42VjgNBF1JHU3KR4zj4fGsdHntzh+z64XQz+GjTMdz+PKe1Z9DTyLUmioLH1fXy4ZbFMwqQnc6VzN9dewQPvvSd+JzSW1Kvo2XtAr3BoOfODQ43g0lF6aoZvP5GEEvvUtFQG0i0q/gg4yamV978ojrMmhK1TT3451rJRkavG5jpk+HMr7/7PX679RkcaJPKFd+dlCxjbp9xk2x94QKqZcbigJK+s5ZOh+oJ1sdPs66Y9lPMz5uN80rOAAAkqvRQKfvIhDvsQ/VduP5JaSqTzDBUNnN38r6sg7Jtb7tkGlqIzJiO0sHFuNDm7ggZmCspIHpgBOHIWMi1JiLQmYtAd5bq8912j+gWEAtCz9gj183D9HGcUOloDcbULG6U4qr/+bYGgBTcj+UlFY42douZMZNBhyuWjYc5mQtIyqzjkZsULBocDrG3jAjGhPOLjqZkE8LxcKSBC6xIXbnXPzuIT76pER/n8ibewhSjUsJCCNYEHG5GDBJJ6Yunf3Yqfn/LKaLqfm8xElWd/EFqoBfOJ++tD7ZmG9D9GNR315BNmQCIyhtM6Tun0zJjERFU9UNNQE2yyvtChAZzNsomXQ0J2cQ7FZAFY16/Dx8d+Qydni7kJGahImuKbNsEffzTVORvhwqol1HSU/X4qnad+NjJuPD58TUAop+OEzIIAHDm7MIwa6rDlVpTQVEIyor4GD/u+tM3shJStAg9Y+nJJsyayAV66k3qI5PmDie+PcDpLqr1Yb2/7ogsYN/6PWdSLVQWhEGotbsaxWDYZNDh7HlFmJXLHaczsqbCYkjC9Ez5cRsOoe+0MJsL9n7Aq9QD3Lm7twGzEBh5mQB8jB8NrXbsJCYk8zIScTHfbD82l5vcJCUuBOuvrDT5b+89/oaftEhKSTL2WSAGQCYrQX4vA4mHL+V2apmx0Y1S18UWh2lsqEZKjehYmD8/aJnwnWplyjggMmPQMTAZpNPMV7Xr8HXdegDqzesJeinQ0VE63DL9uqjflgxsJuFMAADrk0tVrN77muyxw+eExx/bSbi8SNJIOnte7MEYAFjMBrBssGVRA988rbSTiQaGmKYUhih6m3UZTjz8ylb89b8H0dBqF/sJSb450BRUcgMkv9OinGSkJhnR2uXC659xGXSGD2Z/VLYc9825DdMyJwPg+kqjRciM5WdY8OTKBbh0sdSDRlNUVDfgajD+AAIsKwuW7C4GB2vkhuCP37RAsinjf4tkf5TQK6bs6/xqO2cdJ9gUnTYtt89bYsjXI62RBpLlp5eifGw6br44uF91INGCsUHkZLsDR0/IR8/f/Dx46oekvkV+kp5dpl7q0IieybziNomUGRs9F7M+gwjGKL28Z4zsFRPkREhIO6P8pBxMzSxXfYtUFbPvd9ccEf9eBiYN/p50UAYvoOPe5+y5hajrqZdt4/A5kWHm7I+Wjz8/4kcDgPJiKRiL90ZI6DNTlosee3NHXK/Hsiz8/gD0tFT+AiCTLRjpCMF4Z49HtUwJAL98dVvQMlL/Tq+jZfY4E/hhEZPOiOKUImk94kYi3RR6mv1w5zE8v+slAECqMQXZ6fK+RB1NxZUZszm9WPHUevzxX/tQ1yyV172MXxbUKA9PE9+j5eKDsdOm5cqeP2WKZNclBEobeYX6i0NIWfSGe340g9jXwUkqpCebcN+PZw66ztjoVAMcBFiWxWdbajG52IoS3uz44Ve2Bq2392gIvz6eR17jTiZTSqyyA1kjev5v/j347dZnxMfj0oqD1qH4PiVN9DUOZMGYVzbtS17E1LwpyWb9yyZeHPIt7v7hDPG3INDU4YTN4UV9ix1fb6uDYawFSO4EZXLjzgvmYkqJFds36uCDlBXY2Pgtzh3LiVAWWtRFLJWYjXr88Y7TRUHbeBAazE+0OpCTzvXqhFOKj0QgwB2pQsuCMNG6ZmcDfnKWugr6SMXt9eMNFSmLUOQQZWc9cayeMiU35AWa9LJVmwwGADfjxvO7XxIfz8+bHfw6uviCsaMN3E38PsX1wuP1i1mv634wCbMnym/WxcyYh7sJSFbYjF11dhnOnFOIt76sxok2h+xmNJJoczykJ5vw80unIylBC0W0zNgAUddsxwcbjkW88422iZE8gWhET4LejLykHEzIkO7yLCoq6DThI6cRGxRNfGd6n7z8EcX3eUXZJVg57acyj0clhdkWTCoKzki4vH689hnXtM8yRn5/GIzNSeZKQnxwffP0a8VtvqjlhgAEq6xosCQYxCmseBCyFy/8e794jP3tq0OydWIpXzXwGTChSb3LLmUd1SxwRjLvfFUd0daHpDhPUsA3EMNQZHldCfmXCWUYrpS8yE0Mbvyn6fjKlGRzPsmJNoeYbc21JiLRLJ/0Ffo3BR9To+IzJpj0KMlLQUqiET4mABt/PE0pTu+3dpgZEzLFDORoRgvGBgg7odvi9jIy81aSjDB3H298Lk2Gjba73b5iagbX8+Hzc3+P0tRi1fW0acpewMrLlClJ0gUhmm/z9IIFmJ4VuUH66nPKgpa5vYzUhxLgLjw/u6wcKUlGBNgAfH4fxqeViGbQJEoJjf6EDJAEYVZlz0x1nbz3R+CZd3dj9UcHZMteeG8PAIieh7MmSq4chxQyBiMdGzE1ef4pkZvCyaCa7GFS9lCRkBOVTsaF492ST2qXpxubG7fAF5AHwWrBvp6XtlDqekUiU2EFdvulnCRMTVMPjjR2g4K6X7EwvVjJ95WRIrQkgjzKNn7IQRg+0Og/tGBsgGCIkkZDiwNbar8HndYiLrvw1GIAQCDE9JPLw2DjXm5SqKwwbdDq68Odq8svBwDcNv9aFKcU4fopV6quJ9wFspoCf8wEIN1oGEsqkZokXez6suyr5rno8vilvx3DXVA8LNe07QswYMHCqDOq2i71pRp+JMiLqXAhZvgMidDg/dS7e4K2Y1kWlTWd2FHVIgvoEviy59JZBfzrJ4hWPn/8YF9c+3iksRvbDjbHte1Q4dLF4/CbG+aFfF5QiRcgy5RqRtgCOYlZuGPmSjF7e6BdKou+sOev+Ef1v2XSOVMz1Hsfvfx1Qa1lJRxkxj4jxYTysemgKGDPkTYcru/ChMI01alH5W9mcrFV9fUtfDD2jzWcXEbF+IyY9k8jdrRgbIAg+wJqmmx4t/ZtmCbuAmjuhLp4Rj4AIFTG+nCD1Og/WrWDeoNZZ8IYS754d1qUVoD75tyGdLN6elxr4I8fZcCVSYzMHyFM2M8qWtKr90kwqdnYMHDxsgQFyVwzciV/oRQGBkw69fLiQAZjywjF93tXf4u65h7sqOJuzpaEMGAG5BdhcjKwq8cDo4GWZcx7c+h29njwxNs78dLHlcNGHkMXIngakxWs6j4my4Jnbj1NVIkXSE2UHiutpZRMTB+HKyddBgDo9nAK+I32k2hycAGsIKEyL3cWVky7RvU1hPOLzRHbFH2HTZoAXjZrDMxGPbLSEtDS6QILYGKhuq3QmOwk2WfOsap7b7oVZd7UPpSz0FBHC8YGCDKAqmyUrDkoPXdXLFiqhAq0aomJmavO1kqUsRJgA6rZkFBQmgJ/3PgV2mwLp+UB4Mo3x4hyzsXjzuvV+5BTmsKQgNvrh8vDYGJRGu5fvggAsLtlHzrcnWjm1fadPs4qR9kr2BuNs1jR62jZJNuvX5eyKElmrh9NLRQgpSq6+Qu4zeFFzUkbjHqdrK/HFYdwrADp9dmbQYWBRFnmXX566J7De66YodrzRwr6hgruSFKNXL+ZEIz9fscLQesc7jwWsh8xVGYqFN0OL062O9DZ40ZOegJ+t2IBzpnPTXkmE04Qaq4XAFd6PWduZDmW5ER5r9lgyU6MJrRgbIAgdW8Od9ZIT9B+TCpKg8nAnUhDNYzX88HY0z87FUU5Wv0+VmINxkSdMU30NWaU35leR2NH8x78ZstTsuW9LbVTFIXlp5fghvPLcd15XA9Yj9MHxs8i0WxAokG667d5e9Ds4DJPdt7g+dFTHkCBJU9cJ0E3cMEYAMydlBO07Kw53IUyI8WsWiYjb9YEjbJ3+VKSUibjKiJLFuq80mFzY8+RtqDlpDPfCfkAACAASURBVDH0cAnGEkzyzOYFfOuHGqF6pTKI8nE0x6dZb0KC3owuDxe8MoHgAPiC0rNDbk/uY6S+sRf/vR93vbAZD7+yFTanD9YUM3KsieK5KimKYAwA5k/OgVFP49rzgvsmxf06pVj2OJIXpUbv0YKxfsDr96HO1iBbJp5EdV4w6UfF5ZlWA+7mJSoCLIsjDd149p970Ngq1weqaepBklnfqwmu0UwAbEzTQHqKO/mEmpTSCI0yGAuwAbxe+Xd4+DLh2ORC/HL+vX3yXheeVoLTpuWJjddCYJKkmCLTU3oxGF9aeDoATtPs9hk3YWrGJCwsWCAzJB8IJoxJDcq+mPgMhEHPKbOTJcIAy2IXoawuBGNddnXR2tll2WLf2B1/2IQ/K5r+AeAXr2zBH/+1D82dXPD16Xc12He0DTZiGnO4BGPK7A0ZTK28aArO4zNIJcT0pBLSZ/S4QgMyFGmmVHR5ukMahi/ImxNyW5NBh5I87uY6kusCqaoPQPSZFEgi/DjDBWPWFDNeuncJFlXkh1zHaNBhXH4Kv75JPC41+g8tGOsH3j/0MVbt+CMOtPEj9iyLDzdxvTKmyVuhS5ammyaOTQ5SNT5wvAO/fHWb2E/g9fnR1u1GUU6y1rgfArvXgSZHi+pzLMvGnBkz8hfmfW2VWkAWI96AvP9FKe46PWtyzP5+kVD29wg6Xsv4wMvP+uHlBWeNRG9YstGCWyqux4/LLunT/YmGBJMef75nsawcaSaCMUAeCH2z/yRe/VSaqBaCsXCN5ifbuSDL4WawvaolSMvMy09y7qhqgcvD4IMNx/D8+/tkdkLHTtji+HQDT6Rs0OVLx2P13Yvw0FWzQq43Ll/qtSrJV++7UpJmSoWTceHjo58HPXdxaeRS/An+b9TIuy+ooda+onRpIG9A+iJ4uvC0Epw5ewx+c33oAQiNvkMLxvqBva0HZP/anD6x4ZJOkP/ginJD64W18krQ//2O67PR6vaheXn/W3hs69NiuYBEaCinYzjcDTR319nqahcbwDUiE2ADeGrHn2TLvAF5+SWWv0O0hJIhEJry/axfVP836tRLVIOBXkfj3h/PFB8LfT9qwVhtk9zIXLDBEdoWTp+eByU3XyyXCDlwvAMAVxJ768tqcfkHG45h3e5G8TFDBGP/2iBl8ocLcyepB/tmoz6spU9KkhGvPbgMD18zGxeeGp1XYn4S1/u3qfE7+XvpTDglf27E7a//ATdpGS6AalexcVo0Q57ZMhMDLUZ9768V08dl4MqzJgZplWn0D1ohuB/ISLDC0eNEm4s78an5pInrpoc+0N0eBj4mgP9+WwMA2H04uLdDg+No93EAQKuzDWkm+R2tkNmKRdTToJN+Gj3e0WMp01vUsojKzNi0rMl9/r7KWEyYBhOU0v0BP1w+7oJmpIdOMAYAxblSD6igDaUMxj7adAxrdzXKtnN5GNhdPtHw+gxiQlNgWqlckuD4SRsWVeTjzc+rsKNaXvb613op6CKDsTSiv+pgTQf2HWvHZUvGhdXhGgzIvriVF0dv5K3GuCizYgCwsGAB1tRvFB9fPvFiTM2YhDRTalQTunMnZeODtAR4Q2hPAsDJtuCs2VhF73BDi7SO5hwy/NCCsX7AzI/Od7g5YT0mjBSFmj+f+JwvEGQkrBGeHl/wSYthuZOcPhaFdXLSTqsMRw15EWC9JlBGj9grJpCXFNy43luUXoTK382Ghm/R4uJuZgqSgzNIg4meKLEKMiCCebWPCaCt26WquL52VyMO1nais4fLuqvZ1SSY9MhO5yQPAC4YA4AWlUwLiRAEGg002onS5uqPDsDhZjBhTBpmTRxavrikAkd/qcWrobz5WzLmtJhfQ6ejwHhCXydOtHPnNb2OEo91pXr+ufOLxGGMUN6cGkOXoXVrM0IQgrAOTxeYAIMOdyd0WfU4vSL4IuD2S82388rlqfUn/rYTWyqbxMdjsgbXyHQ44FAJxsTMGBX9vQdN0bh+yk9k22tEhsxOlGdx4qVdHqnnaHZ2Rb+8L6NoMp80ljPz/vYE51+5u3U/Gu0nkZuUo2p/NZjoiLKZNZkLqIQyk48J4OVPvg+5rdATBsgbuEmeuGkBbl0+FenJJtEuKdJ0nNAnlpueiHabB//55jhsDq/oe9jeHb+PZn8hZPOeuTX2YKg3GPtg8MOgo2F3+VDJl5GVCJmxBZMlORRlKXJiYRp+de0cLKrIx8wJmdAYXmjBWD8g9MgE2AC6PDa88P3zMJZUwksH9zPZiRLYJYvHBT3/7toj4v/vvWJm0PMacuxetcwYdwGJJTNGri9k1jQiQ2bGZuRyo/OtTqm8bjWn98v7MkRa5I7LpuOyMzhZh3Kr3DLJahp6HnhkFkdoxhfKlF4mgPqW6MrkoYZ7aJrC7LJsGPW06IPojTAhKWiYCaKgH246jr98UikmibtjFCntbxh/AI18wDIYE+cXlHDyFYsKTo1re+Fv98w/g10XAKCJz4yR3sXZKv7ExbkpuPa8SWH74jSGJtpfrB8gS4+CGjMAsLQXLAuwAQrzDcsBAN0eqSk3Oy0B91wxQ2zoJLl1+bQgtWiNYNTKlFJmLNZgjMseqGkHaahDOhYUJXM9TCccJ8Vl5xYv65f3Ffpn5pVno2J8pigZccUk+ZTkQAq7xsKSGfmiDRIg2fK4vAw8PvnNQKjm9EjodJxcRiDAopnQEfv1dXPxuxULVLcxEPZAB2s7xVC7rTt8mTNaukPIcsSKcrJwoFlSuBC3TL8Ol0+8KK7tO3rCZxpbOp0w6mlRB60o26IFXCMMrWcsAizLYlPjFpRZxyMnMXKPBMuysumxLU07xf+30kdAUYDflo48aw7QxYlRkkwptqpaY6hZv2gEY1dptheCqVgzY0LwppUpoydAeHlmJHDq4t/wpcKpGZNg7qdgKC8jCc/ddhqSE+U3LErz74G0PIqFa86VC3AKQVBXT3CwcuGpxThtWh6ef3+vuMwYRtZBQEdT8AcCqG3uEScxBdSyLACwYHIOvj3QFLS8tav3ZcpD9V148p1duGRRaViB1mgQBG9nlw1OH1uC3oypmer+k9FADkww/kBQoNXW5UJ6ihmzy7Jw7XmTBu1zavQfWmgdgeO2Ovzz0Id4YttzUa3vYtwy0cvdLZJJbytbw/2HpZFhscBA64OCMYAbry7MlvupkcrQGsEIGmL2MA38sfSMAYCB5npBlNIMGqERMmMzs6aJgywCun4OhFItJlXNLYqYwLho3Ln9ug99hZGwdwp6zkBjcrG83PvU7adHfE0dTcHvZ8Um/lxrIjJSTMhJT1QtcZ5/ylhMLc3An+9ZHPTc8ZM2fLjxWNDyWDhYy/XW/ruXrwNIwrczxg/PXqkbz5cmjJUiu59sPo5uuxfpFiNoisKiivwgUWON4Y8WjEVA8BxjAoyspKjkWHcNjnXXYmfL3pDr+Gn+bpKlYDbqkWJMlgVjXr8Pv9nyNNbWbcSj188TT8hJZj2y00LrkWlIqAVjHn5IwqyPrZdEKGm5QyhrawQj9IxRFBWUhRqsoVQhI7qs8PSgybehipAZe+frQwC4DJWA0aCTZU5u+X9TUVoQ+XNxmTEWTr4J/8ozJ+Cpn50m6luVFUr9dD+/dDou5XtYlWKqQo/bf3jJnXgh/Q97nL3rQROCsbRhamg9c2KWqHgvSJUIfLSZk+1R2j1pjCy0YCwCfqJfqMF+QnWddfWb8czO1Xhm54t4t/rfoClaVP5WhaWRa00UgzEhk3awoxrNzhZ8cOS//HtzF7ZFM/I15X2CdlcH/nX4E/j80qCE8B022k+i3dUpW1+wKVFmaiKRaOACYCfTN/0xowHh70CphF5qywYCE/93H07aS2SvFiAXfFYGR9F+q0IwJhiImxUTlXf/aAaevPkU3Hl5BWaEmMY7d14RMlKl35G7F2bkpF0m6SwQD128fVOqZfj21R7lJ1jf+rIahxu6gp4nm/c1Rh5aMBYBHzFJV915WHWdhh55kJZqTEF2Yuh0eWmRCdYUM1JNKQiwATGb8/L+t2TrCTIBSv+60YLP78MJe3C/yl8P/A3r6jfjs5r/AQAOdcoVwn/13e9kj4XMVqzN2wl6LRiLFaFMqWo9NUg3FLdUXIdxqSU4syi43DZUUWbCSfkLIVC76YLJyLUmYto4ubBrKITXcPD9VWZFH6pBTyM7LQHTVV5vXAGXtVkwJUfW3/bwK1tDmpBHgizHnVARNY0FQVduOJfvSDmKDXuCb/zPnls4kLujMcBowVgEyEm6NXUbg55nWRZbmnbIlpn1prA+iB0eTksmw8w1OLe71LVlhHNcrAKGR7qO46/73x725bXXKv+Ox7c9i+PddbLlQtlRkEx4Yc8rYV9HzIzFGIwZaQNoiobLN7y/x/6CZVk4fU7YvQ5savwOTICRlSmV0IOUGStOKcLds28ZNiVKQLI4EiCFYYUS5SlTc/HEigVhPRnlr8Ftt3EvN92aoSISG4pbLp6Kx26Yh6KcZEwptuKceVxg0NnjQbc9vhKj0yP1YrZ1u/Hltrowa4fHy0+cmgzD95J288VTxEEtUp6jICsJlgRD0HCKxshi+B65A0SkSTpB1ZvERBtRZC5VWZtDmDJLMnAaPpEyL7FKWrx24B3sbt2P/6kEj8OJfW2VAOTyIABgMXDDDT2+0OPsLc42vLD7FXx89HPU2uoBxJ4ZoygKifqEqDNjZLl0NPDWwX/ivk2/xrO7VuPd6g9xx/pfiFkS1TKlVmqPGmV/0Pc1nfjF1bNx6/Kpcb8mKYmho6mYepCsKWYUZElDRQunS76IT76zU20THDjeDoc79PBLc4f8d/VPQlMxVoRgLJqp0qGKQa/DPT/itCQ//a5WnLD0eP19YvytMbTRgrEICIKhodjfFqyObbMH8MjL+0EFeJPiLmkMOc2UipXTfwpAytS8UfkPbGvaJa4jSCpceeYE5FoTY9YV6vZyvQdNzpaYthuqmBSN94IP5bHuWty69n7VbR7d8ntUdR7GV7Xr8O3J7QBi7xkDuADOHWUw9t6hj3H7ugdHjZelcMw2OyWPwwBf1lcLvIz08C0hDQbkV5iXkYjxBamYXRafxhjAlRgF/GEs2qKhIDNJLKW2drll0gwA0NjmwLP/3ItfvbpNdfsAy6K6rhOpFiNuv2QaAGDimPgzlx4mAJqihn1LB2lx1NjqwIY9jWjrdqtaXWmMLLRgLAx2t1tWojLqgjNU9T2NQcs6WG6Z38ffedJSQHd+yVlIMXIlCCE4cDIuvPn9u+I6QlnyzDmFeGLFgrjT0+2u9ri2G2qEuojHmoUy62OfSE3QJ8AZZbl3U+N3AIAmx8gIgtVwMS5sbtwS5DcpsL7hGwAAzZ9afjRxOYqSCzA1oxznl549YPs5EiAnJn+0bEKfvl5f0OOSjgHBPknAzfdwdfZ4ZD1lnT0e7KhqQUe3GzanD2WFaZhSwlUKepPV8vr8MBroYZ99JUvHXXYP3vyiGgCimpbVGN5os7JheODbX4n/pykaXr8X/oAfOkI8NDMhdPMs6zUDJvmFnFSBV/Yw0RSNABuAL8CACTC9Fqg8YW8Cy7LD/gQVrv8uFuJRX08xJqOupwE7m/didk50voqxSmgMJ16v/Acq26tCaoZtaPgWgJQZWzTmFCwac8qA7d9IgvzVRtsXNpDcunwann6Xs+9pbLVjIiGNQdot9Th9SOVbLZ58Zydau9y49jxuCCApwQCDnoaOpsQpz3jw+gLDukQpkGDS4/Kl4/D+uqOy73Ae4UmpMTLRMmMh6HY6ZY+FLEwN338kIDST31pxA26tuAEAYHFy+jy+oxXwd2ZhadZ54vpkYKEsm5GZHtJAPF4Y1j8iBEvJ70WQs4iHeAyii5ILAACvVb4T9TabGrfE/D7Dhcr2KgBAlzt49J5kuN8ADAXI79Bk7JtTdV+aaE8utuLBn8wCAHQonAJICycv8X9BuX/3Ia60bdBx2awEkx5uT/xOF17GL+oyDncs/EQo+b3N7EV5WmN4MDKO3n6gprVZdfnqva8C4AKEVmc71tVvBgDkJGZhckYZnl70KNiGKQAA1psA7+HZYN1SECD0cwHhMyhupm8823oTvAwV/EQwFq5pPxLxZKyKUsZEtR7pyfjNia0xv89woJa4EQmVrcxP4u7gae3U0nv4WGzmhEzo6L75PtOTTbjmnDLcdOHkyCtH+XoA0GGTVwC8IYIxgb1HuRYKQU/LbNTBHqbZPxJeX2DENLkLGT6vzw+9jkJpfkqQ7pzGyEP7C4egriN4ShKQMlZ/3P0yfr1llbg83cyl6BP0CfAqzinHT9rwi3l3YVL6BMzLnSUuF4yU1bD3Iugge6y8AXlvD8uyqOo4jJMO9WBzqEAGN35C6y1cc7wQCPQlifrEqNZzKZr8R+JUpdMnfcZQmVsr/zvQMmO9x2LmSsF9Lfa5ZGYBTpnSN78VQUXf7pKXGL0+6fj/dEstPD6/qAVG0m7jjqNcayK67V7RYzJWPD4/jPqREoxxl+XjTT1g/OyIyfhphCdiU1Jrayuef/55VFVV4YMPPgAAdHV14ZlnnkFhYSFqampw9913IzOTE6z761//CrvdDpvNhtNOOw1nnHEGAODgwYN45513MGbMGLS3t+OBBx6AXq+Hx+PBqlWrkJOTg5qaGqxYsQIlJSX9+JGj42S3PBgbm1yI2p56FKcUAQAOd8n91MhMgUdxJ3jD+eXItiTi9pk3yZZTFIUMczra3XLFeECyYYqV/x77Ulaa9PKZMTfjxm+2PIWKrKnYyDeav7js93G9x0DgI/TdyMBGze4IABbkzcGVZZdie/NuvH3wvT7bDzIj0eJsRXYIs3ilx6jd5xAHNUYKpNF6qAb+Tk83AEDXR31+o5nrflCOjzYdx6KK/MgrDxJGgw4UAI+i34s8B26pbIbJoFP12RQsgIpyknHgeAfqm3tQXmyNaR8CLAsfExjWGmMkQmZs8z5ODy7HGt0NocbwJuLRu3PnTpxxxhmyTMWzzz6LU045BStWrMCZZ56JVau4DNHevXuxdetW3HnnnXjooYewatUq2Gw2sCyL++67D3fccQduvvlm6HQ6fPjhhwCAN998E3l5eVi5ciWuvfZaPPzww/30UWND2Ty/OIcLKgsswXeUheZx4v9Zlg1Ky2enh/4xjU1RV1XuijMY+7xmjezxK/vfAsuy+HvVB+j29oiB2FDGH/CjwS5NqZLBGBNC983j90JH64L+bosKetc8TuplPbfrJRztqlFdT+lb+veqD3r1vkMRslzsUZTRhe+90c5dQEwqk8casTG52IpfXD0bWUPYl5amKBiNOrgV5zwvI39c32LHnsPB1YYbeIPsohxOw6y2OfaKgI/Pwo2EBn4geFhjTozSRhrDk4jB2LnnnoukJHmafMOGDZg5kxOnmzVrFjZs2AAAWLduHWbMmAEAMBgMKC0txfbt21FfXw+3242srKygbdavXy++VllZGaqqqmC3D75O07ULzwDr576egCMFSTouy6Fm/ZFpny3+v9vhBcsCsyZm4drzJmHlRVPCvs9V5T/ED4rPDFrexWcYekuTswVf1KwJa2A+1Ph71Qd4Zudq8TEpvBvKX3BODn/cKYKxC0vP7dW+kMGYzduDZ3etVl1PmRmrscWvJj5UIcvFHkWZ8uczVsgeG2ktGBstmI3BWS+P4rE12SQGXAKLZ+QjkS/F5vA3rO222N0uhCzcSCnnsYprTPnY9EHaE42BJC7thPb2djFAs1gs6O7uBsMw6OjoQGmppDxvsVjQ0dEhW19Y3t7eHvRa5HMWi/yHqyQ9PRH6fu4RoHTcHZe/KwvJydzdqdGkA5sgvxC5HWb8Y+0RXLJ0PLZVc3d/0ydk4dIotYGuzb0U0wvL8OSmF1GWOQ7VbUfhoVzIyuqbMlebT73/Tfn6ffV+vUVpL5VoMYr7luyWN+FPsBbjoUW3IcmYyJV9GekzXFVxCYrysjAhowRTsifG9Xn9CcEeo2rbsR3yXpdx1qIh830K9HZ/krxSgLW7db/suenF4wFJtxjW1ORB//yD/f4DzWB93iSzAS4PI75/p82N7+vk07YBikKCwjdyyrhMcRsf32NI6+ioP4ew3r837QMApCSbR8Tf3EPEYunJJuRkc6XckfDZomU0fVaBuIKxjIwMOBwOpKSkwG63IzU1FXq9HlarFQ6H1NNjt9thtVrF9cnlGRkZstdSey4cnZ3OiOv0BvJgYBkDOvj3c7q8uO3TX8rW3VXNiXxu3nsCaRYjTEYd5pVlorVVni0JR6FhLJ5b/Ft4/T48sPlRdDvsMW0vQIEKyh65Per9PeTrZ2Ulx/V+/YGgtybQbXOK+9bVLe8Z08MIly0AF7hsKuOUMlk+F4u2NjvurLgFQHyfVwczfjr5Cpkor9p2a49w+lrLx5+PD498ikQqach8n0Df/H07ukJnrHs6vbhj5kr8YfdfAABeFzuon38oHc8DwWB+Xr2OgtPNiO9/1wub0e2Qn3P2HW6FNVmu8+dweMRtHHbuBre7xx3V5xA+b0unE//9hnPkGJc3Mv7mJgr4xdWzoaMpZKSa0draM6qO55H8WcMFmXHldRcvXozdu3cDAHbt2oXFixcDAJYuXYo9ezgRQIZhcPToUcydOxeFhYUwm81obW0N2mbJkiXia1VXV2PSpEkRs2IDDktBqJS5/aHT6C4PA5eHQUqiAWZj7HGuUWeEQcdrzMSpD2YxJCEnMQunE71SoZqthyrK5m+yPKYsEyt7k8gJ1XB/q1ggJ2C5fQielKy3nwAAZPGZNLWhjOHMwY5D2NPCZcMmpo0Lep6maGQnSllEk06zPhotmI16eHx+8bdJBmI/+39TMakoDYyfRUuXYuKYsGQS+qTUmvzD0eOUzpPFuSMnmzK+IBUleSlI0czBRw0RI4Zt27bh448/RmtrK1avXo3rr78ed999N55++mnU1NSgvr4eDzzwAACgoqIC8+fPx7PPPovu7m48+OCDSEnhUqxPPfUUnnvuOeTn58Pv92P58uUAgGuuuQarVq3C6tWrUVdXh8cff7wfP26csJQ4qt3ulNLv/q4sMCeIsmyCAW6vP277IkDqeYpHH8wf8KPHZ4fL78by8eejydGMw13H+kyzbKDQUTr4oD5NqQyETArhXHKqtS89IjPNVrS5OwBwwW0oNf9y60RYzelDXjokVv6056/i/xMM6g3l5PSomnWYxsjEzOt7ebz+IPPxSWPTkZWWgEff4PxhM1PNaOvmbpIYf3AwpqZJFg7SE3MoDzpoaEQiYjA2b948zJs3T7bMbDbjt7/9rer6N954o+ry8vJyPPHEE0HLzWYzHnnkkWj2dcApTilCja0OAUcaPvuuHigCTnZ3AgaAZfTwHpodtI3H6xdPTvFAUzT0tF6WGXvv0EdodbVj5bSfhrVI+hMvSMsEGJh0RszPm4PDXcfEYYAfl12Cf1T/W1x/qFolkZZRgCIYQ/jMGAAk6hPgZFyyjFpvmZwxCRsbuVJkra0ek6zyfsDcxGzYfQ4YdQbkJ+XgQHsV7F4HLMa+1YgaCpDfOU3RuGvWzeL/BUhpEo2RjRiM+eTB2LTSDFgSDHAQ2mEJJj0yUkxot3lk50mapmDQ00GyQJFwuKXjrK+9NzU0BhLt6A3DLRXXYVHi5WCdKWjp5FLsAT1/V3eCK9VkE3djdpcPLP9vb0jUJ8DutWNvayVe3vcmNjR8i+/bq/GFQraCxOf34VDnEQDAafnzAUjlvk4Pl82bniWf7OzLYKUvIb0/AU7OQsgUsorMmMUYXNIWtg8lgxEPl0y4AGkmzqy3U8UKyBfwwcCL7ebx4rMnHU199v5DCVJdf3rmZJSmFouPH5j7c8zOrsDUjEmDsGcag4GQ1RImKMdkcTcgKy7iZCtIyYmWThceumo2zp1fhHmTc4JeJ5oyZWOrHTc8/jXqmnvg4FX7f3LWxN5/EA2NQUQLxsJgMSQhx8QJLvoYLiNDUdy/rI/LDmSkBperTrb3brggLykH7e5OvLz/TextqxSXf16zBl/UrFXdhrQJumzCRQDkmYrMhIwgEVLfEPWtVGbG/nv8S9y54WF4/F5x7PusoiWYnzsbZxSeHrT9gtw5AICJ6cG9TfFioPW4bsqVAIAGvj+MxBvwwaDjsgJC71Srq6PP3n8oQYq/JhnkGnpFyWNw/dSfaGXKUYRgQyQEUg43g/RkE5L46UnSysfj88OaYsYPl44P0tNKMOngdEfOqL679ghaOpx44/MqdNm5/rRMlfOwhsZwQgvGIiCmvll5OY9luIvNWXOCRVt7q3eTE0LlHQD+c+wLVRV60qpG6Dsjg7FEPZfBe3HZ7zE2mdvn3S0HerWf/YXSWkhgb+sBBMBlxsZY8nDN5B/BrNK7ddG4c/HwvLsxO7uiT/drbEohDLQehzqPBj3n8zNiZizDzCmIt7tHZjBGDklkJkSefNYY2QjnyLrmHnh8fnT2eJBLqMZbEgw4YzZ3zFx9dugMVlZaArod3oilSsGCqaPHgw83ck4oBVkjrx1AY3ShBWMR0Ov5IEwZjPGZsZK8ZCybVYDxY1LF5x65bm6v3jNSeW1f6/fB27DSHaXQB0ZOJXYTIrKlqWMBAO9Uvd+r/ewvxiSr279UtleJE1tUGLsdmqKRb8nt8344A61HVkImTqiUH30Bn+gJmmbihlZscbooDHWmZUkm01owprFpL5cpfv3zKuznDcBz0uXN9D85ayJee3AZls4K7ccr9JtFCsYyUrgbMBsxtSks09AYrmjBWAQMYlOo4sLOZ8YSzQZcdXYZLl0kTVXmZfTuLq3VpS7SKlDf0xC0TC2AIzNjNmKycPn488X/O339q9cWD8KEZJLCpNvr94nN/PQgeR8KgdhhIjsWYAPws34xM6bjM5OCfdDXtevxxLbnZE4Cw5UCS55MXT9LC8ZGPTPGS5Imqz/isu3x+CkKRt+Rp3ANswAAIABJREFUJiqV91gUNGN6jeGPFoxFQByXVmTG/u/HC/HAlTPFfoi+9EXLSAhvlNupYpXE8NNr55ecJS6jid4rMktGNsgfH4K2PUKz/q0zbpAtD7B+cRiBHuST7+5WqcS75eROABA14oR9E7J4Hx39DI32k3h5/1sDvJd9DwUKRkJDTMuMafxw2figZTlh/HhD4eNlKt78vCrseoLMkMBVYUqfGhrDBS0Yi0BRTjJOnZoLgIK/U+rlKslLRVmR5Bnm96t7JsbDZRMuRH6SZEhuVEgJ2FX0s4SmclL6gpw8ZEJMTg7FAMEX8IGmaDHTJOBnA1hTtxHA4GXGBIQS5ElHs1juFYYLhH1jIb9oHGg/CDfTN0K0AwnplUdB/t2H0lvTGD0kJxoxriBFtizHGrvml4/PiFXWSILJ3+w/iX186VNcj5H/rkaKQbjG6EYLxqJg4bQ8AADTPDbkOoU5FhRkJuHKM6PzowxHgj4Bs3njawB46vRf44KSc7Bi2k+RbEhCj0oD/4dHPgUg13ciFdFDwQxBPSgv33+lVOJvdUknZUpZNh5gDrQfBAC8c/Bf4rLFY04FAFD8z8qvotQ/HPW3SHutC0rPGcQ90RiqPHz1HPxggXR+jEeAlcywvbf2CFiWxaufHsTz7++VracsY+Znas37GsOfuLwpRxsl+fxdXyD0HZjJoMNjN87vs/eclzsT25t348dll0BP63FeyRkAgJf3vwkAqOo4jKyEDGQkWGWiqBPSSsT/Zydm4eyxS/FV7bqg17+ibDnerf4QwNALEHx+Hww6g6zMCgBtRDCm1CIbaHwBBhsbvsVxW624bGpmOQCpJCxkJq3mdHTw9kjeOJwVBhuh163cOlH8jJdPvFjWO6ahcdmScTAZaJiN+rgEWPMyknDXDyvw3Ht78cW2OqQly9012rvdSEkywvv/27vz+KbLbPHjn+xd6Ua6tyltKVBAFilCUTYFUVAujs51vSr60nG8uOAPR2deMsodFAa96gijd4ArLuOCXuswgrjgggtSgcoygJQiWNsC3Uv3Zvn9EZImTVpKt2+TnvdfafJNeQ5J09NnOafNzNiQOPdZOSF8kSRjnWDQabhuehrv5ub12b8ZGRDBYxc95HG/o7r8Cz+sBeDJKY85i4tmRKSTEeG+fyPUS1FUgEsSJrP9lx0U150k7/Q+4mOm9XAEXddoaSJQE9DhUqRWpUwylhpm4li1PQF7+8j7zvtda6O13TMWogtyJmP9tbZbRxzFgV1nKqcnTlFqOKIfu2rKkHNf1IHRqa17EN/alu+8va+gjOfe2Ud4iB5TTGu9xIg2CZsQvkqWKTtp+rgEbM3K/+A/kvWA29fVTdVUn92/5Dor5mRrfy/b9CT7L9SCqp96boA9oNHcSIDWgEbd/ttTqZmx+8fd7fX+lZe0tvRylN1wzFi6nnT1zWTMHkfbYrxC9JXn3tkHQFVtM3sLytHrNMydbOLhG8YpPDIheoYkY52kVqvAbKD5p0yaDk489xN6SVRghNvXjZZG8kr3A96LxSYPshd4nZqQ7fHYhJhxDA6M4uvinZTWlXs8rgSrzUqztQWDxtDhL3+lEgOtWkuYSyeDC6PH8IeJi902sjtm9A6UH+LNH9+j0dLaqL2/tqDqiNLlRIRoKz0xjF9NS+tSCQ0h+iP5dO0kx9KTpTSZa7OUS8bAvoTpsP7A39lfZi8C66jP5So9fAhLJy3huoyrPR4zaPSMM44GoKqxfxQobTTbE5cAbcfLlDZ67vTq+YoNbu2pd9OI64gPiXV73HXcXxd951yiBLBYPTf193fOZUqF9+mJgcHR07IjKbJPTPgZScY6SaNuPb3n6MWmlD9OWsLDExYBuLVGSvO2TIl9xqy9xMZRCuO5b9f18Ci7ptFiL/0QoAnwOE3pyurlpGJfWTjyJgCuTLkMg5cejOoOTnpafXBmzLGBX5YpRV+YlBnLkuvHdniNSZIx4WckGesktVrFpeMTSRgczIUZ7feO7AtatRbToCQywlsbYf8qfV6Xaj45+liW1ldwsu5Ut8fWYmlhR8muLlebd8yMBWoNHqcpXSlZzT5EH8yamX9mbupsr493NKPnrdxFf9e6Z0w+LkTfCA32flL3gjT7Bv/UhDCvjwvhq+Q05Xm4qZ9VetZqWl++hBDv/RzPxXUJ7ZczxcQGx1DeUEGTpdlj+a0zNh3bymeFX/H6oY2suuQJgnTnV2/Isb/Kvmes/V/+CSFx5z22vuKtNUtSSDyFtcU+umfMPmbZMyb6imtvS61Gjflsdf7brxzBqYp6hiVHUFbmWfxaCF8ln64+TO3y8oUZujZt/0ttifO2xWbFZrOxdMcKluf+d5e+38m6087b/zy29byf76hQ396esYyIdF6YsYIgne9s3P2PEf/OhFj7qa+/7v1fRZdYu8I5MyZ7xkQf0Wk13HbFcABGp7a2hwsL1pORFC69KIXfkWTMh/1Y2VqHpzPV9r35zQW3OW+bbWZ+dmlC3pWkIVjXWg27orHKefvdI5v4qui7cz7/yNkG3AFag9cP3GmJ2T4xQ5MWZt+/Ny76Ai6Ku9Btv1Vlo2dv0f5M9owJJVw8Oo7fzB/JHXMzmTgi2qPlkhD+pP//VhPt0qjsy5TTE6d0OUEJ1YewcOSNgP2k3/6yQ87HmizN5/39gl2WJR3J3OeFX/P5L1/z1o/vnfP5n/z8hf3fNjd5fTxYe/5tVpRw5ZDLSAqJ59KkqYD7fqvTDaVKDatLLFLaQihArVYxcUQMQQFafjN/FH+4ZYLSQxKi18inqw+7Z8ztZISnMcs0vVvfxzHj8faRHEobypz3N1m8J0Qdcd2g7kjGHM29z0d7PTN9ZXlyeORQHpn4AEPCkgH3RGb1D+s446XZe3/VWoFfZsaEEKI3SDLmw9LDh3D/+LsJN3TvZJHrXqB/lf/ovN2VJuKuCVyL1UxtSx2VTa3LlYfKj3Tq+8S1c3igvfZO/d3wSPcG8tt/+VahkZw/q5d2SEIIIXqOfLoKt+XIBnOD87a5C+UjXL9XWUM5P5ze7/b46r0d1zMLPLsMOT76Arf7Q3X2JCzEZU+aLxkcGMVNw69zfr3l+KcKjub8OArVygZ+IYToHVLaQhAZEO71/i7NjLns9apurqG4Te0yvZciqa40KjUxQdEe9y+dtIRma7NP71ty/X92rRHnzY7i79GqtWTFKt97zyKlLYQQolfJp6sgNSyF5Zc97HG/a00sm83G64fe4Z/HPvK47lj1CY5UHgWg2eq+6f/LX74hUBvIs9P+RHxwLM2WZgrPFFHpctLSZrNxuCKf6qYaalvq3JbDLk2ayqzk6QTpAru9HKs0Y2Driddfaou9XmO1WcmvLOD1w++w4eCbHjOLvaHwTBE7S3a3+7g0ChdCiN4lM2MCgKFRnq2UXJcp68z17Cj5HrCXOgjQBjAnZSYAz+xeA8Bfpj/l9QRmg7kBvUbvbL204vvnAbgt8wayYsfxdfFOt5OWxXUnnbevGTqvu6H1G1GBEcxPu4J/FHxIvbmB0/VlbiVJLFYLaw+85uw1CrD2wGusmfnnXh2X4/XIiEgjwsssqWzgF0KI3iUzY8JpSvxFRAcOZnriFMB9mbLZJcn65Ocv+Oexrew5vQ+brbVh94kzv1Df0rrnrK22Jwg3HHyTRnMjO0t29VQI/d5s0wxGRNo7ObieXAXYX3bQLREDe+X+vlLV5L1ZvE1KWwghRK+ST1fhdOPwX/HHyQ8TprcXVzS7LFM2W1o8rl9/4HV2ntzt9nVlUxUZ4WlMiPFs9Hum+YzHfaUNFfxU87Pbfbdn3tDlGHxBVox9H5hrKyqACpdTpw4hbU6PNpgbKWso75VxPb17tdeen9azCbdUPRdCiN4hyZjwoD17as51ZqzF6pmMAXx0/DPn7aome2X5WzJ/TZC2tR7YlPiLALguY77H8+tb6t2+TgiJc7YO8leRARGAe4cC8F7o1mw102xpcTZQX7VrNX/csdLt1GtPqvfyfa3OmTFJxoQQojdIMiY8aM7u7XLsFbLarM59RW2dbrPUBvZkIzt+IunhQ3hw/D38e8a/AXBxwiQenrDI7dq2s2WOivX+rDUZq6TJ0kzD2X6cDZZGj2vzq47x4Jd/4KHtjwFwqt7e+/Oxb1dwoqbQ+dye4m3PnxX7zJhaPi6EEKJXyKer8OCYGWu2NFPeUEm1y16ii2Iv7PC5lybbk6mk0HgeHH8P6eFD3OpTmQYlOfdMgWcylzwosdvj7+/CDYNQq9QUVB3nsW+e5P9tXwq0NklvT4vLTGWDuYE/73qBNw6/2+3xRLuc8mzbdeGzwq94/dBGQPaMCSFEb5FPV+FBe7bn5eeFX7N0x1N86VIt/lzJ2OzkGef8/r92Wa48XW9PxrJixrNkwn8SFxzTlSH7FI1ag9VmpbKpijqzfZnWarOec5bLkRS52nN6X7fHo3ZJltuO4f/y/+m8LXvGhBCid0gyJjw4ZrIctbAczbsBZ69FgPvG3uXx3OBO9I6MDjLywLi7gdaZsZggIymDkjt6ml+ZmjDZ7etFnz/iTKzmDbmcm4dfxwPjfuN2za5TP3h8n+7WXmu2NFPXXOf8+tk9L9Li5bAGgBpJxoQQojdInTHhIUBj8Hr/A+PuRq/Rc9fo/yBIG4jRpUaWQ2dnTxwNvx0zYyF632xz1FVZsePZXrTD62NzUmY6/x9Xz1jJy/96g92n93q91rUwb1d8VfQdZ1rcS478fKaItPAUj2tVskwphBC9QpIx4SEjIt3r/alhKQCMMY4C7JXzk0ITiA+OZUbSJc6G0p0RqA0AWnthhulDuzFi36NT69p9zDWhValUBGi9J8fQtf6hrhz7AW/NvJ5XDr4FwMm6U16TMdkzJoQQvUOSMeFBr/GeKLRtFK1SqXgk6/4u/RvBbRp+p4QNnCVKAIutdTP+vCGX88FP9jZTjkbprsYaR3O44ihDI1JJDTORFjaEb0ty+bHiKKfrS7s1juazJUsSQ+L57Zg7+Ove9bzx4/8x2pjJoDYJsuwZE0KI3iHJmOgUnbpn3yoGjZ5AbSAN5gYGB0Z5/OL3d/HBsYQbwpiWkM3slBnEh8SSc/QD7hh1s8e1mVHDWJb9iNt916TP45ndf3UrzNtWUW0JVpuNpND2q/g7OivoNXoyIlqbl5fUniIo3D0xlD1jQgjRO2TdQXg1P+0KwP5LH+DKlFk9/m84ErAIH28A3hV6jZ7lU/7A7BT76dMxxpE8Pvl3JIUmdPp7aNVarDZruxvun8x9lhXfP+f1sdoW+6Z9x8yYXqNDp9Zy/bBrANhbdoDyNh0CZJlSCCF6h8yMCa9mJU9nRuLFaNVaxkWPdhYq7UmOeZaO9k+J9plCEzlSeZTdp/cyKW5Cu9e9kLeWZbMXO79+68ccvirawSNZD1DbXIsKlXN5NPDs4Y0vf/nWraQJgA0bQgghep78qSu8UqlU6DQ6VCpVryRiAI1nC4wG6Tz3SYlzGz04E4BT59g3drgyn9om+0yYzWbjq7OnOItrS8ivOoZGrXEuQ482jmz3+3jrWymEEKL7JBkTitE52y5ZFR6Jb3IctCiqLeF/9r3C07vWkF9ZAODRu7Kiwd4H07XdUUH1T/YbttYZL4NG77Y/0BSa5Lzt2gFACCFEz5FkTChmQfpcAGYkXqzwSHyTI2n6V/lh9pX9i59qTvBc3v+Qe3IPv5wpdrv244LtgL0fpoOjiGzbxuyPXbQEgLlDZvFw1iJuzbyecEOY2wZ/IYQQPUf2jAnFjDGOYs3MPys9DJ+lbWevnaNeGEBsUDQn60/z8dHtzIydzvLc/3Y+5pglm9SmxVVUYITb6zIxdjwTY8f35NCFEEK4kJkxIXxUZ8qNJITEOW9v+ekTr9fEu1wjhBCi70kyJoSPCtIFEaILJjNqWLvXxIfEOm97a7+UHTexU/1EhRBC9B5ZphTCR+nUWv4r+1F0ah27T/3Aywff9LgmzBDG1IRsthe1lqlYefEf+e7kLiIMYVwYM7YvhyyEEMILScaE8GF6jR6wb8LPK93PD6UHAFg8/rcUVP/EOONojlUdd3tOkC6Qy5Kn9fVQhRBCtEOWKYXwE9nxEwH4dca/kRaewmzTDAK0BhJd2iFdmjRVKukLIUQ/IzNjQviJkVHDeXLKYwzSh7jdf3H8RVRZK6iqrXW2uRJCCNF/SDImhB8JM3g2XNeoNdx54Q2Ulp5RYERCCCHORdYrhBBCCCEUJMmYEEIIIYSCJBkTQgghhFCQJGNCCCGEEAqSZEwIIYQQQkGSjAkhhBBCKKhbpS3WrVtHUVERERERnDhxguXLl9PY2MgzzzxDUlISx48fZ/HixQwePNh5fW1tLTU1NUyZMoVLL70UgEOHDvH3v/+dxMREysvL+d3vfodWK1U3hBBCCOH/upzxlJaW8re//Y3vvvsOtVrNPffcw8cff8yuXbuYPHkyV155JZ999hkrV65k1apV7N27l507d7J27VpaWlqYO3cuWVlZhIaGsmTJEl5++WWMRiMrVqwgJyeH6667rifjFEIIIYTol7q8TBkYGIhOp6O2thaA+vp6hg4dypdffsm4ceMAGD9+PF9++SUAn3/+OWPH2psS63Q6UlNT+f777yksLKSxsRGj0ejxHCGEEEIIf9flmbGQkBCWLFnCgw8+iNFoJDY2luTkZMrLywkODnZeU11djdlspqKigtTUVLfnV1RUuF3vuL+8vPyc/35ERBBaraarw+8Uo9Gzmrk/k3j9m8Tr3yRe/zaQ4h1IsTp0ORk7dOgQ69evJycnB61Wy4oVK1izZg1RUVHU1dUxaNAgamtrCQsLQ6vVEhkZSV1dnfP5tbW1REZGOq93vT8qKuqc/35lZX1Xh94pRmPogGofI/H6N4nXv0m8/m0gxevPsXaUZHY5GTt16hTh4eHOjfZGo5GSkhKmTZtGXl4ecXFx7Nmzh2nTpgEwY8YMVq9eDYDZbKagoMC5ZywgIIDS0lKMRqPbc7oaVE8ZaNm5xOvfJF7/JvH6t4EU70CK1UFls9lsXXmixWLhT3/6EwaDgdDQUPLz8/n973+PXq/n6aefJj4+nsLCQh566CG305Q1NTVUV1czdepUt9OUr732GvHx8VRXV8tpSiGEEEIMGF1OxoQQQgghRPdJ0VchhBBCCAVJMiaEEEIIoSBJxoQQQgghFCTJmBBCCCGEgiQZE0IIIYRQkCRjQgghRD9htVqVHoJQwIBOxjrTdkn4roqKCqWH0KeKioqUHkKfOXXqlNJD6FMFBQVunUr8XUFBAbt37x4wicmPP/7IE088QX19PWq1//9aLi4uVnoI/Y7m8ccff1zpQfS1uro6PvzwQ3JycigoKAAgLi4Om82GSqVSeHQ9r7GxkSeffBKr1cqQIUOwWCx+/QPf2NjIli1beO211zh69ChGo5GIiAilh9Vr6uvr+eSTT1i7di0HDhwAIDk5WeFR9Z7333+fpUuXEhMTQ2pqKlar1S9/bgFqamp4/vnnefXVV8nKyupUqzhf1tDQwLZt29i0aRNxcXHExMSg1+uVHlavqampYfXq1WzcuBGVSsWIESOIjIxUeli9pq6ujo8++ogNGzaQl5eHWq3268+q8+G/v5E78OGHH6JWq1m0aBEqlYr169dz7NgxVCoV/lgD98iRI5SUlLBixQoANBqNX8YJcODAAZYtW0ZCQgIPPPAAe/bs4dChQ0oPq9fk5+fz2GOPERkZybJly6iqqnLOGvnba+yYJbFYLIwcOZKtW7dSV1eHWq32u1gBDh8+zF133UVaWhpvvfUWJpPJ72eKdu3aRUREBMuWLSM9PR2tVovZbAb87/38zTffMGfOHKKjo3nhhRcYOnSoXydiTU1NrFu3Dr1ez9KlS7FarVRVVSk9rH5jwCVjVquVLVu2MHToUIxGI/PmzSM5OZn169cD+NVf2I4Pr5qaGpYvX05ERAQvvvgi4L/7EsLCwkhMTGT8+PEkJSUxYcIEjhw5ovSwek1iYiKRkZFMmjSJ6OhoBg0ahEajoa6uzu/ey47Z3PLycrKysggODuaDDz6gsrLSr2J1SElJYeLEiYwZM4Z33nmHF198kccff5wtW7YoPbQeZ7PZsNlsbNu2DZVKxebNm3n//fdZtWoVa9euBfzrsxlg7NixLFy4kFtuuYXw8HBsNhvbt29Xeli96h//+Acmk4no6GhCQ0MpLCyksLBQ6WH1C36/TFlYWMjWrVtJSUlBr9ejUqk4evQon376KVdccQXBwcEEBASwZ88eMjIyfH45yzVeg8EAQFRUFGFhYcTExPDMM8+wYMECgoOD/WJ5xxGvyWTCYDAQEBDAyJEjCQgIAKC0tJT09HSSkpKoqKggMDBQ4RF3T9v3s06nY+zYsRgMBnbt2sWePXtobm7m3XffJTIyksTERKWH3GVt38sWiwWLxUJJSQlXXXUVx48fJycnh8rKSiZPnuzz2wzavraOWaGcnBwWLFjA7NmzKSws5JtvvsFkMmE0GpUecre0fX1VKhVFRUW8/PLL3HTTTcyZMweATZs2ER8f79PvZfB8ffV6PaNGjUKj0WC1WiktLcVkMhEbG+vz72Xw/n4uLy9n8+bNfPHFFwQGBqLRaHjllVcYPHgwJpNJ6SEryq+TsebmZp5//nny8vLQ6XQMHz4cAKPRyPvvv09sbCwpKSlYLBYOHjzIJZdcQlBQkMKj7rr24nXsuTCZTOzfv5+8vDxmzJhBfX29T+/H8BavVqt1JqEAH330EfPmzePEiRNs27aNMWPGKDji7mnv9XXEO2jQIObOneucDRw0aBDp6elKDrnLvMWqVqvRaDS8+eab1NTUUFRUREBAAEFBQcTFxfn0H1LtvbYmk4mkpCRSUlIA+2dXXl4eF110kV/GGx4ezosvvkhmZibDhg3DaDRSWFhIWloa8fHxCo+669qLV6PRAPZZv507d3L06FGysrJ8PhFrL97JkyeTlpZGeXk5ixcvJisri5KSEkJCQhg6dKjCo1aWXy9TtrS0MGzYMLKzs/nhhx+c06Emk4kFCxbw1FNP0dzcTFlZGRaLxed/ANqL13VJ8qGHHmLjxo08+uijPn+a9Fzx1tXVcebMGbZt28bSpUvR6/U+ve+kvXgdMTU0NACwf/9+jh07RmpqqmJj7a72Yq2srCQ2NpbBgwfz4IMPkp6eztatW9m1a5dfvrYA6enpnDhxArCfIq2rq/PpPxqh/XgTEhK49957WbNmDWDfE1lSUkJ0dLSSw+22jn52He/bmTNnEhQU5BdbSDp6PxcUFJCTkwNAXl4e+fn5Pv1Z1VP8amasoKCAjRs3otfrCQkJITg4mMzMTAICAti3bx/V1dWMHTsWjUbDBRdcQGVlJbt37+bnn39m4cKFPjft39l4HQcTmpub2bNnDyEhIdxxxx3Ov7Z9xfnEC7B9+3b+8pe/EBUVxW9/+1umTZvmUwn3+cTb2NhITk4Ob7/9NiEhIdx4440+9fp2NtbAwEAyMjIYNmwY9fX1lJWVcdddd5Gdne2Xry3Yf2Fv2LCBd955h6CgIG666SZiY2MVjuD8dDZetVrNuHHjKC4uJjc3l1OnTnHnnXf63KzY+fzsOt63O3fudJtF8iXn836Ojo7m8OHDfP7551gsFhYuXDjglygBVDZf/nMSnGvrb7zxBrW1tSQmJvL999/T0NDgPD0I8Oqrr5Kfn89tt91GWlqa836z2YxWq1Vi6F3SnXjNZjO1tbWEh4crNfzz1p14d+/ezcmTJ5k7d65Swz9v3Yn3+PHjVFRUMH78eKWGf17ON9Zbb73VbdnV1/bVdOe1LSkp4fTp0z61zN6deK1WKy0tLW5bDvq77v4u8jXd+fltaGigrKyMpKQkpYbf7/j0zJjNZqOxsRGdTse3337LtGnTmDx5MmPGjGHp0qWMGjXKWcMkLi6OvLw8PvzwQ2pqahg+fDgajcan6m11Jd4tW7Zw5swZhg8fjk6nc25s9wXdjTcpKYmMjAyFo+i87sYbFRVFXFycwlF0Tk/87PpaItad1zY8PNynZsO6G69Wq/W5P5K7E69j75iv6G68AQEBhIWFKRxF/+I7mUgbeXl5PPXUU6xcuZL8/Hxyc3OdFcgjIiK47777WLlypfN6q9VKWVkZI0aMYP78+T63cb2r8WZmZkq8PmAgxSs/u/772oLEK/H6V7x9xedmxurq6nj22Wcxm83ceOONbN682fnX8ksvvcTNN98MwMiRI9m+fTvDhg1j8ODBNDc3k52dzaxZs3zqzSDxSrzgH/EOpFhB4pV4JV5fjrev+dzMmEqlIiYmhuzsbMLCwrj33nvZt28fN998M1qtlg0bNgD2U1epqanONerIyEifmuZ3kHglXvCPeAdSrCDxSrwbAInXV+Ptaz43M6bVaomNjXUWACwrK6OpqYkJEyZgNBrZu3cvubm5HD16lPT0dEaMGKHwiLtH4pV4/SXegRQrSLwSr8QrOs93dkiepVKp3DYpFxcXO0+ktLS0cPfdd1NRUUFiYqJPF0V0kHglXn+JdyDFChKvxCvxis7zuWSsrdLSUsLCwli8eDF6vZ4pU6aQkJCg9LB6jcQr8fqLgRQrSLwSr38ZaPH2Np+uM1ZaWsr1119PRkYGV1xxBVdffbXSQ+pVEq/E6y8GUqwg8Uq8/mWgxdsXfHpmTK1Wc+2113LHHXcMiFMaEq9/G0jxDqRYQeL1dxKv6C6fnhkTQgghhPB1PlfaQgghhBDCn0gyJoQQQgihIEnGhBBCCCEUJMmYEEIIIYSCJBkTQgghhFCQT5e2EEKIjuzevZvnnnuOgoICLrvsMmpqaqivr+eaa65hzpw5HT73vffeIzc3lxUrVvTRaIUQA5UkY0IIv3XhhReyYMEC3nrrLZYtWwbA6dOnufPOOzl58iS33XabsgMUQggkGRNCDDDR0dEsWbKE++67j1mzZrFs2TLS09Ol6JKKAAAB7UlEQVSpqqpi1KhR3HDDDRw/fpxNmzZx6tQpli1bxowZM7jkkkt49dVXOX78OAaDgTNnzvDoo48SHBysdEhCCB8nyZgQYsAZPXo09fX1lJeXc/vttzNp0iQArrrqKmbOnElKSgpXX301ubm5LF26FIAdO3bw2WefsWHDBgCeffZZ1q1bx/33369UGEIIPyHJmBBiwLLZbOTm5rJ582YCAgKorq6msLCQmJgYj2u3b99OZWWlMzmrqqrCaDT29ZCFEH5IkjEhxICzf/9+goKC+O677zh48CAvvfQSAIcPH8ZisXh9js1mY+zYsTzxxBPOrxsaGvpszEII/yWlLYQQA0ppaSmrVq1i0aJFVFVVER4eDoDVauXkyZPO6wwGAxaLBZvNRk5ODlOnTmXnzp2YzWYAPv30U1555RVFYhBC+BdpFC6E8Ft5eXk8//zz5Ofnc/nll1NdXU1tbS3z58/nyiuvpLi4mMWLF2MymQgPD2fbtm0MGzaM5cuX09TUxKJFi0hOTmbSpElce+21bNiwgby8POLi4mhqauKRRx7BYDAoHaYQwsdJMiaEEEIIoSBZphRCCCGEUJAkY0IIIYQQCpJkTAghhBBCQZKMCSGEEEIoSJIxIYQQQggFSTImhBBCCKEgScaEEEIIIRT0/wG5hBdjunwcswAAAABJRU5ErkJggg==\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["mombt.plot_results()\n", "# plt.savefig('../../images/ch04/mom_plot_7.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Strategies based on Mean-Reversion"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Getting into the Basics"]}, {"cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [], "source": ["data = pd.DataFrame(raw['GDX'])"]}, {"cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [], "source": ["data.rename(columns={'GDX': 'price'}, inplace=True)"]}, {"cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [], "source": ["data['returns'] = np.log(data['price'] /\n", " data['price'].shift(1))"]}, {"cell_type": "code", "execution_count": 98, "metadata": {}, "outputs": [], "source": ["SMA = 25"]}, {"cell_type": "code", "execution_count": 99, "metadata": {}, "outputs": [], "source": ["data['SMA'] = data['price'].rolling(SMA).mean()"]}, {"cell_type": "code", "execution_count": 100, "metadata": {}, "outputs": [], "source": ["threshold = 3.5"]}, {"cell_type": "code", "execution_count": 101, "metadata": {}, "outputs": [], "source": ["data['distance'] = data['price'] - data['SMA']"]}, {"cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data['distance'].dropna().plot(figsize=(10, 6), legend=True)\n", "plt.axhline(threshold, color='r')\n", "plt.axhline(-threshold, color='r')\n", "plt.axhline(0, color='r');\n", "# plt.savefig('../../images/ch04/mr_plot_1.png')"]}, {"cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [], "source": ["data['position'] = np.where(data['distance'] > threshold,\n", " -1, np.nan)"]}, {"cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [], "source": ["data['position'] = np.where(data['distance'] < -threshold,\n", " 1, data['position'])"]}, {"cell_type": "code", "execution_count": 105, "metadata": {}, "outputs": [], "source": ["data['position'] = np.where(data['distance'] *\n", " data['distance'].shift(1) < 0, 0, data['position'])"]}, {"cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [], "source": ["data['position'] = data['position'].ffill().fillna(0)"]}, {"cell_type": "code", "execution_count": 107, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data['position'].iloc[SMA:].plot(ylim=[-1.1, 1.1],\n", " figsize=(10, 6));\n", "# plt.savefig('../../images/ch04/mr_plot_2.png')"]}, {"cell_type": "code", "execution_count": 108, "metadata": {}, "outputs": [], "source": ["data['strategy'] = data['position'].shift(1) * data['returns']"]}, {"cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[['returns', 'strategy']].dropna().cumsum(\n", " ).apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch04/mr_plot_3.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Generalizing the Approach "]}, {"cell_type": "code", "execution_count": 110, "metadata": {}, "outputs": [], "source": ["import MRVectorBacktester as MR"]}, {"cell_type": "code", "execution_count": 111, "metadata": {}, "outputs": [], "source": ["mrbt = MR.MRVectorBacktester('GLD', '2010-1-1', '2019-12-31',\n", " 10000, 0.001)"]}, {"cell_type": "code", "execution_count": 112, "metadata": {}, "outputs": [{"data": {"text/plain": ["(14599.04, 3891.53)"]}, "execution_count": 112, "metadata": {}, "output_type": "execute_result"}], "source": ["mrbt.run_strategy(SMA=43, threshold=7.5)"]}, {"cell_type": "code", "execution_count": 113, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["mrbt.plot_results()\n", "# plt.savefig('../../images/ch04/mr_plot_4.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"anaconda-cloud": {}, "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch04/MRVectorBacktester.py b/ch04/MRVectorBacktester.py new file mode 100644 index 0000000..d48f000 --- /dev/null +++ b/ch04/MRVectorBacktester.py @@ -0,0 +1,84 @@ +# +# Python Module with Class +# for Vectorized Backtesting +# of Momentum-based Strategies +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +from MomVectorBacktester import * + + +class MRVectorBacktester(MomVectorBacktester): + ''' Class for the vectorized backtesting of + Mean Reversion-based trading strategies. + + Attributes + ========== + symbol: str + RIC symbol with which to work with + start: str + start date for data retrieval + end: str + end date for data retrieval + amount: int, float + amount to be invested at the beginning + tc: float + proportional transaction costs (e.g. 0.5% = 0.005) per trade + + Methods + ======= + get_data: + retrieves and prepares the base data set + run_strategy: + runs the backtest for the mean reversion-based strategy + plot_results: + plots the performance of the strategy compared to the symbol + ''' + + def run_strategy(self, SMA, threshold): + ''' Backtests the trading strategy. + ''' + data = self.data.copy().dropna() + data['sma'] = data['price'].rolling(SMA).mean() + data['distance'] = data['price'] - data['sma'] + data.dropna(inplace=True) + # sell signals + data['position'] = np.where(data['distance'] > threshold, + -1, np.nan) + # buy signals + data['position'] = np.where(data['distance'] < -threshold, + 1, data['position']) + # crossing of current price and SMA (zero distance) + data['position'] = np.where(data['distance'] * + data['distance'].shift(1) < 0, + 0, data['position']) + data['position'] = data['position'].ffill().fillna(0) + data['strategy'] = data['position'].shift(1) * data['return'] + # determine when a trade takes place + trades = data['position'].diff().fillna(0) != 0 + # subtract transaction costs from return when trade takes place + data['strategy'][trades] -= self.tc + data['creturns'] = self.amount * \ + data['return'].cumsum().apply(np.exp) + data['cstrategy'] = self.amount * \ + data['strategy'].cumsum().apply(np.exp) + self.results = data + # absolute performance of the strategy + aperf = self.results['cstrategy'].iloc[-1] + # out-/underperformance of strategy + operf = aperf - self.results['creturns'].iloc[-1] + return round(aperf, 2), round(operf, 2) + + +if __name__ == '__main__': + mrbt = MRVectorBacktester('GDX', '2010-1-1', '2020-12-31', + 10000, 0.0) + print(mrbt.run_strategy(SMA=25, threshold=5)) + mrbt = MRVectorBacktester('GDX', '2010-1-1', '2020-12-31', + 10000, 0.001) + print(mrbt.run_strategy(SMA=25, threshold=5)) + mrbt = MRVectorBacktester('GLD', '2010-1-1', '2020-12-31', + 10000, 0.001) + print(mrbt.run_strategy(SMA=42, threshold=7.5)) diff --git a/ch04/MomVectorBacktester.py b/ch04/MomVectorBacktester.py new file mode 100644 index 0000000..fc1aa61 --- /dev/null +++ b/ch04/MomVectorBacktester.py @@ -0,0 +1,101 @@ +# +# Python Module with Class +# for Vectorized Backtesting +# of Momentum-based Strategies +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import numpy as np +import pandas as pd + + +class MomVectorBacktester(object): + ''' Class for the vectorized backtesting of + Momentum-based trading strategies. + + Attributes + ========== + symbol: str + RIC (financial instrument) to work with + start: str + start date for data selection + end: str + end date for data selection + amount: int, float + amount to be invested at the beginning + tc: float + proportional transaction costs (e.g. 0.5% = 0.005) per trade + + Methods + ======= + get_data: + retrieves and prepares the base data set + run_strategy: + runs the backtest for the momentum-based strategy + plot_results: + plots the performance of the strategy compared to the symbol + ''' + + def __init__(self, symbol, start, end, amount, tc): + self.symbol = symbol + self.start = start + self.end = end + self.amount = amount + self.tc = tc + self.results = None + self.get_data() + + def get_data(self): + ''' Retrieves and prepares the data. + ''' + raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv', + index_col=0, parse_dates=True).dropna() + raw = pd.DataFrame(raw[self.symbol]) + raw = raw.loc[self.start:self.end] + raw.rename(columns={self.symbol: 'price'}, inplace=True) + raw['return'] = np.log(raw / raw.shift(1)) + self.data = raw + + def run_strategy(self, momentum=1): + ''' Backtests the trading strategy. + ''' + self.momentum = momentum + data = self.data.copy().dropna() + data['position'] = np.sign(data['return'].rolling(momentum).mean()) + data['strategy'] = data['position'].shift(1) * data['return'] + # determine when a trade takes place + data.dropna(inplace=True) + trades = data['position'].diff().fillna(0) != 0 + # subtract transaction costs from return when trade takes place + data['strategy'][trades] -= self.tc + data['creturns'] = self.amount * data['return'].cumsum().apply(np.exp) + data['cstrategy'] = self.amount * \ + data['strategy'].cumsum().apply(np.exp) + self.results = data + # absolute performance of the strategy + aperf = self.results['cstrategy'].iloc[-1] + # out-/underperformance of strategy + operf = aperf - self.results['creturns'].iloc[-1] + return round(aperf, 2), round(operf, 2) + + def plot_results(self): + ''' Plots the cumulative performance of the trading strategy + compared to the symbol. + ''' + if self.results is None: + print('No results to plot yet. Run a strategy.') + title = '%s | TC = %.4f' % (self.symbol, self.tc) + self.results[['creturns', 'cstrategy']].plot(title=title, + figsize=(10, 6)) + + +if __name__ == '__main__': + mombt = MomVectorBacktester('XAU=', '2010-1-1', '2020-12-31', + 10000, 0.0) + print(mombt.run_strategy()) + print(mombt.run_strategy(momentum=2)) + mombt = MomVectorBacktester('XAU=', '2010-1-1', '2020-12-31', + 10000, 0.001) + print(mombt.run_strategy(momentum=2)) diff --git a/ch04/SMAVectorBacktester.py b/ch04/SMAVectorBacktester.py new file mode 100644 index 0000000..92f0d60 --- /dev/null +++ b/ch04/SMAVectorBacktester.py @@ -0,0 +1,137 @@ +# +# Python Module with Class +# for Vectorized Backtesting +# of SMA-based Strategies +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import numpy as np +import pandas as pd +from scipy.optimize import brute + + +class SMAVectorBacktester(object): + ''' Class for the vectorized backtesting of SMA-based trading strategies. + + Attributes + ========== + symbol: str + RIC symbol with which to work with + SMA1: int + time window in days for shorter SMA + SMA2: int + time window in days for longer SMA + start: str + start date for data retrieval + end: str + end date for data retrieval + + Methods + ======= + get_data: + retrieves and prepares the base data set + set_parameters: + sets one or two new SMA parameters + run_strategy: + runs the backtest for the SMA-based strategy + plot_results: + plots the performance of the strategy compared to the symbol + update_and_run: + updates SMA parameters and returns the (negative) absolute performance + optimize_parameters: + implements a brute force optimizeation for the two SMA parameters + ''' + + def __init__(self, symbol, SMA1, SMA2, start, end): + self.symbol = symbol + self.SMA1 = SMA1 + self.SMA2 = SMA2 + self.start = start + self.end = end + self.results = None + self.get_data() + + def get_data(self): + ''' Retrieves and prepares the data. + ''' + raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv', + index_col=0, parse_dates=True).dropna() + raw = pd.DataFrame(raw[self.symbol]) + raw = raw.loc[self.start:self.end] + raw.rename(columns={self.symbol: 'price'}, inplace=True) + raw['return'] = np.log(raw / raw.shift(1)) + raw['SMA1'] = raw['price'].rolling(self.SMA1).mean() + raw['SMA2'] = raw['price'].rolling(self.SMA2).mean() + self.data = raw + + def set_parameters(self, SMA1=None, SMA2=None): + ''' Updates SMA parameters and resp. time series. + ''' + if SMA1 is not None: + self.SMA1 = SMA1 + self.data['SMA1'] = self.data['price'].rolling( + self.SMA1).mean() + if SMA2 is not None: + self.SMA2 = SMA2 + self.data['SMA2'] = self.data['price'].rolling(self.SMA2).mean() + + def run_strategy(self): + ''' Backtests the trading strategy. + ''' + data = self.data.copy().dropna() + data['position'] = np.where(data['SMA1'] > data['SMA2'], 1, -1) + data['strategy'] = data['position'].shift(1) * data['return'] + data.dropna(inplace=True) + data['creturns'] = data['return'].cumsum().apply(np.exp) + data['cstrategy'] = data['strategy'].cumsum().apply(np.exp) + self.results = data + # gross performance of the strategy + aperf = data['cstrategy'].iloc[-1] + # out-/underperformance of strategy + operf = aperf - data['creturns'].iloc[-1] + return round(aperf, 2), round(operf, 2) + + def plot_results(self): + ''' Plots the cumulative performance of the trading strategy + compared to the symbol. + ''' + if self.results is None: + print('No results to plot yet. Run a strategy.') + title = '%s | SMA1=%d, SMA2=%d' % (self.symbol, + self.SMA1, self.SMA2) + self.results[['creturns', 'cstrategy']].plot(title=title, + figsize=(10, 6)) + + def update_and_run(self, SMA): + ''' Updates SMA parameters and returns negative absolute performance + (for minimazation algorithm). + + Parameters + ========== + SMA: tuple + SMA parameter tuple + ''' + self.set_parameters(int(SMA[0]), int(SMA[1])) + return -self.run_strategy()[0] + + def optimize_parameters(self, SMA1_range, SMA2_range): + ''' Finds global maximum given the SMA parameter ranges. + + Parameters + ========== + SMA1_range, SMA2_range: tuple + tuples of the form (start, end, step size) + ''' + opt = brute(self.update_and_run, (SMA1_range, SMA2_range), finish=None) + return opt, -self.update_and_run(opt) + + +if __name__ == '__main__': + smabt = SMAVectorBacktester('EUR=', 42, 252, + '2010-1-1', '2020-12-31') + print(smabt.run_strategy()) + smabt.set_parameters(SMA1=20, SMA2=100) + print(smabt.run_strategy()) + print(smabt.optimize_parameters((30, 56, 4), (200, 300, 4))) diff --git a/ch05/05_pyalgo.ipynb b/ch05/05_pyalgo.ipynb new file mode 100644 index 0000000..d331250 --- /dev/null +++ b/ch05/05_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading "]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Chapter 05 — Predicting Market Movements with Machine Learning**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Using Linear Regression for Market Movement Prediction"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### A Quick Review of Linear Regression"]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["import os\n", "import random\n", "import numpy as np\n", "from pylab import mpl, plt\n", "plt.style.use('seaborn')\n", "mpl.rcParams['font.family'] = 'serif'\n", "os.environ['PYTHONHASHSEED'] = '0'"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["x = np.linspace(0, 10)"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": ["def set_seeds(seed=100):\n", " random.seed(seed)\n", " np.random.seed(seed)\n", "set_seeds() # <4>"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": ["y = x + np.random.standard_normal(len(x))"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": ["reg = np.polyfit(x, y, deg=1)"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([0.94612934, 0.22855261])"]}, "execution_count": 6, "metadata": {}, "output_type": "execute_result"}], "source": ["reg"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"anaconda-cloud": {}, "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch04/MRVectorBacktester.py b/ch04/MRVectorBacktester.py new file mode 100644 index 0000000..d48f000 --- /dev/null +++ b/ch04/MRVectorBacktester.py @@ -0,0 +1,84 @@ +# +# Python Module with Class +# for Vectorized Backtesting +# of Momentum-based Strategies +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +from MomVectorBacktester import * + + +class MRVectorBacktester(MomVectorBacktester): + ''' Class for the vectorized backtesting of + Mean Reversion-based trading strategies. + + Attributes + ========== + symbol: str + RIC symbol with which to work with + start: str + start date for data retrieval + end: str + end date for data retrieval + amount: int, float + amount to be invested at the beginning + tc: float + proportional transaction costs (e.g. 0.5% = 0.005) per trade + + Methods + ======= + get_data: + retrieves and prepares the base data set + run_strategy: + runs the backtest for the mean reversion-based strategy + plot_results: + plots the performance of the strategy compared to the symbol + ''' + + def run_strategy(self, SMA, threshold): + ''' Backtests the trading strategy. + ''' + data = self.data.copy().dropna() + data['sma'] = data['price'].rolling(SMA).mean() + data['distance'] = data['price'] - data['sma'] + data.dropna(inplace=True) + # sell signals + data['position'] = np.where(data['distance'] > threshold, + -1, np.nan) + # buy signals + data['position'] = np.where(data['distance'] < -threshold, + 1, data['position']) + # crossing of current price and SMA (zero distance) + data['position'] = np.where(data['distance'] * + data['distance'].shift(1) < 0, + 0, data['position']) + data['position'] = data['position'].ffill().fillna(0) + data['strategy'] = data['position'].shift(1) * data['return'] + # determine when a trade takes place + trades = data['position'].diff().fillna(0) != 0 + # subtract transaction costs from return when trade takes place + data['strategy'][trades] -= self.tc + data['creturns'] = self.amount * \ + data['return'].cumsum().apply(np.exp) + data['cstrategy'] = self.amount * \ + data['strategy'].cumsum().apply(np.exp) + self.results = data + # absolute performance of the strategy + aperf = self.results['cstrategy'].iloc[-1] + # out-/underperformance of strategy + operf = aperf - self.results['creturns'].iloc[-1] + return round(aperf, 2), round(operf, 2) + + +if __name__ == '__main__': + mrbt = MRVectorBacktester('GDX', '2010-1-1', '2020-12-31', + 10000, 0.0) + print(mrbt.run_strategy(SMA=25, threshold=5)) + mrbt = MRVectorBacktester('GDX', '2010-1-1', '2020-12-31', + 10000, 0.001) + print(mrbt.run_strategy(SMA=25, threshold=5)) + mrbt = MRVectorBacktester('GLD', '2010-1-1', '2020-12-31', + 10000, 0.001) + print(mrbt.run_strategy(SMA=42, threshold=7.5)) diff --git a/ch04/MomVectorBacktester.py b/ch04/MomVectorBacktester.py new file mode 100644 index 0000000..fc1aa61 --- /dev/null +++ b/ch04/MomVectorBacktester.py @@ -0,0 +1,101 @@ +# +# Python Module with Class +# for Vectorized Backtesting +# of Momentum-based Strategies +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import numpy as np +import pandas as pd + + +class MomVectorBacktester(object): + ''' Class for the vectorized backtesting of + Momentum-based trading strategies. + + Attributes + ========== + symbol: str + RIC (financial instrument) to work with + start: str + start date for data selection + end: str + end date for data selection + amount: int, float + amount to be invested at the beginning + tc: float + proportional transaction costs (e.g. 0.5% = 0.005) per trade + + Methods + ======= + get_data: + retrieves and prepares the base data set + run_strategy: + runs the backtest for the momentum-based strategy + plot_results: + plots the performance of the strategy compared to the symbol + ''' + + def __init__(self, symbol, start, end, amount, tc): + self.symbol = symbol + self.start = start + self.end = end + self.amount = amount + self.tc = tc + self.results = None + self.get_data() + + def get_data(self): + ''' Retrieves and prepares the data. + ''' + raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv', + index_col=0, parse_dates=True).dropna() + raw = pd.DataFrame(raw[self.symbol]) + raw = raw.loc[self.start:self.end] + raw.rename(columns={self.symbol: 'price'}, inplace=True) + raw['return'] = np.log(raw / raw.shift(1)) + self.data = raw + + def run_strategy(self, momentum=1): + ''' Backtests the trading strategy. + ''' + self.momentum = momentum + data = self.data.copy().dropna() + data['position'] = np.sign(data['return'].rolling(momentum).mean()) + data['strategy'] = data['position'].shift(1) * data['return'] + # determine when a trade takes place + data.dropna(inplace=True) + trades = data['position'].diff().fillna(0) != 0 + # subtract transaction costs from return when trade takes place + data['strategy'][trades] -= self.tc + data['creturns'] = self.amount * data['return'].cumsum().apply(np.exp) + data['cstrategy'] = self.amount * \ + data['strategy'].cumsum().apply(np.exp) + self.results = data + # absolute performance of the strategy + aperf = self.results['cstrategy'].iloc[-1] + # out-/underperformance of strategy + operf = aperf - self.results['creturns'].iloc[-1] + return round(aperf, 2), round(operf, 2) + + def plot_results(self): + ''' Plots the cumulative performance of the trading strategy + compared to the symbol. + ''' + if self.results is None: + print('No results to plot yet. Run a strategy.') + title = '%s | TC = %.4f' % (self.symbol, self.tc) + self.results[['creturns', 'cstrategy']].plot(title=title, + figsize=(10, 6)) + + +if __name__ == '__main__': + mombt = MomVectorBacktester('XAU=', '2010-1-1', '2020-12-31', + 10000, 0.0) + print(mombt.run_strategy()) + print(mombt.run_strategy(momentum=2)) + mombt = MomVectorBacktester('XAU=', '2010-1-1', '2020-12-31', + 10000, 0.001) + print(mombt.run_strategy(momentum=2)) diff --git a/ch04/SMAVectorBacktester.py b/ch04/SMAVectorBacktester.py new file mode 100644 index 0000000..92f0d60 --- /dev/null +++ b/ch04/SMAVectorBacktester.py @@ -0,0 +1,137 @@ +# +# Python Module with Class +# for Vectorized Backtesting +# of SMA-based Strategies +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import numpy as np +import pandas as pd +from scipy.optimize import brute + + +class SMAVectorBacktester(object): + ''' Class for the vectorized backtesting of SMA-based trading strategies. + + Attributes + ========== + symbol: str + RIC symbol with which to work with + SMA1: int + time window in days for shorter SMA + SMA2: int + time window in days for longer SMA + start: str + start date for data retrieval + end: str + end date for data retrieval + + Methods + ======= + get_data: + retrieves and prepares the base data set + set_parameters: + sets one or two new SMA parameters + run_strategy: + runs the backtest for the SMA-based strategy + plot_results: + plots the performance of the strategy compared to the symbol + update_and_run: + updates SMA parameters and returns the (negative) absolute performance + optimize_parameters: + implements a brute force optimizeation for the two SMA parameters + ''' + + def __init__(self, symbol, SMA1, SMA2, start, end): + self.symbol = symbol + self.SMA1 = SMA1 + self.SMA2 = SMA2 + self.start = start + self.end = end + self.results = None + self.get_data() + + def get_data(self): + ''' Retrieves and prepares the data. + ''' + raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv', + index_col=0, parse_dates=True).dropna() + raw = pd.DataFrame(raw[self.symbol]) + raw = raw.loc[self.start:self.end] + raw.rename(columns={self.symbol: 'price'}, inplace=True) + raw['return'] = np.log(raw / raw.shift(1)) + raw['SMA1'] = raw['price'].rolling(self.SMA1).mean() + raw['SMA2'] = raw['price'].rolling(self.SMA2).mean() + self.data = raw + + def set_parameters(self, SMA1=None, SMA2=None): + ''' Updates SMA parameters and resp. time series. + ''' + if SMA1 is not None: + self.SMA1 = SMA1 + self.data['SMA1'] = self.data['price'].rolling( + self.SMA1).mean() + if SMA2 is not None: + self.SMA2 = SMA2 + self.data['SMA2'] = self.data['price'].rolling(self.SMA2).mean() + + def run_strategy(self): + ''' Backtests the trading strategy. + ''' + data = self.data.copy().dropna() + data['position'] = np.where(data['SMA1'] > data['SMA2'], 1, -1) + data['strategy'] = data['position'].shift(1) * data['return'] + data.dropna(inplace=True) + data['creturns'] = data['return'].cumsum().apply(np.exp) + data['cstrategy'] = data['strategy'].cumsum().apply(np.exp) + self.results = data + # gross performance of the strategy + aperf = data['cstrategy'].iloc[-1] + # out-/underperformance of strategy + operf = aperf - data['creturns'].iloc[-1] + return round(aperf, 2), round(operf, 2) + + def plot_results(self): + ''' Plots the cumulative performance of the trading strategy + compared to the symbol. + ''' + if self.results is None: + print('No results to plot yet. Run a strategy.') + title = '%s | SMA1=%d, SMA2=%d' % (self.symbol, + self.SMA1, self.SMA2) + self.results[['creturns', 'cstrategy']].plot(title=title, + figsize=(10, 6)) + + def update_and_run(self, SMA): + ''' Updates SMA parameters and returns negative absolute performance + (for minimazation algorithm). + + Parameters + ========== + SMA: tuple + SMA parameter tuple + ''' + self.set_parameters(int(SMA[0]), int(SMA[1])) + return -self.run_strategy()[0] + + def optimize_parameters(self, SMA1_range, SMA2_range): + ''' Finds global maximum given the SMA parameter ranges. + + Parameters + ========== + SMA1_range, SMA2_range: tuple + tuples of the form (start, end, step size) + ''' + opt = brute(self.update_and_run, (SMA1_range, SMA2_range), finish=None) + return opt, -self.update_and_run(opt) + + +if __name__ == '__main__': + smabt = SMAVectorBacktester('EUR=', 42, 252, + '2010-1-1', '2020-12-31') + print(smabt.run_strategy()) + smabt.set_parameters(SMA1=20, SMA2=100) + print(smabt.run_strategy()) + print(smabt.optimize_parameters((30, 56, 4), (200, 300, 4))) diff --git a/ch05/05_pyalgo.ipynb b/ch05/05_pyalgo.ipynb new file mode 100644 index 0000000..d331250 --- /dev/null +++ b/ch05/05_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading "]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Chapter 05 — Predicting Market Movements with Machine Learning**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Using Linear Regression for Market Movement Prediction"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### A Quick Review of Linear Regression"]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["import os\n", "import random\n", "import numpy as np\n", "from pylab import mpl, plt\n", "plt.style.use('seaborn')\n", "mpl.rcParams['font.family'] = 'serif'\n", "os.environ['PYTHONHASHSEED'] = '0'"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["x = np.linspace(0, 10)"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": ["def set_seeds(seed=100):\n", " random.seed(seed)\n", " np.random.seed(seed)\n", "set_seeds() # <4>"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": ["y = x + np.random.standard_normal(len(x))"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": ["reg = np.polyfit(x, y, deg=1)"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([0.94612934, 0.22855261])"]}, "execution_count": 6, "metadata": {}, "output_type": "execute_result"}], "source": ["reg"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6))\n", "plt.plot(x, y, 'bo', label='data')\n", "plt.plot(x, np.polyval(reg, x), 'r', lw=2.5,\n", " label='linear regression')\n", "plt.legend(loc=0);\n", "# plt.savefig('../../images/ch05/lr_plot_1.png')"]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6))\n", "plt.plot(x, y, 'bo', label='data')\n", "xn = np.linspace(0, 20)\n", "plt.plot(xn, np.polyval(reg, xn), 'r', lw=2.5,\n", " label='linear regression')\n", "plt.legend(loc=0);\n", "# plt.savefig('../../images/ch05/lr_plot_2.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### The Basic Idea for Price Prediction"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": ["x = np.arange(12)"]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])"]}, "execution_count": 10, "metadata": {}, "output_type": "execute_result"}], "source": ["x"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": ["lags = 3"]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": ["m = np.zeros((lags + 1, len(x) - lags))"]}, {"cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": ["m[lags] = x[lags:]\n", "for i in range(lags):\n", " m[i] = x[i:i - lags]"]}, {"cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0., 1., 2., 3.],\n", " [ 1., 2., 3., 4.],\n", " [ 2., 3., 4., 5.],\n", " [ 3., 4., 5., 6.],\n", " [ 4., 5., 6., 7.],\n", " [ 5., 6., 7., 8.],\n", " [ 6., 7., 8., 9.],\n", " [ 7., 8., 9., 10.],\n", " [ 8., 9., 10., 11.]])"]}, "execution_count": 14, "metadata": {}, "output_type": "execute_result"}], "source": ["m.T"]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": ["reg = np.linalg.lstsq(m[:lags].T, m[lags], rcond=None)[0]"]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([-0.66666667, 0.33333333, 1.33333333])"]}, "execution_count": 16, "metadata": {}, "output_type": "execute_result"}], "source": ["reg"]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 3., 4., 5., 6., 7., 8., 9., 10., 11.])"]}, "execution_count": 17, "metadata": {}, "output_type": "execute_result"}], "source": ["np.dot(m[:lags].T, reg)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Predicting Index Levels"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": ["import pandas as pd"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": ["raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv',\n", " index_col=0, parse_dates=True).dropna()"]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "DatetimeIndex: 2516 entries, 2010-01-04 to 2019-12-31\n", "Data columns (total 12 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 AAPL.O 2516 non-null float64\n", " 1 MSFT.O 2516 non-null float64\n", " 2 INTC.O 2516 non-null float64\n", " 3 AMZN.O 2516 non-null float64\n", " 4 GS.N 2516 non-null float64\n", " 5 SPY 2516 non-null float64\n", " 6 .SPX 2516 non-null float64\n", " 7 .VIX 2516 non-null float64\n", " 8 EUR= 2516 non-null float64\n", " 9 XAU= 2516 non-null float64\n", " 10 GDX 2516 non-null float64\n", " 11 GLD 2516 non-null float64\n", "dtypes: float64(12)\n", "memory usage: 255.5 KB\n"]}], "source": ["raw.info()"]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": ["symbol = 'EUR='"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": ["data = pd.DataFrame(raw[symbol])"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": ["data.rename(columns={symbol: 'price'}, inplace=True)"]}, {"cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": ["lags = 5"]}, {"cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": ["cols = []\n", "for lag in range(1, lags + 1):\n", " col = f'lag_{lag}'\n", " data[col] = data['price'].shift(lag) # <1>\n", " cols.append(col)\n", "data.dropna(inplace=True)"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": ["reg = np.linalg.lstsq(data[cols], data['price'],\n", " rcond=None)[0]"]}, {"cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 0.98635864, 0.02292172, -0.04769849, 0.05037365, -0.01208135])"]}, "execution_count": 27, "metadata": {}, "output_type": "execute_result"}], "source": ["reg"]}, {"cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": ["data['prediction'] = np.dot(data[cols], reg)"]}, {"cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[['price', 'prediction']].plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch05/lr_plot_3.png')"]}, {"cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[['price', 'prediction']].loc['2019-10-1':].plot(\n", " figsize=(10, 6));\n", "# plt.savefig('../../images/ch05/lr_plot_4.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Predicting Future Returns"]}, {"cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": ["data['return'] = np.log(data['price'] /\n", " data['price'].shift(1))"]}, {"cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": ["data.dropna(inplace=True)"]}, {"cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": ["cols = []\n", "for lag in range(1, lags + 1):\n", " col = f'lag_{lag}'\n", " data[col] = data['return'].shift(lag) # <3>\n", " cols.append(col)\n", "data.dropna(inplace=True)"]}, {"cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": ["reg = np.linalg.lstsq(data[cols], data['return'],\n", " rcond=None)[0]"]}, {"cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([-0.015689 , 0.00890227, -0.03634858, 0.01290924, -0.00636023])"]}, "execution_count": 35, "metadata": {}, "output_type": "execute_result"}], "source": ["reg"]}, {"cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": ["data['prediction'] = np.dot(data[cols], reg)"]}, {"cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [{"data": {"image/png": 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k/3Lr7XB4FLVRsu1p7bSDZUKC2On2XrKFoVQXYGjVJxN1kRL0UjbWLysrQ3//oJ2Pw+FAWVmZons++ugjOJ1O3HDDDakWh8gayLyYyDL03GX1XDaCICRJWRA755xz0NLSAq/XCwDYt28fFi1ahJ6eHjgcDgDAokWLUFlZCQCoqanBzJkzI9qwt99+GzabDbfccgtqampw6tSpVIukKQwjdoVGSoIgso8gx+HDLafQbHVoXRSCGJKkLIjl5uZi2bJluO+++/DII49gxowZWLBgAZ555hmsWbMGAPCLX/wCLS0tWLVqFV588UXcf//9AIANGzbggQcewBdffIGf//zn+MMf/oCOjo5Ui0RkBaISK0EQOuLQSRve33IKf3l+l9ZFIYghiSruKxYuXIiFCxdG/XbnnXdG/p+Tk4OlS5fGPXfFFVdg7969ahRB95AfsVioQQgiG3B6/ADoiyWIdEEOXQmCINKEHCeweg/YzYrbWxAEoQIkiGUIfQ+1WkCDO3EaIOPDD6ogiFEsW4LIXkgQIzSCJg4iu0hXjw0G6VsgiNMZEsQyBY21BEEIoPfY4AxtTRJEWiFBjNAIGtyJoY+c9VdA5xox+lIJIr2QIJYhyIYjFv20x0vrjuLzPY1aF4M4TVHFRkw/nxNBEApRxX0FQWQzm/a3AgC+ed54jUtCnI6oIYgRBJG9kEYsQ9BYSxCnH3JcU6TbWL+9ywmPL5D082QiRhDphQQxlUmXwMVxHPr6velJXEPIEJjIGtL0badTEOu2e3DXMztw3+o9KaRC3yhBpBMSxLKE9zefwu9WbsGhkzZZ93McB6fbl+ZSpY4enVkGgxweer0Sm/a3aF0U4jQgnYJYl90NAGju7E86DVorEUR6IUEsjZxq7VMtrS/2NgEADtTKE8Qee7MStz66Ge1dTtXKcLrQauvH0fpuvLSuWuuiEKcBZCNGEKc3JIilkb/xtgMyPdZ+sTt0CvCkisJgOtDj1qQey0RkJ3K+ey3cVzS02+FwydOY09dAEOmFBLEsQ+mQTYOockgOI9Ti3U0n4Q9Ie2xNpxzGCIwADpcPy17cjT8+tV1uIgRBpBESxFRHbFSVP9r29XtR09CtTnEIxZBGjFCTHodH8jqXYY1Y2HbU5fFnNF+CIIQhQUyH/N9zO7F8TSU6e1ypJ0YyhWLSKYc9/+Eh3PbY5oRaEkJ/pMspsxpbk+k0fRDSqhEEoR4kiGUI/jh570u78eGWU6L3hm03ep2D7iqGmpJGz+bJ6Wzq97+qhcPlg92p/xOthDokEmR0b6w/xMYegtAbJIhpQH2bHe9LCGJh1FiJ0mo2CTIg9abTbQfHcWjp7Nf/BE8ASK/7CjW6Mo0gBJFeSBDLEKrNiUNkbtXz4K7nsslhw54m/N9zO7F+F8XPzCQ+v7D3+kTCkN4F5qGmjScIvUGCmMrobUzV6yCqs2aKQqjNOI7DF3ub1LHbSzNVJzoBAPuOWzUuyenDkbou3PzwV/hyX5PiZ9Md4ih1dDqIEMQQgQQxHSMoROloTLQ7vbj3xd04fKpL66IkjdAWISvQ8AdqbXjt82P428uphIrJDJHi631+zzKkFlnbD7cBANbtqFecrjqCGL1sgshWSBDTMW1CXvFjxlufP4iKymZR54zpdMVQUdWC+nY7VrxZlfCIfiw6kidl0TdwcCIbjOwH5TCanDNGCk2ttkLsT09uwYNr9qmWnl616gQxVCBBLEMkY5z97EdHEvoTW7+7AS9/VoMX1h5NtmjJw6vTn5/bqexRtcuSJELlEBJes/LQg14aWQM4jtPIRYjyfqK2Z/3DJ22obugRvU5OoQfp6HaSz0ZCc0gQ0zm1LdIhitq7QzZL9e12weuZGkT73QqdQ2aZkKC2ViCtfp8GCptlTawqj7y9H4sfqsiYMJZKW+vdWH8o86end2D5mkry60doCgliKpO6X/2Y5/Q8SMdIJz5/AGu31+HtjSf0Xe6hzsBrOZ1fwaGTIbtFj0/4JGOqiAlPQgJ7IvMA3RvrD2WV2AA0XhFaYtS6AIQ02TQ+rP60BtsOhYyWz51ejqljh4neq5tq6aYg6WBIV04W6fp+AoEgWKMBQMh+MNzvk0ENQYw86xNE9kIasUyR5EC5aX9LTDL6nVz3D7hNAEITVbaSidVxOt9jeOLMJiE+2/D5Bxv3k+3KT0ryyfTWpGKxiuQwgkgrJIjpnM5ed0rP04knaeQKRNnUjuGykhyWvvfmDw4uNAKB1Fo601uTp4ux/taDrVj1/iHadiR0DwliGSJbhgJ/IBg3cL315Qk89cEhRekI2cX09Q/GzgznkS2DfFZuz2RLp0sjyczB9W12eLzStmV+v7DGNxnBL1YjduikDQ+u2ZewDJkiC3s+AOD5tUexp7oD3XZlrnXSid3pFXU1RJy+kCCmNmma/MQMfg/U2gCE/ImJPKkon8UPVWD5msqo3z7d1YBdRzvib1Y4y/3lhV3xSShKgZAD+RFLnqYOB+59aTceeqNS8j4/X4vF+8SsPW70xvjUSyScxbqv+Odb+1Hd0IOdR9tllRmg7yhb+O3jW3DbY5u1LgahM0gQyxRpUo+HtUxqrrKONQr7IBL7PQx/QhHyTs/XiOkF2a9FbbVABtxX0OysnLAT5ZMJ3MaIacSAkCZGCel1ZaKXRLRDjlNr2r0ktIQEsSxDsX2HzDH04211+NNT2yXveeA1aW/dbv5Wisx8s3uI1zeJ+srhui489vZ+0WDVpyP8Nqtt6RW9T8rvlK0v2q4zUR8Xc+iq6NtI66lJfeNw+fDMh4fR0tmfdBokhxFaQoJYhtDqQ5c7iL676SQ6VAxoLTdfPQ6AQqvjLFKIDRrrJ8hkxRtV2F9rw95jFBxciPtf3hv1N789/QkM9JX0F1FjfQWJLHsxfttfLfSuEPtkRz12HGnH4+8cELyu9/ITBAliWcbGfc1oF4pBiZCGIw6tBqEE+WbdVkBWDubyGjnr3kUakXvCjq8RS7VrqOG+Ihxh43Qk7LTX6RGO7iHr/dA3QGgICWIqI2YgncpYu3Z7XdTfz609Injfijeqks9EZYRsxITQo3yjhpF7po7MBzkOr60/FhUvj0IcpR++IJaonRNdF9OIqXFSV5U0dK5SSlg6OTZi9LUQGkKCWBbw769ORv3t9cl3lqp3twtaD39y5SUl7Vh1vBO/Wr5R8nCDWvWube7FF/uaok66RkqqdeNmIXL7Q6KtSaHu4vb68c+3qlBdHx1kWkm4JCKeQQfGKtjaEYQGkCCWgL+/uhcPvS59lJ2IJ9EkMpRlhH9vqgUArN/dmPa8BAUCOjSZNHI1I26vPyJAJZrow/LBtkNtOHSyCw/GjCe6jzWpIRt21UdF7BBEhbFGDQW2y+PH71ZuwRd7m1JPjDitIEEsASeaenE0ZgWrBUm7p2BCK0Wh1eL+E5148t2DCATVD0eUUIM0UB6Xx49X1tegU8WDAikjJNsoWFarvQIPchyqTnTCJWQDI/BeI37EMrQ9eqyxB3tr9GPw39WXWjQKOTz1wWEsFzlFzHHC/V9M4NK7IKalZu6xN6vwmIgRPgD0u30RH4pi3T2T30FfvxevfX4s4b3k7Z/gQ4JYhlDzw2u1KTumfdczO/CPV+MnjcfeOYC9x6yoaZD2D5YMcgfvo/Xd2LivGf9S6LlfPdIxIEpvlUhRecyKPdXRznN3DpwIe+bDwzKzVzZzpjrPPvDaPjz53sEUU1GPP6zalvzDEq8sVlt2vEncvYUSxNxXEIlZ8ujmuHi8saQy9Na32fH4OwdU94avxjv3eAOob7OrUBpCa0gQU5lMLHT8AU522A4GQEe3CyeaxScNLRZnsXYxvTp09iqG3SldVllykEijr3z3IFa9Hy2UNltDgrfgqVih/GXdxStKpEicLp3uZhK1PgWhPiBk9N5sdWBtikHD043e7UzDpPLuxMbAFW9WoepEJz7b1ZBC6vGooQVd8WYV7n1pNxraSRjLdlQRxLZt24Zly5Zh5cqVeOKJJ+Kuezwe/PWvf8XTTz+Nu+66C6dOnYpcq6+vxy233ILbbrtNjaJklEOnbHjmw8OSW3s1Dd2iq5ZnPzqMB17di3638tVWl13e9stLn1YrTlsNEp20svZEl18rTX1svkGOw2c82662LmfcqdUVb8o7napWnZSe6JLrRyyWNRuO43crt6BWQmgnBEi4Cx//Ig6fCgnVf35+l7hD1wzIP30JFhVA9p8olKeZFr7HN3A6VjyEXHKooRELL65bbcLujIjsIWVBzOVyYenSpbj77ruxZMkS1NTUYPv2aA/tq1evxujRo3HzzTfjhhtuwD333BO5tn//flx22WWpFiMtNHY4JK//88392HGkHUfrxG3Ilq+pxL0v7Ra8tv1wO4419SZUrQshd5LtdWij4UjnJPLCJ0fTZhC7r8Yalfa9L+7Gv786if0nbJHfGtql+4Ve9Adyt0bD5Q3Xu7pBe5tIzciQzLHizaq4mJSxZEIT9cib+9OeR+ZI/uVxENYIh93wqG3Hp+Z2dFhQ9geCOHTSJhn1gdAnxlQTqKqqwpgxY2A2mwEA8+bNQ0VFBRYsWBC5p6KiAnfccQcAYMaMGaiurobD4UBBQQGuueYavPvuu4ryLCnJg9FoSLXogpSXF0b+/8sHvhT8fd32Oqz+eNBeJzffErnuFNFulZTmi+ZZkJ+D8vJCNLbb8Zen5dm3FA/LiyqTUDnlXisuzpV9L//3/HyLaF6lpfmSZYmFZRnZZd9yoBVb0Ir//PYs2emLEXYGGc4jEGN0Hr4eezhRqqxGU6hvms1G0ftKSvNRPrxANA3+c3m55oH/xbdRC0+zGL6Wk2MCABgMrKx3UFiUG/de5b47/n1K3nemKC3Nx7AC8X7Kp7y8EAWFPXG/hSkqzBF8ZvD9hDAY2KiFSFlZAYYX56IwphzPfBwfk5KfX2FRjqI2jb23vLwQfZ5A3HUfr3D17faEeVh5izmt3rG8fIXHkJLSfOyt7sB7FSfw2B2LkGOJn/aGlxXglXVH8cm2Oqz47aWYPqEEAGA0hNrKkmNKWIZh1kHb3UT3FpfkoUSgPyVDYWHo+335kyN4+4vj+I9vTsfPVBgb5aDHbz5ZtKxLyoKYzWZDfv6gkFFQUACbzSbrnoIC8YlIiu7u9Khiy8sLYbUKbyPyf1/1TvQqsrvbGbkueLINQJeEgX1/vwdWqx0vf3wYnb3ythy7uvthLTBJllPutZ7e+BOLctrB0S++ou/udiLPMLiaZFnp1X0gEBTN05hjwoHqdhhYBh/z7Gmk6ioXviBmtdrRJ3LizuuNfq9SeQcGtjHcHp/ofV1d/TBJaKz4zzldXsHfAaC3xxl3zTvQB/0SbcrH3ueKui/cHxMR+72o8T7UxmZzwOtKrBUO16WvL/pb4NdJqG9Yrfao9wOE+jL/1dpsDnA+f9z3clTA5o+fn93uVtSmsfdarfaosTJ8vStm/EyUh1AamYCv0bVa7fD6AqioasGCOSNRmGcWvF+ofDabA08OjNnb9zfhzMllcfdYOx34ZFsdAGDH/maU5EZPjf1Ob8K69/LGUaF7+RN9R4cd/iRMUoToG/h+q2pCh3z213TgW/PHqZK2FFLzZbaRibpILt5TTbysrAz9/YNChsPhQFlZmeJ7shk5amYpO4tktvE4jlNNBZ3ODZBTrX342+o9uP7bM5JO438e3ChoIN/v9sHp9qNcQKMnhccXwNMfHMa3LhiPSaOLoq6pcrpVlrF+MgnHPySYTMRGLLtte7KZZLfm1+0YXGjoZYtbK2IP9Hy6swHvbzmFw6e6cPt1Z8fdL9bbT/BPtyr8JJLdmuQ4TtJONh0uS7TqL29XnMC44QVYcOYojUqQ/aRsI3bOOeegpaUFXm9ooty3bx8WLVqEnp4eOBwhW5pFixahsjLkxLCmpgYzZ85MWhumR1L1w5XMB7TjSDsWP1SRUr5SqHVce+vBVgDx0QFikRqWxE4p3vbYZvzxqe043tSDfQoCV+880o6qE51R3ujDDAVPAnqZwOva+tDcqczVSqqkKnwqfZzjOGzYI22vqCTNtytqlRUgAdnsnT+23awDGqeWTmkbzVie+WgwJFxlIuewiB6Lwpp8pfFAb3tss2RfVNVlSTU+X/8AACAASURBVDipcGizDI9h63Y04NmPhcPuEfJIWRDLzc3FsmXLcN999+GRRx7BjBkzsGDBAjzzzDNYs2YNAOAXv/gFWlpasGrVKrz44ou4//77I89v2LABGzduxMmTJ/Hss8+mWhxNCCQKdwKobgT8VZVyA38l3L5yS2oJDIwGsqudRPuEB5x/vLoPT7wr348Vf1B1uqO3HMUGTyUD8aBDVdmPKExZHlorxP760h78+bmdGc0z01U+2dInciU7JaBAMIhlL+zCJzzNXLKIOZKWS5zWKNWgngA27msWflSknGGLCi7IwecPCN4jlH2/2y9ZnHQY60fGHdVSJjJFyluTALBw4UIsXLgw6rc777wz8v+cnBwsXbpU8NkrrrgCV1xxhRrF0Aw5H5Wk7ZfGy1ah3FUbKAaS0WvIo98/uTXqb9G4fzF/u71+7DtmxfkzR8AUc3Ak4j5ColbprW92CgGqkGLDKnXVIMetQexEKRsNXmNXnwcNHQ40dDjwnYsmyn4uyHGRbbwwf129ByzD4M/Xn5dUWTK5kOBnxRfKwtuLWw+1YeuhNjx5+6XIFTD2F0yT40QHvv97bid+dfUsLDxrdNJljoVRuALcfKAFrZ1OXHf5VMV5uTx+3PfCTlwxb6ziZ4l4yKGrCvCFFrFvYKWExkbraTMdh535TkIB7evIR6oscgf/NRuO47mPj+KjbUKag8S1Vct+q72LfAjxSafPqxqJIO7RZVCHsPuKjh4XTrWKad7k0ylwKAcA/v1VbeS0t8kYPyUk6qvV9d349fKN2B0TEaK+za6o3L39Xjz0emXkGaXbgfx3v+NIm6JnxYg9ZGSTeZgKSDyWPL82/tRsMiQ7lLz4STU+FXBUu/NIe1x0j1g27W/BzsNtuP+VvcllniRbD7aiPU2H9bSEBDEVCMgwmhc7TQlAEymFH9uRS4NhVI/DA58/ODg0JlSJcdhb04F/vX9I8QCsJnLzrmsNnbBptkrYq6hVDZF0ehwevLI+cVy704nY16f4FYg8EOQ4bDsUP7mLdeuo3zmhH+Xzp6e242+r9yT1LL89HntbOGbj2u31eGfAhjNWqyWHsP+5D7ecQktnf9JC49ptdTha3x2JLSkuACYu4zMfKrRZEskqtj2U9CetDsukmuvTHx6Oi+4RixZhuRra7Xh+7VHc/fSOjOedbkgQU4FwpzzV2oevqoRtEKRQUw5zun1oSuCIFkCUk9l0CD7/fHM//rZ6T2QikFPHJ987hN3VHWjkOUyVCs2ULFKnmUQDB0ukF3t6dXBrMr2Irc6T9axPSLwzkQsfD7g8SAdqWyxYe1zgOA7PfRQvpISdyybTZfj9/f+e2ylLaDzW2IOXP62OsgMLj6NhAUbxXJ9Cfxd7NJHbHSlSPMMlm8gYGzbWVyndky19qJJxuCFT2AcOkA3FYY0EMRXwD4wYf1u9R/TUU6aUXvc8txN/eWFXwvv6eUbq6RowmqwOhD8bJTZi/C2Gv2dY9a10FVt5vBOLH6qImlAiVZVISw0hiYJFxxPXrmluosMSUTXCrN/TCI8voIvt+b5+L2pFDxgk7v+dPS6s/PcBWHka9cHTevIb+4HX9qGiqgVH6gd9qYUXhGGB4s0vj8tOD0jxVScw1k8GOQtcjy+AtytORO9QcKFYwnLbU+52vNPtS3jggM99L+/B4+8Ia1G1IB07N3qBBLEkiP025WxNSo3CieIyKiGZkEZKNGJKA8zGrtYS3ac1cssRWx0fvw/IeJ1qVJf8hAmRqvsKddqU3wU27GnSR2BviX4Zrnai6r+y/hgqj3fi5c9q4pJNpun4hx3CbR8WfrYeVMfOSymNHQ50DTjvTWarNkzcNrlAA32xtwnrdjTgUZ7A81VVC37/5FZUVCrbXRk01he+fuujm/G7VE/Da4iWJivphgSxJIhVV8vRTKTyQacbJc4FH3lLWWw6PX46Um8i2dckNMiqVneRMom9t/Dttj53ZEJJJv1sJFUbsXS9M77GQ3YSDCPqQ08ucdqSFMch70AkCj9PgBrcClfeevxHwpp5uQvT2PxSmaf5j+462oE/rAqFmmNSUInFtr3Q5+pwhrbb+Acpdh1tBwDsPCptMM/LCABfIBZvCJdHvkYskrxOBKAhrBAjQSwZkhHEpMi0jBZ7cEDJSsOrQLUN8E5NJrTVz+6vjF/88Gk3ySopqa/IrQEZaSQ6/SSUfqJg93pGD71IqKsnW67fPq6eBoOREUZccEHBxV/nf8+p2CYJpS22aE3nuxX7lFLViFXXd6MnHNxd4Rh3rLFHpnuUAWSWValXf71oomhrkohQ32aP+zjkOHSV+kYyJYe9viFkc/HHp7ZH/Z7ODy28vZB4Chgk2eIkinBg7XGho9uZlgbnoiWxxPerkGe6bPt2yV2J65E4G7HBH/qcXri9EqeXhZ6P/KzClqfK/U7O4iXqFgaiZRAWwORpeRNtiUnBzyN8KtXW50arRGxeIPQu4xfA6o9jbAozZFefGw++XhkZb4VKV9MobWPYZZfvLiNMolYIa9wi9yfoR0KCm7gj4/SRjnnq5c9q8PmeRtXTVYoqDl1PB9btrEd7lwub9sd7tK9vt2Njwv18BmKfyJf7mvH1eekP0vr5nkZwHBcXvohTMKG7PAH88oEvcffP5yvKOxNav5serMC/fn8ZLCaD4PXwgHjjd2YqTjt2DIitTux8F3pGYuBIMKY0d/aj1+HB7EmloveIrmwF2trp9uHDrXX41gUTUFJoSXh/qhwRCGidCaQEpt89vgUGlsGzd35d4nl1ULLwEE9DmN3VITcveTIdi/LTE0szXG/+ZBcIcjAahJ/gbx8OymHKW4+fH/9pqUgZbq8fv3t8C8aPSH+YvFQ0YvaBbcfwwl1oPDg14AZHrL8YZUiCsb4aE8krPTF2xBykh4AVb+7H5fPG4oJZIwEAH2w5pSiknFqkQyEWtsP7yVWz1U9cAaQRk8nbG2sFhTAgpEJ+hWe8KoSUqUEm4/Ft2BsfFy+ZlcazHx3Wxz5QDNbuQVuL2pZewQEjmUlShhs0RSS6/c/P7cTDb1ThcF0X6trsgmVQ8t7e23QK63c34rkMxYR7+I2qjOQTSyIbMa1OmqqpEPvXgI8np5RvQhES2l/xmsfrC8b+JNlvk1FYPPXBYcHf3d5oE4hnPjw8cAp78MR37Ba6P8DFuZKRi3iIoxTcV6hgwyYmCEelG/4P71an24fNB1oE20Opecmxxp7Ie+rt9+KDLacUPS8Xnz+IYJBDr8ODdzfVxpvQ0NYkkTI6Noh+a+MJxc9Ye9zoVWBIrFSQaexwoK5Nufr7H6/tRf2A4HL/y3sFV9aS28RJDrxR7it4aew/0YnfPr45tCXKY92Oeny45VTCbYEVb1ThaL3w9oW4sX58HfoG3lXEXiVNnGjqRU1DYpcOmcTl8aPyuMwVvMj7SNWkz+HyoSMJg301YZjE21D8q4KuDgQeV/PU92Ca0X/vONKOhvbEtotfCCw0UyHWHlhJTeMOE6hQHpk548VPqvHiJ9VYv7sxrixxdmdc6BDWX55P7PYoncLQzQ9X4O5nduC5tUfx8bZ6fBTjo0+s73Ich1fW1+CwRlp4NSBBLEOkY7BSi7AKXSliAXSFUKKFYhhg6Qu78NeXlHsTd3kCeOoDaa/Q1jRMiFHx6SK/hbxU250+fBnTVjuOtOP9LadEhSw5tMoJbxTT71ptzrQdjOA4Dn9/dS+Wr6lMS/ryyhD/978+OISV/5YXFD62ZT7cmuTqP6a7H63vxrod8eFkJJNQYchQeoqUf11ozo3EzeSVLWzb5fEpP5EnRrJVf/PLEwn794mm3riyiu1oxO5kKPly5LivSJiGgpv4h4TCi9iwrR0/67Cmc/BxDgdP2iIaRy3p6HGhbaDMff3RC32xHYCGdgc27mvGCo208GpAgliG0K8YliGUOHRNUU7IyzFJXv9wa11qGQggPGkNCuBiK0n+cXIlzhbtTi/e23RSURnDhLc61UYfGwfxpTh8Kn6l7PMHUdPQjW57tIYwtu+9vzk5QUyN7/3tjcLOoZOHET+MwIX/FerI8b8J1Y+/oEtd2E++BU8mCLH091f34umYLdH9tTbhUqTiWV/B1qTHF8Cd/9qGLQdaZT8TS3REj+jwHvyy+JLcvg1yHB54LT0Otvn9xT9w+C12W5bfFr39XhwYeGf+TIUwSCNkrJ8hYm0eYqltUT+UT6p02z1xJyyTJbFGUL1pvLTQImrPlwixUnpjV/uxK2W+Rox3LTyOi9tzDf5+88NfySojx3Fxq0Wxsm092IrzZpTHbDkFZQt9gWAQbV0ujCnL07VWN4xQK7MME+fq4+aHKyL/f+FPl6e3UEmixlZmrAF9wq+Md4OwUCYv39gDQZnkZHNikwa5oXukbMS6+tzIzzHBYhY+HKRUI9bZ68YLnxzFzAnFssoWSVfgh9gwa/ysfTFjmVxhz+n2w9qj/BSnHPi2m+Gxko05qMBfzP71pd3otnuw7Mbzk85TTy6TSCOmE+5/eW9a4iqmwu7qjqSNX2NJ7L9IlWwAAMUFFry0rpqXduqJVzf0SF4X1Hhx3KCPJZEirNmgLIxLr8ODXy3fiE93ytvmauxw4A+rtsX5E1vy6GZZz6/5/Dj+/NxOVB7vTNyOOhjXhIqYBfKjKvT2e+M0fHwYQNwGbuDlyd66TNCo2wUCpGeKNxSGRpJCTBDz+gL4w6ptuPtZ8QDUydpT8Rc88lyURJ+aFLrGT8frD6bsKFgJchZ9fLs1VmQXgb+YDffzL/c1oVqBecfxph7c//Ie9Dg8ehiuIpAgpiM6RYI4a4aK0lEmJ0OzKbpbK6pGkuXki6thoe1YU29EMyA2oEpNnLH4/EHc/sRWAMDWFCc6rwxHkQCw/XAonyfePYhfLd8oaQeUqq+tdMDxhOEwL35yVPJ+NdBC+Lt95Rb8/smt0T/yqsOI70xGLvDrH9mu5N8mtYXJI1Wb7lTaT80oJmJBv8PfQbfdE+eXK0xsE8htk9iDPXx8/gD21nRICjccuEgbhLPkn5b3+YNRjoL5r7LquLimMJlvo6KyGTc//FVCdzb8Bb/BICaIxT+3aX8r/v2VfBONFW9WobalD+t3Nepi4RiGBDFCF6Tzm8iEZ+hEXp+lyqC2ilxNGSBWiGmXc0BAQ4TaMnZe3hxjh8PniEgQbz3sYjR2OOJsiBIRW+yESk3+1qTgVxn67UhdN9olBAYthXJDKpG6YxBLip+HmAuO2L54TKbmxtY3uDiLfV/vbT6FJ987hPd4tovhexj+fiQTfe2dikF7Qykh7vF/iwf5TuaNfry9DsDggk4MP88peliIjHU1o8aJzXAaLMvoauFIghghiprdNKP2RRnIKvYUaCJhb9N+8Qn08XfEB790EOtdXupEa5zjWolq6kFYESpC7Ckx0Wc5TrbtkBYsfWEXXpDQ5sXi9voVu3Pgt9+d/9qOmobuKGfV/HcsdAhC6L5kSGW4kGtgz4/vKIaYRkwO/DFhY2Uzlj6r3N42Vlg4NeDRPpFneymn0vHacJkvK8FtqSx4+QcIwjtD8bFEUx9gAhFBTB/jVRgSxETYr+MBORtJOJyl8aNQ8gEnO+zK3bIRQuzEVrqIdVcitTLMOvuqFPqRfvWSyfHWlyew88jgthnDMOK+mCL/ib6+dkc99tZY4++DtJCipSG0QWanvfNfiQUjsQWkHOVMH8+DfSKH36LE5DMYTmrwwmufH4Pb64+cFm3ocKC9W1zIjBXE5L6qf7y2T/J6Khorv4CpRFho8vmD6OpzK9ruPlDbKWg7Fq4ryzC6EsTo1KQIj2VYS6FH1OyoWk7ocj/gzh4XXAlOt4ohdDpJ0fMZtMfrT+FEW5DjEAxyeOerWpw1rRzWBDEBY7H2uFBSaIHRILwG7HV4UJhvVmzn4w8E0WpzoijfrOi5KCRfgfz3w3GcDsQwoKJK+cnh2FrGakvrea5PpLYAhb45W68bT314CCNL8hKWI5UQUWqNNf5AMEqQlaLymDVOE/fGl8odZcci1utif3/6g8OCJ6nD78HAMhHBJtng2YnMEqTGMAahRcDxpl5MGFmAHHO06CF0KCws2D3w2l6carXjqgsnyC7ro2+H5m+xE9GhRQTvpKbGXvtJIyaAno61Dh2kR8c49xAqIvd93vnUdtmnEQUyAZC8el6NHlfb3Aun2xeJXydGrB8hya1JgVmt8ngnPt3ZgIde3RtzOlW6fK22fvzxqe2izlWbrQ7c/sRWPPuR8jBMq9dVY+kLu3AgRpOtzCO+Ot+9WieN04G4FxVO+roAUoKY0GS/fM0+1Db3RRzA6p33NscbgQudQgSAlRKxMVMhTjCOMcIPc0rMN+BAOU3Gwak+9tWoNdtVN/Tg3gG3EjHZAwg5NX7gtX14UqCt4rz9Y1AjFh7PrCoeZjOw0RqxgMa+yEgQE4DEsBBqGjMqCHGXel4xgkUm5OpBjViyKrHUy7BhbxP++tKeuBh8cVnFDcTytyaDHCcamWDNhmOS+YZD1Bw8GdqK7ev3RrVXeGtFrhaCz7YBY+BkXcD4/EH0OtQ50i80qegFsXedTP81SASkFlqQSJ0KjzuNm4JWS63vXSgSgrXHjUOnbIJ5pCW014AGOmzXObg1GX3biOJcwcf31Fix9WBrlAY6zoO+Su31yFv7Ud9mx++f3Irmzn48+9HhQaGMQSSKyGGBAzFCi5dYY301FSQsw0RVm39YQAtoa1KAbNaIWcwGeJLcXoulq1e9uISJhAM1iRUe0vI+46zYQ/8ku7BSQ+hlmOScgD7z4RHYRCbJOI0YJx6v8qsEW2H8yflUax/+tnoPCnJNWPE/F8NkFHaKqZS4U4Iy2/V/V25CbZO4EKekCyUbMizdMNG7MVF4fAE0WR14+sPD8c+IIL01Kb/B6tvsuPel3dH5yn46nnSehnvyvZA25++LL4q79tmuRtXz4wAse3E3mqwOPPfHrw8a4cfUUWoB8vxa+Qc81OLtjScinu/DrN1eL3q/kLf/IMdFxRtWcxhn2Wh7yYDGWmzSiAmQxXKY6HHrZPhin7oBdLUiE9v/4SykJiBpFxaplyEV/0lCvniO1nfH2Z1wSD5wOH/gqxnwteZw+fDBljoA0ZrMFW9UCtqkcByHo/XdcSc/wyRr6yElhA0VJOQwON1+PPLWfrTa5LsnkepuLrf8xaDQwSgpY/NEZGL8VmuxmxBuUIMVDHKRRlezjukQXPlboXLw++PLEAxyUfGGk1lQi425bMzWpNYaMRLEBMhuQUwPZsL6Ip32Z7HUScS5q5VYtX6p0M2AEGq+eo7j8NDr8cG7OY6D0y0sBInR7/ZhY2VzVJgvflnr2+Lb7HBdd5T9WZiDJ2146PVKPPmecGD3OPujLP6W04FYc/j8QUFj70ROpsVCGSlZxKnt5y8T4/cjb2UmwDTfcz/H8d1SqJdHOtrLnEDDHeS4KLsseVuTysuxcV+z4G5MrDZXa7tOEsQEyOatyWyIB5iIVJu/KebD+8OqbaklKEB9jHFsuM889Ib4AM0P8B2LGies1Hz3UjbdSr+PJY9uxiuf1UQFW5dT0prGnjg/WC2dIY2NlA+rdJC9I8IgDMNIflyxEx8AtHSKn4rlOOC2x+SFysokmRi/+zK0/RxdFU7k/6lRedya+CaFiMXfDPOX53fhjicGo0AIbk2K2IglGjvW7xq07Xvt82NY+sKuuHteXX8Mp3iLZhLEdEgWy2GaBttVi1RV5Zn2ywUkDuoOpF8zp+a2tNQrSHarN0rjIlNofO3zY3C6Q33a6fbjrY3xAuum/S2i36zTo0x7N5SRCnGUzjGvvdsp6YBUbdOBLB6+JTl8qhuHBhYgar6v5z5W34bMHLM1Gfu1t3T2R9lSCpkUxGnEBv6V8l/XZHXIXtQ+zFs0Cy1CMgkJYgJkIiQOIUEWNv8DCZwdAoPhPtIF3/GmFHJcdIieruM4VTQOSmTG8BgZGyYlXA6hLcwwy17cLXrtdKPH4ZX4tpS/U7lRCO56egfue3mP6PWwoK0WQ3X4Xrdz0Nhd71WM9RMoFmsy/A0LzbnxGrHQv1JruL88H6/9kgNpxHTIUP2Qs4XVn4pPrMmitcM+YNB9Q7rol2m7JUdLtErEBsvrD6r/fSTQjoUH61i7DiXBflNG++6jCp/sED65lsznoZY/sPp2ab93Sslm0xIpRHcpdUis1oofP5PPi59Uo6/fizoB34exvr3C7zWZsFMfbauLircZlxe5r9AfegoGejrSZFXmrV0OWjvsyzYqjwtrOyqPWdWZ6Jj4/4r5YfrL87tw18/mxQ3An+yox7WLpqRelgS02vpRWpiT9nwygVjA86EkvAyhqkTDq5fe39fH2+pk3bflYCu2HBTpkzF/h7VmyRxIe2+T9KItpBHTTi9FGjEBdN7HiSTQ+njyUKHH4U16mcKI/D/MVhENS2+/Fx9sqZP0W5VOlsvYds52elRyZqsHhupCmu8r7HQwn4lz1RjZmlR/HNBaI0aCmACnQyc/3dDaGHOo0NBhT3qhwh9AowZTRsCzegwsK+xAdN8x9U98xdLn9EW8/hPqk0pcSSFOh+Fbib+3oYJYeCk18Gu8Y0JbkwKcDh/y6YbWnpOHCl19HnSJ2Hskgu/ZPS50UgJBmWEYQduQJ1SI8bfizcQ+oYR8qhGEVpyOC8vqASfQck6oK8WvcVgy0ogJoPf9d0I5mdiaDMdSI4ThTx5KdSAsw6RtazLTPskIgpBD5kwRtBZsSRATgOSwoUcmjPVJayIffkxMBkxCcwCWkQ4yTRAEkSzkvkKHqKIRY/2AyQ1Z54zZAJi8oR/rTkvIWF9f8AMkN3bY8fqG45L3MywD/chh1JdUJfuDgRBpIJNBYshYX4ekKoexw6zIPW8Dcs+tgGliYq/F5mn7kHPm9sTCmNELPU8CbGEXci/4FOywQQNqtqQNjDn5AL5qobXqmRCnx+FN6JOqVSLUTlowemGaeHhgMRXCUNoCtqQNuRd8Bra4I8mEOTAWJ/T8HSeEDYDJ79G6FAQfJhha/A8hMimfz5pcmsHc4iFBTIBYjRiT3xs1IAticoMt7ALAwTJjb+Rn48jEXswNw0IheRiLCwAH84zdMIyIdrzI5DiQO+9LmCaHHW1yAOuHYUQDDCMS55EMjMUJy+ztYHJ4jkiZINgCYVsoy6yQV2PLjL2AwQsmxwHLtCrknPOVZD7GMSdgHJ28c062oAuG4U0D7S+M9NYkB/PMXTBNOpx0GdKCyTMgfCPU7oU2yJnAGYsT5hm7wVgyLLykkeqGHjz+jrBhPjvMCsNI/vcSBIxeMHl9SNRe7DArYOB7dg/CNPEwLLO3wziyEbnnVkTuM089AMu0kGG/aYJCp8NGD8AEYRjRiJyzNyX+Zpng4LsP/2R2heqVaweTq64TVCWYp1QhZ84Oye9NCWSTmzqWuZuRe94GrYuRlcydUobSIm39BNKpSQH4UzY7zArLjL3gggy81RcABj/AsQj2lUU9kzN3MxiDktMcQTA5TiDIC44aNAAmDwzDbDAMs8FtL4VxRCOCzgKYJtQAAIzlzQg6C2GeGD0ReDmAMXnB+SwIWMeDMTvBBY2A3zxwBwfj2BPgvDkIWMdHfgMAQ3kTAj3lQMAIgAmVgw0g5+xNAADz1P3wHLoYxjG1MI0LxfHyHD8Hwe5RADgwOU5wXktUeQzFneD8psjfTH4vGJMHlun7EHTlg3PnwVc/G+ywzkiafus4gGNgmngExuGtcFUuApvfBzbXDrawG2xeH9xViwAwYIsGhFezG+YzBr3Au3Z9e7AMZS0IOgvBuQoHtyaZQGipNdDu4fcLACjqQqB7BMAGEOwZAXAC6xSjB/Bb4n+XTXjSCa33jGNqweTa4as9Z6DQPuTO/wL+tokwjqqP1Cn3/PUAAG/dbAQdxUDACM6Ti+h1Ixf13phplfAc+hrABMBYXODcBSmUW3vE7MjC788LDozBD0NxB9iCkLsJ78kzwXlzwHlywXnywOQ6ADYIrr8IhpH1ME+sRsBeAu/RCwGjF7nzvoxLny3oilpcAQCb44TpjAMwFNngPnApEDSAyXHAOKoOwb6y0Pdk8CPnzK3w1s2BZVoV/J2jYRwecl5pHNGIQMfEwQQNPhjH1CLYU46gvQyWOdvA5jng2n0lwLFgcu3IOWtrVBlcey8HY/IiZ+4WAID74MXgXEUhAT5gAIKh4Z3J6wXnyQMCJrAF3aH28OYqa3wmCMbkhqG0DYYS60C6fYCzAGyeHUF7GRizCxzHAj4LYPCBMfgF82ELbQDDIdg3HMYxJ9Ay9gTY/nMR7BkJQ2kLDGWtCHSNQqBvOOCzgC3uAOcsFC8zExj4VpmQAMsB8nQMQYANRtopupD+0FjvC0/QHCLfmskdGlcj4wMH04RqBHpGxM0LCWH9YPP7ELRHa2QMI+sRtBeDcw6TLj8DwOADawnvOvDKGVsfIKauAveGhX+/GWxBF7igEZyzKDqpok6ADcBQ0g5f3RyAM4imxRZ2I9g9QrhMasIEQ2XgpIONC3FAg9jEsTCcCsuRbdu2Yf369SgrKwPDMLj11lujrns8HixfvhwjR45EXV0dFi9ejMmTJwMAPvjgAxw9ehQsy2LChAn4z//8z4T5Wa3pWQ2WlxfCarWjzmrDA5tfgKFY3EdR0B2aBDlXPoL20oigJIS/fQL8rZPAFvSCCxgBNhBZWXNc9F445zOBMaUWe81bPxPmidUIunPhOXBZtLAxcJ3NcYpq6wJdI8EWdkWVI9BbFtHcRdKpnQvzlAMplVVtXPsuB5vfC/MZB8GYQoNKoKcchmIruCADhh3s7uHfxQi6c+GtOQ+c3wwETDCUN8I8eVBr5muYAb91HBizG5Y52+Grnwk2z46AbQw4vwmcOx9MTj/AMeCCBjBMEDnnbELQMQy+lilgc/oj/cbXMB2mCccEy+E5ej4ss+JjJvrbJiDoDrm6VQAAIABJREFUyYNhmA2BzjEwDG+GoTjaI76rchHMUw7AUNQFT3WoLsYRDTCOaELQMQye6vPB5PSH2orhEOwZAcbsimgxfU1TweT2A0EW/tYzwLnzwRZ1IugqgHnKAQR7ygfr0DoJ/tbJYIy+SD4IGsB5c8AWdsPXOCMkABs9IaGfDQnF5mmV8DdOR9BRAraoE4zRh0D3SIBjwB/AmRwHON/ABMgGYRzRCM5riRLEk8XfMQ7GEU2C14LOArB50uGp3IcvgvmMg2BzlWkh/W0T4WuaBuOIhsj797VOgml0Xej/LZOBgAmm8cJ9I66sjmFgC0ImDq5dV8I8tQqG0g4EPTlgLYNafW/tXJgmH0TAOg6+5qmA3wLjuGMwjQlppgN9pTAUdcHfNgFsUTfYPOkxN+jOA5sT8m3lOXIhLLN3Dl7zhARhb+3ZEQ0jEBIkc+cPCr7e2rNgnhKt9QzYi2EoFN4G9dbOBRcwhhZ3jiJ4js1H7ryNAAD3oQWhvhY0gMmzw1DWgkDHeJgmH4a/dRLMk49E2sRbexYC3aMANgDT2BPgfObI4tB7ag7YIhuMZfFb537rGPibp8I4/jiMZSEB23NsHoI95QgtioJg83thKG+Gr252aCE6Zzt8dXNgGNGAYG953Hv11s8EW9AbSc978kwEbKPBWFzImbsFnN8EX+M0MGYPTGNDIXu4gCGiBHDtuxzG8tC3DYYL5T+iKSKouSoXAQEjmJx+WGbtAufKB4w+MCYPvMfnwTJzT9z7BACOY+BvnoJgXykss6PjOfrbJ8A4sgGBrpEwlLZH8gm/a0/NfBjKWuFrnA74cmAob4B58hG4918aWiCEGRCmcuZ9AQRM8Bw/F+ZJh+Grnx1aAJS2wd82CUFXAThvDhijF0yuA4GO8ci9YH0kGffhi8D1F/PSDUSUFBHh2egFgmxoLOydhLfv+2Ha5Iow5eWFotdSFsRcLheuueYarF27FmazGUuWLMFPfvITLFiwIHLPM888A4ZhcNNNN6Gmpgb33nsv1qxZg7a2Ntx88814//33wTAMfvzjH2PFihWYNGmSZJ7pFsRW7H4KJ+0ZjGNHEARBEIQmvPrjx9DbnZx/RLlICWIpb01WVVVhzJgxMJtDW2Dz5s1DRUVFlCBWUVGBO+64AwAwY8YMVFdXw+FwYPPmzZgzZ07Ey/a5556LTZs2JRTESkryYDQqV0HKoby8ENPLppEgRhAEQRCnAce76jBnxHTN8k9ZELPZbMjPz4/8XVBQAJvNJuuerq6uqN/z8/PjnhWiuzs94R3CGrF5RRfhw1NNUdtQRPbjqT4Plpl7orZ+1CRgLw5t1Y2XdsUg+Gx3ORiLK+EWWCKC/YVg89OrYudvfynBbx0LtrAbjMkTsnsyDm59B135CFjHCW7xc14Lgo5icD4z2KKuyPYf5zfC1zhDle/UUzMfTE5/nO3l6U7QMQwcx4huD6qFp2Z+nB1esgR6hsdt0Q8Fgo5hCLoKwOY6Qra+fWUwTzoi61nOb4r63rSAv4UKDI4jvsZpgCEAhg1E7GIj98RskYbx20YJbheLEegtBVvQA++Jc+P62QXlF2DW8Kmabk2mLIiVlZWhv3/QLsLhcKCsrEzWPaWlpaivH2z4/v5+TJgwIdUipQzHcQhYx8PdV4qcszeHfvOZwHlzweaHjIBdu68EDH4Yimwhuy+OgWXmHvjbx8M4slEwXe+Js2Geul80X+/JM8GYPLIm8kBfCby15wA+M3Iv+Cz0fP1MBDrHRNldhHHvvxQw+mCefBBsngMBezHY/N4om6kwQccwBHrLQkbDM3cj6ChCoK8MpjGnAIRsIzhXAQLdI2E5c5voIQVfyxkIdI+AcUQjfE3TYShtFZ3ofK2TEbCNhmniEfhq54LjDDCOOgXGEABjccbZp4nh2vUthI12wwbunurzI0a0YWN+xhCAobwRnv2XwTy1atCuZt/XwRh9EQPooLMQTE4/fCfPinp3rt1XgrE4wRh9CLoKgMDgwQR/xwRY5mwD/GZ4jlwE08SjYAu7BgzneeU6ciFMZxxEsL8oYqxvHF0b9/49Ry6I2GW4KhfBUGwNCSauQjA5jkhZvfUzEWifGOkPQOhQhaGwC8ZRDfAcmwc2rw/+tklg83vBFnZHbGFce64AgsZI/uG/wQRDNmRmN9iCHvjbJ8QdVmBL2mCZVhXqk9UXwDTxCIKuQjBsAKYJNfDUzEewt1zgbUUfXAAAv210yH5MyIBaBI+rAIayVjAmD7igAcbhLVHXXbu+jZzzPwXDAJzPjED3CDC5/TAUdg9cH+gzveVwtU9C7gWfRj3vrroMnM8C85T9ERsYAHDt/iYss3aByeuL+o64gAGcJzdKqPa3TUTQnQfzpKNxaZtn7IkIl6G2Gg7j2BOhQyOO4lDbdo2Ev20SmPxeGEc0INA1OmSvw7Md5AIG+OrmINBbFjIe7xgPsBwsM0P3BLpHwHt8HoBgxKYm6CiC3zoenDcn+h0ZvEDAHPmT3yYcB3hPnAP4LAi6CmAoaY/Y6fnbJsA4qgHeE3PBDrPBWN4Mb+1cBO0lEWN7Q3kDOL85YidbcOwHcPW6o2xO3Qe+FrLpYYIRu68wgZ7h8B47DwDAFnfAMn0wKLv7wNdCh1JM7oiNUthGzVDUHVVG96GLkXPmtsizQVce2FznwDO58B6bBwTZyBwAAL7G6Qi6CkKHeYzekB1jwBSydwyyME06DENJO9z7LwvZqBn8MI6qC9lOWlwhOygGyJmzPdSH9l0ONteOoKsADBsMzSVBFrnnfx66XrkodPhBxNidG3c8SsDyVJ8H07jj8BybD4ADm+NEsL8I4AxgLP0wjGgE581FwDoW5un7QrajR88PHbbI7wFjCITs7mbtAPxmBPpK4Ts5F0yeHWCC4JxFkfEr0iYNM2CaUAN/28SQ7VauPWTEb/TBNP4YfPWzosZHKXwNs0L/YQIDNqLRhy4Mpa2AyYNA+yT4GgZsHn0WGEfVwVDWCs+Ri4QPWfHgH+gCgGv+ZyFYjZ0Ups1GbNasWTAajSgoKMg6G7HGDgeWvhCa+NiCbhjH1wwMPDkAOIDhBF82k9MPzpMb11H97RPgb58QMpCcHu193VN9HoJ9ZWAszgHDRQZMjgOGkvaoCdlvHQtjeTOAgcHGkxcpQ3iQdO26EgAbGkQ5FrPPGAabqwvtHRzv9I8Q3EA6nyHQWwZvzfmDdcrrBecqCJ1GYYJx9WYsThjHngBj8EVOUwGhwc7XMDvqXragO8qI17Xv8tDk6TdJDjYAYJ6+B4biTnhPzUGwd/ig0Xb4XfBPTimELeqMGKmGP9LwAQe+EGeevheGYit8jdPgb52iOJ8wpin7wfUXwd82Of7iwMk9X9NU+NsmDZzuZGCeuROM2QPPgUvjn2ECYIu6EOwtA8CCMTuRc84mcEEW7j3fRKhNRE5TGXyhAU+B4COI0RMabBMMgpnANKUqarUceqfBgb4iw6SBN4kPPh/yI2aeeiDu9whsAIzJDc6THyUgc34j3PuuABDyGWgo6YgIXOF3wg6zgjG7eSea5cEXkFx7vyE44ZnOOADG5B74rkP5MRYnTAOG0Jw7P+4ZsXz8bRMHJ0s+TCD0LXt5xtfgQqd1+QbZfIweAAyG5xehszc0qRrKGxDsL447qScOBybXDs6TH+rLkuOcQLHz+pBz5raBU+AjweT3gesvQtxp5Ax7nWVyHKGDP12jE9w4cMaf4ULfsWrfX6I6czCUtiHQWxYS2E0ewGdO8Iw+eXTJ1zBlUll2G+sDwNatW/HZZ5+hpKQEJpMJt956Kx588EEUFxdj8eLFcLvdWL58OcrLy9HQ0ICbb7456tTkoUOHYDAYMGnSJF2cmmxot2PZi/Gn1ORiObsickIpSrBhgjBPq0TANhrB/mHg3CHBS4ywMOBvmwBf40zknPslGKM/bgII+Zdi4o5AnzttODp6XGi2yj3JldqAY562NyKMRbQMMeTM/xyMITCgPblQYQ7pGhA5GMcfQ6BrZPRpm9j8DD6whV2h1XBaBxyhesZrj5SncbrAgRlwexKwjUlqcmLMTljO3AbvqTMH3LQgSpvJcYB797clUgAMw5tgHHMydLov0q84wOQdWHikTvgEGiAgGKoIW2SDaeKR0Clipa4vElBSaEG3Pb2G0gQhxsrfXYJJ40uzXxDLNOkWxOrb7Lj3peQFMUNZM8xTDoaO8zfOQGoTIm9CZf0hFbhMP1bzp5ejrcuJ5gx5JWfMLphn7YSvdi6CDmFPxYzZCdPEo/A1zBJfKROETglrhnwtk+FvmqFxaRDRfgLJC2J5FiOcnqHllZ0g5LLqjksxfmxJdtuIDUUSBSBORMA2Bu7+YQMq/1S1Erzng8psZxiWyWggFc6bC8/+RQnuyYP3+PzMFIiQhCZg5YR9JcnZzssEnDdv0MlvkrDs6ao5JQjAoIMgttqXYEjCDHgx13aAM7AMhQ8hRMm1pMcFzFDGe/IseI6di0DnWK2LEiHQMUGBTVU8BgMJYunmkrkJbL0IzdBD/ydBTIBUNWJ6IdmF7thyfaz2ifRiNulbEBs+TNv4b4IEjQj2jITWiyw1MZBGLO2cO13o1DCRDsaV5+PK8+UfemEZ7fs/CWICDBE5DCzDJFWXCSOyOyYhIQ89DEBS6L18Q4Uxw2nhRQwlGJiM2SXaZFdpM8RQ2c4j2w9CEp13j4W0nZMRuvs8miy+TitN3NCYUlTlv74xDcUF5sQ3KiTIcZg9SfiwmF4hQUyAISKHgVVgrH9aDYoZINPbajdcNVPxM3p+4//zw7NQkENniTJBc2c/xmhgjmA2Db3ph7S4CmCAQFD9yTYY5DBrYonq6aaTofclqIAeNGIjilP31RPampRXF9KeqcvI0sy65khu/GcwLF/9FakasCzgD2j/HRLpw2QYetOPUQeG33rl+m/PwJzJ0ZqqG78zCzlmdW1VwzbeT95+Kc6dNlzVtNPF0PsSVCANQromKBGu+Cs5vVY/m1ab2WBnxzDADy89I615iL2z8Qnah2UY+IPBdBSJiOGMMcmfuEyFbLPjESLXEq21NQxB4VIt8nNMKCmI9oF5ztThWHXHZarmExyYwHMtRuTnygutpDXUawTQg0ZMDViGkS1VlauggUs3OnD3IouZE4rx/a8JhC9KI4zARuOkUYVYeNYoiWeAS88eg6+dNWiL9V/fmKZuuURk53nTy/F/vzhP9DmOI41YpkhmW1sNjEZ9n9qVR3QfNZFGTJJMzK38PLJl8Z4lU1tm0YUcpkL/YVmAkymJXXL24GSs164r56P6yRXqChLJcO2iqbJcQ6g5SAgldf7METBJTHZM+CHes5NGF6KsSJ3wO2LlAkKrVgtvS2JYjNGuPxBEIEAasUyQZzFq8s1nYmuyVMW+LESsjRNpxMRhmMy4huK/Ev6uUFG+GYV5+tSQUa8RQA8aMTUGRpaV777CaGBVnYDTASNjq3VcufZbgnL9sBmN6Z/+5OQQ299T2Zq/8Tsz8efrxTVdkTzBRZVtyphheO6PX4/8bTAwaTHkJeKJ3V7LFCad9P9U8Puj+6jaNmKTRxfh6/P04zxYDgyAuVPKBK9k4pPmjxvhKSM/x4gV/3Mx/nnrwvQXIAlIEBNgqIz/SjQuoQ6rV11YCDn10YMm2iLTUapRxb1WoXrzu3FhninulFrYBotviiVlLzR13LCE5Zg6dhjKioRPjP78yumDZeOiy8xxHFiGwRXzxwEApowdhvkzQk4w+Qa3i6+ZLUvQI+RjUdlYWi5DQXsUq+ExitQp2cNQBbkmXDhrZFLPagUHYd90DDNov5VOpo8fDPcVnjOCHAcDy+oinJEQ+iyVxny09ZTWRVAFRYIYb6DQqxwqZyxj9CCJySTTxsqx2tHw1lBYIzaiOBcGlhXUCP/j5ovwp5/MS5hH/IQz+PfX542L1Dk4IHiFCRvV/uSb0/HcH7+OojwzJo0qwjP/uwhLfjw3cl9BjgmTR2tjXD5UUXOLfFx5vqBgd9GceGHCmJGT2vF5XDg7fYKN2EQ/Z3Ly7hSyxc4pEQyite/8Wl339am4ZO7oiBulVKp8I8/mMTweCZ37mTCiABelsS8ogQQxAWpb+rQugioYRLYmhYykWYYZ7Pw6lcTkCFnpGrPScQpSTUFMyFg/VqCK7QuFeSG7rPCqPrz1K9RnCnJNslb1LMNIKlbD74cLRr+r/7doSnQaA4hpGAh98qNLp2A2z4dT2J+eUP/0+VO3ATxnqrR7gpGl8YeQLp83Vlac1WRCvYltt6aiiWGGyCdgMLCipjLfvnACbvzOLEwb0LpLtddD/30xHr3ta6LX+VvtEUFMIONlv7wAi6+ZI6foaWeIvGJ1GV2WWR9QgqggUYQm1vgOOE5ggIkSxHSKHEFAaMBPlaU3nI8//jSxNkgpE0YWqpLOOVOHJ9xV5jhx28fwbkG4eYXuk9uqLMMgT8LmiL9VwO9wYaEwEZl2PCx16jSb+X9fn5L4piQwmaIn2/D/hcaWySq4zZg9qUTSIP+m784W/L1IRn9LxnYudlv+HzdflLJd0lDRiM2ZXJLQWD88FkkF4i4bliPr/QG88Ya3JfrwLRfjkSXigpwWkCCmU1Qx1hfxXiH0XbMsExFidKoQk9Um6RizJo4qTMmg+effmoFfXT0r7vdEvrTkUphnEm8b3oWviYQMuubiSSjINeHnV84AIPb+5TUsw4S0WIPGutGp8QUxJYPPnf91Li6ZOxozJmTWY/a8aUMzWPPIkjyMHZ7P0yip8+EwGNQ+TBxViPD7j039R5eeISmwK8tTvOzDCpI/gKR0cnz8t5fEablHluShOIUyANkpiAmV2MCyUQKR4A7HQN9Rsm0tdUAirFjjC4ClRTm6c2RNgtgQRujUZKybAP69jIRGRBfIksTUzZIfC41vJC7XIB8IbestPCteCEp1fA2vvgNBTla9f3bldMHj2+NGFODx316CmQNbSkKvX25Zw1pLg8g2Z1gYnDmhRJE938yJJbjxO7Mi6d/9/9s79/goyuv/f2avud83F3LZkPsNkgCBBOQqApFbQbAoXrgoKhS0WMFWi8pXqVbRatuvtkWL+rK10p+oFNSvpVX8Wisi8VutoogNRm4mIRdyISHJ/v7Y7G12ZnZmdnZndjnvP5TsPjN7zswzz3PmPOc555qxGF+aqthkzkcoxRxKgQGwdfV4bFgy2mdbqed1THo6xuXhYF9HhlHGwGAYBtFySmEN//b40lTBNssk5tUT6i9y1RXyDmkRoc0fQx7eUu+BxrFYLcXzLRS+UD5cc3LGmCzR51MDMsSCTKk1EfMn5gbs/De5rXnrOZ78G+aVcQ4WOsY1iISyHSZlcK+fkOOzzR1XVTv/7R4kLjY/G8Avt7/Dq+NNcHDIxhMj5vm3XqdDhojSS/4Y4o7rnzt8rQpZOy2vnF6AbWtqUV2Y4pchWpAVj5sXVgR8w4MadlgwqjIwDKOYkekxaTKulz+PZ5HxfJYYEaEQNSUCRpIbt3yvArVlac5dtg5mjuOefPl2BteWpeHelTXuImNWTbYoGQB7X3FX6U5WOIOY3IJcSHnpCyTrF48S/N7hXeXbNQ34Hlsc37vvqJ09XvgeCI0BxTmJeGTtRE3klxSCDDEOAvkWrGNExjrJFME9XoLRedeaZMD9BuEeIyZ1IlYypi5GoCSF0vdlbLHwQJ9liUFGMk/ALs8lkiShn/o4BiulE59y3X6xBq6jb9dPyMH6K0Zh6fQCr+/Tk6LAMExIFJoX2+dy0hQ0niRclhkyc0wp+Sixr5Fj/GDcat3qGM9xguE4To6MDGOv67pmQTlK3Jati7MTOKtELJiUyxsIvmZBOXLSYlE0/PIg9RoxsMcvAUB5bqJHGgUAsmsqqpXnjU11kfAyfXSkXc5IQY+YL0PM/n/3seFK1hjCxteGnqS4CM17tskQCzJDrPxJgSwOzTV58npndIyzvZoOsdwM/wLY2TpvuEL+0ouQnRDHE2MgJV+Qv0ODY7AaHLLxThpeH4sYkDjvv9ilyeF2Br0O1YUWwezpoVBrUOztLMxK8N0oAAh5H4RQ1hBz+zdcgdEM427UMx7PphiPmKi8gTyfb7q62mvyvX1ZFRYMlx4TOrNDZDmTd32tFUun5ePG+d678basrpV8PoaRb8D5YlrVCEXPt2RaAWrL0nDj/DKvCzy3zgoAPmPEnN5UnWdfeVKgHmU4FI8PfQ1CEPfuNyaA1eH1Oka0UeWedkDNpUmhwdfXuFg/IcerjT/xFVwDhWPZKDGWOwBXkiHm52ToMMT4ajLaIGxU8y2v+rNr0ss7ItA2FAwxsZPxhYFB5X5Tgoku901f6Dmrr/W9ZA+4YoHcz8Qw7rtwGY/PPQw2kd4uuY24rkuWJcZLb66xTv74x8Bs1KO+1sr5olaUk4iVl0uv6xmoFC4lVv83vmy8stL57/hoE9YsKEdqosu5YNAz2LF5Oq6Yat+l6yufq3NpkjWOCsWdGUJgHPFF6GsQAALpxPTK7RTA39JxbZvkGbh0OtcEoGawvj8BvHkjvDO/+2XscBwbxREY7D5xBXOHk6OcU2pCJD5rbBN1jBjpxO605cJ7ouPvS0pMMIHuqWL19qcc0w/dJjOpyM3YzmcEp8RHiN4A4fSosERwBuu7vQgyYHk5IGZpUr5HjAu9ztMwBOz95783TsGTt7s8Lo4XFDH3fu33KrzOGQ4ouavQfUwoH5kk2Na1NCl+bFC6rJQakCEWZGw2iHpilVjTZrjsMJ62OoZxyyPl/f1kntQHSiOkNvura9xK5jiOZRsC/lxHrjnOEa/hHrcxtzbXGRjMNTFyiTC+NFW0bNfNKeb8fNmlhbjq0kIsnpqH3r4BzjZytOc2nrjPNGlUOspzXW/WUvJWaj1uAxAvoz+lW/LZweMSLovcMDuhwHGxOrtyhHkuI7lixNz6EsOxNOnj/JJjtGQudUaYDB4B8Vx68TFO5IYCLcCOWYuOEIrHDYwMc2utgt87YpwdiYCFcMQcunvgQhVtRAFeRNhsnsWO+fq7El4pvY7xsqr4HjDPpUmOpSmBB1NJB5rwG76wkcV4N8EIvmB7MbJwKH3NrGJEmAy4YmoefvTf/wBgf4O2DTmO8X3en91Ui7TEKLz+z+Oi5MhK4Q4Ej4ow4LLhXV2+Bk73ydEXQukr1l8xCn39g4iKMOKDI9/h+jnFMOh1WPXg34bb+V76ceeOZVWik7mqgVhDxx+PmD/l92R7xAS8kWLHHqfBwvO5zm0Hpd0D5taI4TiQBdfzVz4yCf/+z1lOWX1dCbEvCUJJaP2lYqQ9v96Safn489vHlP8BAHddOxbRkUb85Lf/9Pg8Jy0Gl9fm4Pf7jmBq1QiUub1ALb+sCC+89aXzb9H9iqcZn5nt67zXzynBiJQmTKxIx8dftQi2vevacfiuvQeHv2wWJaqWIY8YFwo/gO7pKtgOMaWXVtzHUB0jPkZMr3dtZ+c6JliF0KXEiHm1ZLwNgQiTHk9vno6JFdIzpNsTUnqSGGvGjfPLkOQWJD00ZMMgT2wDj6SCH7vj144pmRaykCFWXWhBbXk6Rucn4ycrxnstL0o1DEpzk5AVhHQNchHrHeIqciwWdh4s91/8zY/4g5QB+UvhRqMSy8Lcxr0rWN9zKdDDIwbfsXBcqhWx0qF0nef2BHPBea04OrvzpUXiRCDmViTGmvH05um43IdnyB8izAakc2wCY8BgdH4KHlt/Cb43Oc/j/kyrHuHVNtBwXa+4aBOumJrvrD0rRFSEAbnpcUGRNdCQIcaB0rc1OzXG+fZhr+zi+xeSeILBpcAw3LUmucgfEe98++fcYixxTucq8isGwaVJtiHmZZh5p0Rgho0zqRPWDfNKvVIvsHFkj480G5yTj7Rdk77bjkgR53bn0s/9lnH1uUSejN/cwfri9PKKEQtwFFegh2Ax3ebelTWyC5GvuryUM9mpA6NBeMccu7+tWcBd0of9XCiy08xtR6TzX4y7R8zTqGEvYbL5+S11Hn9ztamvtWLNfJeOXT0XRIvrfq3GDKdiKM31jlly7ZoUfWp7e9HVJ6T32ntW1Phu5EDGCxjDMJ451ESKmDa8LOi1vC4gyo+WVaHUmoi6cv6XYylXqDDbOzY41KClSU6UHd7dkyfaIG5psrY8HWNLUvHcG1/48bvi29oz6w/LyGmHeX6YNyIOXwsUR09N8C62K1YOsXBNYOw8ZI42Uj01Eyt8x8TdumQ0BodsMOh18gwxMU3Fjqkc53KffLmMqytnCBuavs4vBq0mBxaLmEkzJy3W5zIKm3WLKvDx0RZMKJP3wuKALR2fMWDQ6zA45NrZyY4R89zRKDJGbPj/HvlcwbiKyLu/CDKeS4P2BNKuv5PizEiJ9xwzuOQw6HWoLU/Hywe+RkvHeXT19nMr4cbWVePR3NHr4b1dNDkP44pTkc2V/01unw3gWwGXd14qvuJvHZ7pCJPe64VqZb19t+ekUel475PTzs8tCZH42U21khwHZblJKOMwgD1lFX8xK0Ym479umICf7vhA9DFagzxiQUDnCr8aDtZ3fcf3zDMMMK1KXrJG1+96d2YxJTi4Jm32R2N8JPeTixTPldckxNjd1fmZrrczxyQRiOShDMM4B3dHjBD3Nec5XsRviJ4TOBpOr86CZdggZhcYL8yK5w3WdUykrjqEgfc8aRWx3dEmce2+siAFq+eV8exeFH+1xRr+7J1lQh4xrpcorgzz7uPEldMLkBhrRk5aDGvXpGv5ku0RYzzO5S2H0LV3vHCdc/OI8TXPSo1BNatmqE7HwJoey+NJdnjxPHH3GAF2r3kwWTR5JCLNgckp5lg1eGTtRGxfNwmMW79KS4zE5Er70uXquWW4Ymqex7FpiVE+PbdSkTpcZw6HBnAtyYYCZIhxcJWEcgjVhSm4banw9nPGh7eJCyU8CR67lkS1F/CIsT7zZdjI3REnvDTJ9oCxouMTAAAgAElEQVR5+wN0DIO7rh3n8RkgP6hZLDabBI+YxLUPMct7XKeKijDg0rFZuGZWEW5eaE8w6cjGL2jwDv+ce1FyufczbjgQX6higj8E2uEm9sXAV8bwQOG9S9j1b3dDmp1rSSiH29hiC25eWO7MlVdVkMJZc9E98emcCTnYvm4STEY9a2lyuA0roSs7ep/r+ukEDNKrLytCTKQRi6bk8baRC9+uSfbLDNtr7u8Is6JeOMfY/Ekj8esfCscMAsIv975IiotApNngYQi5l6YSi78bHbjSV9y2tNKjhB+bJ2+fivtvmODfD6sEGWIclIpMdPfI2olYu6gCcdHCk4y7G96+a9LtzVC2lGIQ750BXJ2By3hjG16TR/NnZfZHJ6EJ33vZkX0s1/ns/xdbt04uDo8Yl4HKp5Eoj5jI+d1R1JbtqTTodZgxJsu5M/GaWUUoyUngTYkBeNqJ44otfmX2To6PwJ3LxwR8gCwfmYTxpamwuk2Wjhg+fxA7ofiza9IfGIER3L2gN9sDJvTCwDAMxpemOT2mjmvgyFvnPMfwF2yjrnL4updYE3nfORh49n8uj6LQtS/IjMcTt06WHZsnhJQdxu4EKuUDm/raHFG5s9hjgZSgdse9HVts8diYFCzMJj2unlmITW5G4Oj8ZMGlfLNRH/AX7kBBhpgfJMVFiEo85+6GF5lGjHcCdn/L9QVH9grhh1HAI5bAigHgSmzqIFlEDhg+hDxtI5KjPQJ1fe6ihGtAKcpOkFTAVyrO5Rg3oVbPLUV6UhRKc3kMe1FjhrgJPj8zHjs2T8f3hku48JGWGIVNV4/hr6HpLh7DYO2iUfj1D6eIkoGPouwE3pJQSpESH4GbF1Y4jcbi7AReT/XSafl46OY6zu/YiJ28RuUlK7YsIim2k9XYIYOV5b3RiwzO93z2PfveXdeNxdLp+c6/59VZUT4yyauM2OKpebjrurGYVp3Ja9QwDOPR/7nsWPZLWZbFR59VaA529/QBdiNf3JKgNAEuG+c5HrkfnRIfgQiTHosme3v8lk4r8EhAy8faRRV44tbJLkNZgniOS8+VHy9Y+f9mjstWJPt/KEDB+kGAYYDIYcNFx4gb2vmWo7JTY8QHBjPSlm5cCV29j8qT+OYp91EVflO3b2L47Z7Phv/2bYl57kAL3HsHV7D+pFEZmDSKP+ifa9nLZNShzJokOfjbeT4Fx0jHqcQMvAkxJrR39ftsF2jE9He9jnHGzvlC7JwTaTZg25paZz41f84r5RbqGAabr67GQ39oAGBfPnt4w2REsTwmBl+hBELfDQtrNuo9jM34GDNu/36VV3u9Tof84SoXCy8ZiV1/P4axxXaPdKk1EZ8fb0OWJQZfn+xwHiOUu9Bs1OPu68b6fMFTrOuz8qNtvLIyIEvgQsbdz2+ZKHisoAPALY9bTKSRN9+bEDqBl3JCecgQCwIMw2DZpYXo7h3A4il5+KKp3fdBww/AAzdOwOnWHvzy5U+GzyXhd8HAa2oSEYM1xPGd5JqNMkdFMXnEIs169PYNIpZnhyTfZ4EcVPiWacSSHGdGa2cfdAwj6G30hZLvqlL62sNrJ/qVXV5ppMhePyEHbx36FgOD3j0/mCWrHLAv4z0ranDfzg852+p0DIpzEvHgTbXov2CXv8SahObmcx7t5GxWUeJu1k+w4tIxWc5dmhuWjMbp1h5Y02Pxn1OuXddcXcdlDNiQafGda04pTw07K4eYKgD2dgr9rkzio03ITY/lyGkn3RJzzgV+1J0lxENLk0FAxzCIizLhh1dWwpoeK2m3XEZyNKrl7lBk7BmTuUjmWPd3DiQcI4LQGzXXAFKUlcDxqW+EJwz7d/esqMFVMwu96pb5uq6BrKF55YwClOUmYvVc8Tup3Aduh8eALaHNJtGAVNBwkDKx6XU6xXdOyYJ1sbavm+TdhqXX0ukFePmheZynC5QdJjS1sw1aodQFaUmuMi9CiXHdlyaDbVu6p8owG/Wc+gh5xIJt37uWU4N3oZ64dTKqC1MQE2l0poqQSl15Om5dWum1quC+YUIsrphmri/Fy0QeNXGQRywIeNkWQRwIJ1ZkYMdfPvf66W1ranG+fwD/+PS0M3s74/YGykZsjIkDuWv7Qh4Ix3VMTYzCZeO4Mke7uOvasWjpOO/xfSAHBUtCJH60TNzuIrfUSk7cN3O4y8kn8h3LvJeE2Of0FxWcQYqTKDK/Ed+kq0Y9zMEhLp80N5kiM/q7B3dPFZkWp7YsDf/vna9RWeD/pgcu3C8td/oK/vGIi4QYexyio16hXK6bXYwnX/kUC9wqojhIjDWj7Vwf53H+dBXHRqQnbp0s/yQ+4JKvrjwN35zp8vrcYcz5k9yZEA8ZYiIZmRHn4UqXAmdNRB8o4b0R+h2jQQejwYTZ43Nc7QXeQNmlbAKF4K4XHyOd+3XOz4xHfqZnxmW1Ugzw4p5XyXG3fIgYadZjTJGFMyM465R+EwpFuR0IOHP9O2+gLoHAecXuwBTays9GztLk5bVW1JSkesTTKTkJu6eD4FwCE/LKcDAqLxkr6ktQMVI4WagvinMS8YsN3AbR9XNK8Itd/+fX+ZWGIwBFNDfO5+5DrrnAvycqhIYQVSFDTCR3XFWFgUEbNjz+ruRjOXcM+SBgJoNgkLCARyxI24J9BesL4et7rRlinB4xt/+y/wkAv7ptStAMpFAeRJW6RmrEiIkxxJZMy5eUld/Doy34HLi+YxgGqYmBS5BZ4PaiJLQ7T+xLKcMwmFLJn1ZHCfKGS/lw1YrUqqdIzrCnVLC+xoZczUIxYiLR6xjZSSnFDuZbVrglIlUooavXZwKDBSPglBGTt0YJBB1ifp5ba4OCxwYIt6XJNLfJj7171peBoaSRptWJRQiuW/zAjROw8nJ5cTdK2mHuCTuFTjs4KCKBr8Tfdo/x5Dy7yrea69nUCYxHahETacSOzdOxZFq+95cSr2HUcEiI2OVzubiqG0iJERsO1pcZoBfKL3Fq4JdHrL29Hdu3b0d2djYaGxuxceNGpKR457l69dVX8fnnn0On0yEnJwfLli0DAPT39+O5557DE088gffffx/R0eLiHUINoaK+Dgx6HXLTXSkilBl8uHYR8rfWCbyBCi5NKmjhCHrEfIx0PgcaLY3oACaUpmHv+8cxvjTNOeDZbPaEja/8739knZPGP28ykqORkRyN3+87AkDaNVLSsI2NEvcil2mJRmvneeFGEsVy94gFctOKXLiD9bXZm/lerKVKO606E62dfZg+xr9Sdj6Rlb5i+FCBJWNxP629vqZF/PKIPfroo6irq8OaNWswc+ZMPPTQQ15tTp8+jWeeeQabN2/Gpk2bsGvXLjQ2NgIAPv74Y8yePRt9fdzBj9rC3vsyfSUV5DqSvTQpoo0a7huhmAzJ6StkIiZ9hVy0sjTpGNxMRj0evKkOi6fkoSDLvkxTW54Go0HvStwrVWQFb1NIJqlW+BYHbNckz4kXTMr12g3MebzIG71+8ShcN6fYI7SgpsSPQuMBuh6cm/NCsf9JwGTU46qZhX4nAvbV5eU8Eq70FTIOJiTjlyH2zjvvoLravlNszJgxeOedd7zavPvuuygvL3fe2Orqahw4cAAAMH78eGRnBy7beSC4Z0WN70YsvIwLjhGGbSPw9X9fxoT7G4z0Eh1CMWLiu4qv3xXa1SQYi+ZnjJgWPQEOKvOTce/KGlw/x3MJzQaJ9UIVlEmrHgkxKCU634uBY4ee0hRmJSh6D6uLLJhWlel8kYqNMnIaeo6aoIkqlLPhI9T6X7Dlvfu6cVhZXwKTUdzYLKlig+CuSUJpfC5Nrl69Gi0t3lm+N2zYgNbWVudyYkxMDDo6OjAwMACDwXXas2fPeiw5RkdHo7W11S+hExOjYAhQziKLhTtnj8US65Ws09G24/yg4DmTkqI9zjt5TDaef/MLLL200LkkxTCevx0TbeaUxWwWXt5ISHDLfB0f6XWOfGsSkuO5s4qbh2MWdBzLkGmpnudxPy87tYVer+O9jgCw465ZaO3oxY3b/ur1XZzARBAdxX1NHCQmRAt+b47wvHaJAoHIQufxF3Z/cJCa6lqadtwLg0HncU99yTXoZjD7q0NMrPD1VuI3/MUxYUREmmCxxDqLW5uMBl7ZYmI89RLSISWFOzfXLVdU4mfPfujzeHfi41zPHd8x8fGRONc36LNdrI97w/4uJsr+8mM26jmPW7GgAlFRJsy7JA8pAlUH4pu7fcomF/b5YmPMvN9pETEyKqmH41x/2H8UABAZZeI8f3yMCR1d/UhOFB4f3XGMP3qD91geHeMao/nOV5ZvwV/+cRzjStNC4t4B6vYxn4bY008/zftdcnIyuru7ERcXh66uLsTHx3sYYQCQlJSE48ePO//u7u5GTk4O+1SSaGvr8et4PiyWWK+M1A5aWs55xUk52ra3C8vT0d6DZpPrWAOA394xDQa9Drv+/pXX+QDgXFcfpyydPDlsHLjL0tnR63GOa2YVYah/gFfHC/0D9v9f8DYsO1g6up9jUkU6dr19zPn34OAQ728AwNnWLpzr4S6H09Pt+jwm0oiu3gvOv8+f7xc8b3tHD5qb+Q3VqrwkvPlPe1+846pqzvv2g8WjkJEcJfg7/nL2bDfMPl4r+533YshDTl9ynW3vFd3WF908fdCB0PMSLBwvMud77X3jwoC97164wN/Pu1h6NTef4x2Ez57t5vw80uC6gWKvQUen73vT0dGL7u4+n+2E7g3XfRm4YO9P/RcGeY+bOyEHNoHr5pDPl2xyYZ+vx22MULuficGXjIF6Xhxeq94e7vHxR9+vwluHvsX44hTRvz8wPAf09Xv3FzH9s3hELDZeWYmCrPiQuHfBGMuEDD2/lianTp2KhgZ7jbPDhw9j6lR7IdKhoSGcPHkSADB58mT8+9//dnaWhoYGTJniXxFhreErIJEvON/jHOylSZ7lqAEJyR7Z+Er+6Fqa9P5OaMkw0xKDW75XIXju2eP5C9y64x6s/zCr3prvYH3Br1Gck4jf/GganrlzBkp5Es6OKbKIKojtD0YROdkWT82HJSEC188plnTui35pUswqrgS1FL0CCsom9d6UDeedGy8h5QXn7/p1tDQc+cDYYwchjUxLDFbUl8BsFL+KdMXUfCTGmjkrs4jpAwzDoCIvGREmypAlBr+u0saNG/HII4+gsbERTU1N2Lx5MwDgiy++wKZNm7Bnzx6kp6dj1apV2LZtG/R6PZYuXYrc3FwAwLfffovXXnsNALBjxw7MmzcP+fkc24I1gD9zkpwJjW/MFrO13fXD0n5TOH0Fv/Egptb02OJUvHmwySUXzzVxN8TMJtbA4StGTITCgSz87Yu7rh2Lk23nBZd+HGSmROOhm+2G6BfftIn/kYs9WN+BQkYk77MbwHDD88PeUEEkqje22IL7b5jgd2C40lw3uxjPvfmFs7qHOzlpsXjx/svRfa6X40gikGSnxnCXBwMoSCwA+GWIJSQk4P777/f6vLS0FHv27HH+vXDhQixcuNCrXVZWFtauXYu1a9f6I4bq+Oup4YRnoB/kKEwcHWFA93kRg7cPhIL1BTPeizm3j7+dvyMUq8/xXUp8hLOUkdYdOPmZ8aitygqoC1zR3F9av6AcKG4fqXAJHCV0uIwTB1LFYhiGoxi0+kwalYETLd2YWsWdiDU60oieLh+pPAgixKGEriLxZ4KTk52b1yPGsZ/4vlXjOdtKldm93qEU5GxG5LskUvOIPXRznc9zEvIIVjWFQKCU5MHOrM8AaO+yx0YJJfoMyWVjDowGHZZfVoQsC3/BckJbJMXag/Uz6Z4pBhliYvFnaVJOSga+GDEOjxgfFyS0tYvCHSPmazmDbbhxGoBeGTy4FRea/DkrBXDVawwzHLX+RmYEZ1fPpquqUVWQIqmEjlZQOkMJn72TMGwkWdOE78nofOkFsx0bWRIDlCKDIPxhTFEKVtaXYNtanqVLQjJkiCmAr2B9OReZ74wDHDFibKNm0ZQ8AEBeRpxXWyH4silvW1MLwB7PwQVbIp+bFwRl4P82gh0zdpGQFBeBh26uw53Lx/hsq0Qm6xJrIjYsGS0puFdzyE9HJ6ptTKQRj/5gEu66bizvsTfMK8WGJaMl/Jqdq2YWwpoWi+Wz+DdqqOUQCxNHHOEHDMNgcuUIJGko51yoQ1saROLP+CMrWJ9nPhUTqzWvzoqVCyrQ0tIl6TedMWI83/OVaJGTKJVPDT79EmPNuHRsluA5w3mSsIgI8CcApaPEhJ7dhBjhGoFGg17y0iYDIDc9DvesFE4cHcZdnSAuOsgjxsOqy0sRH2MSzALvICDB+jxMqkjH+NJU3H3dON42DMPIMv6EShxJ+Zzrenh/xrNrkkfulfUlvFuhHUtoZKwQjr7I2QeHPwrWztmBAc/QAEVNxHB+6wDws5tq1RaBIIIGecR4uGR0Bi4ZnYEhmw0DA0N+BcfKS1/BPWwbjTrcvFA4Z5dcHGJKrckoxyPGd0nkBIivmV+G1XNLhQuTXyxot4pTYGD1vRX1JXhm3+dYdmmBV9Mt19dg/+FvMbEiXfTp/QnWlxLPKZXwNsOANIGqFwQRbpAh5gMdw8DkZ6yMrNQPfBOqHxOtL4NQKKGr/XsekUTI5H6s3WPH047nWgndA4ZhYAhSUXKtc7HZYWxy0mJx70ruXcTW9FisurxU2gn96FaBNMTUs8ToOSMIpSFDLAjIeamWMqH6On+ESY/z/YO8MV6u8/DnEbN/zn3ckM0mIxZG3K7Je1bU4OjJThRmxUs6/8XKxW6IKY0/GTwuSEm+7EDkcxTstBoEQQQOMsSCgKw8Ygruw3/gxlp8c+acz9I9vmLERCOqBgb3x+xrZU2PxbhRI0KiXhkRjmhzaTJcKc9NlGfAEkQIQ4ZYEAj0yysDINMSjRPN3Ujm2FKcGGsWTA7pQAdhjxifHl4eMTFLlXwyBPFF35oWi6qCFMREGvG/n5wK3g8TIYM/z275cH3HQBCu/rDbl1WrLQJBBB0yxIKAPI8Yz+c87e+6dixaOsTVMeRDrkdMXmZ937UmA41Ox2DDktH45OvW8DHElM5oepEj1xCbPT4b1nTpCXh9/ZzRoMOFgSHVyhXRiihBKA8ZYkFA3OBlE/jL9w9EmAz+lwlxGGISI428PGicGfCF/3agtaLExMWN3N3SgUqGe9vSSpiNeuSNkJasmSAI7UKGWBCQNZir4NlwTB4RJgN6+wZFH8cWNSZSeFMAFzfOL8OovGRZxxIu4qLtZXFyZXhjQhoZz1hslBGRPLnpnKeVK0+AICOMIMIPMsRkUJSdgPP9A6Lbi1tt82zEm72C4wulJos5E3LQ3N6LeXW52PLMQdHHsWW6aUG5Vxv2Lkn2ci3DyDPgCE8iTAY8cetkRJpDuDxRkHjsB5d4PDxXXVqIP+4/6tFGrkdM7nsULf2FHgVZ8TjR3K22GEQIQ4aYDO5cPkbSrkZxg7lN8M9gEB1hlJUsln0tRGW4pwknYJBBKw52POJlNdlehphUGIR3ChF6bL358fIxYX3PicBDhphMpLwpywrWl/KNyqOjnEFISOSl0/NhiQ9euSKKbw8DFL6Jk0al4z+n5KdM4ZKG+ll4wjC+itwRhDBkiAUBcXYYa2kyhEZtqSWRAGFDtn6C1R9xCMJvrptdIqsmJcMww88u9zMxtsiCpu+6ZMtFS5cEEX5Qcb4gIGtpMoTgs8OWzfCu90cQoYD7Izu22CL5OL5nYt3iUVTQmiAID8gQUxm2U9vxF28esSDba1tXc9ft84BHKMcOPkDbb/Jalo1Qn3WLRolue+3sYgBAbTl/YXG5GwAIgghPaGlSZfhydmnFPzbCR1kkABhSwGikKAvCLxQ2buSebkrlCEweneFhbBn0DAYGbYiJDIPhlh5TglCcMBgZtM2lY7KkHeDcduVpxUSaDejtG/DwMgUFEQOvzWZz7tTji6sJZsZ8qYRQOB4RJPx5MWB7vP5r9QR8+p+zKMpO8Fcs9aFnhSAUhwyxALN8VpHg995LkwxssHkZB1tXjcfRE+0YmRHcZI6iottsQHFOApZfVoSKPFd9Pff5KD7YBiRB+IGSDra0pCikhUnFCLLDCEJ5KEZMZdhLk3wTQHJ8BGrL+ONOAoWYeBbbcLtLx2YhLdE14ej1ru5Fua2IQDC6IAUAMFLhSgJqxXFpPX6MvMcEoTzkEdMYcgtvqwlfqg33/Gm+JhiNzz+ERrl2VhEmVaSjMByW/UKCEBqYCCJEII+YyvDFokgtvK0mfEajXu+pm0FP1hahLEaDHsU5ibKSJhPS4duYQxCEfMgQU5gb55c5/50qotQP2+BKiDEDsNcM1DrTqzMBgDcI2cAK0H98w2RsXzcp4HIRRLiiur1JhhhBKI72Z/sQw2x0FVuW49Xa+P0qvHWoCZeNk7jbUgWumVWEhZeM5N3JGWH27F6RZgMizdTlCCJUCSVPPUGECjQrBhAxcV7spcn0pChcO6s4QBL5C2uHJ8MIptPIHxGHuXVWVBWmBFowgiCCAdlhBKE4ZIgpjNorB4FF2ijMMAyumJofIFmUIyPZvtOzJIcCvglubvleBTq7+/HCW1+qLYqqUIwYQSgPGWIKw16OI7SPJSESj6ydGPxkuUTIUFOSit6+gYAbYr5iwNSvQEGWGEEoDQXrK0BinD3APssS7eFViQo7o0ztSSBwJMVFwKCnx4FQh2lVIwAAmSm+S4qpSSil1SGIUCHcLAVViIsy4ee31CE+2gSGYfD4hkvw4v6vsGBSrtqiKQyNwgQRCK6bU4Lls4qg12n7ZYBGAIJQHjLEFCIl3pWqIjbK5JHGgiAIwhdaN8IA/uTNBEHIR/tPPqEhwndpkiAIgiDUgAwxjUAvmgRBaJ0hGqgIQnHIECMIgiDEQXYYQSgOGWIawZ/SJexSQqGIr6LgBEGoD9lhBKE8FKyvEeR4/H96/Th8+10XoiKMygvEQVy0/XcizXofLQmCCEvIEtMcBZnx+KyxDamJvmsbE9qEDDGV8ccRNDIjDiMz4pQTxgcFmfFYeXkJSnMSg/abBKEVHHVky3Mv3v5PMWLa4+aFFfjXsRZMKEtTWxRCJn4ZYu3t7di+fTuys7PR2NiIjRs3IiXFu67gq6++is8//xw6nQ45OTlYtmwZbDYbNm3ahNzcXNhsNnzzzTe49957ERUV5Y9IIYdWx7VlMwpgNHp6vhiGweTRI1SSiCDURadj8Ns7pkGvYigAreATbGIijZhYkaG2GIQf+BUj9uijj6Kurg5r1qzBzJkz8dBDD3m1OX36NJ555hls3rwZmzZtwq5du9DY2IihoSFkZ2dj3bp1+MEPfoDIyEi8+OKL/ohDKMis8TmYXp0ZtN+j+YUIBQx6HcUzEgShKH4ZYu+88w6qq6sBAGPGjME777zj1ebdd99FeXm5c/Cqrq7GgQMHoNfrsWHDBmc7m8120XnDAHrDJQgidKClSYJQHp9Lk6tXr0ZLS4vX5xs2bEBrayuio+210WJiYtDR0YGBgQEYDK7Tnj171tkGAKKjo9Ha2upxrm+//RZNTU24++67RQmdmBgFgyEwAeMWS2xAzstHZKS90DTDKP/bwdbFH+LiIgXlDSVdfEG6aBN3XbSqV2JitCjZAiV/bExEwH+DjVbvhRzCSRcgvPRRUxefhtjTTz/N+11ycjK6u7sRFxeHrq4uxMfHexhhAJCUlITjx487/+7u7kZOTo7z79OnT+PRRx/FY489BpPJJErotrYeUe2kYrHEorn5XEDOzUdPTz8Ae6yYkr+thi7+0NnZyytvqOkiBOmiTdi6aFWvtrZuNJuEFzICeV86z513/jsY1yic+1ioE076BEMXIUPPr6XJqVOnoqGhAQBw+PBhTJ06FQAwNDSEkydPAgAmT56Mf//7384aZQ0NDZgyZQoA4JtvvsH27duxdetWJCQk4M033/RHnJCEliYJghBLVARtdCeIcMOvp3rjxo145JFH0NjYiKamJmzevBkA8MUXX2DTpk3Ys2cP0tPTsWrVKmzbtg16vR5Lly5Fbm4u+vr6sHz5cqSlpeGWW24BAFitVsyePdt/rUIICrkgCMIXP7+5Dt82dyMlXt1cURQjRhDK45chlpCQgPvvv9/r89LSUuzZs8f598KFC7Fw4UKPNmazGe+++64/P0+EOD+9fhz+69lDaotBEJonJSESKQkaSNhJdhhBKA6VOFKZi3lpMpjJaAmC8B8becQIQnEo4IBQlSXT8vHnt4+hOCdBbVEIArd/vwqDQ2Rs8EFXhiCUhwwxQlUur7WifkIOJckkNEH5yCS1RdA05BAjCOWhpUlCdcgIIwiCIC5WyBAjCIIgREG7JglCecgQIwiCIMRBdhhBKA4ZYgRBEIQoyA4jCOUhQ4wgCIIQBy1NEoTikCFGEARBiIIyexCE8pAhRhAEQRAEoRJkiBEEQRCisFGUGEEoDhliBEEQhDjIDiMIxSFDjCAIghAF5REjCOUhQ4wgCIIgCEIlqNYkQRAEIYoplSPwwWffYcm0fLVFIYiwgQwxgiAIQhSxUSZsXT1ebTEIIqygpUmCIAiCIAiVIEOMIAiCIAhCJcgQIwiCIAiCUAkyxAiCIAiCIFSCDDGCIAiCIAiVIEOMIAiCIAhCJcgQIwiCIAiCUAkyxAiCIAiCIFSCDDGCIAiCIAiVIENMZYx6+y0wG/UqS0IQBEEQRLChEkcqM3NcNpqauzCvLldtUQiCIAiCCDJkiKlMVIQB6xaNUlsMgiAIgiBUgJYmCYIgCIIgVIIMMYIgCIIgCJUgQ4wgCIIgCEIlyBAjCIIgCIJQCTLECIIgCIIgVIIMMYIgCIIgCJUgQ4wgCIIgCEIlyBAjCIIgCIJQCTLECIIgCIIgVIIMMYIgCIIgCJUgQ4wgCIIgCEIlGJvNZlNbCIIgCIIgiIsR8ogRBEEQBEGoBBliBEEQBEEQKkGGGEEQBEEQhIXbXQIAAA+kSURBVEqQIUYQBEEQBKESZIgRBEEQBEGoBBliBEEQBEEQKkGGGEEQBEEQhEqQIUYQBEFogqGhIbVFIIigc1EZYq2trWqLQHBw9uxZtUVQlBMnTqgtgmKcOXNGbREU49ixY+ju7lZbDEU4duwYPvroo7AwXL744gvcd9996OnpgU4X2lPSyZMn1RZBMZqbm9UWQTG0Pvfr77333nvVFiLQdHd34/XXX8fu3btx7NgxAEBGRgZsNhsYhlFZOmmcP38e27Ztw9DQEEaOHInBwcGQHbzOnz+Pffv24fnnn8dXX30Fi8WCxMREtcWSTU9PD9566y387ne/w6effgoAyMnJUVkq+bzyyivYsmUL0tLSkJeXh6GhoZB7XgCgs7MTjz/+OJ577jnU1NQgOTlZbZFk09vbi/379+O1115DRkYG0tLSYDKZ1BZLFp2dnfjVr36Fl156CQzDoLS0FElJSWqLJYvu7m68+eab2LlzJxoaGqDT6UL22XfosmvXLhw5cgQDAwPIzs4OyfkyVOb+0JzBJfL6669Dp9Nh/fr1YBgGTz/9NL7++mswDINQq/D05Zdf4tSpU3jwwQcBAHq9PuR0AIBPP/0UW7duRWZmJm677TYcPnwYn3/+udpiyebo0aP46U9/iqSkJGzduhXt7e1Ob1Ko3R+Hl2VwcBDl5eV444030N3dDZ1OF3K6HDlyBGvWrEF+fj5efPFFWK3WkPYiHTp0CImJidi6dSsKCgpgMBgwMDAAILT62XvvvYc5c+YgNTUVv/zlL1FYWBiyRlhfXx927NgBk8mELVu2YGhoCO3t7WqLJYu+vj48//zziIuLw2233Qaj0YhnnnkGx48fD8n5MlTm/rA3xIaGhrBv3z4UFhbCYrFg3rx5yMnJwdNPPw0AmrKKhXB0ms7OTjzwwANITEzEk08+CSA04yri4+ORlZWFMWPGIDs7G+PGjcOXX36ptliyycrKQlJSEmpra5Gamoq4uDjo9Xp0d3eHTB8D7P3M4WFtbW1FTU0NoqOj8Ze//AVtbW0hpQsA5ObmYvz48aisrMSuXbvw5JNP4t5778W+ffvUFk0SNpsNNpsN+/fvB8Mw2Lt3L1555RU8/PDD+N3vfgcgdMYyAKiqqsKqVatw7bXXIiEhATabDQcOHFBbLNm8+uqrsFqtSE1NRWxsLJqamtDU1KS2WJIZHBzEnj17UFBQgNTUVIwfPx5tbW144YUXAIRGH3N/kdy7d29IzP1htzTZ1NSEN954A7m5uTCZTGAYBl999RX++te/or6+HtHR0YiIiMDhw4dRVFSk6aUwd13MZjMAIDk5GfHx8UhLS8P27duxaNEiREdHa37ZyKGL1WqF2WxGREQEysvLERERAcAej1BQUIDs7GycPXsWkZGRKkssDLufGY1GVFVVwWw249ChQzh8+DD6+/vx5z//GUlJScjKylJbZF7Y/WxwcBCDg4M4deoU5s+fj8bGRuzevRttbW2oq6vTnFvfHfZ9cXiMdu/ejUWLFmHWrFloamrCe++9B6vVCovForbIvLDvC8MwOHHiBH7/+99j+fLlmDNnDgDgtddew4gRI0Kmj5lMJphMJlRUVECv12NoaAjNzc2wWq1IT0/XdP8CuPtYa2sr9u7di7fffhuRkZHQ6/V49tlnkZKSAqvVqrbIvHCNY8eOHcNbb72F+vp66HQ6tLe3o62tDRUVFYiJiVFbZF5aW1vx29/+Fg0NDWAYBllZWThy5Aj+9re/aX7uDytDrL+/H48//jgaGhpgNBpRUlICALBYLHjllVeQnp6O3NxcDA4O4rPPPsPkyZMRFRWlstTc8OniiAexWq345JNP0NDQgOnTp6Onp0ezsSJcuhgMBqdxCQBvvvkm5s2bh+PHj2P//v2orKxUUWJh+O6NQ5+4uDjMnTvX6eWLi4tDQUGBmiLzwqWLTqeDXq/HH//4R3R2duLEiROIiIhAVFQUMjIyNDWAucN3X6xWK7Kzs5GbmwvAPh40NDRgwoQJIadLQkICnnzySZSVlaG4uBgWiwVNTU3Iz8/HiBEjVJaaGz5d9Ho9ALtn4oMPPsBXX32FmpoaTRthfLrU1dUhPz8fra2t2LhxI2pqanDq1CnExMSgsLBQZam54dOlvLwcf/zjH9HS0oLPP/8clZWV6OzsxCWXXAKj0aiy1N7YbDa8+uqreO+99zBx4kR0dnbinnvuwY033oiMjAy8/PLLyMjI0PTcH1ZLkxcuXEBxcTEmTpyIjz/+2OkatlqtWLRoEX72s5+hv78fLS0tGBwc1PQDz6eL+zLk7bffjpdeegk//vGPNb0rxJcu3d3dOHfuHPbv348tW7bAZDJpav2eDZ8+Dpl7e3sBAJ988gm+/vpr5OXlqSarL/h0aWtrQ3p6OlJSUvDDH/4QBQUFeOONN3Do0CHN3hs+XQCgoKAAx48fB2DfCdrd3a2pgZgNny6ZmZlYt24dfv3rXwOwxyaeOnUKqampaooriNDz4uhLM2bMQFRUlObDLIT62LFjx7B7924AQENDA44ePRqSz35KSgqef/55LFmyBLfccguys7Odqy5apLOzE9999x2uuOIK1NTU4LrrrkNtbS3OnDmDvLw8LF68WPNzf0h7xI4dO4aXXnoJJpMJMTExiI6ORllZGSIiIvCvf/0LHR0dqKqqgl6vx+jRo9HW1oaPPvoI33zzDVatWqWpZQmxujiCDPv7+3H48GHExMRg9erVzrd9LSBFFwA4cOAAnnjiCSQnJ2Pt2rWYOnWqph4UKfqcP38eu3fvxp/+9CfExMTg6quvDsl7ExkZiaKiIhQXF6OnpwctLS1Ys2YNJk6cqJl7I1YXwD7p79y5E7t27UJUVBSWL1+O9PR0lTVwIVYXnU6H6upqnDx5EgcPHsSZM2dwww03aMobJuV5cfSlDz74wMMroxWk9LHU1FQcOXIEf//73zE4OIhVq1ZpallSii5GoxGHDh3Cb37zG/T392PevHlISEhQWQMX7rpkZmbCbDYjMzMTRqMRJ06cwLFjx1BfXw+bzYbKykq0t7fjww8/RFNTk+bmfgBgbFp9veXBET/whz/8AV1dXcjKysKHH36I3t5e505CAHjuuedw9OhRrFixAvn5+c7PBwYGYDAY1BDdC390GRgYQFdXl2YeDn90+eijj3D69GnMnTtXLfG98EefxsZGnD17FmPGjFFLfA+k6nL99dd7LKVqKWbHn/ty6tQpfPfdd5pZ9vZHl6GhIVy4cMFjeV9N/B2XtYQ/z0tvby9aWlqQnZ2tlvge+HNfmpub8fXXX2PChAlqie8Bly4ffPABBgYG8MADDzjbvf/++zh16hQWLlyIt99+G5deeikAbc39bELKI2az2XD+/HkYjUb84x//wNSpU1FXV4fKykps2bIFFRUVztwtGRkZaGhowOuvv47Ozk6UlJRAr9drJueWHF327duHc+fOoaSkBEaj0Rnorjb+6pKdnY2ioiKVtXDhrz7JycnIyMhQWQs7SjwzWjLC/LkvCQkJmvGC+auLwWDQzKTiry6OWDEt4K8uERERiI+PV1kLO/7qEhcXp5kNIHy6VFVV4e677/bQ5ejRo0hJScH//M//4KmnnsKMGTMQFxenmbmfC208ySJwTBD9/f1Yvnw5Dh48iIKCApSUlCAxMREbNmzAQw89hEsuuQSA/Y2xpaUFpaWlWLhwoaYC2eXqUlZWRroEmHDSh56Z8LovpEtgIV1CU5f169d76PLCCy/gzJkzmDVrFv70pz+FRH46zXvEuru78dhjj2FgYABXX3019u7d63xbf+qpp3DNNdcAsO/0OHDgAIqLi5GSkoL+/n5MnDgRl112mWY6FemiTV2A8NKHdCFdAg3pQroEGjm6DA4O4sSJE7j55puxYMECzadBcqBdX90wDMMgLS0NEydORHx8PNatW4d//etfuOaaa2AwGLBz504A9l1eeXl5zrX6pKQkzSxDOCBdtKkLEF76kC6kS6AhXUiXQCNFl5EjR6K4uBhpaWm44447MGrUKHWFl4jmPWIGgwHp6enOteqWlhb09fVh3LhxsFgs+L//+z8cPHgQX331FQoKClBaWqqyxPyQLtolnPQhXbQJ6aJNSBdtIkWXwsJCFBcXa2pjkRQ0HyPGMIxH4PPJkyeduzouXLiAm266CWfPnkVWVpZmkzM6IF20SzjpQ7poE9JFm5Au2kSOLqFohAEhYIixaW5uRnx8PDZu3AiTyYRJkyYhMzNTbbFkQbpol3DSh3TRJqSLNiFdtEk46cImpPKINTc3Y9myZSgqKkJ9fT0WLFigtkiyIV20SzjpQ7poE9JFm5Au2iScdOFC8zFi7pw/fx42mw0/+clPUFZWprY4fkG6aJdw0od00SakizYhXbRJOOnCRUh5xAiCIAiCIMIJzaevIAiCIAiCCFfIECMIgiAIglAJMsQIgiAIgiBUggwxgiAIgiAIlSBDjCAIgiAIQiVCLqErQRCEGD766CP84he/wLFjxzBz5kx0dnaip6cHixcvxpw5cwSPffnll3Hw4EE8+OCDQZKWIIiLFTLECIIIS8aOHYtFixbhxRdfxNatWwEA3333HW644QacPn0aK1asUFdAgiAIkCFGEMRFRGpqKu644w5s2LABl112GbZu3YqCggK0t7ejoqICV111FRobG/Haa6/hzJkz2Lp1K6ZPn47JkyfjueeeQ2NjI8xmM86dO4cf//jHiI6OVlslgiBCHDLECIK4qBg1ahR6enrQ2tqKlStXora2FgAwf/58zJgxA7m5uViwYAEOHjyILVu2AADef/99/O1vf8POnTsBAI899hh27NiBW2+9VS01CIIIE8gQIwjiosRms+HgwYPYu3cvIiIi0NHRgaamJqSlpXm1PXDgANra2pyGWXt7OywWS7BFJggiDCFDjCCIi4pPPvkEUVFR+Oc//4nPPvsMTz31FADgyJEjGBwc5DzGZrOhqqoK9913n/Pv3t7eoMlMEET4QukrCIK4aGhubsbDDz+M9evXo729HQkJCQCAoaEhnD592tnObDZjcHAQNpsNu3fvxpQpU/DBBx9gYGAAAPDXv/4Vzz77rCo6EAQRXlDRb4IgwpKGhgY8/vjjOHr0KGbPno2Ojg50dXVh4cKFuPzyy3Hy5Els3LgRVqsVCQkJ2L9/P4qLi/HAAw+gr68P69evR05ODmpra7FkyRLs3LkTDQ0NyMjIQF9fH+68806YzWa11SQIIsQhQ4wgCIIgCEIlaGmSIAiCIAhCJcgQIwiCIAiCUAkyxAiCIAiCIFSCDDGCIAiCIAiVIEOMIAiCIAhCJcgQIwiCIAiCUAkyxAiCIAiCIFTi/wNErQ4bn74yRQAAAABJRU5ErkJggg==\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[['return', 'prediction']].iloc[lags:].plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch05/lr_plot_5.png')"]}, {"cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [], "source": ["hits = np.sign(data['return'] *\n", " data['prediction']).value_counts()"]}, {"cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [{"data": {"text/plain": [" 1.0 1250\n", "-1.0 1242\n", " 0.0 13\n", "dtype: int64"]}, "execution_count": 39, "metadata": {}, "output_type": "execute_result"}], "source": ["hits"]}, {"cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.499001996007984"]}, "execution_count": 40, "metadata": {}, "output_type": "execute_result"}], "source": ["hits.values[0] / sum(hits)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Prediction Future Market Direction"]}, {"cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [], "source": ["reg = np.linalg.lstsq(data[cols], np.sign(data['return']),\n", " rcond=None)[0]"]}, {"cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([-5.11938725, -2.24077248, -5.13080606, -3.03753232, -2.14819119])"]}, "execution_count": 42, "metadata": {}, "output_type": "execute_result"}], "source": ["reg"]}, {"cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [], "source": ["data['prediction'] = np.sign(np.dot(data[cols], reg))"]}, {"cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [{"data": {"text/plain": [" 1.0 1300\n", "-1.0 1205\n", "Name: prediction, dtype: int64"]}, "execution_count": 44, "metadata": {}, "output_type": "execute_result"}], "source": ["data['prediction'].value_counts()"]}, {"cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": ["hits = np.sign(data['return'] *\n", " data['prediction']).value_counts()"]}, {"cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [{"data": {"text/plain": [" 1.0 1301\n", "-1.0 1191\n", " 0.0 13\n", "dtype: int64"]}, "execution_count": 46, "metadata": {}, "output_type": "execute_result"}], "source": ["hits"]}, {"cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.5193612774451097"]}, "execution_count": 47, "metadata": {}, "output_type": "execute_result"}], "source": ["hits.values[0] / sum(hits)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Vectorized Backtesting of Regression-based Strategy "]}, {"cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [{"data": {"text/html": ["
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" price lag_1 lag_2 lag_3 lag_4 lag_5 \\\n", "Date \n", "2010-01-20 1.4101 -0.005858 -0.008309 -0.000551 0.001103 -0.001310 \n", "2010-01-21 1.4090 -0.013874 -0.005858 -0.008309 -0.000551 0.001103 \n", "2010-01-22 1.4137 -0.000780 -0.013874 -0.005858 -0.008309 -0.000551 \n", "2010-01-25 1.4150 0.003330 -0.000780 -0.013874 -0.005858 -0.008309 \n", "2010-01-26 1.4073 0.000919 0.003330 -0.000780 -0.013874 -0.005858 \n", "\n", " prediction return \n", "Date \n", "2010-01-20 1.0 -0.013874 \n", "2010-01-21 1.0 -0.000780 \n", "2010-01-22 1.0 0.003330 \n", "2010-01-25 1.0 0.000919 \n", "2010-01-26 1.0 -0.005457 "]}, "execution_count": 48, "metadata": {}, "output_type": "execute_result"}], "source": ["data.head()"]}, {"cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [], "source": ["data['strategy'] = data['prediction'] * data['return']"]}, {"cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [{"data": {"text/plain": ["return 0.784026\n", "strategy 1.654154\n", "dtype: float64"]}, "execution_count": 50, "metadata": {}, "output_type": "execute_result"}], "source": ["data[['return', 'strategy']].sum().apply(np.exp)"]}, {"cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["| \n", " | price | \n", "lag_1 | \n", "lag_2 | \n", "lag_3 | \n", "lag_4 | \n", "lag_5 | \n", "prediction | \n", "return | \n", "
|---|---|---|---|---|---|---|---|---|
| Date | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
| 2010-01-20 | \n", "1.4101 | \n", "-0.005858 | \n", "-0.008309 | \n", "-0.000551 | \n", "0.001103 | \n", "-0.001310 | \n", "1.0 | \n", "-0.013874 | \n", "
| 2010-01-21 | \n", "1.4090 | \n", "-0.013874 | \n", "-0.005858 | \n", "-0.008309 | \n", "-0.000551 | \n", "0.001103 | \n", "1.0 | \n", "-0.000780 | \n", "
| 2010-01-22 | \n", "1.4137 | \n", "-0.000780 | \n", "-0.013874 | \n", "-0.005858 | \n", "-0.008309 | \n", "-0.000551 | \n", "1.0 | \n", "0.003330 | \n", "
| 2010-01-25 | \n", "1.4150 | \n", "0.003330 | \n", "-0.000780 | \n", "-0.013874 | \n", "-0.005858 | \n", "-0.008309 | \n", "1.0 | \n", "0.000919 | \n", "
| 2010-01-26 | \n", "1.4073 | \n", "0.000919 | \n", "0.003330 | \n", "-0.000780 | \n", "-0.013874 | \n", "-0.005858 | \n", "1.0 | \n", "-0.005457 | \n", "
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[['return', 'strategy']].dropna().cumsum(\n", " ).apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch05/lr_plot_6.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Generalizing the Approach"]}, {"cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [], "source": ["import LRVectorBacktester as LR"]}, {"cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [], "source": ["lrbt = LR.LRVectorBacktester('EUR=', '2010-1-1', '2019-12-31',\n", " 10000, 0.0)"]}, {"cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [{"data": {"text/plain": ["(17166.53, 9442.42)"]}, "execution_count": 54, "metadata": {}, "output_type": "execute_result"}], "source": ["lrbt.run_strategy('2010-1-1', '2019-12-31',\n", " '2010-1-1', '2019-12-31', lags=5)"]}, {"cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [{"data": {"text/plain": ["(10160.86, 791.87)"]}, "execution_count": 55, "metadata": {}, "output_type": "execute_result"}], "source": ["lrbt.run_strategy('2010-1-1', '2017-12-31',\n", " '2018-1-1', '2019-12-31', lags=5)"]}, {"cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["lrbt.plot_results()\n", "# plt.savefig('../../images/ch05/lr_plot_7.png')"]}, {"cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [], "source": ["lrbt = LR.LRVectorBacktester('GDX', '2010-1-1', '2019-12-31',\n", " 10000, 0.002)"]}, {"cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [{"data": {"text/plain": ["(23642.32, 17649.69)"]}, "execution_count": 58, "metadata": {}, "output_type": "execute_result"}], "source": ["lrbt.run_strategy('2010-1-1', '2019-12-31',\n", " '2010-1-1', '2019-12-31', lags=7) "]}, {"cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [{"data": {"text/plain": ["(28513.35, 14888.41)"]}, "execution_count": 59, "metadata": {}, "output_type": "execute_result"}], "source": ["lrbt.run_strategy('2010-1-1', '2014-12-31',\n", " '2015-1-1', '2019-12-31', lags=7)"]}, {"cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["lrbt.plot_results()\n", "# plt.savefig('../../images/ch05/lr_plot_8.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Using Machine Learning for Market Movement Prediction"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Linear Regression with scikit-learn"]}, {"cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [], "source": ["x = np.arange(12)"]}, {"cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])"]}, "execution_count": 62, "metadata": {}, "output_type": "execute_result"}], "source": ["x"]}, {"cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": ["lags = 3"]}, {"cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [], "source": ["m = np.zeros((lags + 1, len(x) - lags))"]}, {"cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [], "source": ["m[lags] = x[lags:]\n", "for i in range(lags):\n", " m[i] = x[i:i - lags]"]}, {"cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [], "source": ["from sklearn import linear_model"]}, {"cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": ["lm = linear_model.LinearRegression()"]}, {"cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [{"data": {"text/plain": ["LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"]}, "execution_count": 68, "metadata": {}, "output_type": "execute_result"}], "source": ["lm.fit(m[:lags].T, m[lags])"]}, {"cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([0.33333333, 0.33333333, 0.33333333])"]}, "execution_count": 69, "metadata": {}, "output_type": "execute_result"}], "source": ["lm.coef_"]}, {"cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [{"data": {"text/plain": ["2.0"]}, "execution_count": 70, "metadata": {}, "output_type": "execute_result"}], "source": ["lm.intercept_"]}, {"cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 3., 4., 5., 6., 7., 8., 9., 10., 11.])"]}, "execution_count": 71, "metadata": {}, "output_type": "execute_result"}], "source": ["lm.predict(m[:lags].T)"]}, {"cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [], "source": ["lm = linear_model.LinearRegression(fit_intercept=False)"]}, {"cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [{"data": {"text/plain": ["LinearRegression(copy_X=True, fit_intercept=False, n_jobs=None, normalize=False)"]}, "execution_count": 73, "metadata": {}, "output_type": "execute_result"}], "source": ["lm.fit(m[:lags].T, m[lags])"]}, {"cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([-0.66666667, 0.33333333, 1.33333333])"]}, "execution_count": 74, "metadata": {}, "output_type": "execute_result"}], "source": ["lm.coef_"]}, {"cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.0"]}, "execution_count": 75, "metadata": {}, "output_type": "execute_result"}], "source": ["lm.intercept_"]}, {"cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 3., 4., 5., 6., 7., 8., 9., 10., 11.])"]}, "execution_count": 76, "metadata": {}, "output_type": "execute_result"}], "source": ["lm.predict(m[:lags].T)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### A Simple Classification Problem"]}, {"cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [], "source": ["hours = np.array([0.5, 0.75, 1., 1.25, 1.5, 1.75, 1.75, 2.,\n", " 2.25, 2.5, 2.75, 3., 3.25, 3.5, 4., 4.25,\n", " 4.5, 4.75, 5., 5.5])"]}, {"cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [], "source": ["success = np.array([0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1,\n", " 0, 1, 1, 1, 1, 1, 1])"]}, {"cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [{"data": {"image/png": "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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6))\n", "plt.plot(hours, success, 'ro')\n", "plt.ylim(-0.2, 1.2);\n", "# plt.savefig('../../images/ch05/ml_plot_1.png')"]}, {"cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [], "source": ["reg = np.polyfit(hours, success, deg=1)"]}, {"cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6))\n", "plt.plot(hours, success, 'ro')\n", "plt.plot(hours, np.polyval(reg, hours), 'b')\n", "plt.ylim(-0.2, 1.2);\n", "# plt.savefig('../../images/ch05/ml_plot_2.png')"]}, {"cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [], "source": ["lm = linear_model.LogisticRegression(solver='lbfgs')"]}, {"cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [], "source": ["hrs = hours.reshape(1, -1).T"]}, {"cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [{"data": {"text/plain": ["LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n", " intercept_scaling=1, l1_ratio=None, max_iter=100,\n", " multi_class='auto', n_jobs=None, penalty='l2',\n", " random_state=None, solver='lbfgs', tol=0.0001, verbose=0,\n", " warm_start=False)"]}, "execution_count": 84, "metadata": {}, "output_type": "execute_result"}], "source": ["lm.fit(hrs, success)"]}, {"cell_type": "code", "execution_count": 85, "metadata": {}, "outputs": [], "source": ["prediction = lm.predict(hrs)"]}, {"cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6))\n", "plt.plot(hours, success, 'ro', label='data')\n", "plt.plot(hours, prediction, 'b', label='prediction')\n", "plt.legend(loc=0)\n", "plt.ylim(-0.2, 1.2);\n", "# plt.savefig('../../images/ch05/ml_plot_3.png')"]}, {"cell_type": "code", "execution_count": 87, "metadata": {}, "outputs": [], "source": ["prob = lm.predict_proba(hrs)"]}, {"cell_type": "code", "execution_count": 88, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6))\n", "plt.plot(hours, success, 'ro')\n", "plt.plot(hours, prediction, 'b')\n", "plt.plot(hours, prob.T[0], 'm--',\n", " label='$p(h)$ for zero')\n", "plt.plot(hours, prob.T[1], 'g-.',\n", " label='$p(h)$ for one')\n", "plt.ylim(-0.2, 1.2)\n", "plt.legend(loc=0);\n", "# plt.savefig('../../images/ch05/ml_plot_4.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Using Logistic Regression to Predict Market Direction"]}, {"cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [], "source": ["symbol = 'GLD'"]}, {"cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [], "source": ["data = pd.DataFrame(raw[symbol])"]}, {"cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [], "source": ["data.rename(columns={symbol: 'price'}, inplace=True)"]}, {"cell_type": "code", "execution_count": 92, "metadata": {}, "outputs": [], "source": ["data['return'] = np.log(data['price'] / data['price'].shift(1))"]}, {"cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [], "source": ["data.dropna(inplace=True)"]}, {"cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [], "source": ["lags = 3"]}, {"cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [], "source": ["cols = []\n", "for lag in range(1, lags + 1):\n", " col = 'lag_{}'.format(lag)\n", " data[col] = data['return'].shift(lag)\n", " cols.append(col)"]}, {"cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [], "source": ["data.dropna(inplace=True)"]}, {"cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [], "source": ["from sklearn.metrics import accuracy_score"]}, {"cell_type": "code", "execution_count": 98, "metadata": {}, "outputs": [], "source": ["lm = linear_model.LogisticRegression(C=1e7, solver='lbfgs',\n", " multi_class='auto',\n", " max_iter=1000)"]}, {"cell_type": "code", "execution_count": 99, "metadata": {}, "outputs": [{"data": {"text/plain": ["LogisticRegression(C=10000000.0, class_weight=None, dual=False,\n", " fit_intercept=True, intercept_scaling=1, l1_ratio=None,\n", " max_iter=1000, multi_class='auto', n_jobs=None, penalty='l2',\n", " random_state=None, solver='lbfgs', tol=0.0001, verbose=0,\n", " warm_start=False)"]}, "execution_count": 99, "metadata": {}, "output_type": "execute_result"}], "source": ["lm.fit(data[cols], np.sign(data['return']))"]}, {"cell_type": "code", "execution_count": 100, "metadata": {}, "outputs": [], "source": ["data['prediction'] = lm.predict(data[cols])"]}, {"cell_type": "code", "execution_count": 101, "metadata": {}, "outputs": [{"data": {"text/plain": [" 1.0 1983\n", "-1.0 529\n", "Name: prediction, dtype: int64"]}, "execution_count": 101, "metadata": {}, "output_type": "execute_result"}], "source": ["data['prediction'].value_counts()"]}, {"cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [], "source": ["hits = np.sign(data['return'].iloc[lags:] *\n", " data['prediction'].iloc[lags:]\n", " ).value_counts()"]}, {"cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [{"data": {"text/plain": [" 1.0 1338\n", "-1.0 1159\n", " 0.0 12\n", "dtype: int64"]}, "execution_count": 103, "metadata": {}, "output_type": "execute_result"}], "source": ["hits"]}, {"cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.5338375796178344"]}, "execution_count": 104, "metadata": {}, "output_type": "execute_result"}], "source": ["accuracy_score(data['prediction'],\n", " np.sign(data['return']))"]}, {"cell_type": "code", "execution_count": 105, "metadata": {}, "outputs": [], "source": ["data['strategy'] = data['prediction'] * data['return']"]}, {"cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [{"data": {"text/plain": ["return 1.289478\n", "strategy 2.458716\n", "dtype: float64"]}, "execution_count": 106, "metadata": {}, "output_type": "execute_result"}], "source": ["data[['return', 'strategy']].sum().apply(np.exp)"]}, {"cell_type": "code", "execution_count": 107, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[['return', 'strategy']].cumsum().apply(np.exp).plot(\n", " figsize=(10, 6));\n", "# plt.savefig('../../images/ch05/ml_plot_5.png')"]}, {"cell_type": "code", "execution_count": 108, "metadata": {}, "outputs": [], "source": ["data = pd.DataFrame(raw[symbol])"]}, {"cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [], "source": ["data.rename(columns={symbol: 'price'}, inplace=True)"]}, {"cell_type": "code", "execution_count": 110, "metadata": {}, "outputs": [], "source": ["data['return'] = np.log(data['price'] / data['price'].shift(1))"]}, {"cell_type": "code", "execution_count": 111, "metadata": {}, "outputs": [], "source": ["lags = 5"]}, {"cell_type": "code", "execution_count": 112, "metadata": {}, "outputs": [], "source": ["cols = []\n", "for lag in range(1, lags + 1):\n", " col = 'lag_%d' % lag\n", " data[col] = data['price'].shift(lag)\n", " cols.append(col)"]}, {"cell_type": "code", "execution_count": 113, "metadata": {}, "outputs": [], "source": ["data.dropna(inplace=True)"]}, {"cell_type": "code", "execution_count": 114, "metadata": {}, "outputs": [{"data": {"text/plain": ["LogisticRegression(C=10000000.0, class_weight=None, dual=False,\n", " fit_intercept=True, intercept_scaling=1, l1_ratio=None,\n", " max_iter=1000, multi_class='auto', n_jobs=None, penalty='l2',\n", " random_state=None, solver='lbfgs', tol=0.0001, verbose=0,\n", " warm_start=False)"]}, "execution_count": 114, "metadata": {}, "output_type": "execute_result"}], "source": ["lm.fit(data[cols], np.sign(data['return']))"]}, {"cell_type": "code", "execution_count": 115, "metadata": {}, "outputs": [], "source": ["data['prediction'] = lm.predict(data[cols])"]}, {"cell_type": "code", "execution_count": 116, "metadata": {}, "outputs": [{"data": {"text/plain": [" 1.0 2047\n", "-1.0 464\n", "Name: prediction, dtype: int64"]}, "execution_count": 116, "metadata": {}, "output_type": "execute_result"}], "source": ["data['prediction'].value_counts()"]}, {"cell_type": "code", "execution_count": 117, "metadata": {}, "outputs": [], "source": ["hits = np.sign(data['return'].iloc[lags:] *\n", " data['prediction'].iloc[lags:]\n", " ).value_counts()"]}, {"cell_type": "code", "execution_count": 118, "metadata": {}, "outputs": [{"data": {"text/plain": [" 1.0 1331\n", "-1.0 1163\n", " 0.0 12\n", "dtype: int64"]}, "execution_count": 118, "metadata": {}, "output_type": "execute_result"}], "source": ["hits"]}, {"cell_type": "code", "execution_count": 119, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.5312624452409399"]}, "execution_count": 119, "metadata": {}, "output_type": "execute_result"}], "source": ["accuracy_score(data['prediction'],\n", " np.sign(data['return']))"]}, {"cell_type": "code", "execution_count": 120, "metadata": {}, "outputs": [], "source": ["data['strategy'] = data['prediction'] * data['return']"]}, {"cell_type": "code", "execution_count": 121, "metadata": {}, "outputs": [{"data": {"text/plain": ["return 1.283110\n", "strategy 2.656833\n", "dtype: float64"]}, "execution_count": 121, "metadata": {}, "output_type": "execute_result"}], "source": ["data[['return', 'strategy']].sum().apply(np.exp)"]}, {"cell_type": "code", "execution_count": 122, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[['return', 'strategy']].cumsum().apply(np.exp).plot(\n", " figsize=(10, 6));\n", "# plt.savefig('../../images/ch05/ml_plot_6.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Generalizing the Approach"]}, {"cell_type": "code", "execution_count": 123, "metadata": {}, "outputs": [], "source": ["import ScikitVectorBacktester as SCI"]}, {"cell_type": "code", "execution_count": 124, "metadata": {}, "outputs": [], "source": ["scibt = SCI.ScikitVectorBacktester('EUR=',\n", " '2010-1-1', '2019-12-31',\n", " 10000, 0.0, 'logistic')"]}, {"cell_type": "code", "execution_count": 125, "metadata": {}, "outputs": [{"data": {"text/plain": ["(12192.18, 2189.5)"]}, "execution_count": 125, "metadata": {}, "output_type": "execute_result"}], "source": ["scibt.run_strategy('2015-1-1', '2019-12-31',\n", " '2015-1-1', '2019-12-31', lags=15)"]}, {"cell_type": "code", "execution_count": 126, "metadata": {}, "outputs": [{"data": {"text/plain": ["(10580.54, 729.93)"]}, "execution_count": 126, "metadata": {}, "output_type": "execute_result"}], "source": ["scibt.run_strategy('2016-1-1', '2018-12-31',\n", " '2019-1-1', '2019-12-31', lags=15)"]}, {"cell_type": "code", "execution_count": 127, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["scibt.plot_results()\n", "# plt.savefig('../../images/ch05/ml_plot_7.png')"]}, {"cell_type": "code", "execution_count": 128, "metadata": {}, "outputs": [], "source": ["scibt = SCI.ScikitVectorBacktester('GDX',\n", " '2010-1-1', '2019-12-31',\n", " 10000, 0.00, 'logistic')"]}, {"cell_type": "code", "execution_count": 129, "metadata": {}, "outputs": [{"data": {"text/plain": ["(12686.81, 4032.73)"]}, "execution_count": 129, "metadata": {}, "output_type": "execute_result"}], "source": ["scibt.run_strategy('2013-1-1', '2017-12-31',\n", " '2018-1-1', '2018-12-31', lags=10)"]}, {"cell_type": "code", "execution_count": 130, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["scibt.plot_results()\n", "# plt.savefig('../../images/ch05/ml_plot_8.png')"]}, {"cell_type": "code", "execution_count": 131, "metadata": {}, "outputs": [], "source": ["scibt = SCI.ScikitVectorBacktester('GDX',\n", " '2010-1-1', '2019-12-31',\n", " 10000, 0.0025, 'logistic')"]}, {"cell_type": "code", "execution_count": 132, "metadata": {}, "outputs": [{"data": {"text/plain": ["(9588.48, 934.4)"]}, "execution_count": 132, "metadata": {}, "output_type": "execute_result"}], "source": ["scibt.run_strategy('2013-1-1', '2017-12-31',\n", " '2018-1-1', '2018-12-31', lags=10)"]}, {"cell_type": "code", "execution_count": 133, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", 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"]}, "metadata": {}, "output_type": "display_data"}], "source": ["scibt.plot_results()\n", "# plt.savefig('../../images/ch05/ml_plot_8_a.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Using Deep Learning for Market Movement Prediction"]}, {"cell_type": "markdown", "metadata": {}, "source": ["#### The Simple Classification Problem Revisited "]}, {"cell_type": "code", "execution_count": 134, "metadata": {}, "outputs": [], "source": ["hours = np.array([0.5, 0.75, 1., 1.25, 1.5, 1.75, 1.75, 2.,\n", " 2.25, 2.5, 2.75, 3., 3.25, 3.5, 4., 4.25,\n", " 4.5, 4.75, 5., 5.5])"]}, {"cell_type": "code", "execution_count": 135, "metadata": {}, "outputs": [], "source": ["success = np.array([0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1,\n", " 0, 1, 1, 1, 1, 1, 1]) "]}, {"cell_type": "code", "execution_count": 136, "metadata": {}, "outputs": [], "source": ["data = pd.DataFrame({'hours': hours, 'success': success})"]}, {"cell_type": "code", "execution_count": 137, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "RangeIndex: 20 entries, 0 to 19\n", "Data columns (total 2 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 hours 20 non-null float64\n", " 1 success 20 non-null int64 \n", "dtypes: float64(1), int64(1)\n", "memory usage: 448.0 bytes\n"]}], "source": ["data.info()"]}, {"cell_type": "code", "execution_count": 138, "metadata": {}, "outputs": [], "source": ["from sklearn.neural_network import MLPClassifier"]}, {"cell_type": "code", "execution_count": 139, "metadata": {}, "outputs": [], "source": ["model = MLPClassifier(hidden_layer_sizes=[32],\n", " max_iter=1000, random_state=100)"]}, {"cell_type": "code", "execution_count": 140, "metadata": {}, "outputs": [{"data": {"text/plain": ["MLPClassifier(activation='relu', alpha=0.0001, batch_size='auto', beta_1=0.9,\n", " beta_2=0.999, early_stopping=False, epsilon=1e-08,\n", " hidden_layer_sizes=[32], learning_rate='constant',\n", " learning_rate_init=0.001, max_fun=15000, max_iter=1000,\n", " momentum=0.9, n_iter_no_change=10, nesterovs_momentum=True,\n", " power_t=0.5, random_state=100, shuffle=True, solver='adam',\n", " tol=0.0001, validation_fraction=0.1, verbose=False,\n", " warm_start=False)"]}, "execution_count": 140, "metadata": {}, "output_type": "execute_result"}], "source": ["model.fit(data['hours'].values.reshape(-1, 1), data['success'])"]}, {"cell_type": "code", "execution_count": 141, "metadata": {}, "outputs": [], "source": ["data['prediction'] = model.predict(data['hours'].values.reshape(-1, 1)) # <2>"]}, {"cell_type": "code", "execution_count": 142, "metadata": {}, "outputs": [{"data": {"text/html": ["
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" hours success prediction\n", "15 4.25 1 1\n", "16 4.50 1 1\n", "17 4.75 1 1\n", "18 5.00 1 1\n", "19 5.50 1 1"]}, "execution_count": 142, "metadata": {}, "output_type": "execute_result"}], "source": ["data.tail()"]}, {"cell_type": "code", "execution_count": 143, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["| \n", " | hours | \n", "success | \n", "prediction | \n", "
|---|---|---|---|
| 15 | \n", "4.25 | \n", "1 | \n", "1 | \n", "
| 16 | \n", "4.50 | \n", "1 | \n", "1 | \n", "
| 17 | \n", "4.75 | \n", "1 | \n", "1 | \n", "
| 18 | \n", "5.00 | \n", "1 | \n", "1 | \n", "
| 19 | \n", "5.50 | \n", "1 | \n", "1 | \n", "
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data.plot(x='hours', y=['success', 'prediction'],\n", " style=['ro', 'b-'], ylim=[-.1, 1.1],\n", " figsize=(10, 6));\n", "# plt.savefig('../../images/ch05/dl_plot_1.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Using Deep Neural Networks to Predict Market Direction"]}, {"cell_type": "code", "execution_count": 144, "metadata": {}, "outputs": [], "source": ["symbol = 'EUR='"]}, {"cell_type": "code", "execution_count": 145, "metadata": {}, "outputs": [], "source": ["data = pd.DataFrame(raw[symbol])"]}, {"cell_type": "code", "execution_count": 146, "metadata": {}, "outputs": [], "source": ["data.rename(columns={symbol: 'price'}, inplace=True)"]}, {"cell_type": "code", "execution_count": 147, "metadata": {}, "outputs": [], "source": ["data['return'] = np.log(data['price'] /\n", " data['price'].shift(1)) "]}, {"cell_type": "code", "execution_count": 148, "metadata": {}, "outputs": [], "source": ["data['direction'] = np.where(data['return'] > 0, 1, 0)"]}, {"cell_type": "code", "execution_count": 149, "metadata": {}, "outputs": [], "source": ["lags = 5\n"]}, {"cell_type": "code", "execution_count": 150, "metadata": {}, "outputs": [], "source": ["cols = []\n", "for lag in range(1, lags + 1): # <5>\n", " col = f'lag_{lag}'\n", " data[col] = data['return'].shift(lag) # <6>\n", " cols.append(col)\n", "data.dropna(inplace=True) # <7>"]}, {"cell_type": "code", "execution_count": 151, "metadata": {}, "outputs": [{"data": {"text/html": [""]}, "execution_count": 162, "metadata": {}, "output_type": "execute_result"}], "source": ["%%time\n", "model.fit(training_data[cols],\n", " training_data['direction'],\n", " epochs=50, verbose=False,\n", " validation_split=0.2, shuffle=False)"]}, {"cell_type": "code", "execution_count": 163, "metadata": {}, "outputs": [], "source": ["res = pd.DataFrame(model.history.history)"]}, {"cell_type": "code", "execution_count": 164, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", 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\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" price return direction lag_1 lag_2 lag_3 lag_4 lag_5\n", "Date \n", "2019-12-24 1.1087 0.0001 1 0.0007 -0.0038 0.0008 -0.0034 0.0006\n", "2019-12-26 1.1096 0.0008 1 0.0001 0.0007 -0.0038 0.0008 -0.0034\n", "2019-12-27 1.1175 0.0071 1 0.0008 0.0001 0.0007 -0.0038 0.0008\n", "2019-12-30 1.1197 0.0020 1 0.0071 0.0008 0.0001 0.0007 -0.0038\n", "2019-12-31 1.1210 0.0012 1 0.0020 0.0071 0.0008 0.0001 0.0007"]}, "execution_count": 151, "metadata": {}, "output_type": "execute_result"}], "source": ["data.round(4).tail()"]}, {"cell_type": "code", "execution_count": 152, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["Using TensorFlow backend.\n"]}], "source": ["import tensorflow as tf\n", "from keras.models import Sequential\n", "from keras.layers import Dense\n", "from keras.optimizers import adam"]}, {"cell_type": "code", "execution_count": 153, "metadata": {}, "outputs": [], "source": ["optimizer = adam(learning_rate=0.0001)"]}, {"cell_type": "code", "execution_count": 154, "metadata": {}, "outputs": [], "source": ["def set_seeds(seed=100):\n", " random.seed(seed)\n", " np.random.seed(seed)\n", " tf.random.set_seed(100)"]}, {"cell_type": "code", "execution_count": 155, "metadata": {}, "outputs": [], "source": ["set_seeds()\n", "model = Sequential()\n", "model.add(Dense(64, activation='relu',\n", " input_shape=(lags,)))\n", "model.add(Dense(64, activation='relu'))\n", "model.add(Dense(1, activation='sigmoid')) # <5>\n", "model.compile(optimizer=optimizer,\n", " loss='binary_crossentropy',\n", " metrics=['accuracy'])"]}, {"cell_type": "code", "execution_count": 156, "metadata": {}, "outputs": [], "source": ["cutoff = '2017-12-31'"]}, {"cell_type": "code", "execution_count": 157, "metadata": {}, "outputs": [], "source": ["training_data = data[data.index < cutoff].copy()"]}, {"cell_type": "code", "execution_count": 158, "metadata": {}, "outputs": [], "source": ["mu, std = training_data.mean(), training_data.std()"]}, {"cell_type": "code", "execution_count": 159, "metadata": {}, "outputs": [], "source": ["training_data_ = (training_data - mu) / std"]}, {"cell_type": "code", "execution_count": 160, "metadata": {}, "outputs": [], "source": ["test_data = data[data.index >= cutoff].copy()"]}, {"cell_type": "code", "execution_count": 161, "metadata": {}, "outputs": [], "source": ["test_data_ = (test_data - mu) / std"]}, {"cell_type": "code", "execution_count": 162, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["CPU times: user 5.15 s, sys: 919 ms, total: 6.07 s\n", "Wall time: 3.33 s\n"]}, {"data": {"text/plain": ["| \n", " | price | \n", "return | \n", "direction | \n", "lag_1 | \n", "lag_2 | \n", "lag_3 | \n", "lag_4 | \n", "lag_5 | \n", "
|---|---|---|---|---|---|---|---|---|
| Date | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
| 2019-12-24 | \n", "1.1087 | \n", "0.0001 | \n", "1 | \n", "0.0007 | \n", "-0.0038 | \n", "0.0008 | \n", "-0.0034 | \n", "0.0006 | \n", "
| 2019-12-26 | \n", "1.1096 | \n", "0.0008 | \n", "1 | \n", "0.0001 | \n", "0.0007 | \n", "-0.0038 | \n", "0.0008 | \n", "-0.0034 | \n", "
| 2019-12-27 | \n", "1.1175 | \n", "0.0071 | \n", "1 | \n", "0.0008 | \n", "0.0001 | \n", "0.0007 | \n", "-0.0038 | \n", "0.0008 | \n", "
| 2019-12-30 | \n", "1.1197 | \n", "0.0020 | \n", "1 | \n", "0.0071 | \n", "0.0008 | \n", "0.0001 | \n", "0.0007 | \n", "-0.0038 | \n", "
| 2019-12-31 | \n", "1.1210 | \n", "0.0012 | \n", "1 | \n", "0.0020 | \n", "0.0071 | \n", "0.0008 | \n", "0.0001 | \n", "0.0007 | \n", "
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["res[['accuracy', 'val_accuracy']].plot(figsize=(10, 6), style='--');\n", "# plt.savefig('../../images/ch05/dnn_plot_metrics.png')"]}, {"cell_type": "code", "execution_count": 165, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["2007/2007 [==============================] - 0s 15us/step\n"]}, {"data": {"text/plain": ["[0.7528249417957407, 0.5151968002319336]"]}, "execution_count": 165, "metadata": {}, "output_type": "execute_result"}], "source": ["model.evaluate(training_data_[cols], training_data['direction'])"]}, {"cell_type": "code", "execution_count": 166, "metadata": {}, "outputs": [], "source": ["pred = model.predict_classes(training_data_[cols])"]}, {"cell_type": "code", "execution_count": 167, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1,\n", " 0, 1, 0, 1, 0, 1, 1, 1], dtype=int32)"]}, "execution_count": 167, "metadata": {}, "output_type": "execute_result"}], "source": ["pred[:30].flatten()"]}, {"cell_type": "code", "execution_count": 168, "metadata": {}, "outputs": [], "source": ["training_data['prediction'] = np.where(pred > 0, 1, -1)"]}, {"cell_type": "code", "execution_count": 169, "metadata": {}, "outputs": [], "source": ["training_data['strategy'] = (training_data['prediction'] *\n", " training_data['return'])"]}, {"cell_type": "code", "execution_count": 170, "metadata": {}, "outputs": [{"data": {"text/plain": ["return 0.826569\n", "strategy 1.238151\n", "dtype: float64"]}, "execution_count": 170, "metadata": {}, "output_type": "execute_result"}], "source": ["training_data[['return', 'strategy']].sum().apply(np.exp)"]}, {"cell_type": "code", "execution_count": 171, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["training_data[['return', 'strategy']].cumsum(\n", " ).apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch05/dl_plot_2.png')"]}, {"cell_type": "code", "execution_count": 172, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["503/503 [==============================] - 0s 29us/step\n"]}, {"data": {"text/plain": ["[0.7452366796449923, 0.4811133146286011]"]}, "execution_count": 172, "metadata": {}, "output_type": "execute_result"}], "source": ["model.evaluate(test_data_[cols], test_data['direction'])"]}, {"cell_type": "code", "execution_count": 173, "metadata": {}, "outputs": [], "source": ["pred = model.predict_classes(test_data_[cols])"]}, {"cell_type": "code", "execution_count": 174, "metadata": {}, "outputs": [], "source": ["test_data['prediction'] = np.where(pred > 0, 1, -1)"]}, {"cell_type": "code", "execution_count": 175, "metadata": {}, "outputs": [{"data": {"text/plain": ["-1 256\n", " 1 247\n", "Name: prediction, dtype: int64"]}, "execution_count": 175, "metadata": {}, "output_type": "execute_result"}], "source": ["test_data['prediction'].value_counts()"]}, {"cell_type": "code", "execution_count": 176, "metadata": {}, "outputs": [], "source": ["test_data['strategy'] = (test_data['prediction'] *\n", " test_data['return'])"]}, {"cell_type": "code", "execution_count": 177, "metadata": {}, "outputs": [{"data": {"text/plain": ["return 0.934478\n", "strategy 1.026139\n", "dtype: float64"]}, "execution_count": 177, "metadata": {}, "output_type": "execute_result"}], "source": ["test_data[['return', 'strategy']].sum().apply(np.exp)"]}, {"cell_type": "code", "execution_count": 178, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["test_data[['return', 'strategy']].cumsum(\n", " ).apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch05/dl_plot_3.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Adding Different Types of Features"]}, {"cell_type": "code", "execution_count": 179, "metadata": {}, "outputs": [], "source": ["data['momentum'] = data['return'].rolling(5).mean().shift(1)"]}, {"cell_type": "code", "execution_count": 180, "metadata": {}, "outputs": [], "source": ["data['volatility'] = data['return'].rolling(20).std().shift(1)"]}, {"cell_type": "code", "execution_count": 181, "metadata": {}, "outputs": [], "source": ["data['distance'] = (data['price'] - data['price'].rolling(50).mean()).shift(1)"]}, {"cell_type": "code", "execution_count": 182, "metadata": {}, "outputs": [], "source": ["data.dropna(inplace=True)"]}, {"cell_type": "code", "execution_count": 183, "metadata": {}, "outputs": [], "source": ["cols.extend(['momentum', 'volatility', 'distance'])"]}, {"cell_type": "code", "execution_count": 184, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": [" price return direction lag_1 lag_2 lag_3 lag_4 lag_5 \\\n", "Date \n", "2019-12-24 1.1087 0.0001 1 0.0007 -0.0038 0.0008 -0.0034 0.0006 \n", "2019-12-26 1.1096 0.0008 1 0.0001 0.0007 -0.0038 0.0008 -0.0034 \n", "2019-12-27 1.1175 0.0071 1 0.0008 0.0001 0.0007 -0.0038 0.0008 \n", "2019-12-30 1.1197 0.0020 1 0.0071 0.0008 0.0001 0.0007 -0.0038 \n", "2019-12-31 1.1210 0.0012 1 0.0020 0.0071 0.0008 0.0001 0.0007 \n", "\n", " momentum volatility distance \n", "Date \n", "2019-12-24 -0.0010 0.0024 0.0005 \n", "2019-12-26 -0.0011 0.0024 0.0004 \n", "2019-12-27 -0.0003 0.0024 0.0012 \n", "2019-12-30 0.0010 0.0028 0.0089 \n", "2019-12-31 0.0021 0.0028 0.0110 \n"]}], "source": ["print(data.round(4).tail())"]}, {"cell_type": "code", "execution_count": 185, "metadata": {}, "outputs": [], "source": ["training_data = data[data.index < cutoff].copy()"]}, {"cell_type": "code", "execution_count": 186, "metadata": {}, "outputs": [], "source": ["mu, std = training_data.mean(), training_data.std()"]}, {"cell_type": "code", "execution_count": 187, "metadata": {}, "outputs": [], "source": ["training_data_ = (training_data - mu) / std"]}, {"cell_type": "code", "execution_count": 188, "metadata": {}, "outputs": [], "source": ["test_data = data[data.index >= cutoff].copy() "]}, {"cell_type": "code", "execution_count": 189, "metadata": {}, "outputs": [], "source": ["test_data_ = (test_data - mu) / std"]}, {"cell_type": "code", "execution_count": 190, "metadata": {}, "outputs": [], "source": ["set_seeds()\n", "model = Sequential()\n", "model.add(Dense(32, activation='relu',\n", " input_shape=(len(cols),)))\n", "model.add(Dense(32, activation='relu'))\n", "model.add(Dense(1, activation='sigmoid'))\n", "model.compile(optimizer=optimizer,\n", " loss='binary_crossentropy',\n", " metrics=['accuracy'])"]}, {"cell_type": "code", "execution_count": 191, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["CPU times: user 2.9 s, sys: 483 ms, total: 3.38 s\n", "Wall time: 1.99 s\n"]}, {"data": {"text/plain": [""]}, "execution_count": 191, "metadata": {}, "output_type": "execute_result"}], "source": ["%%time \n", "model.fit(training_data_[cols], training_data['direction'],\n", " verbose=False, epochs=25)"]}, {"cell_type": "code", "execution_count": 192, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["1957/1957 [==============================] - 0s 23us/step\n"]}, {"data": {"text/plain": ["[0.6812173691585348, 0.5462442636489868]"]}, "execution_count": 192, "metadata": {}, "output_type": "execute_result"}], "source": ["model.evaluate(training_data_[cols], training_data['direction'])"]}, {"cell_type": "code", "execution_count": 193, "metadata": {}, "outputs": [], "source": ["pred = model.predict_classes(training_data_[cols])"]}, {"cell_type": "code", "execution_count": 194, "metadata": {}, "outputs": [], "source": ["training_data['prediction'] = np.where(pred > 0, 1, -1)"]}, {"cell_type": "code", "execution_count": 195, "metadata": {}, "outputs": [], "source": ["training_data['strategy'] = training_data['prediction'] * \\\n", " training_data['return']"]}, {"cell_type": "code", "execution_count": 196, "metadata": {}, "outputs": [{"data": {"text/plain": ["return 0.901074\n", "strategy 1.815211\n", "dtype: float64"]}, "execution_count": 196, "metadata": {}, "output_type": "execute_result"}], "source": ["training_data[['return', 'strategy']].sum().apply(np.exp)"]}, {"cell_type": "code", "execution_count": 197, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["training_data[['return', 'strategy']].cumsum(\n", " ).apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch05/dl_plot_4.png')"]}, {"cell_type": "code", "execution_count": 198, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["503/503 [==============================] - 0s 22us/step\n"]}, {"data": {"text/plain": ["[0.6964824583611005, 0.4990059733390808]"]}, "execution_count": 198, "metadata": {}, "output_type": "execute_result"}], "source": ["model.evaluate(test_data_[cols], test_data['direction'])"]}, {"cell_type": "code", "execution_count": 199, "metadata": {}, "outputs": [], "source": ["pred = model.predict_classes(test_data_[cols])"]}, {"cell_type": "code", "execution_count": 200, "metadata": {}, "outputs": [], "source": ["test_data['prediction'] = np.where(pred > 0, 1, -1)"]}, {"cell_type": "code", "execution_count": 201, "metadata": {}, "outputs": [{"data": {"text/plain": ["-1 339\n", " 1 164\n", "Name: prediction, dtype: int64"]}, "execution_count": 201, "metadata": {}, "output_type": "execute_result"}], "source": ["test_data['prediction'].value_counts()"]}, {"cell_type": "code", "execution_count": 202, "metadata": {}, "outputs": [], "source": ["test_data['strategy'] = (test_data['prediction'] *\n", " test_data['return'])"]}, {"cell_type": "code", "execution_count": 203, "metadata": {}, "outputs": [{"data": {"text/plain": ["return 0.934478\n", "strategy 1.109780\n", "dtype: float64"]}, "execution_count": 203, "metadata": {}, "output_type": "execute_result"}], "source": ["test_data[['return', 'strategy']].sum().apply(np.exp)"]}, {"cell_type": "code", "execution_count": 204, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["test_data[['return', 'strategy']].cumsum(\n", " ).apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch05/dl_plot_5.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"anaconda-cloud": {}, "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch05/LRVectorBacktester.py b/ch05/LRVectorBacktester.py new file mode 100644 index 0000000..e072a1e --- /dev/null +++ b/ch05/LRVectorBacktester.py @@ -0,0 +1,141 @@ +# +# Python Module with Class +# for Vectorized Backtesting +# of Linear Regression-based Strategies +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import numpy as np +import pandas as pd + + +class LRVectorBacktester(object): + ''' Class for the vectorized backtesting of + Linear Regression-based trading strategies. + + Attributes + ========== + symbol: str + TR RIC (financial instrument) to work with + start: str + start date for data selection + end: str + end date for data selection + amount: int, float + amount to be invested at the beginning + tc: float + proportional transaction costs (e.g. 0.5% = 0.005) per trade + + Methods + ======= + get_data: + retrieves and prepares the base data set + select_data: + selects a sub-set of the data + prepare_lags: + prepares the lagged data for the regression + fit_model: + implements the regression step + run_strategy: + runs the backtest for the regression-based strategy + plot_results: + plots the performance of the strategy compared to the symbol + ''' + + def __init__(self, symbol, start, end, amount, tc): + self.symbol = symbol + self.start = start + self.end = end + self.amount = amount + self.tc = tc + self.results = None + self.get_data() + + def get_data(self): + ''' Retrieves and prepares the data. + ''' + raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv', + index_col=0, parse_dates=True).dropna() + raw = pd.DataFrame(raw[self.symbol]) + raw = raw.loc[self.start:self.end] + raw.rename(columns={self.symbol: 'price'}, inplace=True) + raw['returns'] = np.log(raw / raw.shift(1)) + self.data = raw.dropna() + + def select_data(self, start, end): + ''' Selects sub-sets of the financial data. + ''' + data = self.data[(self.data.index >= start) & + (self.data.index <= end)].copy() + return data + + def prepare_lags(self, start, end): + ''' Prepares the lagged data for the regression and prediction steps. + ''' + data = self.select_data(start, end) + self.cols = [] + for lag in range(1, self.lags + 1): + col = f'lag_{lag}' + data[col] = data['returns'].shift(lag) + self.cols.append(col) + data.dropna(inplace=True) + self.lagged_data = data + + def fit_model(self, start, end): + ''' Implements the regression step. + ''' + self.prepare_lags(start, end) + reg = np.linalg.lstsq(self.lagged_data[self.cols], + np.sign(self.lagged_data['returns']), + rcond=None)[0] + self.reg = reg + + def run_strategy(self, start_in, end_in, start_out, end_out, lags=3): + ''' Backtests the trading strategy. + ''' + self.lags = lags + self.fit_model(start_in, end_in) + self.results = self.select_data(start_out, end_out).iloc[lags:] + self.prepare_lags(start_out, end_out) + prediction = np.sign(np.dot(self.lagged_data[self.cols], self.reg)) + self.results['prediction'] = prediction + self.results['strategy'] = self.results['prediction'] * \ + self.results['returns'] + # determine when a trade takes place + trades = self.results['prediction'].diff().fillna(0) != 0 + # subtract transaction costs from return when trade takes place + self.results['strategy'][trades] -= self.tc + self.results['creturns'] = self.amount * \ + self.results['returns'].cumsum().apply(np.exp) + self.results['cstrategy'] = self.amount * \ + self.results['strategy'].cumsum().apply(np.exp) + # gross performance of the strategy + aperf = self.results['cstrategy'].iloc[-1] + # out-/underperformance of strategy + operf = aperf - self.results['creturns'].iloc[-1] + return round(aperf, 2), round(operf, 2) + + def plot_results(self): + ''' Plots the cumulative performance of the trading strategy + compared to the symbol. + ''' + if self.results is None: + print('No results to plot yet. Run a strategy.') + title = '%s | TC = %.4f' % (self.symbol, self.tc) + self.results[['creturns', 'cstrategy']].plot(title=title, + figsize=(10, 6)) + + +if __name__ == '__main__': + lrbt = LRVectorBacktester('.SPX', '2010-1-1', '2018-06-29', 10000, 0.0) + print(lrbt.run_strategy('2010-1-1', '2019-12-31', + '2010-1-1', '2019-12-31')) + print(lrbt.run_strategy('2010-1-1', '2015-12-31', + '2016-1-1', '2019-12-31')) + lrbt = LRVectorBacktester('GDX', '2010-1-1', '2019-12-31', 10000, 0.001) + print(lrbt.run_strategy('2010-1-1', '2019-12-31', + '2010-1-1', '2019-12-31', lags=5)) + print(lrbt.run_strategy('2010-1-1', '2016-12-31', + '2017-1-1', '2019-12-31', lags=5)) diff --git a/ch05/ScikitVectorBacktester.py b/ch05/ScikitVectorBacktester.py new file mode 100644 index 0000000..cd10cd1 --- /dev/null +++ b/ch05/ScikitVectorBacktester.py @@ -0,0 +1,158 @@ +# +# Python Module with Class +# for Vectorized Backtesting +# of Machine Learning-based Strategies +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import numpy as np +import pandas as pd +from sklearn import linear_model + + +class ScikitVectorBacktester(object): + ''' Class for the vectorized backtesting of + Machine Learning-based trading strategies. + + Attributes + ========== + symbol: str + TR RIC (financial instrument) to work with + start: str + start date for data selection + end: str + end date for data selection + amount: int, float + amount to be invested at the beginning + tc: float + proportional transaction costs (e.g. 0.5% = 0.005) per trade + model: str + either 'regression' or 'logistic' + + Methods + ======= + get_data: + retrieves and prepares the base data set + select_data: + selects a sub-set of the data + prepare_features: + prepares the features data for the model fitting + fit_model: + implements the fitting step + run_strategy: + runs the backtest for the regression-based strategy + plot_results: + plots the performance of the strategy compared to the symbol + ''' + + def __init__(self, symbol, start, end, amount, tc, model): + self.symbol = symbol + self.start = start + self.end = end + self.amount = amount + self.tc = tc + self.results = None + if model == 'regression': + self.model = linear_model.LinearRegression() + elif model == 'logistic': + self.model = linear_model.LogisticRegression(C=1e6, + solver='lbfgs', multi_class='ovr', max_iter=1000) + else: + raise ValueError('Model not known or not yet implemented.') + self.get_data() + + def get_data(self): + ''' Retrieves and prepares the data. + ''' + raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv', + index_col=0, parse_dates=True).dropna() + raw = pd.DataFrame(raw[self.symbol]) + raw = raw.loc[self.start:self.end] + raw.rename(columns={self.symbol: 'price'}, inplace=True) + raw['returns'] = np.log(raw / raw.shift(1)) + self.data = raw.dropna() + + def select_data(self, start, end): + ''' Selects sub-sets of the financial data. + ''' + data = self.data[(self.data.index >= start) & + (self.data.index <= end)].copy() + return data + + def prepare_features(self, start, end): + ''' Prepares the feature columns for the regression and prediction steps. + ''' + self.data_subset = self.select_data(start, end) + self.feature_columns = [] + for lag in range(1, self.lags + 1): + col = 'lag_{}'.format(lag) + self.data_subset[col] = self.data_subset['returns'].shift(lag) + self.feature_columns.append(col) + self.data_subset.dropna(inplace=True) + + def fit_model(self, start, end): + ''' Implements the fitting step. + ''' + self.prepare_features(start, end) + self.model.fit(self.data_subset[self.feature_columns], + np.sign(self.data_subset['returns'])) + + def run_strategy(self, start_in, end_in, start_out, end_out, lags=3): + ''' Backtests the trading strategy. + ''' + self.lags = lags + self.fit_model(start_in, end_in) + # data = self.select_data(start_out, end_out) + self.prepare_features(start_out, end_out) + prediction = self.model.predict( + self.data_subset[self.feature_columns]) + self.data_subset['prediction'] = prediction + self.data_subset['strategy'] = (self.data_subset['prediction'] * + self.data_subset['returns']) + # determine when a trade takes place + trades = self.data_subset['prediction'].diff().fillna(0) != 0 + # subtract transaction costs from return when trade takes place + self.data_subset['strategy'][trades] -= self.tc + self.data_subset['creturns'] = (self.amount * + self.data_subset['returns'].cumsum().apply(np.exp)) + self.data_subset['cstrategy'] = (self.amount * + self.data_subset['strategy'].cumsum().apply(np.exp)) + self.results = self.data_subset + # absolute performance of the strategy + aperf = self.results['cstrategy'].iloc[-1] + # out-/underperformance of strategy + operf = aperf - self.results['creturns'].iloc[-1] + return round(aperf, 2), round(operf, 2) + + def plot_results(self): + ''' Plots the cumulative performance of the trading strategy + compared to the symbol. + ''' + if self.results is None: + print('No results to plot yet. Run a strategy.') + title = '%s | TC = %.4f' % (self.symbol, self.tc) + self.results[['creturns', 'cstrategy']].plot(title=title, + figsize=(10, 6)) + + +if __name__ == '__main__': + scibt = ScikitVectorBacktester('.SPX', '2010-1-1', '2019-12-31', + 10000, 0.0, 'regression') + print(scibt.run_strategy('2010-1-1', '2019-12-31', + '2010-1-1', '2019-12-31')) + print(scibt.run_strategy('2010-1-1', '2016-12-31', + '2017-1-1', '2019-12-31')) + scibt = ScikitVectorBacktester('.SPX', '2010-1-1', '2019-12-31', + 10000, 0.0, 'logistic') + print(scibt.run_strategy('2010-1-1', '2019-12-31', + '2010-1-1', '2019-12-31')) + print(scibt.run_strategy('2010-1-1', '2016-12-31', + '2017-1-1', '2019-12-31')) + scibt = ScikitVectorBacktester('.SPX', '2010-1-1', '2019-12-31', + 10000, 0.001, 'logistic') + print(scibt.run_strategy('2010-1-1', '2019-12-31', + '2010-1-1', '2019-12-31', lags=15)) + print(scibt.run_strategy('2010-1-1', '2013-12-31', + '2014-1-1', '2019-12-31', lags=15)) diff --git a/ch06/BacktestBase.py b/ch06/BacktestBase.py new file mode 100644 index 0000000..5b31861 --- /dev/null +++ b/ch06/BacktestBase.py @@ -0,0 +1,158 @@ +# +# Python Script with Base Class +# for Event-based Backtesting +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import numpy as np +import pandas as pd +from pylab import mpl, plt +plt.style.use('seaborn') +mpl.rcParams['font.family'] = 'serif' + + +class BacktestBase(object): + ''' Base class for event-based backtesting of trading strategies. + + Attributes + ========== + symbol: str + TR RIC (financial instrument) to be used + start: str + start date for data selection + end: str + end date for data selection + amount: float + amount to be invested either once or per trade + ftc: float + fixed transaction costs per trade (buy or sell) + ptc: float + proportional transaction costs per trade (buy or sell) + + Methods + ======= + get_data: + retrieves and prepares the base data set + plot_data: + plots the closing price for the symbol + get_date_price: + returns the date and price for the given bar + print_balance: + prints out the current (cash) balance + print_net_wealth: + prints auf the current net wealth + place_buy_order: + places a buy order + place_sell_order: + places a sell order + close_out: + closes out a long or short position + ''' + + def __init__(self, symbol, start, end, amount, + ftc=0.0, ptc=0.0, verbose=True): + self.symbol = symbol + self.start = start + self.end = end + self.initial_amount = amount + self.amount = amount + self.ftc = ftc + self.ptc = ptc + self.units = 0 + self.position = 0 + self.trades = 0 + self.verbose = verbose + self.get_data() + + def get_data(self): + ''' Retrieves and prepares the data. + ''' + raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv', + index_col=0, parse_dates=True).dropna() + raw = pd.DataFrame(raw[self.symbol]) + raw = raw.loc[self.start:self.end] + raw.rename(columns={self.symbol: 'price'}, inplace=True) + raw['return'] = np.log(raw / raw.shift(1)) + self.data = raw.dropna() + + def plot_data(self, cols=None): + ''' Plots the closing prices for symbol. + ''' + if cols is None: + cols = ['price'] + self.data['price'].plot(figsize=(10, 6), title=self.symbol) + + def get_date_price(self, bar): + ''' Return date and price for bar. + ''' + date = str(self.data.index[bar])[:10] + price = self.data.price.iloc[bar] + return date, price + + def print_balance(self, bar): + ''' Print out current cash balance info. + ''' + date, price = self.get_date_price(bar) + print(f'{date} | current balance {self.amount:.2f}') + + def print_net_wealth(self, bar): + ''' Print out current cash balance info. + ''' + date, price = self.get_date_price(bar) + net_wealth = self.units * price + self.amount + print(f'{date} | current net wealth {net_wealth:.2f}') + + def place_buy_order(self, bar, units=None, amount=None): + ''' Place a buy order. + ''' + date, price = self.get_date_price(bar) + if units is None: + units = int(amount / price) + self.amount -= (units * price) * (1 + self.ptc) + self.ftc + self.units += units + self.trades += 1 + if self.verbose: + print(f'{date} | selling {units} units at {price:.2f}') + self.print_balance(bar) + self.print_net_wealth(bar) + + def place_sell_order(self, bar, units=None, amount=None): + ''' Place a sell order. + ''' + date, price = self.get_date_price(bar) + if units is None: + units = int(amount / price) + self.amount += (units * price) * (1 - self.ptc) - self.ftc + self.units -= units + self.trades += 1 + if self.verbose: + print(f'{date} | selling {units} units at {price:.2f}') + self.print_balance(bar) + self.print_net_wealth(bar) + + def close_out(self, bar): + ''' Closing out a long or short position. + ''' + date, price = self.get_date_price(bar) + self.amount += self.units * price + self.units = 0 + self.trades += 1 + if self.verbose: + print(f'{date} | inventory {self.units} units at {price:.2f}') + print('=' * 55) + print('Final balance [$] {:.2f}'.format(self.amount)) + perf = ((self.amount - self.initial_amount) / + self.initial_amount * 100) + print('Net Performance [%] {:.2f}'.format(perf)) + print('Trades Executed [#] {:.2f}'.format(self.trades)) + print('=' * 55) + + +if __name__ == '__main__': + bb = BacktestBase('AAPL.O', '2010-1-1', '2019-12-31', 10000) + print(bb.data.info()) + print(bb.data.tail()) + bb.plot_data() + plt.savefig('../../images/ch06/backtestbaseplot.png') diff --git a/ch06/BacktestLongOnly.py b/ch06/BacktestLongOnly.py new file mode 100644 index 0000000..08587b0 --- /dev/null +++ b/ch06/BacktestLongOnly.py @@ -0,0 +1,118 @@ +# +# Python Script with Long Only Class +# for Event-based Backtesting +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +from BacktestBase import * + + +class BacktestLongOnly(BacktestBase): + + def run_sma_strategy(self, SMA1, SMA2): + ''' Backtesting a SMA-based strategy. + + Parameters + ========== + SMA1, SMA2: int + shorter and longer term simple moving average (in days) + ''' + msg = f'\n\nRunning SMA strategy | SMA1={SMA1} & SMA2={SMA2}' + msg += f'\nfixed costs {self.ftc} | ' + msg += f'proportional costs {self.ptc}' + print(msg) + print('=' * 55) + self.position = 0 # initial neutral position + self.trades = 0 # no trades yet + self.amount = self.initial_amount # reset initial capital + self.data['SMA1'] = self.data['price'].rolling(SMA1).mean() + self.data['SMA2'] = self.data['price'].rolling(SMA2).mean() + + for bar in range(SMA2, len(self.data)): + if self.position == 0: + if self.data['SMA1'].iloc[bar] > self.data['SMA2'].iloc[bar]: + self.place_buy_order(bar, amount=self.amount) + self.position = 1 # long position + elif self.position == 1: + if self.data['SMA1'].iloc[bar] < self.data['SMA2'].iloc[bar]: + self.place_sell_order(bar, units=self.units) + self.position = 0 # market neutral + self.close_out(bar) + + def run_momentum_strategy(self, momentum): + ''' Backtesting a momentum-based strategy. + + Parameters + ========== + momentum: int + number of days for mean return calculation + ''' + msg = f'\n\nRunning momentum strategy | {momentum} days' + msg += f'\nfixed costs {self.ftc} | ' + msg += f'proportional costs {self.ptc}' + print(msg) + print('=' * 55) + self.position = 0 # initial neutral position + self.trades = 0 # no trades yet + self.amount = self.initial_amount # reset initial capital + self.data['momentum'] = self.data['return'].rolling(momentum).mean() + for bar in range(momentum, len(self.data)): + if self.position == 0: + if self.data['momentum'].iloc[bar] > 0: + self.place_buy_order(bar, amount=self.amount) + self.position = 1 # long position + elif self.position == 1: + if self.data['momentum'].iloc[bar] < 0: + self.place_sell_order(bar, units=self.units) + self.position = 0 # market neutral + self.close_out(bar) + + def run_mean_reversion_strategy(self, SMA, threshold): + ''' Backtesting a mean reversion-based strategy. + + Parameters + ========== + SMA: int + simple moving average in days + threshold: float + absolute value for deviation-based signal relative to SMA + ''' + msg = f'\n\nRunning mean reversion strategy | ' + msg += f'SMA={SMA} & thr={threshold}' + msg += f'\nfixed costs {self.ftc} | ' + msg += f'proportional costs {self.ptc}' + print(msg) + print('=' * 55) + self.position = 0 + self.trades = 0 + self.amount = self.initial_amount + + self.data['SMA'] = self.data['price'].rolling(SMA).mean() + + for bar in range(SMA, len(self.data)): + if self.position == 0: + if (self.data['price'].iloc[bar] < + self.data['SMA'].iloc[bar] - threshold): + self.place_buy_order(bar, amount=self.amount) + self.position = 1 + elif self.position == 1: + if self.data['price'].iloc[bar] >= self.data['SMA'].iloc[bar]: + self.place_sell_order(bar, units=self.units) + self.position = 0 + self.close_out(bar) + + +if __name__ == '__main__': + def run_strategies(): + lobt.run_sma_strategy(42, 252) + lobt.run_momentum_strategy(60) + lobt.run_mean_reversion_strategy(50, 5) + lobt = BacktestLongOnly('AAPL.O', '2010-1-1', '2019-12-31', 10000, + verbose=False) + run_strategies() + # transaction costs: 10 USD fix, 1% variable + lobt = BacktestLongOnly('AAPL.O', '2010-1-1', '2019-12-31', + 10000, 10.0, 0.01, False) + run_strategies() diff --git a/ch06/BacktestLongShort.py b/ch06/BacktestLongShort.py new file mode 100644 index 0000000..429a5ca --- /dev/null +++ b/ch06/BacktestLongShort.py @@ -0,0 +1,123 @@ +# +# Python Script with Long Short Class +# for Event-based Backtesting +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +from BacktestBase import * + + +class BacktestLongShort(BacktestBase): + + def go_long(self, bar, units=None, amount=None): + if self.position == -1: + self.place_buy_order(bar, units=-self.units) + if units: + self.place_buy_order(bar, units=units) + elif amount: + if amount == 'all': + amount = self.amount + self.place_buy_order(bar, amount=amount) + + def go_short(self, bar, units=None, amount=None): + if self.position == 1: + self.place_sell_order(bar, units=self.units) + if units: + self.place_sell_order(bar, units=units) + elif amount: + if amount == 'all': + amount = self.amount + self.place_sell_order(bar, amount=amount) + + def run_sma_strategy(self, SMA1, SMA2): + msg = f'\n\nRunning SMA strategy | SMA1={SMA1} & SMA2={SMA2}' + msg += f'\nfixed costs {self.ftc} | ' + msg += f'proportional costs {self.ptc}' + print(msg) + print('=' * 55) + self.position = 0 # initial neutral position + self.trades = 0 # no trades yet + self.amount = self.initial_amount # reset initial capital + self.data['SMA1'] = self.data['price'].rolling(SMA1).mean() + self.data['SMA2'] = self.data['price'].rolling(SMA2).mean() + + for bar in range(SMA2, len(self.data)): + if self.position in [0, -1]: + if self.data['SMA1'].iloc[bar] > self.data['SMA2'].iloc[bar]: + self.go_long(bar, amount='all') + self.position = 1 # long position + if self.position in [0, 1]: + if self.data['SMA1'].iloc[bar] < self.data['SMA2'].iloc[bar]: + self.go_short(bar, amount='all') + self.position = -1 # short position + self.close_out(bar) + + def run_momentum_strategy(self, momentum): + msg = f'\n\nRunning momentum strategy | {momentum} days' + msg += f'\nfixed costs {self.ftc} | ' + msg += f'proportional costs {self.ptc}' + print(msg) + print('=' * 55) + self.position = 0 # initial neutral position + self.trades = 0 # no trades yet + self.amount = self.initial_amount # reset initial capital + self.data['momentum'] = self.data['return'].rolling(momentum).mean() + for bar in range(momentum, len(self.data)): + if self.position in [0, -1]: + if self.data['momentum'].iloc[bar] > 0: + self.go_long(bar, amount='all') + self.position = 1 # long position + if self.position in [0, 1]: + if self.data['momentum'].iloc[bar] <= 0: + self.go_short(bar, amount='all') + self.position = -1 # short position + self.close_out(bar) + + def run_mean_reversion_strategy(self, SMA, threshold): + msg = f'\n\nRunning mean reversion strategy | ' + msg += f'SMA={SMA} & thr={threshold}' + msg += f'\nfixed costs {self.ftc} | ' + msg += f'proportional costs {self.ptc}' + print(msg) + print('=' * 55) + self.position = 0 # initial neutral position + self.trades = 0 # no trades yet + self.amount = self.initial_amount # reset initial capital + + self.data['SMA'] = self.data['price'].rolling(SMA).mean() + + for bar in range(SMA, len(self.data)): + if self.position == 0: + if (self.data['price'].iloc[bar] < + self.data['SMA'].iloc[bar] - threshold): + self.go_long(bar, amount=self.initial_amount) + self.position = 1 + elif (self.data['price'].iloc[bar] > + self.data['SMA'].iloc[bar] + threshold): + self.go_short(bar, amount=self.initial_amount) + self.position = -1 + elif self.position == 1: + if self.data['price'].iloc[bar] >= self.data['SMA'].iloc[bar]: + self.place_sell_order(bar, units=self.units) + self.position = 0 + elif self.position == -1: + if self.data['price'].iloc[bar] <= self.data['SMA'].iloc[bar]: + self.place_buy_order(bar, units=-self.units) + self.position = 0 + self.close_out(bar) + + +if __name__ == '__main__': + def run_strategies(): + lsbt.run_sma_strategy(42, 252) + lsbt.run_momentum_strategy(60) + lsbt.run_mean_reversion_strategy(50, 5) + lsbt = BacktestLongShort('EUR=', '2010-1-1', '2019-12-31', 10000, + verbose=False) + run_strategies() + # transaction costs: 10 USD fix, 1% variable + lsbt = BacktestLongShort('AAPL.O', '2010-1-1', '2019-12-31', + 10000, 10.0, 0.01, False) + run_strategies() diff --git a/ch07/07_pyalgo.ipynb b/ch07/07_pyalgo.ipynb new file mode 100644 index 0000000..7b7610f --- /dev/null +++ b/ch07/07_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading "]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Chapter 07 — Working with Real-Time Data and Sockets**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Visualizing Streaming Data with Plotly"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### The Basics"]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["import zmq\n", "from datetime import datetime\n", "import plotly.graph_objects as go"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["symbol = 'SYMBOL'"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [{"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "ba95385085734ec4a103893d884a4f60", "version_major": 2, "version_minor": 0}, "text/plain": ["FigureWidget({\n", " 'data': [{'type': 'scatter', 'uid': '9bdc6757-dd01-49a1-be7d-9d41cf280b90'}], 'layout': {'t\u2026"]}, "metadata": {}, "output_type": "display_data"}], "source": ["fig = go.FigureWidget()\n", "fig.add_scatter()\n", "fig"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": ["context = zmq.Context()"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": ["socket = context.socket(zmq.SUB)"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": ["socket.connect('tcp://0.0.0.0:5555')"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": ["socket.setsockopt_string(zmq.SUBSCRIBE, 'SYMBOL')"]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": ["times = list()\n", "prices = list()"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": ["for _ in range(50):\n", " msg = socket.recv_string()\n", " t = datetime.now()\n", " times.append(t)\n", " _, price = msg.split()\n", " prices.append(float(price))\n", " fig.data[0].x = times\n", " fig.data[0].y = prices"]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "5f1a651c1d2049c9bf9d1337fbb66313", "version_major": 2, "version_minor": 0}, "text/plain": ["FigureWidget({\n", " 'data': [{'name': 'SYMBOL', 'type': 'scatter', 'uid': '8aa33f31-7e9f-4a50-a563-75211b8241df\u2026"]}, "metadata": {}, "output_type": "display_data"}], "source": ["fig = go.FigureWidget()\n", "fig.add_scatter(name='SYMBOL')\n", "fig.add_scatter(name='SMA1', line=dict(width=1, dash='dot'),\n", " mode='lines+markers')\n", "fig.add_scatter(name='SMA2', line=dict(width=1, dash='dash'),\n", " mode='lines+markers')\n", "fig"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": ["import pandas as pd"]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": ["df = pd.DataFrame()"]}, {"cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": ["for _ in range(75):\n", " msg = socket.recv_string()\n", " t = datetime.now()\n", " sym, price = msg.split()\n", " df = df.append(pd.DataFrame({sym: float(price)}, index=[t]))\n", " df['SMA1'] = df[sym].rolling(5).mean()\n", " df['SMA2'] = df[sym].rolling(10).mean()\n", " fig.data[0].x = df.index\n", " fig.data[1].x = df.index\n", " fig.data[2].x = df.index\n", " fig.data[0].y = df[sym]\n", " fig.data[1].y = df['SMA1']\n", " fig.data[2].y = df['SMA2']"]}, {"cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": ["from plotly.subplots import make_subplots"]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": ["f = make_subplots(rows=3, cols=1, shared_xaxes=True)\n", "f.append_trace(go.Scatter(name='SYMBOL'), row=1, col=1)\n", "f.append_trace(go.Scatter(name='RETURN', line=dict(width=1, dash='dot'),\n", " mode='lines+markers', marker={'symbol': 'triangle-up'}),\n", " row=2, col=1)\n", "f.append_trace(go.Scatter(name='MOMENTUM', line=dict(width=1, dash='dash'),\n", " mode='lines+markers', marker={'symbol': 'x'}), row=3, col=1)\n", "# f.update_layout(height=600)"]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": ["fig = go.FigureWidget(f)"]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [{"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "d091b40017f040fba5703c023d2e3ff3", "version_major": 2, "version_minor": 0}, "text/plain": ["FigureWidget({\n", " 'data': [{'name': 'SYMBOL',\n", " 'type': 'scatter',\n", " 'uid': 'd8f37a5f\u2026"]}, "metadata": {}, "output_type": "display_data"}], "source": ["fig"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": ["import numpy as np"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": ["df = pd.DataFrame()"]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": ["for _ in range(75):\n", " msg = socket.recv_string()\n", " t = datetime.now()\n", " sym, price = msg.split()\n", " df = df.append(pd.DataFrame({sym: float(price)}, index=[t]))\n", " df['RET'] = np.log(df[sym] / df[sym].shift(1))\n", " df['MOM'] = df['RET'].rolling(10).mean()\n", " fig.data[0].x = df.index\n", " fig.data[1].x = df.index\n", " fig.data[2].x = df.index\n", " fig.data[0].y = df[sym]\n", " fig.data[1].y = df['RET']\n", " fig.data[2].y = df['MOM']"]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": ["socket = context.socket(zmq.SUB)"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": ["socket.connect('tcp://0.0.0.0:5556')"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": ["socket.setsockopt_string(zmq.SUBSCRIBE, '')"]}, {"cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["49.102 19.185 74.012 26.288 69.924 90.448 60.010 30.055\n", "48.869 80.757 13.682 87.540 24.016 93.654 28.022 73.590\n", "87.966 12.753 25.665 84.953 41.787 47.367 11.784 15.018\n", "23.722 19.868 19.881 3.453 58.011 6.336 36.881 7.048\n", "68.677 85.995 83.560 13.433 53.904 29.649 94.214 1.951\n"]}], "source": ["for _ in range(5):\n", " msg = socket.recv_string()\n", " print(msg)"]}, {"cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [{"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "0db232d0b6584629bf127769a90415c2", "version_major": 2, "version_minor": 0}, "text/plain": ["FigureWidget({\n", " 'data': [{'type': 'bar', 'uid': '325ded67-8023-45c7-9d9c-c016d2bc0da0'}], 'layout': {'templ\u2026"]}, "metadata": {}, "output_type": "display_data"}], "source": ["fig = go.FigureWidget()\n", "fig.add_bar()\n", "fig"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": ["x = list('abcdefgh')\n", "fig.data[0].x = x\n", "for _ in range(100):\n", " msg = socket.recv_string()\n", " y = msg.split()\n", " y = [float(n) for n in y]\n", " fig.data[0].y = y"]}, {"cell_type": "markdown", "metadata": {}, "source": ["
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"anaconda-cloud": {}, "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch07/BarsServer.py b/ch07/BarsServer.py new file mode 100644 index 0000000..db69358 --- /dev/null +++ b/ch07/BarsServer.py @@ -0,0 +1,23 @@ +# +# Python Script to Serve +# Random Bars Data +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import zmq +import math +import time +import random + +context = zmq.Context() +socket = context.socket(zmq.PUB) +socket.bind('tcp://0.0.0.0:5556') + +while True: + bars = [random.random() * 100 for _ in range(8)] + msg = ' '.join([f'{bar:.3f}' for bar in bars]) + print(msg) + socket.send_string(msg) + time.sleep(random.random() * 2) diff --git a/ch07/OnlineAlgorithm.py b/ch07/OnlineAlgorithm.py new file mode 100644 index 0000000..fd958dc --- /dev/null +++ b/ch07/OnlineAlgorithm.py @@ -0,0 +1,42 @@ +# +# Python Script +# with Online Trading Algorithm +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import zmq +import datetime +import numpy as np +import pandas as pd + +context = zmq.Context() +socket = context.socket(zmq.SUB) +socket.connect('tcp://0.0.0.0:5555') +socket.setsockopt_string(zmq.SUBSCRIBE, 'SYMBOL') + +df = pd.DataFrame() +mom = 3 +min_length = mom + 1 + +while True: + data = socket.recv_string() + t = datetime.datetime.now() + sym, value = data.split() + df = df.append(pd.DataFrame({sym: float(value)}, index=[t])) + dr = df.resample('5s', label='right').last() + dr['returns'] = np.log(dr / dr.shift(1)) + if len(dr) > min_length: + min_length += 1 + dr['momentum'] = np.sign(dr['returns'].rolling(mom).mean()) + print('\n' + '=' * 51) + print('NEW SIGNAL | {}'.format(datetime.datetime.now())) + print('=' * 51) + print(dr.iloc[:-1].tail()) + if dr['momentum'].iloc[-2] == 1.0: + print('\nLong market position.') + # take some action (e.g. place buy order) + elif dr['momentum'].iloc[-2] == -1.0: + print('\nShort market position.') + # take some action (e.g. place sell order) diff --git a/ch07/TickClient.py b/ch07/TickClient.py new file mode 100644 index 0000000..176cd22 --- /dev/null +++ b/ch07/TickClient.py @@ -0,0 +1,18 @@ +# +# Python Script +# with Tick Data Client +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import zmq + +context = zmq.Context() +socket = context.socket(zmq.SUB) +socket.connect('tcp://0.0.0.0:5555') +socket.setsockopt_string(zmq.SUBSCRIBE, 'SYMBOL') + +while True: + data = socket.recv_string() + print(data) diff --git a/ch07/TickServer.py b/ch07/TickServer.py new file mode 100644 index 0000000..e83295b --- /dev/null +++ b/ch07/TickServer.py @@ -0,0 +1,45 @@ +# +# Python Script to Simulate a +# Financial Tick Data Server +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import zmq +import math +import time +import random + +context = zmq.Context() +socket = context.socket(zmq.PUB) +socket.bind('tcp://0.0.0.0:5555') + + +class InstrumentPrice(object): + def __init__(self): + self.symbol = 'SYMBOL' + self.t = time.time() + self.value = 100. + self.sigma = 0.4 + self.r = 0.01 + + def simulate_value(self): + ''' Generates a new, random stock price. + ''' + t = time.time() + dt = (t - self.t) / (252 * 8 * 60 * 60) + dt *= 500 + self.t = t + self.value *= math.exp((self.r - 0.5 * self.sigma ** 2) * dt + + self.sigma * math.sqrt(dt) * random.gauss(0, 1)) + return self.value + + +ip = InstrumentPrice() + +while True: + msg = '{} {:.2f}'.format(ip.symbol, ip.simulate_value()) + print(msg) + socket.send_string(msg) + time.sleep(random.random() * 2) diff --git a/ch08/08_pyalgo.ipynb b/ch08/08_pyalgo.ipynb new file mode 100644 index 0000000..1bc9a3f --- /dev/null +++ b/ch08/08_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading "]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Chapter 08 — CFD Trading with Oanda**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## The Oanda API"]}, {"cell_type": "markdown", "metadata": {}, "source": ["`pip install git+https://github.com/yhilpisch/tpqoa.git`"]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["import tpqoa"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["api = tpqoa.tpqoa('../pyalgo.cfg')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Retrieving Historical Data"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Looking Up Instruments Available for Trading"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [{"data": {"text/plain": ["[('AUD/CAD', 'AUD_CAD'),\n", " ('AUD/CHF', 'AUD_CHF'),\n", " ('AUD/HKD', 'AUD_HKD'),\n", " ('AUD/JPY', 'AUD_JPY'),\n", " ('AUD/NZD', 'AUD_NZD'),\n", " ('AUD/SGD', 'AUD_SGD'),\n", " ('AUD/USD', 'AUD_USD'),\n", " ('Australia 200', 'AU200_AUD'),\n", " ('Brent Crude Oil', 'BCO_USD'),\n", " ('Bund', 'DE10YB_EUR'),\n", " ('CAD/CHF', 'CAD_CHF'),\n", " ('CAD/HKD', 'CAD_HKD'),\n", " ('CAD/JPY', 'CAD_JPY'),\n", " ('CAD/SGD', 'CAD_SGD'),\n", " ('CHF/HKD', 'CHF_HKD')]"]}, "execution_count": 3, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_instruments()[:15]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Backtesting a Momentum Strategy on Minute Bars"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Help on method get_history in module tpqoa.tpqoa:\n", "\n", "get_history(instrument, start, end, granularity, price, localize=True) method of tpqoa.tpqoa.tpqoa instance\n", " Retrieves historical data for instrument.\n", " \n", " Parameters\n", " ==========\n", " instrument: string\n", " valid instrument name\n", " start, end: datetime, str\n", " Python datetime or string objects for start and end\n", " granularity: string\n", " a string like 'S5', 'M1' or 'D'\n", " price: string\n", " one of 'A' (ask), 'B' (bid) or 'M' (middle)\n", " \n", " Returns\n", " =======\n", " data: pd.DataFrame\n", " pandas DataFrame object with data\n", "\n"]}], "source": ["help(api.get_history)"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": ["instrument = 'EUR_USD'\n", "start = '2020-05-27'\n", "end = '2020-05-29'\n", "granularity = 'M1'\n", "price = 'M'"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": ["data = api.get_history(instrument, start, end,\n", " granularity, price)"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "DatetimeIndex: 2822 entries, 2020-05-27 00:00:00 to 2020-05-28 23:59:00\n", "Data columns (total 6 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 o 2822 non-null float64\n", " 1 h 2822 non-null float64\n", " 2 l 2822 non-null float64\n", " 3 c 2822 non-null float64\n", " 4 volume 2822 non-null int64 \n", " 5 complete 2822 non-null bool \n", "dtypes: bool(1), float64(4), int64(1)\n", "memory usage: 135.0 KB\n"]}], "source": ["data.info()"]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [{"data": {"text/html": ["
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"anaconda-cloud": {}, "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch05/LRVectorBacktester.py b/ch05/LRVectorBacktester.py new file mode 100644 index 0000000..e072a1e --- /dev/null +++ b/ch05/LRVectorBacktester.py @@ -0,0 +1,141 @@ +# +# Python Module with Class +# for Vectorized Backtesting +# of Linear Regression-based Strategies +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import numpy as np +import pandas as pd + + +class LRVectorBacktester(object): + ''' Class for the vectorized backtesting of + Linear Regression-based trading strategies. + + Attributes + ========== + symbol: str + TR RIC (financial instrument) to work with + start: str + start date for data selection + end: str + end date for data selection + amount: int, float + amount to be invested at the beginning + tc: float + proportional transaction costs (e.g. 0.5% = 0.005) per trade + + Methods + ======= + get_data: + retrieves and prepares the base data set + select_data: + selects a sub-set of the data + prepare_lags: + prepares the lagged data for the regression + fit_model: + implements the regression step + run_strategy: + runs the backtest for the regression-based strategy + plot_results: + plots the performance of the strategy compared to the symbol + ''' + + def __init__(self, symbol, start, end, amount, tc): + self.symbol = symbol + self.start = start + self.end = end + self.amount = amount + self.tc = tc + self.results = None + self.get_data() + + def get_data(self): + ''' Retrieves and prepares the data. + ''' + raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv', + index_col=0, parse_dates=True).dropna() + raw = pd.DataFrame(raw[self.symbol]) + raw = raw.loc[self.start:self.end] + raw.rename(columns={self.symbol: 'price'}, inplace=True) + raw['returns'] = np.log(raw / raw.shift(1)) + self.data = raw.dropna() + + def select_data(self, start, end): + ''' Selects sub-sets of the financial data. + ''' + data = self.data[(self.data.index >= start) & + (self.data.index <= end)].copy() + return data + + def prepare_lags(self, start, end): + ''' Prepares the lagged data for the regression and prediction steps. + ''' + data = self.select_data(start, end) + self.cols = [] + for lag in range(1, self.lags + 1): + col = f'lag_{lag}' + data[col] = data['returns'].shift(lag) + self.cols.append(col) + data.dropna(inplace=True) + self.lagged_data = data + + def fit_model(self, start, end): + ''' Implements the regression step. + ''' + self.prepare_lags(start, end) + reg = np.linalg.lstsq(self.lagged_data[self.cols], + np.sign(self.lagged_data['returns']), + rcond=None)[0] + self.reg = reg + + def run_strategy(self, start_in, end_in, start_out, end_out, lags=3): + ''' Backtests the trading strategy. + ''' + self.lags = lags + self.fit_model(start_in, end_in) + self.results = self.select_data(start_out, end_out).iloc[lags:] + self.prepare_lags(start_out, end_out) + prediction = np.sign(np.dot(self.lagged_data[self.cols], self.reg)) + self.results['prediction'] = prediction + self.results['strategy'] = self.results['prediction'] * \ + self.results['returns'] + # determine when a trade takes place + trades = self.results['prediction'].diff().fillna(0) != 0 + # subtract transaction costs from return when trade takes place + self.results['strategy'][trades] -= self.tc + self.results['creturns'] = self.amount * \ + self.results['returns'].cumsum().apply(np.exp) + self.results['cstrategy'] = self.amount * \ + self.results['strategy'].cumsum().apply(np.exp) + # gross performance of the strategy + aperf = self.results['cstrategy'].iloc[-1] + # out-/underperformance of strategy + operf = aperf - self.results['creturns'].iloc[-1] + return round(aperf, 2), round(operf, 2) + + def plot_results(self): + ''' Plots the cumulative performance of the trading strategy + compared to the symbol. + ''' + if self.results is None: + print('No results to plot yet. Run a strategy.') + title = '%s | TC = %.4f' % (self.symbol, self.tc) + self.results[['creturns', 'cstrategy']].plot(title=title, + figsize=(10, 6)) + + +if __name__ == '__main__': + lrbt = LRVectorBacktester('.SPX', '2010-1-1', '2018-06-29', 10000, 0.0) + print(lrbt.run_strategy('2010-1-1', '2019-12-31', + '2010-1-1', '2019-12-31')) + print(lrbt.run_strategy('2010-1-1', '2015-12-31', + '2016-1-1', '2019-12-31')) + lrbt = LRVectorBacktester('GDX', '2010-1-1', '2019-12-31', 10000, 0.001) + print(lrbt.run_strategy('2010-1-1', '2019-12-31', + '2010-1-1', '2019-12-31', lags=5)) + print(lrbt.run_strategy('2010-1-1', '2016-12-31', + '2017-1-1', '2019-12-31', lags=5)) diff --git a/ch05/ScikitVectorBacktester.py b/ch05/ScikitVectorBacktester.py new file mode 100644 index 0000000..cd10cd1 --- /dev/null +++ b/ch05/ScikitVectorBacktester.py @@ -0,0 +1,158 @@ +# +# Python Module with Class +# for Vectorized Backtesting +# of Machine Learning-based Strategies +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import numpy as np +import pandas as pd +from sklearn import linear_model + + +class ScikitVectorBacktester(object): + ''' Class for the vectorized backtesting of + Machine Learning-based trading strategies. + + Attributes + ========== + symbol: str + TR RIC (financial instrument) to work with + start: str + start date for data selection + end: str + end date for data selection + amount: int, float + amount to be invested at the beginning + tc: float + proportional transaction costs (e.g. 0.5% = 0.005) per trade + model: str + either 'regression' or 'logistic' + + Methods + ======= + get_data: + retrieves and prepares the base data set + select_data: + selects a sub-set of the data + prepare_features: + prepares the features data for the model fitting + fit_model: + implements the fitting step + run_strategy: + runs the backtest for the regression-based strategy + plot_results: + plots the performance of the strategy compared to the symbol + ''' + + def __init__(self, symbol, start, end, amount, tc, model): + self.symbol = symbol + self.start = start + self.end = end + self.amount = amount + self.tc = tc + self.results = None + if model == 'regression': + self.model = linear_model.LinearRegression() + elif model == 'logistic': + self.model = linear_model.LogisticRegression(C=1e6, + solver='lbfgs', multi_class='ovr', max_iter=1000) + else: + raise ValueError('Model not known or not yet implemented.') + self.get_data() + + def get_data(self): + ''' Retrieves and prepares the data. + ''' + raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv', + index_col=0, parse_dates=True).dropna() + raw = pd.DataFrame(raw[self.symbol]) + raw = raw.loc[self.start:self.end] + raw.rename(columns={self.symbol: 'price'}, inplace=True) + raw['returns'] = np.log(raw / raw.shift(1)) + self.data = raw.dropna() + + def select_data(self, start, end): + ''' Selects sub-sets of the financial data. + ''' + data = self.data[(self.data.index >= start) & + (self.data.index <= end)].copy() + return data + + def prepare_features(self, start, end): + ''' Prepares the feature columns for the regression and prediction steps. + ''' + self.data_subset = self.select_data(start, end) + self.feature_columns = [] + for lag in range(1, self.lags + 1): + col = 'lag_{}'.format(lag) + self.data_subset[col] = self.data_subset['returns'].shift(lag) + self.feature_columns.append(col) + self.data_subset.dropna(inplace=True) + + def fit_model(self, start, end): + ''' Implements the fitting step. + ''' + self.prepare_features(start, end) + self.model.fit(self.data_subset[self.feature_columns], + np.sign(self.data_subset['returns'])) + + def run_strategy(self, start_in, end_in, start_out, end_out, lags=3): + ''' Backtests the trading strategy. + ''' + self.lags = lags + self.fit_model(start_in, end_in) + # data = self.select_data(start_out, end_out) + self.prepare_features(start_out, end_out) + prediction = self.model.predict( + self.data_subset[self.feature_columns]) + self.data_subset['prediction'] = prediction + self.data_subset['strategy'] = (self.data_subset['prediction'] * + self.data_subset['returns']) + # determine when a trade takes place + trades = self.data_subset['prediction'].diff().fillna(0) != 0 + # subtract transaction costs from return when trade takes place + self.data_subset['strategy'][trades] -= self.tc + self.data_subset['creturns'] = (self.amount * + self.data_subset['returns'].cumsum().apply(np.exp)) + self.data_subset['cstrategy'] = (self.amount * + self.data_subset['strategy'].cumsum().apply(np.exp)) + self.results = self.data_subset + # absolute performance of the strategy + aperf = self.results['cstrategy'].iloc[-1] + # out-/underperformance of strategy + operf = aperf - self.results['creturns'].iloc[-1] + return round(aperf, 2), round(operf, 2) + + def plot_results(self): + ''' Plots the cumulative performance of the trading strategy + compared to the symbol. + ''' + if self.results is None: + print('No results to plot yet. Run a strategy.') + title = '%s | TC = %.4f' % (self.symbol, self.tc) + self.results[['creturns', 'cstrategy']].plot(title=title, + figsize=(10, 6)) + + +if __name__ == '__main__': + scibt = ScikitVectorBacktester('.SPX', '2010-1-1', '2019-12-31', + 10000, 0.0, 'regression') + print(scibt.run_strategy('2010-1-1', '2019-12-31', + '2010-1-1', '2019-12-31')) + print(scibt.run_strategy('2010-1-1', '2016-12-31', + '2017-1-1', '2019-12-31')) + scibt = ScikitVectorBacktester('.SPX', '2010-1-1', '2019-12-31', + 10000, 0.0, 'logistic') + print(scibt.run_strategy('2010-1-1', '2019-12-31', + '2010-1-1', '2019-12-31')) + print(scibt.run_strategy('2010-1-1', '2016-12-31', + '2017-1-1', '2019-12-31')) + scibt = ScikitVectorBacktester('.SPX', '2010-1-1', '2019-12-31', + 10000, 0.001, 'logistic') + print(scibt.run_strategy('2010-1-1', '2019-12-31', + '2010-1-1', '2019-12-31', lags=15)) + print(scibt.run_strategy('2010-1-1', '2013-12-31', + '2014-1-1', '2019-12-31', lags=15)) diff --git a/ch06/BacktestBase.py b/ch06/BacktestBase.py new file mode 100644 index 0000000..5b31861 --- /dev/null +++ b/ch06/BacktestBase.py @@ -0,0 +1,158 @@ +# +# Python Script with Base Class +# for Event-based Backtesting +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import numpy as np +import pandas as pd +from pylab import mpl, plt +plt.style.use('seaborn') +mpl.rcParams['font.family'] = 'serif' + + +class BacktestBase(object): + ''' Base class for event-based backtesting of trading strategies. + + Attributes + ========== + symbol: str + TR RIC (financial instrument) to be used + start: str + start date for data selection + end: str + end date for data selection + amount: float + amount to be invested either once or per trade + ftc: float + fixed transaction costs per trade (buy or sell) + ptc: float + proportional transaction costs per trade (buy or sell) + + Methods + ======= + get_data: + retrieves and prepares the base data set + plot_data: + plots the closing price for the symbol + get_date_price: + returns the date and price for the given bar + print_balance: + prints out the current (cash) balance + print_net_wealth: + prints auf the current net wealth + place_buy_order: + places a buy order + place_sell_order: + places a sell order + close_out: + closes out a long or short position + ''' + + def __init__(self, symbol, start, end, amount, + ftc=0.0, ptc=0.0, verbose=True): + self.symbol = symbol + self.start = start + self.end = end + self.initial_amount = amount + self.amount = amount + self.ftc = ftc + self.ptc = ptc + self.units = 0 + self.position = 0 + self.trades = 0 + self.verbose = verbose + self.get_data() + + def get_data(self): + ''' Retrieves and prepares the data. + ''' + raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv', + index_col=0, parse_dates=True).dropna() + raw = pd.DataFrame(raw[self.symbol]) + raw = raw.loc[self.start:self.end] + raw.rename(columns={self.symbol: 'price'}, inplace=True) + raw['return'] = np.log(raw / raw.shift(1)) + self.data = raw.dropna() + + def plot_data(self, cols=None): + ''' Plots the closing prices for symbol. + ''' + if cols is None: + cols = ['price'] + self.data['price'].plot(figsize=(10, 6), title=self.symbol) + + def get_date_price(self, bar): + ''' Return date and price for bar. + ''' + date = str(self.data.index[bar])[:10] + price = self.data.price.iloc[bar] + return date, price + + def print_balance(self, bar): + ''' Print out current cash balance info. + ''' + date, price = self.get_date_price(bar) + print(f'{date} | current balance {self.amount:.2f}') + + def print_net_wealth(self, bar): + ''' Print out current cash balance info. + ''' + date, price = self.get_date_price(bar) + net_wealth = self.units * price + self.amount + print(f'{date} | current net wealth {net_wealth:.2f}') + + def place_buy_order(self, bar, units=None, amount=None): + ''' Place a buy order. + ''' + date, price = self.get_date_price(bar) + if units is None: + units = int(amount / price) + self.amount -= (units * price) * (1 + self.ptc) + self.ftc + self.units += units + self.trades += 1 + if self.verbose: + print(f'{date} | selling {units} units at {price:.2f}') + self.print_balance(bar) + self.print_net_wealth(bar) + + def place_sell_order(self, bar, units=None, amount=None): + ''' Place a sell order. + ''' + date, price = self.get_date_price(bar) + if units is None: + units = int(amount / price) + self.amount += (units * price) * (1 - self.ptc) - self.ftc + self.units -= units + self.trades += 1 + if self.verbose: + print(f'{date} | selling {units} units at {price:.2f}') + self.print_balance(bar) + self.print_net_wealth(bar) + + def close_out(self, bar): + ''' Closing out a long or short position. + ''' + date, price = self.get_date_price(bar) + self.amount += self.units * price + self.units = 0 + self.trades += 1 + if self.verbose: + print(f'{date} | inventory {self.units} units at {price:.2f}') + print('=' * 55) + print('Final balance [$] {:.2f}'.format(self.amount)) + perf = ((self.amount - self.initial_amount) / + self.initial_amount * 100) + print('Net Performance [%] {:.2f}'.format(perf)) + print('Trades Executed [#] {:.2f}'.format(self.trades)) + print('=' * 55) + + +if __name__ == '__main__': + bb = BacktestBase('AAPL.O', '2010-1-1', '2019-12-31', 10000) + print(bb.data.info()) + print(bb.data.tail()) + bb.plot_data() + plt.savefig('../../images/ch06/backtestbaseplot.png') diff --git a/ch06/BacktestLongOnly.py b/ch06/BacktestLongOnly.py new file mode 100644 index 0000000..08587b0 --- /dev/null +++ b/ch06/BacktestLongOnly.py @@ -0,0 +1,118 @@ +# +# Python Script with Long Only Class +# for Event-based Backtesting +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +from BacktestBase import * + + +class BacktestLongOnly(BacktestBase): + + def run_sma_strategy(self, SMA1, SMA2): + ''' Backtesting a SMA-based strategy. + + Parameters + ========== + SMA1, SMA2: int + shorter and longer term simple moving average (in days) + ''' + msg = f'\n\nRunning SMA strategy | SMA1={SMA1} & SMA2={SMA2}' + msg += f'\nfixed costs {self.ftc} | ' + msg += f'proportional costs {self.ptc}' + print(msg) + print('=' * 55) + self.position = 0 # initial neutral position + self.trades = 0 # no trades yet + self.amount = self.initial_amount # reset initial capital + self.data['SMA1'] = self.data['price'].rolling(SMA1).mean() + self.data['SMA2'] = self.data['price'].rolling(SMA2).mean() + + for bar in range(SMA2, len(self.data)): + if self.position == 0: + if self.data['SMA1'].iloc[bar] > self.data['SMA2'].iloc[bar]: + self.place_buy_order(bar, amount=self.amount) + self.position = 1 # long position + elif self.position == 1: + if self.data['SMA1'].iloc[bar] < self.data['SMA2'].iloc[bar]: + self.place_sell_order(bar, units=self.units) + self.position = 0 # market neutral + self.close_out(bar) + + def run_momentum_strategy(self, momentum): + ''' Backtesting a momentum-based strategy. + + Parameters + ========== + momentum: int + number of days for mean return calculation + ''' + msg = f'\n\nRunning momentum strategy | {momentum} days' + msg += f'\nfixed costs {self.ftc} | ' + msg += f'proportional costs {self.ptc}' + print(msg) + print('=' * 55) + self.position = 0 # initial neutral position + self.trades = 0 # no trades yet + self.amount = self.initial_amount # reset initial capital + self.data['momentum'] = self.data['return'].rolling(momentum).mean() + for bar in range(momentum, len(self.data)): + if self.position == 0: + if self.data['momentum'].iloc[bar] > 0: + self.place_buy_order(bar, amount=self.amount) + self.position = 1 # long position + elif self.position == 1: + if self.data['momentum'].iloc[bar] < 0: + self.place_sell_order(bar, units=self.units) + self.position = 0 # market neutral + self.close_out(bar) + + def run_mean_reversion_strategy(self, SMA, threshold): + ''' Backtesting a mean reversion-based strategy. + + Parameters + ========== + SMA: int + simple moving average in days + threshold: float + absolute value for deviation-based signal relative to SMA + ''' + msg = f'\n\nRunning mean reversion strategy | ' + msg += f'SMA={SMA} & thr={threshold}' + msg += f'\nfixed costs {self.ftc} | ' + msg += f'proportional costs {self.ptc}' + print(msg) + print('=' * 55) + self.position = 0 + self.trades = 0 + self.amount = self.initial_amount + + self.data['SMA'] = self.data['price'].rolling(SMA).mean() + + for bar in range(SMA, len(self.data)): + if self.position == 0: + if (self.data['price'].iloc[bar] < + self.data['SMA'].iloc[bar] - threshold): + self.place_buy_order(bar, amount=self.amount) + self.position = 1 + elif self.position == 1: + if self.data['price'].iloc[bar] >= self.data['SMA'].iloc[bar]: + self.place_sell_order(bar, units=self.units) + self.position = 0 + self.close_out(bar) + + +if __name__ == '__main__': + def run_strategies(): + lobt.run_sma_strategy(42, 252) + lobt.run_momentum_strategy(60) + lobt.run_mean_reversion_strategy(50, 5) + lobt = BacktestLongOnly('AAPL.O', '2010-1-1', '2019-12-31', 10000, + verbose=False) + run_strategies() + # transaction costs: 10 USD fix, 1% variable + lobt = BacktestLongOnly('AAPL.O', '2010-1-1', '2019-12-31', + 10000, 10.0, 0.01, False) + run_strategies() diff --git a/ch06/BacktestLongShort.py b/ch06/BacktestLongShort.py new file mode 100644 index 0000000..429a5ca --- /dev/null +++ b/ch06/BacktestLongShort.py @@ -0,0 +1,123 @@ +# +# Python Script with Long Short Class +# for Event-based Backtesting +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +from BacktestBase import * + + +class BacktestLongShort(BacktestBase): + + def go_long(self, bar, units=None, amount=None): + if self.position == -1: + self.place_buy_order(bar, units=-self.units) + if units: + self.place_buy_order(bar, units=units) + elif amount: + if amount == 'all': + amount = self.amount + self.place_buy_order(bar, amount=amount) + + def go_short(self, bar, units=None, amount=None): + if self.position == 1: + self.place_sell_order(bar, units=self.units) + if units: + self.place_sell_order(bar, units=units) + elif amount: + if amount == 'all': + amount = self.amount + self.place_sell_order(bar, amount=amount) + + def run_sma_strategy(self, SMA1, SMA2): + msg = f'\n\nRunning SMA strategy | SMA1={SMA1} & SMA2={SMA2}' + msg += f'\nfixed costs {self.ftc} | ' + msg += f'proportional costs {self.ptc}' + print(msg) + print('=' * 55) + self.position = 0 # initial neutral position + self.trades = 0 # no trades yet + self.amount = self.initial_amount # reset initial capital + self.data['SMA1'] = self.data['price'].rolling(SMA1).mean() + self.data['SMA2'] = self.data['price'].rolling(SMA2).mean() + + for bar in range(SMA2, len(self.data)): + if self.position in [0, -1]: + if self.data['SMA1'].iloc[bar] > self.data['SMA2'].iloc[bar]: + self.go_long(bar, amount='all') + self.position = 1 # long position + if self.position in [0, 1]: + if self.data['SMA1'].iloc[bar] < self.data['SMA2'].iloc[bar]: + self.go_short(bar, amount='all') + self.position = -1 # short position + self.close_out(bar) + + def run_momentum_strategy(self, momentum): + msg = f'\n\nRunning momentum strategy | {momentum} days' + msg += f'\nfixed costs {self.ftc} | ' + msg += f'proportional costs {self.ptc}' + print(msg) + print('=' * 55) + self.position = 0 # initial neutral position + self.trades = 0 # no trades yet + self.amount = self.initial_amount # reset initial capital + self.data['momentum'] = self.data['return'].rolling(momentum).mean() + for bar in range(momentum, len(self.data)): + if self.position in [0, -1]: + if self.data['momentum'].iloc[bar] > 0: + self.go_long(bar, amount='all') + self.position = 1 # long position + if self.position in [0, 1]: + if self.data['momentum'].iloc[bar] <= 0: + self.go_short(bar, amount='all') + self.position = -1 # short position + self.close_out(bar) + + def run_mean_reversion_strategy(self, SMA, threshold): + msg = f'\n\nRunning mean reversion strategy | ' + msg += f'SMA={SMA} & thr={threshold}' + msg += f'\nfixed costs {self.ftc} | ' + msg += f'proportional costs {self.ptc}' + print(msg) + print('=' * 55) + self.position = 0 # initial neutral position + self.trades = 0 # no trades yet + self.amount = self.initial_amount # reset initial capital + + self.data['SMA'] = self.data['price'].rolling(SMA).mean() + + for bar in range(SMA, len(self.data)): + if self.position == 0: + if (self.data['price'].iloc[bar] < + self.data['SMA'].iloc[bar] - threshold): + self.go_long(bar, amount=self.initial_amount) + self.position = 1 + elif (self.data['price'].iloc[bar] > + self.data['SMA'].iloc[bar] + threshold): + self.go_short(bar, amount=self.initial_amount) + self.position = -1 + elif self.position == 1: + if self.data['price'].iloc[bar] >= self.data['SMA'].iloc[bar]: + self.place_sell_order(bar, units=self.units) + self.position = 0 + elif self.position == -1: + if self.data['price'].iloc[bar] <= self.data['SMA'].iloc[bar]: + self.place_buy_order(bar, units=-self.units) + self.position = 0 + self.close_out(bar) + + +if __name__ == '__main__': + def run_strategies(): + lsbt.run_sma_strategy(42, 252) + lsbt.run_momentum_strategy(60) + lsbt.run_mean_reversion_strategy(50, 5) + lsbt = BacktestLongShort('EUR=', '2010-1-1', '2019-12-31', 10000, + verbose=False) + run_strategies() + # transaction costs: 10 USD fix, 1% variable + lsbt = BacktestLongShort('AAPL.O', '2010-1-1', '2019-12-31', + 10000, 10.0, 0.01, False) + run_strategies() diff --git a/ch07/07_pyalgo.ipynb b/ch07/07_pyalgo.ipynb new file mode 100644 index 0000000..7b7610f --- /dev/null +++ b/ch07/07_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading "]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Chapter 07 — Working with Real-Time Data and Sockets**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Visualizing Streaming Data with Plotly"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### The Basics"]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["import zmq\n", "from datetime import datetime\n", "import plotly.graph_objects as go"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["symbol = 'SYMBOL'"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [{"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "ba95385085734ec4a103893d884a4f60", "version_major": 2, "version_minor": 0}, "text/plain": ["FigureWidget({\n", " 'data': [{'type': 'scatter', 'uid': '9bdc6757-dd01-49a1-be7d-9d41cf280b90'}], 'layout': {'t\u2026"]}, "metadata": {}, "output_type": "display_data"}], "source": ["fig = go.FigureWidget()\n", "fig.add_scatter()\n", "fig"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": ["context = zmq.Context()"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": ["socket = context.socket(zmq.SUB)"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": ["socket.connect('tcp://0.0.0.0:5555')"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": ["socket.setsockopt_string(zmq.SUBSCRIBE, 'SYMBOL')"]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": ["times = list()\n", "prices = list()"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": ["for _ in range(50):\n", " msg = socket.recv_string()\n", " t = datetime.now()\n", " times.append(t)\n", " _, price = msg.split()\n", " prices.append(float(price))\n", " fig.data[0].x = times\n", " fig.data[0].y = prices"]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "5f1a651c1d2049c9bf9d1337fbb66313", "version_major": 2, "version_minor": 0}, "text/plain": ["FigureWidget({\n", " 'data': [{'name': 'SYMBOL', 'type': 'scatter', 'uid': '8aa33f31-7e9f-4a50-a563-75211b8241df\u2026"]}, "metadata": {}, "output_type": "display_data"}], "source": ["fig = go.FigureWidget()\n", "fig.add_scatter(name='SYMBOL')\n", "fig.add_scatter(name='SMA1', line=dict(width=1, dash='dot'),\n", " mode='lines+markers')\n", "fig.add_scatter(name='SMA2', line=dict(width=1, dash='dash'),\n", " mode='lines+markers')\n", "fig"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": ["import pandas as pd"]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": ["df = pd.DataFrame()"]}, {"cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": ["for _ in range(75):\n", " msg = socket.recv_string()\n", " t = datetime.now()\n", " sym, price = msg.split()\n", " df = df.append(pd.DataFrame({sym: float(price)}, index=[t]))\n", " df['SMA1'] = df[sym].rolling(5).mean()\n", " df['SMA2'] = df[sym].rolling(10).mean()\n", " fig.data[0].x = df.index\n", " fig.data[1].x = df.index\n", " fig.data[2].x = df.index\n", " fig.data[0].y = df[sym]\n", " fig.data[1].y = df['SMA1']\n", " fig.data[2].y = df['SMA2']"]}, {"cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": ["from plotly.subplots import make_subplots"]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": ["f = make_subplots(rows=3, cols=1, shared_xaxes=True)\n", "f.append_trace(go.Scatter(name='SYMBOL'), row=1, col=1)\n", "f.append_trace(go.Scatter(name='RETURN', line=dict(width=1, dash='dot'),\n", " mode='lines+markers', marker={'symbol': 'triangle-up'}),\n", " row=2, col=1)\n", "f.append_trace(go.Scatter(name='MOMENTUM', line=dict(width=1, dash='dash'),\n", " mode='lines+markers', marker={'symbol': 'x'}), row=3, col=1)\n", "# f.update_layout(height=600)"]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": ["fig = go.FigureWidget(f)"]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [{"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "d091b40017f040fba5703c023d2e3ff3", "version_major": 2, "version_minor": 0}, "text/plain": ["FigureWidget({\n", " 'data': [{'name': 'SYMBOL',\n", " 'type': 'scatter',\n", " 'uid': 'd8f37a5f\u2026"]}, "metadata": {}, "output_type": "display_data"}], "source": ["fig"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": ["import numpy as np"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": ["df = pd.DataFrame()"]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": ["for _ in range(75):\n", " msg = socket.recv_string()\n", " t = datetime.now()\n", " sym, price = msg.split()\n", " df = df.append(pd.DataFrame({sym: float(price)}, index=[t]))\n", " df['RET'] = np.log(df[sym] / df[sym].shift(1))\n", " df['MOM'] = df['RET'].rolling(10).mean()\n", " fig.data[0].x = df.index\n", " fig.data[1].x = df.index\n", " fig.data[2].x = df.index\n", " fig.data[0].y = df[sym]\n", " fig.data[1].y = df['RET']\n", " fig.data[2].y = df['MOM']"]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": ["socket = context.socket(zmq.SUB)"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": ["socket.connect('tcp://0.0.0.0:5556')"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": ["socket.setsockopt_string(zmq.SUBSCRIBE, '')"]}, {"cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["49.102 19.185 74.012 26.288 69.924 90.448 60.010 30.055\n", "48.869 80.757 13.682 87.540 24.016 93.654 28.022 73.590\n", "87.966 12.753 25.665 84.953 41.787 47.367 11.784 15.018\n", "23.722 19.868 19.881 3.453 58.011 6.336 36.881 7.048\n", "68.677 85.995 83.560 13.433 53.904 29.649 94.214 1.951\n"]}], "source": ["for _ in range(5):\n", " msg = socket.recv_string()\n", " print(msg)"]}, {"cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [{"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "0db232d0b6584629bf127769a90415c2", "version_major": 2, "version_minor": 0}, "text/plain": ["FigureWidget({\n", " 'data': [{'type': 'bar', 'uid': '325ded67-8023-45c7-9d9c-c016d2bc0da0'}], 'layout': {'templ\u2026"]}, "metadata": {}, "output_type": "display_data"}], "source": ["fig = go.FigureWidget()\n", "fig.add_bar()\n", "fig"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": ["x = list('abcdefgh')\n", "fig.data[0].x = x\n", "for _ in range(100):\n", " msg = socket.recv_string()\n", " y = msg.split()\n", " y = [float(n) for n in y]\n", " fig.data[0].y = y"]}, {"cell_type": "markdown", "metadata": {}, "source": ["
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"anaconda-cloud": {}, "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch07/BarsServer.py b/ch07/BarsServer.py new file mode 100644 index 0000000..db69358 --- /dev/null +++ b/ch07/BarsServer.py @@ -0,0 +1,23 @@ +# +# Python Script to Serve +# Random Bars Data +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import zmq +import math +import time +import random + +context = zmq.Context() +socket = context.socket(zmq.PUB) +socket.bind('tcp://0.0.0.0:5556') + +while True: + bars = [random.random() * 100 for _ in range(8)] + msg = ' '.join([f'{bar:.3f}' for bar in bars]) + print(msg) + socket.send_string(msg) + time.sleep(random.random() * 2) diff --git a/ch07/OnlineAlgorithm.py b/ch07/OnlineAlgorithm.py new file mode 100644 index 0000000..fd958dc --- /dev/null +++ b/ch07/OnlineAlgorithm.py @@ -0,0 +1,42 @@ +# +# Python Script +# with Online Trading Algorithm +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import zmq +import datetime +import numpy as np +import pandas as pd + +context = zmq.Context() +socket = context.socket(zmq.SUB) +socket.connect('tcp://0.0.0.0:5555') +socket.setsockopt_string(zmq.SUBSCRIBE, 'SYMBOL') + +df = pd.DataFrame() +mom = 3 +min_length = mom + 1 + +while True: + data = socket.recv_string() + t = datetime.datetime.now() + sym, value = data.split() + df = df.append(pd.DataFrame({sym: float(value)}, index=[t])) + dr = df.resample('5s', label='right').last() + dr['returns'] = np.log(dr / dr.shift(1)) + if len(dr) > min_length: + min_length += 1 + dr['momentum'] = np.sign(dr['returns'].rolling(mom).mean()) + print('\n' + '=' * 51) + print('NEW SIGNAL | {}'.format(datetime.datetime.now())) + print('=' * 51) + print(dr.iloc[:-1].tail()) + if dr['momentum'].iloc[-2] == 1.0: + print('\nLong market position.') + # take some action (e.g. place buy order) + elif dr['momentum'].iloc[-2] == -1.0: + print('\nShort market position.') + # take some action (e.g. place sell order) diff --git a/ch07/TickClient.py b/ch07/TickClient.py new file mode 100644 index 0000000..176cd22 --- /dev/null +++ b/ch07/TickClient.py @@ -0,0 +1,18 @@ +# +# Python Script +# with Tick Data Client +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import zmq + +context = zmq.Context() +socket = context.socket(zmq.SUB) +socket.connect('tcp://0.0.0.0:5555') +socket.setsockopt_string(zmq.SUBSCRIBE, 'SYMBOL') + +while True: + data = socket.recv_string() + print(data) diff --git a/ch07/TickServer.py b/ch07/TickServer.py new file mode 100644 index 0000000..e83295b --- /dev/null +++ b/ch07/TickServer.py @@ -0,0 +1,45 @@ +# +# Python Script to Simulate a +# Financial Tick Data Server +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import zmq +import math +import time +import random + +context = zmq.Context() +socket = context.socket(zmq.PUB) +socket.bind('tcp://0.0.0.0:5555') + + +class InstrumentPrice(object): + def __init__(self): + self.symbol = 'SYMBOL' + self.t = time.time() + self.value = 100. + self.sigma = 0.4 + self.r = 0.01 + + def simulate_value(self): + ''' Generates a new, random stock price. + ''' + t = time.time() + dt = (t - self.t) / (252 * 8 * 60 * 60) + dt *= 500 + self.t = t + self.value *= math.exp((self.r - 0.5 * self.sigma ** 2) * dt + + self.sigma * math.sqrt(dt) * random.gauss(0, 1)) + return self.value + + +ip = InstrumentPrice() + +while True: + msg = '{} {:.2f}'.format(ip.symbol, ip.simulate_value()) + print(msg) + socket.send_string(msg) + time.sleep(random.random() * 2) diff --git a/ch08/08_pyalgo.ipynb b/ch08/08_pyalgo.ipynb new file mode 100644 index 0000000..1bc9a3f --- /dev/null +++ b/ch08/08_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading "]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Chapter 08 — CFD Trading with Oanda**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## The Oanda API"]}, {"cell_type": "markdown", "metadata": {}, "source": ["`pip install git+https://github.com/yhilpisch/tpqoa.git`"]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["import tpqoa"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["api = tpqoa.tpqoa('../pyalgo.cfg')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Retrieving Historical Data"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Looking Up Instruments Available for Trading"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [{"data": {"text/plain": ["[('AUD/CAD', 'AUD_CAD'),\n", " ('AUD/CHF', 'AUD_CHF'),\n", " ('AUD/HKD', 'AUD_HKD'),\n", " ('AUD/JPY', 'AUD_JPY'),\n", " ('AUD/NZD', 'AUD_NZD'),\n", " ('AUD/SGD', 'AUD_SGD'),\n", " ('AUD/USD', 'AUD_USD'),\n", " ('Australia 200', 'AU200_AUD'),\n", " ('Brent Crude Oil', 'BCO_USD'),\n", " ('Bund', 'DE10YB_EUR'),\n", " ('CAD/CHF', 'CAD_CHF'),\n", " ('CAD/HKD', 'CAD_HKD'),\n", " ('CAD/JPY', 'CAD_JPY'),\n", " ('CAD/SGD', 'CAD_SGD'),\n", " ('CHF/HKD', 'CHF_HKD')]"]}, "execution_count": 3, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_instruments()[:15]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Backtesting a Momentum Strategy on Minute Bars"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Help on method get_history in module tpqoa.tpqoa:\n", "\n", "get_history(instrument, start, end, granularity, price, localize=True) method of tpqoa.tpqoa.tpqoa instance\n", " Retrieves historical data for instrument.\n", " \n", " Parameters\n", " ==========\n", " instrument: string\n", " valid instrument name\n", " start, end: datetime, str\n", " Python datetime or string objects for start and end\n", " granularity: string\n", " a string like 'S5', 'M1' or 'D'\n", " price: string\n", " one of 'A' (ask), 'B' (bid) or 'M' (middle)\n", " \n", " Returns\n", " =======\n", " data: pd.DataFrame\n", " pandas DataFrame object with data\n", "\n"]}], "source": ["help(api.get_history)"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": ["instrument = 'EUR_USD'\n", "start = '2020-05-27'\n", "end = '2020-05-29'\n", "granularity = 'M1'\n", "price = 'M'"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": ["data = api.get_history(instrument, start, end,\n", " granularity, price)"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" c volume\n", "time \n", "2020-05-27 00:00:00 1.09788 34\n", "2020-05-27 00:01:00 1.09776 31\n", "2020-05-27 00:02:00 1.09763 27\n", "2020-05-27 00:03:00 1.09764 25\n", "2020-05-27 00:04:00 1.09768 20"]}, "execution_count": 8, "metadata": {}, "output_type": "execute_result"}], "source": ["data[['c', 'volume']].head()"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": ["import numpy as np"]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": ["data['returns'] = np.log(data['c'] / data['c'].shift(1))"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": ["cols = []"]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": ["for momentum in [15, 30, 60, 120]:\n", " col = 'position_{}'.format(momentum)\n", " data[col] = np.sign(data['returns'].rolling(momentum).mean())\n", " cols.append(col)"]}, {"cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": ["from pylab import plt\n", "plt.style.use('seaborn')\n", "import matplotlib as mpl\n", "mpl.rcParams['font.family'] = 'serif'"]}, {"cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": ["strats = ['returns']"]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": ["for col in cols:\n", " strat = 'strategy_{}'.format(col.split('_')[1])\n", " data[strat] = data[col].shift(1) * data['returns']\n", " strats.append(strat)"]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["| \n", " | c | \n", "volume | \n", "
|---|---|---|
| time | \n", "\n", " | \n", " |
| 2020-05-27 00:00:00 | \n", "1.09788 | \n", "34 | \n", "
| 2020-05-27 00:01:00 | \n", "1.09776 | \n", "31 | \n", "
| 2020-05-27 00:02:00 | \n", "1.09763 | \n", "27 | \n", "
| 2020-05-27 00:03:00 | \n", "1.09764 | \n", "25 | \n", "
| 2020-05-27 00:04:00 | \n", "1.09768 | \n", "20 | \n", "
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[strats].dropna().cumsum(\n", " ).apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch08/oanda_plot_1.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Factoring In Leverage and Margin"]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["data[strats].dropna().cumsum().apply(\n", " lambda x: x * 20).apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch08/oanda_plot_2.png');"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Working with Streaming Data"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": ["instrument = 'EUR_USD'"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["2020-06-01T12:09:53.948885097Z 1.11147 1.11159\n", "2020-06-01T12:09:58.590777185Z 1.11149 1.11162\n", "2020-06-01T12:09:58.673870044Z 1.1115 1.11164\n", "2020-06-01T12:09:59.202511358Z 1.11152 1.11165\n", "2020-06-01T12:09:59.730651854Z 1.11151 1.11164\n", "2020-06-01T12:09:59.970253663Z 1.1115 1.11163\n", "2020-06-01T12:10:07.050565764Z 1.11148 1.11162\n", "2020-06-01T12:10:18.148637040Z 1.11151 1.11164\n", "2020-06-01T12:10:18.459492370Z 1.11152 1.11165\n", "2020-06-01T12:10:20.439281118Z 1.11153 1.11167\n"]}], "source": ["api.stream_data(instrument, stop=10)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Placing Orders"]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Help on method create_order in module tpqoa.tpqoa:\n", "\n", "create_order(instrument, units, price=None, sl_distance=None, tsl_distance=None, tp_price=None, comment=None, touch=False, suppress=False, ret=False) method of tpqoa.tpqoa.tpqoa instance\n", " Places order with Oanda.\n", " \n", " Parameters\n", " ==========\n", " instrument: string\n", " valid instrument name\n", " units: int\n", " number of units of instrument to be bought\n", " (positive int, eg 'units=50')\n", " or to be sold (negative int, eg 'units=-100')\n", " price: float\n", " limit order price, touch order price\n", " sl_distance: float\n", " stop loss distance price, mandatory eg in Germany\n", " tsl_distance: float\n", " trailing stop loss distance\n", " tp_price: float\n", " take profit price to be used for the trade\n", " comment: str\n", " string\n", " touch: boolean\n", " market_if_touched order (requires price to be set)\n", " suppress: boolean\n", " whether to suppress print out\n", " ret: boolean\n", " whether to return the order object\n", "\n"]}], "source": ["help(api.create_order)"]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "\n", " {'id': '903', 'time': '2020-06-01T12:10:20.832960817Z', 'userID': 13834683, 'accountID': '101-004-13834683-001', 'batchID': '902', 'requestID': '60716389480704559', 'type': 'ORDER_FILL', 'orderID': '902', 'instrument': 'EUR_USD', 'units': '1000.0', 'gainQuoteHomeConversionFactor': '0.899547527594', 'lossQuoteHomeConversionFactor': '0.899660827868', 'price': 1.11167, 'fullVWAP': 1.11167, 'fullPrice': {'type': 'PRICE', 'bids': [{'price': 1.11153, 'liquidity': '10000000'}], 'asks': [{'price': 1.11167, 'liquidity': '10000000'}], 'closeoutBid': 1.11153, 'closeoutAsk': 1.11167}, 'reason': 'MARKET_ORDER', 'pl': '0.0', 'financing': '0.0', 'commission': '0.0', 'guaranteedExecutionFee': '0.0', 'accountBalance': '99392.4254', 'tradeOpened': {'tradeID': '903', 'units': '1000.0', 'price': 1.11167, 'guaranteedExecutionFee': '0.0', 'halfSpreadCost': '0.063', 'initialMarginRequired': '33.3'}, 'halfSpreadCost': '0.063'} \n", "\n"]}], "source": ["api.create_order(instrument, 1000)"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "\n", " {'id': '905', 'time': '2020-06-01T12:10:20.994033040Z', 'userID': 13834683, 'accountID': '101-004-13834683-001', 'batchID': '904', 'requestID': '60716389480704952', 'type': 'ORDER_FILL', 'orderID': '904', 'instrument': 'EUR_USD', 'units': '-1500.0', 'gainQuoteHomeConversionFactor': '0.899547527594', 'lossQuoteHomeConversionFactor': '0.899660827868', 'price': 1.11153, 'fullVWAP': 1.11153, 'fullPrice': {'type': 'PRICE', 'bids': [{'price': 1.11153, 'liquidity': '10000000'}], 'asks': [{'price': 1.11167, 'liquidity': '9999000'}], 'closeoutBid': 1.11153, 'closeoutAsk': 1.11167}, 'reason': 'MARKET_ORDER', 'pl': '-0.126', 'financing': '0.0', 'commission': '0.0', 'guaranteedExecutionFee': '0.0', 'accountBalance': '99392.2994', 'tradeOpened': {'tradeID': '905', 'units': '-500.0', 'price': 1.11153, 'guaranteedExecutionFee': '0.0', 'halfSpreadCost': '0.0315', 'initialMarginRequired': '16.65'}, 'tradesClosed': [{'tradeID': '903', 'units': '-1000.0', 'price': 1.11153, 'realizedPL': '-0.126', 'financing': '0.0', 'guaranteedExecutionFee': '0.0', 'halfSpreadCost': '0.063'}], 'halfSpreadCost': '0.0945'} \n", "\n"]}], "source": ["api.create_order(instrument, -1500)"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "\n", " {'id': '907', 'time': '2020-06-01T12:10:21.153454837Z', 'userID': 13834683, 'accountID': '101-004-13834683-001', 'batchID': '906', 'requestID': '60716389484899631', 'type': 'ORDER_FILL', 'orderID': '906', 'instrument': 'EUR_USD', 'units': '500.0', 'gainQuoteHomeConversionFactor': '0.899547527594', 'lossQuoteHomeConversionFactor': '0.899660827868', 'price': 1.11167, 'fullVWAP': 1.11167, 'fullPrice': {'type': 'PRICE', 'bids': [{'price': 1.11153, 'liquidity': '9998500'}], 'asks': [{'price': 1.11167, 'liquidity': '9999000'}], 'closeoutBid': 1.11153, 'closeoutAsk': 1.11167}, 'reason': 'MARKET_ORDER', 'pl': '-0.063', 'financing': '0.0', 'commission': '0.0', 'guaranteedExecutionFee': '0.0', 'accountBalance': '99392.2364', 'tradesClosed': [{'tradeID': '905', 'units': '500.0', 'price': 1.11167, 'realizedPL': '-0.063', 'financing': '0.0', 'guaranteedExecutionFee': '0.0', 'halfSpreadCost': '0.0315'}], 'halfSpreadCost': '0.0315'} \n", "\n"]}], "source": ["api.create_order(instrument, 500)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Implementing Trading Strategies in Real-Time"]}, {"cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": ["import MomentumTrader as MT"]}, {"cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": ["mt = MT.MomentumTrader('../pyalgo.cfg',\n", " instrument=instrument,\n", " bar_length='15s',\n", " momentum=6,\n", " units=10000)"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 \n", "\n", " {'id': '909', 'time': '2020-06-01T12:12:15.999798563Z', 'userID': 13834683, 'accountID': '101-004-13834683-001', 'batchID': '908', 'requestID': '24687592944511579', 'type': 'ORDER_FILL', 'orderID': '908', 'instrument': 'EUR_USD', 'units': '10000.0', 'gainQuoteHomeConversionFactor': '0.899547527594', 'lossQuoteHomeConversionFactor': '0.899652734045', 'price': 1.11167, 'fullVWAP': 1.11167, 'fullPrice': {'type': 'PRICE', 'bids': [{'price': 1.11154, 'liquidity': '10000000'}], 'asks': [{'price': 1.11167, 'liquidity': '10000000'}], 'closeoutBid': 1.11154, 'closeoutAsk': 1.11167}, 'reason': 'MARKET_ORDER', 'pl': '0.0', 'financing': '0.0', 'commission': '0.0', 'guaranteedExecutionFee': '0.0', 'accountBalance': '99392.2364', 'tradeOpened': {'tradeID': '909', 'units': '10000.0', 'price': 1.11167, 'guaranteedExecutionFee': '0.0', 'halfSpreadCost': '0.5847', 'initialMarginRequired': '333.0'}, 'halfSpreadCost': '0.5847'} \n", "\n", "69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 \n", "\n", " {'id': '911', 'time': '2020-06-01T12:13:48.497339577Z', 'userID': 13834683, 'accountID': '101-004-13834683-001', 'batchID': '910', 'requestID': '42701991845942185', 'type': 'ORDER_FILL', 'orderID': '910', 'instrument': 'EUR_USD', 'units': '-20000.0', 'gainQuoteHomeConversionFactor': '0.899612267113', 'lossQuoteHomeConversionFactor': '0.899717488709', 'price': 1.11146, 'fullVWAP': 1.11146, 'fullPrice': {'type': 'PRICE', 'bids': [{'price': 1.11146, 'liquidity': '10000000'}], 'asks': [{'price': 1.11159, 'liquidity': '10000000'}], 'closeoutBid': 1.11146, 'closeoutAsk': 1.11159}, 'reason': 'MARKET_ORDER', 'pl': '-1.8894', 'financing': '0.0', 'commission': '0.0', 'guaranteedExecutionFee': '0.0', 'accountBalance': '99390.347', 'tradeOpened': {'tradeID': '911', 'units': '-10000.0', 'price': 1.11146, 'guaranteedExecutionFee': '0.0', 'halfSpreadCost': '0.5848', 'initialMarginRequired': '333.0'}, 'tradesClosed': [{'tradeID': '909', 'units': '-10000.0', 'price': 1.11146, 'realizedPL': '-1.8894', 'financing': '0.0', 'guaranteedExecutionFee': '0.0', 'halfSpreadCost': '0.5848'}], 'halfSpreadCost': '1.1696'} \n", "\n", "138 139 140 141 142 143 144 145 146 147 148 149 150 "]}], "source": ["mt.stream_data(mt.instrument, stop=150)"]}, {"cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [{"data": {"text/plain": ["{'id': '913',\n", " 'time': '2020-06-01T12:13:59.975513465Z',\n", " 'userID': 13834683,\n", " 'accountID': '101-004-13834683-001',\n", " 'batchID': '912',\n", " 'requestID': '60716390399775646',\n", " 'type': 'ORDER_FILL',\n", " 'orderID': '912',\n", " 'instrument': 'EUR_USD',\n", " 'units': '10000.0',\n", " 'gainQuoteHomeConversionFactor': '0.899539435809',\n", " 'lossQuoteHomeConversionFactor': '0.899636546835',\n", " 'price': 1.11168,\n", " 'fullVWAP': 1.11168,\n", " 'fullPrice': {'type': 'PRICE',\n", " 'bids': [{'price': 1.11156, 'liquidity': '10000000'}],\n", " 'asks': [{'price': 1.11168, 'liquidity': '10000000'}],\n", " 'closeoutBid': 1.11156,\n", " 'closeoutAsk': 1.11168},\n", " 'reason': 'MARKET_ORDER',\n", " 'pl': '-1.9792',\n", " 'financing': '0.0',\n", " 'commission': '0.0',\n", " 'guaranteedExecutionFee': '0.0',\n", " 'accountBalance': '99388.3678',\n", " 'tradesClosed': [{'tradeID': '911',\n", " 'units': '10000.0',\n", " 'price': 1.11168,\n", " 'realizedPL': '-1.9792',\n", " 'financing': '0.0',\n", " 'guaranteedExecutionFee': '0.0',\n", " 'halfSpreadCost': '0.5398'}],\n", " 'halfSpreadCost': '0.5398'}"]}, "execution_count": 27, "metadata": {}, "output_type": "execute_result"}], "source": ["oo = mt.create_order(instrument, units=-mt.position * mt.units,\n", " ret=True, suppress=True)\n", "oo"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Retrieving Account Information"]}, {"cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [{"data": {"text/plain": ["{'id': '101-004-13834683-001',\n", " 'alias': 'Primary',\n", " 'currency': 'EUR',\n", " 'balance': '99388.3678',\n", " 'createdByUserID': 13834683,\n", " 'createdTime': '2020-03-19T06:08:14.363139403Z',\n", " 'guaranteedStopLossOrderMode': 'DISABLED',\n", " 'pl': '-564.3049',\n", " 'resettablePL': '-564.3049',\n", " 'resettablePLTime': '0',\n", " 'financing': '-47.3273',\n", " 'commission': '0.0',\n", " 'guaranteedExecutionFees': '0.0',\n", " 'marginRate': '0.01',\n", " 'openTradeCount': 1,\n", " 'openPositionCount': 1,\n", " 'pendingOrderCount': 0,\n", " 'hedgingEnabled': False,\n", " 'unrealizedPL': '270.4915',\n", " 'NAV': '99658.8593',\n", " 'marginUsed': '331.68',\n", " 'marginAvailable': '99327.1793',\n", " 'positionValue': '3316.8',\n", " 'marginCloseoutUnrealizedPL': '271.8555',\n", " 'marginCloseoutNAV': '99660.2233',\n", " 'marginCloseoutMarginUsed': '331.68',\n", " 'marginCloseoutPercent': '0.00166',\n", " 'marginCloseoutPositionValue': '3316.8',\n", " 'withdrawalLimit': '99327.1793',\n", " 'marginCallMarginUsed': '331.68',\n", " 'marginCallPercent': '0.00333',\n", " 'lastTransactionID': '913'}"]}, "execution_count": 28, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_account_summary()"]}, {"cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [{"data": {"text/plain": ["[{'id': '912',\n", " 'time': '2020-06-01T12:13:59.975513465Z',\n", " 'userID': 13834683,\n", " 'accountID': '101-004-13834683-001',\n", " 'batchID': '912',\n", " 'requestID': '60716390399775646',\n", " 'type': 'MARKET_ORDER',\n", " 'instrument': 'EUR_USD',\n", " 'units': '10000.0',\n", " 'timeInForce': 'FOK',\n", " 'positionFill': 'DEFAULT',\n", " 'reason': 'CLIENT_ORDER'},\n", " {'id': '913',\n", " 'time': '2020-06-01T12:13:59.975513465Z',\n", " 'userID': 13834683,\n", " 'accountID': '101-004-13834683-001',\n", " 'batchID': '912',\n", " 'requestID': '60716390399775646',\n", " 'type': 'ORDER_FILL',\n", " 'orderID': '912',\n", " 'instrument': 'EUR_USD',\n", " 'units': '10000.0',\n", " 'gainQuoteHomeConversionFactor': '0.899539435809',\n", " 'lossQuoteHomeConversionFactor': '0.899636546835',\n", " 'price': 1.11168,\n", " 'fullVWAP': 1.11168,\n", " 'fullPrice': {'type': 'PRICE',\n", " 'bids': [{'price': 1.11156, 'liquidity': '10000000'}],\n", " 'asks': [{'price': 1.11168, 'liquidity': '10000000'}],\n", " 'closeoutBid': 1.11156,\n", " 'closeoutAsk': 1.11168},\n", " 'reason': 'MARKET_ORDER',\n", " 'pl': '-1.9792',\n", " 'financing': '0.0',\n", " 'commission': '0.0',\n", " 'guaranteedExecutionFee': '0.0',\n", " 'accountBalance': '99388.3678',\n", " 'tradesClosed': [{'tradeID': '911',\n", " 'units': '10000.0',\n", " 'price': 1.11168,\n", " 'realizedPL': '-1.9792',\n", " 'financing': '0.0',\n", " 'guaranteedExecutionFee': '0.0',\n", " 'halfSpreadCost': '0.5398'}],\n", " 'halfSpreadCost': '0.5398'}]"]}, "execution_count": 29, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_transactions(tid=int(oo['id']) - 2)"]}, {"cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": [" 896 | 2020-06-01T12:05:17.943789810Z | EUR_USD | 1000.0 | 0.0\n", " 898 | 2020-06-01T12:05:18.094374690Z | EUR_USD | -1500.0 | -0.108\n", " 900 | 2020-06-01T12:05:18.262928049Z | EUR_USD | 500.0 | -0.054\n", " 903 | 2020-06-01T12:10:20.832960817Z | EUR_USD | 1000.0 | 0.0\n", " 905 | 2020-06-01T12:10:20.994033040Z | EUR_USD | -1500.0 | -0.126\n", " 907 | 2020-06-01T12:10:21.153454837Z | EUR_USD | 500.0 | -0.063\n", " 909 | 2020-06-01T12:12:15.999798563Z | EUR_USD | 10000.0 | 0.0\n", " 911 | 2020-06-01T12:13:48.497339577Z | EUR_USD | -20000.0 | -1.8894\n", " 913 | 2020-06-01T12:13:59.975513465Z | EUR_USD | 10000.0 | -1.9792\n"]}], "source": ["api.print_transactions(tid=int(oo['id']) - 18)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"anaconda-cloud": {}, "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch08/MomentumTrader.py b/ch08/MomentumTrader.py new file mode 100644 index 0000000..8e09ad8 --- /dev/null +++ b/ch08/MomentumTrader.py @@ -0,0 +1,68 @@ +# +# Python Script +# with Momentum Trading Class +# for Oanda v20 +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import tpqoa +import numpy as np +import pandas as pd + + +class MomentumTrader(tpqoa.tpqoa): + def __init__(self, conf_file, instrument, bar_length, momentum, units, + *args, **kwargs): + super(MomentumTrader, self).__init__(conf_file) + self.position = 0 + self.instrument = instrument + self.momentum = momentum + self.bar_length = bar_length + self.units = units + self.raw_data = pd.DataFrame() + self.min_length = self.momentum + 1 + + def on_success(self, time, bid, ask): + ''' Takes actions when new tick data arrives. ''' + print(self.ticks, end=' ') + self.raw_data = self.raw_data.append(pd.DataFrame( + {'bid': bid, 'ask': ask}, index=[pd.Timestamp(time)])) + self.data = self.raw_data.resample( + self.bar_length, label='right').last().ffill().iloc[:-1] + self.data['mid'] = self.data.mean(axis=1) + self.data['returns'] = np.log(self.data['mid'] / + self.data['mid'].shift(1)) + self.data['position'] = np.sign( + self.data['returns'].rolling(self.momentum).mean()) + + if len(self.data) > self.min_length: + self.min_length += 1 + if self.data['position'].iloc[-1] == 1: + if self.position == 0: + self.create_order(self.instrument, self.units) + elif self.position == -1: + self.create_order(self.instrument, self.units * 2) + self.position = 1 + elif self.data['position'].iloc[-1] == -1: + if self.position == 0: + self.create_order(self.instrument, -self.units) + elif self.position == 1: + self.create_order(self.instrument, -self.units * 2) + self.position = -1 + + +if __name__ == '__main__': + strat = 2 + if strat == 1: + mom = MomentumTrader('../pyalgo.cfg', 'DE30_EUR', 3, 1) + mom.stream_data(mom.instrument, stop=100) + mom.create_order(mom.instrument, units=-mom.position * mom.units) + elif strat == 2: + mom = MomentumTrader('../pyalgo.cfg', instrument='EUR_USD', + momentum=6, units=100000) + mom.stream_data(mom.instrument, stop=100) + mom.create_order(mom.instrument, units=-mom.position * mom.units) + else: + print('Strategy not known.') diff --git a/ch09/09_pyalgo.ipynb b/ch09/09_pyalgo.ipynb new file mode 100644 index 0000000..4b6bf8a --- /dev/null +++ b/ch09/09_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading "]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Chapter 09 — FX Trading with FXCM**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Risk Disclaimer"]}, {"cell_type": "markdown", "metadata": {}, "source": ["\n", "Trading forex/CFDs on margin carries a high level of risk and may not be suitable for all investors as you could sustain losses in excess of deposits. Leverage can work against you. Due to the certain restrictions imposed by the local law and regulation, German resident retail client(s) could sustain a total loss of deposited funds but are not subject to subsequent payment obligations beyond the deposited funds. Be aware and fully understand all risks associated with the market and trading. Prior to trading any products, carefully consider your financial situation and experience level. Any opinions, news, research, analyses, prices, or other information is provided as general market commentary, and does not constitute investment advice. FXCM & TPQ will not accept liability for any loss or damage, including without limitation to, any loss of profit, which may arise directly or indirectly from use of or reliance on such information.\n", ""]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Author Disclaimer"]}, {"cell_type": "markdown", "metadata": {}, "source": ["The author is neither an employee, agent nor representative of FXCM and is therefore acting independently. The opinions given are their own, constitute general market commentary, and do not constitute the opinion or advice of FXCM or any form of personal or investment advice. FXCM assumes no responsibility for any loss or damage, including but not limited to, any loss or gain arising out of the direct or indirect use of this or any other content. Trading forex/CFDs on margin carries a high level of risk and may not be suitable for all investors as you could sustain losses in excess of deposits."]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Retrieving Tick Data"]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["import time\n", "import numpy as np\n", "import pandas as pd\n", "import datetime as dt\n", "from pylab import mpl, plt"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["plt.style.use('seaborn')\n", "mpl.rcParams['font.family'] = 'serif'\n", "%matplotlib inline"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": ["from fxcmpy import fxcmpy_tick_data_reader as tdr"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'EURAUD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURUSD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY')\n"]}], "source": ["print(tdr.get_available_symbols())"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": ["start = dt.datetime(2020, 3, 25)\n", "stop = dt.datetime(2020, 3, 30)"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": ["td = tdr('EURUSD', start, stop)"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "Index: 4504288 entries, 03/22/2020 21:12:02.256 to 03/27/2020 20:59:00.022\n", "Data columns (total 2 columns):\n", " # Column Dtype \n", "--- ------ ----- \n", " 0 Bid float64\n", " 1 Ask float64\n", "dtypes: float64(2)\n", "memory usage: 103.1+ MB\n"]}], "source": ["td.get_raw_data().info()"]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "DatetimeIndex: 4504288 entries, 2020-03-22 21:12:02.256000 to 2020-03-27 20:59:00.022000\n", "Data columns (total 2 columns):\n", " # Column Dtype \n", "--- ------ ----- \n", " 0 Bid float64\n", " 1 Ask float64\n", "dtypes: float64(2)\n", "memory usage: 103.1 MB\n"]}], "source": ["td.get_data().info()"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [{"data": {"text/html": ["
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"anaconda-cloud": {}, "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch08/MomentumTrader.py b/ch08/MomentumTrader.py new file mode 100644 index 0000000..8e09ad8 --- /dev/null +++ b/ch08/MomentumTrader.py @@ -0,0 +1,68 @@ +# +# Python Script +# with Momentum Trading Class +# for Oanda v20 +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# The Python Quants GmbH +# +import tpqoa +import numpy as np +import pandas as pd + + +class MomentumTrader(tpqoa.tpqoa): + def __init__(self, conf_file, instrument, bar_length, momentum, units, + *args, **kwargs): + super(MomentumTrader, self).__init__(conf_file) + self.position = 0 + self.instrument = instrument + self.momentum = momentum + self.bar_length = bar_length + self.units = units + self.raw_data = pd.DataFrame() + self.min_length = self.momentum + 1 + + def on_success(self, time, bid, ask): + ''' Takes actions when new tick data arrives. ''' + print(self.ticks, end=' ') + self.raw_data = self.raw_data.append(pd.DataFrame( + {'bid': bid, 'ask': ask}, index=[pd.Timestamp(time)])) + self.data = self.raw_data.resample( + self.bar_length, label='right').last().ffill().iloc[:-1] + self.data['mid'] = self.data.mean(axis=1) + self.data['returns'] = np.log(self.data['mid'] / + self.data['mid'].shift(1)) + self.data['position'] = np.sign( + self.data['returns'].rolling(self.momentum).mean()) + + if len(self.data) > self.min_length: + self.min_length += 1 + if self.data['position'].iloc[-1] == 1: + if self.position == 0: + self.create_order(self.instrument, self.units) + elif self.position == -1: + self.create_order(self.instrument, self.units * 2) + self.position = 1 + elif self.data['position'].iloc[-1] == -1: + if self.position == 0: + self.create_order(self.instrument, -self.units) + elif self.position == 1: + self.create_order(self.instrument, -self.units * 2) + self.position = -1 + + +if __name__ == '__main__': + strat = 2 + if strat == 1: + mom = MomentumTrader('../pyalgo.cfg', 'DE30_EUR', 3, 1) + mom.stream_data(mom.instrument, stop=100) + mom.create_order(mom.instrument, units=-mom.position * mom.units) + elif strat == 2: + mom = MomentumTrader('../pyalgo.cfg', instrument='EUR_USD', + momentum=6, units=100000) + mom.stream_data(mom.instrument, stop=100) + mom.create_order(mom.instrument, units=-mom.position * mom.units) + else: + print('Strategy not known.') diff --git a/ch09/09_pyalgo.ipynb b/ch09/09_pyalgo.ipynb new file mode 100644 index 0000000..4b6bf8a --- /dev/null +++ b/ch09/09_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading "]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Chapter 09 — FX Trading with FXCM**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Risk Disclaimer"]}, {"cell_type": "markdown", "metadata": {}, "source": ["\n", "Trading forex/CFDs on margin carries a high level of risk and may not be suitable for all investors as you could sustain losses in excess of deposits. Leverage can work against you. Due to the certain restrictions imposed by the local law and regulation, German resident retail client(s) could sustain a total loss of deposited funds but are not subject to subsequent payment obligations beyond the deposited funds. Be aware and fully understand all risks associated with the market and trading. Prior to trading any products, carefully consider your financial situation and experience level. Any opinions, news, research, analyses, prices, or other information is provided as general market commentary, and does not constitute investment advice. FXCM & TPQ will not accept liability for any loss or damage, including without limitation to, any loss of profit, which may arise directly or indirectly from use of or reliance on such information.\n", ""]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Author Disclaimer"]}, {"cell_type": "markdown", "metadata": {}, "source": ["The author is neither an employee, agent nor representative of FXCM and is therefore acting independently. The opinions given are their own, constitute general market commentary, and do not constitute the opinion or advice of FXCM or any form of personal or investment advice. FXCM assumes no responsibility for any loss or damage, including but not limited to, any loss or gain arising out of the direct or indirect use of this or any other content. Trading forex/CFDs on margin carries a high level of risk and may not be suitable for all investors as you could sustain losses in excess of deposits."]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Retrieving Tick Data"]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["import time\n", "import numpy as np\n", "import pandas as pd\n", "import datetime as dt\n", "from pylab import mpl, plt"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["plt.style.use('seaborn')\n", "mpl.rcParams['font.family'] = 'serif'\n", "%matplotlib inline"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": ["from fxcmpy import fxcmpy_tick_data_reader as tdr"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'EURAUD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURUSD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY')\n"]}], "source": ["print(tdr.get_available_symbols())"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": ["start = dt.datetime(2020, 3, 25)\n", "stop = dt.datetime(2020, 3, 30)"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": ["td = tdr('EURUSD', start, stop)"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" Bid Ask\n", "2020-03-22 21:12:02.256 1.07006 1.07050\n", "2020-03-22 21:12:02.258 1.07002 1.07050\n", "2020-03-22 21:12:02.259 1.07003 1.07033\n", "2020-03-22 21:12:02.653 1.07003 1.07034\n", "2020-03-22 21:12:02.749 1.07000 1.07034"]}, "execution_count": 9, "metadata": {}, "output_type": "execute_result"}], "source": ["td.get_data().head()"]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": ["sub = td.get_data(start='2020-03-25 12:00:00',\n", " end='2020-03-25 12:15:00')"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | Bid | \n", "Ask | \n", "
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| 2020-03-22 21:12:02.256 | \n", "1.07006 | \n", "1.07050 | \n", "
| 2020-03-22 21:12:02.258 | \n", "1.07002 | \n", "1.07050 | \n", "
| 2020-03-22 21:12:02.259 | \n", "1.07003 | \n", "1.07033 | \n", "
| 2020-03-22 21:12:02.653 | \n", "1.07003 | \n", "1.07034 | \n", "
| 2020-03-22 21:12:02.749 | \n", "1.07000 | \n", "1.07034 | \n", "
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\n", "
"], "text/plain": [" Bid Ask\n", "2020-03-25 12:00:00.067 1.08109 1.0811\n", "2020-03-25 12:00:00.072 1.08110 1.0811\n", "2020-03-25 12:00:00.074 1.08109 1.0811\n", "2020-03-25 12:00:00.078 1.08111 1.0811\n", "2020-03-25 12:00:00.121 1.08112 1.0811"]}, "execution_count": 11, "metadata": {}, "output_type": "execute_result"}], "source": ["sub.head()"]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": ["sub['Mid'] = sub.mean(axis=1)"]}, {"cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": ["sub['SMA'] = sub['Mid'].rolling(1000).mean()"]}, {"cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["| \n", " | Bid | \n", "Ask | \n", "
|---|---|---|
| 2020-03-25 12:00:00.067 | \n", "1.08109 | \n", "1.0811 | \n", "
| 2020-03-25 12:00:00.072 | \n", "1.08110 | \n", "1.0811 | \n", "
| 2020-03-25 12:00:00.074 | \n", "1.08109 | \n", "1.0811 | \n", "
| 2020-03-25 12:00:00.078 | \n", "1.08111 | \n", "1.0811 | \n", "
| 2020-03-25 12:00:00.121 | \n", "1.08112 | \n", "1.0811 | \n", "
"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["sub[['Mid', 'SMA']].plot(figsize=(10, 6), lw=1.5);\n", "plt.savefig('../../images/ch09/fxcm_plot_01.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Retrieving Candles Data"]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": ["from fxcmpy import fxcmpy_candles_data_reader as cdr"]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'EURAUD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURUSD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY')\n"]}], "source": ["print(cdr.get_available_symbols())"]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": ["start = dt.datetime(2020, 4, 1)\n", "stop = dt.datetime(2020, 5, 1)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["`period` must be one of `m1`, `H1` or `D1`"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": ["period = 'H1'"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": ["candles = cdr('EURUSD', start, stop, period)"]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": ["data = candles.get_data()"]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "DatetimeIndex: 600 entries, 2020-03-29 21:00:00 to 2020-05-01 20:00:00\n", "Data columns (total 8 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 BidOpen 600 non-null float64\n", " 1 BidHigh 600 non-null float64\n", " 2 BidLow 600 non-null float64\n", " 3 BidClose 600 non-null float64\n", " 4 AskOpen 600 non-null float64\n", " 5 AskHigh 600 non-null float64\n", " 6 AskLow 600 non-null float64\n", " 7 AskClose 600 non-null float64\n", "dtypes: float64(8)\n", "memory usage: 42.2 KB\n"]}], "source": ["data.info()"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [{"data": {"text/html": ["
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"], "text/plain": [" BidOpen BidHigh BidLow BidClose\n", "2020-05-01 16:00:00 1.09976 1.09996 1.09850 1.09874\n", "2020-05-01 17:00:00 1.09874 1.09888 1.09785 1.09818\n", "2020-05-01 18:00:00 1.09818 1.09820 1.09757 1.09766\n", "2020-05-01 19:00:00 1.09766 1.09816 1.09747 1.09793\n", "2020-05-01 20:00:00 1.09793 1.09812 1.09730 1.09788"]}, "execution_count": 22, "metadata": {}, "output_type": "execute_result"}], "source": ["data[data.columns[:4]].tail()"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | BidOpen | \n", "BidHigh | \n", "BidLow | \n", "BidClose | \n", "
|---|---|---|---|---|
| 2020-05-01 16:00:00 | \n", "1.09976 | \n", "1.09996 | \n", "1.09850 | \n", "1.09874 | \n", "
| 2020-05-01 17:00:00 | \n", "1.09874 | \n", "1.09888 | \n", "1.09785 | \n", "1.09818 | \n", "
| 2020-05-01 18:00:00 | \n", "1.09818 | \n", "1.09820 | \n", "1.09757 | \n", "1.09766 | \n", "
| 2020-05-01 19:00:00 | \n", "1.09766 | \n", "1.09816 | \n", "1.09747 | \n", "1.09793 | \n", "
| 2020-05-01 20:00:00 | \n", "1.09793 | \n", "1.09812 | \n", "1.09730 | \n", "1.09788 | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" AskOpen AskHigh AskLow AskClose\n", "2020-05-01 16:00:00 1.09980 1.09998 1.09853 1.09876\n", "2020-05-01 17:00:00 1.09876 1.09891 1.09786 1.09818\n", "2020-05-01 18:00:00 1.09818 1.09822 1.09758 1.09768\n", "2020-05-01 19:00:00 1.09768 1.09818 1.09748 1.09795\n", "2020-05-01 20:00:00 1.09795 1.09856 1.09733 1.09841"]}, "execution_count": 23, "metadata": {}, "output_type": "execute_result"}], "source": ["data[data.columns[4:]].tail()"]}, {"cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": ["data['MidClose'] = data[['BidClose', 'AskClose']].mean(axis=1)"]}, {"cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": ["data['SMA1'] = data['MidClose'].rolling(30).mean()\n", "data['SMA2'] = data['MidClose'].rolling(100).mean()"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["| \n", " | AskOpen | \n", "AskHigh | \n", "AskLow | \n", "AskClose | \n", "
|---|---|---|---|---|
| 2020-05-01 16:00:00 | \n", "1.09980 | \n", "1.09998 | \n", "1.09853 | \n", "1.09876 | \n", "
| 2020-05-01 17:00:00 | \n", "1.09876 | \n", "1.09891 | \n", "1.09786 | \n", "1.09818 | \n", "
| 2020-05-01 18:00:00 | \n", "1.09818 | \n", "1.09822 | \n", "1.09758 | \n", "1.09768 | \n", "
| 2020-05-01 19:00:00 | \n", "1.09768 | \n", "1.09818 | \n", "1.09748 | \n", "1.09795 | \n", "
| 2020-05-01 20:00:00 | \n", "1.09795 | \n", "1.09856 | \n", "1.09733 | \n", "1.09841 | \n", "
"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["data[['MidClose', 'SMA1', 'SMA2']].plot(figsize=(10, 6));\n", "plt.savefig('../../images/ch09/fxcm_plot_02.png')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Connecting to the API"]}, {"cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": ["import fxcmpy"]}, {"cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [{"data": {"text/plain": ["'1.2.6'"]}, "execution_count": 28, "metadata": {}, "output_type": "execute_result"}], "source": ["fxcmpy.__version__"]}, {"cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": ["api = fxcmpy.fxcmpy(config_file='../pyalgo.cfg')"]}, {"cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": ["instruments = api.get_instruments()"]}, {"cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["['EUR/USD', 'USD/JPY', 'GBP/USD', 'USD/CHF', 'EUR/CHF', 'AUD/USD', 'USD/CAD', 'NZD/USD', 'EUR/GBP', 'EUR/JPY', 'GBP/JPY', 'CHF/JPY', 'GBP/CHF', 'EUR/AUD', 'EUR/CAD', 'AUD/CAD', 'AUD/JPY', 'CAD/JPY', 'NZD/JPY', 'GBP/CAD', 'GBP/NZD', 'GBP/AUD', 'AUD/NZD', 'USD/SEK', 'EUR/SEK', 'EUR/NOK', 'USD/NOK', 'USD/MXN', 'AUD/CHF', 'EUR/NZD', 'USD/ZAR', 'USD/HKD', 'ZAR/JPY', 'USD/TRY', 'EUR/TRY', 'NZD/CHF', 'CAD/CHF', 'NZD/CAD', 'TRY/JPY', 'USD/ILS', 'USD/CNH', 'AUS200', 'ESP35', 'FRA40', 'GER30', 'HKG33', 'JPN225', 'NAS100', 'SPX500', 'UK100', 'US30', 'Copper', 'CHN50', 'EUSTX50', 'USDOLLAR', 'US2000', 'USOil', 'UKOil', 'SOYF', 'NGAS', 'WHEATF', 'CORNF', 'Bund', 'XAU/USD', 'XAG/USD', 'EMBasket', 'JPYBasket', 'BTC/USD', 'BCH/USD', 'ETH/USD', 'LTC/USD', 'XRP/USD', 'CryptoMajor', 'EOS/USD', 'XLM/USD', 'USEquities']\n"]}], "source": ["print(instruments)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Retrieving Historical Data"]}, {"cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": ["candles = api.get_candles('USD/JPY', period='D1', number=10)"]}, {"cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "DatetimeIndex: 438 entries, 2019-01-02 22:00:00 to 2020-06-01 21:00:00\n", "Data columns (total 9 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 bidopen 438 non-null float64\n", " 1 bidclose 438 non-null float64\n", " 2 bidhigh 438 non-null float64\n", " 3 bidlow 438 non-null float64\n", " 4 askopen 438 non-null float64\n", " 5 askclose 438 non-null float64\n", " 6 askhigh 438 non-null float64\n", " 7 asklow 438 non-null float64\n", " 8 tickqty 438 non-null int64 \n", "dtypes: float64(8), int64(1)\n", "memory usage: 34.2 KB\n"]}], "source": ["candles.info()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["The parameter `period` must be one of `m1, m5, m15, m30, H1, H2, H3, H4, H6, H8, D1, W1` or `M1`."]}, {"cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [], "source": ["candles = api.get_candles('EUR/USD', period='m1', number=250)"]}, {"cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [{"data": {"image/png": 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G8Ngksckkv/HWIxzKk6nM1dCUCVJburS5uYiISD7akoFZS+cIyZTD/mkrF90u+YOZOrOh0bk1ZgDXmzA+r8Wv33mEVxyuXacRr4/ddaUAXNI2TSIiInkpZ42ZMaYOeAA4Ztv2TQtccw/wUeD9tm0/PO34fuATQMK27bunHf8YEAQ6gVuAD9i2fdYY81rgzwG3Z8Ujtm1/fLkv6lymvmx6YFaZCcwGRmI01YWyG4JPn8oEeO21Ddx6VR1+n3e5T5v3GsLFeD0Wl5QxExERyUtLKf6/DXgIuHa+k8aYPUAv0DbP6ZuBfwXeOOt4FPgD27YdY8zvAR8Efj1z7ndt2/7+Esa1oOkrMl2VpekArD+zAGAoMoHXYxEKzm2FsRWDMphaANDWM6YFACIiInkoZ2Bm2/bXM5mshc43A83GmA/Pc+6Lxph3z3P8f0z7dD9wetrn9xpjbgRKgb+1bXu+gG+OcDjEwEiMyXiSi5dHqKsKsn9Pdfb83ki6tiyWcAiHQ4xG41SUFlFbU7qUh98yDu2p5FL3KN0jE1x7sGajhyMiIiLTbFi7DGOMAe4DwsAHModPAx+xbbvFGHMU+LYx5oht2zk3ePy3xy/w6QdPZj+/em8lvb1TPbs8qSQA7d0jdPeM0D+cntKcfs12cPXuCr719CU++vfP8oFfuDZbdyYiIiLrIxxeuEn8hs1l2WnvAR4EPpc51mPbdkvm41NAObBrKY/n1pVdd6Ca1xyr52de2TTjfHlJIR7LYmBkgsh4nGTKmbEic7s4sruSX/vZI4xPJvizL79Aq3YCEBERyRsrCsyMMZXGmBWnWowxH5z2aTOwN3P8fmNMpfscQAHQvZTH7B6MAvCrdxzm3W85TEO4ZMZ5j8eiPFTAwGiM3sFxYO6KzO3ilqN1vOeOw4zFEnz6X04yPpHY6CGJiIgISwjMjDG3A/cC9caYDxljAsD9wG9nzlvGmA8BTcA7jTFvmnbvXcCdwCFjzH3THvYmY8z/NMb8IfA+4P2Z4y3Ap4wxfwB8CrjXtu0YS9A1ECUU9FNctPC+lpWlRQyNTvKFb58F2FI9ypbrVVels4o9Q+N87t/PZBvvioiIyMaxtsIf5Hgi5dx9/8PsbSjlD991w4LX/fVDJ3nm5R4Abr26jvfccWS9hpiXEskUf/ql45zvGOaX32x47bUNGz0kERGRLS8cDlkLndsS/RK6B8ZIOQ51FcFFr3N7me2oLuZdbzDrMbS85vN6eO9dRyku8vGP3zlHW48az4qIiGykLRGYdWQCitrKwKLXXbu/mn07Svmtu45SWLA1e5UtV2VpEe+54wjxRIq/evAksUnVm4mIiGyUrRGYZTblrqtcPGN2cFc5//WXb5yzMGC7u/ZANW+8aRddA1G++K2zGz0cERGRbWtLBGaX+9IZs1yBmSzs7tfuoyFczBMnu7RKU0REZINsicCsozeCBdRULD6VKQvzeT0czqxSvdw3tsGjERER2Z62RGB2uTdCVVnRlt3jcr3szEzxtvdqEYCIiMhG2BKB2cDIBLWaxrxibmDm1uyJiIjI+toSgRmQs1WG5NZQXYyFMmYiIiIbZcsEZrlaZUhuhQVewuUB2nvHtBOAiIjIBtgygZlWZK6OhnAxkfE4I2OTGz0UERGRbWfLBGaqMVsdUwsAVGcmIiKy3rZEYPYLbzRUlxVt9DC2hIZwMaA6MxERkY2wJQKzX3zTISxrwf1AZRnUMkNERGTjbInATFZPbWUAn9ejlhkiIiIbQIGZzOD1eNhRFeRy3xiplFZmioiIrCcFZjJHQ7iEyUSKnqHxjR6KiIjItqLATObYv7MMgBfO9W3wSERERLYXBWYyx02HavB6LJ442alGsyIiIutIgZnMURLwc+3+ajp6x2jt1upMERGR9aLATOZ169X1APzopc4NHomIiMj2ocBM5nXV3kpCQT9Pn+4mkUxt9HBERES2BQVmMi+f18Mrj9QRGY/z4oX+jR6OiIjItqDATBZ0bH8VAJe6Rjd4JCIiItuDAjNZUGlxAQCR8fgGj0RERGR7UGAmCwoF04HZaHRyg0ciIiKyPSgwkwWVBHwAjEaVMRMREVkPCsxkQV6Ph+Iin6YyRURE1okCM1lUSbBAU5kiIiLrRIGZLCoU8BMZT5DS1kwiIiJrzpfrAmNMHfAAcMy27ZsWuOYe4KPA+23bfnja8f3AJ4CEbdt3Tzv+MSAIdAK3AB+wbfusMcYD/DEQAZqAz9q2/eOVvji5cqGgn5TjEI0lKAn4N3o4IiIiW9pSMma3AQ8B1nwnjTF7gF6gbZ7TNwP/Os/xKOkg7qPAY8AHM8fvAUpt234A+H3g88YY7xLGKGskFEwHY5rOFBERWXs5AzPbtr8OLNhh1LbtZtu2H1vg3BeBOX/Rbdv+H7Ztu3Nj+4HTmY/vAJ7KXDMAxICjucYoa6ckoF5mIiIi6yXnVOZaMcYY4D4gDHwgc7iGmUHgSOZYTuFwaFXHJ2n1NSUAWD6fvsYiIiJrbMMCM9u2beA9xphfBT5HehqzB5j+1780cyyn3l5tG7QmMhuYX+4eobeuZIMHIyIisvktluhY0apMY0ylMaZ0pQMyxnxw2qfNwN7Mx4+QXgyAMaYSKAJOrfR55Mqp+7+IiMj6WcqqzNuBe4F6Y8yHgD8D7gcGgI8ZYyzgv5JeRflOY0zctu1HM/feBdyZ/tDcZ9v2n2Ye9iZjzP8ExoDrgfdnjn8VuM4Y82GgEfhl27aTq/RaZQWmiv9VYyYiIrLWLGdr9KdyNJW5NvqGxrnvr5/ilqN1/PqdRzZ6OCIiIpteOByat9MFqMGs5JCdyhzXVKaIiMhaU2Amiyrwe/D7PEQ0lSkiIrLmFJjJoizLIhT0q8ZMRERkHSgwk5xCgQJNZYqIiKwDBWaSU0nQz2Q8xURcC2RFRETWkgIzycltmaE6MxERkbWlwExyKglkAjPtlykiIrKmFJhJTur+LyIisj4UmElO6v4vIiKyPhSYSU6hgBuYTfKZh0/zqa+d2OARiYiIbE0598oUcacyv/1cG/0jEwAMjMSoLC3ayGGJiIhsOcqYSU5u8b8blAGc7xjeqOGIiIhsWQrMJCe3xswC3vbqPQCcb1dgJiIisto0lSk5lQT8vOZYPU11pdx2dR0PP9nCOWXMREREVp0CM8nJsize/ZbD2c+b6kI0Xx4lNpmgqEDfQiIiIqtFU5mybAcaykk5Ds2do8u6bzKe5GNfeJ4fvNCxRiMTERHZ3BSYybLtaygD4Hz70LLuu9Q9ytn2YR77iQIzERGR+Sgwk2XbvzMTmHWMLOu+1u4IAG09EcZialYrIiIymwIzWbay4gJqKgJc6Bgm5TgLXpdKOURjieznbT3pwMwBzrYtL9smIiKyHSgwkxXZ31BGdCJB90B0wWv+7elL/Je/fIL+4RgAbT1TNWl2qwIzERGR2RSYyYqEywMADI5OLHhNa3eEiXiSFy/2k0ylaO8do74qiM9rKTATERGZhwIzWRF3N4DI+MK1YqPRSQBONw/QPTBOPJFi745S9taX0tozOmOaU0RERBSYyQq5uwGMRhcLzNLnTl8apKUrvVCgsSaEaazAceDcMld1ioiIbHUKzGRF3I3N3azYfNxz4xMJHj/RCUBjbQmmsRxQnZmIiMhsatsuKxLKTGWOLjCVmXIcIuMJLNKrMO3MKsydNSX4vB68Hgu7bXCdRisiIrI5KGMmK5JrKjMaS5ByHA7uKsey0seqSosoLvJT6PfSUF1MR+8YziLtNkRERLYbBWayIsVu8f8CU5kjY+njtZVBdteVArCrpiR7PlwRYDKRYnhs4alQERGR7UaBmayIz+shWOhbcCrTrS8LBf0c3VMBpOvLXDWZdhs9g+NrPFIREZHNQ4GZrFgo6CeywFSmO8VZGizgtmt2cHBXOa84XJs9H65IB2a9QwrMREREXCr+lxUrCfrpG47hOA6WW0iW4WbSQkE/NeUB7v+l62ecdxvUKjATERGZkjMwM8bUAQ8Ax2zbvmmBa+4BPgq837bth6cd3w98AkjYtn135pgFfB44Szpjtw/4Ldu2x4wxrwX+HHD7KDxi2/bHV/jaZI2FAgUkUw7RiQTFRf4Z56amMgvmvTc7lanATEREJGspGbPbgIeAa+c7aYzZA/QCbfOcvhn4V+CN0455gIu2bX8kc/9fAe8F/ixz/ndt2/7+UgYvG8tdmRmJxucGZmPxGdfMVllaiNdjKWMmIiIyTc7AzLbtr2cyWQudbwaajTEfnufcF40x7551LAlMv9YDRKZ9fq8x5kagFPhb27bnC/jmCIdDS7lMVlFNVTEA3gL/nK//ZCrdBmP3rgqqygLz318RpH94Qv92IiIiGRtaY2aM2Q3sBf5T5tBp4CO2bbcYY44C3zbGHLFtO5XrsXp7R9duoDIvb+b/bZ1DVJfMzIz1DUYBmIhO0js5/56YlaWFnGoeo7V9kEChyh1FRGR7WCwhsWGrMo0xO0nXpb3Ttu0JANu2e2zbbsl8fAooB3Zt1BhlcYs1mR2NThIo9OH3Lfwt5i4A6BuOrc0ARURENpkVBWbGmEpjTOlKn9QYs490UPabtm0PGGPekTl+vzGm0n0OoADoXunzyNqaCszmNokdjcYXrC9zqZeZiIjITDkDM2PM7cC9QL0x5kPGmABwP/DbmfOWMeZDQBPwTmPMm6bdexdwJ3DIGHNf5lgR8EPAAN8wxnwfeHPmlhbgU8aYPwA+Bdxr27bSKXnKXXEZmdVkNuU4SwrMwuVFgFpmiIiIuJZS/P8D4AezDt837bxDup3GA/Pc+xDpFZ3Tj8WAhgWe68vAl3OOWvJCSWD+qUx3n8xQYP5WGS71MhMREZlJnf9lxbLtMmZlzKZvx7SY8Dr1MnvipU5Otwys6XOIiIisBgVmsmKFfi8+r2dOjVl2O6bixTNmgUIfoaCf3jWsMRsYifHZR17m7//tzJo9h4iIyGpRYCYrZlkWoaB/zlRmNmMWWDxjBukFAP0jMZKphTuijEQnuXh5ZEVjfN7uBdIrP3syLTxERETylQIzuSKhoD+7L6bLDdQW2o5punBFgGTKWbBlRt/QOB/5++f44394nsHRiWWP71m7J/vxqZbBZd8vIiKynhSYyRUJBfxMTCaJJ5LZY0utMQPYVVMCwKWuuQ2C+4bH+dN/PE7/SIyU43C+Y3hZYxscneB8+3C2LcepZtWZiYhIflNgJlfEzYpNn85cTsZsd226+/Gl7rmB2V89eJK+4Rg3HAwDcK59aM41i3k+ky17w027CJcX8fKlwUWnTEVERDaaAjO5IvO1zHCnNpeSMWuqywRmszJmk/EkLZ2j7N9Zxq/feQSvx+J8+/IyZs/ZvVjADSbM0d2VjE8kaO7U1l0iIpK/tEGhXJFs9//xqZWZI2NLn8oMFvmpKQ9wqWsUx3GwLAtIt9BwgIbqYgr8XnbXhWjuHGViMklhgXfBx7t4eYTPP3qGRNKhs2+MAzvLKC8p5MjuSr7/wmVONw+wv6HsCl6xiIjI2lHGTK5Itvv/rKnMogIvft/CAdR0TXUhxmKJGQsAugfSKyhrK4IA7N9ZRspxaO6cuTqzZ2h8xqKA58700NodYWh0gtLiAt5wU3qr1cO7K7AsOKV+ZiIikscUmMkVcbNiw5ksmeM49A2PU1VatOTH2D3PdGZXJjCrq8wEZpks1/QFAPFEkgc+9xyffvCl7LHO/jEAPvbeW/hf//E2bjA1ABQX+dldF+JCxwjxhOrMREQkPykwkysSnrUR+Wg0TmwySU1FYMmPka0zm7YAoHsg/Xh1VW7GrByYGZidbB4gMh6npXOURDIdbHUORAkF/dnat+l2hktIOY62gBIRkbylwEyuiDvV6Ga43ADNPb4UbmDWMj1jNhjFY1lUl6Uzb2XFBdSUBzjfPkzKcYD0tCVAMuXQPThOPJGid2ic+sr5n9sNFnvWcKcBERGRK6HATK5IYYGXilAh3Zmu+u7/l5MxKy7yEy4vyi4AAOjqjxIuL8LnnfoW3ddQRnQiQWffGPFEihfO92XPdfRG6BmM4jhQV1U87/O4waJ2ABARkXylwEyuWF1lkIGRCSbiSbqzGbOlB2YATbUhIuNxBkYmiIzHiYzHqZ2V+Tqyu327MK4AACAASURBVAKAf/7hRU41DzA+kaQx06C2vTdCZ3864KqvWjxj1q2pTBERyVMKzOSKuQFUz+B4NhtVs4ypTJiazrzYOZLNutXNCsxuOVrHocZyjp/r4/OPpjclv+vVewBo7xnLFv7nCsx6BpQxExGR/KTATK6YG0B1D0TpGRzH5/VQUVq4rMe4ak8VAM+c7p5qlTErMPN4LH79zqOEgn6GIpNUlhZy7f5qQkF/OmM24GbM5p/KLCrwUVZckM3qiYiI5BsFZnLF6irTmajOgSjdg+PUVATwZBrFLlVjbQk7w8W8cL6PCx3pXmV180yHVoQK+fU7j+CxLF51VR2WZdFQXUzfcIyWzlH8Ps+irTpqKwL0j8SyqzhFRETyiQIzuWJuZutCxzDjE4nspuHLYVkWr7qqnmTK4fEXO2c87mxX7aniz973Ku66LT2NuTOcrjPrGohSWxHE41k4KKypCOI4zGhmKyIiki8UmMkVqy4rwuuxePnSILC8FZnT3XK0Fo9lkUimKPB7KA8tPB1aVlKI15P+9t2ZWQAAC9eXubILAFRnJiIieUiBmVwxr8dDuDyQ7ai/UKYrl7KSQq7aWwlAXUVwydOhDeGpmrJcgdn0hQoiIiL5RoGZrIrpKyhXmjEDuPXq+vRjLCO4a6ieCszqcmXMytVkVkRE8pcCM1kVtZVTwVjtCmrMXNcdqOaNN+3ijZnNx5eiqMBHuDxd8F9fOf+KTNdULzNNZYqISP7xbfQAZGtwM2Y+r0XlMjYwn83n9fD//fSBZd9ndlUwPtGXM2MWKPRRGvTTM6CMmYiI5B8FZrIq3MAsXB5YdFXkWnnXGw9yz0/tp9DvzXltTWWQix0jJJKpGVs+iYiIbDT9VZJVUVdVjGUt3Nx1rRX4vZQE/Eu6trY8QMpx6B9RywwREckvypjJqigrLuD3fv7YildkrqfqTA1c33Asu7G5iIhIPlBgJqvmqr1VGz2EJXEza2Pj8Q0eiYiIyEyaypRtpziQfj8SjSU2eCQiIiIzKTCTbaekKJMxiyljJiIi+UWBmWw7QTcwG1fGTERE8kvOGjNjTB3wAHDMtu2bFrjmHuCjwPtt23542vH9wCeAhG3bd2eOWcDngbOkA8N9wG/Ztj1mjPEAfwxEgCbgs7Zt//gKXp/IHO5UZkQZMxERyTNLyZjdBjwEzNucyhizB+gF2uY5fTPwr/M850Xbtj9i2/Z/B8aA92bO3QOU2rb9APD7wOeNMbkbU4ksQ3EmY6YaMxERyTc5M2a2bX/dGPPaRc43A83GmA/Pc+6Lxph3zzqWBKZf6yGdIQO4A/hW5roBY0wMOAq8mGuc4XAo1yUiAFSmHAAmkyl934iISF7Z0HYZxpjdwF7gP2UO1QCj0y4ZyRzLqbd3NPdFIhnBQh9DIzF934iIyLpbLCmwYcX/xpidpOvS3mnb9kTmcA8wfbSlmWMiq6o44GNMU5kikhGNJfjMw6fpHoxu9FC2lXgiyT88avPES504jrPRw8kLKwrMjDGVxpjSlT6pMWYf6aDsNzNTlu/InHoEuMV9DqAIOLXS5xFZSHGRX+0yRCTrdMsAT57s4tGnWzd6KNvKC+f7eex4B5995GU+9fUXGRydyH3TFpczMDPG3A7cC9QbYz5kjAkA9wO/nTlvGWM+RHoV5TuNMW+adu9dwJ3AIWPMfZljRcAPAQN8wxjzfeDNmVu+Coxm6tU+DvxypiZNZFUVF/mYjKeIJ/TtJSJTfQ1PXOhX5mYdnTjfB0BTXYgXL/Tz1w+d3OARbbylFP//APjBrMP3TTvvkG6n8cA89z5EekXn9GMxoGGB50qRXo0psqaK3W2ZYgnKS7TwV2S7c1dpD45O0NYTobFWC4PWWirl8OKFfspLCvhv/+FGPvaFn3C+fZhoLJ7tN7kdqcGsbEvFRdovU0SmRCemak7dLI6srYudI0TG41yzrxqPZXG4qQIHONs+vNFD21AKzGRbcpvMagGAiMDM3wUvnO/fwJFsH24AfGx/FQCHGssBsFsHN2xM+UCBmWxLwULtlykiU6KZ3wV1lUGaO0cYHpvc4BFtfSfO9+HzejjSVAnA3oYyvB4Lu3Vog0e2sRSYybaUzZhpv0wRYarG7Jar6gB48YKmM5frW8+28UeffWZJb3j7hsdp7x3jcFMFhQXpOt9Cv5e9O0q51D3K+MT2/d2swEy2pZIiZcxEZMpYLIHPa3GjCQNwqnlgg0e0uUzGk3zziWbaeyM8fqIz5/UvXUx/fa/ZVzXjuGksx3HgXPv2zZopMJNtKVikGjMRmRKdSBAs8lNbGcTrsegfiW30kDaVp093Z3+ffu8n7aRSi7cccQOvw00VM46bxvTn23k6U4GZbEtT7TKUMRORdI1ZcZEPj2VRVlLA0KhqzJbKcRy++3w7Hsvimn1V9A3HePHC4gsozrcPU1zko64qOOP4/h3pOrMzCsxEthe1yxARl+M4RGMJgoXpTHpZcSHDYxNqNLtE59qHae2JcN3Bau6+fR8A332+bcHrB0cn6BuOsb+hDI9lzThXWOBld32IS12jTMa3ZwNwBWayLRVrKlNEMibjKZIpJ9vUtLykgETS0e+HJfreT9oBeP0NO9lZU4LZVc6plkE6+8fmvf5CR7pP2f6dZfOeb6guJuU423Y6WYGZbEsFfi9+nye7RF5Eti+3pMGtPS0vKQRgKKJ9G3NJOenu/TUVAQ7uSvchu/26HQA8Z/fOe895NzBrmD8wqyotAqBvWIGZyLZSXORTuwwRyXb9dwOzspICQIHZUnQPRIlNJtm3oxQrMy151Z4qLBZe2XqufRivx2JPfem856vLAoACM5FtpzjgV/G/iGR7mLk1Zm7GbDiiBQC5XOoaBaCpbirIKgn42V0f4kLHMLHJmW9+J+JJWrtHaawNUeCff5/iqjI3Yza+RqPObwrMZNsqLvITjSVIqcBXZFtzA7PiaTVmoIzZUrRkArPddTM3fT+yu5JkypnT9qKlc4RkyuHAAvVlANWZwKxfGTOR7aW4yIcD27rDtIjMrTErK3ZrzJQxy6W1exQLaKwtmXH86O70NkuzpzNz1ZdBOmPp9VgKzES2G7XMEBGYVmPmTmWG3KlMZcwWk3IcLnWPUlcVpKjAN+PcvoYyCvweTrXMDMzc/mQLrcgE8HgsKksLVWMmst1k98vUkniRNRObTDCR5/2osjVmmYxZKOjHY1nKmOXQOzjO+ESSptrQnHN+n4dDjRV09kcZyLS9iE0msFsHaawpydbxLaS6LMDw2OS27GWmwEy2raAyZiJrKjIe548++wx/+qWfbPRQFuVOZbpZdI9lUVrsV41ZDi3Zwv+5gRmk68wATrcMAnCqeZBE0uGa/dU5H9tdALAde5kpMJNtq0RNZkXWjOM4/N0jL9M3HKO5c5TRaP5mn8ZnZcwgXec0FJlU9/9FXFqg8N911Z50YPbUqS4ATlzoA+DaJQRm23kBgC/3JSJbk/bLFFk73362jRfO9+HzekgkU5zvGOa6A+GNHta8xhYIzFq6RolOJLKZtO0slXI42TzAs2e6aeka5bar62nuHAGgcZ6pTIAd1cUcbqrg5UuDnG0b4sUL/ZQG0600csk2mVXGTGT7cH/ZjkanArOeoXFaukY2akgim14imeLBxy/y1ccuUBr08ys/cwhIb1o926mWASJ5UEoQnUhgAYHC6YFZpmXG6NabzrRbB5fVIyyeSPKpr7/In3/tBE+81MXlvjG+8r3z2G1D1FYGZ3zdZrvrtj0AfPaR04yMTXLNvuo5+2POZztnzBSYybZVW5HuLj19P7e//eYp/uSLx0kkUxs1LJFNazQ6yUc+9xzfeKKF8lAB//Ed13Dt/mosa6pNgqu1e5Q/+/ILfOk7ZzdotFOisThFhb4ZAUOZuy3TWP5Owa7EifN9/MmXjvOFby3t6x5PpPg//3ySly72c3R3BX947w188ndu4waTzn4eXGR1JcDBXeUcbqqgdygdYB3bX7Wk593O3f81lSnbVlVZEYFCH63dESD9Tv9S1yiJpEP34DgN1cUbPMLlSSRTJJMOhQXzd9MWWWtPvNRFW0+EVx6p5d43mWwmZVdNCc2do8QTKfy+dD7gpYv9ABw/18dkPLlgF/j1kJ6unPnn0N2WaSu1zBgYifHZR14GoKN3/g3Go7EERYVePJbFwEiMzzx8mjOtQ1y9t4rfeftV+H3pf6fffttVtHZHCJcHcj7vW2/dzcuXBvF5reyCgFzKQwV4Pda27P6vwEy2LcuyaKwp4WzbEBOTSboGoiSS6ULfzr6xTReY/cOjNi9e6OdP3nvLhv6Rk+3rXHu6R9U7bt83Y3prf0MZrd0RLnWPZhuLuo1HJyaTnGwe4PqDG1d/NhZLUDsrwJjayHxrZMySqRR/841TRMbjFPg9DIzEZgTE0Vicf/zOOZ442UVlaSFX7ank2TM9jE8kue5ANe+962g2KIP078+FVmPOZhoreP0NOwkW+Rad9pzO6/FQEdqevcw0lSnb2q6aEhygvS8yo7bsct/87ybzVcpx+MnZXobHJrNL2EXWk+M4XOgYpiJUmG114HKbibp1ZhOTSc61D2ezVM+d6VnfwU6TSKaYmEzOKPyHrbct0/GzfZxrH+YGE+aVR+pwSNfUArT1RPhvn32GJ052UVsZZHwiyQ9PdOI48CtvOcTvvP3qGUHZSvziGw7ytlfvXdY91WVFDEcmiSe2V2mJMmayre3KbCPS1h2htXsqoLncv7kCs47esezKsnPtQxzcVb7BI5LtpmdonJFonJsO1cw5d6Ah/f3o1pnZbUMkUw6vuXYHz77cwwvn+4gnklf8x38l3C3ZgrNWXm61jNmJ8+lWFT/zyqbs/pXdA1F2hkt49JlWBkcneOutu/nZV+3GceDi5WHqKoPZWruN4Ab4AyMxaiuDGzaO9aaMmWxrjTXpVHxrT4SWrlF8XotCv5eOTZYxO9M6mP34QodWlcr6c7Nh8221U1laSEWokPPtQziOw+nMNj1X7a7kRlNDbDLJyYsDc+5bD7O7/rtKgwVY1taoMUulHF682E9ZSQFNdSHqMkFO10AUSPcjK/R7eeute/B5Pfh9HkxjxYYGZQDhzAKAv/inF/nGj5rzfgeJ1aLATLa1HdXFeD0WzZ0jtPdGaAiXsKM6SFd/lGRq86TPz2beAQcKvZzvGFZTTFl3bjbswDyBmWVZmF3ljETjfPPJFk41D1Dg87B/Zzk3ZjJsPz7dva7jdc3eJ9Pl8ViUBgu2xFRmc+cIo9E4x/ZV4bEsaivTAU/XQJSJySSX+8dorC3B48ndxmI93Xp1PdcfDNM7FOPBHzXz0I+aN3pI60KBmWxrfp+H+qpgdjXm7roQO6qKSaYcegbzezWQu4dcynGw24aoKi3k2L5qIuPx7DvhrSCRTKl9ySZwvn2YAr+HneGSec+/4/Z9VJcV8eDjzXT0jXFwVzl+n4c99SHqq4I8e6aHf3v60jqPevp2THMre2oqAvQNxxjJ410LlsLtuH9sX7rjfrg8gMey6B4Yp60nguMsvK3SRqoqK+J33n41f/4fb8Xv82QXjGx1Csxk29tVM/ULqakuxI5wejVmPi8AsFsH+U9/8Thf+s5ZLveNERmPYxor5hRZb3aO4/CRzz3H//nnlzZ6KDKP7sEobT0RxmJxOvrG2Ftfis87/5+VqrIi7vuF66gqTU+PuW0TLMvi/XdfQ0WokK89doFHn2ldt/HD9KnMud39rzsQxnHg+NneJT9eukN+P6k8ylqfON+Pz+vh8O4KAHxeD+HyIroGolzqXnxbpXwQLPKzb0cp7T2RvGhIvNZyBmbGmDpjzGeMMc8ucs09xpgLxpifnXV8vzHmQWPM12cdLzTGfNAYM26MKZl2/LXGmBeMMd/P/PfBlbwokeXYVTP1Dr+pNp0xg/wNzEaik/zNN04xGU/xnefa+cp3zwFgdpVnWxGc69gagVnfcIy2nggnLw5ki7QlP6RSDh//x+N8+O+e4dP/chKA/TsXX3RSXR7g93/xet7yykZefaw+e7ymIsh9v3gd5SUFfPWx8+v6x3ehGjOAGzNNVJezavTpl7v55FdO8OPM/pAbbWAk/TN0qKmcooKp11hbGSQyHs/W+zXVlW7UEJfENFbgAOfahjZ6KGtuKRmz24CHgHknn40xe4BeoG2e0zcD/zrP8VcC/wQUzXPud23bfm3mv48vYXwiV6QxszLT67HYGS7J9i+73J9/04Epx+Ez3zzNUGSS113fQKHfy6mWdOG/aapgZ7iEogLvlsmYuXVLKcfh3BZ5TVvFqZYBBkYm8HosXr6U/h503xgspro8wM+/dv+c/SdrK4LpNg4OdK3jz95iU5nV5QH21Id4+dLQjE3YJ+JJ/vxrJ3jyZOece5ovpxff5MvP4IkL6Ua+szcOdxcAvHSxnwK/h/o8X/VoMivNbQVmYNv214EFGyPZtt1s2/ZjC5z7IjBnct627R/Ytn1xgYe81xjzAWPM/zDG7Mo1PpEr5WbMGsLF+H0eKsuKKPB7FsyY9Q/HZmzjtJ6ePt3NyeYBrtpbyS+94SC//GYDQEWokHBZER6Pxb4dpXQNRGf8Idmspv9xs9sGF7lS1tsTL6WDkv/yzmu545Ymju2rwjReWZuWmsw2ad2D6xeYuXvlBgvn36j8xkM1pByH4+f6sseePt3Nixf6eeKluVmx9t70TiKXuvOjn2BbT3o8B2ZlM932E4mkQ2NNKO8K/2fb15CeJp++An2ryrc+ZqeBj9i23WKMOQp82xhzxLbtnJW/4XD+zo9LfgsDv/Pzx9gRLsl+HzXWhrjUNUplVQneWb+wPv7lF+geGONzH37zuo+1pfs8AL/xc9dQW1PKW2tK8RX4CJcHqKlJT0VcdSDMqZZBhmNJ9jZt7p+L5q5RCnwekimHi5dH9XOeJyLjcY6f66MhXMxtN+zi1Tc2rsrjHtyd3kcxMplct3/r85dH8Hk9HDtcO2+d2Rtv2cPXHrvAixcHeMfrDY7j8P0XLgPQOzQ+Y5yO42Qz7e29Y1RUFi9Yc7deRjLTwof2Vc94fWbP1J6Vh/ZUboqfLdNUwenmfgIlRZQE5g+kt4K8Csxs2+6Z9vEpY0w5sAvIuVSntzc/3p3I5nT9vvQvKff7qKY8wPn2YV4600XDrFVmLZ3DjE8kaW0fXPL2Iqvl9MV+Cv1egl4rO9abDlTPGLs/E0de7h5hZ2XufezyQcpxSKWcGX/ExicSXOoc4cCucpLJFOfahjbkay5zff+FDuKJFK88UktfX2TVHrcw88/f0jG8Lr/TB0ZiXOwY5uieSsZGY4yNzt3+x0t6UdCJc72cPNvNcGSSls70dGXfcIz2jqHs/rTDY5OMZDY9jydSnHi5i8bapQU88UQqm+UuLvKv2p63nb0Riot8c15fwDv1hrO2rGhT/A3dWxfi1MV+njrezrUHquec3+g9V5djsUB4RaG8MabSGLPqlYLGmPuNMZXucwAFwMY0t5Ft7Whmxdg3n2yZcTwaizM+kW5TsVr9jUajk1y4nLseZXwiweW+MXbXLT7t4AYublHzZvCV757nP/+fJ2YU+F+4PIxDui+WaawgldnyZzKe5GRz/4wWGu29EQZHN3+/qc3iyZe6sIBbjtat6uNWlBbi83roXqd2Ly9m6q+O7ata9LrX37CTZMrhT790nAcfT1fhuG1Bpk+7utOY7gboS90e7bkzPXzg00/wgU8/yQc+/SQf/KsnV2Wxi+M49A/HqC6b+watvKSAAn86BMjHVhnzOdTo1pnNnc584qVO3ve/fsjjJy6v97BW3VJWZd4O3AvUG2M+ZIwJAPcDv505bxljPgQ0Ae80xrxp2r13AXcCh4wx9007vjtzD8B9xphDmY9bgE8ZY/4A+BRwr23b228HU9lwNx+tZU99Kc+83JMtbAZmbKi7Wlu1fPHbZ/mfn3+eM5cWr51o6RrFAfbsWPw9kdsoc7OsYhyJTvLY8Q4i43E6eqdq97Kd5BvKsrVLJy7088mvnuCTXznBA59/jvPtw3zu38/wR599hv/7jVMbMv7tZmAkxvmOYQ41VVBZOt/6rZXzWBbh8iK6B8fXpUmyu03RNfvnZl+mu/Xqen7+dfsYHJ3gTOsQO8Ml3HZ1OijtntbvsCNTz/WqTMB6KUdg5jgOn3n4NJ9+8CSxySSvOFzDvh2lRMbjvHC+b9F7l2I0GmcykaK6bO6/k2VZ7KopIVjoo74qvwv/XXsbyvB5rRm/kwGeOtnF3z3yMsmUM+fcZpRzTsC27R8AP5h1+L5p5x3ggcx/s+99iPSKztnHW+a7x7btLwNfXsK4RdaUx7J41xsP8sDnnuNL3z7Lh3/lJnxez6zA7MozNPFEKrtq6ovTnmc+zZnpk731OQKzzOqy6CYJzB4/cTmb/ersH5vqxZZZkbmvoQyvx8JjWXz3+XYgXbjc2h3hj7/wfPZxWntGcRwHy8rvIubNzt1n8eq9i2eZVqq2Ikhnf5SxWCJnHdFIdJJk0sHrTXfpX46JeJLTlwbZUV1MTXnuKf+33NyE48C//PAiP/uqJooyU43Tmzm3Z95Y3Hyklm8925ZzAUBbT4QnT3axM1zMb73tKuqriunoG+O/feZpnjvTc8UZSff31exN5V2/eedRYvEkXs/maGla6Peyv6EMuzW9SjYULODkxX4+88hpAoU+EqkUrT2rN7W+UTbHv4bIBthTX8prrt1BR98YT2V6Eq12YHa2bYiJySQFfg8dfWN87ycdC157MbMMf2+OjFl2KnMTBGbJVIrHjk+95s7MH7lkKsWFyyPUVwUpCfgJFPrYXZ+ebrnBhPnIe17B++++hsbaEn72Vbu5Zl8V4xNJRqJbv/nkRnOnkQ41XdkKzIUsdWXmt59t43f/4kf8l798gt/9ix/xw2VOYZ25NEg8keLY/qUHmD/zyib+8vdewysO12ZXNXYPzJzK9HktGsLFNISLaeuJLLq1m1uPdtOhGuoz/RMbqovZUV3MS6vQu69/ZPHArLo8sOBODfnq6J5KHMhmxr7zfDuOA797zzGaakN09o9ld0XZrBSYiSzip67fCUxtDN4/LTBbjZomdyrlV3/mMMVFPh760UWGx+afIm3uHKGspICK0OIbC2enMjdBjdkL5/oYGJnI7pfo9q/q6B1jYjI5oy/W3bfv46237uY333o0vYpufzX//6+8gre/Zi8Nmd0a1qs2aTs70zpEoNBLY83a1CXVZgKznoGFt0QbHJ3gnx+/SHGRj2sy9WGty2xPcSJbX7b4NOZsbnF5dVkRXo+V/Z5LpRwu941RX1WM1+Nhd12IeCLF5b6FvydHMysmQ7OyfTeaMIlkKruV0kr1DY9nx7pVuDtGnGweIBqLc6p5gF01JexvKKOxJoTjQEeeNgdfKgVmIouorwri9Vh0ZIp63V90sPIas0QyheM4OI7DC+f7CBR6uf5gmDtu2c34RDIbrE03ODrB4OgEe+tLc07VbaaMmTs1eddteygJ+LP94S5mpm33TQvMDjVV8LZX7513qreuIp292Ep7hOajwdEJegbHObCzfM36XtVk/i0Xy5h99bHzTEwmufu1+/gPb06XKC93t4ALHem9Pfc1rGwdm9fjIVweyH7P9Q6NM5lIsTPzJsHtpN/SNbLgY7g91ELBmVO2N2XeqDx/Jr0VVDyRWlHNXXYqc5VrATdSU22IkoCf0y0DHD/XRzLlZN/Y7co0C2/b5NOZCsxEFuHzeqirDNLeN0Yqs8KpwO/BY1krmsoci8X5vf/9I/7qwZO09UToG45x1Z4qfF5Pdopyvj9IS53GBCgq8GJZ+R+YtfdEONM6xOGmChqqi6mrCtI7FCOeSGVf754c9XSu+aaVZPXZmeaehxor1uw5shmzofSboIuXR4jGpoKuM5cGefp0N3vqQ7z62I5sHdpyA7OhyASVoaIrqq+qqwwyFksQGY9nV2S6U4Pu3pOtXQsHCZHx9Ju72bV0O6qLqa8K8uLFfv7kiz/hvZ/4Po8+M9/mOotzM/xbKWPm8VgcbqpgYGSCf3s6va+qG8i6zcKXmz3NNwrMRHJoCBczMZmkfzhGX2bpeVlJAUMrmMo81z7MWCzBc3Yvn/zKCwDZGpfFpnAudqYL4ZcSqFiWRbDQl/dTmd/9STpb9vob0tPF9ZVBUo5Dz9A4zZ0jFPq92e2xcnG3l1HGbG2dyRT+X2mH/8VUlqanCHsGx3ne7uWBzz/Hf/3bpzl+rpfHjnfwqa+/CMAvvcHgsSz8Pg+FBV4iy6gvTCRTjEbjlJcsb8HAbLWZPoFd/dFs4b/b93BHdTEW0LFIn7epjNnMcViWxSsO1xJPpLDbhvB4LB59pnVGi5il6B+OESz0zds4dzM7uic9nXm5b4yd4eLsz39DdTEey9r0GTN1ahTJoSFcAi/3cL59mOhEgv07yxiNTtLWE1n2KkB3H72q0kL6RyawmFrdVlpcQGGBd8bye5e77H73EjcaDhT68jpjNhaL89SpLqrLijiWaVXgFj+3dI5wuXeMA7uWPl0WCqYXCMz3tZPVY7cNUVTgze4vuxY8His9Rdgf5cvfPYvXYzEWi/O//+klIF1D+RtvPTIjexwK+InElh6Yudnu8hz1mrm4mdq23ghPnezCY1nZnmCFfi/V5UULbu0GU4FZSXBu4PSWmxvZUV3M/oYyHn2mlW8928ZzZ3p4ZY6VmqnMlKdFeirTfcO3lRzZPZWxdacxIV3/V1cVpK0nQspx8GzSFdrKmInk4NaMuIW4VWVFlJcUkkg6jC2QlRoYidE7NF/mKx2Y/cG7buCGg2Fec+2O7Ltly7KoLQ/QMxSdU0/S3jtGVWlRthVGLsGi/A7MHj/RyWQ8xeuub8gGX24vpR+f6sJhadO2LsuyqKsM0jMYJZVa+/5X29FQZILugSgHdpaveXuF2ooA0YkE/SMTvPEVu/ijd9+E2VXOpQmeGwAAIABJREFUDQfDfOTXbuaVR2YGJ8UB/7IyZm59aEXJlQVm7sbfDz1+kZ6hcV5/407KiqeyXw3VJYxE4wvuWxuJTmIBJfNktAr8Xm46VENFqJCfur4Bi6mazIUkkin+8P/+mM88fJrIeJyJeHLBFZmbWXVZIBsU3zQtMANorCkhNpmkb57fv5uFAjORHNyakZcuDgBQXVqUfae90HTmJ7+aboA6MW3ZtuM4NF8eoaYiQGVpEe97+9XZwmVXTUWAyXhqxsrMkWh6mxc3QFyKYKGPicnkokv1N0oq5fDY8XYKfB5efc2O7HE3MDvdkq5jytWvbba6ygCJpJNtESCr66WL6VWMh9ZwGtPlLgCoCBVy56t2szNcwu//0vW87+1Xz7sqORTwM5lIzfh5W4z7c1t+hYGZGxyMROOUFhfw1lv3zDhfX50+v1DWbHQ8TnHAnzMzXFMR5Op9VVy4PJLtZzif0y2D9AyO8/Sp7mw7ia0YmAH84usPcM/r9mcz7a6tsABAgZlIDlVlRRQWeLM9hdyMGcDgPAsABkZiXO4bYzQa5+nTUzuKdQ+OE51ILBpwZFekTauVcrvh76xZ+vRRINv9P//6+bx8aZDeoRg3H6mdUfRcXRbA57Vw813LyZjB1B/JroEoZ9uG+LMvH9c2TavoqZPpXn43zMpQrIV9DaVYwC/89AGKCnJnid3vo7ElLgAYXKWpzLJM+QHAPa/bNyejvSMTNLgbm882Go3PWZG5ELcW8zvPLZw1e+5MertpB/jnH6a3jppvO6at4Oq9Vbz55sY5x6cWACgwE9myPJbFzmlF6NVlgWzR8HwZM7ttKPvxd59vz05LuvVli22plF0AMK1Wyl3t1bDMjBnk57ZMT5zsBJiRLYN0bZEbXJUV5+7XNlt2AUB/lC99+yynWgb55hPNqzBi6Rsa50zrEAd3li2pS/6VuulQDZ96/6tn1A8tZrkrM90asyudyrQsi9uurucVh2vm7dLv/sxe7p2bMUulHMbG44Ry7G7gOrKnkvqqIE+f7p63TCKRTHH8XC9lJQWUFhdkf4dspRWZS+H211vqPqX5SIGZyBI0TOuOXV1WlP2FPl/LDLelQH2mCPVcZs/HbMuLRTNmM1sFANkeajurl5ExK8rPjczHJxL8xO6ltiIwb/8ot2ZnzxL6tc1Wm8k2fu8n7dltWR5/sXNGU2BZmSczO1/cenX9ujyfZVk5t2Oazr12dKmB2Wi6VOBKV2UC/NIbDvLeu66a9/u1vtLNmM0NzCKxOA5QssStpDyWxZ2v2k3KcXjkqRYg3Tvt3358ifGJBGcuDTIWS3CjqeG110696dlKPcyWorS4gB3Vxbx8aTAv35guhQIzkSVw67sKfB5CQX92CmRwniazdqYz+rveaID0liGQLvz3eqxFV7TNN5XZ3juG12NRt4yNhoN52mT22TM9TCZS/6+9Ow+P864OPf59Z5VGMxrt+2rL/nmJY2dxFtshCQlrSFMIhUCf0EtvW+hCaQul9BIeSkOhpS00T0tLby8tXSAtpc0NEOAmBEKIs9lJHG/xL5J3ydYujTRaZkYzc/945x2N5NEy2makOZ/nyeNoNr2SXo3Oe37ndw77rqpJ+4esJrH0k+kyJky3LugZmsDA3NUWjcX5/vPnl3XM+S4ej/Ps8W5cDtuiM1hrzdrVuNilTOuCyr/MjNlC3C47Ff70OzODczSXnc8N26upKfNw8Fg3J84N8oV/e4n/fOo0X/7WqzxzzMxE791Wxa176rEn6tYqSvIrMIPpyQlHE9Md1hsJzIRYBCtjVu4vwDCMZI3Z7KXModEQPYnO6NuaSmio9PKy7uOJQxe52DtKY5UXp8M+5+cp8bpwOW3JZYhYPE5X3xg15Z45h5unk6tLmc8eu4wB7Lsqfebluq2V1FcULSkAKHA5khmQ67dV8a5bN1FVUsjPjl7ixdd6eOX1vuRsQrF4HV0BeocmuFZVJmsXc00yY7bInZnDwRDeQidOx+r/CayrKCIwFr5imdXaqZlJYGazmVmzaCzOX/77EYaDYZqqvXR0BXjxtV78XhdtDX5KfW7eemMT12ypSL4X5BPr/cOquVtvJDATYhEaq7xm1iqx1FZU4MBht12xlJkc8NxUimEYvP/OLRS67Tz8ZDtT0fiCmSDDMKgq8dAzPEE8Hqc/MEkoEs140HCuLWVGY2b9y+udAbY1l865U6y5xseDv3Jj8vucqfpKLwZw9/4W7DYb79jXwlQ0zlcfPcFf//cx/uG7J5bxVawvQ6MhHn/xApGp5W0AeUmbY4H2LdA/K5uWUmO23B2Zi1WXqE+dnTWzjtVbmNly6g07qpK1mO+5vY1P/9L13LDdDESu31qV7N11762b+ci9V2dcErAR1KdMTpgM58Z7YCbyL5QWYgm8hU4+ft+eZL2GYRiU+lxX7MrUszqjb2su5cFfuZF/+aHmSEd/spnsfKpLC+nsCzIyHqGr1xrzsvjCf8itjNlLupd//qFO/iG6/Zr6Vftc9795K4MjoWQgu2+XGUyMT0Z44nAn7V0BorHYnH24Mm0YnMt+9NJFfvD8BcYmp3jnGzYt+XWseYtN1asztHwlZBKYTYanmAhFKfEtv75sMaZ3Zo6xtXG61chcczIXYrfZ+Nh7d9M3NMH2xEDvX717B9dsqUx2xM93hmFwvariu8+e4+jpAW7YXp3tQ8qIBGZCLJKaNR+wxOumY9Yf+lMXruyMXuJ185F7dxGciFwxeiUdawNAz+A4nf0zx7wsVi7VmP345S6CExFuv7aem3ZUs6Vh9fpgVZV6knV6YBZMH7jaXDbt6h/jZ0cvc6l/PLmlPlUoHOUz//Qie9oquO+OLat2jGvFarPygxcusH9XzYzvSyaGRidx2I203elzRSaBmdVcdq0yZnPtzFzKUqalwl84ow2G3Wbjxh3rK/hYbXu3mYHZ4VO96y4wk6VMIZaoxOsmHoeRMfOPQXAiQs/gOG31/isyMoZhLCoog+l+XL1DEyk7MjPLmFlLmdnOmEVj5kDyuooi7n+zWtWgbCFWm5Izl8xdsoMjkzxx6GJy/uBzJ7rpHZrg+ZM9V0xeWI8u9Y9hGGYbhYd/1L7k1xkcDVHqc+f0eJuMArMVai67WNay/OydmdYOUl+GS5liceori6guM5czM50xmm0SmAmxRCWzWmZYb/iVy5xNZ/WJeuRnZ3i1Y4AClz3j7t3JjFmWa8wu9gYJRaK01fuzehww3abE6pz+yM/O8PCT7fzwhQvE4/HkuJuRsfC6H4YeCkfpD0yiGs1NKK+eHkh27s/EVDTGSDBMqS+3d/a5nHZcTtuixjIle5gts7nsYhW6HZQXFySHnFuWsitTLJ5hGGxrKiEciSWzx+uFBGZCLJG1AzCQWBqxxiilzspbiuYaH9VlHsYmI8SJc9OO6ozrngpzZCmzI9HDbUtD9gOz+soiXE4bZy6NmM04Xzdnn37v2XM8e7ybrv4xCt3mjlmrVnC9srIz9RXe5Jigk+cGM36d4WCIOFC2RkHMcvgKnYvKmCW7/q9AD7PFaqzyMjIWnjFqbTRZ/C+B2WqxLsbOzDPGKhdJjZkQS+S3ArOx0Ix/lxuYFbodfOHXblr2a0D2lzI7uszALBcyZnabjZZqH+1dAY609zMemqK6zEPP4Dj/+P3XAHjfHVv5x++/xqkLQ9y2ipsUVpu1A7AusZwDLGk8lfWctcouLUdRoZOewYUHV083l127r6mp2suRjn4u9o7ibzU3AI2Oh3E77bicc7fPEcuTWr6wmpuOVppkzIRYIn+R+cY+O2NWvMzAbCU47DZcTlvWlzLbOwP4PM7khoZsa60rJh6fniP4wbdto63eTzwOzdU+9u+qobjIhb44vK7rzKyMWV25B3+RC5thMDiy9MCsbB10j/cVOglFogu2BxkOrm2NGUzPb7yYMr8xkzmZYmnqyotwu+ycvby+xjNJYCbEEk1nzBKBWdBaysyN7ILH7chqxmxwZJKh0RBt9f6caUGxqc7M3HUPjlPqc9PW4Of+tygq/AXcc6A1WZcSCIbpGVo4+5KrLvebNXJ1FUXYbAYlPhdDo5mPprKCufWSMQMITkzxjSde54/+6UWisemi78sDY0SmYgwFQxjG8jPbmWhMtBqxRoXF43GCExFZxlxlNptBa42Py/1jWV89yIQEZkIskfXGbl2Bj6xQjdlK8RQ4s1pjZs0IbcuB+jJLa+10L67rtlZiMwwaq7x88df3sWdLBQAq0WvKmnm6HnX1B/F5nMmdwKU+N8PBMLFYZlnAwUQwtx4CM2t3Y2AsxMFjl7nQE+RUolbwxLlBPvUPL/DZrx+ie2DczCLa1u5iocJfQIHLzsVEYGZm9mKL3qktlq61rpg4cG4d1ZlJYCbEEnkLndhtxnTGLIeWMgEK3XYmQlNZW5Kz6su21GevRcZs5cUFyZ/PXGOfrH5163UDQCgSpX94kvqUFiulvgKisTgj45mNpEouZa6DwMzqs3b09ACTYXM50xrJ89MjlwCz9i44EVnTZUwgeQFweWCMcCSa3JEpGbPVtx43AEhgJsQSGYaB3+tKLmGOjIUpKnCsyfy9xfC4nURjccKR7PTw0ReGcdhtNNfkTsd4wzA4sKuWbU0lc2byass9FHucHD87uKSC+WzrHhgnDtSmBGZWYDX763n+RDcf+8pB+gPpl22HRkPYbQa+HLnYmI8V5Lxwsid520u6j9HxMEfa+6gt9/D79+2httzDVYuYwLHSmqp8xONmo+NkDzOpMVt1VvnCmUsSmAmRF/xFLgJjIeLxOIGxcM5ky4Bk64elLGdORWMcPT3AU0e6iC0h43bm0gidfUGuai3LmUDV8u7bNvOJ9187Z8NUwzB4095GghMRvvjNl9ddcJbckVl+ZWA2ODKzzuz5kz0MjYZ47kQP6Qytg+ayFiswuzwwjs0wuHFHNcGJCP/6/zRT0TgHdtWyvaWMP/nVm3jXMkZULVVjYhrIxd7gsrr+i8yU+tyUeF3J/oXrgbTLEGIZ/EVuzkZHGRmPEJyIZDzTcjV5Csw3/fHQ1II1QvF4nG8+0c6F3lHiwOX+McYSOzpLitzJ+qvFevKliwDccV1D5geeA95+UzOT4SiPPXeeLz78Cp/94N5109ZguodZylJmYlflYEqQGYvHOZ1Ybj58qpe797XMeJ1oLMZwMJQTrU4WI3VZsLXOxxuuruWFkz0c1n0YBtyU5SHs1s7MCz2jxGLm/0uN2drYVOfn5df7GByZXBc7jHPrUlaIdcbamdmZKOrNxYzZxCJaZgwHwzz5ciftnQFOdwVwOe3ctNOcL3coUaezWIGxMIdO9VJb7mFHS+nCT8hBhmHwrjds4uadNfQMjq+Lq+2+4QkeefoMzxy9DJg7Mi2laZYyuwfGk8H3xd4gPbOmHQSCYeLx9VH4DzMDs50tZWxtKklmpHa2lmX966ivKMJmGBw9PcC3ftKBzTBoyaFl/o3MumBeLxM9JGMmxDJYOzAv9I4mPs6dP2KZDDLvTmRZ3rGvmXe9YTNgZtFevzjMkY5+IlOxRS9JPn2ki6lonDde25AzbTKWwjAMtjT6ee5ENwMjmbeaWEuRqSh/8i+HGRmP4HLYuP3a+hnLZOlqzKzNGZvrijl9aYTDupe7bm5J3j+4jnqYwazArLUMu83GdaqKp17pYv9VtVk8MpPLaaem3MOl/jFshsGH7tlJU7UEZmuhxDez52Suk4yZEMtg7e66kGgc6V/DMS8LmV7KXHhMzeXElWRt2XSWxTAMrldVTISmFj3OZyoa46kjlyhw2dl3VXaXjlZCRSIoGQjkdmB26sIwI+MR9l1Vw0O/fQv3v1nNCIr9XheGAUMpAWZ7p7nr9N23bcZuM67IjK6nrv8wvSuzwGWnNbET7523tPLBt29j7/b0O3DX2pYGP4YBv/ZzO9g7x65gsfJKimbONc51C2bMlFI1wOeA3VrrvXM85j3AF4CPaq2/l3J7G/AXwJTW+t0pt7uB3wb+GKjUWgcTt9uAzwNBoBn4mtb6+SV+bUKsumTGrGd0xse5ILmUGZq/EzqYBdMANeWeGbdfv62Kxw9d5PCpXna3LVxn9uzxboZGQ9x5fUNyLNR6ZmWLBpbQNX81HTszwNd/cIrf/YXdNFR5ebXDnPt5YFctbteVtXB2m40Sr3tGjVlH1wiFbjtbGkvY3lLK8TOD9A6NU1WaGOGUCOLWQ6sMALfTzo6WUhqrvDjsZs7B53Fxy9V1WT6yae+7Ywt33dxMhT83JmHkixKf1XNy42TMDgCPAmnXJJRSrUAfcDHN3TcC309z+03AfwGzc+TvAYq11p8D/gD4F6XU+qi4FXnJn8iYWbULuVRj5nEnMmaTC2fMrKXMmrKZgdmmumJKfW5eae9nKjp/242paIzvPXsOh93gbTc2L/Goc0t5MjDLrYzZc4kA+AcvXCAej/NqxwCFbse8zXxLfW6GRkPE4mY/s57BcTbX+bEZBnuVmb05eKw7+fjBZMZsfSxlAnz8vmt47xu3ZPsw5uRy2iUoy4Lk+Lyx3LrAmsuCl7Ra628rpW6b5/6zwFml1GfS3PcNpdT/SHP7TwGUUrPvugt4PPGYQaXUJLATOLrQcVZWylq9WHtxh3ndYHWUaGkozZlzsTmRKRsMhhc8pp7hScr9BTQ1XFmsf8ueer7zszOc6R1j/zzZhydeOE9/YJK79reydVNmuzhzmc/jYngR38O1Eo/HaU/Uhx061ctdt2xiYGSSW/bUU1szd2BWU1HEmUsjuApd9PWagfhuVUVlpY+337KZ/3r6DD9+uZP3v30H3kInY4kmrVtay9dNnZkQ6ZSVFWEzYCwUzZnf4/nk2lpDFZA6bXQkcduC+vrW15BSsTFEZ2WRYuFIzpyLPpeNCn8Bzx69zC/cOkSBK/2v+2R4iv7hCXa0lKY99mvbynns4Fm+/PDL2KKxtFmZqWiMhx8/hcNucPvu2pz5HqyEMp+bywNj9PaO5MRmhp6hcQYCk7iddkKRKH/5jZcA2Nbon/f77kkscXacG+Dl18x6stqSguRz3ry3kW8/dZr/+OFrvOWGJjouDGEzDCITYfoWUacoRC7zeVz0DY3nzHvTfAFirhX/9wKpR1ucuE2InOSw25K7wQwjt/oS2QyDfVfVEIpEeUn3zfm4nkGz63tq4X+qpmofH/q5nUQiMb70rSNpW0ccae+nb3iSW66u23DZlbJiN+GpWLJbe7ZZo6Lesa+ZApedoVFzKPeuBbrZlyWWJPuHJznS0Y/NMNhUV5y8/43X1uMtdPL4oYs89O1X6Rma4Oad1Ws6U1KI1eL3uhgOhrI2oi4TSwrMlFJlSqnihR+ZsceAm63PgVmDdmIVPo8QK8Yq+Pd51nYw8mJYOyMPHrs852MuW/Vlswr/U12/rYoP3bOTyXCUR585e8X9r7Sbgd8bdudOofVKserMZnfNzxZruPrutgr27zLbQLTV+xecu1hWbNbZPHrwLJcHxtm/q2ZGFrXA5eAtNzQyHpri1IVhrt1ayS+9bdsqfRVCrK0Sr5twJJaco5rLFgzMlFK3AvcDtUqpB5RShcAngd9I3G8opR7A3EX5XqXUW1Keew9wN7BNKfWJlNtbEs8B+IRSyvrt/xYwmqhX+3PgA1rr3P8uirxmtcgozqFsmaWq1MPWBj+nLgzPOQ/R2pFZO09gBrB3WxXFRa5kIGeJxeIcPT1AiddFU2LszEZS7s+dlhnxeBx9cRhvoZO6iiLetLeREq+LW/csHBBbbS+6+sbwuB3ce9vmKx7zxmsbaKj0cvPOaj58z87k7kYh1rsSr7UzM/c3ACym+P+nwE9n3fyJlPvjmO00PpfmuY9i7uicffu5dM/RWscwd2MKsW5YGbNc6mGWat+uWl7vDPDc8W7u3t96xf3JHmblC4+TqiktpL0rMKPh7OlLAcYmp7h1T11O1GCttPIcapnRF5hkcCTEdVsrsRkGVSWFfOm3Dizquan9yN5166a0FxKFbgef/eW9G/LnKPKb1XNyOBhe1HtdNsnlkBDLZLXMyKUeZqn2bqvCbjNHwaTTPTCG22VPXlHOp7rMQzxujv+xvNphvu7uzRtnJ2aqXMqYWcuYqqkk4+eWeN143A6aq33ctqd+zsdJUCY2Iut9OrARMmZCiPmVWBmzHA3MCt0Oyv0FM4IpSywWp3twgobKokX9Qbb6nPUMjidnMb7a0Y/TYWP7Op2LuZCyHKoxswr/tzVl/r122G380S/vxeN25lwtpBCrzXqfXg9NZiVjJsQyWX+4c3l0TaW/gJHxCKFZha/9I5NMRWOLTu1XJwKz7iFz+bNveIKu/jG2N5fidm7MXtDFHicOu43+HAjM2juH8bgd1FUubSmmwl+Ip0Cux0X+seZlrnSN2Uu6b8Uv2iQwE2KZ9myp4BfftJUDV2d/UPJcKkrMbuOzNwD0JurLqssW1408NWMGJJdHFzOuab0yDIPyYnfWM2aBYIi+4UnaGsxu/UKIxbNWNAJjK5cx6x+e4CuPHOOv/vMo0dj8k1EyIYGZEMvksNu447qGORu45oKKRJ1U36w6KSutX+pdXLavsqQQw4DuxE7OY2es+rL5e2itd+X+AkbHI4QiC28SD0eiPPjPh3jicLopdUvXkej2v7l+7u7+Qoj0iotcGMDw6PwZs3g8vuismrVy0NkX5KlXLi33EJMkMBMiD1QmMmaz68ys2XH+RQZmToc5TaB7aIKpaAx9YZjacs+Gayo7WyZ1Zl39Y5y9PMp3njm7qEBusazAbIsEZkJkzGG34fM4GZ4nYxYYC/M3/32M3/ubgzx/snvOx1n6h6ffDx55+gwjK5SNk8BMiDxgDU5OfSMBCCQyZplsXKgu8zAyFub4mUFCkSg7WspW7kBzVEUGw8ytgfZjk1O8cLJnxY6hozOAzTBorVuN3t5CbHx+rzttNqxncJzvPnuOT/+fF3ilvR+Aw6fmnpZi6UuUhuzdVsV4aIr/fvr0ihynBGZC5IHKksQ4nlk1ZtbV42JaZVhqSs06sx+/3AnAztaNH5hZGbP+RbTMsOrvAH50uHNFRsCEI1HOdY/SVO3dsJsshFhtJV43oXCUyfBU8rZ/f7KdP/zfz/PI02cIT0V5/51bqCwp4LXzgwvWjVkXuu+5vY3yYve8o+8yIYGZEHnAW+jE7bLTd0XGLJTxjE9rZ+bxs4PYbQaqMfOeWutNfWIX5Lk0c0JnszJmm+uK6ewL8vrF4WV//nPdo0Rj8bQD5IUQi2M1AbdWCqaiMZ56pYsSr4v/edd2vvSb+7nz+kZ2tpQxEYpy9vL8A8/7AxM47DZKi900VvkYm5wiuAIzdSUwEyIPGIZBpb+A/sDEjAxOYCxMcYYzPq2dmWAGH4Xu3N30sFKaqr0Uuu2curBwkNU9OI7TYePdiZFHT77UuezPb9WXtUl9mRBLNnss07nLo4SnYly7tZL9u2rxFJjzZq3yjJNnB+d9vb7hScr9BdgMI/m+2J2SMV8qCcyEyBMV/kImw1HGJqfT+IFgOONRUqmtNfJhGRPAbrOxpaGE3qEJhubZ1RWPx+kZnKC6tJCtjSXUlHk4emaAWGx5y5kdnYnC/4aNn50UYrWkjmUCOJWYpDG7YfP2llIMA46fmzswmwiZ2bHKxI53632xRwIzIcRiVSTqzKydmZPhKUKRKP6izBrjlhUXJOdk7siTwAymxyBZY5HSGQ6GCUWi1JR5MAyDzXXFhCOx5DzSpYjF43R0BSgvdud0E2Mhcp0VmFnBk06UGWydVY5RVOCktbaYM10jTISmSMeqN7V6RM7OmEWmYrz4Ws+S+ptJYCZEnpjdMiO5IzPDjJnNMGiq9uIvctFakz87BK2raj1PzVhPsmGv+SbdXOMD4EL3/LUq87nYEyQ4EWFb88YceSXEWlFNJbicNp45dpnIVJSOzgB1FUUUp9mVvqOljFg8nsyqzdafeB+dzpjNDMyefvUSX330BE8cyryUQQIzIfJEpdUyI3GlZ9VZZLIj0/Kb79zFpz5wXV7NXGyq9lLgmr/OzGo4WTMrMDu3jMDsRGI5ZWcetCURYjUVFTi5eWcN/YFJvnPwHKFIdM7NS1clVgNOzFFn1jcrY+YvcuF22a/Ixv345c6MSxkkMBMiT1hLmdaVnjWaJNOlTDCXBKzeaPnCqjPrGRyfszP47IxZU5UPw4Dz3Qvv5pyL9YchH/rFCbHa7ri2AYDvP38emC5RmG1TXTGFbjtHTw+kbXljvY9aU1UMw6Cm1EPP0IRZftBpBmb9gUlePd2f0TFKYCZEnpg9lmkpzWXz3XSdWfqsmTWqysqYuV12asuLON8bJLaEfmahSJT2zmGaqrxpl1uEEJlpqPKiGkuwfh3nypg57DZ2tpbTH5jk0sCVNaLWyoNVIgLmBoDIVIz2i8MMB8PUV5htdjLdmS2BmRB5osDlwOdxXpkxW8JSZr6yArOjKVfAT73Sxef/9SUGRybpHpqgqMCBt9CZvL+52kcoHF3Sbq32i8NMReN5tclCiNV2x3Vm1qy23DPvOLo9beYM4KMdV2a8+gITFLrtFBVMtwuyLsieOXYZgANX16IaSzh5bohL/WOLPj4JzITII5UlhfQHJpmKxggEM5uTKaClxkdtuYfnTvTwSnsfr18c5t8ef52OrgBfffQE/cMTM/q8Wc8BOL+EOrPjZ6W+TIiVds3WCm7aWc1bb2ya93G7NpVjAEdmBWbxeJy+4Qkq/IUYxnSdrVXCYI1zamvwJ4PAp19d/JBzCcyEyCPNNT6isTjnukdTaswkY7ZYdpuND99zFU6HjX987DX+/jsniGN25O/oChCNxa8IzJazAeDkuUGcDhtbpOO/ECvGbrPxa3fv5Jar6+Z9nM/jYnO9+bsdnIjw2vkh/v3Jdjr7xghHYsnyEIv1ux+KRHE6bDRX+9jdVoHTYeO189O7O0+dn7vlDkiemCSZAAAMhUlEQVRgJkReSbZ8uDDEcDBModsusxcz1Fjl5X13bmFscoqh0RA/f8smfvcXdlOVqDWpnhWYNVV7Mcg8YxYIhujsG2Nrgx+X/IyEyIrdbeXE4/Ctn3Tw5W+9yuOHLvLgPx8GZtaXAVSXTv/ut9b4cNhtOB02czxbbzA5ruk/ftwx7+eUwEyIPGI1Ujx1YZjAWGhJOzIF3Lq7jrtubub2a+q566ZmCt0OfuOdV7G9uZRrtlbOeGyBy0FNuYfzPaMZbQA4c8ncyTm7+aUQYu3s3lwBwDNHL2MY8JYbGrElIqfZgZmnwJHcpNOWMqVjW1Mpccya0aHREOd75r9I2/hD7oQQSf4iF7XlHto7h4lEYtSVF2X7kNYlwzC499bNM25rqvbx+++7Ju3jW2uLuTzQzbHTA+xuq1jU57CWPltq86eJrxC5pr6yiKqSQgZHQ/z2vVezs7WM26+p5+Cxbm7YXnXF42tKCxkZC8+Ya2ttGjp1YZiR8fCCn1MCMyHyjGoq5alXugDZkblW3npDE8+f6OHhJ9vZ0VKWHGk1H+uqurnat9qHJ4SYg2EY/N59e5iailGXaH9RVerhnW/YlPbx21vK6B4cZ2vjdGC2qa4Yh92GvjiUnLwyH1nKFCLPbEtpqChLmWujocrLG6+rp3dogscPXVjw8fG4uUGj1OeW/mVCZFlVSWEyKFvIPQda+dJHDuApmG6Z43TY2VxXzMWeICfODVJb7pnnFSQwEyLvpDZUXMo4JrE0P3+glWKPk+8+e47Bkcl5HzscDDMyFk622hBCrB8248pRdaqphDjmcPOFyhkkMBMiz/i97uS2blnKXDueAif33LKJcCTGi6/1zvtYawdnswRmQmwIKrEjHmCPBGZCiNms5cwSaS67pnZtMhvFnu4KzPu4c4nZmpIxE2Jj2FxXjMNuUFTgYHP9/Bt6pPhfiDz0jn0tlPjccw7wFaujvLiAUp+b9q4A8Xh8RtfwVMmMmRT+C7EhuJx2fuUdO3A57dht8+fEJGMmRB4qKy7g5/a3LvgGIVaWYRhsrvczMhaed3fWuZ5RSrwuGZclxAZyw/bqBZcxYREZM6VUDfA5YLfWeu8cj3kP8AXgo1rr76Xc3gb8BTCltX53yu0twKeBDqAF+JjWOqiUug34K2A48dDHtNZ/vuBXIYQQ68SWej+HT/XS0RWgqvTK3VnDwRCBYHhRb+BCiI1nMZfLB4BHgbQ5d6VUK9AHXExz943A99Pc/lXg77XWXwCOA3+Qct/vaK1vS/wnQZkQYkNpS8y97OhMX2cmhf9C5LcFAzOt9beBOecHaK3Paq1/Msd93wBmtLlVSjmB24FDiZsOAnelPOR+pdTHlVJ/rJRqXOj4hBBiPWms8uJy2uiYYwPApYExABoqvWt5WEKIHJGN4v8KYEJrbQ2NGwGsuQYngQe11ueUUjuBJ5RSO7TWsYVetLJSri6FEOuDairj+Jl+Cr0FeAudM+6biJhvd20tZfK+JkQeykZg1g8UKqWMRHBWDPQCaK2TzX201ieUUiVAI3B+oRft65t/KKgQQuSK5uoijp3u58WjXezaVD7jvku9QQCMqai8rwmxQc130bWkLVlKqTKl1JIm62qtI8BPAGsjwX7gscTrflIpVWZ9DsAF9Czl8wghRK6yBhy3dw5fcd/Q6CQOu4HX47ziPiHExrdgYKaUuhW4H6hVSj2glCoEPgn8RuJ+Qyn1ANAMvFcp9ZaU594D3A1sU0p9IuVlPwx8OPG8XcCfJW4/BzyklPpD4CHgfq31/LNLhBBindnSUILDbuPwqT7i8fiM+wZHQ5R43WnHugghNj5j9pvCOhWXlL8QYj356qPHefG1Xj71gevYXGdm0KaiMT7050+xpbGET/7itVk+QiHEaqms9M155SXdJYUQIgv2XVULwMFj3cnbhoMh4kCZTxrLCpGvJDATQogs2Nlait/r4sWTPUSmogAMjYYAKJXATIi8JYGZEEJkgd1m4+adNYyHpjjSMQBIYCaEkMBMCCGyZv9VNQAcPHYZgMERMzArKy7I2jEJIbJLAjMhhMiS+kovteUe9IVhYrG4ZMyEEBKYCSFENm2u8xOKRLnUP8bgqNkdSIr/hchfEpgJIUQWbaoze3WfuTzC0GgIu83AV+TK8lEJIbJFAjMhhMii1tpEYHbJDMxKfdJcVoh8JoGZEEJkUX1lES6HjdNdAYaDIakvEyLPSWAmhBBZ5LDbaKrx0dU/Rjwuhf9C5DsJzIQQIss2JZYzQVplCJHvJDATQogsszYAgGTMhMh3EpgJIUSWtaZmzCQwEyKvSWAmhBBZVuEvwOdxAlDqk6VMIfKZBGZCCJFlhmHQVu/HMMwgTQiRv4x4PJ7tY1gJ8b6+0WwfgxBCLNngyCTdg+PsaCnL9qEIIVZZZaVvzmaFjrU8ECGEEOmVFRfIjkwhhCxlCiGEEELkCgnMhBBCCCFyhARmQgghhBA5QgIzIYQQQogcIYGZEEIIIUSOkMBMCCGEECJHSGAmhBBCCJEjJDATQgghhMgREpgJIYQQQuQICcyEEEIIIXKEBGZCCCGEEDlCAjMhhBBCiBxhxOPxbB+DEEIIIYRAMmZCCCGEEDlDAjMhhBBCiBwhgZkQQgghRI6QwEwIIYQQIkc4sn0AG4FS6k7gXUAvENdaf1YpdQ3wUeAksBP4tNb6Qprn7gF+EzgLVAEf11pPKaUKgL8AuoAtwJ9qrV9fky9IrAilVA3wOWC31npv4rYy4E+BM5g/1/+lte5J81w5LzawOc4NG/CrwIPAG7XWx+d4rpwbG9Qc58WXgXEgCOwGfkdr3Z3muXJebBCSMVsmpZQH+Crwu1rrPwKuVkrdAfwT8JDW+ovAt4G/TvNcA/g3zKDt80AU+KXE3b8DXNBafwH4MvC11f5axIo7ADwKGCm3fR74kdb6T4H/i/mGOYOcF3kh3bmxG3gB849wWnJubHjpzosxrfWnEj/XV4BPzX6SnBcbiwRmy3czcF5rHUp8fBC4C/PKxMqQnQHuSPPcTUBhytWP9VwS/z4HoLU+BuxWShWv/OGL1aK1/jYwOuvm5M+VmT/vVHJebHDpzg2t9Sta6yMLPFXOjQ1sjvPigZQPbZiZs9nkvNhAZClz+aqY+Ys0krjtGeAm4DHgBsCjlHIAFcBLQMs8z53vdUdW/CsQayn15zoClMp5IeaTWN6ScyPPKaVKgDcD9yY+lvNig5KM2fL1Ar6Uj4sTt90P3KyU+ihmWvqS1noqcUVzg9Y6Ms9z53tdsb6l/lyLgSE5L8R85NwQSik/8LfAL2utB0HOi41MArPlew5oVkq5Ex/vx8yS1WqtH9BaPwR0Av+a8hxn4t8zwETiyif1uST+vRlAKbULeFVrLVc461/y58rMnzfIeSHmJudGnlJKVQBfAX5fa31WKXVvyt1yXmxAMpJpBSil3gS8G+gDIoldmQ9grvufBPzA57XWE0qpWuAQ0Kq1jiR20nwEOA+UMb2TphCzMPwy0JZ4vuykWUeUUrcCHwDeCvwd8JdAIfBnmD/vzcAntdY9cl7klznOjQLMXXUfw7yQ+6bW+nk5N/LHHOfFQcyyo8HEw0a11nfLebFxSWAmhBBCCJEjZClTCCGEECJHSGAmhBBCCJEjJDATQgghhMgREpgJIYQQQuQICcyEEEIIIXKEBGZCiLyklGpQSn1HKfXUAo+7baHHCCHESpHATAiRl7TWncCXsn0cQgiRSvqYCSHyilLqI5gNoU9hzgvcC9wJPAJozEavA1rrzyilyoCvYc67fQR4Vmv9TaXUe4A3AQNAPWZX9u4rPpkQQmRIMmZCiLyRGEnzKeCtWusPAaGUu7+utf641vq3gOuVUjcm5hI+BLRrrX8rEZQp4DPAh7TWnwR+Cnxxjb8UIcQG5cj2AQghxBq6HTistZ5IfPwz4AAQBZqUUl8DRoFWYCvwQprXeBNmVu1vzRgNH+BO8zghhMiYBGZCiHxiAOnqN+7DnFF4vdY6qpT6OmCf5zVe11p/2LpBKeVd6QMVQuQnWcoUQuSTnwB7E4OdwcyWAZQDAa11NPFxU8pzJkkEaUqpDwJPYC51+hK3XQN8ebUPXAiRH6T4XwiRV1KK/48BMeBezBqxu4AAcB64A7Ow/9eBLuBx4HXgrNb6QaXUfZhZttNACfAJrfXAGn8pQogNSAIzIYQQQogcIUuZQgghhBA5QgIzIYQQQogcIYGZEEIIIUSOkMBMCCGEECJHSGAmhBBCCJEjJDATQgghhMgREpgJIYQQQuSI/w9OC1ee06jfwAAAAABJRU5ErkJggg==\n", "text/plain": ["
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"], "text/plain": [" bidopen bidclose bidhigh bidlow\n", "date \n", "2020-05-21 21:00:00 107.502 107.598 107.843 107.503\n", "2020-05-22 21:00:00 107.598 107.595 107.757 107.316\n", "2020-05-24 21:00:00 107.595 107.593 107.593 107.545\n", "2020-05-25 21:00:00 107.593 107.667 107.776 107.545\n", "2020-05-26 21:00:00 107.667 107.501 107.917 107.395\n", "2020-05-27 21:00:00 107.501 107.706 107.941 107.359\n", "2020-05-28 21:00:00 107.706 107.591 107.897 107.564\n", "2020-05-29 21:00:00 107.591 107.767 107.891 107.071\n", "2020-05-31 21:00:00 107.628 107.656 107.682 107.628\n", "2020-06-01 21:00:00 107.656 107.682 107.850 107.373"]}, "execution_count": 33, "metadata": {}, "output_type": "execute_result"}], "source": ["candles[candles.columns[:4]]"]}, {"cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | bidopen | \n", "bidclose | \n", "bidhigh | \n", "bidlow | \n", "
|---|---|---|---|---|
| date | \n", "\n", " | \n", " | \n", " | \n", " |
| 2020-05-21 21:00:00 | \n", "107.502 | \n", "107.598 | \n", "107.843 | \n", "107.503 | \n", "
| 2020-05-22 21:00:00 | \n", "107.598 | \n", "107.595 | \n", "107.757 | \n", "107.316 | \n", "
| 2020-05-24 21:00:00 | \n", "107.595 | \n", "107.593 | \n", "107.593 | \n", "107.545 | \n", "
| 2020-05-25 21:00:00 | \n", "107.593 | \n", "107.667 | \n", "107.776 | \n", "107.545 | \n", "
| 2020-05-26 21:00:00 | \n", "107.667 | \n", "107.501 | \n", "107.917 | \n", "107.395 | \n", "
| 2020-05-27 21:00:00 | \n", "107.501 | \n", "107.706 | \n", "107.941 | \n", "107.359 | \n", "
| 2020-05-28 21:00:00 | \n", "107.706 | \n", "107.591 | \n", "107.897 | \n", "107.564 | \n", "
| 2020-05-29 21:00:00 | \n", "107.591 | \n", "107.767 | \n", "107.891 | \n", "107.071 | \n", "
| 2020-05-31 21:00:00 | \n", "107.628 | \n", "107.656 | \n", "107.682 | \n", "107.628 | \n", "
| 2020-06-01 21:00:00 | \n", "107.656 | \n", "107.682 | \n", "107.850 | \n", "107.373 | \n", "
\n", "\n", "\n", " \n", "
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"], "text/plain": [" askopen askclose askhigh asklow tickqty\n", "date \n", "2020-05-21 21:00:00 107.589 107.613 107.854 107.528 189628\n", "2020-05-22 21:00:00 107.613 107.661 107.770 107.329 168381\n", "2020-05-24 21:00:00 107.661 107.660 107.667 107.635 6\n", "2020-05-25 21:00:00 107.660 107.753 107.789 107.576 112616\n", "2020-05-26 21:00:00 107.753 107.566 107.930 107.407 191402\n", "2020-05-27 21:00:00 107.566 107.740 107.955 107.373 274980\n", "2020-05-28 21:00:00 107.740 107.676 107.909 107.576 251491\n", "2020-05-29 21:00:00 107.676 107.843 107.903 107.086 344564\n", "2020-05-31 21:00:00 107.701 107.703 107.748 107.653 160\n", "2020-06-01 21:00:00 107.703 107.693 107.863 107.385 154702"]}, "execution_count": 34, "metadata": {}, "output_type": "execute_result"}], "source": ["candles[candles.columns[4:]]"]}, {"cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": ["start = dt.datetime(2019, 1, 1)\n", "end = dt.datetime(2020, 6, 1)"]}, {"cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": ["candles = api.get_candles('EUR/GBP', period='D1',\n", " start=start, stop=end)"]}, {"cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["| \n", " | askopen | \n", "askclose | \n", "askhigh | \n", "asklow | \n", "tickqty | \n", "
|---|---|---|---|---|---|
| date | \n", "\n", " | \n", " | \n", " | \n", " | \n", " |
| 2020-05-21 21:00:00 | \n", "107.589 | \n", "107.613 | \n", "107.854 | \n", "107.528 | \n", "189628 | \n", "
| 2020-05-22 21:00:00 | \n", "107.613 | \n", "107.661 | \n", "107.770 | \n", "107.329 | \n", "168381 | \n", "
| 2020-05-24 21:00:00 | \n", "107.661 | \n", "107.660 | \n", "107.667 | \n", "107.635 | \n", "6 | \n", "
| 2020-05-25 21:00:00 | \n", "107.660 | \n", "107.753 | \n", "107.789 | \n", "107.576 | \n", "112616 | \n", "
| 2020-05-26 21:00:00 | \n", "107.753 | \n", "107.566 | \n", "107.930 | \n", "107.407 | \n", "191402 | \n", "
| 2020-05-27 21:00:00 | \n", "107.566 | \n", "107.740 | \n", "107.955 | \n", "107.373 | \n", "274980 | \n", "
| 2020-05-28 21:00:00 | \n", "107.740 | \n", "107.676 | \n", "107.909 | \n", "107.576 | \n", "251491 | \n", "
| 2020-05-29 21:00:00 | \n", "107.676 | \n", "107.843 | \n", "107.903 | \n", "107.086 | \n", "344564 | \n", "
| 2020-05-31 21:00:00 | \n", "107.701 | \n", "107.703 | \n", "107.748 | \n", "107.653 | \n", "160 | \n", "
| 2020-06-01 21:00:00 | \n", "107.703 | \n", "107.693 | \n", "107.863 | \n", "107.385 | \n", "154702 | \n", "
"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["candles['askclose'].plot(figsize=(10, 6))\n", "plt.savefig('../../images/ch09/fxcm_plot_03.png');"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Streaming Data"]}, {"cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": ["def output(data, dataframe):\n", " print('%3d | %s | %s | %6.5f, %6.5f' \n", " % (len(dataframe), data['Symbol'],\n", " pd.to_datetime(int(data['Updated']), unit='ms'), \n", " data['Rates'][0], data['Rates'][1]))"]}, {"cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": [" 2 | EUR/USD | 2020-06-01 12:49:52.904000 | 1.11049, 1.11062\n", " 3 | EUR/USD | 2020-06-01 12:49:54.481000 | 1.11055, 1.11066\n", " 4 | EUR/USD | 2020-06-01 12:49:54.592000 | 1.11055, 1.11068\n", " 5 | EUR/USD | 2020-06-01 12:49:57.317000 | 1.11057, 1.11068\n", " 6 | EUR/USD | 2020-06-01 12:49:58.104000 | 1.11056, 1.11068\n", " 7 | EUR/USD | 2020-06-01 12:49:58.827000 | 1.11055, 1.11068\n"]}], "source": ["api.subscribe_market_data('EUR/USD', (output,))"]}, {"cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [{"data": {"text/plain": ["Bid 1.11055\n", "Ask 1.11068\n", "High 1.11548\n", "Low 1.10999\n", "Name: 2020-06-01 12:49:58.827000, dtype: float64"]}, "execution_count": 42, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_last_price('EUR/USD')"]}, {"cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [], "source": ["api.unsubscribe_market_data('EUR/USD')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Placing Orders"]}, {"cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [{"data": {"text/html": ["
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch10/10_pyalgo.ipynb b/ch10/10_pyalgo.ipynb new file mode 100644 index 0000000..addd85e --- /dev/null +++ b/ch10/10_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading\n", "\n", "**Chapter 12 — Automating Trading Operations**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Risk Disclaimer"]}, {"cell_type": "markdown", "metadata": {}, "source": ["\n", "Trading forex/CFDs on margin carries a high level of risk and may not be suitable for all investors as you could sustain losses in excess of deposits. Leverage can work against you. Due to the certain restrictions imposed by the local law and regulation, German resident retail client(s) could sustain a total loss of deposited funds but are not subject to subsequent payment obligations beyond the deposited funds. Be aware and fully understand all risks associated with the market and trading. Prior to trading any products, carefully consider your financial situation and experience level. Any opinions, news, research, analyses, prices, or other information is provided as general market commentary, and does not constitute investment advice. Oanda & TPQ will not accept liability for any loss or damage, including without limitation to, any loss of profit, which may arise directly or indirectly from use of or reliance on such information.\n", ""]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Author Disclaimer"]}, {"cell_type": "markdown", "metadata": {}, "source": ["\n", "The author is neither an employee, agent nor representative of Oanda and is therefore acting independently. The opinions given are their own, constitute general market commentary, and do not constitute the opinion or advice of Oanda or any form of personal or investment advice. Oanda assumes no responsibility for any loss or damage, including but not limited to, any loss or gain arising out of the direct or indirect use of this or any other content. Trading forex/CFDs on margin carries a high level of risk and may not be suitable for all investors as you could sustain losses in excess of deposits.\n", ""]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["import math\n", "import time\n", "import numpy as np\n", "import pandas as pd\n", "import datetime as dt\n", "from pylab import plt, mpl"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["np.random.seed(1000)\n", "plt.style.use('seaborn')\n", "mpl.rcParams['font.family'] = 'serif'"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Capital Management"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Kelly Criterion in a Binomial Setting"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": ["p = 0.55"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": ["f = p - (1 - p)"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.10000000000000009"]}, "execution_count": 5, "metadata": {}, "output_type": "execute_result"}], "source": ["f"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": ["I = 50"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": ["n = 100"]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": ["def run_simulation(f):\n", " c = np.zeros((n, I))\n", " c[0] = 100\n", " for i in range(I):\n", " for t in range(1, n):\n", " o = np.random.binomial(1, p)\n", " if o > 0:\n", " c[t, i] = (1 + f) * c[t - 1, i]\n", " else:\n", " c[t, i] = (1 - f) * c[t - 1, i]\n", " return c"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": ["c_1 = run_simulation(f)"]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[100. , 100. , 100. , ..., 100. , 100. , 100. ],\n", " [ 90. , 110. , 90. , ..., 110. , 90. , 110. ],\n", " [ 99. , 121. , 99. , ..., 121. , 81. , 121. ],\n", " ...,\n", " [226.35, 338.13, 413.27, ..., 123.97, 123.97, 123.97],\n", " [248.99, 371.94, 454.6 , ..., 136.37, 136.37, 136.37],\n", " [273.89, 409.14, 409.14, ..., 122.73, 150.01, 122.73]])"]}, "execution_count": 10, "metadata": {}, "output_type": "execute_result"}], "source": ["c_1.round(2)"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", 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"], "text/plain": ["Empty DataFrame\n", "Columns: []\n", "Index: []"]}, "execution_count": 44, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_open_positions()"]}, {"cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": ["order = api.create_market_buy_order('EUR/USD', 100)"]}, {"cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [], "source": ["sel = ['tradeId', 'amountK', 'currency',\n", " 'grossPL', 'isBuy']"]}, {"cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " |
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"], "text/plain": [" tradeId amountK currency grossPL isBuy\n", "0 167805715 100 EUR/USD -11.70591 True"]}, "execution_count": 47, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_open_positions()[sel]"]}, {"cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": ["order = api.create_market_buy_order('EUR/GBP', 50)"]}, {"cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | tradeId | \n", "amountK | \n", "currency | \n", "grossPL | \n", "isBuy | \n", "
|---|---|---|---|---|---|
| 0 | \n", "167805715 | \n", "100 | \n", "EUR/USD | \n", "-11.70591 | \n", "True | \n", "
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"], "text/plain": [" tradeId amountK currency grossPL isBuy\n", "0 167805715 100 EUR/USD -10.80536 True\n", "1 167805717 50 EUR/GBP -10.60469 True"]}, "execution_count": 49, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_open_positions()[sel]"]}, {"cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [], "source": ["order = api.create_market_sell_order('EUR/USD', 25)"]}, {"cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [], "source": ["order = api.create_market_buy_order('EUR/GBP', 50)"]}, {"cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | tradeId | \n", "amountK | \n", "currency | \n", "grossPL | \n", "isBuy | \n", "
|---|---|---|---|---|---|
| 0 | \n", "167805715 | \n", "100 | \n", "EUR/USD | \n", "-10.80536 | \n", "True | \n", "
| 1 | \n", "167805717 | \n", "50 | \n", "EUR/GBP | \n", "-10.60469 | \n", "True | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" tradeId amountK currency grossPL isBuy\n", "0 167805715 100 EUR/USD -13.50706 True\n", "1 167805717 50 EUR/GBP -7.25536 True\n", "2 167805718 25 EUR/USD -1.12547 False\n", "3 167805719 50 EUR/GBP -11.72019 True"]}, "execution_count": 52, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_open_positions()[sel]"]}, {"cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [], "source": ["api.close_all_for_symbol('EUR/GBP')"]}, {"cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | tradeId | \n", "amountK | \n", "currency | \n", "grossPL | \n", "isBuy | \n", "
|---|---|---|---|---|---|
| 0 | \n", "167805715 | \n", "100 | \n", "EUR/USD | \n", "-13.50706 | \n", "True | \n", "
| 1 | \n", "167805717 | \n", "50 | \n", "EUR/GBP | \n", "-7.25536 | \n", "True | \n", "
| 2 | \n", "167805718 | \n", "25 | \n", "EUR/USD | \n", "-1.12547 | \n", "False | \n", "
| 3 | \n", "167805719 | \n", "50 | \n", "EUR/GBP | \n", "-11.72019 | \n", "True | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" tradeId amountK currency grossPL isBuy\n", "0 167805715 100 EUR/USD -17.10956 True\n", "1 167805718 25 EUR/USD -0.22510 False"]}, "execution_count": 54, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_open_positions()[sel]"]}, {"cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [], "source": ["api.close_all()"]}, {"cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | tradeId | \n", "amountK | \n", "currency | \n", "grossPL | \n", "isBuy | \n", "
|---|---|---|---|---|---|
| 0 | \n", "167805715 | \n", "100 | \n", "EUR/USD | \n", "-17.10956 | \n", "True | \n", "
| 1 | \n", "167805718 | \n", "25 | \n", "EUR/USD | \n", "-0.22510 | \n", "False | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": ["Empty DataFrame\n", "Columns: []\n", "Index: []"]}, "execution_count": 56, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_open_positions()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Account Information"]}, {"cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [{"data": {"text/plain": ["1224934"]}, "execution_count": 57, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_default_account()"]}, {"cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " |
|---|
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" 0\n", "t 6\n", "ratePrecision 0\n", "accountId 1224934\n", "balance 49924.1\n", "usdMr 0\n", "mc N\n", "mcDate \n", "accountName 01224934\n", "usdMr3 0\n", "hedging Y\n", "usableMargin3 49924.1\n", "usableMarginPerc 100\n", "usableMargin3Perc 100\n", "equity 49924.1\n", "usableMargin 49924.1\n", "bus 1000\n", "dayPL -75.95\n", "grossPL 0"]}, "execution_count": 58, "metadata": {}, "output_type": "execute_result"}], "source": ["api.get_accounts().T"]}, {"cell_type": "markdown", "metadata": {}, "source": ["| \n", " | 0 | \n", "
|---|---|
| t | \n", "6 | \n", "
| ratePrecision | \n", "0 | \n", "
| accountId | \n", "1224934 | \n", "
| balance | \n", "49924.1 | \n", "
| usdMr | \n", "0 | \n", "
| mc | \n", "N | \n", "
| mcDate | \n", "\n", " |
| accountName | \n", "01224934 | \n", "
| usdMr3 | \n", "0 | \n", "
| hedging | \n", "Y | \n", "
| usableMargin3 | \n", "49924.1 | \n", "
| usableMarginPerc | \n", "100 | \n", "
| usableMargin3Perc | \n", "100 | \n", "
| equity | \n", "49924.1 | \n", "
| usableMargin | \n", "49924.1 | \n", "
| bus | \n", "1000 | \n", "
| dayPL | \n", "-75.95 | \n", "
| grossPL | \n", "0 | \n", "
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch10/10_pyalgo.ipynb b/ch10/10_pyalgo.ipynb new file mode 100644 index 0000000..addd85e --- /dev/null +++ b/ch10/10_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading\n", "\n", "**Chapter 12 — Automating Trading Operations**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Risk Disclaimer"]}, {"cell_type": "markdown", "metadata": {}, "source": ["\n", "Trading forex/CFDs on margin carries a high level of risk and may not be suitable for all investors as you could sustain losses in excess of deposits. Leverage can work against you. Due to the certain restrictions imposed by the local law and regulation, German resident retail client(s) could sustain a total loss of deposited funds but are not subject to subsequent payment obligations beyond the deposited funds. Be aware and fully understand all risks associated with the market and trading. Prior to trading any products, carefully consider your financial situation and experience level. Any opinions, news, research, analyses, prices, or other information is provided as general market commentary, and does not constitute investment advice. Oanda & TPQ will not accept liability for any loss or damage, including without limitation to, any loss of profit, which may arise directly or indirectly from use of or reliance on such information.\n", ""]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Author Disclaimer"]}, {"cell_type": "markdown", "metadata": {}, "source": ["\n", "The author is neither an employee, agent nor representative of Oanda and is therefore acting independently. The opinions given are their own, constitute general market commentary, and do not constitute the opinion or advice of Oanda or any form of personal or investment advice. Oanda assumes no responsibility for any loss or damage, including but not limited to, any loss or gain arising out of the direct or indirect use of this or any other content. Trading forex/CFDs on margin carries a high level of risk and may not be suitable for all investors as you could sustain losses in excess of deposits.\n", ""]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["import math\n", "import time\n", "import numpy as np\n", "import pandas as pd\n", "import datetime as dt\n", "from pylab import plt, mpl"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["np.random.seed(1000)\n", "plt.style.use('seaborn')\n", "mpl.rcParams['font.family'] = 'serif'"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Capital Management"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Kelly Criterion in a Binomial Setting"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": ["p = 0.55"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": ["f = p - (1 - p)"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.10000000000000009"]}, "execution_count": 5, "metadata": {}, "output_type": "execute_result"}], "source": ["f"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": ["I = 50"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": ["n = 100"]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": ["def run_simulation(f):\n", " c = np.zeros((n, I))\n", " c[0] = 100\n", " for i in range(I):\n", " for t in range(1, n):\n", " o = np.random.binomial(1, p)\n", " if o > 0:\n", " c[t, i] = (1 + f) * c[t - 1, i]\n", " else:\n", " c[t, i] = (1 - f) * c[t - 1, i]\n", " return c"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": ["c_1 = run_simulation(f)"]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[100. , 100. , 100. , ..., 100. , 100. , 100. ],\n", " [ 90. , 110. , 90. , ..., 110. , 90. , 110. ],\n", " [ 99. , 121. , 99. , ..., 121. , 81. , 121. ],\n", " ...,\n", " [226.35, 338.13, 413.27, ..., 123.97, 123.97, 123.97],\n", " [248.99, 371.94, 454.6 , ..., 136.37, 136.37, 136.37],\n", " [273.89, 409.14, 409.14, ..., 122.73, 150.01, 122.73]])"]}, "execution_count": 10, "metadata": {}, "output_type": "execute_result"}], "source": ["c_1.round(2)"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6))\n", "plt.plot(c_1, 'b', lw=0.5)\n", "plt.plot(c_1.mean(axis=1), 'r', lw=2.5);\n", "# plt.savefig('../../images/ch12/auto_plot_01.png');"]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": ["c_2 = run_simulation(0.05)"]}, {"cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": ["c_3 = run_simulation(0.25)"]}, {"cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": ["c_4 = run_simulation(0.5)"]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6))\n", "plt.plot(c_1.mean(axis=1), 'r', label='$f^*=0.1$')\n", "plt.plot(c_2.mean(axis=1), 'b', label='$f=0.05$')\n", "plt.plot(c_3.mean(axis=1), 'y', label='$f=0.25$')\n", "plt.plot(c_4.mean(axis=1), 'm', label='$f=0.5$')\n", "plt.legend(loc=0);\n", "# plt.savefig('../../images/ch12/auto_plot_02.png');"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Kelly Criterion for Stocks and Indices"]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": ["raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv',\n", " index_col=0, parse_dates=True)"]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": ["symbol = '.SPX'"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": ["data = pd.DataFrame(raw[symbol])"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": ["data['return'] = np.log(data / data.shift(1))"]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": ["data.dropna(inplace=True)"]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [{"data": {"text/html": ["
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" .SPX return\n", "Date \n", "2019-12-23 3224.01 0.000866\n", "2019-12-24 3223.38 -0.000195\n", "2019-12-27 3240.02 0.000034\n", "2019-12-30 3221.29 -0.005798\n", "2019-12-31 3230.78 0.002942"]}, "execution_count": 21, "metadata": {}, "output_type": "execute_result"}], "source": ["data.tail()"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": ["mu = data['return'].mean() * 252"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.09992181916534204"]}, "execution_count": 23, "metadata": {}, "output_type": "execute_result"}], "source": ["mu"]}, {"cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": ["sigma = data['return'].std() * 252 ** 0.5"]}, {"cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.14761569775486563"]}, "execution_count": 25, "metadata": {}, "output_type": "execute_result"}], "source": ["sigma"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": ["r = 0.0"]}, {"cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": ["f = (mu - r) / sigma ** 2 # <5>"]}, {"cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [{"data": {"text/plain": ["4.585590244019818"]}, "execution_count": 28, "metadata": {}, "output_type": "execute_result"}], "source": ["f"]}, {"cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": ["equs = []"]}, {"cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": ["def kelly_strategy(f):\n", " global equs\n", " equ = 'equity_{:.2f}'.format(f)\n", " equs.append(equ)\n", " cap = 'capital_{:.2f}'.format(f)\n", " data[equ] = 1\n", " data[cap] = data[equ] * f\n", " for i, t in enumerate(data.index[1:]):\n", " t_1 = data.index[i]\n", " data.loc[t, cap] = data[cap].loc[t_1] * \\\n", " math.exp(data['return'].loc[t])\n", " data.loc[t, equ] = data[cap].loc[t] - \\\n", " data[cap].loc[t_1] + \\\n", " data[equ].loc[t_1]\n", " data.loc[t, cap] = data[equ].loc[t] * f"]}, {"cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": ["kelly_strategy(f * 0.5)"]}, {"cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": ["kelly_strategy(f * 0.66)"]}, {"cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": ["kelly_strategy(f)"]}, {"cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": [" equity_2.29 equity_3.03 equity_4.59\n", "Date \n", "2019-12-23 6.628865 9.585294 14.205748\n", "2019-12-24 6.625895 9.579626 14.193019\n", "2019-12-27 6.626410 9.580610 14.195229\n", "2019-12-30 6.538582 9.412991 13.818934\n", "2019-12-31 6.582748 9.496919 14.005618\n"]}], "source": ["print(data[equs].tail())"]}, {"cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["| \n", " | .SPX | \n", "return | \n", "
|---|---|---|
| Date | \n", "\n", " | \n", " |
| 2019-12-23 | \n", "3224.01 | \n", "0.000866 | \n", "
| 2019-12-24 | \n", "3223.38 | \n", "-0.000195 | \n", "
| 2019-12-27 | \n", "3240.02 | \n", "0.000034 | \n", "
| 2019-12-30 | \n", "3221.29 | \n", "-0.005798 | \n", "
| 2019-12-31 | \n", "3230.78 | \n", "0.002942 | \n", "
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["ax = data['return'].cumsum().apply(np.exp).plot(figsize=(10, 6))\n", "data[equs].plot(ax=ax, legend=True);\n", "# plt.savefig('../../images/ch12/auto_plot_03.png');"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## ML-Based Trading Strategy"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Vectorized Backtesting"]}, {"cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": ["import tpqoa"]}, {"cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["CPU times: user 1.22 ms, sys: 1.26 ms, total: 2.47 ms\n", "Wall time: 1.43 ms\n"]}], "source": ["%time api = tpqoa.tpqoa('../pyalgo.cfg')"]}, {"cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [], "source": ["instrument = 'EUR_USD'"]}, {"cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [], "source": ["raw = api.get_history(instrument,\n", " start='2020-06-08',\n", " end='2020-06-13',\n", " granularity='M10',\n", " price='M')"]}, {"cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "DatetimeIndex: 701 entries, 2020-06-08 00:00:00 to 2020-06-12 20:50:00\n", "Data columns (total 6 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 o 701 non-null float64\n", " 1 h 701 non-null float64\n", " 2 l 701 non-null float64\n", " 3 c 701 non-null float64\n", " 4 volume 701 non-null int64 \n", " 5 complete 701 non-null bool \n", "dtypes: bool(1), float64(4), int64(1)\n", "memory usage: 33.5 KB\n"]}], "source": ["raw.info()"]}, {"cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [], "source": ["spread = 0.00012"]}, {"cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [], "source": ["mean = raw['c'].mean()"]}, {"cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.00010599557439495706"]}, "execution_count": 44, "metadata": {}, "output_type": "execute_result"}], "source": ["ptc = spread / mean\n", "ptc"]}, {"cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", 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"], "text/plain": [" o h l c volume complete\n", "time \n", "2020-06-12 20:10:00 1.12572 1.12593 1.12532 1.12568 221 True\n", "2020-06-12 20:20:00 1.12569 1.12578 1.12532 1.12558 163 True\n", "2020-06-12 20:30:00 1.12560 1.12573 1.12534 1.12543 192 True\n", "2020-06-12 20:40:00 1.12544 1.12594 1.12528 1.12542 219 True\n", "2020-06-12 20:50:00 1.12544 1.12624 1.12541 1.12554 296 True"]}, "execution_count": 40, "metadata": {}, "output_type": "execute_result"}], "source": ["raw.tail()"]}, {"cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["| \n", " | o | \n", "h | \n", "l | \n", "c | \n", "volume | \n", "complete | \n", "
|---|---|---|---|---|---|---|
| time | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
| 2020-06-12 20:10:00 | \n", "1.12572 | \n", "1.12593 | \n", "1.12532 | \n", "1.12568 | \n", "221 | \n", "True | \n", "
| 2020-06-12 20:20:00 | \n", "1.12569 | \n", "1.12578 | \n", "1.12532 | \n", "1.12558 | \n", "163 | \n", "True | \n", "
| 2020-06-12 20:30:00 | \n", "1.12560 | \n", "1.12573 | \n", "1.12534 | \n", "1.12543 | \n", "192 | \n", "True | \n", "
| 2020-06-12 20:40:00 | \n", "1.12544 | \n", "1.12594 | \n", "1.12528 | \n", "1.12542 | \n", "219 | \n", "True | \n", "
| 2020-06-12 20:50:00 | \n", "1.12544 | \n", "1.12624 | \n", "1.12541 | \n", "1.12554 | \n", "296 | \n", "True | \n", "
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["raw['c'].plot(figsize=(10, 6), legend=True);\n", "# plt.savefig('../../images/ch12/auto_plot_04.png');"]}, {"cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [], "source": ["data = pd.DataFrame(raw['c'])"]}, {"cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [], "source": ["data.columns = [instrument,]"]}, {"cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": ["window = 20\n", "data['return'] = np.log(data / data.shift(1))\n", "data['vol'] = data['return'].rolling(window).std()\n", "data['mom'] = np.sign(data['return'].rolling(window).mean())\n", "data['sma'] = data[instrument].rolling(window).mean()\n", "data['min'] = data[instrument].rolling(window).min()\n", "data['max'] = data[instrument].rolling(window).max()"]}, {"cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [], "source": ["data.dropna(inplace=True)"]}, {"cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [], "source": ["lags = 6"]}, {"cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [], "source": ["features = ['return', 'vol', 'mom', 'sma', 'min', 'max']"]}, {"cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [], "source": ["cols = []\n", "for f in features:\n", " for lag in range(1, lags + 1):\n", " col = f'{f}_lag_{lag}'\n", " data[col] = data[f].shift(lag)\n", " cols.append(col)"]}, {"cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [], "source": ["data.dropna(inplace=True)"]}, {"cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [], "source": ["data['direction'] = np.where(data['return'] > 0, 1, -1)"]}, {"cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [{"data": {"text/html": ["
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"], "text/plain": [" return_lag_1 return_lag_2 return_lag_3 return_lag_4 \\\n", "time \n", "2020-06-08 04:20:00 0.000097 0.000018 -0.000452 0.000035 \n", "2020-06-08 04:30:00 -0.000115 0.000097 0.000018 -0.000452 \n", "2020-06-08 04:40:00 0.000027 -0.000115 0.000097 0.000018 \n", "2020-06-08 04:50:00 -0.000142 0.000027 -0.000115 0.000097 \n", "2020-06-08 05:00:00 0.000035 -0.000142 0.000027 -0.000115 \n", "2020-06-08 05:10:00 -0.000159 0.000035 -0.000142 0.000027 \n", "\n", " return_lag_5 return_lag_6 \n", "time \n", "2020-06-08 04:20:00 0.000000 0.000009 \n", "2020-06-08 04:30:00 0.000035 0.000000 \n", "2020-06-08 04:40:00 -0.000452 0.000035 \n", "2020-06-08 04:50:00 0.000018 -0.000452 \n", "2020-06-08 05:00:00 0.000097 0.000018 \n", "2020-06-08 05:10:00 -0.000115 0.000097 "]}, "execution_count": 55, "metadata": {}, "output_type": "execute_result"}], "source": ["data[cols].iloc[:lags, :lags]"]}, {"cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [], "source": ["from sklearn.metrics import accuracy_score\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.ensemble import AdaBoostClassifier"]}, {"cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [], "source": ["n_estimators=15\n", "random_state=100\n", "max_depth=2\n", "min_samples_leaf=15\n", "subsample=0.33"]}, {"cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [], "source": ["dtc = DecisionTreeClassifier(random_state=random_state\n", " max_depth=max_depth,\n", " min_samples_leaf=min_samples_leaf)"]}, {"cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [], "source": ["model = AdaBoostClassifier(base_estimator=dtc,\n", " n_estimators=n_estimators,\n", " random_state=random_state)"]}, {"cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [], "source": ["split = int(len(data) * 0.7)"]}, {"cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [], "source": ["train = data.iloc[:split].copy()"]}, {"cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [], "source": ["mu, std = train.mean(), train.std()"]}, {"cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": ["train_ = (train - mu) / std"]}, {"cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [{"data": {"text/plain": ["AdaBoostClassifier(algorithm='SAMME.R',\n", " base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,\n", " class_weight=None,\n", " criterion='gini',\n", " max_depth=2,\n", " max_features=None,\n", " max_leaf_nodes=None,\n", " min_impurity_decrease=0.0,\n", " min_impurity_split=None,\n", " min_samples_leaf=15,\n", " min_samples_split=2,\n", " min_weight_fraction_leaf=0.0,\n", " presort='deprecated',\n", " random_state=100,\n", " splitter='best'),\n", " learning_rate=1.0, n_estimators=15, random_state=100)"]}, "execution_count": 64, "metadata": {}, "output_type": "execute_result"}], "source": ["model.fit(train_[cols], train['direction'])"]}, {"cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.8050847457627118"]}, "execution_count": 65, "metadata": {}, "output_type": "execute_result"}], "source": ["accuracy_score(train['direction'], model.predict(train_[cols]))"]}, {"cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [], "source": ["test = data.iloc[split:].copy()"]}, {"cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": ["test_ = (test - mu) / std"]}, {"cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [], "source": ["test['position'] = model.predict(test_[cols])"]}, {"cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.5665024630541872"]}, "execution_count": 69, "metadata": {}, "output_type": "execute_result"}], "source": ["accuracy_score(test['direction'], test['position'])"]}, {"cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [], "source": ["test['strategy'] = test['position'] * test['return']"]}, {"cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [{"data": {"text/plain": ["77"]}, "execution_count": 71, "metadata": {}, "output_type": "execute_result"}], "source": ["sum(test['position'].diff() != 0)"]}, {"cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [], "source": ["test['strategy_tc'] = np.where(test['position'].diff() != 0,\n", " test['strategy'] - ptc,\n", " test['strategy'])"]}, {"cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [{"data": {"text/plain": ["return 0.990182\n", "strategy 1.015827\n", "strategy_tc 1.007570\n", "dtype: float64"]}, "execution_count": 73, "metadata": {}, "output_type": "execute_result"}], "source": ["test[['return', 'strategy', 'strategy_tc']].sum(\n", " ).apply(np.exp)"]}, {"cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["| \n", " | return_lag_1 | \n", "return_lag_2 | \n", "return_lag_3 | \n", "return_lag_4 | \n", "return_lag_5 | \n", "return_lag_6 | \n", "
|---|---|---|---|---|---|---|
| time | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
| 2020-06-08 04:20:00 | \n", "0.000097 | \n", "0.000018 | \n", "-0.000452 | \n", "0.000035 | \n", "0.000000 | \n", "0.000009 | \n", "
| 2020-06-08 04:30:00 | \n", "-0.000115 | \n", "0.000097 | \n", "0.000018 | \n", "-0.000452 | \n", "0.000035 | \n", "0.000000 | \n", "
| 2020-06-08 04:40:00 | \n", "0.000027 | \n", "-0.000115 | \n", "0.000097 | \n", "0.000018 | \n", "-0.000452 | \n", "0.000035 | \n", "
| 2020-06-08 04:50:00 | \n", "-0.000142 | \n", "0.000027 | \n", "-0.000115 | \n", "0.000097 | \n", "0.000018 | \n", "-0.000452 | \n", "
| 2020-06-08 05:00:00 | \n", "0.000035 | \n", "-0.000142 | \n", "0.000027 | \n", "-0.000115 | \n", "0.000097 | \n", "0.000018 | \n", "
| 2020-06-08 05:10:00 | \n", "-0.000159 | \n", "0.000035 | \n", "-0.000142 | \n", "0.000027 | \n", "-0.000115 | \n", "0.000097 | \n", "
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["test[['return', 'strategy', 'strategy_tc']].cumsum(\n", " ).apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch12/auto_plot_05.png');"]}, {"cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [{"data": {"text/plain": ["return -1.705965\n", "strategy_tc 1.304023\n", "dtype: float64"]}, "execution_count": 75, "metadata": {}, "output_type": "execute_result"}], "source": ["mean = test[['return', 'strategy_tc']].mean() * len(data) * 52\n", "mean"]}, {"cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [{"data": {"text/plain": ["return 0.011306\n", "strategy_tc 0.011370\n", "dtype: float64"]}, "execution_count": 76, "metadata": {}, "output_type": "execute_result"}], "source": ["var = test[['return', 'strategy_tc']].var() * len(data) * 52\n", "var"]}, {"cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [{"data": {"text/plain": ["return 0.106332\n", "strategy_tc 0.106631\n", "dtype: float64"]}, "execution_count": 77, "metadata": {}, "output_type": "execute_result"}], "source": ["vol = var ** 0.5\n", "vol"]}, {"cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [{"data": {"text/plain": ["return -150.884961\n", "strategy_tc 114.687875\n", "dtype: float64"]}, "execution_count": 78, "metadata": {}, "output_type": "execute_result"}], "source": ["mean / var"]}, {"cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [{"data": {"text/plain": ["return -75.442481\n", "strategy_tc 57.343938\n", "dtype: float64"]}, "execution_count": 79, "metadata": {}, "output_type": "execute_result"}], "source": ["mean / var * 0.5"]}, {"cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [], "source": ["to_plot = ['return', 'strategy_tc'] "]}, {"cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [], "source": ["for lev in [10, 20, 30, 40, 50]: \n", " label = 'lstrategy_tc_%d' % lev \n", " test[label] = test['strategy_tc'] * lev\n", " to_plot.append(label) "]}, {"cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", 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"]}, "metadata": {}, "output_type": "display_data"}], "source": ["test[to_plot].cumsum().apply(np.exp).plot(figsize=(10, 6));\n", "# plt.savefig('../../images/ch12/auto_plot_06.png');"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Risk Analysis"]}, {"cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [], "source": ["equity = 3333"]}, {"cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [], "source": ["risk = pd.DataFrame(test['lstrategy_tc_30'])"]}, {"cell_type": "code", "execution_count": 85, "metadata": {}, "outputs": [], "source": ["risk['equity'] = risk['lstrategy_tc_30'].cumsum(\n", " ).apply(np.exp) * equity"]}, {"cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [], "source": ["risk['cummax'] = risk['equity'].cummax()"]}, {"cell_type": "code", "execution_count": 87, "metadata": {}, "outputs": [], "source": ["risk['drawdown'] = risk['cummax'] - risk['equity']"]}, {"cell_type": "code", "execution_count": 88, "metadata": {}, "outputs": [{"data": {"text/plain": ["511.38321383258017"]}, "execution_count": 88, "metadata": {}, "output_type": "execute_result"}], "source": ["risk['drawdown'].max()"]}, {"cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [{"data": {"text/plain": ["Timestamp('2020-06-12 10:30:00')"]}, "execution_count": 89, "metadata": {}, "output_type": "execute_result"}], "source": ["t_max = risk['drawdown'].idxmax()\n", "t_max"]}, {"cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [], "source": ["temp = risk['drawdown'][risk['drawdown'] == 0]"]}, {"cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [], "source": ["periods = (temp.index[1:].to_pydatetime() -\n", " temp.index[:-1].to_pydatetime())"]}, {"cell_type": "code", "execution_count": 92, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([datetime.timedelta(seconds=600), datetime.timedelta(seconds=1200),\n", " datetime.timedelta(seconds=1200), datetime.timedelta(seconds=1200)],\n", " dtype=object)"]}, "execution_count": 92, "metadata": {}, "output_type": "execute_result"}], "source": ["periods[20:30]"]}, {"cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [], "source": ["t_per = periods.max()"]}, {"cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [{"data": {"text/plain": ["datetime.timedelta(seconds=26400)"]}, "execution_count": 94, "metadata": {}, "output_type": "execute_result"}], "source": ["t_per"]}, {"cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [{"data": {"text/plain": ["7.333333333333333"]}, "execution_count": 95, "metadata": {}, "output_type": "execute_result"}], "source": ["t_per.seconds / 60 / 60"]}, {"cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["risk[['equity', 'cummax']].plot(figsize=(10, 6))\n", "plt.axvline(t_max, c='r', alpha=0.5);\n", "# plt.savefig('../../images/ch12/auto_plot_07.png');"]}, {"cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [], "source": ["import scipy.stats as scs"]}, {"cell_type": "code", "execution_count": 98, "metadata": {}, "outputs": [], "source": ["percs = [0.01, 0.1, 1., 2.5, 5.0, 10.0]"]}, {"cell_type": "code", "execution_count": 99, "metadata": {}, "outputs": [], "source": ["risk['return'] = np.log(risk['equity'] /\n", " risk['equity'].shift(1))"]}, {"cell_type": "code", "execution_count": 100, "metadata": {}, "outputs": [], "source": ["VaR = scs.scoreatpercentile(equity * risk['return'], percs)"]}, {"cell_type": "code", "execution_count": 101, "metadata": {}, "outputs": [], "source": ["def print_var():\n", " print('{} {}'.format('Confidence Level', 'Value-at-Risk'))\n", " print(33 * '-')\n", " for pair in zip(percs, VaR):\n", " print('{:16.2f} {:16.3f}'.format(100 - pair[0], -pair[1])) "]}, {"cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Confidence Level Value-at-Risk\n", "---------------------------------\n", " 99.99 162.570\n", " 99.90 161.348\n", " 99.00 132.382\n", " 97.50 122.913\n", " 95.00 100.950\n", " 90.00 62.622\n"]}], "source": ["print_var()"]}, {"cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [], "source": ["hourly = risk.resample('1H', label='right').last()"]}, {"cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [], "source": ["hourly['return'] = np.log(hourly['equity'] /\n", " hourly['equity'].shift(1))"]}, {"cell_type": "code", "execution_count": 105, "metadata": {}, "outputs": [], "source": ["VaR = scs.scoreatpercentile(equity * hourly['return'], percs)"]}, {"cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Confidence Level Value-at-Risk\n", "---------------------------------\n", " 99.99 252.460\n", " 99.90 251.744\n", " 99.00 244.593\n", " 97.50 232.674\n", " 95.00 125.498\n", " 90.00 61.701\n"]}], "source": ["print_var()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Persisting the Model Object"]}, {"cell_type": "code", "execution_count": 107, "metadata": {}, "outputs": [], "source": ["import pickle"]}, {"cell_type": "code", "execution_count": 108, "metadata": {}, "outputs": [], "source": ["algorithm = {'model': model, 'mu': mu, 'std': std}"]}, {"cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [], "source": ["pickle.dump(algorithm, open('algorithm.pkl', 'wb'))"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Online Algorithm"]}, {"cell_type": "code", "execution_count": 110, "metadata": {}, "outputs": [], "source": ["algorithm = pickle.load(open('algorithm.pkl', 'rb'))"]}, {"cell_type": "code", "execution_count": 111, "metadata": {}, "outputs": [{"data": {"text/plain": ["AdaBoostClassifier(algorithm='SAMME.R',\n", " base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,\n", " class_weight=None,\n", " criterion='gini',\n", " max_depth=2,\n", " max_features=None,\n", " max_leaf_nodes=None,\n", " min_impurity_decrease=0.0,\n", " min_impurity_split=None,\n", " min_samples_leaf=15,\n", " min_samples_split=2,\n", " min_weight_fraction_leaf=0.0,\n", " presort='deprecated',\n", " random_state=100,\n", " splitter='best'),\n", " learning_rate=1.0, n_estimators=15, random_state=100)"]}, "execution_count": 111, "metadata": {}, "output_type": "execute_result"}], "source": ["algorithm['model']"]}, {"cell_type": "code", "execution_count": 112, "metadata": {}, "outputs": [], "source": ["class MLTrader(tpqoa.tpqoa):\n", " def __init__(self, config_file, algorithm):\n", " super(MLTrader, self).__init__(config_file)\n", " self.model = algorithm['model']\n", " self.mu = algorithm['mu']\n", " self.std = algorithm['std']\n", " self.units = 100000\n", " self.position = 0\n", " self.bar = '5s'\n", " self.window = 2\n", " self.lags = 6\n", " self.min_length = self.lags + self.window + 1\n", " self.features = ['return', 'vol', 'mom', 'sma', 'min', 'max']\n", " self.raw_data = pd.DataFrame()\n", " def prepare_features(self):\n", " self.data['return'] = np.log(self.data['mid'] /\n", " self.data['mid'].shift(1))\n", " self.data['vol'] = self.data['return'].rolling(\n", " self.window).std()\n", " self.data['mom'] = np.sign(\n", " self.data['return'].rolling(self.window).mean())\n", " self.data['sma'] = self.data['mid'].rolling(self.window).mean()\n", " self.data['min'] = self.data['mid'].rolling(self.window).min()\n", " self.data['max'] = self.data['mid'].rolling(self.window).max()\n", " self.data.dropna(inplace=True)\n", " self.data[self.features] -= self.mu\n", " self.data[self.features] /= self.std\n", " self.cols = []\n", " for f in self.features:\n", " for lag in range(1, self.lags + 1):\n", " col = f'{f}_lag_{lag}'\n", " self.data[col] = self.data[f].shift(lag)\n", " self.cols.append(col)\n", " def on_success(self, time, bid, ask):\n", " # print(self.ticks, 20 * ' ', end='\\r')\n", " df = pd.DataFrame({'bid': float(bid), 'ask': float(ask)},\n", " index=[pd.Timestamp(time).tz_localize(None)])\n", " self.raw_data = self.raw_data.append(df)\n", " self.data = self.raw_data.resample(self.bar,\n", " label='right').last().ffill()\n", " self.data = self.data.iloc[:-1]\n", " if len(self.data) > self.min_length:\n", " self.min_length +=1\n", " self.data['mid'] = (self.data['bid'] +\n", " self.data['ask']) / 2\n", " self.prepare_features()\n", " features = self.data[\n", " self.cols].iloc[-1].values.reshape(1, -1)\n", " signal = self.model.predict(features)[0]\n", " print(f'NEW SIGNAL: {signal}', end='\\r')\n", " if self.position in [0, -1] and signal == 1:\n", " print('*** GOING LONG ***')\n", " self.create_order(self.stream_instrument,\n", " units=(1 - self.position) * self.units)\n", " self.position = 1\n", " elif self.position in [0, 1] and signal == -1:\n", " print('*** GOING SHORT ***')\n", " self.create_order(self.stream_instrument,\n", " units=-(1 + self.position) * self.units)\n", " self.position = -1"]}, {"cell_type": "code", "execution_count": 113, "metadata": {}, "outputs": [], "source": ["mlt = MLTrader('../pyalgo.cfg', algorithm)"]}, {"cell_type": "code", "execution_count": 114, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["*** GOING LONG ***\n", "\n", "\n", " {'id': '992', 'time': '2020-06-15T15:38:41.229125978Z', 'userID': 13834683, 'accountID': '101-004-13834683-001', 'batchID': '991', 'requestID': '42707116835048495', 'type': 'ORDER_FILL', 'orderID': '991', 'instrument': 'EUR_USD', 'units': '100000.0', 'gainQuoteHomeConversionFactor': '0.882639939534', 'lossQuoteHomeConversionFactor': '0.891510692695', 'price': 1.12737, 'fullVWAP': 1.12737, 'fullPrice': {'type': 'PRICE', 'bids': [{'price': 1.12723, 'liquidity': '10000000'}], 'asks': [{'price': 1.12737, 'liquidity': '10000000'}], 'closeoutBid': 1.12723, 'closeoutAsk': 1.12737}, 'reason': 'MARKET_ORDER', 'pl': '0.0', 'financing': '0.0', 'commission': '0.0', 'guaranteedExecutionFee': '0.0', 'accountBalance': '99143.8015', 'tradeOpened': {'tradeID': '992', 'units': '100000.0', 'price': 1.12737, 'guaranteedExecutionFee': '0.0', 'halfSpreadCost': '6.2095', 'initialMarginRequired': '3330.0'}, 'halfSpreadCost': '6.2095'} \n", "\n", "*** CLOSING OUT ***\n", "\n", "\n", " {'id': '994', 'time': '2020-06-15T15:41:30.840800760Z', 'userID': 13834683, 'accountID': '101-004-13834683-001', 'batchID': '993', 'requestID': '42707117544392823', 'type': 'ORDER_FILL', 'orderID': '993', 'instrument': 'EUR_USD', 'units': '-100000.0', 'gainQuoteHomeConversionFactor': '0.882620365297', 'lossQuoteHomeConversionFactor': '0.891490921732', 'price': 1.12726, 'fullVWAP': 1.12726, 'fullPrice': {'type': 'PRICE', 'bids': [{'price': 1.12726, 'liquidity': '10000000'}], 'asks': [{'price': 1.12739, 'liquidity': '10000000'}], 'closeoutBid': 1.12726, 'closeoutAsk': 1.12739}, 'reason': 'MARKET_ORDER', 'pl': '-9.8064', 'financing': '0.0', 'commission': '0.0', 'guaranteedExecutionFee': '0.0', 'accountBalance': '99133.9951', 'tradesClosed': [{'tradeID': '992', 'units': '-100000.0', 'price': 1.12726, 'realizedPL': '-9.8064', 'financing': '0.0', 'guaranteedExecutionFee': '0.0', 'halfSpreadCost': '5.7659'}], 'halfSpreadCost': '5.7659'} \n", "\n"]}], "source": ["mlt.stream_data(instrument, stop=250)\n", "print('*** CLOSING OUT ***')\n", "mlt.create_order(mlt.stream_instrument,\n", " units=-mlt.position * mlt.units)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Logging and Monitoring"]}, {"cell_type": "code", "execution_count": 115, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["#\n", "# Automated ML-Based Trading Strategy for Oanda\n", "# Online Algorithm, Logging, Monitoring\n", "#\n", "# Python for Algorithmic Trading\n", "# (c) Dr. Yves J. Hilpisch\n", "#\n", "import zmq\n", "import tpqoa\n", "import pickle\n", "import numpy as np\n", "import pandas as pd\n", "import datetime as dt\n", "\n", "log_file = 'automated_strategy.log'\n", "\n", "# loads the persisted algorithm object\n", "algorithm = pickle.load(open('algorithm.pkl', 'rb'))\n", "\n", "# sets up the socket communication via ZeroMQ (here: \"publisher\")\n", "context = zmq.Context()\n", "socket = context.socket(zmq.PUB)\n", "\n", "# this binds the socket communication to all IP addresses of the machine\n", "socket.bind('tcp://127.0.0.1:5555')\n", "\n", "# recreating the log file\n", "with open(log_file, 'w') as f:\n", " f.write('*** NEW LOG FILE ***\\n')\n", " f.write(str(dt.datetime.now()) + '\\n\\n\\n')\n", "\n", "\n", "def logger_monitor(message, time=True, sep=True):\n", " ''' Custom logger and monitor function.\n", " '''\n", " with open(log_file, 'a') as f:\n", " t = str(dt.datetime.now())\n", " msg = ''\n", " if time:\n", " msg += '\\n' + t + '\\n'\n", " if sep:\n", " msg += 80 * '=' + '\\n'\n", " msg += message + '\\n\\n'\n", " # sends the message via the socket\n", " socket.send_string(msg)\n", " # writes the message to the log file\n", " f.write(msg)\n", "\n", "\n", "class MLTrader(tpqoa.tpqoa):\n", " def __init__(self, config_file, algorithm):\n", " super(MLTrader, self).__init__(config_file)\n", " self.model = algorithm['model']\n", " self.mu = algorithm['mu']\n", " self.std = algorithm['std']\n", " self.units = 100000\n", " self.position = 0\n", " self.bar = '2s'\n", " self.window = 2\n", " self.lags = 6\n", " self.min_length = self.lags + self.window + 1\n", " self.features = ['return', 'vol', 'mom', 'sma', 'min', 'max']\n", " self.raw_data = pd.DataFrame()\n", "\n", " def prepare_features(self):\n", " self.data['return'] = np.log(\n", " self.data['mid'] / self.data['mid'].shift(1))\n", " self.data['vol'] = self.data['return'].rolling(self.window).std()\n", " self.data['mom'] = np.sign(\n", " self.data['return'].rolling(self.window).mean())\n", " self.data['sma'] = self.data['mid'].rolling(self.window).mean()\n", " self.data['min'] = self.data['mid'].rolling(self.window).min()\n", " self.data['max'] = self.data['mid'].rolling(self.window).max()\n", " self.data.dropna(inplace=True)\n", " self.data[self.features] -= self.mu\n", " self.data[self.features] /= self.std\n", " self.cols = []\n", " for f in self.features:\n", " for lag in range(1, self.lags + 1):\n", " col = f'{f}_lag_{lag}'\n", " self.data[col] = self.data[f].shift(lag)\n", " self.cols.append(col)\n", "\n", " def report_trade(self, pos, order):\n", " ''' Prints, logs and sends trade data.\n", " '''\n", " out = '\\n\\n' + 80 * '=' + '\\n'\n", " out += '*** GOING {} *** \\n'.format(pos) + '\\n'\n", " out += str(order) + '\\n'\n", " out += 80 * '=' + '\\n'\n", " logger_monitor(out)\n", " print(out)\n", "\n", " def on_success(self, time, bid, ask):\n", " print(self.ticks, 20 * ' ', end='\\r')\n", " df = pd.DataFrame({'bid': float(bid), 'ask': float(ask)},\n", " index=[pd.Timestamp(time).tz_localize(None)])\n", " self.raw_data = self.raw_data.append(df)\n", " self.data = self.raw_data.resample(\n", " self.bar, label='right').last().ffill()\n", " self.data = self.data.iloc[:-1]\n", " if len(self.data) > self.min_length:\n", " logger_monitor('NUMBER OF TICKS: {} | '.format(self.ticks) +\n", " 'NUMBER OF BARS: {}'.format(self.min_length))\n", " self.min_length += 1\n", " self.data['mid'] = (self.data['bid'] + self.data['ask']) / 2\n", " self.prepare_features()\n", " features = self.data[self.cols].iloc[-1].values.reshape(1, -1)\n", " signal = self.model.predict(features)[0]\n", " # logs and sends major financial information\n", " logger_monitor('MOST RECENT DATA\\n' +\n", " str(self.data[self.cols].tail()),\n", " False)\n", " logger_monitor('features:\\n' + str(features) + '\\n' +\n", " 'position: ' + str(self.position) + '\\n' +\n", " 'signal: ' + str(signal), False)\n", " if self.position in [0, -1] and signal == 1: # going long?\n", " order = self.create_order(self.stream_instrument,\n", " units=(1 - self.position) *\n", " self.units,\n", " suppress=True, ret=True)\n", " self.report_trade('LONG', order)\n", " self.position = 1\n", " elif self.position in [0, 1] and signal == -1: # going short?\n", " order = self.create_order(self.stream_instrument,\n", " units=-(1 + self.position) *\n", " self.units,\n", " suppress=True, ret=True)\n", " self.report_trade('SHORT', order)\n", " self.position = -1\n", " else: # no trade\n", " logger_monitor('*** NO TRADE PLACED ***')\n", "\n", " logger_monitor('*** END OF CYCLE ***\\n\\n', False, False)\n", "\n", "\n", "if __name__ == '__main__':\n", " mlt = MLTrader('../pyalgo.cfg', algorithm)\n", " mlt.stream_data('EUR_USD', stop=150)\n", " order = mlt.create_order(mlt.stream_instrument,\n", " units=-mlt.position * mlt.units,\n", " suppress=True, ret=True)\n", " mlt.position = 0\n", " mlt.report_trade('NEUTRAL', order)\n"]}], "source": ["!cat automated_strategy.py"]}, {"cell_type": "code", "execution_count": 116, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["#\n", "# Automated ML-Based Trading Strategy for Oanda\n", "# Strategy Monitoring via Socket Communication\n", "#\n", "# Python for Algorithmic Trading\n", "# (c) Dr. Yves J. Hilpisch\n", "#\n", "import zmq\n", "\n", "# sets up the socket communication via ZeroMQ (here: \"subscriber\")\n", "context = zmq.Context()\n", "socket = context.socket(zmq.SUB)\n", "\n", "# adjust the IP address to reflect the remote location\n", "# socket.connect('tcp://REMOTE_IP_ADDRESS:5555')\n", "\n", "# local IP address used for testing\n", "socket.connect('tcp://127.0.0.1:5555')\n", "\n", "\n", "# configures the socket to retrieve every message\n", "socket.setsockopt_string(zmq.SUBSCRIBE, '')\n", "\n", "while True:\n", " msg = socket.recv_string()\n", " print(msg)\n"]}], "source": ["!cat strategy_monitoring.py"]}, {"cell_type": "markdown", "metadata": {}, "source": ["
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch10/OandaSMATrader.py b/ch10/OandaSMATrader.py new file mode 100644 index 0000000..e69de29 diff --git a/ch10/automated_strategy.py b/ch10/automated_strategy.py new file mode 100644 index 0000000..90a012d --- /dev/null +++ b/ch10/automated_strategy.py @@ -0,0 +1,144 @@ +# +# Automated ML-Based Trading Strategy for Oanda +# Online Algorithm, Logging, Monitoring +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# +import zmq +import tpqoa +import pickle +import numpy as np +import pandas as pd +import datetime as dt + +log_file = 'automated_strategy.log' + +# loads the persisted algorithm object +algorithm = pickle.load(open('algorithm.pkl', 'rb')) + +# sets up the socket communication via ZeroMQ (here: "publisher") +context = zmq.Context() +socket = context.socket(zmq.PUB) + +# this binds the socket communication to all IP addresses of the machine +socket.bind('tcp://0.0.0.0:5555') + +# recreating the log file +with open(log_file, 'w') as f: + f.write('*** NEW LOG FILE ***\n') + f.write(str(dt.datetime.now()) + '\n\n\n') + + +def logger_monitor(message, time=True, sep=True): + ''' Custom logger and monitor function. + ''' + with open(log_file, 'a') as f: + t = str(dt.datetime.now()) + msg = '' + if time: + msg += '\n' + t + '\n' + if sep: + msg += 80 * '=' + '\n' + msg += message + '\n\n' + # sends the message via the socket + socket.send_string(msg) + # writes the message to the log file + f.write(msg) + + +class MLTrader(tpqoa.tpqoa): + def __init__(self, config_file, algorithm): + super(MLTrader, self).__init__(config_file) + self.model = algorithm['model'] + self.mu = algorithm['mu'] + self.std = algorithm['std'] + self.units = 100000 + self.position = 0 + self.bar = '2s' + self.window = 2 + self.lags = 6 + self.min_length = self.lags + self.window + 1 + self.features = ['return', 'vol', 'mom', 'sma', 'min', 'max'] + self.raw_data = pd.DataFrame() + + def prepare_features(self): + self.data['return'] = np.log( + self.data['mid'] / self.data['mid'].shift(1)) + self.data['vol'] = self.data['return'].rolling(self.window).std() + self.data['mom'] = np.sign( + self.data['return'].rolling(self.window).mean()) + self.data['sma'] = self.data['mid'].rolling(self.window).mean() + self.data['min'] = self.data['mid'].rolling(self.window).min() + self.data['max'] = self.data['mid'].rolling(self.window).max() + self.data.dropna(inplace=True) + self.data[self.features] -= self.mu + self.data[self.features] /= self.std + self.cols = [] + for f in self.features: + for lag in range(1, self.lags + 1): + col = f'{f}_lag_{lag}' + self.data[col] = self.data[f].shift(lag) + self.cols.append(col) + + def report_trade(self, pos, order): + ''' Prints, logs and sends trade data. + ''' + out = '\n\n' + 80 * '=' + '\n' + out += '*** GOING {} *** \n'.format(pos) + '\n' + out += str(order) + '\n' + out += 80 * '=' + '\n' + logger_monitor(out) + print(out) + + def on_success(self, time, bid, ask): + print(self.ticks, 20 * ' ', end='\r') + df = pd.DataFrame({'bid': float(bid), 'ask': float(ask)}, + index=[pd.Timestamp(time).tz_localize(None)]) + self.raw_data = self.raw_data.append(df) + self.data = self.raw_data.resample( + self.bar, label='right').last().ffill() + self.data = self.data.iloc[:-1] + if len(self.data) > self.min_length: + logger_monitor('NUMBER OF TICKS: {} | '.format(self.ticks) + + 'NUMBER OF BARS: {}'.format(self.min_length)) + self.min_length += 1 + self.data['mid'] = (self.data['bid'] + self.data['ask']) / 2 + self.prepare_features() + features = self.data[self.cols].iloc[-1].values.reshape(1, -1) + signal = self.model.predict(features)[0] + # logs and sends major financial information + logger_monitor('MOST RECENT DATA\n' + + str(self.data[self.cols].tail()), + False) + logger_monitor('features:\n' + str(features) + '\n' + + 'position: ' + str(self.position) + '\n' + + 'signal: ' + str(signal), False) + if self.position in [0, -1] and signal == 1: # going long? + order = self.create_order(self.stream_instrument, + units=(1 - self.position) * + self.units, + suppress=True, ret=True) + self.report_trade('LONG', order) + self.position = 1 + elif self.position in [0, 1] and signal == -1: # going short? + order = self.create_order(self.stream_instrument, + units=-(1 + self.position) * + self.units, + suppress=True, ret=True) + self.report_trade('SHORT', order) + self.position = -1 + else: # no trade + logger_monitor('*** NO TRADE PLACED ***') + + logger_monitor('*** END OF CYCLE ***\n\n', False, False) + + +if __name__ == '__main__': + mlt = MLTrader('../pyalgo.cfg', algorithm) + mlt.stream_data('EUR_USD', stop=150) + order = mlt.create_order(mlt.stream_instrument, + units=-mlt.position * mlt.units, + suppress=True, ret=True) + mlt.position = 0 + mlt.report_trade('NEUTRAL', order) diff --git a/ch10/strategy_monitoring.py b/ch10/strategy_monitoring.py new file mode 100644 index 0000000..b9d850a --- /dev/null +++ b/ch10/strategy_monitoring.py @@ -0,0 +1,26 @@ +# +# Automated ML-Based Trading Strategy for Oanda +# Strategy Monitoring via Socket Communication +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# +import zmq + +# sets up the socket communication via ZeroMQ (here: "subscriber") +context = zmq.Context() +socket = context.socket(zmq.SUB) + +# adjust the IP address to reflect the remote location +socket.connect('tcp://134.122.70.51:5555') + +# local IP address used for testing +# socket.connect('tcp://0.0.0.0:5555') + + +# configures the socket to retrieve every message +socket.setsockopt_string(zmq.SUBSCRIBE, '') + +while True: + msg = socket.recv_string() + print(msg) diff --git a/chA/A_pyalgo.ipynb b/chA/A_pyalgo.ipynb new file mode 100644 index 0000000..863fd67 --- /dev/null +++ b/chA/A_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading\n", "\n", "**Appendix A — Python, NumPy, pandas**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python Basics"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Data Types"]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["a = 3"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [{"data": {"text/plain": ["int"]}, "execution_count": 2, "metadata": {}, "output_type": "execute_result"}], "source": ["type(a)"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [{"data": {"text/plain": ["2"]}, "execution_count": 3, "metadata": {}, "output_type": "execute_result"}], "source": ["a.bit_length()"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": ["b = 5."]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [{"data": {"text/plain": ["float"]}, "execution_count": 5, "metadata": {}, "output_type": "execute_result"}], "source": ["type(b)"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": ["c = 10 ** 100"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"data": {"text/plain": ["10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000"]}, "execution_count": 7, "metadata": {}, "output_type": "execute_result"}], "source": ["c "]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [{"data": {"text/plain": ["333"]}, "execution_count": 8, "metadata": {}, "output_type": "execute_result"}], "source": ["c.bit_length()"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.6"]}, "execution_count": 9, "metadata": {}, "output_type": "execute_result"}], "source": ["3 / 5."]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"data": {"text/plain": ["15.0"]}, "execution_count": 10, "metadata": {}, "output_type": "execute_result"}], "source": ["a * b"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [{"data": {"text/plain": ["-2.0"]}, "execution_count": 11, "metadata": {}, "output_type": "execute_result"}], "source": ["a - b"]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [{"data": {"text/plain": ["8.0"]}, "execution_count": 12, "metadata": {}, "output_type": "execute_result"}], "source": ["b + a"]}, {"cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [{"data": {"text/plain": ["243.0"]}, "execution_count": 13, "metadata": {}, "output_type": "execute_result"}], "source": ["a ** b"]}, {"cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": ["import math"]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [{"data": {"text/plain": ["1.0986122886681098"]}, "execution_count": 15, "metadata": {}, "output_type": "execute_result"}], "source": ["math.log(a)"]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [{"data": {"text/plain": ["20.085536923187668"]}, "execution_count": 16, "metadata": {}, "output_type": "execute_result"}], "source": ["math.exp(a)"]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [{"data": {"text/plain": ["-0.9589242746631385"]}, "execution_count": 17, "metadata": {}, "output_type": "execute_result"}], "source": ["math.sin(b)"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": ["s = 'Python for Algorithmic Trading.'"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [{"data": {"text/plain": ["str"]}, "execution_count": 19, "metadata": {}, "output_type": "execute_result"}], "source": ["type(s)"]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [{"data": {"text/plain": ["'python for algorithmic trading.'"]}, "execution_count": 20, "metadata": {}, "output_type": "execute_result"}], "source": ["s.lower()"]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [{"data": {"text/plain": ["'PYTHON FOR ALGORITHMIC TRADING.'"]}, "execution_count": 21, "metadata": {}, "output_type": "execute_result"}], "source": ["s.upper()"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [{"data": {"text/plain": ["'Python'"]}, "execution_count": 22, "metadata": {}, "output_type": "execute_result"}], "source": ["s[0:6]"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": ["st = s[0:6] + s[-9:-1]"]}, {"cell_type": "code", "execution_count": 24, "metadata": {"scrolled": true}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Python Trading\n"]}], "source": ["print(st)"]}, {"cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": ["repl = 'My name is %s, I am %d years old and %4.2f m tall.'"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["My name is Gordon Gekko, I am 43 years old and 1.78 m tall.\n"]}], "source": ["print(repl % ('Gordon Gekko', 43, 1.78))"]}, {"cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": ["repl = 'My name is {:s}, I am {:d} years old and {:4.2f} m tall.' # <3>"]}, {"cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["My name is Gordon Gekko, I am 43 years old and 1.78 m tall.\n"]}], "source": ["print(repl.format('Gordon Gekko', 43, 1.78))"]}, {"cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": ["name, age, height = 'Gordon Gekko', 43, 1.78 # <5>"]}, {"cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["My name is Gordon Gekko, I am 43 years old and 1.78m tall.\n"]}], "source": ["print(f'My name is {name:s}, I am {age:d} years old and {height:4.2f}m tall.')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Data Structures"]}, {"cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": ["t1 = (a, b, st)"]}, {"cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [{"data": {"text/plain": ["(3, 5.0, 'Python Trading')"]}, "execution_count": 32, "metadata": {}, "output_type": "execute_result"}], "source": ["t1"]}, {"cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [{"data": {"text/plain": ["tuple"]}, "execution_count": 33, "metadata": {}, "output_type": "execute_result"}], "source": ["type(t1)"]}, {"cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": ["t2 = st, b, a"]}, {"cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [{"data": {"text/plain": ["('Python Trading', 5.0, 3)"]}, "execution_count": 35, "metadata": {}, "output_type": "execute_result"}], "source": ["t2"]}, {"cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [{"data": {"text/plain": ["tuple"]}, "execution_count": 36, "metadata": {}, "output_type": "execute_result"}], "source": ["type(t2)"]}, {"cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": ["t = (t1, t2)"]}, {"cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [{"data": {"text/plain": ["((3, 5.0, 'Python Trading'), ('Python Trading', 5.0, 3))"]}, "execution_count": 38, "metadata": {}, "output_type": "execute_result"}], "source": ["t"]}, {"cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [{"data": {"text/plain": ["'Python Trading'"]}, "execution_count": 39, "metadata": {}, "output_type": "execute_result"}], "source": ["t[0][2]"]}, {"cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": ["l = [a, b, st]"]}, {"cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [{"data": {"text/plain": ["[3, 5.0, 'Python Trading']"]}, "execution_count": 41, "metadata": {}, "output_type": "execute_result"}], "source": ["l"]}, {"cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [{"data": {"text/plain": ["list"]}, "execution_count": 42, "metadata": {}, "output_type": "execute_result"}], "source": ["type(l)"]}, {"cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [], "source": ["l.append(s.split()[3])"]}, {"cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [{"data": {"text/plain": ["[3, 5.0, 'Python Trading', 'Trading.']"]}, "execution_count": 44, "metadata": {}, "output_type": "execute_result"}], "source": ["l"]}, {"cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": ["l = list(('Z', 'Q', 'D', 'J', 'E', 'H', '5.', 'a'))"]}, {"cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [{"data": {"text/plain": ["['Z', 'Q', 'D', 'J', 'E', 'H', '5.', 'a']"]}, "execution_count": 46, "metadata": {}, "output_type": "execute_result"}], "source": ["l"]}, {"cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [], "source": ["l.sort()"]}, {"cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [{"data": {"text/plain": ["['5.', 'D', 'E', 'H', 'J', 'Q', 'Z', 'a']"]}, "execution_count": 48, "metadata": {}, "output_type": "execute_result"}], "source": ["l"]}, {"cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [], "source": ["d = {'int_obj': a, 'float_obj': b, 'string_obj': st}"]}, {"cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [{"data": {"text/plain": ["dict"]}, "execution_count": 50, "metadata": {}, "output_type": "execute_result"}], "source": ["type(d)"]}, {"cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [{"data": {"text/plain": ["{'int_obj': 3, 'float_obj': 5.0, 'string_obj': 'Python Trading'}"]}, "execution_count": 51, "metadata": {}, "output_type": "execute_result"}], "source": ["d"]}, {"cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [{"data": {"text/plain": ["5.0"]}, "execution_count": 52, "metadata": {}, "output_type": "execute_result"}], "source": ["d['float_obj']"]}, {"cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [], "source": ["d['int_obj_long'] = 10 ** 20"]}, {"cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [{"data": {"text/plain": ["{'int_obj': 3,\n", " 'float_obj': 5.0,\n", " 'string_obj': 'Python Trading',\n", " 'int_obj_long': 100000000000000000000}"]}, "execution_count": 54, "metadata": {}, "output_type": "execute_result"}], "source": ["d"]}, {"cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [{"data": {"text/plain": ["dict_keys(['int_obj', 'float_obj', 'string_obj', 'int_obj_long'])"]}, "execution_count": 55, "metadata": {}, "output_type": "execute_result"}], "source": ["d.keys()"]}, {"cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [{"data": {"text/plain": ["dict_values([3, 5.0, 'Python Trading', 100000000000000000000])"]}, "execution_count": 56, "metadata": {}, "output_type": "execute_result"}], "source": ["d.values()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Control Structures"]}, {"cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [{"data": {"text/plain": ["range(0, 5)"]}, "execution_count": 57, "metadata": {}, "output_type": "execute_result"}], "source": ["range(5)"]}, {"cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [{"data": {"text/plain": ["range(3, 15, 2)"]}, "execution_count": 58, "metadata": {}, "output_type": "execute_result"}], "source": ["range(3, 15, 2)"]}, {"cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["0 1 4 9 16 "]}], "source": ["for i in range(5):\n", " print(i ** 2, end=' ')"]}, {"cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["3 5 7 9 11 13 "]}], "source": ["for i in range(3, 15, 2):\n", " print(i, end=' ')"]}, {"cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [], "source": ["l = ['a', 'b', 'c', 'd', 'e']"]}, {"cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["a\n", "b\n", "c\n", "d\n", "e\n"]}], "source": ["for _ in l:\n", " print(_)"]}, {"cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": ["s = 'Python Trading'"]}, {"cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["P|y|t|h|o|n| |T|r|a|d|i|n|g|"]}], "source": ["for c in s:\n", " print(c + '|', end='')"]}, {"cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [], "source": ["i = 0"]}, {"cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["0.0 1.0 1.4142135623730951 1.7320508075688772 2.0 "]}], "source": ["while i < 5:\n", " print(i ** 0.5, end=' ')\n", " i += 1"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Python Idioms "]}, {"cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": ["lc = [i ** 2 for i in range(10)]"]}, {"cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [{"data": {"text/plain": ["[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"]}, "execution_count": 68, "metadata": {}, "output_type": "execute_result"}], "source": ["lc"]}, {"cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [{"data": {"text/plain": ["list"]}, "execution_count": 69, "metadata": {}, "output_type": "execute_result"}], "source": ["type(lc)"]}, {"cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [], "source": ["f = lambda x: math.cos(x)"]}, {"cell_type": "code", "execution_count": 71, "metadata": {"scrolled": true}, "outputs": [{"data": {"text/plain": ["0.2836621854632263"]}, "execution_count": 71, "metadata": {}, "output_type": "execute_result"}], "source": ["f(5)"]}, {"cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [{"data": {"text/plain": ["[1.0,\n", " 0.5403023058681398,\n", " -0.4161468365471424,\n", " -0.9899924966004454,\n", " -0.6536436208636119,\n", " 0.2836621854632263,\n", " 0.9601702866503661,\n", " 0.7539022543433046,\n", " -0.14550003380861354,\n", " -0.9111302618846769]"]}, "execution_count": 72, "metadata": {}, "output_type": "execute_result"}], "source": ["list(map(lambda x: math.cos(x), range(10)))"]}, {"cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [], "source": ["def f(x):\n", " return math.exp(x)"]}, {"cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [{"data": {"text/plain": ["148.4131591025766"]}, "execution_count": 74, "metadata": {}, "output_type": "execute_result"}], "source": ["f(5)"]}, {"cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [], "source": ["def f(*args):\n", " for arg in args:\n", " print(arg)\n", " return None"]}, {"cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["['a', 'b', 'c', 'd', 'e']\n"]}], "source": ["f(l)"]}, {"cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [], "source": ["import random"]}, {"cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [], "source": ["a = random.randint(0, 1000)"]}, {"cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Random number is 74\n"]}], "source": ["print(f'Random number is {a}')"]}, {"cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [], "source": ["def number_decide(number):\n", " if a < 10:\n", " return \"Number is single digit.\"\n", " elif 10 <= a < 100:\n", " return \"Number is double digit.\"\n", " else:\n", " return \"Number is triple digit.\""]}, {"cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [{"data": {"text/plain": ["'Number is double digit.'"]}, "execution_count": 81, "metadata": {}, "output_type": "execute_result"}], "source": ["number_decide(a)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# NumPy"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Regular ndarray Objects"]}, {"cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [], "source": ["import numpy as np"]}, {"cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [], "source": ["a = np.array(range(24))"]}, {"cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,\n", " 17, 18, 19, 20, 21, 22, 23])"]}, "execution_count": 84, "metadata": {}, "output_type": "execute_result"}], "source": ["a"]}, {"cell_type": "code", "execution_count": 85, "metadata": {}, "outputs": [], "source": ["b = a.reshape((4, 6))"]}, {"cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0, 1, 2, 3, 4, 5],\n", " [ 6, 7, 8, 9, 10, 11],\n", " [12, 13, 14, 15, 16, 17],\n", " [18, 19, 20, 21, 22, 23]])"]}, "execution_count": 86, "metadata": {}, "output_type": "execute_result"}], "source": ["b"]}, {"cell_type": "code", "execution_count": 87, "metadata": {}, "outputs": [], "source": ["c = a.reshape((2, 3, 4))"]}, {"cell_type": "code", "execution_count": 88, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[[ 0, 1, 2, 3],\n", " [ 4, 5, 6, 7],\n", " [ 8, 9, 10, 11]],\n", "\n", " [[12, 13, 14, 15],\n", " [16, 17, 18, 19],\n", " [20, 21, 22, 23]]])"]}, "execution_count": 88, "metadata": {}, "output_type": "execute_result"}], "source": ["c"]}, {"cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [], "source": ["b = np.array(b, dtype=np.float)"]}, {"cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0., 1., 2., 3., 4., 5.],\n", " [ 6., 7., 8., 9., 10., 11.],\n", " [12., 13., 14., 15., 16., 17.],\n", " [18., 19., 20., 21., 22., 23.]])"]}, "execution_count": 90, "metadata": {}, "output_type": "execute_result"}], "source": ["b"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Vectorized Operations"]}, {"cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0., 2., 4., 6., 8., 10.],\n", " [12., 14., 16., 18., 20., 22.],\n", " [24., 26., 28., 30., 32., 34.],\n", " [36., 38., 40., 42., 44., 46.]])"]}, "execution_count": 91, "metadata": {}, "output_type": "execute_result"}], "source": ["2 * b"]}, {"cell_type": "code", "execution_count": 92, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0., 1., 4., 9., 16., 25.],\n", " [ 36., 49., 64., 81., 100., 121.],\n", " [144., 169., 196., 225., 256., 289.],\n", " [324., 361., 400., 441., 484., 529.]])"]}, "execution_count": 92, "metadata": {}, "output_type": "execute_result"}], "source": ["b ** 2"]}, {"cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [], "source": ["f = lambda x: x ** 2 - 2 * x + 0.5"]}, {"cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 0.5, -0.5, 0.5, 3.5, 8.5, 15.5, 24.5, 35.5, 48.5,\n", " 63.5, 80.5, 99.5, 120.5, 143.5, 168.5, 195.5, 224.5, 255.5,\n", " 288.5, 323.5, 360.5, 399.5, 440.5, 483.5])"]}, "execution_count": 94, "metadata": {}, "output_type": "execute_result"}], "source": ["f(a)"]}, {"cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([2, 3, 4, 5])"]}, "execution_count": 95, "metadata": {}, "output_type": "execute_result"}], "source": ["a[2:6]"]}, {"cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [{"data": {"text/plain": ["16.0"]}, "execution_count": 96, "metadata": {}, "output_type": "execute_result"}], "source": ["b[2, 4]"]}, {"cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 8., 9.],\n", " [14., 15.]])"]}, "execution_count": 97, "metadata": {}, "output_type": "execute_result"}], "source": ["b[1:3, 2:4]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Boolean Operations"]}, {"cell_type": "code", "execution_count": 98, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[False, False, False, False, False, False],\n", " [False, False, False, False, False, True],\n", " [ True, True, True, True, True, True],\n", " [ True, True, True, True, True, True]])"]}, "execution_count": 98, "metadata": {}, "output_type": "execute_result"}], "source": ["b > 10"]}, {"cell_type": "code", "execution_count": 99, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23.])"]}, "execution_count": 99, "metadata": {}, "output_type": "execute_result"}], "source": ["b[b > 10]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## `ndarray` Methods and NumPy Functions"]}, {"cell_type": "code", "execution_count": 100, "metadata": {}, "outputs": [{"data": {"text/plain": ["276"]}, "execution_count": 100, "metadata": {}, "output_type": "execute_result"}], "source": ["a.sum()"]}, {"cell_type": "code", "execution_count": 101, "metadata": {}, "outputs": [{"data": {"text/plain": ["11.5"]}, "execution_count": 101, "metadata": {}, "output_type": "execute_result"}], "source": ["b.mean()"]}, {"cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 9., 10., 11., 12., 13., 14.])"]}, "execution_count": 102, "metadata": {}, "output_type": "execute_result"}], "source": ["b.mean(axis=0)"]}, {"cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 2.5, 8.5, 14.5, 20.5])"]}, "execution_count": 103, "metadata": {}, "output_type": "execute_result"}], "source": ["b.mean(axis=1)"]}, {"cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [{"data": {"text/plain": ["6.922186552431729"]}, "execution_count": 104, "metadata": {}, "output_type": "execute_result"}], "source": ["c.std()"]}, {"cell_type": "code", "execution_count": 105, "metadata": {}, "outputs": [{"data": {"text/plain": ["276"]}, "execution_count": 105, "metadata": {}, "output_type": "execute_result"}], "source": ["np.sum(a)"]}, {"cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 9., 10., 11., 12., 13., 14.])"]}, "execution_count": 106, "metadata": {}, "output_type": "execute_result"}], "source": ["np.mean(b, axis=0)"]}, {"cell_type": "code", "execution_count": 107, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0. , 0.84, 0.91, 0.14, -0.76, -0.96],\n", " [-0.28, 0.66, 0.99, 0.41, -0.54, -1. ],\n", " [-0.54, 0.42, 0.99, 0.65, -0.29, -0.96],\n", " [-0.75, 0.15, 0.91, 0.84, -0.01, -0.85]])"]}, "execution_count": 107, "metadata": {}, "output_type": "execute_result"}], "source": ["np.sin(b).round(2)"]}, {"cell_type": "code", "execution_count": 108, "metadata": {}, "outputs": [{"data": {"text/plain": ["-0.977530117665097"]}, "execution_count": 108, "metadata": {}, "output_type": "execute_result"}], "source": ["np.sin(4.5)"]}, {"cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["CPU times: user 1.21 s, sys: 24.1 ms, total: 1.23 s\n", "Wall time: 1.26 s\n"]}], "source": ["%time l = [np.sin(x) for x in range(1000000)]"]}, {"cell_type": "code", "execution_count": 110, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["CPU times: user 205 ms, sys: 19.7 ms, total: 225 ms\n", "Wall time: 223 ms\n"]}], "source": ["%time l = [math.sin(x) for x in range(1000000)]"]}, {"cell_type": "code", "execution_count": 111, "metadata": {"scrolled": true}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["CPU times: user 21.2 ms, sys: 4.77 ms, total: 26 ms\n", "Wall time: 25 ms\n"]}], "source": ["%time a = np.sin(np.arange(1000000))"]}, {"cell_type": "code", "execution_count": 112, "metadata": {}, "outputs": [], "source": ["import sys"]}, {"cell_type": "code", "execution_count": 113, "metadata": {}, "outputs": [{"data": {"text/plain": ["8000096"]}, "execution_count": 113, "metadata": {}, "output_type": "execute_result"}], "source": ["sys.getsizeof(a)"]}, {"cell_type": "code", "execution_count": 114, "metadata": {}, "outputs": [{"data": {"text/plain": ["8000000"]}, "execution_count": 114, "metadata": {}, "output_type": "execute_result"}], "source": ["a.nbytes"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## ndarray Creation"]}, {"cell_type": "code", "execution_count": 115, "metadata": {}, "outputs": [], "source": ["ai = np.arange(10)"]}, {"cell_type": "code", "execution_count": 116, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"]}, "execution_count": 116, "metadata": {}, "output_type": "execute_result"}], "source": ["ai"]}, {"cell_type": "code", "execution_count": 117, "metadata": {}, "outputs": [{"data": {"text/plain": ["dtype('int64')"]}, "execution_count": 117, "metadata": {}, "output_type": "execute_result"}], "source": ["ai.dtype"]}, {"cell_type": "code", "execution_count": 118, "metadata": {}, "outputs": [], "source": ["af = np.arange(0.5, 9.5, 0.5)"]}, {"cell_type": "code", "execution_count": 119, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. , 4.5, 5. , 5.5, 6. , 6.5,\n", " 7. , 7.5, 8. , 8.5, 9. ])"]}, "execution_count": 119, "metadata": {}, "output_type": "execute_result"}], "source": ["af"]}, {"cell_type": "code", "execution_count": 120, "metadata": {}, "outputs": [{"data": {"text/plain": ["dtype('float64')"]}, "execution_count": 120, "metadata": {}, "output_type": "execute_result"}], "source": ["af.dtype"]}, {"cell_type": "code", "execution_count": 121, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 0. , 0.90909091, 1.81818182, 2.72727273, 3.63636364,\n", " 4.54545455, 5.45454545, 6.36363636, 7.27272727, 8.18181818,\n", " 9.09090909, 10. ])"]}, "execution_count": 121, "metadata": {}, "output_type": "execute_result"}], "source": ["np.linspace(0, 10, 12)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Random Numbers"]}, {"cell_type": "code", "execution_count": 122, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([-2.1522647 , 2.13160089, 0.56002594, -0.79347248, -0.72049978,\n", " 2.53017257, -1.31409766, -3.32250941, -2.38801578, -1.53071788])"]}, "execution_count": 122, "metadata": {}, "output_type": "execute_result"}], "source": ["np.random.standard_normal(10) "]}, {"cell_type": "code", "execution_count": 123, "metadata": {"scrolled": true}, "outputs": [{"data": {"text/plain": ["array([0, 1, 2, 0, 1, 1, 0, 1, 0, 1])"]}, "execution_count": 123, "metadata": {}, "output_type": "execute_result"}], "source": ["np.random.poisson(0.5, 10)"]}, {"cell_type": "code", "execution_count": 124, "metadata": {}, "outputs": [], "source": ["np.random.seed(1000)"]}, {"cell_type": "code", "execution_count": 125, "metadata": {}, "outputs": [], "source": ["data = np.random.standard_normal((5, 100))"]}, {"cell_type": "code", "execution_count": 126, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[-0.8044583 , 0.32093155, -0.02548288],\n", " [-0.39031935, -0.58069634, 1.94898697],\n", " [-1.11573322, -1.34477121, 0.75334374],\n", " [ 0.42400699, -1.56680276, 0.76499895],\n", " [-1.74866738, -0.06913021, 1.52621653]])"]}, "execution_count": 126, "metadata": {}, "output_type": "execute_result"}], "source": ["data[:, :3]"]}, {"cell_type": "code", "execution_count": 127, "metadata": {}, "outputs": [{"data": {"text/plain": ["-0.02714981205311327"]}, "execution_count": 127, "metadata": {}, "output_type": "execute_result"}], "source": ["data.mean()"]}, {"cell_type": "code", "execution_count": 128, "metadata": {}, "outputs": [{"data": {"text/plain": ["1.0016799134894265"]}, "execution_count": 128, "metadata": {}, "output_type": "execute_result"}], "source": ["data.std()"]}, {"cell_type": "code", "execution_count": 129, "metadata": {}, "outputs": [], "source": ["data = data - data.mean()"]}, {"cell_type": "code", "execution_count": 130, "metadata": {}, "outputs": [{"data": {"text/plain": ["3.552713678800501e-18"]}, "execution_count": 130, "metadata": {}, "output_type": "execute_result"}], "source": ["data.mean()"]}, {"cell_type": "code", "execution_count": 131, "metadata": {}, "outputs": [], "source": ["data = data / data.std()"]}, {"cell_type": "code", "execution_count": 132, "metadata": {}, "outputs": [{"data": {"text/plain": ["1.0"]}, "execution_count": 132, "metadata": {}, "output_type": "execute_result"}], "source": ["data.std()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# matplotlib"]}, {"cell_type": "code", "execution_count": 133, "metadata": {}, "outputs": [], "source": ["import matplotlib.pyplot as plt"]}, {"cell_type": "code", "execution_count": 134, "metadata": {}, "outputs": [], "source": ["plt.style.use('seaborn')"]}, {"cell_type": "code", "execution_count": 135, "metadata": {}, "outputs": [], "source": ["import matplotlib as mpl"]}, {"cell_type": "code", "execution_count": 136, "metadata": {}, "outputs": [], "source": ["mpl.rcParams['font.family'] = 'serif'\n", "%matplotlib inline"]}, {"cell_type": "code", "execution_count": 137, "metadata": {}, "outputs": [], "source": ["data = np.random.standard_normal((5, 100))"]}, {"cell_type": "code", "execution_count": 138, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/ch10/OandaSMATrader.py b/ch10/OandaSMATrader.py new file mode 100644 index 0000000..e69de29 diff --git a/ch10/automated_strategy.py b/ch10/automated_strategy.py new file mode 100644 index 0000000..90a012d --- /dev/null +++ b/ch10/automated_strategy.py @@ -0,0 +1,144 @@ +# +# Automated ML-Based Trading Strategy for Oanda +# Online Algorithm, Logging, Monitoring +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# +import zmq +import tpqoa +import pickle +import numpy as np +import pandas as pd +import datetime as dt + +log_file = 'automated_strategy.log' + +# loads the persisted algorithm object +algorithm = pickle.load(open('algorithm.pkl', 'rb')) + +# sets up the socket communication via ZeroMQ (here: "publisher") +context = zmq.Context() +socket = context.socket(zmq.PUB) + +# this binds the socket communication to all IP addresses of the machine +socket.bind('tcp://0.0.0.0:5555') + +# recreating the log file +with open(log_file, 'w') as f: + f.write('*** NEW LOG FILE ***\n') + f.write(str(dt.datetime.now()) + '\n\n\n') + + +def logger_monitor(message, time=True, sep=True): + ''' Custom logger and monitor function. + ''' + with open(log_file, 'a') as f: + t = str(dt.datetime.now()) + msg = '' + if time: + msg += '\n' + t + '\n' + if sep: + msg += 80 * '=' + '\n' + msg += message + '\n\n' + # sends the message via the socket + socket.send_string(msg) + # writes the message to the log file + f.write(msg) + + +class MLTrader(tpqoa.tpqoa): + def __init__(self, config_file, algorithm): + super(MLTrader, self).__init__(config_file) + self.model = algorithm['model'] + self.mu = algorithm['mu'] + self.std = algorithm['std'] + self.units = 100000 + self.position = 0 + self.bar = '2s' + self.window = 2 + self.lags = 6 + self.min_length = self.lags + self.window + 1 + self.features = ['return', 'vol', 'mom', 'sma', 'min', 'max'] + self.raw_data = pd.DataFrame() + + def prepare_features(self): + self.data['return'] = np.log( + self.data['mid'] / self.data['mid'].shift(1)) + self.data['vol'] = self.data['return'].rolling(self.window).std() + self.data['mom'] = np.sign( + self.data['return'].rolling(self.window).mean()) + self.data['sma'] = self.data['mid'].rolling(self.window).mean() + self.data['min'] = self.data['mid'].rolling(self.window).min() + self.data['max'] = self.data['mid'].rolling(self.window).max() + self.data.dropna(inplace=True) + self.data[self.features] -= self.mu + self.data[self.features] /= self.std + self.cols = [] + for f in self.features: + for lag in range(1, self.lags + 1): + col = f'{f}_lag_{lag}' + self.data[col] = self.data[f].shift(lag) + self.cols.append(col) + + def report_trade(self, pos, order): + ''' Prints, logs and sends trade data. + ''' + out = '\n\n' + 80 * '=' + '\n' + out += '*** GOING {} *** \n'.format(pos) + '\n' + out += str(order) + '\n' + out += 80 * '=' + '\n' + logger_monitor(out) + print(out) + + def on_success(self, time, bid, ask): + print(self.ticks, 20 * ' ', end='\r') + df = pd.DataFrame({'bid': float(bid), 'ask': float(ask)}, + index=[pd.Timestamp(time).tz_localize(None)]) + self.raw_data = self.raw_data.append(df) + self.data = self.raw_data.resample( + self.bar, label='right').last().ffill() + self.data = self.data.iloc[:-1] + if len(self.data) > self.min_length: + logger_monitor('NUMBER OF TICKS: {} | '.format(self.ticks) + + 'NUMBER OF BARS: {}'.format(self.min_length)) + self.min_length += 1 + self.data['mid'] = (self.data['bid'] + self.data['ask']) / 2 + self.prepare_features() + features = self.data[self.cols].iloc[-1].values.reshape(1, -1) + signal = self.model.predict(features)[0] + # logs and sends major financial information + logger_monitor('MOST RECENT DATA\n' + + str(self.data[self.cols].tail()), + False) + logger_monitor('features:\n' + str(features) + '\n' + + 'position: ' + str(self.position) + '\n' + + 'signal: ' + str(signal), False) + if self.position in [0, -1] and signal == 1: # going long? + order = self.create_order(self.stream_instrument, + units=(1 - self.position) * + self.units, + suppress=True, ret=True) + self.report_trade('LONG', order) + self.position = 1 + elif self.position in [0, 1] and signal == -1: # going short? + order = self.create_order(self.stream_instrument, + units=-(1 + self.position) * + self.units, + suppress=True, ret=True) + self.report_trade('SHORT', order) + self.position = -1 + else: # no trade + logger_monitor('*** NO TRADE PLACED ***') + + logger_monitor('*** END OF CYCLE ***\n\n', False, False) + + +if __name__ == '__main__': + mlt = MLTrader('../pyalgo.cfg', algorithm) + mlt.stream_data('EUR_USD', stop=150) + order = mlt.create_order(mlt.stream_instrument, + units=-mlt.position * mlt.units, + suppress=True, ret=True) + mlt.position = 0 + mlt.report_trade('NEUTRAL', order) diff --git a/ch10/strategy_monitoring.py b/ch10/strategy_monitoring.py new file mode 100644 index 0000000..b9d850a --- /dev/null +++ b/ch10/strategy_monitoring.py @@ -0,0 +1,26 @@ +# +# Automated ML-Based Trading Strategy for Oanda +# Strategy Monitoring via Socket Communication +# +# Python for Algorithmic Trading +# (c) Dr. Yves J. Hilpisch +# +import zmq + +# sets up the socket communication via ZeroMQ (here: "subscriber") +context = zmq.Context() +socket = context.socket(zmq.SUB) + +# adjust the IP address to reflect the remote location +socket.connect('tcp://134.122.70.51:5555') + +# local IP address used for testing +# socket.connect('tcp://0.0.0.0:5555') + + +# configures the socket to retrieve every message +socket.setsockopt_string(zmq.SUBSCRIBE, '') + +while True: + msg = socket.recv_string() + print(msg) diff --git a/chA/A_pyalgo.ipynb b/chA/A_pyalgo.ipynb new file mode 100644 index 0000000..863fd67 --- /dev/null +++ b/chA/A_pyalgo.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python for Algorithmic Trading\n", "\n", "**Appendix A — Python, NumPy, pandas**"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Python Basics"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Data Types"]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["a = 3"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [{"data": {"text/plain": ["int"]}, "execution_count": 2, "metadata": {}, "output_type": "execute_result"}], "source": ["type(a)"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [{"data": {"text/plain": ["2"]}, "execution_count": 3, "metadata": {}, "output_type": "execute_result"}], "source": ["a.bit_length()"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": ["b = 5."]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [{"data": {"text/plain": ["float"]}, "execution_count": 5, "metadata": {}, "output_type": "execute_result"}], "source": ["type(b)"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": ["c = 10 ** 100"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"data": {"text/plain": ["10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000"]}, "execution_count": 7, "metadata": {}, "output_type": "execute_result"}], "source": ["c "]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [{"data": {"text/plain": ["333"]}, "execution_count": 8, "metadata": {}, "output_type": "execute_result"}], "source": ["c.bit_length()"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.6"]}, "execution_count": 9, "metadata": {}, "output_type": "execute_result"}], "source": ["3 / 5."]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"data": {"text/plain": ["15.0"]}, "execution_count": 10, "metadata": {}, "output_type": "execute_result"}], "source": ["a * b"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [{"data": {"text/plain": ["-2.0"]}, "execution_count": 11, "metadata": {}, "output_type": "execute_result"}], "source": ["a - b"]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [{"data": {"text/plain": ["8.0"]}, "execution_count": 12, "metadata": {}, "output_type": "execute_result"}], "source": ["b + a"]}, {"cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [{"data": {"text/plain": ["243.0"]}, "execution_count": 13, "metadata": {}, "output_type": "execute_result"}], "source": ["a ** b"]}, {"cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": ["import math"]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [{"data": {"text/plain": ["1.0986122886681098"]}, "execution_count": 15, "metadata": {}, "output_type": "execute_result"}], "source": ["math.log(a)"]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [{"data": {"text/plain": ["20.085536923187668"]}, "execution_count": 16, "metadata": {}, "output_type": "execute_result"}], "source": ["math.exp(a)"]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [{"data": {"text/plain": ["-0.9589242746631385"]}, "execution_count": 17, "metadata": {}, "output_type": "execute_result"}], "source": ["math.sin(b)"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": ["s = 'Python for Algorithmic Trading.'"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [{"data": {"text/plain": ["str"]}, "execution_count": 19, "metadata": {}, "output_type": "execute_result"}], "source": ["type(s)"]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [{"data": {"text/plain": ["'python for algorithmic trading.'"]}, "execution_count": 20, "metadata": {}, "output_type": "execute_result"}], "source": ["s.lower()"]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [{"data": {"text/plain": ["'PYTHON FOR ALGORITHMIC TRADING.'"]}, "execution_count": 21, "metadata": {}, "output_type": "execute_result"}], "source": ["s.upper()"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [{"data": {"text/plain": ["'Python'"]}, "execution_count": 22, "metadata": {}, "output_type": "execute_result"}], "source": ["s[0:6]"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": ["st = s[0:6] + s[-9:-1]"]}, {"cell_type": "code", "execution_count": 24, "metadata": {"scrolled": true}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Python Trading\n"]}], "source": ["print(st)"]}, {"cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": ["repl = 'My name is %s, I am %d years old and %4.2f m tall.'"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["My name is Gordon Gekko, I am 43 years old and 1.78 m tall.\n"]}], "source": ["print(repl % ('Gordon Gekko', 43, 1.78))"]}, {"cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": ["repl = 'My name is {:s}, I am {:d} years old and {:4.2f} m tall.' # <3>"]}, {"cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["My name is Gordon Gekko, I am 43 years old and 1.78 m tall.\n"]}], "source": ["print(repl.format('Gordon Gekko', 43, 1.78))"]}, {"cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": ["name, age, height = 'Gordon Gekko', 43, 1.78 # <5>"]}, {"cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["My name is Gordon Gekko, I am 43 years old and 1.78m tall.\n"]}], "source": ["print(f'My name is {name:s}, I am {age:d} years old and {height:4.2f}m tall.')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Data Structures"]}, {"cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": ["t1 = (a, b, st)"]}, {"cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [{"data": {"text/plain": ["(3, 5.0, 'Python Trading')"]}, "execution_count": 32, "metadata": {}, "output_type": "execute_result"}], "source": ["t1"]}, {"cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [{"data": {"text/plain": ["tuple"]}, "execution_count": 33, "metadata": {}, "output_type": "execute_result"}], "source": ["type(t1)"]}, {"cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": ["t2 = st, b, a"]}, {"cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [{"data": {"text/plain": ["('Python Trading', 5.0, 3)"]}, "execution_count": 35, "metadata": {}, "output_type": "execute_result"}], "source": ["t2"]}, {"cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [{"data": {"text/plain": ["tuple"]}, "execution_count": 36, "metadata": {}, "output_type": "execute_result"}], "source": ["type(t2)"]}, {"cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": ["t = (t1, t2)"]}, {"cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [{"data": {"text/plain": ["((3, 5.0, 'Python Trading'), ('Python Trading', 5.0, 3))"]}, "execution_count": 38, "metadata": {}, "output_type": "execute_result"}], "source": ["t"]}, {"cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [{"data": {"text/plain": ["'Python Trading'"]}, "execution_count": 39, "metadata": {}, "output_type": "execute_result"}], "source": ["t[0][2]"]}, {"cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": ["l = [a, b, st]"]}, {"cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [{"data": {"text/plain": ["[3, 5.0, 'Python Trading']"]}, "execution_count": 41, "metadata": {}, "output_type": "execute_result"}], "source": ["l"]}, {"cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [{"data": {"text/plain": ["list"]}, "execution_count": 42, "metadata": {}, "output_type": "execute_result"}], "source": ["type(l)"]}, {"cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [], "source": ["l.append(s.split()[3])"]}, {"cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [{"data": {"text/plain": ["[3, 5.0, 'Python Trading', 'Trading.']"]}, "execution_count": 44, "metadata": {}, "output_type": "execute_result"}], "source": ["l"]}, {"cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": ["l = list(('Z', 'Q', 'D', 'J', 'E', 'H', '5.', 'a'))"]}, {"cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [{"data": {"text/plain": ["['Z', 'Q', 'D', 'J', 'E', 'H', '5.', 'a']"]}, "execution_count": 46, "metadata": {}, "output_type": "execute_result"}], "source": ["l"]}, {"cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [], "source": ["l.sort()"]}, {"cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [{"data": {"text/plain": ["['5.', 'D', 'E', 'H', 'J', 'Q', 'Z', 'a']"]}, "execution_count": 48, "metadata": {}, "output_type": "execute_result"}], "source": ["l"]}, {"cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [], "source": ["d = {'int_obj': a, 'float_obj': b, 'string_obj': st}"]}, {"cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [{"data": {"text/plain": ["dict"]}, "execution_count": 50, "metadata": {}, "output_type": "execute_result"}], "source": ["type(d)"]}, {"cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [{"data": {"text/plain": ["{'int_obj': 3, 'float_obj': 5.0, 'string_obj': 'Python Trading'}"]}, "execution_count": 51, "metadata": {}, "output_type": "execute_result"}], "source": ["d"]}, {"cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [{"data": {"text/plain": ["5.0"]}, "execution_count": 52, "metadata": {}, "output_type": "execute_result"}], "source": ["d['float_obj']"]}, {"cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [], "source": ["d['int_obj_long'] = 10 ** 20"]}, {"cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [{"data": {"text/plain": ["{'int_obj': 3,\n", " 'float_obj': 5.0,\n", " 'string_obj': 'Python Trading',\n", " 'int_obj_long': 100000000000000000000}"]}, "execution_count": 54, "metadata": {}, "output_type": "execute_result"}], "source": ["d"]}, {"cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [{"data": {"text/plain": ["dict_keys(['int_obj', 'float_obj', 'string_obj', 'int_obj_long'])"]}, "execution_count": 55, "metadata": {}, "output_type": "execute_result"}], "source": ["d.keys()"]}, {"cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [{"data": {"text/plain": ["dict_values([3, 5.0, 'Python Trading', 100000000000000000000])"]}, "execution_count": 56, "metadata": {}, "output_type": "execute_result"}], "source": ["d.values()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Control Structures"]}, {"cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [{"data": {"text/plain": ["range(0, 5)"]}, "execution_count": 57, "metadata": {}, "output_type": "execute_result"}], "source": ["range(5)"]}, {"cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [{"data": {"text/plain": ["range(3, 15, 2)"]}, "execution_count": 58, "metadata": {}, "output_type": "execute_result"}], "source": ["range(3, 15, 2)"]}, {"cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["0 1 4 9 16 "]}], "source": ["for i in range(5):\n", " print(i ** 2, end=' ')"]}, {"cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["3 5 7 9 11 13 "]}], "source": ["for i in range(3, 15, 2):\n", " print(i, end=' ')"]}, {"cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [], "source": ["l = ['a', 'b', 'c', 'd', 'e']"]}, {"cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["a\n", "b\n", "c\n", "d\n", "e\n"]}], "source": ["for _ in l:\n", " print(_)"]}, {"cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": ["s = 'Python Trading'"]}, {"cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["P|y|t|h|o|n| |T|r|a|d|i|n|g|"]}], "source": ["for c in s:\n", " print(c + '|', end='')"]}, {"cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [], "source": ["i = 0"]}, {"cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["0.0 1.0 1.4142135623730951 1.7320508075688772 2.0 "]}], "source": ["while i < 5:\n", " print(i ** 0.5, end=' ')\n", " i += 1"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Python Idioms "]}, {"cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": ["lc = [i ** 2 for i in range(10)]"]}, {"cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [{"data": {"text/plain": ["[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"]}, "execution_count": 68, "metadata": {}, "output_type": "execute_result"}], "source": ["lc"]}, {"cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [{"data": {"text/plain": ["list"]}, "execution_count": 69, "metadata": {}, "output_type": "execute_result"}], "source": ["type(lc)"]}, {"cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [], "source": ["f = lambda x: math.cos(x)"]}, {"cell_type": "code", "execution_count": 71, "metadata": {"scrolled": true}, "outputs": [{"data": {"text/plain": ["0.2836621854632263"]}, "execution_count": 71, "metadata": {}, "output_type": "execute_result"}], "source": ["f(5)"]}, {"cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [{"data": {"text/plain": ["[1.0,\n", " 0.5403023058681398,\n", " -0.4161468365471424,\n", " -0.9899924966004454,\n", " -0.6536436208636119,\n", " 0.2836621854632263,\n", " 0.9601702866503661,\n", " 0.7539022543433046,\n", " -0.14550003380861354,\n", " -0.9111302618846769]"]}, "execution_count": 72, "metadata": {}, "output_type": "execute_result"}], "source": ["list(map(lambda x: math.cos(x), range(10)))"]}, {"cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [], "source": ["def f(x):\n", " return math.exp(x)"]}, {"cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [{"data": {"text/plain": ["148.4131591025766"]}, "execution_count": 74, "metadata": {}, "output_type": "execute_result"}], "source": ["f(5)"]}, {"cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [], "source": ["def f(*args):\n", " for arg in args:\n", " print(arg)\n", " return None"]}, {"cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["['a', 'b', 'c', 'd', 'e']\n"]}], "source": ["f(l)"]}, {"cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [], "source": ["import random"]}, {"cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [], "source": ["a = random.randint(0, 1000)"]}, {"cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Random number is 74\n"]}], "source": ["print(f'Random number is {a}')"]}, {"cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [], "source": ["def number_decide(number):\n", " if a < 10:\n", " return \"Number is single digit.\"\n", " elif 10 <= a < 100:\n", " return \"Number is double digit.\"\n", " else:\n", " return \"Number is triple digit.\""]}, {"cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [{"data": {"text/plain": ["'Number is double digit.'"]}, "execution_count": 81, "metadata": {}, "output_type": "execute_result"}], "source": ["number_decide(a)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# NumPy"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Regular ndarray Objects"]}, {"cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [], "source": ["import numpy as np"]}, {"cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [], "source": ["a = np.array(range(24))"]}, {"cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,\n", " 17, 18, 19, 20, 21, 22, 23])"]}, "execution_count": 84, "metadata": {}, "output_type": "execute_result"}], "source": ["a"]}, {"cell_type": "code", "execution_count": 85, "metadata": {}, "outputs": [], "source": ["b = a.reshape((4, 6))"]}, {"cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0, 1, 2, 3, 4, 5],\n", " [ 6, 7, 8, 9, 10, 11],\n", " [12, 13, 14, 15, 16, 17],\n", " [18, 19, 20, 21, 22, 23]])"]}, "execution_count": 86, "metadata": {}, "output_type": "execute_result"}], "source": ["b"]}, {"cell_type": "code", "execution_count": 87, "metadata": {}, "outputs": [], "source": ["c = a.reshape((2, 3, 4))"]}, {"cell_type": "code", "execution_count": 88, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[[ 0, 1, 2, 3],\n", " [ 4, 5, 6, 7],\n", " [ 8, 9, 10, 11]],\n", "\n", " [[12, 13, 14, 15],\n", " [16, 17, 18, 19],\n", " [20, 21, 22, 23]]])"]}, "execution_count": 88, "metadata": {}, "output_type": "execute_result"}], "source": ["c"]}, {"cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [], "source": ["b = np.array(b, dtype=np.float)"]}, {"cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0., 1., 2., 3., 4., 5.],\n", " [ 6., 7., 8., 9., 10., 11.],\n", " [12., 13., 14., 15., 16., 17.],\n", " [18., 19., 20., 21., 22., 23.]])"]}, "execution_count": 90, "metadata": {}, "output_type": "execute_result"}], "source": ["b"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Vectorized Operations"]}, {"cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0., 2., 4., 6., 8., 10.],\n", " [12., 14., 16., 18., 20., 22.],\n", " [24., 26., 28., 30., 32., 34.],\n", " [36., 38., 40., 42., 44., 46.]])"]}, "execution_count": 91, "metadata": {}, "output_type": "execute_result"}], "source": ["2 * b"]}, {"cell_type": "code", "execution_count": 92, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0., 1., 4., 9., 16., 25.],\n", " [ 36., 49., 64., 81., 100., 121.],\n", " [144., 169., 196., 225., 256., 289.],\n", " [324., 361., 400., 441., 484., 529.]])"]}, "execution_count": 92, "metadata": {}, "output_type": "execute_result"}], "source": ["b ** 2"]}, {"cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [], "source": ["f = lambda x: x ** 2 - 2 * x + 0.5"]}, {"cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 0.5, -0.5, 0.5, 3.5, 8.5, 15.5, 24.5, 35.5, 48.5,\n", " 63.5, 80.5, 99.5, 120.5, 143.5, 168.5, 195.5, 224.5, 255.5,\n", " 288.5, 323.5, 360.5, 399.5, 440.5, 483.5])"]}, "execution_count": 94, "metadata": {}, "output_type": "execute_result"}], "source": ["f(a)"]}, {"cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([2, 3, 4, 5])"]}, "execution_count": 95, "metadata": {}, "output_type": "execute_result"}], "source": ["a[2:6]"]}, {"cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [{"data": {"text/plain": ["16.0"]}, "execution_count": 96, "metadata": {}, "output_type": "execute_result"}], "source": ["b[2, 4]"]}, {"cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 8., 9.],\n", " [14., 15.]])"]}, "execution_count": 97, "metadata": {}, "output_type": "execute_result"}], "source": ["b[1:3, 2:4]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Boolean Operations"]}, {"cell_type": "code", "execution_count": 98, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[False, False, False, False, False, False],\n", " [False, False, False, False, False, True],\n", " [ True, True, True, True, True, True],\n", " [ True, True, True, True, True, True]])"]}, "execution_count": 98, "metadata": {}, "output_type": "execute_result"}], "source": ["b > 10"]}, {"cell_type": "code", "execution_count": 99, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23.])"]}, "execution_count": 99, "metadata": {}, "output_type": "execute_result"}], "source": ["b[b > 10]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## `ndarray` Methods and NumPy Functions"]}, {"cell_type": "code", "execution_count": 100, "metadata": {}, "outputs": [{"data": {"text/plain": ["276"]}, "execution_count": 100, "metadata": {}, "output_type": "execute_result"}], "source": ["a.sum()"]}, {"cell_type": "code", "execution_count": 101, "metadata": {}, "outputs": [{"data": {"text/plain": ["11.5"]}, "execution_count": 101, "metadata": {}, "output_type": "execute_result"}], "source": ["b.mean()"]}, {"cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 9., 10., 11., 12., 13., 14.])"]}, "execution_count": 102, "metadata": {}, "output_type": "execute_result"}], "source": ["b.mean(axis=0)"]}, {"cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 2.5, 8.5, 14.5, 20.5])"]}, "execution_count": 103, "metadata": {}, "output_type": "execute_result"}], "source": ["b.mean(axis=1)"]}, {"cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [{"data": {"text/plain": ["6.922186552431729"]}, "execution_count": 104, "metadata": {}, "output_type": "execute_result"}], "source": ["c.std()"]}, {"cell_type": "code", "execution_count": 105, "metadata": {}, "outputs": [{"data": {"text/plain": ["276"]}, "execution_count": 105, "metadata": {}, "output_type": "execute_result"}], "source": ["np.sum(a)"]}, {"cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 9., 10., 11., 12., 13., 14.])"]}, "execution_count": 106, "metadata": {}, "output_type": "execute_result"}], "source": ["np.mean(b, axis=0)"]}, {"cell_type": "code", "execution_count": 107, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0. , 0.84, 0.91, 0.14, -0.76, -0.96],\n", " [-0.28, 0.66, 0.99, 0.41, -0.54, -1. ],\n", " [-0.54, 0.42, 0.99, 0.65, -0.29, -0.96],\n", " [-0.75, 0.15, 0.91, 0.84, -0.01, -0.85]])"]}, "execution_count": 107, "metadata": {}, "output_type": "execute_result"}], "source": ["np.sin(b).round(2)"]}, {"cell_type": "code", "execution_count": 108, "metadata": {}, "outputs": [{"data": {"text/plain": ["-0.977530117665097"]}, "execution_count": 108, "metadata": {}, "output_type": "execute_result"}], "source": ["np.sin(4.5)"]}, {"cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["CPU times: user 1.21 s, sys: 24.1 ms, total: 1.23 s\n", "Wall time: 1.26 s\n"]}], "source": ["%time l = [np.sin(x) for x in range(1000000)]"]}, {"cell_type": "code", "execution_count": 110, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["CPU times: user 205 ms, sys: 19.7 ms, total: 225 ms\n", "Wall time: 223 ms\n"]}], "source": ["%time l = [math.sin(x) for x in range(1000000)]"]}, {"cell_type": "code", "execution_count": 111, "metadata": {"scrolled": true}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["CPU times: user 21.2 ms, sys: 4.77 ms, total: 26 ms\n", "Wall time: 25 ms\n"]}], "source": ["%time a = np.sin(np.arange(1000000))"]}, {"cell_type": "code", "execution_count": 112, "metadata": {}, "outputs": [], "source": ["import sys"]}, {"cell_type": "code", "execution_count": 113, "metadata": {}, "outputs": [{"data": {"text/plain": ["8000096"]}, "execution_count": 113, "metadata": {}, "output_type": "execute_result"}], "source": ["sys.getsizeof(a)"]}, {"cell_type": "code", "execution_count": 114, "metadata": {}, "outputs": [{"data": {"text/plain": ["8000000"]}, "execution_count": 114, "metadata": {}, "output_type": "execute_result"}], "source": ["a.nbytes"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## ndarray Creation"]}, {"cell_type": "code", "execution_count": 115, "metadata": {}, "outputs": [], "source": ["ai = np.arange(10)"]}, {"cell_type": "code", "execution_count": 116, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"]}, "execution_count": 116, "metadata": {}, "output_type": "execute_result"}], "source": ["ai"]}, {"cell_type": "code", "execution_count": 117, "metadata": {}, "outputs": [{"data": {"text/plain": ["dtype('int64')"]}, "execution_count": 117, "metadata": {}, "output_type": "execute_result"}], "source": ["ai.dtype"]}, {"cell_type": "code", "execution_count": 118, "metadata": {}, "outputs": [], "source": ["af = np.arange(0.5, 9.5, 0.5)"]}, {"cell_type": "code", "execution_count": 119, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. , 4.5, 5. , 5.5, 6. , 6.5,\n", " 7. , 7.5, 8. , 8.5, 9. ])"]}, "execution_count": 119, "metadata": {}, "output_type": "execute_result"}], "source": ["af"]}, {"cell_type": "code", "execution_count": 120, "metadata": {}, "outputs": [{"data": {"text/plain": ["dtype('float64')"]}, "execution_count": 120, "metadata": {}, "output_type": "execute_result"}], "source": ["af.dtype"]}, {"cell_type": "code", "execution_count": 121, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 0. , 0.90909091, 1.81818182, 2.72727273, 3.63636364,\n", " 4.54545455, 5.45454545, 6.36363636, 7.27272727, 8.18181818,\n", " 9.09090909, 10. ])"]}, "execution_count": 121, "metadata": {}, "output_type": "execute_result"}], "source": ["np.linspace(0, 10, 12)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Random Numbers"]}, {"cell_type": "code", "execution_count": 122, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([-2.1522647 , 2.13160089, 0.56002594, -0.79347248, -0.72049978,\n", " 2.53017257, -1.31409766, -3.32250941, -2.38801578, -1.53071788])"]}, "execution_count": 122, "metadata": {}, "output_type": "execute_result"}], "source": ["np.random.standard_normal(10) "]}, {"cell_type": "code", "execution_count": 123, "metadata": {"scrolled": true}, "outputs": [{"data": {"text/plain": ["array([0, 1, 2, 0, 1, 1, 0, 1, 0, 1])"]}, "execution_count": 123, "metadata": {}, "output_type": "execute_result"}], "source": ["np.random.poisson(0.5, 10)"]}, {"cell_type": "code", "execution_count": 124, "metadata": {}, "outputs": [], "source": ["np.random.seed(1000)"]}, {"cell_type": "code", "execution_count": 125, "metadata": {}, "outputs": [], "source": ["data = np.random.standard_normal((5, 100))"]}, {"cell_type": "code", "execution_count": 126, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[-0.8044583 , 0.32093155, -0.02548288],\n", " [-0.39031935, -0.58069634, 1.94898697],\n", " [-1.11573322, -1.34477121, 0.75334374],\n", " [ 0.42400699, -1.56680276, 0.76499895],\n", " [-1.74866738, -0.06913021, 1.52621653]])"]}, "execution_count": 126, "metadata": {}, "output_type": "execute_result"}], "source": ["data[:, :3]"]}, {"cell_type": "code", "execution_count": 127, "metadata": {}, "outputs": [{"data": {"text/plain": ["-0.02714981205311327"]}, "execution_count": 127, "metadata": {}, "output_type": "execute_result"}], "source": ["data.mean()"]}, {"cell_type": "code", "execution_count": 128, "metadata": {}, "outputs": [{"data": {"text/plain": ["1.0016799134894265"]}, "execution_count": 128, "metadata": {}, "output_type": "execute_result"}], "source": ["data.std()"]}, {"cell_type": "code", "execution_count": 129, "metadata": {}, "outputs": [], "source": ["data = data - data.mean()"]}, {"cell_type": "code", "execution_count": 130, "metadata": {}, "outputs": [{"data": {"text/plain": ["3.552713678800501e-18"]}, "execution_count": 130, "metadata": {}, "output_type": "execute_result"}], "source": ["data.mean()"]}, {"cell_type": "code", "execution_count": 131, "metadata": {}, "outputs": [], "source": ["data = data / data.std()"]}, {"cell_type": "code", "execution_count": 132, "metadata": {}, "outputs": [{"data": {"text/plain": ["1.0"]}, "execution_count": 132, "metadata": {}, "output_type": "execute_result"}], "source": ["data.std()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# matplotlib"]}, {"cell_type": "code", "execution_count": 133, "metadata": {}, "outputs": [], "source": ["import matplotlib.pyplot as plt"]}, {"cell_type": "code", "execution_count": 134, "metadata": {}, "outputs": [], "source": ["plt.style.use('seaborn')"]}, {"cell_type": "code", "execution_count": 135, "metadata": {}, "outputs": [], "source": ["import matplotlib as mpl"]}, {"cell_type": "code", "execution_count": 136, "metadata": {}, "outputs": [], "source": ["mpl.rcParams['font.family'] = 'serif'\n", "%matplotlib inline"]}, {"cell_type": "code", "execution_count": 137, "metadata": {}, "outputs": [], "source": ["data = np.random.standard_normal((5, 100))"]}, {"cell_type": "code", "execution_count": 138, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6))\n", "plt.plot(data.cumsum())\n", "# plt.savefig('../../images/chA/plot_01.png');"]}, {"cell_type": "code", "execution_count": 139, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6));\n", "plt.plot(data.T.cumsum(axis=0), label='line')\n", "plt.legend(loc=0);\n", "plt.xlabel('data point')\n", "plt.ylabel('value');\n", "plt.title('random series');\n", "# plt.savefig('../../images/chA/plot_02.png');"]}, {"cell_type": "code", "execution_count": 140, "metadata": {}, "outputs": [{"data": {"image/png": "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\n", "text/plain": ["
"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6))\n", "plt.hist(data.flatten(), bins=30);\n", "# plt.savefig('../../images/chA/plot_03.png');"]}, {"cell_type": "code", "execution_count": 141, "metadata": {}, "outputs": [{"data": {"image/png": "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\n", "text/plain": ["
"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6))\n", "plt.bar(np.arange(1, 12) - 0.25,\n", " data[0, :11], width=0.5);\n", "# plt.savefig('../../images/chA/plot_04.png');"]}, {"cell_type": "code", "execution_count": 142, "metadata": {}, "outputs": [], "source": ["x = np.arange(len(data.cumsum()))"]}, {"cell_type": "code", "execution_count": 143, "metadata": {}, "outputs": [], "source": ["y = 0.2 * data.cumsum() ** 2 # <2>"]}, {"cell_type": "code", "execution_count": 144, "metadata": {}, "outputs": [], "source": ["rg1 = np.polyfit(x, y, 1)"]}, {"cell_type": "code", "execution_count": 145, "metadata": {}, "outputs": [], "source": ["rg3 = np.polyfit(x, y, 3)"]}, {"cell_type": "code", "execution_count": 146, "metadata": {}, "outputs": [], "source": ["rg9 = np.polyfit(x, y, 9)"]}, {"cell_type": "code", "execution_count": 147, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", 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| 2022-04-30 | \n", "-0.732239 | \n", "0.207433 | \n", "0.152912 | \n", "
| 2022-05-31 | \n", "-1.928309 | \n", "-0.198527 | \n", "-0.029466 | \n", "
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| 2022-10-31 | \n", "-0.723832 | \n", "-0.206284 | \n", "2.310688 | \n", "
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| 2022-03-31 | \n", "-0.267572 | \n", "-0.459848 | \n", "0.959027 | \n", "
| 2022-04-30 | \n", "-0.732239 | \n", "0.207433 | \n", "0.152912 | \n", "
| 2022-05-31 | \n", "-1.928309 | \n", "-0.198527 | \n", "-0.029466 | \n", "
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| 2022-06-30 | \n", "-1.825116 | \n", "-0.336949 | \n", "0.676227 | \n", "
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| 2022-08-31 | \n", "-0.652803 | \n", "-0.916504 | \n", "1.260779 | \n", "
| 2022-09-30 | \n", "-0.340685 | \n", "0.616657 | \n", "0.710605 | \n", "
| 2022-10-31 | \n", "-0.723832 | \n", "-0.206284 | \n", "2.310688 | \n", "
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"], "text/plain": [" no1 no2 no3\n", "count 10.000000 10.000000 10.000000\n", "mean -0.798847 -0.227665 0.672067\n", "std 0.607430 0.578071 0.712430\n", "min -1.928309 -1.323696 -0.029466\n", "25% -0.786404 -0.429123 0.200031\n", "50% -0.688317 -0.202406 0.520109\n", "75% -0.393844 0.160609 0.896922\n", "max -0.160134 0.616657 2.310688"]}, "execution_count": 160, "metadata": {}, "output_type": "execute_result"}], "source": ["df.describe()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Numerical Operations"]}, {"cell_type": "code", "execution_count": 161, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": [" no1 no2 no3\n", "2022-01-31 -1.608917 0.641863 -0.050966\n", "2022-02-28 -0.320269 0.040270 0.727983\n", "2022-03-31 -0.535144 -0.919696 1.918054\n", "2022-04-30 -1.464479 0.414866 0.305823\n", "2022-05-31 -3.856618 -0.397054 -0.058932\n", "2022-06-30 -3.650232 -0.673898 1.352453\n", "2022-07-31 -1.106642 -2.647393 0.682782\n", "2022-08-31 -1.305605 -1.833009 2.521557\n", "2022-09-30 -0.681369 1.233314 1.421210\n", "2022-10-31 -1.447664 -0.412568 4.621376\n"]}], "source": ["print(df * 2)"]}, {"cell_type": "code", "execution_count": 162, "metadata": {}, "outputs": [{"data": {"text/plain": ["no1 0.607430\n", "no2 0.578071\n", "no3 0.712430\n", "dtype: float64"]}, "execution_count": 162, "metadata": {}, "output_type": "execute_result"}], "source": ["df.std()"]}, {"cell_type": "code", "execution_count": 163, "metadata": {}, "outputs": [{"data": {"text/plain": ["no1 -0.798847\n", "no2 -0.227665\n", "no3 0.672067\n", "dtype: float64"]}, "execution_count": 163, "metadata": {}, "output_type": "execute_result"}], "source": ["df.mean()"]}, {"cell_type": "code", "execution_count": 164, "metadata": {}, "outputs": [{"data": {"text/plain": ["2022-01-31 -0.169670\n", "2022-02-28 0.074664\n", "2022-03-31 0.077202\n", "2022-04-30 -0.123965\n", "2022-05-31 -0.718767\n", "2022-06-30 -0.495280\n", "2022-07-31 -0.511875\n", "2022-08-31 -0.102843\n", "2022-09-30 0.328859\n", "2022-10-31 0.460191\n", "Freq: M, dtype: float64"]}, "execution_count": 164, "metadata": {}, "output_type": "execute_result"}], "source": ["df.mean(axis=1)"]}, {"cell_type": "code", "execution_count": 165, "metadata": {}, "outputs": [{"data": {"text/plain": ["no1 -0.798847\n", "no2 -0.227665\n", "no3 0.672067\n", "dtype: float64"]}, "execution_count": 165, "metadata": {}, "output_type": "execute_result"}], "source": ["np.mean(df)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Data Selection"]}, {"cell_type": "code", "execution_count": 166, "metadata": {}, "outputs": [{"data": {"text/plain": ["2022-01-31 0.320932\n", "2022-02-28 0.020135\n", "2022-03-31 -0.459848\n", "2022-04-30 0.207433\n", "2022-05-31 -0.198527\n", "2022-06-30 -0.336949\n", "2022-07-31 -1.323696\n", "2022-08-31 -0.916504\n", "2022-09-30 0.616657\n", "2022-10-31 -0.206284\n", "Freq: M, Name: no2, dtype: float64"]}, "execution_count": 166, "metadata": {}, "output_type": "execute_result"}], "source": ["df['no2']"]}, {"cell_type": "code", "execution_count": 167, "metadata": {}, "outputs": [{"data": {"text/plain": ["no1 -0.804458\n", "no2 0.320932\n", "no3 -0.025483\n", "Name: 2022-01-31 00:00:00, dtype: float64"]}, "execution_count": 167, "metadata": {}, "output_type": "execute_result"}], "source": ["df.iloc[0]"]}, {"cell_type": "code", "execution_count": 168, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | no1 | \n", "no2 | \n", "no3 | \n", "
|---|---|---|---|
| count | \n", "10.000000 | \n", "10.000000 | \n", "10.000000 | \n", "
| mean | \n", "-0.798847 | \n", "-0.227665 | \n", "0.672067 | \n", "
| std | \n", "0.607430 | \n", "0.578071 | \n", "0.712430 | \n", "
| min | \n", "-1.928309 | \n", "-1.323696 | \n", "-0.029466 | \n", "
| 25% | \n", "-0.786404 | \n", "-0.429123 | \n", "0.200031 | \n", "
| 50% | \n", "-0.688317 | \n", "-0.202406 | \n", "0.520109 | \n", "
| 75% | \n", "-0.393844 | \n", "0.160609 | \n", "0.896922 | \n", "
| max | \n", "-0.160134 | \n", "0.616657 | \n", "2.310688 | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" no1 no2 no3\n", "2022-03-31 -0.267572 -0.459848 0.959027\n", "2022-04-30 -0.732239 0.207433 0.152912"]}, "execution_count": 168, "metadata": {}, "output_type": "execute_result"}], "source": ["df.iloc[2:4]"]}, {"cell_type": "code", "execution_count": 169, "metadata": {}, "outputs": [{"data": {"text/plain": ["2022-03-31 -0.459848\n", "2022-04-30 0.207433\n", "Freq: M, Name: no2, dtype: float64"]}, "execution_count": 169, "metadata": {}, "output_type": "execute_result"}], "source": ["df.iloc[2:4, 1]"]}, {"cell_type": "code", "execution_count": 170, "metadata": {}, "outputs": [{"data": {"text/plain": ["2022-04-30 0.152912\n", "2022-05-31 -0.029466\n", "2022-06-30 0.676227\n", "2022-07-31 0.341391\n", "Freq: M, Name: no3, dtype: float64"]}, "execution_count": 170, "metadata": {}, "output_type": "execute_result"}], "source": ["df.no3.iloc[3:7]"]}, {"cell_type": "code", "execution_count": 171, "metadata": {}, "outputs": [{"data": {"text/plain": ["no1 -0.267572\n", "no2 -0.459848\n", "no3 0.959027\n", "Name: 2022-03-31 00:00:00, dtype: float64"]}, "execution_count": 171, "metadata": {}, "output_type": "execute_result"}], "source": ["df.loc['2022-3-31']"]}, {"cell_type": "code", "execution_count": 172, "metadata": {}, "outputs": [{"data": {"text/plain": ["-0.02946577492329111"]}, "execution_count": 172, "metadata": {}, "output_type": "execute_result"}], "source": ["df.loc['2022-5-31', 'no3']"]}, {"cell_type": "code", "execution_count": 173, "metadata": {}, "outputs": [{"data": {"text/plain": ["2022-01-31 -0.880907\n", "2022-02-28 0.931841\n", "2022-03-31 2.609510\n", "2022-04-30 -0.273505\n", "2022-05-31 -2.016706\n", "2022-06-30 0.203564\n", "2022-07-31 0.470852\n", "2022-08-31 3.129533\n", "2022-09-30 1.791130\n", "2022-10-31 6.208233\n", "Freq: M, dtype: float64"]}, "execution_count": 173, "metadata": {}, "output_type": "execute_result"}], "source": ["df['no1'] + 3 * df['no3']"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Boolean Operations"]}, {"cell_type": "code", "execution_count": 174, "metadata": {}, "outputs": [{"data": {"text/plain": ["2022-01-31 False\n", "2022-02-28 False\n", "2022-03-31 True\n", "2022-04-30 False\n", "2022-05-31 False\n", "2022-06-30 True\n", "2022-07-31 False\n", "2022-08-31 True\n", "2022-09-30 True\n", "2022-10-31 True\n", "Freq: M, Name: no3, dtype: bool"]}, "execution_count": 174, "metadata": {}, "output_type": "execute_result"}], "source": ["df['no3'] > 0.5"]}, {"cell_type": "code", "execution_count": 175, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | no1 | \n", "no2 | \n", "no3 | \n", "
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| 2022-03-31 | \n", "-0.267572 | \n", "-0.459848 | \n", "0.959027 | \n", "
| 2022-04-30 | \n", "-0.732239 | \n", "0.207433 | \n", "0.152912 | \n", "
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"], "text/plain": [" no1 no2 no3\n", "2022-03-31 -0.267572 -0.459848 0.959027\n", "2022-06-30 -1.825116 -0.336949 0.676227\n", "2022-08-31 -0.652803 -0.916504 1.260779\n", "2022-09-30 -0.340685 0.616657 0.710605\n", "2022-10-31 -0.723832 -0.206284 2.310688"]}, "execution_count": 175, "metadata": {}, "output_type": "execute_result"}], "source": ["df[df['no3'] > 0.5]"]}, {"cell_type": "code", "execution_count": 176, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | no1 | \n", "no2 | \n", "no3 | \n", "
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| 2022-03-31 | \n", "-0.267572 | \n", "-0.459848 | \n", "0.959027 | \n", "
| 2022-06-30 | \n", "-1.825116 | \n", "-0.336949 | \n", "0.676227 | \n", "
| 2022-08-31 | \n", "-0.652803 | \n", "-0.916504 | \n", "1.260779 | \n", "
| 2022-09-30 | \n", "-0.340685 | \n", "0.616657 | \n", "0.710605 | \n", "
| 2022-10-31 | \n", "-0.723832 | \n", "-0.206284 | \n", "2.310688 | \n", "
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"], "text/plain": [" no1 no2 no3\n", "2022-09-30 -0.340685 0.616657 0.710605\n", "2022-10-31 -0.723832 -0.206284 2.310688"]}, "execution_count": 176, "metadata": {}, "output_type": "execute_result"}], "source": ["df[(df.no3 > 0.5) & (df.no2 > -0.25)]"]}, {"cell_type": "code", "execution_count": 177, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | no1 | \n", "no2 | \n", "no3 | \n", "
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| 2022-09-30 | \n", "-0.340685 | \n", "0.616657 | \n", "0.710605 | \n", "
| 2022-10-31 | \n", "-0.723832 | \n", "-0.206284 | \n", "2.310688 | \n", "
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"], "text/plain": [" no1 no2 no3\n", "2022-05-31 -1.928309 -0.198527 -0.029466\n", "2022-06-30 -1.825116 -0.336949 0.676227\n", "2022-07-31 -0.553321 -1.323696 0.341391\n", "2022-08-31 -0.652803 -0.916504 1.260779\n", "2022-09-30 -0.340685 0.616657 0.710605\n", "2022-10-31 -0.723832 -0.206284 2.310688"]}, "execution_count": 177, "metadata": {}, "output_type": "execute_result"}], "source": ["df[df.index > '2022-5-15']"]}, {"cell_type": "code", "execution_count": 178, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["| \n", " | no1 | \n", "no2 | \n", "no3 | \n", "
|---|---|---|---|
| 2022-05-31 | \n", "-1.928309 | \n", "-0.198527 | \n", "-0.029466 | \n", "
| 2022-06-30 | \n", "-1.825116 | \n", "-0.336949 | \n", "0.676227 | \n", "
| 2022-07-31 | \n", "-0.553321 | \n", "-1.323696 | \n", "0.341391 | \n", "
| 2022-08-31 | \n", "-0.652803 | \n", "-0.916504 | \n", "1.260779 | \n", "
| 2022-09-30 | \n", "-0.340685 | \n", "0.616657 | \n", "0.710605 | \n", "
| 2022-10-31 | \n", "-0.723832 | \n", "-0.206284 | \n", "2.310688 | \n", "
"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["df.plot(figsize=(10, 6))\n", "# plt.savefig('../../images/chA/plot_06.png');"]}, {"cell_type": "code", "execution_count": 179, "metadata": {}, "outputs": [], "source": ["index = ['2022-01-31', '2022-02-28', '2022-03-31', '2022-04-30',\n", " '2022-05-31', '2022-06-30', '2022-07-31', '2022-08-31',\n", " '2022-09-30', '2022-10-31']"]}, {"cell_type": "code", "execution_count": 180, "metadata": {}, "outputs": [{"data": {"text/plain": ["DatetimeIndex(['2022-01-31', '2022-02-28', '2022-03-31', '2022-04-30',\n", " '2022-05-31', '2022-06-30', '2022-07-31', '2022-08-31',\n", " '2022-09-30', '2022-10-31'],\n", " dtype='datetime64[ns]', freq='M')"]}, "execution_count": 180, "metadata": {}, "output_type": "execute_result"}], "source": ["pd.DatetimeIndex(df.index)"]}, {"cell_type": "code", "execution_count": 181, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["df.hist(figsize=(10, 6));\n", "# plt.savefig('../../images/chA/plot_07.png');"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Input-Output Operations"]}, {"cell_type": "code", "execution_count": 182, "metadata": {}, "outputs": [], "source": ["df.to_csv('data.csv')"]}, {"cell_type": "code", "execution_count": 183, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": [",no1,no2,no3\n", "2022-01-31,-0.8044583035248052,0.3209315470898572,-0.025482880472072204\n", "2022-02-28,-0.16013447509799061,0.020134874302836725,0.363991673815235\n", "2022-03-31,-0.26757177678888727,-0.4598482010579319,0.9590271758917923\n", "2022-04-30,-0.7322393029842283,0.2074331059300848,0.15291156544935125\n", "2022-05-31,-1.9283091368170622,-0.19852705542997268,-0.02946577492329111\n", "2022-06-30,-1.8251162427820806,-0.33694904401573555,0.6762266000356951\n", "2022-07-31,-0.5533209663746153,-1.3236963728130973,0.34139114682415433\n", "2022-08-31,-0.6528026643843922,-0.9165042724715742,1.2607786860286034\n", "2022-09-30,-0.34068465431802875,0.6166567928863607,0.7106048210003031\n", "2022-10-31,-0.7238320652023266,-0.20628417055270565,2.310688189060956\n"]}], "source": ["with open('data.csv') as f:\n", " for line in f.readlines():\n", " print(line, end='')"]}, {"cell_type": "code", "execution_count": 184, "metadata": {}, "outputs": [], "source": ["from_csv = pd.read_csv('data.csv',\n", " index_col=0,\n", " parse_dates=True)"]}, {"cell_type": "code", "execution_count": 185, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "File path: data.h5"]}, "execution_count": 188, "metadata": {}, "output_type": "execute_result"}], "source": ["h5"]}, {"cell_type": "code", "execution_count": 189, "metadata": {}, "outputs": [], "source": ["from_h5 = h5['df']"]}, {"cell_type": "code", "execution_count": 190, "metadata": {}, "outputs": [], "source": ["h5.close()"]}, {"cell_type": "code", "execution_count": 191, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "DatetimeIndex: 2516 entries, 2010-01-04 to 2019-12-31\n", "Data columns (total 1 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 .SPX 2516 non-null float64\n", "dtypes: float64(1)\n", "memory usage: 39.3 KB\n"]}], "source": ["spx.info()"]}, {"cell_type": "code", "execution_count": 196, "metadata": {}, "outputs": [], "source": ["vix = pd.DataFrame(raw['.VIX'])"]}, {"cell_type": "code", "execution_count": 197, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "DatetimeIndex: 2516 entries, 2010-01-04 to 2019-12-31\n", "Data columns (total 1 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 .VIX 2516 non-null float64\n", "dtypes: float64(1)\n", "memory usage: 39.3 KB\n"]}], "source": ["vix.info()"]}, {"cell_type": "code", "execution_count": 198, "metadata": {}, "outputs": [], "source": ["spxvix = pd.DataFrame(spx).join(vix)"]}, {"cell_type": "code", "execution_count": 199, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "DatetimeIndex: 2516 entries, 2010-01-04 to 2019-12-31\n", "Data columns (total 2 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 .SPX 2516 non-null float64\n", " 1 .VIX 2516 non-null float64\n", "dtypes: float64(2)\n", "memory usage: 139.0 KB\n"]}], "source": ["spxvix.info()"]}, {"cell_type": "code", "execution_count": 200, "metadata": {}, "outputs": [], "source": ["spxvix = pd.merge(spx, vix,\n", " left_index=True, # merge on left index\n", " right_index=True, # merge on right index\n", " )"]}, {"cell_type": "code", "execution_count": 201, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "DatetimeIndex: 2516 entries, 2010-01-04 to 2019-12-31\n", "Data columns (total 2 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 .SPX 2516 non-null float64\n", " 1 .VIX 2516 non-null float64\n", "dtypes: float64(2)\n", "memory usage: 139.0 KB\n"]}], "source": ["spxvix.info()"]}, {"cell_type": "code", "execution_count": 202, "metadata": {}, "outputs": [], "source": ["spxvix = pd.DataFrame({'SPX': spx['.SPX'],\n", " 'VIX': vix['.VIX']},\n", " index=spx.index)"]}, {"cell_type": "code", "execution_count": 203, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "DatetimeIndex: 2516 entries, 2010-01-04 to 2019-12-31\n", "Data columns (total 2 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 SPX 2516 non-null float64\n", " 1 VIX 2516 non-null float64\n", "dtypes: float64(2)\n", "memory usage: 139.0 KB\n"]}], "source": ["spxvix.info()"]}, {"cell_type": "code", "execution_count": 204, "metadata": {"scrolled": true}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" no1 no2 no3\n", "2022-01-31 -0.804458 0.320932 -0.025483\n", "2022-02-28 -0.160134 0.020135 0.363992\n", "2022-03-31 -0.267572 -0.459848 0.959027\n", "2022-04-30 -0.732239 0.207433 0.152912\n", "2022-05-31 -1.928309 -0.198527 -0.029466"]}, "execution_count": 185, "metadata": {}, "output_type": "execute_result"}], "source": ["from_csv.head() # <6>"]}, {"cell_type": "code", "execution_count": 186, "metadata": {}, "outputs": [], "source": ["h5 = pd.HDFStore('data.h5', 'w')"]}, {"cell_type": "code", "execution_count": 187, "metadata": {}, "outputs": [], "source": ["h5['df'] = df"]}, {"cell_type": "code", "execution_count": 188, "metadata": {}, "outputs": [{"data": {"text/plain": ["| \n", " | no1 | \n", "no2 | \n", "no3 | \n", "
|---|---|---|---|
| 2022-01-31 | \n", "-0.804458 | \n", "0.320932 | \n", "-0.025483 | \n", "
| 2022-02-28 | \n", "-0.160134 | \n", "0.020135 | \n", "0.363992 | \n", "
| 2022-03-31 | \n", "-0.267572 | \n", "-0.459848 | \n", "0.959027 | \n", "
| 2022-04-30 | \n", "-0.732239 | \n", "0.207433 | \n", "0.152912 | \n", "
| 2022-05-31 | \n", "-1.928309 | \n", "-0.198527 | \n", "-0.029466 | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" no1 no2 no3\n", "2022-06-30 -1.825116 -0.336949 0.676227\n", "2022-07-31 -0.553321 -1.323696 0.341391\n", "2022-08-31 -0.652803 -0.916504 1.260779\n", "2022-09-30 -0.340685 0.616657 0.710605\n", "2022-10-31 -0.723832 -0.206284 2.310688"]}, "execution_count": 191, "metadata": {}, "output_type": "execute_result"}], "source": ["from_h5.tail()"]}, {"cell_type": "code", "execution_count": 192, "metadata": {}, "outputs": [], "source": ["!rm data.csv data.h5 # <7>"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Case Study"]}, {"cell_type": "code", "execution_count": 193, "metadata": {}, "outputs": [], "source": ["raw = pd.read_csv('http://hilpisch.com/pyalgo_eikon_eod_data.csv',\n", " index_col=0, parse_dates=True).dropna()"]}, {"cell_type": "code", "execution_count": 194, "metadata": {}, "outputs": [], "source": ["spx = pd.DataFrame(raw['.SPX'])"]}, {"cell_type": "code", "execution_count": 195, "metadata": {"scrolled": true}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["| \n", " | no1 | \n", "no2 | \n", "no3 | \n", "
|---|---|---|---|
| 2022-06-30 | \n", "-1.825116 | \n", "-0.336949 | \n", "0.676227 | \n", "
| 2022-07-31 | \n", "-0.553321 | \n", "-1.323696 | \n", "0.341391 | \n", "
| 2022-08-31 | \n", "-0.652803 | \n", "-0.916504 | \n", "1.260779 | \n", "
| 2022-09-30 | \n", "-0.340685 | \n", "0.616657 | \n", "0.710605 | \n", "
| 2022-10-31 | \n", "-0.723832 | \n", "-0.206284 | \n", "2.310688 | \n", "
"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["spxvix.plot(figsize=(10, 6), subplots=True);\n", "# plt.savefig('../../images/chA/example_01.png');"]}, {"cell_type": "code", "execution_count": 205, "metadata": {}, "outputs": [], "source": ["rets = np.log(spxvix / spxvix.shift(1))"]}, {"cell_type": "code", "execution_count": 206, "metadata": {}, "outputs": [], "source": ["rets = rets.dropna()"]}, {"cell_type": "code", "execution_count": 207, "metadata": {}, "outputs": [{"data": {"text/html": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["rets.plot(kind='scatter', x='SPX', y='VIX',\n", " style='.', figsize=(10, 6))\n", "plt.plot(rets['SPX'], np.polyval(rg, rets['SPX']), 'r-');\n", "# plt.savefig('../../images/chA/example_02.png');"]}, {"cell_type": "code", "execution_count": 210, "metadata": {}, "outputs": [], "source": ["ret = rets.mean() * 252"]}, {"cell_type": "code", "execution_count": 211, "metadata": {}, "outputs": [{"data": {"text/plain": ["SPX 0.104995\n", "VIX -0.037526\n", "dtype: float64"]}, "execution_count": 211, "metadata": {}, "output_type": "execute_result"}], "source": ["ret"]}, {"cell_type": "code", "execution_count": 212, "metadata": {}, "outputs": [], "source": ["vol = rets.std() * math.sqrt(252)"]}, {"cell_type": "code", "execution_count": 213, "metadata": {}, "outputs": [{"data": {"text/plain": ["SPX 0.147902\n", "VIX 1.229086\n", "dtype: float64"]}, "execution_count": 213, "metadata": {}, "output_type": "execute_result"}], "source": ["vol"]}, {"cell_type": "code", "execution_count": 214, "metadata": {}, "outputs": [{"data": {"text/plain": ["SPX 0.642279\n", "VIX -0.038667\n", "dtype: float64"]}, "execution_count": 214, "metadata": {}, "output_type": "execute_result"}], "source": ["(ret - 0.01) / vol"]}, {"cell_type": "code", "execution_count": 215, "metadata": {"scrolled": true}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["plt.figure(figsize=(10, 6))\n", "spxvix['SPX'].plot(label='S&P 500')\n", "spxvix['SPX'].cummax().plot(label='running maximum')\n", "plt.legend(loc=0);\n", "# plt.savefig('../../images/chA/example_03.png');"]}, {"cell_type": "code", "execution_count": 216, "metadata": {}, "outputs": [], "source": ["adrawdown = spxvix['SPX'].cummax() - spxvix['SPX']"]}, {"cell_type": "code", "execution_count": 217, "metadata": {}, "outputs": [{"data": {"text/plain": ["579.6500000000001"]}, "execution_count": 217, "metadata": {}, "output_type": "execute_result"}], "source": ["adrawdown.max()"]}, {"cell_type": "code", "execution_count": 218, "metadata": {}, "outputs": [], "source": ["rdrawdown = ((spxvix['SPX'].cummax() - spxvix['SPX']) /\n", " spxvix['SPX'].cummax())"]}, {"cell_type": "code", "execution_count": 219, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.1977821376780688"]}, "execution_count": 219, "metadata": {}, "output_type": "execute_result"}], "source": ["rdrawdown.max()"]}, {"cell_type": "code", "execution_count": 220, "metadata": {}, "outputs": [], "source": ["temp = adrawdown[adrawdown == 0]"]}, {"cell_type": "code", "execution_count": 221, "metadata": {}, "outputs": [], "source": ["periods_spx = (temp.index[1:].to_pydatetime() -\n", " temp.index[:-1].to_pydatetime())"]}, {"cell_type": "code", "execution_count": 222, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([datetime.timedelta(days=67), datetime.timedelta(days=1),\n", " datetime.timedelta(days=1), datetime.timedelta(days=1),\n", " datetime.timedelta(days=301), datetime.timedelta(days=3),\n", " datetime.timedelta(days=1), datetime.timedelta(days=2),\n", " datetime.timedelta(days=12), datetime.timedelta(days=2)],\n", " dtype=object)"]}, "execution_count": 222, "metadata": {}, "output_type": "execute_result"}], "source": ["periods_spx[50:60]"]}, {"cell_type": "code", "execution_count": 223, "metadata": {}, "outputs": [{"data": {"text/plain": ["datetime.timedelta(days=417)"]}, "execution_count": 223, "metadata": {}, "output_type": "execute_result"}], "source": ["max(periods_spx)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["
\n", "\n", "http://tpq.io | @dyjh | training@tpq.io"]}], "metadata": {"anaconda-cloud": {}, "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6"}}, "nbformat": 4, "nbformat_minor": 4} \ No newline at end of file diff --git a/data/AAPL.csv b/data/AAPL.csv new file mode 100644 index 0000000..2c0728f --- /dev/null +++ b/data/AAPL.csv @@ -0,0 +1,22 @@ +Date,HIGH,CLOSE,LOW,OPEN,COUNT,VOLUME +2020-04-01,248.72,240.91,239.13,246.5,460606.0,44054638.0 +2020-04-02,245.15,244.93,236.9,240.34,380294.0,41483493.0 +2020-04-03,245.7,241.41,238.9741,242.8,293699.0,32470017.0 +2020-04-06,263.11,262.47,249.38,250.9,486681.0,50455071.0 +2020-04-07,271.7,259.43,259.0,270.8,467375.0,50721831.0 +2020-04-08,267.37,266.07,261.23,262.74,391246.0,42223821.0 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\n", "
"], "text/plain": [" SPX VIX\n", "Date \n", "2010-01-05 0.003111 -0.035038\n", "2010-01-06 0.000545 -0.009868\n", "2010-01-07 0.003993 -0.005233\n", "2010-01-08 0.002878 -0.050024\n", "2010-01-11 0.001745 -0.032514"]}, "execution_count": 207, "metadata": {}, "output_type": "execute_result"}], "source": ["rets.head()"]}, {"cell_type": "code", "execution_count": 208, "metadata": {}, "outputs": [], "source": ["rg = np.polyfit(rets['SPX'], rets['VIX'], 1)"]}, {"cell_type": "code", "execution_count": 209, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": ["| \n", " | SPX | \n", "VIX | \n", "
|---|---|---|
| Date | \n", "\n", " | \n", " |
| 2010-01-05 | \n", "0.003111 | \n", "-0.035038 | \n", "
| 2010-01-06 | \n", "0.000545 | \n", "-0.009868 | \n", "
| 2010-01-07 | \n", "0.003993 | \n", "-0.005233 | \n", "
| 2010-01-08 | \n", "0.002878 | \n", "-0.050024 | \n", "
| 2010-01-11 | \n", "0.001745 | \n", "-0.032514 | \n", "
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