From 7c5b52520165833b709a9658ebc578a1ac955b14 Mon Sep 17 00:00:00 2001 From: mamahfouz Date: Mon, 17 Jun 2019 13:41:38 +0100 Subject: [PATCH 1/3] market replay changes --- README.md | 15 +- agent/ExchangeAgent.py | 23 +- agent/ExperimentalAgent.py | 35 + agent/MarketReplayAgent.py | 113 ++ agent/TradingAgent.py | 13 +- agent/__init__.py | 0 config/__init__.py | 0 config/impact.py | 1 - config/marketreplay.py | 146 ++ ...MarketReplayAgentAnalysis-checkpoint.ipynb | 423 +++++ .../OrderBookOracle-checkpoint.ipynb | 1357 +++++++++++++++++ notebooks/MarketReplayAgentAnalysis.ipynb | 423 +++++ notebooks/OrderBookOracle.ipynb | 1313 ++++++++++++++++ util/OrderBook.py | 51 + util/__init__.py | 0 util/oracle/OrderBookOracle.py | 269 ++++ util/oracle/__init__.py | 0 util/order/LimitOrder.py | 22 +- util/order/Order.py | 11 +- util/order/__init__.py | 0 util/util.py | 7 + 21 files changed, 4203 insertions(+), 19 deletions(-) create mode 100644 agent/ExperimentalAgent.py create mode 100644 agent/MarketReplayAgent.py create mode 100644 agent/__init__.py create mode 100644 config/__init__.py create mode 100644 config/marketreplay.py create mode 100644 notebooks/.ipynb_checkpoints/MarketReplayAgentAnalysis-checkpoint.ipynb create mode 100644 notebooks/.ipynb_checkpoints/OrderBookOracle-checkpoint.ipynb create mode 100644 notebooks/MarketReplayAgentAnalysis.ipynb create mode 100644 notebooks/OrderBookOracle.ipynb create mode 100644 util/__init__.py create mode 100644 util/oracle/OrderBookOracle.py create mode 100644 util/oracle/__init__.py create mode 100644 util/order/__init__.py diff --git a/README.md b/README.md index c55fe734d..9b8863b5d 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,21 @@ +# ABIDES: Agent-Based Interactive Discrete Event Simulation environment + +> ABIDES is an Agent-Based Interactive Discrete Event Simulation environment. ABIDES is designed from the ground up to support AI agent research in market applications. While simulations are certainly available within trading firms for their own internal use, there are no broadly available high-fidelity market simulation environments. We hope that the availability of such a platform will facilitate AI research in this important area. ABIDES currently enables the simulation of tens of thousands of trading agents interacting with an exchange agent to facilitate transactions. It supports configurable pairwise network latencies between each individual agent as well as the exchange. Our simulator's message-based design is modeled after NASDAQ's published equity trading protocols ITCH and OUCH. + Please see our arXiv paper for preliminary documentation: https://arxiv.org/abs/1904.12066 - Please see the wiki for tutorials and example configurations: https://github.com/abides-sim/abides/wiki + +## Quickstart +``` +mkdir project +cd project + +git clone https://github.com/abides-sim/abides.git +cd abides +pip install -r requirements.txt +``` \ No newline at end of file diff --git a/agent/ExchangeAgent.py b/agent/ExchangeAgent.py index fcc6f0658..e307f43bd 100644 --- a/agent/ExchangeAgent.py +++ b/agent/ExchangeAgent.py @@ -115,8 +115,11 @@ def kernelTerminating (self): quotes = sorted(dfLog.index.get_level_values(1).unique()) min_quote = quotes[0] max_quote = quotes[-1] - quotes = range(min_quote, max_quote+1) - + try: + quotes = range(min_quote, max_quote+1) + except Exception as e: + quotes = np.arange(min_quote, max_quote + 0.01, step=0.01) + # Restructure the log to have multi-level rows of all possible pairs of time and quote # with volume as the only column. filledIndex = pd.MultiIndex.from_product([time_idx, quotes], names=['time','quote']) @@ -260,6 +263,22 @@ def receiveMessage (self, currentTime, msg): else: # Hand the order to the order book for processing. self.order_books[order.symbol].cancelOrder(deepcopy(order)) + elif msg.body['msg'] == 'MODIFY_ORDER': + order = msg.body['order'] + new_order = msg.body['new_order'] + log_print ("{} received MODIFY_ORDER: {}, new order: {}".format(self.name, order, new_order)) + if order.symbol not in self.order_books: + log_print ("Modification request discarded. Unknown symbol: {}".format(order.symbol)) + else: + self.order_books[order.symbol].modifyOrder(deepcopy(order), deepcopy(new_order)) + elif msg.body['msg'] == 'REPLICATE_ORDERBOOK_SNAPSHOT': + timestamp = msg.body['timestamp'] + symbol = msg.body['symbol'] + log_print ("{} received REPLICATE_ORDERBOOK_SNAPSHOT for t= {}".format(self.name, timestamp)) + if symbol not in self.order_books: + log_print ("Orderbook replication request discarded. Unknown symbol: {}".format(symbol)) + else: + self.order_books[symbol].replicateOrderbookSnapshot() def sendMessage (self, recipientID, msg): diff --git a/agent/ExperimentalAgent.py b/agent/ExperimentalAgent.py new file mode 100644 index 000000000..2258b8284 --- /dev/null +++ b/agent/ExperimentalAgent.py @@ -0,0 +1,35 @@ +import pandas as pd + +from agent.TradingAgent import TradingAgent + + +class ExperimentalAgent(TradingAgent): + + def __init__(self, id, name, symbol, + startingCash, execution_timestamp, quantity, is_buy_order, limit_price, + random_state = None): + super().__init__(id, name, startingCash, random_state) + self.symbol = symbol + self.execution_timestamp = execution_timestamp + self.quantity = quantity + self.is_buy_order = is_buy_order + self.limit_price = limit_price + self.timestamp = pd.Timestamp("2012-06-21 09:30:02") + + def kernelStarting(self, startTime): + super().kernelStarting(startTime) + + def wakeup(self, currentTime): + super().wakeup(currentTime) + self.last_trade[self.symbol] = 0 + if not self.mkt_open or not self.mkt_close: + return + elif (currentTime > self.mkt_open) and (currentTime < self.mkt_close): + if currentTime == self.execution_timestamp: + self.placeLimitOrder(self.symbol, self.quantity, self.is_buy_order, self.limit_price, dollar=False) + + def receiveMessage(self, currentTime, msg): + super().receiveMessage(currentTime, msg) + + def getWakeFrequency(self): + return self.execution_timestamp - self.mkt_open diff --git a/agent/MarketReplayAgent.py b/agent/MarketReplayAgent.py new file mode 100644 index 000000000..eb27bd4ad --- /dev/null +++ b/agent/MarketReplayAgent.py @@ -0,0 +1,113 @@ +import pandas as pd + +from agent.TradingAgent import TradingAgent +from util.util import log_print +from util.order.LimitOrder import LimitOrder +from message.Message import Message + +class MarketReplayAgent(TradingAgent): + + + def __init__(self, id, name, symbol, date, startingCash, log_orders = False, random_state = None): + super().__init__(id, name, startingCash, random_state) + self.symbol = symbol + self.date = date + self.log_orders = log_orders + + + def kernelStarting(self, startTime): + super().kernelStarting(startTime) + self.oracle = self.kernel.oracle + + + def wakeup (self, currentTime): + super().wakeup(currentTime) + self.last_trade[self.symbol] = self.oracle.getDailyOpenPrice(self.symbol, self.mkt_open) + if not self.mkt_open or not self.mkt_close: + return + elif currentTime == self.oracle.orderbook_df.iloc[0].name: + order = self.oracle.trades_df.loc[self.oracle.trades_df.timestamp == currentTime] + self.placeMktOpenOrders(order, t=currentTime) + self.setWakeup(self.oracle.trades_df.loc[self.oracle.trades_df.timestamp > currentTime].iloc[0].timestamp) + elif (currentTime > self.mkt_open) and (currentTime < self.mkt_close): + try: + order = self.oracle.trades_df.loc[self.oracle.trades_df.timestamp == currentTime] + self.placeOrder(currentTime, order) + self.setWakeup(self.oracle.trades_df.loc[self.oracle.trades_df.timestamp > currentTime].iloc[0].timestamp) + except Exception as e: + log_print(e) + + + def receiveMessage (self, currentTime, msg): + super().receiveMessage(currentTime, msg) + + + def placeMktOpenOrders(self, snapshot_order, t=0): + orders_snapshot = self.oracle.orderbook_df.loc[self.oracle.orderbook_df.index == t].T + for i in range(0, len(orders_snapshot) - 1, 4): + ask_price = orders_snapshot.iloc[i][0] + ask_vol = orders_snapshot.iloc[i + 1][0] + bid_price = orders_snapshot.iloc[i + 2][0] + bid_vol = orders_snapshot.iloc[i + 3][0] + + if snapshot_order.direction.item() == 'BUY' and bid_price == snapshot_order.price.item(): + bid_vol -= snapshot_order.vol.item() + elif snapshot_order.direction.item() == 'SELL' and ask_price == snapshot_order.price.item(): + ask_vol -= snapshot_order.vol.item() + + self.placeLimitOrder(self.symbol, bid_vol, True, float(bid_price), dollar=False) + self.placeLimitOrder(self.symbol, ask_vol, False, float(ask_price), dollar=False) + self.placeOrder(snapshot_order.timestamp.item(), snapshot_order) + + + def placeOrder(self, currentTime, order): + if len(order) == 1: + type = order.type.item() + id = order.order_id.item() + direction = order.direction.item() + price = order.price.item() + vol = order.vol.item() + if type == 'NEW': + self.placeLimitOrder(self.symbol, vol, direction == 'BUY', float(price), dollar=False, order_id=id) + elif type in ['CANCELLATION', 'PARTIAL_CANCELLATION']: + existing_order = self.orders.get(id) + if existing_order: + if type == 'CANCELLATION': + self.cancelOrder(existing_order) + elif type == 'PARTIAL_CANCELLATION': + new_order = LimitOrder(self.id, currentTime, self.symbol, vol, direction == 'BUY', float(price), + dollar=False, order_id=id) + self.modifyOrder(existing_order, new_order) + else: + self.replicateOrderbookSnapshot(currentTime) + elif type in ['EXECUTE_VISIBLE', 'EXECUTE_HIDDEN']: + existing_order = self.orders.get(id) + if existing_order: + if existing_order.quantity == vol: + self.cancelOrder(existing_order) + else: + new_vol = existing_order.quantity - vol + if new_vol == 0: + self.cancelOrder(existing_order) + else: + executed_order = LimitOrder(self.id, currentTime, self.symbol, new_vol, direction == 'BUY', float(price), + dollar=False, order_id=id) + self.modifyOrder(existing_order, executed_order) + self.orders.get(id).quantity = new_vol + else: + self.replicateOrderbookSnapshot(currentTime) + else: + orders = self.oracle.trades_df.loc[self.oracle.trades_df.timestamp == currentTime] + for index, order in orders.iterrows(): + self.placeOrder(currentTime, order = pd.DataFrame(order).T) + + + def replicateOrderbookSnapshot(self, currentTime): + log_print("Received notification of orderbook snapshot replication at: {}".format(currentTime)) + self.sendMessage(self.exchangeID, Message({"msg": "REPLICATE_ORDERBOOK_SNAPSHOT", "sender": self.id, + "symbol": self.symbol, "timestamp": str(currentTime)})) + if self.log_orders: self.logEvent('REPLICATE_ORDERBOOK_SNAPSHOT', currentTime) + + + def getWakeFrequency(self): + return self.oracle.trades_df.iloc[0].timestamp - self.mkt_open \ No newline at end of file diff --git a/agent/TradingAgent.py b/agent/TradingAgent.py index 8b1c9d740..52285f753 100644 --- a/agent/TradingAgent.py +++ b/agent/TradingAgent.py @@ -253,8 +253,8 @@ def getOrderStream (self, symbol, length=1): # Used by any Trading Agent subclass to place a limit order. Parameters expect: # string (valid symbol), int (positive share quantity), bool (True == BUY), int (price in cents). - def placeLimitOrder (self, symbol, quantity, is_buy_order, limit_price, ignore_risk = False): - order = LimitOrder(self.id, self.currentTime, symbol, quantity, is_buy_order, limit_price) + def placeLimitOrder (self, symbol, quantity, is_buy_order, limit_price, dollar=True, order_id=None, ignore_risk = False): + order = LimitOrder(self.id, self.currentTime, symbol, quantity, is_buy_order, limit_price, dollar, order_id) if quantity > 0: # Test if this order can be permitted given our at-risk limits. @@ -299,6 +299,15 @@ def cancelOrder (self, order): # Log this activity. if self.log_orders: self.logEvent('CANCEL_SUBMITTED', js.dump(order)) + # Used by any Trading Agent subclass to modify any existing limitorder. The order must currently + # appear in the agent's open orders list. + def modifyOrder (self, order, newOrder): + self.sendMessage(self.exchangeID, Message({ "msg" : "MODIFY_ORDER", "sender": self.id, + "order" : order, "new_order" : newOrder})) + + # Log this activity. + if self.log_orders: self.logEvent('MODIFY_ORDER', js.dump(order)) + # Handles ORDER_EXECUTED messages from an exchange agent. Subclasses may wish to extend, # but should still call parent method for basic portfolio/returns tracking. diff --git a/agent/__init__.py b/agent/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/config/__init__.py b/config/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/config/impact.py b/config/impact.py index 8e2258b18..08ed60e66 100644 --- a/config/impact.py +++ b/config/impact.py @@ -7,7 +7,6 @@ from util.oracle.MeanRevertingOracle import MeanRevertingOracle from util import util -import datetime as dt import numpy as np import pandas as pd import sys diff --git a/config/marketreplay.py b/config/marketreplay.py new file mode 100644 index 000000000..53ad88563 --- /dev/null +++ b/config/marketreplay.py @@ -0,0 +1,146 @@ +from Kernel import Kernel + +from agent.MarketReplayAgent import MarketReplayAgent +from agent.ExchangeAgent import ExchangeAgent +from agent.ExperimentalAgent import ExperimentalAgent +from util.oracle.OrderBookOracle import OrderBookOracle + +from util import util +from util.order import LimitOrder + +import datetime as dt +import numpy as np +import pandas as pd +import sys +import argparse + +parser = argparse.ArgumentParser(description='Options for Market Replay Agent Config.') + +# General Config for all agents +parser.add_argument('-c', '--config', required=True, + help='Name of config file to execute') +parser.add_argument('-s', '--seed', type=int, default=None, + help='numpy.random.seed() for simulation') +parser.add_argument('-l', '--log_dir', default=None, + help='Log directory name (default: unix timestamp at program start)') +parser.add_argument('-v', '--verbose', action='store_true', + help='Maximum verbosity!') +parser.add_argument('-o', '--log_orders', action='store_true', + help='Log every order-related action by every agent.') +parser.add_argument('--config_help', action='store_true', + help='Print argument options for this config file') + +args, remaining_args = parser.parse_known_args() + +log_orders = args.log_orders + +if args.config_help: + parser.print_help() + sys.exit() + +# Simulation Start Time +simulation_start_time = dt.datetime.now() +print ("Simulation Start Time: {}".format(simulation_start_time)) + +# Random Seed Config +seed = args.seed +if not seed: seed = int(pd.Timestamp.now().timestamp() * 1000000) % (2**32 - 1) +np.random.seed(seed) +print ("Configuration seed: {}".format(seed)) + +random_state = np.random.RandomState(seed=np.random.randint(low=1)) + +util.silent_mode = not args.verbose +LimitOrder.silent_mode = not args.verbose +print ("Silent mode: {}".format(util.silent_mode)) + +######################## Agents Config ######################################################################### + +# 1) Symbols +symbols = ['AAPL'] +print("Symbols traded: {}".format(symbols)) + +# 2) Historical Date to simulate +date = '2012-06-21' +date_pd = pd.to_datetime(date) +print("Historical Simulation Date: {}".format(date)) + +agents = [] + +# 3) ExchangeAgent Config +num_exchanges = 1 +mkt_open = date_pd + pd.to_timedelta('09:30:00') +mkt_close = date_pd + pd.to_timedelta('09:30:05') +print("ExchangeAgent num_exchanges: {}".format(num_exchanges)) +print("ExchangeAgent mkt_open: {}".format(mkt_open)) +print("ExchangeAgent mkt_close: {}".format(mkt_close)) + +ea = ExchangeAgent(id = 0, + name = 'Exchange_Agent', + type = 'ExchangeAgent', + mkt_open = mkt_open, + mkt_close = mkt_close, + symbols = symbols, + log_orders=log_orders, + book_freq = '1s', + pipeline_delay = 0, + computation_delay = 0, + stream_history = 10, + random_state = random_state) + +agents.extend([ea]) + +# 4) MarketReplayAgent Config +num_mr_agents = 1 +cash_mr_agents = 10000000 + +mr_agents = [MarketReplayAgent(id = 1, + name = "Market_Replay_Agent", + symbol = symbols[0], + date = date, + startingCash = cash_mr_agents, + random_state = random_state)] +agents.extend(mr_agents) + +# 5) ExperimentalAgent Config +num_exp_agents = 1 +cash_exp_agents = 10000000 + +exp_agents = [ExperimentalAgent(id = 2, + name = "Experimental_Agent", + symbol = symbols[0], + startingCash = cash_exp_agents, + execution_timestamp = pd.Timestamp("2012-06-21 09:30:02"), + quantity = 1000, + is_buy_order = True, + limit_price = 500, + random_state = random_state)] +agents.extend(exp_agents) +####################################################################################################################### + +# 6) Kernel Parameters +kernel = Kernel("Market Replay Kernel", random_state = random_state) + +kernelStartTime = date_pd + pd.to_timedelta('09:30:00') +kernelStopTime = date_pd + pd.to_timedelta('09:30:05') +defaultComputationDelay = 0 +latency = np.zeros((3, 3)) +noise = [ 0.0 ] + +# 7) Data Oracle +oracle = OrderBookOracle(symbol='AAPL', + date='2012-06-21', + orderbook_file_path='C:/_code/py/air/abides_open_source/abides/data/LOBSTER/AAPL_2012-06-21_34200000_57600000_orderbook_10.csv', + message_file_path='C:/_code/py/air/abides_open_source/abides/data/LOBSTER/AAPL_2012-06-21_34200000_57600000_message_10.csv', + num_price_levels=10) + +kernel.runner(agents = agents, startTime = kernelStartTime, + stopTime = kernelStopTime, agentLatency = latency, + latencyNoise = noise, + defaultComputationDelay = defaultComputationDelay, + defaultLatency=0, + oracle = oracle, log_dir = args.log_dir) + +simulation_end_time = dt.datetime.now() +print ("Simulation End Time: {}".format(simulation_end_time)) +print ("Time taken to run simulation: {}".format(simulation_end_time - simulation_start_time)) \ No newline at end of file diff --git a/notebooks/.ipynb_checkpoints/MarketReplayAgentAnalysis-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/MarketReplayAgentAnalysis-checkpoint.ipynb new file mode 100644 index 000000000..0aa6b87e4 --- /dev/null +++ b/notebooks/.ipynb_checkpoints/MarketReplayAgentAnalysis-checkpoint.ipynb @@ -0,0 +1,423 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Simulation Logs" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "folder_path = 'C:/_code/py/air/abides_open_source/abides/'" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "orderbook_log_df = pd.read_pickle(folder_path + 'log/1560778365/orderbook_AAPL.bz2', compression='bz2')\n", + "summary_log_df = pd.read_pickle(folder_path + 'log/1560778365/summary_log.bz2', compression='bz2')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "market_replay_agent_log_df = pd.read_pickle(folder_path + 'log/1560778365/Market_Replay_Agent.bz2', compression='bz2')\n", + "exchange_agent_log_df = pd.read_pickle(folder_path + 'log/1560778365/Exchange_Agent.bz2', compression='bz2')" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " Event EventType\n", + "EventTime \n", + "NaT 10000000 AGENT_TYPE\n", + "NaT 100000 STARTING_CASH\n", + "2012-06-21 09:30:00.000000 {'CASH': 100000} HOLDINGS_UPDATED\n", + "2012-06-21 09:30:00.004261 100000 MARKED_TO_MARKET\n", + "2012-06-21 09:30:00.004261 18.0 AAPL @ 585.32 == 10535.76 MARK_TO_MARKET" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "market_replay_agent_log_df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "MARKED_TO_MARKET 377\n", + "MARK_TO_MARKET 188\n", + "FINAL_CASH_POSITION 1\n", + "FINAL_HOLDINGS 1\n", + "AGENT_TYPE 1\n", + "STARTING_CASH 1\n", + "ENDING_CASH 1\n", + "HOLDINGS_UPDATED 1\n", + "Name: EventType, dtype: int64" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "market_replay_agent_log_df.EventType.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "ORDER_ACCEPTED 184\n", + "BEST_BID 184\n", + "LIMIT_ORDER 184\n", + "BEST_ASK 183\n", + "ORDER_CANCELLED 131\n", + "CANCEL_ORDER 131\n", + "MODIFY_ORDER 27\n", + "REPLICATE_ORDERBOOK_SNAPSHOT 4\n", + "WHEN_MKT_CLOSE 2\n", + "WHEN_MKT_OPEN 2\n", + "AGENT_TYPE 1\n", + "Name: EventType, dtype: int64" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "exchange_agent_log_df.EventType.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "conda_py_36", + "language": "python", + "name": "conda_py_36" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/.ipynb_checkpoints/OrderBookOracle-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/OrderBookOracle-checkpoint.ipynb new file mode 100644 index 000000000..871f05706 --- /dev/null +++ b/notebooks/.ipynb_checkpoints/OrderBookOracle-checkpoint.ipynb @@ -0,0 +1,1357 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/efs/abides\n" + ] + } + ], + "source": [ + "cd ../" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from util.oracle.OrderBookOracle import OrderBookOracle" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### OrderBookOracle" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "OrderBookOracle Message File: /efs/abides/data/LOBSTER/AAPL_2012-06-21_34200000_57600000_message_10.csv\n", + "OrderBookOracle Orderbook File: /efs/abides/data/LOBSTER/AAPL_2012-06-21_34200000_57600000_orderbook_10.csv\n", + "OrderBookOracle initialized for AAPL and date: 2012-06-21\n" + ] + } + ], + "source": [ + "obo = OrderBookOracle(symbol='AAPL',\n", + " date='2012-06-21',\n", + " orderbook_file_path='/efs/abides/data/LOBSTER/AAPL_2012-06-21_34200000_57600000_orderbook_10.csv', \n", + " message_file_path='/efs/abides/data/LOBSTER/AAPL_2012-06-21_34200000_57600000_message_10.csv',\n", + " num_price_levels=10)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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timestamptypeorder_idvolpricedirection
02012-06-21 09:30:00.004260640NEW1611358418585.32BUY
12012-06-21 09:30:00.004447484NEW1611359418585.31BUY
22012-06-21 09:30:00.025551909NEW1612045618585.91SELL
32012-06-21 09:30:00.025579546NEW1612048018585.92SELL
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timestamp
2012-06-21 09:30:00.004260640585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100587.651160587.90500
2012-06-21 09:30:00.004447484585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100587.651160587.90500
2012-06-21 09:30:00.025551909585.9118585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100587.651160
2012-06-21 09:30:00.025579546585.9118585.9218585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100
2012-06-21 09:30:00.025613151585.9118585.9218585.9318585.94200585.98200586.10200586.89300586.9550587.00100587.1010
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bid_sizebidaskask_size
118585.33585.94200
218585.32585.98200
3150585.3586.1200
45585.1586.89300
589585.01586.9550
65584.97587100
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" + ], + "text/plain": [ + " bid_size bid ask ask_size\n", + "1 18 585.33 585.94 200\n", + "2 18 585.32 585.98 200\n", + "3 150 585.3 586.1 200\n", + "4 5 585.1 586.89 300\n", + "5 89 585.01 586.95 50\n", + "6 5 584.97 587 100\n", + "7 300 584.93 587.1 10\n", + "8 300 584.65 587.39 100\n", + "9 300 584.53 587.65 1160\n", + "10 200 584.38 587.9 500" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ob_snap" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Best Bid: 585.33\n", + "Best Bid Size: 18.0\n", + "Best Ask: 585.94\n", + "Best Ask Size: 200.0\n", + "Mid Price: 585.635\n", + "Spread: 0.6100000000000136\n" + ] + } + ], + "source": [ + "print(\"Best Bid: {}\".format(obo.bestBid(ob_snap)))\n", + "print(\"Best Bid Size: {}\".format(obo.bestBidSize(ob_snap)))\n", + "print(\"Best Ask: {}\".format(obo.bestAsk(ob_snap)))\n", + "print(\"Best Ask Size: {}\".format(obo.bestAskSize(ob_snap)))\n", + "print(\"Mid Price: {}\".format(obo.midPrice(ob_snap)))\n", + "print(\"Spread: {}\".format(obo.spread(ob_snap)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Order Book Visualisation" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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bid_price_1bid_size_1bid_price_2bid_size_2bid_price_3bid_size_3bid_price_4bid_size_4bid_price_5bid_size_5bid_price_6bid_size_6bid_price_7bid_size_7bid_price_8bid_size_8bid_price_9bid_size_9bid_price_10bid_size_10
timestamp
2012-06-21 09:30:00.004261585.3318585.3218585.30150585.15585.0189584.975584.93300584.65300584.53300584.38200
2012-06-21 09:30:00.004447585.3318585.3218585.3118585.3150585.105585.0189584.975584.93300584.65300584.53300
2012-06-21 09:30:00.025552585.3318585.3218585.3118585.3150585.105585.0189584.975584.93300584.65300584.53300
2012-06-21 09:30:00.025580585.3318585.3218585.3118585.3150585.105585.0189584.975584.93300584.65300584.53300
2012-06-21 09:30:00.025613585.3318585.3218585.3118585.3150585.105585.0189584.975584.93300584.65300584.53300
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" + ], + "text/plain": [ + " bid_price_1 bid_size_1 bid_price_2 bid_size_2 \\\n", + "timestamp \n", + "2012-06-21 09:30:00.004261 585.33 18 585.32 18 \n", + "2012-06-21 09:30:00.004447 585.33 18 585.32 18 \n", + "2012-06-21 09:30:00.025552 585.33 18 585.32 18 \n", + "2012-06-21 09:30:00.025580 585.33 18 585.32 18 \n", + "2012-06-21 09:30:00.025613 585.33 18 585.32 18 \n", + "\n", + " bid_price_3 bid_size_3 bid_price_4 bid_size_4 \\\n", + "timestamp \n", + "2012-06-21 09:30:00.004261 585.30 150 585.1 5 \n", + "2012-06-21 09:30:00.004447 585.31 18 585.3 150 \n", + "2012-06-21 09:30:00.025552 585.31 18 585.3 150 \n", + "2012-06-21 09:30:00.025580 585.31 18 585.3 150 \n", + "2012-06-21 09:30:00.025613 585.31 18 585.3 150 \n", + "\n", + " bid_price_5 bid_size_5 bid_price_6 bid_size_6 \\\n", + "timestamp \n", + "2012-06-21 09:30:00.004261 585.01 89 584.97 5 \n", + "2012-06-21 09:30:00.004447 585.10 5 585.01 89 \n", + "2012-06-21 09:30:00.025552 585.10 5 585.01 89 \n", + "2012-06-21 09:30:00.025580 585.10 5 585.01 89 \n", + "2012-06-21 09:30:00.025613 585.10 5 585.01 89 \n", + "\n", + " bid_price_7 bid_size_7 bid_price_8 bid_size_8 \\\n", + "timestamp \n", + "2012-06-21 09:30:00.004261 584.93 300 584.65 300 \n", + "2012-06-21 09:30:00.004447 584.97 5 584.93 300 \n", + "2012-06-21 09:30:00.025552 584.97 5 584.93 300 \n", + "2012-06-21 09:30:00.025580 584.97 5 584.93 300 \n", + "2012-06-21 09:30:00.025613 584.97 5 584.93 300 \n", + "\n", + " bid_price_9 bid_size_9 bid_price_10 bid_size_10 \n", + "timestamp \n", + "2012-06-21 09:30:00.004261 584.53 300 584.38 200 \n", + "2012-06-21 09:30:00.004447 584.65 300 584.53 300 \n", + "2012-06-21 09:30:00.025552 584.65 300 584.53 300 \n", + "2012-06-21 09:30:00.025580 584.65 300 584.53 300 \n", + "2012-06-21 09:30:00.025613 584.65 300 584.53 300 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "obo.bids().head()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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timestamp
2012-06-21 09:30:00.004261585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100587.651160587.90500
2012-06-21 09:30:00.004447585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100587.651160587.90500
2012-06-21 09:30:00.025552585.9118585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100587.651160
2012-06-21 09:30:00.025580585.9118585.9218585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100
2012-06-21 09:30:00.025613585.9118585.9218585.9318585.94200585.98200586.10200586.89300586.9550587.00100587.1010
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" + ], + "text/plain": [ + " ask_price_1 ask_size_1 ask_price_2 ask_size_2 \\\n", + "timestamp \n", + "2012-06-21 09:30:00.004261 585.94 200 585.98 200 \n", + "2012-06-21 09:30:00.004447 585.94 200 585.98 200 \n", + "2012-06-21 09:30:00.025552 585.91 18 585.94 200 \n", + "2012-06-21 09:30:00.025580 585.91 18 585.92 18 \n", + "2012-06-21 09:30:00.025613 585.91 18 585.92 18 \n", + "\n", + " ask_price_3 ask_size_3 ask_price_4 ask_size_4 \\\n", + "timestamp \n", + "2012-06-21 09:30:00.004261 586.10 200 586.89 300 \n", + "2012-06-21 09:30:00.004447 586.10 200 586.89 300 \n", + "2012-06-21 09:30:00.025552 585.98 200 586.10 200 \n", + "2012-06-21 09:30:00.025580 585.94 200 585.98 200 \n", + "2012-06-21 09:30:00.025613 585.93 18 585.94 200 \n", + "\n", + " ask_price_5 ask_size_5 ask_price_6 ask_size_6 \\\n", + "timestamp \n", + "2012-06-21 09:30:00.004261 586.95 50 587.00 100 \n", + "2012-06-21 09:30:00.004447 586.95 50 587.00 100 \n", + "2012-06-21 09:30:00.025552 586.89 300 586.95 50 \n", + "2012-06-21 09:30:00.025580 586.10 200 586.89 300 \n", + "2012-06-21 09:30:00.025613 585.98 200 586.10 200 \n", + "\n", + " ask_price_7 ask_size_7 ask_price_8 ask_size_8 \\\n", + "timestamp \n", + "2012-06-21 09:30:00.004261 587.10 10 587.39 100 \n", + "2012-06-21 09:30:00.004447 587.10 10 587.39 100 \n", + "2012-06-21 09:30:00.025552 587.00 100 587.10 10 \n", + "2012-06-21 09:30:00.025580 586.95 50 587.00 100 \n", + "2012-06-21 09:30:00.025613 586.89 300 586.95 50 \n", + "\n", + " ask_price_9 ask_size_9 ask_price_10 ask_size_10 \n", + "timestamp \n", + "2012-06-21 09:30:00.004261 587.65 1160 587.90 500 \n", + "2012-06-21 09:30:00.004447 587.65 1160 587.90 500 \n", + "2012-06-21 09:30:00.025552 587.39 100 587.65 1160 \n", + "2012-06-21 09:30:00.025580 587.10 10 587.39 100 \n", + "2012-06-21 09:30:00.025613 587.00 100 587.10 10 " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "obo.asks().head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Order Book Metrics" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Orderbook snapshot @ t= 2012-06-21 09:30:00.004261\n" + ] + } + ], + "source": [ + "t=pd.Timestamp('2012-06-21 09:30:00.004261')\n", + "ob_snap = obo.orderbook_snapshot(t=t)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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bid_sizebidaskask_size
118585.33585.94200
218585.32585.98200
3150585.3586.1200
45585.1586.89300
589585.01586.9550
65584.97587100
7300584.93587.110
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10200584.38587.9500
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" + ], + "text/plain": [ + " bid_size bid ask ask_size\n", + "1 18 585.33 585.94 200\n", + "2 18 585.32 585.98 200\n", + "3 150 585.3 586.1 200\n", + "4 5 585.1 586.89 300\n", + "5 89 585.01 586.95 50\n", + "6 5 584.97 587 100\n", + "7 300 584.93 587.1 10\n", + "8 300 584.65 587.39 100\n", + "9 300 584.53 587.65 1160\n", + "10 200 584.38 587.9 500" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ob_snap" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Best Bid: 585.33\n", + "Best Bid Size: 18.0\n", + "Best Ask: 585.94\n", + "Best Ask Size: 200.0\n", + "Mid Price: 585.635\n", + "Spread: 0.6100000000000136\n" + ] + } + ], + "source": [ + "print(\"Best Bid: {}\".format(obo.bestBid(ob_snap)))\n", + "print(\"Best Bid Size: {}\".format(obo.bestBidSize(ob_snap)))\n", + "print(\"Best Ask: {}\".format(obo.bestAsk(ob_snap)))\n", + "print(\"Best Ask Size: {}\".format(obo.bestAskSize(ob_snap)))\n", + "print(\"Mid Price: {}\".format(obo.midPrice(ob_snap)))\n", + "print(\"Spread: {}\".format(obo.spread(ob_snap)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Order Book Visualisation" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "obo.plotDepth(t, ob_snap)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "obo.plotPriceLevelVolume(obo.orderbook_df)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "conda_py_36", + "language": "python", + "name": "conda_py_36" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/util/OrderBook.py b/util/OrderBook.py index 813ee2ae8..6c27b314e 100644 --- a/util/OrderBook.py +++ b/util/OrderBook.py @@ -29,6 +29,11 @@ def __init__ (self, owner, symbol): # Create an order history for the exchange to report to certain agent types. self.history = [{}] + self.bid_levels_price = dict() + self.bid_levels_size = dict() + self.ask_levels_price = dict() + self.ask_levels_size = dict() + def handleLimitOrder (self, order): # Matches a limit order or adds it to the order book. Handles partial matches piecewise, @@ -142,6 +147,7 @@ def handleLimitOrder (self, order): self.quotes_seen.add(quote) self.book_log.append(row) + self.updateOrderbookDataframe() self.prettyPrint() @@ -309,6 +315,30 @@ def cancelOrder (self, order): # We found the order and cancelled it, so stop looking. return + def modifyOrder (self, order, new_order): + book = self.bids if order.is_buy_order else self.asks + if not book: return + for i, o in enumerate(book): + if self.isEqualPrice(order, o[0]): + for mi, mo in enumerate(book[i]): + if order.order_id == mo.order_id: + book[i][0] = new_order + for idx, orders in enumerate(self.history): + if new_order.order_id not in orders: continue + self.history[idx][new_order.order_id]['transactions'].append((self.owner.currentTime, new_order.quantity)) + print("MODIFIED: order {}".format(order)) + print("SENT: notifications of order modification to agent {} for order {}".format(new_order.agent_id, new_order.order_id)) + self.owner.sendMessage(order.agent_id, Message({"msg": "ORDER_MODIFIED", "new_order": new_order})) + if order.is_buy_order: + self.bids = book + else: + self.asks = book + self.updateOrderbookDataframe() + + + def replicateOrderbookSnapshot(self): + self.updateOrderbookDataframe() + # Get the inside bid price(s) and share volume available at each price, to a limit # of "depth". (i.e. inside price, inside 2 prices) Returns a list of tuples: @@ -338,6 +368,27 @@ def getInsideAsks (self, depth=sys.maxsize): return book + def updateOrderbookDataframe(self): + bid_list = self.getInsideBids(30) + ask_list = self.getInsideAsks(30) + bldp = {} + blds = {} + sldp = {} + slds = {} + for level, order in enumerate(bid_list): + level += 1 + bldp[level] = order[0] + blds[level] = order[1] + self.bid_levels_price[self.owner.currentTime] = bldp + self.bid_levels_size[self.owner.currentTime] = blds + for level, order in enumerate(ask_list): + level += 1 + sldp[level] = order[0] + slds[level] = order[1] + self.ask_levels_price[self.owner.currentTime] = sldp + self.ask_levels_size[self.owner.currentTime] = slds + + # These could be moved to the LimitOrder class. We could even operator overload them # into >, <, ==, etc. def isBetterPrice (self, order, o): diff --git a/util/__init__.py b/util/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/util/oracle/OrderBookOracle.py b/util/oracle/OrderBookOracle.py new file mode 100644 index 000000000..9da661edd --- /dev/null +++ b/util/oracle/OrderBookOracle.py @@ -0,0 +1,269 @@ +import pandas as pd +import numpy as np +import matplotlib.pyplot as plt +from matplotlib.dates import DateFormatter + +from util.util import log_print, delist + +class OrderBookOracle: + + + def __init__(self, symbol, date, orderbook_file_path, message_file_path, num_price_levels=10, filter_trades=False): + self.symbol = symbol + self.date = date + self.num_price_levels = num_price_levels + self.message_df = self.readMessageFile(message_file_path) + self.orderbook_df = self.readOrderbookFile(orderbook_file_path) + self.trades_df = self.filter_trades() if filter_trades else self.message_df + log_print("OrderBookOracle initialized for {} and date: {}".format(self.symbol, self.date)) + + + def readMessageFile(self, message_file_path): + """ + :return: a pandas Dataframe of the trade messages file for the given symbol and date + """ + log_print("OrderBookOracle Message File: {}".format(message_file_path)) + + direction = {-1: 'SELL', + 1: 'BUY'} + + order_type = { + 1: 'NEW', + 2: 'PARTIAL_CANCELLATION', + 3: 'CANCELLATION', + 4: 'EXECUTE_VISIBLE', + 5: 'EXECUTE_HIDDEN', + 7: 'TRADING_HALT' + } + + message_df = pd.read_csv(message_file_path) + message_df.columns = ['timestamp', 'type', 'order_id', 'vol', 'price', 'direction'] + message_df['timestamp'] = pd.to_datetime(self.date) + pd.to_timedelta(message_df['timestamp'], unit='s') + message_df['direction'] = message_df['direction'].replace(direction) + message_df['price'] = message_df['price'] / 10000 + message_df['type'] = message_df['type'].replace(order_type) + return message_df + + + def readOrderbookFile(self, orderbook_file_path): + """ + :return: a pandas Dataframe of the orderbook file for the given symbol and date + """ + log_print("OrderBookOracle Orderbook File: {}".format(orderbook_file_path)) + all_cols = delist([[f"ask_price_{level}", f"ask_size_{level}", f"bid_price_{level}", f"bid_size_{level}"] for level in range(1, self.num_price_levels+1)]) + price_cols = delist([[f"ask_price_{level}", f"bid_price_{level}"] for level in range(1, self.num_price_levels+1)]) + orderbook_df = pd.read_csv(orderbook_file_path) + orderbook_df.columns = all_cols + orderbook_df[price_cols] = orderbook_df[price_cols] / 10000 + orderbook_df = orderbook_df.join(self.message_df[['timestamp']]) + orderbook_df = orderbook_df[['timestamp'] + all_cols] + #orderbook_df = orderbook_df.drop_duplicates(subset=['timestamp'], keep='last') + orderbook_df.set_index('timestamp', inplace=True) + return orderbook_df + + + def bids(self): + """ + :return: bid side of the orderbook (pandas dataframe) + """ + orderbook_bid_cols = delist([[f"bid_price_{level}", f"bid_size_{level}"] for level in range(1, self.num_price_levels+1)]) + return self.orderbook_df[orderbook_bid_cols] + + + def asks(self): + """ + :return: ask side of the orderbook (pandas dataframe) + """ + orderbook_ask_cols = delist([[f"ask_price_{level}", f"ask_size_{level}"] for level in range(1, self.num_price_levels+1)]) + return self.orderbook_df[orderbook_ask_cols] + + + def orderbook_snapshot(self, t=None): + """ + :return: orderbook snapshot for a given timestamp (pandas dataframe) + """ + log_print(f"Orderbook snapshot @ t= {t}") + orderbook_snapshot = pd.DataFrame(columns=['bid_size', 'bid', 'ask', 'ask_size'], index=range(1, self.num_price_levels+1)) + bids = self.bids().loc[t] + asks = self.asks().loc[t] + level = 1 + for i in range(0, len(asks), 2): + bid_price = bids.iloc[i] + bid_size = bids.iloc[i + 1] + ask_price = asks.iloc[i] + ask_size = asks.iloc[i + 1] + orderbook_snapshot.loc[level] = [bid_size, bid_price, ask_price, ask_size] + level += 1 + return orderbook_snapshot + + + @staticmethod + def bestBid(ob_snap_t): + """Return int + best bid price for a given orderbook snapshot + """ + return ob_snap_t.loc[1]['bid'] + + + @staticmethod + def bestAsk(ob_snap_t): + """Return int + + best ask price for a given orderbook snapshot + """ + return ob_snap_t.loc[1]['ask'] + + + @staticmethod + def bestBidSize(ob_snap_t): + """Return int + + best bid size (volume) for a given orderbook snapshot + """ + return ob_snap_t.loc[1]['bid_size'] + + + @staticmethod + def bestAskSize(ob_snap_t): + """Return int + + best ask size (volume) for a given orderbook snapshot + """ + return ob_snap_t.loc[1]['ask_size'] + + + def midPrice(self, ob_snap_t): + """Return int + + mid price for a given orderbook snapshot + """ + return (self.bestBid(ob_snap_t) + self.bestAsk(ob_snap_t)) / 2 + + + def spread(self, ob_snap_t): + """Return int + + spread for a given orderbook snapshot + """ + return self.bestAsk(ob_snap_t) - self.bestBid(ob_snap_t) + + + def plotOrderbookSnapshotMetrics(self, t, ob_snap_t): + """ + at t, plot against l (x-axis): Pb, Pa, Sb, Sa, Pa+Pb/2, Pa-Pb, Pa+Pb + :param t: timestamp of the orderbook snapshot + :param ob_snap_t: orderbook snapshot dataframe + :return: None + """ + fig, axes = plt.subplots(nrows=2, ncols=3) + fig.set_size_inches(30, 10) + fig.suptitle(f"{self.symbol} Orderbook snapshot metrics @ {t}", size=20) + + fig.text(0.05, 0.95, + f"Best Bid: {self.bestBid(ob_snap_t)}, Best Ask: {self.bestAsk(ob_snap_t)}, Mid Price: {self.midPrice(ob_snap_t)}, " + f"Spread: {self.spread(ob_snap_t)}, Best Bid Size: {self.bestBidSize(ob_snap_t)}, Best Ask Size: {self.bestAskSize(ob_snap_t)}", + fontsize=14, verticalalignment='top') + axes[0, 0].plot(ob_snap_t.index, ob_snap_t.bid) + axes[0, 0].set_ylabel("Bid Price ( $Pb$ )", size=13) + + axes[0, 1].plot(ob_snap_t.index, ob_snap_t.ask) + axes[0, 1].set_ylabel("Ask Price ( $Pa$ )", size=13) + + axes[0, 2].plot(ob_snap_t.index, ob_snap_t.ask_size) + axes[0, 2].plot(ob_snap_t.index, ob_snap_t.bid_size) + axes[0, 2].set_ylabel("Bid nd Ask Sizes ( $Sb, Sa$ )", size=13) + axes[0, 2].legend() + + axes[1, 0].plot(ob_snap_t.index, ((ob_snap_t.ask + ob_snap_t.bid) / 2)) + axes[1, 0].set_ylabel("Mid Price ( $(Pa+Pb) / 2$ )", size=13) + + axes[1, 1].plot(ob_snap_t.index, (ob_snap_t.ask - ob_snap_t.bid)) + axes[1, 1].set_ylabel("Spread ( $Pa-Pb$ )", size=13) + + axes[1, 2].plot(ob_snap_t.index, (ob_snap_t.ask + ob_snap_t.bid)) + axes[1, 2].set_ylabel("$Pa + Pb$", size=13) + + for ax in axes: + for in_ax in ax: + in_ax.set_xlabel("Price Level", size=13) + + + def plotDepth(self, t, ob_snap_t): + """ + plots the orderbook depth for the given snapshot + :param t: timestamp of the orderbook snapshot + :param ob_snap_t: orderbook snapshot dataframe + :return: None + """ + fig, axes = plt.subplots(nrows=1, ncols=1) + fig.set_size_inches(20, 5) + axes.set_title(f"Orderbook Depth chart for {self.symbol} @ {t}") + axes.set_xlabel("Price ($)") + axes.set_ylabel("Cumulative Volume") + + plt.plot(ob_snap_t.bid, ob_snap_t.bid_size.cumsum(), color='green', marker='o') + axes.fill_between(ob_snap_t.bid.values.astype(float), 0, + ob_snap_t.bid_size.cumsum().values.astype(int), color='palegreen') + plt.bar(ob_snap_t.bid, ob_snap_t.bid_size, width=[0.01] * 10, color='grey') + + plt.plot(ob_snap_t.ask, ob_snap_t.ask_size.cumsum(), color='red', marker='o') + axes.fill_between(ob_snap_t.ask.values.astype(float), 0, + ob_snap_t.ask_size.cumsum().values.astype(int), color='salmon') + plt.bar(ob_snap_t.ask, ob_snap_t.ask_size, width=[0.01] * 10, color='grey', label='volume') + + plt.axvline(x=self.midPrice(ob_snap_t), label='mid') + plt.legend() + + + def plotPriceLevelVolume(self, orderbook_df): + """ + plot the price level coloured by volumes available at each level + :param orderbook_df: + :return: None + """ + + price_cols = delist([[f"ask_price_{level}", f"bid_price_{level}"] for level in range(1, self.num_price_levels+1)]) + size_cols = delist([[f"ask_size_{level}", f"bid_size_{level}"] for level in range(1, self.num_price_levels+1)]) + fig, ax = plt.subplots(nrows=1, ncols=1) + fig.set_size_inches(30, 15) + ax.set_title(f"Orderbook Price Level Volume for {self.symbol}, {self.num_price_levels} levels", size=22) + ax.set_xlabel("Time", size=24, fontweight='bold') + ax.set_ylabel("Price ($)", size=24, fontweight='bold') + ax.set_facecolor("white") + + mid_price = (orderbook_df.ask_price_1 + orderbook_df.bid_price_1) / 2 + + myFmt = DateFormatter("%H:%M") + ax.xaxis.set_major_formatter(myFmt) + ax.plot(orderbook_df.index, mid_price, color='black', label='mid price') + + for price_col, size_col in zip(price_cols, size_cols): + im = ax.scatter(x=orderbook_df.index, y=orderbook_df[price_col], c=np.log(orderbook_df[size_col]), s=0.7, + cmap=plt.cm.jet, alpha=0.7) + cbar = fig.colorbar(im, ax=ax, label='volume') + cbar.ax.get_yaxis().labelpad = 20 + cbar.ax.set_ylabel('Size', rotation=270, fontsize=20, fontweight='bold') + + + def filter_trades(self): + log_print("Original trades type counts:") + log_print(self.message_df.type.value_counts()) + trades_df = self.message_df.loc[self.message_df.type.isin(['NEW', 'CANCELLATION', 'PARTIAL_CANCELLATION', 'EXECUTE_VISIBLE'])] + order_id_types_series = trades_df.groupby('order_id')['type'].apply(list) + order_id_types_series = order_id_types_series.apply(lambda x: str(x)) + cancel_only_order_ids = list(order_id_types_series[order_id_types_series == "['CANCELLATION']"].index) + part_cancel_only_order_ids = list(order_id_types_series[order_id_types_series == "['PARTIAL_CANCELLATION']"].index) + trades_df = trades_df.loc[~trades_df.order_id.isin(cancel_only_order_ids + part_cancel_only_order_ids)] + log_print("Filtered trades type counts:") + log_print(trades_df.type.value_counts()) + return trades_df + + + def getDailyOpenPrice(self, symbol, mkt_open): + price = self.message_df.iloc[0]['price'] + log_print("Opening price at {} for {}".format(mkt_open, symbol)) + return price + + def observePrice(self, symbol, currentTime, sigma_n = 0): + return self.message_df.iloc[0]['price'] + diff --git a/util/oracle/__init__.py b/util/oracle/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/util/order/LimitOrder.py b/util/order/LimitOrder.py index c34c248af..7271b521c 100644 --- a/util/order/LimitOrder.py +++ b/util/order/LimitOrder.py @@ -12,25 +12,29 @@ class LimitOrder (Order): - def __init__ (self, agent_id, time_placed, symbol, quantity, is_buy_order, limit_price): - super().__init__(agent_id, time_placed, symbol, quantity, is_buy_order) - - # The limit price is the minimum price the agent will accept (for a sell order) or - # the maximum price the agent will pay (for a buy order). + def __init__ (self, agent_id, time_placed, symbol, quantity, is_buy_order, limit_price, dollar=True, order_id=None): + super().__init__(agent_id, time_placed, symbol, quantity, is_buy_order, order_id) self.limit_price = limit_price + self.dollar = dollar def __str__ (self): if silent_mode: return '' filled = '' - if self.fill_price: filled = " (filled @ {})".format(dollarize(self.fill_price)) + if self.dollar: + self.limit_price = dollarize(self.limit_price) if abs(self.limit_price) < sys.maxsize else 'MKT' + if self.fill_price: filled = " (filled @ {})".format(dollarize(self.fill_price)) + else: + if self.fill_price: filled = " (filled @ {})".format(self.fill_price) # Until we make explicit market orders, we make a few assumptions that EXTREME prices on limit # orders are trying to represent a market order. This only affects printing - they still hit # the order book like limit orders, which is wrong. - return "(Agent {} @ {}) : {} {} {} @ {}{}".format(self.agent_id, Kernel.fmtTime(self.time_placed), - "BUY" if self.is_buy_order else "SELL", self.quantity, self.symbol, - dollarize(self.limit_price) if abs(self.limit_price) < sys.maxsize else 'MKT', filled) + return "(Order_ID: {} Agent {} @ {}) : {} {} {} @ {}{}".format(self.order_id, self.agent_id, + Kernel.fmtTime(self.time_placed), + "BUY" if self.is_buy_order else "SELL", + self.quantity, self.symbol, + self.limit_price, filled) def __repr__ (self): if silent_mode: return '' diff --git a/util/order/Order.py b/util/order/Order.py index fddc39759..518eabf64 100644 --- a/util/order/Order.py +++ b/util/order/Order.py @@ -6,8 +6,7 @@ class Order: order_id = 0 - def __init__(self, agent_id, time_placed, symbol, quantity, is_buy_order): - # Numeric agent id that placed the order. + def __init__(self, agent_id, time_placed, symbol, quantity, is_buy_order, order_id=None): self.agent_id = agent_id # Time at which the order was created by the agent. @@ -23,8 +22,12 @@ def __init__(self, agent_id, time_placed, symbol, quantity, is_buy_order): self.is_buy_order = is_buy_order # Assign and increment the next unique order_id (simulation-wide). - self.order_id = Order.order_id - Order.order_id += 1 + + if not order_id: + self.order_id = Order.order_id + Order.order_id += 1 + else: + self.order_id = order_id # Create placeholder fields that don't get filled in until certain # events happen. (We could instead subclass to a special FilledOrder diff --git a/util/order/__init__.py b/util/order/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/util/util.py b/util/util.py index 78f57eada..70ad298bb 100644 --- a/util/util.py +++ b/util/util.py @@ -19,3 +19,10 @@ def log_print (str, *args): def be_silent (): return silent_mode + +def delist(list_of_lists): + delisted_list = [] + for lst in list_of_lists: + for item in lst: + delisted_list.append(item) + return delisted_list From ffd4f3d3a1a6fb1fa2085455c6e982bb3e678ca7 Mon Sep 17 00:00:00 2001 From: mamahfouz Date: Mon, 17 Jun 2019 18:22:30 +0100 Subject: [PATCH 2/3] small changes to market replay code --- agent/ExperimentalAgent.py | 3 --- agent/MarketReplayAgent.py | 9 ++++----- config/marketreplay.py | 4 ++-- 3 files changed, 6 insertions(+), 10 deletions(-) diff --git a/agent/ExperimentalAgent.py b/agent/ExperimentalAgent.py index 2258b8284..2134549b0 100644 --- a/agent/ExperimentalAgent.py +++ b/agent/ExperimentalAgent.py @@ -1,5 +1,3 @@ -import pandas as pd - from agent.TradingAgent import TradingAgent @@ -14,7 +12,6 @@ def __init__(self, id, name, symbol, self.quantity = quantity self.is_buy_order = is_buy_order self.limit_price = limit_price - self.timestamp = pd.Timestamp("2012-06-21 09:30:02") def kernelStarting(self, startTime): super().kernelStarting(startTime) diff --git a/agent/MarketReplayAgent.py b/agent/MarketReplayAgent.py index eb27bd4ad..547765510 100644 --- a/agent/MarketReplayAgent.py +++ b/agent/MarketReplayAgent.py @@ -25,17 +25,16 @@ def wakeup (self, currentTime): self.last_trade[self.symbol] = self.oracle.getDailyOpenPrice(self.symbol, self.mkt_open) if not self.mkt_open or not self.mkt_close: return - elif currentTime == self.oracle.orderbook_df.iloc[0].name: - order = self.oracle.trades_df.loc[self.oracle.trades_df.timestamp == currentTime] + order = self.oracle.trades_df.loc[self.oracle.trades_df.timestamp == currentTime] + wake_up_time = self.oracle.trades_df.loc[self.oracle.trades_df.timestamp > currentTime].iloc[0].timestamp + if currentTime == self.oracle.orderbook_df.iloc[0].name: self.placeMktOpenOrders(order, t=currentTime) - self.setWakeup(self.oracle.trades_df.loc[self.oracle.trades_df.timestamp > currentTime].iloc[0].timestamp) elif (currentTime > self.mkt_open) and (currentTime < self.mkt_close): try: - order = self.oracle.trades_df.loc[self.oracle.trades_df.timestamp == currentTime] self.placeOrder(currentTime, order) - self.setWakeup(self.oracle.trades_df.loc[self.oracle.trades_df.timestamp > currentTime].iloc[0].timestamp) except Exception as e: log_print(e) + self.setWakeup(wake_up_time) def receiveMessage (self, currentTime, msg): diff --git a/config/marketreplay.py b/config/marketreplay.py index 53ad88563..af5122d83 100644 --- a/config/marketreplay.py +++ b/config/marketreplay.py @@ -130,8 +130,8 @@ # 7) Data Oracle oracle = OrderBookOracle(symbol='AAPL', date='2012-06-21', - orderbook_file_path='C:/_code/py/air/abides_open_source/abides/data/LOBSTER/AAPL_2012-06-21_34200000_57600000_orderbook_10.csv', - message_file_path='C:/_code/py/air/abides_open_source/abides/data/LOBSTER/AAPL_2012-06-21_34200000_57600000_message_10.csv', + orderbook_file_path='C:/_code/py/air/abides_open_source/abides/data/lob_data/AAPL_2012-06-21_34200000_57600000_orderbook_10.csv', + message_file_path='C:/_code/py/air/abides_open_source/abides/data/lob_data/AAPL_2012-06-21_34200000_57600000_message_10.csv', num_price_levels=10) kernel.runner(agents = agents, startTime = kernelStartTime, From 7079c23adc17a8aaa5e5893bca8e65a31430f87b Mon Sep 17 00:00:00 2001 From: mamahfouz Date: Wed, 19 Jun 2019 08:35:52 +0100 Subject: [PATCH 3/3] remove data oracle and other changes --- agent/ExchangeAgent.py | 30 +- agent/ExperimentalAgent.py | 11 +- agent/MarketReplayAgent.py | 80 +- agent/RandomAgent.py | 43 + config/marketreplay.py | 68 +- ...MarketReplayAgentAnalysis-checkpoint.ipynb | 423 ----- .../OrderBookOracle-checkpoint.ipynb | 1357 ----------------- notebooks/MarketReplayAgentAnalysis.ipynb | 423 ----- notebooks/OrderBookOracle.ipynb | 1313 ---------------- util/OrderBook.py | 35 +- util/oracle/OrderBookOracle.py | 269 ---- util/oracle/RandomOrderBookOracle.py | 59 + util/util.py | 6 +- 13 files changed, 203 insertions(+), 3914 deletions(-) create mode 100644 agent/RandomAgent.py delete mode 100644 notebooks/.ipynb_checkpoints/MarketReplayAgentAnalysis-checkpoint.ipynb delete mode 100644 notebooks/.ipynb_checkpoints/OrderBookOracle-checkpoint.ipynb delete mode 100644 notebooks/MarketReplayAgentAnalysis.ipynb delete mode 100644 notebooks/OrderBookOracle.ipynb delete mode 100644 util/oracle/OrderBookOracle.py create mode 100644 util/oracle/RandomOrderBookOracle.py diff --git a/agent/ExchangeAgent.py b/agent/ExchangeAgent.py index e307f43bd..76a6d6ba0 100644 --- a/agent/ExchangeAgent.py +++ b/agent/ExchangeAgent.py @@ -9,8 +9,6 @@ from util.OrderBook import OrderBook from util.util import log_print -import sys - import jsons as js import numpy as np import pandas as pd @@ -68,8 +66,11 @@ def kernelInitializing (self, kernel): # Obtain opening prices (in integer cents). These are not noisy right now. for symbol in self.order_books: - self.order_books[symbol].last_trade = self.oracle.getDailyOpenPrice(symbol, self.mkt_open) - log_print ("Opening price for {} is {}", symbol, self.order_books[symbol].last_trade) + try: + self.order_books[symbol].last_trade = self.oracle.getDailyOpenPrice(symbol, self.mkt_open) + log_print ("Opening price for {} is {}", symbol, self.order_books[symbol].last_trade) + except AttributeError as e: + log_print(str(e)) # The exchange agent overrides this to additionally log the full depth of its @@ -77,8 +78,13 @@ def kernelInitializing (self, kernel): def kernelTerminating (self): super().kernelTerminating() - # Skip order book dump if requested. - if self.book_freq is None: return + if self.book_freq is None: + for symbol in self.order_books: + book = self.order_books[symbol] + dfLog = pd.DataFrame([book.mid_dict, book.bid_levels_price_dict, book.bid_levels_size_dict, + book.ask_levels_price_dict, book.ask_levels_size_dict]).T + dfLog.columns = ['mid_price', 'bid_level_prices', 'bid_level_sizes', 'ask_level_prices', 'ask_level_sizes'] + self.writeLog(dfLog, filename='orderbook_{}'.format(symbol)) # Iterate over the order books controlled by this exchange. for symbol in self.order_books: @@ -137,7 +143,7 @@ def kernelTerminating (self): # to the exchange agent log. self.writeLog(df, filename='orderbook_{}'.format(symbol)) - print ("Order book archival complete.") + print ("Order book archival complete.") def receiveMessage (self, currentTime, msg): @@ -271,15 +277,7 @@ def receiveMessage (self, currentTime, msg): log_print ("Modification request discarded. Unknown symbol: {}".format(order.symbol)) else: self.order_books[order.symbol].modifyOrder(deepcopy(order), deepcopy(new_order)) - elif msg.body['msg'] == 'REPLICATE_ORDERBOOK_SNAPSHOT': - timestamp = msg.body['timestamp'] - symbol = msg.body['symbol'] - log_print ("{} received REPLICATE_ORDERBOOK_SNAPSHOT for t= {}".format(self.name, timestamp)) - if symbol not in self.order_books: - log_print ("Orderbook replication request discarded. Unknown symbol: {}".format(symbol)) - else: - self.order_books[symbol].replicateOrderbookSnapshot() - + def sendMessage (self, recipientID, msg): # The ExchangeAgent automatically applies appropriate parallel processing pipeline delay diff --git a/agent/ExperimentalAgent.py b/agent/ExperimentalAgent.py index 2134549b0..4253a20ae 100644 --- a/agent/ExperimentalAgent.py +++ b/agent/ExperimentalAgent.py @@ -4,14 +4,15 @@ class ExperimentalAgent(TradingAgent): def __init__(self, id, name, symbol, - startingCash, execution_timestamp, quantity, is_buy_order, limit_price, - random_state = None): - super().__init__(id, name, startingCash, random_state) + starting_cash, execution_timestamp, quantity, is_buy_order, limit_price, + log_orders = False, random_state = None): + super().__init__(id, name, starting_cash, random_state) self.symbol = symbol self.execution_timestamp = execution_timestamp self.quantity = quantity self.is_buy_order = is_buy_order self.limit_price = limit_price + self.log_orders = log_orders def kernelStarting(self, startTime): super().kernelStarting(startTime) @@ -24,6 +25,10 @@ def wakeup(self, currentTime): elif (currentTime > self.mkt_open) and (currentTime < self.mkt_close): if currentTime == self.execution_timestamp: self.placeLimitOrder(self.symbol, self.quantity, self.is_buy_order, self.limit_price, dollar=False) + if self.log_orders: self.logEvent('LIMIT_ORDER', {'agent_id': self.id, 'dollar': False, 'fill_price': None, + 'is_buy_order': self.is_buy_order, 'limit_price': self.limit_price, + 'order_id': 1, 'quantity': self.quantity, 'symbol': self.symbol, + 'time_placed': str(currentTime)}) def receiveMessage(self, currentTime, msg): super().receiveMessage(currentTime, msg) diff --git a/agent/MarketReplayAgent.py b/agent/MarketReplayAgent.py index 547765510..0ffb0753a 100644 --- a/agent/MarketReplayAgent.py +++ b/agent/MarketReplayAgent.py @@ -1,64 +1,52 @@ import pandas as pd from agent.TradingAgent import TradingAgent -from util.util import log_print from util.order.LimitOrder import LimitOrder -from message.Message import Message +from util.util import log_print + class MarketReplayAgent(TradingAgent): - def __init__(self, id, name, symbol, date, startingCash, log_orders = False, random_state = None): - super().__init__(id, name, startingCash, random_state) + def __init__(self, id, name, type, symbol, date, starting_cash, log_orders = False, random_state = None): + super().__init__(id, name, type, starting_cash=starting_cash, log_orders=log_orders, random_state = random_state) self.symbol = symbol self.date = date - self.log_orders = log_orders + self.log_orders = log_orders + self.state = 'AWAITING_WAKEUP' def kernelStarting(self, startTime): super().kernelStarting(startTime) self.oracle = self.kernel.oracle + def kernelStopping (self): + super().kernelStopping() def wakeup (self, currentTime): - super().wakeup(currentTime) - self.last_trade[self.symbol] = self.oracle.getDailyOpenPrice(self.symbol, self.mkt_open) - if not self.mkt_open or not self.mkt_close: - return - order = self.oracle.trades_df.loc[self.oracle.trades_df.timestamp == currentTime] - wake_up_time = self.oracle.trades_df.loc[self.oracle.trades_df.timestamp > currentTime].iloc[0].timestamp - if currentTime == self.oracle.orderbook_df.iloc[0].name: - self.placeMktOpenOrders(order, t=currentTime) - elif (currentTime > self.mkt_open) and (currentTime < self.mkt_close): - try: - self.placeOrder(currentTime, order) - except Exception as e: - log_print(e) - self.setWakeup(wake_up_time) + self.state = 'INACTIVE' + try: + super().wakeup(currentTime) + self.last_trade[self.symbol] = self.oracle.getDailyOpenPrice(self.symbol, self.mkt_open) + if not self.mkt_open or not self.mkt_close: + return + order = self.oracle.trades_df.loc[self.oracle.trades_df.timestamp == currentTime] + wake_up_time = self.oracle.trades_df.loc[self.oracle.trades_df.timestamp > currentTime].iloc[0].timestamp + if (currentTime > self.mkt_open) and (currentTime < self.mkt_close): + self.state = 'ACTIVE' + try: + self.placeOrder(currentTime, order) + except Exception as e: + log_print(e) + self.setWakeup(wake_up_time) + except Exception as e: + log_print(str(e)) def receiveMessage (self, currentTime, msg): super().receiveMessage(currentTime, msg) - def placeMktOpenOrders(self, snapshot_order, t=0): - orders_snapshot = self.oracle.orderbook_df.loc[self.oracle.orderbook_df.index == t].T - for i in range(0, len(orders_snapshot) - 1, 4): - ask_price = orders_snapshot.iloc[i][0] - ask_vol = orders_snapshot.iloc[i + 1][0] - bid_price = orders_snapshot.iloc[i + 2][0] - bid_vol = orders_snapshot.iloc[i + 3][0] - - if snapshot_order.direction.item() == 'BUY' and bid_price == snapshot_order.price.item(): - bid_vol -= snapshot_order.vol.item() - elif snapshot_order.direction.item() == 'SELL' and ask_price == snapshot_order.price.item(): - ask_vol -= snapshot_order.vol.item() - - self.placeLimitOrder(self.symbol, bid_vol, True, float(bid_price), dollar=False) - self.placeLimitOrder(self.symbol, ask_vol, False, float(ask_price), dollar=False) - self.placeOrder(snapshot_order.timestamp.item(), snapshot_order) - - def placeOrder(self, currentTime, order): if len(order) == 1: type = order.type.item() @@ -66,10 +54,12 @@ def placeOrder(self, currentTime, order): direction = order.direction.item() price = order.price.item() vol = order.vol.item() + + existing_order = self.orders.get(id) + if type == 'NEW': self.placeLimitOrder(self.symbol, vol, direction == 'BUY', float(price), dollar=False, order_id=id) elif type in ['CANCELLATION', 'PARTIAL_CANCELLATION']: - existing_order = self.orders.get(id) if existing_order: if type == 'CANCELLATION': self.cancelOrder(existing_order) @@ -77,10 +67,7 @@ def placeOrder(self, currentTime, order): new_order = LimitOrder(self.id, currentTime, self.symbol, vol, direction == 'BUY', float(price), dollar=False, order_id=id) self.modifyOrder(existing_order, new_order) - else: - self.replicateOrderbookSnapshot(currentTime) elif type in ['EXECUTE_VISIBLE', 'EXECUTE_HIDDEN']: - existing_order = self.orders.get(id) if existing_order: if existing_order.quantity == vol: self.cancelOrder(existing_order) @@ -90,23 +77,14 @@ def placeOrder(self, currentTime, order): self.cancelOrder(existing_order) else: executed_order = LimitOrder(self.id, currentTime, self.symbol, new_vol, direction == 'BUY', float(price), - dollar=False, order_id=id) + dollar=False, order_id=id) self.modifyOrder(existing_order, executed_order) self.orders.get(id).quantity = new_vol - else: - self.replicateOrderbookSnapshot(currentTime) else: orders = self.oracle.trades_df.loc[self.oracle.trades_df.timestamp == currentTime] for index, order in orders.iterrows(): self.placeOrder(currentTime, order = pd.DataFrame(order).T) - def replicateOrderbookSnapshot(self, currentTime): - log_print("Received notification of orderbook snapshot replication at: {}".format(currentTime)) - self.sendMessage(self.exchangeID, Message({"msg": "REPLICATE_ORDERBOOK_SNAPSHOT", "sender": self.id, - "symbol": self.symbol, "timestamp": str(currentTime)})) - if self.log_orders: self.logEvent('REPLICATE_ORDERBOOK_SNAPSHOT', currentTime) - - def getWakeFrequency(self): return self.oracle.trades_df.iloc[0].timestamp - self.mkt_open \ No newline at end of file diff --git a/agent/RandomAgent.py b/agent/RandomAgent.py new file mode 100644 index 000000000..acca41fc0 --- /dev/null +++ b/agent/RandomAgent.py @@ -0,0 +1,43 @@ +from agent.TradingAgent import TradingAgent +import numpy as np +import pandas as pd + + +class RandomAgent(TradingAgent): + + + def __init__(self, id, name, symbol, startingCash, + buy_price_range = [90, 105], sell_price_range = [95, 110], quantity_range = [50, 500], + random_state = None): + super().__init__(id, name, startingCash, random_state) + self.symbol = symbol + self.buy_price_range = buy_price_range + self.sell_price_range = sell_price_range + self.quantity_range = quantity_range + + + def kernelStarting(self, startTime): + super().kernelStarting(startTime) + + + def wakeup(self, currentTime): + super().wakeup(currentTime) + self.last_trade[self.symbol] = 0 + if not self.mkt_open or not self.mkt_close: + return + elif (currentTime > self.mkt_open) and (currentTime < self.mkt_close): + direction = np.random.randint(0, 2) + price = np.random.randint(self.buy_price_range[0], self.buy_price_range[1]) \ + if direction == 1 else np.random.randint(self.sell_price_range[0], self.sell_price_range[1]) + quantity = np.random.randint(self.quantity_range[0], self.quantity_range[1]) + self.placeLimitOrder(self.symbol, quantity, direction, price, dollar=False) + delta_time = self.random_state.exponential(scale=1.0 / 0.005) + self.setWakeup(currentTime + pd.Timedelta('{}ms'.format(int(round(delta_time))))) + + + def receiveMessage(self, currentTime, msg): + super().receiveMessage(currentTime, msg) + + + def getWakeFrequency(self): + return pd.Timedelta('1ms') diff --git a/config/marketreplay.py b/config/marketreplay.py index af5122d83..8f049bb8c 100644 --- a/config/marketreplay.py +++ b/config/marketreplay.py @@ -3,9 +3,9 @@ from agent.MarketReplayAgent import MarketReplayAgent from agent.ExchangeAgent import ExchangeAgent from agent.ExperimentalAgent import ExperimentalAgent -from util.oracle.OrderBookOracle import OrderBookOracle from util import util +from util.oracle.RandomOrderBookOracle import RandomOrderBookOracle from util.order import LimitOrder import datetime as dt @@ -61,7 +61,7 @@ print("Symbols traded: {}".format(symbols)) # 2) Historical Date to simulate -date = '2012-06-21' +date = '2019-06-19' date_pd = pd.to_datetime(date) print("Historical Simulation Date: {}".format(date)) @@ -70,19 +70,19 @@ # 3) ExchangeAgent Config num_exchanges = 1 mkt_open = date_pd + pd.to_timedelta('09:30:00') -mkt_close = date_pd + pd.to_timedelta('09:30:05') +mkt_close = date_pd + pd.to_timedelta('09:35:00') print("ExchangeAgent num_exchanges: {}".format(num_exchanges)) print("ExchangeAgent mkt_open: {}".format(mkt_open)) print("ExchangeAgent mkt_close: {}".format(mkt_close)) -ea = ExchangeAgent(id = 0, - name = 'Exchange_Agent', - type = 'ExchangeAgent', - mkt_open = mkt_open, - mkt_close = mkt_close, - symbols = symbols, - log_orders=log_orders, - book_freq = '1s', +ea = ExchangeAgent(id = 0, + name = 'Exchange_Agent', + type = 'ExchangeAgent', + mkt_open = mkt_open, + mkt_close = mkt_close, + symbols = symbols, + log_orders = log_orders, + book_freq = None, pipeline_delay = 0, computation_delay = 0, stream_history = 10, @@ -91,48 +91,46 @@ agents.extend([ea]) # 4) MarketReplayAgent Config -num_mr_agents = 1 -cash_mr_agents = 10000000 - -mr_agents = [MarketReplayAgent(id = 1, - name = "Market_Replay_Agent", - symbol = symbols[0], - date = date, - startingCash = cash_mr_agents, - random_state = random_state)] -agents.extend(mr_agents) +market_replay_agents = [MarketReplayAgent(id = 1, + name = "Market_Replay_Agent", + type = 'MarketReplayAgent', + symbol = symbols[0], + log_orders = log_orders, + date = date, + starting_cash = 0, + random_state = random_state)] +agents.extend(market_replay_agents) # 5) ExperimentalAgent Config -num_exp_agents = 1 -cash_exp_agents = 10000000 - -exp_agents = [ExperimentalAgent(id = 2, +experimental_agents = [ExperimentalAgent(id = 2, name = "Experimental_Agent", symbol = symbols[0], - startingCash = cash_exp_agents, - execution_timestamp = pd.Timestamp("2012-06-21 09:30:02"), + starting_cash = 10000000, + log_orders = log_orders, + execution_timestamp = pd.Timestamp("2019-06-19 09:32:00"), quantity = 1000, is_buy_order = True, limit_price = 500, random_state = random_state)] -agents.extend(exp_agents) +agents.extend(experimental_agents) ####################################################################################################################### # 6) Kernel Parameters kernel = Kernel("Market Replay Kernel", random_state = random_state) kernelStartTime = date_pd + pd.to_timedelta('09:30:00') -kernelStopTime = date_pd + pd.to_timedelta('09:30:05') +kernelStopTime = date_pd + pd.to_timedelta('09:35:00') defaultComputationDelay = 0 latency = np.zeros((3, 3)) noise = [ 0.0 ] -# 7) Data Oracle -oracle = OrderBookOracle(symbol='AAPL', - date='2012-06-21', - orderbook_file_path='C:/_code/py/air/abides_open_source/abides/data/lob_data/AAPL_2012-06-21_34200000_57600000_orderbook_10.csv', - message_file_path='C:/_code/py/air/abides_open_source/abides/data/lob_data/AAPL_2012-06-21_34200000_57600000_message_10.csv', - num_price_levels=10) +oracle = RandomOrderBookOracle(symbol = 'AAPL', + market_open_ts = mkt_open, + market_close_ts = mkt_close, + buy_price_range = [90, 105], + sell_price_range = [95, 110], + quantity_range = [50, 500], + seed=seed) kernel.runner(agents = agents, startTime = kernelStartTime, stopTime = kernelStopTime, agentLatency = latency, diff --git a/notebooks/.ipynb_checkpoints/MarketReplayAgentAnalysis-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/MarketReplayAgentAnalysis-checkpoint.ipynb deleted file mode 100644 index 0aa6b87e4..000000000 --- a/notebooks/.ipynb_checkpoints/MarketReplayAgentAnalysis-checkpoint.ipynb +++ /dev/null @@ -1,423 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Simulation Logs" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "folder_path = 'C:/_code/py/air/abides_open_source/abides/'" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "orderbook_log_df = pd.read_pickle(folder_path + 'log/1560778365/orderbook_AAPL.bz2', compression='bz2')\n", - "summary_log_df = pd.read_pickle(folder_path + 'log/1560778365/summary_log.bz2', compression='bz2')" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "market_replay_agent_log_df = pd.read_pickle(folder_path + 'log/1560778365/Market_Replay_Agent.bz2', compression='bz2')\n", - "exchange_agent_log_df = pd.read_pickle(folder_path + 'log/1560778365/Exchange_Agent.bz2', compression='bz2')" - 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" - ], - "text/plain": [ - " Event EventType\n", - "EventTime \n", - "NaT 10000000 AGENT_TYPE\n", - "NaT 100000 STARTING_CASH\n", - "2012-06-21 09:30:00.000000 {'CASH': 100000} HOLDINGS_UPDATED\n", - "2012-06-21 09:30:00.004261 100000 MARKED_TO_MARKET\n", - "2012-06-21 09:30:00.004261 18.0 AAPL @ 585.32 == 10535.76 MARK_TO_MARKET" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "market_replay_agent_log_df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MARKED_TO_MARKET 377\n", - "MARK_TO_MARKET 188\n", - "FINAL_CASH_POSITION 1\n", - "FINAL_HOLDINGS 1\n", - "AGENT_TYPE 1\n", - "STARTING_CASH 1\n", - "ENDING_CASH 1\n", - "HOLDINGS_UPDATED 1\n", - "Name: EventType, dtype: int64" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "market_replay_agent_log_df.EventType.value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ORDER_ACCEPTED 184\n", - "BEST_BID 184\n", - "LIMIT_ORDER 184\n", - "BEST_ASK 183\n", - "ORDER_CANCELLED 131\n", - "CANCEL_ORDER 131\n", - "MODIFY_ORDER 27\n", - "REPLICATE_ORDERBOOK_SNAPSHOT 4\n", - "WHEN_MKT_CLOSE 2\n", - "WHEN_MKT_OPEN 2\n", - "AGENT_TYPE 1\n", - "Name: EventType, dtype: int64" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "exchange_agent_log_df.EventType.value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "conda_py_36", - "language": "python", - "name": "conda_py_36" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.5" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/.ipynb_checkpoints/OrderBookOracle-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/OrderBookOracle-checkpoint.ipynb deleted file mode 100644 index 871f05706..000000000 --- a/notebooks/.ipynb_checkpoints/OrderBookOracle-checkpoint.ipynb +++ /dev/null @@ -1,1357 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/efs/abides\n" - ] - } - ], - "source": [ - "cd ../" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from util.oracle.OrderBookOracle import OrderBookOracle" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### OrderBookOracle" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OrderBookOracle Message File: /efs/abides/data/LOBSTER/AAPL_2012-06-21_34200000_57600000_message_10.csv\n", - "OrderBookOracle Orderbook File: /efs/abides/data/LOBSTER/AAPL_2012-06-21_34200000_57600000_orderbook_10.csv\n", - "OrderBookOracle initialized for AAPL and date: 2012-06-21\n" - ] - } - ], - "source": [ - "obo = OrderBookOracle(symbol='AAPL',\n", - " date='2012-06-21',\n", - " orderbook_file_path='/efs/abides/data/LOBSTER/AAPL_2012-06-21_34200000_57600000_orderbook_10.csv', \n", - " message_file_path='/efs/abides/data/LOBSTER/AAPL_2012-06-21_34200000_57600000_message_10.csv',\n", - " num_price_levels=10)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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timestamp
2012-06-21 09:30:00.004260640585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100587.651160587.90500
2012-06-21 09:30:00.004447484585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100587.651160587.90500
2012-06-21 09:30:00.025551909585.9118585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100587.651160
2012-06-21 09:30:00.025579546585.9118585.9218585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100
2012-06-21 09:30:00.025613151585.9118585.9218585.9318585.94200585.98200586.10200586.89300586.9550587.00100587.1010
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" - ], - "text/plain": [ - " ask_price_1 ask_size_1 ask_price_2 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004260640 585.94 200 585.98 \n", - "2012-06-21 09:30:00.004447484 585.94 200 585.98 \n", - "2012-06-21 09:30:00.025551909 585.91 18 585.94 \n", - "2012-06-21 09:30:00.025579546 585.91 18 585.92 \n", - "2012-06-21 09:30:00.025613151 585.91 18 585.92 \n", - "\n", - " ask_size_2 ask_price_3 ask_size_3 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004260640 200 586.10 200 \n", - "2012-06-21 09:30:00.004447484 200 586.10 200 \n", - "2012-06-21 09:30:00.025551909 200 585.98 200 \n", - "2012-06-21 09:30:00.025579546 18 585.94 200 \n", - "2012-06-21 09:30:00.025613151 18 585.93 18 \n", - "\n", - " ask_price_4 ask_size_4 ask_price_5 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004260640 586.89 300 586.95 \n", - "2012-06-21 09:30:00.004447484 586.89 300 586.95 \n", - "2012-06-21 09:30:00.025551909 586.10 200 586.89 \n", - "2012-06-21 09:30:00.025579546 585.98 200 586.10 \n", - "2012-06-21 09:30:00.025613151 585.94 200 585.98 \n", - "\n", - " ask_size_5 ask_price_6 ask_size_6 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004260640 50 587.00 100 \n", - "2012-06-21 09:30:00.004447484 50 587.00 100 \n", - "2012-06-21 09:30:00.025551909 300 586.95 50 \n", - "2012-06-21 09:30:00.025579546 200 586.89 300 \n", - "2012-06-21 09:30:00.025613151 200 586.10 200 \n", - "\n", - " ask_price_7 ask_size_7 ask_price_8 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004260640 587.10 10 587.39 \n", - "2012-06-21 09:30:00.004447484 587.10 10 587.39 \n", - "2012-06-21 09:30:00.025551909 587.00 100 587.10 \n", - "2012-06-21 09:30:00.025579546 586.95 50 587.00 \n", - "2012-06-21 09:30:00.025613151 586.89 300 586.95 \n", - "\n", - " ask_size_8 ask_price_9 ask_size_9 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004260640 100 587.65 1160 \n", - "2012-06-21 09:30:00.004447484 100 587.65 1160 \n", - "2012-06-21 09:30:00.025551909 10 587.39 100 \n", - "2012-06-21 09:30:00.025579546 100 587.10 10 \n", - "2012-06-21 09:30:00.025613151 50 587.00 100 \n", - "\n", - " ask_price_10 ask_size_10 \n", - "timestamp \n", - "2012-06-21 09:30:00.004260640 587.90 500 \n", - "2012-06-21 09:30:00.004447484 587.90 500 \n", - "2012-06-21 09:30:00.025551909 587.65 1160 \n", - "2012-06-21 09:30:00.025579546 587.39 100 \n", - "2012-06-21 09:30:00.025613151 587.10 10 " - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "obo.asks().head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Order Book Metrics" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Orderbook snapshot @ t= 2012-06-21 09:30:00.004260640\n" - ] - } - ], - "source": [ - "t=pd.Timestamp('2012-06-21 09:30:00.004260640')\n", - "ob_snap = obo.orderbook_snapshot(t=t)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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bid_sizebidaskask_size
118585.33585.94200
218585.32585.98200
3150585.3586.1200
45585.1586.89300
589585.01586.9550
65584.97587100
7300584.93587.110
8300584.65587.39100
9300584.53587.651160
10200584.38587.9500
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" - ], - "text/plain": [ - " bid_size bid ask ask_size\n", - "1 18 585.33 585.94 200\n", - "2 18 585.32 585.98 200\n", - "3 150 585.3 586.1 200\n", - "4 5 585.1 586.89 300\n", - "5 89 585.01 586.95 50\n", - "6 5 584.97 587 100\n", - "7 300 584.93 587.1 10\n", - "8 300 584.65 587.39 100\n", - "9 300 584.53 587.65 1160\n", - "10 200 584.38 587.9 500" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ob_snap" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Best Bid: 585.33\n", - "Best Bid Size: 18.0\n", - "Best Ask: 585.94\n", - "Best Ask Size: 200.0\n", - "Mid Price: 585.635\n", - "Spread: 0.6100000000000136\n" - ] - } - ], - "source": [ - "print(\"Best Bid: {}\".format(obo.bestBid(ob_snap)))\n", - "print(\"Best Bid Size: {}\".format(obo.bestBidSize(ob_snap)))\n", - "print(\"Best Ask: {}\".format(obo.bestAsk(ob_snap)))\n", - "print(\"Best Ask Size: {}\".format(obo.bestAskSize(ob_snap)))\n", - "print(\"Mid Price: {}\".format(obo.midPrice(ob_snap)))\n", - "print(\"Spread: {}\".format(obo.spread(ob_snap)))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Order Book Visualisation" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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2012-06-21 09:30:00.025613585.3318585.3218585.3118585.3150585.105585.0189584.975584.93300584.65300584.53300
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" - ], - "text/plain": [ - " bid_price_1 bid_size_1 bid_price_2 bid_size_2 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004261 585.33 18 585.32 18 \n", - "2012-06-21 09:30:00.004447 585.33 18 585.32 18 \n", - "2012-06-21 09:30:00.025552 585.33 18 585.32 18 \n", - "2012-06-21 09:30:00.025580 585.33 18 585.32 18 \n", - "2012-06-21 09:30:00.025613 585.33 18 585.32 18 \n", - "\n", - " bid_price_3 bid_size_3 bid_price_4 bid_size_4 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004261 585.30 150 585.1 5 \n", - "2012-06-21 09:30:00.004447 585.31 18 585.3 150 \n", - "2012-06-21 09:30:00.025552 585.31 18 585.3 150 \n", - "2012-06-21 09:30:00.025580 585.31 18 585.3 150 \n", - "2012-06-21 09:30:00.025613 585.31 18 585.3 150 \n", - "\n", - " bid_price_5 bid_size_5 bid_price_6 bid_size_6 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004261 585.01 89 584.97 5 \n", - "2012-06-21 09:30:00.004447 585.10 5 585.01 89 \n", - "2012-06-21 09:30:00.025552 585.10 5 585.01 89 \n", - "2012-06-21 09:30:00.025580 585.10 5 585.01 89 \n", - "2012-06-21 09:30:00.025613 585.10 5 585.01 89 \n", - "\n", - " bid_price_7 bid_size_7 bid_price_8 bid_size_8 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004261 584.93 300 584.65 300 \n", - "2012-06-21 09:30:00.004447 584.97 5 584.93 300 \n", - "2012-06-21 09:30:00.025552 584.97 5 584.93 300 \n", - "2012-06-21 09:30:00.025580 584.97 5 584.93 300 \n", - "2012-06-21 09:30:00.025613 584.97 5 584.93 300 \n", - "\n", - " bid_price_9 bid_size_9 bid_price_10 bid_size_10 \n", - "timestamp \n", - "2012-06-21 09:30:00.004261 584.53 300 584.38 200 \n", - "2012-06-21 09:30:00.004447 584.65 300 584.53 300 \n", - "2012-06-21 09:30:00.025552 584.65 300 584.53 300 \n", - "2012-06-21 09:30:00.025580 584.65 300 584.53 300 \n", - "2012-06-21 09:30:00.025613 584.65 300 584.53 300 " - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "obo.bids().head()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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2012-06-21 09:30:00.004261585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100587.651160587.90500
2012-06-21 09:30:00.004447585.94200585.98200586.10200586.89300586.9550587.00100587.1010587.39100587.651160587.90500
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2012-06-21 09:30:00.025613585.9118585.9218585.9318585.94200585.98200586.10200586.89300586.9550587.00100587.1010
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" - ], - "text/plain": [ - " ask_price_1 ask_size_1 ask_price_2 ask_size_2 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004261 585.94 200 585.98 200 \n", - "2012-06-21 09:30:00.004447 585.94 200 585.98 200 \n", - "2012-06-21 09:30:00.025552 585.91 18 585.94 200 \n", - "2012-06-21 09:30:00.025580 585.91 18 585.92 18 \n", - "2012-06-21 09:30:00.025613 585.91 18 585.92 18 \n", - "\n", - " ask_price_3 ask_size_3 ask_price_4 ask_size_4 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004261 586.10 200 586.89 300 \n", - "2012-06-21 09:30:00.004447 586.10 200 586.89 300 \n", - "2012-06-21 09:30:00.025552 585.98 200 586.10 200 \n", - "2012-06-21 09:30:00.025580 585.94 200 585.98 200 \n", - "2012-06-21 09:30:00.025613 585.93 18 585.94 200 \n", - "\n", - " ask_price_5 ask_size_5 ask_price_6 ask_size_6 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004261 586.95 50 587.00 100 \n", - "2012-06-21 09:30:00.004447 586.95 50 587.00 100 \n", - "2012-06-21 09:30:00.025552 586.89 300 586.95 50 \n", - "2012-06-21 09:30:00.025580 586.10 200 586.89 300 \n", - "2012-06-21 09:30:00.025613 585.98 200 586.10 200 \n", - "\n", - " ask_price_7 ask_size_7 ask_price_8 ask_size_8 \\\n", - "timestamp \n", - "2012-06-21 09:30:00.004261 587.10 10 587.39 100 \n", - "2012-06-21 09:30:00.004447 587.10 10 587.39 100 \n", - "2012-06-21 09:30:00.025552 587.00 100 587.10 10 \n", - "2012-06-21 09:30:00.025580 586.95 50 587.00 100 \n", - "2012-06-21 09:30:00.025613 586.89 300 586.95 50 \n", - "\n", - " ask_price_9 ask_size_9 ask_price_10 ask_size_10 \n", - "timestamp \n", - "2012-06-21 09:30:00.004261 587.65 1160 587.90 500 \n", - "2012-06-21 09:30:00.004447 587.65 1160 587.90 500 \n", - "2012-06-21 09:30:00.025552 587.39 100 587.65 1160 \n", - "2012-06-21 09:30:00.025580 587.10 10 587.39 100 \n", - "2012-06-21 09:30:00.025613 587.00 100 587.10 10 " - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "obo.asks().head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Order Book Metrics" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Orderbook snapshot @ t= 2012-06-21 09:30:00.004261\n" - ] - } - ], - "source": [ - "t=pd.Timestamp('2012-06-21 09:30:00.004261')\n", - "ob_snap = obo.orderbook_snapshot(t=t)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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bid_sizebidaskask_size
118585.33585.94200
218585.32585.98200
3150585.3586.1200
45585.1586.89300
589585.01586.9550
65584.97587100
7300584.93587.110
8300584.65587.39100
9300584.53587.651160
10200584.38587.9500
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" - ], - "text/plain": [ - " bid_size bid ask ask_size\n", - "1 18 585.33 585.94 200\n", - "2 18 585.32 585.98 200\n", - "3 150 585.3 586.1 200\n", - "4 5 585.1 586.89 300\n", - "5 89 585.01 586.95 50\n", - "6 5 584.97 587 100\n", - "7 300 584.93 587.1 10\n", - "8 300 584.65 587.39 100\n", - "9 300 584.53 587.65 1160\n", - "10 200 584.38 587.9 500" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ob_snap" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Best Bid: 585.33\n", - "Best Bid Size: 18.0\n", - "Best Ask: 585.94\n", - "Best Ask Size: 200.0\n", - "Mid Price: 585.635\n", - "Spread: 0.6100000000000136\n" - ] - } - ], - "source": [ - "print(\"Best Bid: {}\".format(obo.bestBid(ob_snap)))\n", - "print(\"Best Bid Size: {}\".format(obo.bestBidSize(ob_snap)))\n", - "print(\"Best Ask: {}\".format(obo.bestAsk(ob_snap)))\n", - "print(\"Best Ask Size: {}\".format(obo.bestAskSize(ob_snap)))\n", - "print(\"Mid Price: {}\".format(obo.midPrice(ob_snap)))\n", - "print(\"Spread: {}\".format(obo.spread(ob_snap)))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Order Book Visualisation" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "obo.plotDepth(t, ob_snap)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "obo.plotPriceLevelVolume(obo.orderbook_df)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "conda_py_36", - "language": "python", - "name": "conda_py_36" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.5" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/util/OrderBook.py b/util/OrderBook.py index 6c27b314e..23fe5bd1e 100644 --- a/util/OrderBook.py +++ b/util/OrderBook.py @@ -4,11 +4,9 @@ import sys from message.Message import Message -from util.order.LimitOrder import LimitOrder from util.util import log_print, be_silent from copy import deepcopy -from agent.FinancialAgent import dollarize class OrderBook: @@ -29,10 +27,11 @@ def __init__ (self, owner, symbol): # Create an order history for the exchange to report to certain agent types. self.history = [{}] - self.bid_levels_price = dict() - self.bid_levels_size = dict() - self.ask_levels_price = dict() - self.ask_levels_size = dict() + self.mid_dict = dict() + self.bid_levels_price_dict = dict() + self.bid_levels_size_dict = dict() + self.ask_levels_price_dict = dict() + self.ask_levels_size_dict = dict() def handleLimitOrder (self, order): @@ -147,7 +146,7 @@ def handleLimitOrder (self, order): self.quotes_seen.add(quote) self.book_log.append(row) - self.updateOrderbookDataframe() + self.updateOrderbookLevelDicts() self.prettyPrint() @@ -333,11 +332,7 @@ def modifyOrder (self, order, new_order): self.bids = book else: self.asks = book - self.updateOrderbookDataframe() - - - def replicateOrderbookSnapshot(self): - self.updateOrderbookDataframe() + self.updateOrderbookLevelDicts() # Get the inside bid price(s) and share volume available at each price, to a limit @@ -368,9 +363,11 @@ def getInsideAsks (self, depth=sys.maxsize): return book - def updateOrderbookDataframe(self): - bid_list = self.getInsideBids(30) - ask_list = self.getInsideAsks(30) + def updateOrderbookLevelDicts(self): + if self.asks and self.bids: + self.mid_dict[self.owner.currentTime] = (self.asks[0][0].limit_price + self.bids[0][0].limit_price) / 2 + bid_list = self.getInsideBids(10) + ask_list = self.getInsideAsks(10) bldp = {} blds = {} sldp = {} @@ -379,14 +376,14 @@ def updateOrderbookDataframe(self): level += 1 bldp[level] = order[0] blds[level] = order[1] - self.bid_levels_price[self.owner.currentTime] = bldp - self.bid_levels_size[self.owner.currentTime] = blds + self.bid_levels_price_dict[self.owner.currentTime] = bldp + self.bid_levels_size_dict[self.owner.currentTime] = blds for level, order in enumerate(ask_list): level += 1 sldp[level] = order[0] slds[level] = order[1] - self.ask_levels_price[self.owner.currentTime] = sldp - self.ask_levels_size[self.owner.currentTime] = slds + self.ask_levels_price_dict[self.owner.currentTime] = sldp + self.ask_levels_size_dict[self.owner.currentTime] = slds # These could be moved to the LimitOrder class. We could even operator overload them diff --git a/util/oracle/OrderBookOracle.py b/util/oracle/OrderBookOracle.py deleted file mode 100644 index 9da661edd..000000000 --- a/util/oracle/OrderBookOracle.py +++ /dev/null @@ -1,269 +0,0 @@ -import pandas as pd -import numpy as np -import matplotlib.pyplot as plt -from matplotlib.dates import DateFormatter - -from util.util import log_print, delist - -class OrderBookOracle: - - - def __init__(self, symbol, date, orderbook_file_path, message_file_path, num_price_levels=10, filter_trades=False): - self.symbol = symbol - self.date = date - self.num_price_levels = num_price_levels - self.message_df = self.readMessageFile(message_file_path) - self.orderbook_df = self.readOrderbookFile(orderbook_file_path) - self.trades_df = self.filter_trades() if filter_trades else self.message_df - log_print("OrderBookOracle initialized for {} and date: {}".format(self.symbol, self.date)) - - - def readMessageFile(self, message_file_path): - """ - :return: a pandas Dataframe of the trade messages file for the given symbol and date - """ - log_print("OrderBookOracle Message File: {}".format(message_file_path)) - - direction = {-1: 'SELL', - 1: 'BUY'} - - order_type = { - 1: 'NEW', - 2: 'PARTIAL_CANCELLATION', - 3: 'CANCELLATION', - 4: 'EXECUTE_VISIBLE', - 5: 'EXECUTE_HIDDEN', - 7: 'TRADING_HALT' - } - - message_df = pd.read_csv(message_file_path) - message_df.columns = ['timestamp', 'type', 'order_id', 'vol', 'price', 'direction'] - message_df['timestamp'] = pd.to_datetime(self.date) + pd.to_timedelta(message_df['timestamp'], unit='s') - message_df['direction'] = message_df['direction'].replace(direction) - message_df['price'] = message_df['price'] / 10000 - message_df['type'] = message_df['type'].replace(order_type) - return message_df - - - def readOrderbookFile(self, orderbook_file_path): - """ - :return: a pandas Dataframe of the orderbook file for the given symbol and date - """ - log_print("OrderBookOracle Orderbook File: {}".format(orderbook_file_path)) - all_cols = delist([[f"ask_price_{level}", f"ask_size_{level}", f"bid_price_{level}", f"bid_size_{level}"] for level in range(1, self.num_price_levels+1)]) - price_cols = delist([[f"ask_price_{level}", f"bid_price_{level}"] for level in range(1, self.num_price_levels+1)]) - orderbook_df = pd.read_csv(orderbook_file_path) - orderbook_df.columns = all_cols - orderbook_df[price_cols] = orderbook_df[price_cols] / 10000 - orderbook_df = orderbook_df.join(self.message_df[['timestamp']]) - orderbook_df = orderbook_df[['timestamp'] + all_cols] - #orderbook_df = orderbook_df.drop_duplicates(subset=['timestamp'], keep='last') - orderbook_df.set_index('timestamp', inplace=True) - return orderbook_df - - - def bids(self): - """ - :return: bid side of the orderbook (pandas dataframe) - """ - orderbook_bid_cols = delist([[f"bid_price_{level}", f"bid_size_{level}"] for level in range(1, self.num_price_levels+1)]) - return self.orderbook_df[orderbook_bid_cols] - - - def asks(self): - """ - :return: ask side of the orderbook (pandas dataframe) - """ - orderbook_ask_cols = delist([[f"ask_price_{level}", f"ask_size_{level}"] for level in range(1, self.num_price_levels+1)]) - return self.orderbook_df[orderbook_ask_cols] - - - def orderbook_snapshot(self, t=None): - """ - :return: orderbook snapshot for a given timestamp (pandas dataframe) - """ - log_print(f"Orderbook snapshot @ t= {t}") - orderbook_snapshot = pd.DataFrame(columns=['bid_size', 'bid', 'ask', 'ask_size'], index=range(1, self.num_price_levels+1)) - bids = self.bids().loc[t] - asks = self.asks().loc[t] - level = 1 - for i in range(0, len(asks), 2): - bid_price = bids.iloc[i] - bid_size = bids.iloc[i + 1] - ask_price = asks.iloc[i] - ask_size = asks.iloc[i + 1] - orderbook_snapshot.loc[level] = [bid_size, bid_price, ask_price, ask_size] - level += 1 - return orderbook_snapshot - - - @staticmethod - def bestBid(ob_snap_t): - """Return int - best bid price for a given orderbook snapshot - """ - return ob_snap_t.loc[1]['bid'] - - - @staticmethod - def bestAsk(ob_snap_t): - """Return int - - best ask price for a given orderbook snapshot - """ - return ob_snap_t.loc[1]['ask'] - - - @staticmethod - def bestBidSize(ob_snap_t): - """Return int - - best bid size (volume) for a given orderbook snapshot - """ - return ob_snap_t.loc[1]['bid_size'] - - - @staticmethod - def bestAskSize(ob_snap_t): - """Return int - - best ask size (volume) for a given orderbook snapshot - """ - return ob_snap_t.loc[1]['ask_size'] - - - def midPrice(self, ob_snap_t): - """Return int - - mid price for a given orderbook snapshot - """ - return (self.bestBid(ob_snap_t) + self.bestAsk(ob_snap_t)) / 2 - - - def spread(self, ob_snap_t): - """Return int - - spread for a given orderbook snapshot - """ - return self.bestAsk(ob_snap_t) - self.bestBid(ob_snap_t) - - - def plotOrderbookSnapshotMetrics(self, t, ob_snap_t): - """ - at t, plot against l (x-axis): Pb, Pa, Sb, Sa, Pa+Pb/2, Pa-Pb, Pa+Pb - :param t: timestamp of the orderbook snapshot - :param ob_snap_t: orderbook snapshot dataframe - :return: None - """ - fig, axes = plt.subplots(nrows=2, ncols=3) - fig.set_size_inches(30, 10) - fig.suptitle(f"{self.symbol} Orderbook snapshot metrics @ {t}", size=20) - - fig.text(0.05, 0.95, - f"Best Bid: {self.bestBid(ob_snap_t)}, Best Ask: {self.bestAsk(ob_snap_t)}, Mid Price: {self.midPrice(ob_snap_t)}, " - f"Spread: {self.spread(ob_snap_t)}, Best Bid Size: {self.bestBidSize(ob_snap_t)}, Best Ask Size: {self.bestAskSize(ob_snap_t)}", - fontsize=14, verticalalignment='top') - axes[0, 0].plot(ob_snap_t.index, ob_snap_t.bid) - axes[0, 0].set_ylabel("Bid Price ( $Pb$ )", size=13) - - axes[0, 1].plot(ob_snap_t.index, ob_snap_t.ask) - axes[0, 1].set_ylabel("Ask Price ( $Pa$ )", size=13) - - axes[0, 2].plot(ob_snap_t.index, ob_snap_t.ask_size) - axes[0, 2].plot(ob_snap_t.index, ob_snap_t.bid_size) - axes[0, 2].set_ylabel("Bid nd Ask Sizes ( $Sb, Sa$ )", size=13) - axes[0, 2].legend() - - axes[1, 0].plot(ob_snap_t.index, ((ob_snap_t.ask + ob_snap_t.bid) / 2)) - axes[1, 0].set_ylabel("Mid Price ( $(Pa+Pb) / 2$ )", size=13) - - axes[1, 1].plot(ob_snap_t.index, (ob_snap_t.ask - ob_snap_t.bid)) - axes[1, 1].set_ylabel("Spread ( $Pa-Pb$ )", size=13) - - axes[1, 2].plot(ob_snap_t.index, (ob_snap_t.ask + ob_snap_t.bid)) - axes[1, 2].set_ylabel("$Pa + Pb$", size=13) - - for ax in axes: - for in_ax in ax: - in_ax.set_xlabel("Price Level", size=13) - - - def plotDepth(self, t, ob_snap_t): - """ - plots the orderbook depth for the given snapshot - :param t: timestamp of the orderbook snapshot - :param ob_snap_t: orderbook snapshot dataframe - :return: None - """ - fig, axes = plt.subplots(nrows=1, ncols=1) - fig.set_size_inches(20, 5) - axes.set_title(f"Orderbook Depth chart for {self.symbol} @ {t}") - axes.set_xlabel("Price ($)") - axes.set_ylabel("Cumulative Volume") - - plt.plot(ob_snap_t.bid, ob_snap_t.bid_size.cumsum(), color='green', marker='o') - axes.fill_between(ob_snap_t.bid.values.astype(float), 0, - ob_snap_t.bid_size.cumsum().values.astype(int), color='palegreen') - plt.bar(ob_snap_t.bid, ob_snap_t.bid_size, width=[0.01] * 10, color='grey') - - plt.plot(ob_snap_t.ask, ob_snap_t.ask_size.cumsum(), color='red', marker='o') - axes.fill_between(ob_snap_t.ask.values.astype(float), 0, - ob_snap_t.ask_size.cumsum().values.astype(int), color='salmon') - plt.bar(ob_snap_t.ask, ob_snap_t.ask_size, width=[0.01] * 10, color='grey', label='volume') - - plt.axvline(x=self.midPrice(ob_snap_t), label='mid') - plt.legend() - - - def plotPriceLevelVolume(self, orderbook_df): - """ - plot the price level coloured by volumes available at each level - :param orderbook_df: - :return: None - """ - - price_cols = delist([[f"ask_price_{level}", f"bid_price_{level}"] for level in range(1, self.num_price_levels+1)]) - size_cols = delist([[f"ask_size_{level}", f"bid_size_{level}"] for level in range(1, self.num_price_levels+1)]) - fig, ax = plt.subplots(nrows=1, ncols=1) - fig.set_size_inches(30, 15) - ax.set_title(f"Orderbook Price Level Volume for {self.symbol}, {self.num_price_levels} levels", size=22) - ax.set_xlabel("Time", size=24, fontweight='bold') - ax.set_ylabel("Price ($)", size=24, fontweight='bold') - ax.set_facecolor("white") - - mid_price = (orderbook_df.ask_price_1 + orderbook_df.bid_price_1) / 2 - - myFmt = DateFormatter("%H:%M") - ax.xaxis.set_major_formatter(myFmt) - ax.plot(orderbook_df.index, mid_price, color='black', label='mid price') - - for price_col, size_col in zip(price_cols, size_cols): - im = ax.scatter(x=orderbook_df.index, y=orderbook_df[price_col], c=np.log(orderbook_df[size_col]), s=0.7, - cmap=plt.cm.jet, alpha=0.7) - cbar = fig.colorbar(im, ax=ax, label='volume') - cbar.ax.get_yaxis().labelpad = 20 - cbar.ax.set_ylabel('Size', rotation=270, fontsize=20, fontweight='bold') - - - def filter_trades(self): - log_print("Original trades type counts:") - log_print(self.message_df.type.value_counts()) - trades_df = self.message_df.loc[self.message_df.type.isin(['NEW', 'CANCELLATION', 'PARTIAL_CANCELLATION', 'EXECUTE_VISIBLE'])] - order_id_types_series = trades_df.groupby('order_id')['type'].apply(list) - order_id_types_series = order_id_types_series.apply(lambda x: str(x)) - cancel_only_order_ids = list(order_id_types_series[order_id_types_series == "['CANCELLATION']"].index) - part_cancel_only_order_ids = list(order_id_types_series[order_id_types_series == "['PARTIAL_CANCELLATION']"].index) - trades_df = trades_df.loc[~trades_df.order_id.isin(cancel_only_order_ids + part_cancel_only_order_ids)] - log_print("Filtered trades type counts:") - log_print(trades_df.type.value_counts()) - return trades_df - - - def getDailyOpenPrice(self, symbol, mkt_open): - price = self.message_df.iloc[0]['price'] - log_print("Opening price at {} for {}".format(mkt_open, symbol)) - return price - - def observePrice(self, symbol, currentTime, sigma_n = 0): - return self.message_df.iloc[0]['price'] - diff --git a/util/oracle/RandomOrderBookOracle.py b/util/oracle/RandomOrderBookOracle.py new file mode 100644 index 000000000..dd2afbe9d --- /dev/null +++ b/util/oracle/RandomOrderBookOracle.py @@ -0,0 +1,59 @@ +import numpy as np +import pandas as pd + +from util.util import log_print + +class RandomOrderBookOracle: + order_id = 0 + + def __init__(self, symbol, + market_open_ts = pd.Timestamp("2019-06-18 09:30:00"), + market_close_ts = pd.Timestamp("2019-06-18 09:35:00"), + buy_price_range = [90, 105], sell_price_range = [95, 110], quantity_range = [50, 500], + seed=None): + self.symbol = symbol + self.market_open_ts = market_open_ts + self.market_close_ts = market_close_ts + self.buy_price_range = buy_price_range + self.sell_price_range = sell_price_range + self.quantity_range = quantity_range + self.random_state = np.random.RandomState(seed=seed) + np.random.seed(seed) + self.trades_df = self.generateTradesDataframe() + log_print("RandomOrderBookOracle initialized for {} and date: {}".format(self.symbol, + str(market_open_ts.date()))) + + def generateRandomTimestamps(self): + start_timestamp = self.market_open_ts + pd.Timedelta('1ms') + timestamp_list = [] + timestamp_list.append(start_timestamp) + current_timestamp = start_timestamp + while current_timestamp < self.market_close_ts: + delta_time = self.random_state.exponential(scale=1.0 / 0.005) + current_timestamp = current_timestamp + pd.Timedelta('{}ms'.format(int(round(delta_time)))) + timestamp_list.append(current_timestamp) + del timestamp_list[-1] + return timestamp_list + + def generateTradesDataframe(self): + trades_df = pd.DataFrame(columns=['timestamp', 'type', 'order_id', 'vol', 'price', 'direction']) + trades_df.timestamp = self.generateRandomTimestamps() + trades_df.set_index('timestamp', inplace=True) + trades_df.type = 'NEW' + for index, row in trades_df.iterrows(): + row['order_id'] = RandomOrderBookOracle.order_id + RandomOrderBookOracle.order_id += 1 + direction = np.random.randint(0, 2) + row['direction'] = 'BUY' if direction == 1 else 'SELL' + row['price'] = np.random.randint(self.buy_price_range[0], self.buy_price_range[1]) \ + if direction == 1 else np.random.randint(self.sell_price_range[0], self.sell_price_range[1]) + row['vol'] = np.random.randint(self.quantity_range[0], self.quantity_range[1]) + RandomOrderBookOracle.order_id = 0 + trades_df.reset_index(inplace=True) + log_print("RandomOrderBookOracle generated with {} synthetic random trades".format(len(trades_df))) + return trades_df + + def getDailyOpenPrice(self, symbol, mkt_open): + price = self.trades_df.iloc[0]['price'] + log_print("Opening price at {} for {}".format(mkt_open, symbol)) + return price \ No newline at end of file diff --git a/util/util.py b/util/util.py index 70ad298bb..0953a9622 100644 --- a/util/util.py +++ b/util/util.py @@ -21,8 +21,4 @@ def be_silent (): def delist(list_of_lists): - delisted_list = [] - for lst in list_of_lists: - for item in lst: - delisted_list.append(item) - return delisted_list + return [x for b in list_of_lists for x in b]