portfolio_management.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import datetime as datetime\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import talib\n",
    "import seaborn as sns\n",
    "from time import time\n",
    "import pytz\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from modules import RiskManagement as RM\n",
    "from modules import AccountManagement as AM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['DU1440139']\n",
      " ['U2909804']]\n"
     ]
    }
   ],
   "source": [
    "availabe_accounts = pd.read_csv('account_ids.txt',header=None)\n",
    "print (availabe_accounts.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "account_number = availabe_accounts.values[1][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "rth = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "if account_number == availabe_accounts.values[1][0]:\n",
    "\n",
    "    optimal_weights_regularized = pd.read_csv('data/optimal_weights_regularized_sa.csv',index_col = 'asset')\n",
    "    close = pd.read_csv('data/close_sa.csv', index_col = 'date')\n",
    "    \n",
    "elif account_number == availabe_accounts.values[0][0]:\n",
    "    \n",
    "    optimal_weights_regularized = pd.read_csv('output/optimal_weights_regularized.csv',index_col = 'asset')\n",
    "    close = pd.read_csv('data/close.csv', index_col = 'date')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Portfolio Reading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PositionEnd\n",
      "Reading Portfolio\n"
     ]
    }
   ],
   "source": [
    "portfolio = AM().read_positions(subscribe = True, acctCode = account_number)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Position</th>\n",
       "      <th>marketPrice</th>\n",
       "      <th>marketValue</th>\n",
       "      <th>averageCost</th>\n",
       "      <th>unrealizedPNL</th>\n",
       "      <th>realizedPNL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>10.0</td>\n",
       "      <td>119.540001</td>\n",
       "      <td>1195.40</td>\n",
       "      <td>117.280000</td>\n",
       "      <td>22.60</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABBV</th>\n",
       "      <td>9.0</td>\n",
       "      <td>97.570000</td>\n",
       "      <td>878.13</td>\n",
       "      <td>99.341111</td>\n",
       "      <td>-15.94</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB</th>\n",
       "      <td>-8.0</td>\n",
       "      <td>118.500000</td>\n",
       "      <td>-948.00</td>\n",
       "      <td>117.362287</td>\n",
       "      <td>-9.10</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALTR</th>\n",
       "      <td>-12.0</td>\n",
       "      <td>48.886299</td>\n",
       "      <td>-586.64</td>\n",
       "      <td>48.685467</td>\n",
       "      <td>-2.41</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMD</th>\n",
       "      <td>12.0</td>\n",
       "      <td>82.440002</td>\n",
       "      <td>989.28</td>\n",
       "      <td>75.949033</td>\n",
       "      <td>77.89</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3123.000000</td>\n",
       "      <td>3123.00</td>\n",
       "      <td>3035.900000</td>\n",
       "      <td>87.10</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATVI</th>\n",
       "      <td>14.0</td>\n",
       "      <td>77.699997</td>\n",
       "      <td>1087.80</td>\n",
       "      <td>80.811179</td>\n",
       "      <td>-43.56</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BABA</th>\n",
       "      <td>2.0</td>\n",
       "      <td>265.500000</td>\n",
       "      <td>531.00</td>\n",
       "      <td>285.250000</td>\n",
       "      <td>-39.50</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAKE</th>\n",
       "      <td>-10.0</td>\n",
       "      <td>34.660000</td>\n",
       "      <td>-346.60</td>\n",
       "      <td>37.499050</td>\n",
       "      <td>28.39</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CBRL</th>\n",
       "      <td>-3.0</td>\n",
       "      <td>127.000000</td>\n",
       "      <td>-381.00</td>\n",
       "      <td>134.743567</td>\n",
       "      <td>23.23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHTR</th>\n",
       "      <td>1.0</td>\n",
       "      <td>638.599976</td>\n",
       "      <td>638.60</td>\n",
       "      <td>629.800000</td>\n",
       "      <td>8.80</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CINF</th>\n",
       "      <td>-7.0</td>\n",
       "      <td>83.026398</td>\n",
       "      <td>-581.18</td>\n",
       "      <td>87.145100</td>\n",
       "      <td>28.83</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CLB</th>\n",
       "      <td>-20.0</td>\n",
       "      <td>17.590000</td>\n",
       "      <td>-351.80</td>\n",
       "      <td>18.469470</td>\n",
       "      <td>17.59</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CMA</th>\n",
       "      <td>-44.0</td>\n",
       "      <td>48.320000</td>\n",
       "      <td>-2126.08</td>\n",
       "      <td>51.686011</td>\n",
       "      <td>148.10</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CTRE</th>\n",
       "      <td>29.0</td>\n",
       "      <td>19.177099</td>\n",
       "      <td>556.14</td>\n",
       "      <td>19.634483</td>\n",
       "      <td>-13.26</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CWT</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>51.526199</td>\n",
       "      <td>-51.53</td>\n",
       "      <td>52.913200</td>\n",
       "      <td>1.39</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EA</th>\n",
       "      <td>30.0</td>\n",
       "      <td>119.809998</td>\n",
       "      <td>3594.30</td>\n",
       "      <td>126.443333</td>\n",
       "      <td>-199.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EBS</th>\n",
       "      <td>1.0</td>\n",
       "      <td>85.559998</td>\n",
       "      <td>85.56</td>\n",
       "      <td>90.305100</td>\n",
       "      <td>-4.75</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EQH</th>\n",
       "      <td>29.0</td>\n",
       "      <td>24.185499</td>\n",
       "      <td>701.38</td>\n",
       "      <td>24.814483</td>\n",
       "      <td>-18.24</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>2.0</td>\n",
       "      <td>276.699982</td>\n",
       "      <td>553.40</td>\n",
       "      <td>274.500000</td>\n",
       "      <td>4.40</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HRL</th>\n",
       "      <td>-12.0</td>\n",
       "      <td>51.709999</td>\n",
       "      <td>-620.52</td>\n",
       "      <td>51.215417</td>\n",
       "      <td>-5.93</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBM</th>\n",
       "      <td>7.0</td>\n",
       "      <td>115.080002</td>\n",
       "      <td>805.56</td>\n",
       "      <td>118.412857</td>\n",
       "      <td>-23.33</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KBH</th>\n",
       "      <td>28.0</td>\n",
       "      <td>33.009998</td>\n",
       "      <td>924.28</td>\n",
       "      <td>33.335714</td>\n",
       "      <td>-9.12</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KEY</th>\n",
       "      <td>-48.0</td>\n",
       "      <td>14.590000</td>\n",
       "      <td>-700.32</td>\n",
       "      <td>15.558704</td>\n",
       "      <td>46.50</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KR</th>\n",
       "      <td>18.0</td>\n",
       "      <td>32.099998</td>\n",
       "      <td>577.80</td>\n",
       "      <td>32.055556</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LEN</th>\n",
       "      <td>6.0</td>\n",
       "      <td>73.999199</td>\n",
       "      <td>444.00</td>\n",
       "      <td>75.636667</td>\n",
       "      <td>-9.82</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>6.0</td>\n",
       "      <td>216.750000</td>\n",
       "      <td>1300.50</td>\n",
       "      <td>212.686667</td>\n",
       "      <td>24.38</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCLH</th>\n",
       "      <td>-17.0</td>\n",
       "      <td>19.120001</td>\n",
       "      <td>-325.04</td>\n",
       "      <td>20.480606</td>\n",
       "      <td>23.13</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEM</th>\n",
       "      <td>14.0</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>924.00</td>\n",
       "      <td>64.381429</td>\n",
       "      <td>22.66</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NSP</th>\n",
       "      <td>1.0</td>\n",
       "      <td>88.754402</td>\n",
       "      <td>88.75</td>\n",
       "      <td>93.769400</td>\n",
       "      <td>-5.01</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NXST</th>\n",
       "      <td>7.0</td>\n",
       "      <td>95.349998</td>\n",
       "      <td>667.45</td>\n",
       "      <td>95.312857</td>\n",
       "      <td>0.26</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OI</th>\n",
       "      <td>-58.0</td>\n",
       "      <td>11.100000</td>\n",
       "      <td>-643.80</td>\n",
       "      <td>11.922376</td>\n",
       "      <td>47.70</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFE</th>\n",
       "      <td>10.0</td>\n",
       "      <td>37.750000</td>\n",
       "      <td>377.50</td>\n",
       "      <td>38.795000</td>\n",
       "      <td>-10.45</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHM</th>\n",
       "      <td>9.0</td>\n",
       "      <td>41.959999</td>\n",
       "      <td>377.64</td>\n",
       "      <td>42.861111</td>\n",
       "      <td>-8.11</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTEN</th>\n",
       "      <td>-50.0</td>\n",
       "      <td>3.230000</td>\n",
       "      <td>-161.50</td>\n",
       "      <td>3.619800</td>\n",
       "      <td>19.49</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QRVO</th>\n",
       "      <td>3.0</td>\n",
       "      <td>147.050003</td>\n",
       "      <td>441.15</td>\n",
       "      <td>143.763333</td>\n",
       "      <td>9.86</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RCL</th>\n",
       "      <td>-20.0</td>\n",
       "      <td>68.900002</td>\n",
       "      <td>-1378.00</td>\n",
       "      <td>73.758250</td>\n",
       "      <td>97.16</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REGN</th>\n",
       "      <td>1.0</td>\n",
       "      <td>558.250000</td>\n",
       "      <td>558.25</td>\n",
       "      <td>565.850000</td>\n",
       "      <td>-7.60</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RES</th>\n",
       "      <td>-208.0</td>\n",
       "      <td>2.591660</td>\n",
       "      <td>-539.07</td>\n",
       "      <td>2.764820</td>\n",
       "      <td>36.02</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RNST</th>\n",
       "      <td>-20.0</td>\n",
       "      <td>30.755699</td>\n",
       "      <td>-615.11</td>\n",
       "      <td>32.969150</td>\n",
       "      <td>44.27</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SHAK</th>\n",
       "      <td>-6.0</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>-456.00</td>\n",
       "      <td>79.751450</td>\n",
       "      <td>22.51</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SYNA</th>\n",
       "      <td>4.0</td>\n",
       "      <td>77.545502</td>\n",
       "      <td>310.18</td>\n",
       "      <td>79.780000</td>\n",
       "      <td>-8.94</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TCBI</th>\n",
       "      <td>-59.0</td>\n",
       "      <td>50.419998</td>\n",
       "      <td>-2974.78</td>\n",
       "      <td>52.991761</td>\n",
       "      <td>151.73</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TXRH</th>\n",
       "      <td>-8.0</td>\n",
       "      <td>72.456497</td>\n",
       "      <td>-579.65</td>\n",
       "      <td>76.573188</td>\n",
       "      <td>32.93</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TXT</th>\n",
       "      <td>-20.0</td>\n",
       "      <td>41.589802</td>\n",
       "      <td>-831.80</td>\n",
       "      <td>43.828910</td>\n",
       "      <td>44.78</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UAA</th>\n",
       "      <td>-3.0</td>\n",
       "      <td>14.380000</td>\n",
       "      <td>-43.14</td>\n",
       "      <td>14.977233</td>\n",
       "      <td>1.79</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WELL</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>62.879997</td>\n",
       "      <td>-62.88</td>\n",
       "      <td>54.517000</td>\n",
       "      <td>-8.36</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Position  marketPrice  marketValue  averageCost  unrealizedPNL  \\\n",
       "Symbol                                                                   \n",
       "AAPL        10.0   119.540001      1195.40   117.280000          22.60   \n",
       "ABBV         9.0    97.570000       878.13    99.341111         -15.94   \n",
       "ALB         -8.0   118.500000      -948.00   117.362287          -9.10   \n",
       "ALTR       -12.0    48.886299      -586.64    48.685467          -2.41   \n",
       "AMD         12.0    82.440002       989.28    75.949033          77.89   \n",
       "AMZN         1.0  3123.000000      3123.00  3035.900000          87.10   \n",
       "ATVI        14.0    77.699997      1087.80    80.811179         -43.56   \n",
       "BABA         2.0   265.500000       531.00   285.250000         -39.50   \n",
       "CAKE       -10.0    34.660000      -346.60    37.499050          28.39   \n",
       "CBRL        -3.0   127.000000      -381.00   134.743567          23.23   \n",
       "CHTR         1.0   638.599976       638.60   629.800000           8.80   \n",
       "CINF        -7.0    83.026398      -581.18    87.145100          28.83   \n",
       "CLB        -20.0    17.590000      -351.80    18.469470          17.59   \n",
       "CMA        -44.0    48.320000     -2126.08    51.686011         148.10   \n",
       "CTRE        29.0    19.177099       556.14    19.634483         -13.26   \n",
       "CWT         -1.0    51.526199       -51.53    52.913200           1.39   \n",
       "EA          30.0   119.809998      3594.30   126.443333        -199.00   \n",
       "EBS          1.0    85.559998        85.56    90.305100          -4.75   \n",
       "EQH         29.0    24.185499       701.38    24.814483         -18.24   \n",
       "FB           2.0   276.699982       553.40   274.500000           4.40   \n",
       "HRL        -12.0    51.709999      -620.52    51.215417          -5.93   \n",
       "IBM          7.0   115.080002       805.56   118.412857         -23.33   \n",
       "KBH         28.0    33.009998       924.28    33.335714          -9.12   \n",
       "KEY        -48.0    14.590000      -700.32    15.558704          46.50   \n",
       "KR          18.0    32.099998       577.80    32.055556           0.80   \n",
       "LEN          6.0    73.999199       444.00    75.636667          -9.82   \n",
       "MSFT         6.0   216.750000      1300.50   212.686667          24.38   \n",
       "NCLH       -17.0    19.120001      -325.04    20.480606          23.13   \n",
       "NEM         14.0    66.000000       924.00    64.381429          22.66   \n",
       "NSP          1.0    88.754402        88.75    93.769400          -5.01   \n",
       "NXST         7.0    95.349998       667.45    95.312857           0.26   \n",
       "OI         -58.0    11.100000      -643.80    11.922376          47.70   \n",
       "PFE         10.0    37.750000       377.50    38.795000         -10.45   \n",
       "PHM          9.0    41.959999       377.64    42.861111          -8.11   \n",
       "PTEN       -50.0     3.230000      -161.50     3.619800          19.49   \n",
       "QRVO         3.0   147.050003       441.15   143.763333           9.86   \n",
       "RCL        -20.0    68.900002     -1378.00    73.758250          97.16   \n",
       "REGN         1.0   558.250000       558.25   565.850000          -7.60   \n",
       "RES       -208.0     2.591660      -539.07     2.764820          36.02   \n",
       "RNST       -20.0    30.755699      -615.11    32.969150          44.27   \n",
       "SHAK        -6.0    76.000000      -456.00    79.751450          22.51   \n",
       "SYNA         4.0    77.545502       310.18    79.780000          -8.94   \n",
       "TCBI       -59.0    50.419998     -2974.78    52.991761         151.73   \n",
       "TXRH        -8.0    72.456497      -579.65    76.573188          32.93   \n",
       "TXT        -20.0    41.589802      -831.80    43.828910          44.78   \n",
       "UAA         -3.0    14.380000       -43.14    14.977233           1.79   \n",
       "WELL        -1.0    62.879997       -62.88    54.517000          -8.36   \n",
       "\n",
       "        realizedPNL  \n",
       "Symbol               \n",
       "AAPL            0.0  \n",
       "ABBV            0.0  \n",
       "ALB             0.0  \n",
       "ALTR            0.0  \n",
       "AMD             0.0  \n",
       "AMZN            0.0  \n",
       "ATVI            0.0  \n",
       "BABA            0.0  \n",
       "CAKE            0.0  \n",
       "CBRL            0.0  \n",
       "CHTR            0.0  \n",
       "CINF            0.0  \n",
       "CLB             0.0  \n",
       "CMA             0.0  \n",
       "CTRE            0.0  \n",
       "CWT             0.0  \n",
       "EA              0.0  \n",
       "EBS             0.0  \n",
       "EQH             0.0  \n",
       "FB              0.0  \n",
       "HRL             0.0  \n",
       "IBM             0.0  \n",
       "KBH             0.0  \n",
       "KEY            -0.0  \n",
       "KR              0.0  \n",
       "LEN             0.0  \n",
       "MSFT            0.0  \n",
       "NCLH            0.0  \n",
       "NEM             0.0  \n",
       "NSP             0.0  \n",
       "NXST           -0.0  \n",
       "OI              0.0  \n",
       "PFE             0.0  \n",
       "PHM             0.0  \n",
       "PTEN            0.0  \n",
       "QRVO            0.0  \n",
       "RCL             0.0  \n",
       "REGN            0.0  \n",
       "RES             0.0  \n",
       "RNST            0.0  \n",
       "SHAK           -0.0  \n",
       "SYNA            0.0  \n",
       "TCBI            0.0  \n",
       "TXRH            0.0  \n",
       "TXT            -0.0  \n",
       "UAA             0.0  \n",
       "WELL            0.0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AccountDownloadEnd. Account: U2909804\n",
      "Reading Account\n"
     ]
    }
   ],
   "source": [
    "acc = AM().read_account(subscribe = True, acctCode = account_number)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_weights, long, short, grv = RM.portfolio_calculation(portfolio)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gross Market Value: 37035.49 $\n",
      " Long Value: 21731.05 $\n",
      " Short Value: -15304.44 $\n",
      " Net Liquidation: 21423.85 $\n",
      " Unrealize PNL: 632.0 $\n",
      " Loan Value: 15611.63 $\n",
      "#####################################\n",
      "Leverage Value: 1.7287\n",
      " Long Leverage Value: 1.0143\n",
      " Short Leverage Value: 0.7144\n"
     ]
    }
   ],
   "source": [
    "long_value = long['marketValue'].sum()\n",
    "short_value = short['marketValue'].sum()\n",
    "#print ('Buying Power: {} $'.format(np.round(float(acc.loc['BuyingPower',:].values[0]), 4)))\n",
    "print ('Gross Market Value: {} $'.format(np.round(grv, 4)))\n",
    "print (' Long Value: {} $'.format(np.round(long_value,4)))\n",
    "print (' Short Value: {} $'.format(np.round(short_value,4)))\n",
    "print (' Net Liquidation: {} $'.format(np.round(float(acc.loc['EquityWithLoanValue',:].values[0]),4)))\n",
    "print (' Unrealize PNL: {} $'.format(np.round(portfolio['unrealizedPNL'].sum()),4))\n",
    "print (' Loan Value: {} $'.format(np.round(float(acc.loc['GrossPositionValue'][0]) - float(acc.loc['EquityWithLoanValue'][0]), 4)))\n",
    "print ('#####################################')\n",
    "print ('Leverage Value: {}'.format(np.round(grv/float(acc.loc['EquityWithLoanValue'][0]), 4)))\n",
    "print (' Long Leverage Value: {}'.format(np.round(long_value/float(acc.loc['EquityWithLoanValue'][0]), 4)))\n",
    "print (' Short Leverage Value: {}'.format(np.round(np.abs(short_value)/float(acc.loc['EquityWithLoanValue'][0]), 4)))       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "universe = portfolio.index\n",
    "long_universe = long.index \n",
    "short_universe = short.index "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "net_liq = np.round(float(acc.loc['EquityWithLoanValue',:].values[0]),4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Projected portfolio balance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-4899.715000000007 $\n"
     ]
    }
   ],
   "source": [
    "target_leverage = 1.5\n",
    "grv_target = net_liq * target_leverage\n",
    "excess_grv = grv_target - grv\n",
    "print (excess_grv,'$')\n",
    "marketVal_target = all_weights * grv_target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "balancing_order = marketVal_target['weights'] - portfolio['marketValue']\n",
    "df_port = portfolio['marketPrice']\n",
    "action_balance = pd.DataFrame(index = df_port.index, columns = ['shares'])\n",
    "action_balance['shares'] = np.round(balancing_order / df_port,2)\n",
    "to_drop = action_balance[action_balance['shares']==0.0].index\n",
    "action_balance.drop(to_drop,axis=0,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "32135.774999999998"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grv_target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NextValidId: 653\n"
     ]
    }
   ],
   "source": [
    "val = AM().read_nextvalidid()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filtering stocks with significant market value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_c = pd.DataFrame(data=close[optimal_weights_regularized.index].iloc[-1].values,\n",
    "                   index = close[optimal_weights_regularized.index].iloc[-1].index,\n",
    "                   columns = ['close'])\n",
    "df_c.index.name = 'asset'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(2, 1, figsize=(20, 15))\n",
    "\n",
    "x1 = all_weights.index\n",
    "y1 = all_weights.values.flatten()\n",
    "axs[0].grid(True)\n",
    "axs[0].bar(x1, y1, width = 0.8, linewidth = 1, color='orange')\n",
    "for tick in axs[0].get_xticklabels():\n",
    "    tick.set_rotation(45)\n",
    "axs[0].set_title('actual portfolio')\n",
    "\n",
    "x2 = optimal_weights_regularized.index\n",
    "y2 = optimal_weights_regularized.values.flatten()\n",
    "axs[1].grid(True,)\n",
    "axs[1].bar(x2, y2, width = 0.8, linewidth = 1, color='green')\n",
    "for tick in axs[1].get_xticklabels():\n",
    "    tick.set_rotation(45)\n",
    "axs[1].set_title('expected balanced portfolio')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Processing data for execution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "stock_to_balance = portfolio.index & optimal_weights_regularized.index\n",
    "stock_to_close = portfolio.index ^ stock_to_balance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_c_target = df_c.reindex(optimal_weights_regularized.index)\n",
    "shares_target_float = (optimal_weights_regularized * grv_target)['optimal_weights']/df_c_target['close']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "portfolio_shares_float = portfolio['marketValue'] / portfolio['marketPrice']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rebalance to optimal weights\n",
    "action_final = pd.DataFrame(index = shares_target_float.index, columns = ['shares'])\n",
    "\n",
    "for i in shares_target_float.index:\n",
    "    \n",
    "    if (i in stock_to_balance) and (i not in action_balance.index):\n",
    "        action_final.loc[i,'shares'] = shares_target_float[i] - portfolio_shares_float[i]\n",
    "        \n",
    "    elif (i in stock_to_balance) and (i in action_balance.index):\n",
    "        action_final.loc[i,'shares'] = shares_target_float[i] - (portfolio_shares_float[i] + action_balance['shares'][i])\n",
    "\n",
    "    elif (i in action_balance.index) and (i not in stock_to_balance):\n",
    "        action_final.loc[i,'shares'] = shares_target_float[i] + action_balance['shares'][i]\n",
    "    else:\n",
    "        action_final.loc[i,'shares'] = shares_target_float[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rename columns\n",
    "portfolio_shares_float = pd.DataFrame(portfolio_shares_float,columns = ['portfolio_shares'],index=portfolio_shares_float.index)\n",
    "shares_target_float = pd.DataFrame(shares_target_float,columns = ['target_shares_not_balanced'],index=shares_target_float.index)\n",
    "\n",
    "action_balance.columns = ['balance_lev_shares']\n",
    "action_final.columns = ['final_action_shares']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# replacing too small actions value with nan value\n",
    "treshold_long = 1\n",
    "treshold_short = -1\n",
    "\n",
    "action_final[(action_final['final_action_shares']>0) & (action_final['final_action_shares']< treshold_long)] = np.nan\n",
    "action_final[(action_final['final_action_shares']<0) & (action_final['final_action_shares']> treshold_short)] = np.nan\n",
    "action_final[action_final['final_action_shares']==0.0] = np.nan\n",
    "action_final.dropna(axis=0,inplace=True)\n",
    "action_final['final_action_shares'] = pd.to_numeric(action_final['final_action_shares'], errors='coerce')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "action_conc = pd.concat([portfolio_shares_float,\n",
    "                         action_balance,\n",
    "                         shares_target_float,\n",
    "                         action_final],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "isna_df = action_conc.isna()\n",
    "for i in action_conc.index:\n",
    "    if (isna_df.loc[i]['final_action_shares'] == True) & (isna_df.loc[i]['target_shares_not_balanced'] == False) :\n",
    "        action_conc.drop(i, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>portfolio_shares</th>\n",
       "      <th>balance_lev_shares</th>\n",
       "      <th>target_shares_not_balanced</th>\n",
       "      <th>final_action_shares</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>-1.32</td>\n",
       "      <td>11.384772</td>\n",
       "      <td>2.704772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABBV</th>\n",
       "      <td>9.000000</td>\n",
       "      <td>-1.19</td>\n",
       "      <td>9.654555</td>\n",
       "      <td>1.844555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB</th>\n",
       "      <td>-8.000000</td>\n",
       "      <td>1.06</td>\n",
       "      <td>-8.920257</td>\n",
       "      <td>-1.980257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALTR</th>\n",
       "      <td>-12.000090</td>\n",
       "      <td>1.61</td>\n",
       "      <td>-12.996443</td>\n",
       "      <td>-2.606353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMD</th>\n",
       "      <td>12.000000</td>\n",
       "      <td>-1.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATVI</th>\n",
       "      <td>14.000001</td>\n",
       "      <td>-1.84</td>\n",
       "      <td>17.158155</td>\n",
       "      <td>4.998154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BABA</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>-0.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAKE</th>\n",
       "      <td>-10.000000</td>\n",
       "      <td>1.28</td>\n",
       "      <td>-10.603761</td>\n",
       "      <td>-1.883761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CINF</th>\n",
       "      <td>-6.999942</td>\n",
       "      <td>0.92</td>\n",
       "      <td>-7.675003</td>\n",
       "      <td>-1.595061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CLB</th>\n",
       "      <td>-20.000000</td>\n",
       "      <td>2.64</td>\n",
       "      <td>-21.307736</td>\n",
       "      <td>-3.947736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CMA</th>\n",
       "      <td>-44.000000</td>\n",
       "      <td>5.83</td>\n",
       "      <td>-46.603399</td>\n",
       "      <td>-8.433399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CTRE</th>\n",
       "      <td>29.000215</td>\n",
       "      <td>-3.86</td>\n",
       "      <td>31.058853</td>\n",
       "      <td>5.918638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EA</th>\n",
       "      <td>30.000001</td>\n",
       "      <td>-3.96</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EQH</th>\n",
       "      <td>29.000022</td>\n",
       "      <td>-3.89</td>\n",
       "      <td>30.984816</td>\n",
       "      <td>5.874794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>-0.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HRL</th>\n",
       "      <td>-12.000000</td>\n",
       "      <td>1.56</td>\n",
       "      <td>-13.453696</td>\n",
       "      <td>-3.013696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBM</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>-0.91</td>\n",
       "      <td>8.343796</td>\n",
       "      <td>2.253797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KBH</th>\n",
       "      <td>28.000001</td>\n",
       "      <td>-3.66</td>\n",
       "      <td>30.050914</td>\n",
       "      <td>5.710913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KEY</th>\n",
       "      <td>-48.000000</td>\n",
       "      <td>6.37</td>\n",
       "      <td>-50.622995</td>\n",
       "      <td>-8.992995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KR</th>\n",
       "      <td>18.000001</td>\n",
       "      <td>-2.38</td>\n",
       "      <td>18.862392</td>\n",
       "      <td>3.242391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LEN</th>\n",
       "      <td>6.000065</td>\n",
       "      <td>-0.79</td>\n",
       "      <td>6.700544</td>\n",
       "      <td>1.490479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>-0.80</td>\n",
       "      <td>6.453267</td>\n",
       "      <td>1.253267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCLH</th>\n",
       "      <td>-16.999999</td>\n",
       "      <td>2.21</td>\n",
       "      <td>-18.322772</td>\n",
       "      <td>-3.532773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEM</th>\n",
       "      <td>14.000000</td>\n",
       "      <td>-1.88</td>\n",
       "      <td>15.141535</td>\n",
       "      <td>3.021535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NXST</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>-0.93</td>\n",
       "      <td>8.050751</td>\n",
       "      <td>1.980751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OI</th>\n",
       "      <td>-57.999998</td>\n",
       "      <td>7.63</td>\n",
       "      <td>-60.994046</td>\n",
       "      <td>-10.624048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFE</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>-1.32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHM</th>\n",
       "      <td>9.000000</td>\n",
       "      <td>-1.19</td>\n",
       "      <td>9.805151</td>\n",
       "      <td>1.995150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTEN</th>\n",
       "      <td>-50.000000</td>\n",
       "      <td>6.22</td>\n",
       "      <td>-52.855180</td>\n",
       "      <td>-9.075180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RCL</th>\n",
       "      <td>-20.000000</td>\n",
       "      <td>2.65</td>\n",
       "      <td>-21.097070</td>\n",
       "      <td>-3.747070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RES</th>\n",
       "      <td>-208.001821</td>\n",
       "      <td>26.97</td>\n",
       "      <td>-217.713617</td>\n",
       "      <td>-36.681796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RNST</th>\n",
       "      <td>-19.999870</td>\n",
       "      <td>2.65</td>\n",
       "      <td>-21.015598</td>\n",
       "      <td>-3.665728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SHAK</th>\n",
       "      <td>-6.000000</td>\n",
       "      <td>0.80</td>\n",
       "      <td>-6.500761</td>\n",
       "      <td>-1.300761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SYNA</th>\n",
       "      <td>3.999974</td>\n",
       "      <td>-0.52</td>\n",
       "      <td>4.738539</td>\n",
       "      <td>1.258565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TCBI</th>\n",
       "      <td>-59.000002</td>\n",
       "      <td>7.82</td>\n",
       "      <td>-62.045786</td>\n",
       "      <td>-10.865784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TXRH</th>\n",
       "      <td>-7.999973</td>\n",
       "      <td>1.04</td>\n",
       "      <td>-8.570064</td>\n",
       "      <td>-1.610091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TXT</th>\n",
       "      <td>-20.000095</td>\n",
       "      <td>2.61</td>\n",
       "      <td>-21.485959</td>\n",
       "      <td>-4.095864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WELL</th>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.13</td>\n",
       "      <td>-17.367085</td>\n",
       "      <td>-16.497085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BBY</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.003799</td>\n",
       "      <td>1.003799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CREE</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-12.451462</td>\n",
       "      <td>-12.451462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OHI</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.446126</td>\n",
       "      <td>18.446126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TLRY</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-36.612358</td>\n",
       "      <td>-36.612358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.005992</td>\n",
       "      <td>2.005992</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      portfolio_shares  balance_lev_shares  target_shares_not_balanced  \\\n",
       "AAPL         10.000000               -1.32                   11.384772   \n",
       "ABBV          9.000000               -1.19                    9.654555   \n",
       "ALB          -8.000000                1.06                   -8.920257   \n",
       "ALTR        -12.000090                1.61                  -12.996443   \n",
       "AMD          12.000000               -1.59                         NaN   \n",
       "ATVI         14.000001               -1.84                   17.158155   \n",
       "BABA          2.000000               -0.27                         NaN   \n",
       "CAKE        -10.000000                1.28                  -10.603761   \n",
       "CINF         -6.999942                0.92                   -7.675003   \n",
       "CLB         -20.000000                2.64                  -21.307736   \n",
       "CMA         -44.000000                5.83                  -46.603399   \n",
       "CTRE         29.000215               -3.86                   31.058853   \n",
       "EA           30.000001               -3.96                         NaN   \n",
       "EQH          29.000022               -3.89                   30.984816   \n",
       "FB            2.000000               -0.27                         NaN   \n",
       "HRL         -12.000000                1.56                  -13.453696   \n",
       "IBM           7.000000               -0.91                    8.343796   \n",
       "KBH          28.000001               -3.66                   30.050914   \n",
       "KEY         -48.000000                6.37                  -50.622995   \n",
       "KR           18.000001               -2.38                   18.862392   \n",
       "LEN           6.000065               -0.79                    6.700544   \n",
       "MSFT          6.000000               -0.80                    6.453267   \n",
       "NCLH        -16.999999                2.21                  -18.322772   \n",
       "NEM          14.000000               -1.88                   15.141535   \n",
       "NXST          7.000000               -0.93                    8.050751   \n",
       "OI          -57.999998                7.63                  -60.994046   \n",
       "PFE          10.000000               -1.32                         NaN   \n",
       "PHM           9.000000               -1.19                    9.805151   \n",
       "PTEN        -50.000000                6.22                  -52.855180   \n",
       "RCL         -20.000000                2.65                  -21.097070   \n",
       "RES        -208.001821               26.97                 -217.713617   \n",
       "RNST        -19.999870                2.65                  -21.015598   \n",
       "SHAK         -6.000000                0.80                   -6.500761   \n",
       "SYNA          3.999974               -0.52                    4.738539   \n",
       "TCBI        -59.000002                7.82                  -62.045786   \n",
       "TXRH         -7.999973                1.04                   -8.570064   \n",
       "TXT         -20.000095                2.61                  -21.485959   \n",
       "WELL         -1.000000                0.13                  -17.367085   \n",
       "BBY                NaN                 NaN                    1.003799   \n",
       "CREE               NaN                 NaN                  -12.451462   \n",
       "OHI                NaN                 NaN                   18.446126   \n",
       "TLRY               NaN                 NaN                  -36.612358   \n",
       "TSLA               NaN                 NaN                    2.005992   \n",
       "\n",
       "      final_action_shares  \n",
       "AAPL             2.704772  \n",
       "ABBV             1.844555  \n",
       "ALB             -1.980257  \n",
       "ALTR            -2.606353  \n",
       "AMD                   NaN  \n",
       "ATVI             4.998154  \n",
       "BABA                  NaN  \n",
       "CAKE            -1.883761  \n",
       "CINF            -1.595061  \n",
       "CLB             -3.947736  \n",
       "CMA             -8.433399  \n",
       "CTRE             5.918638  \n",
       "EA                    NaN  \n",
       "EQH              5.874794  \n",
       "FB                    NaN  \n",
       "HRL             -3.013696  \n",
       "IBM              2.253797  \n",
       "KBH              5.710913  \n",
       "KEY             -8.992995  \n",
       "KR               3.242391  \n",
       "LEN              1.490479  \n",
       "MSFT             1.253267  \n",
       "NCLH            -3.532773  \n",
       "NEM              3.021535  \n",
       "NXST             1.980751  \n",
       "OI             -10.624048  \n",
       "PFE                   NaN  \n",
       "PHM              1.995150  \n",
       "PTEN            -9.075180  \n",
       "RCL             -3.747070  \n",
       "RES            -36.681796  \n",
       "RNST            -3.665728  \n",
       "SHAK            -1.300761  \n",
       "SYNA             1.258565  \n",
       "TCBI           -10.865784  \n",
       "TXRH            -1.610091  \n",
       "TXT             -4.095864  \n",
       "WELL           -16.497085  \n",
       "BBY              1.003799  \n",
       "CREE           -12.451462  \n",
       "OHI             18.446126  \n",
       "TLRY           -36.612358  \n",
       "TSLA             2.005992  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "action_conc.head(50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Executing on TWS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "open order ended\n"
     ]
    }
   ],
   "source": [
    "op = AM.cancel_openorders()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "app is running ...\n",
      "closing 15 positions which are not present in action\n",
      "closing position for AGNC is: 58 \n",
      "closing position for ALL is: 59 \n",
      "closing position for AMD is: 12 \n",
      "closing position for AON is: 5 \n",
      "closing position for ARE is: 17 \n",
      "closing position for BABA is: 2 \n",
      "closing position for D is: 1 \n",
      "closing position for DD is: 17 \n",
      "closing position for EA is: 30 \n",
      "closing position for FB is: 2 \n",
      "closing position for ISRG is: 1 \n",
      "closing position for PANW is: 5 \n",
      "closing position for PFE is: 10 \n",
      "closing position for SWK is: 11 \n",
      "closing position for WDAY is: 3 \n"
     ]
    }
   ],
   "source": [
    "# closing positions not in shares target\n",
    "if not stock_to_close.empty:\n",
    "    next_order_id = AM.closing_positions(stock_to_close = stock_to_close,\n",
    "                                              portfolio = portfolio , \n",
    "                                              order_id = val,\n",
    "                                              ordersPriority = 'Patient',\n",
    "                                              transmit = True)\n",
    "else:\n",
    "    print ('There is no stock to close...')\n",
    "    next_order_id = val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "buy order quantity placed for AAPL is: 10 \n",
      "buy order quantity placed for ABBV is: 9 \n",
      "sell order quantity placed for ALB is: 8 \n",
      "sell order quantity placed for ALTR is: 12 \n",
      "sell order quantity placed for AMZN is: 1 \n",
      "buy order quantity placed for ATVI is: 4 \n",
      "sell order quantity placed for CAKE is: 10 \n",
      "sell order quantity placed for CBRL is: 3 \n",
      "buy order quantity placed for CHTR is: 1 \n",
      "sell order quantity placed for CINF is: 7 \n",
      "sell order quantity placed for CLB is: 20 \n",
      "sell order quantity placed for CMA is: 44 \n",
      "sell order quantity placed for CREE is: 11 \n",
      "buy order quantity placed for CTRE is: 29 \n",
      "sell order quantity placed for CWT is: 1 \n",
      "buy order quantity placed for EBS is: 1 \n",
      "buy order quantity placed for EQH is: 29 \n",
      "sell order quantity placed for HRL is: 12 \n",
      "buy order quantity placed for IBM is: 7 \n",
      "buy order quantity placed for KBH is: 28 \n",
      "sell order quantity placed for KEY is: 48 \n",
      "buy order quantity placed for KR is: 18 \n",
      "buy order quantity placed for LEN is: 6 \n",
      "buy order quantity placed for MSFT is: 6 \n",
      "sell order quantity placed for NCLH is: 17 \n",
      "buy order quantity placed for NEM is: 14 \n",
      "buy order quantity placed for NSP is: 1 \n",
      "buy order quantity placed for NXST is: 7 \n",
      "buy order quantity placed for OHI is: 17 \n",
      "sell order quantity placed for OI is: 58 \n",
      "buy order quantity placed for PHM is: 9 \n",
      "sell order quantity placed for PTEN is: 50 \n",
      "buy order quantity placed for QRVO is: 3 \n",
      "sell order quantity placed for RCL is: 20 \n",
      "buy order quantity placed for REGN is: 1 \n",
      "sell order quantity placed for RES is: 208 \n",
      "sell order quantity placed for RNST is: 20 \n",
      "sell order quantity placed for SHAK is: 6 \n",
      "buy order quantity placed for SYNA is: 4 \n",
      "sell order quantity placed for TCBI is: 59 \n",
      "sell order quantity placed for TLRY is: 35 \n",
      "buy order quantity placed for TSLA is: 1 \n",
      "sell order quantity placed for TXRH is: 8 \n",
      "sell order quantity placed for TXT is: 20 \n",
      "sell order quantity placed for UAA is: 3 \n",
      "sell order quantity placed for WELL is: 15 \n"
     ]
    }
   ],
   "source": [
    "action_final = action_final.astype('int')\n",
    "AM.placing_final_orders(action_final=action_final, \n",
    "                             order_id = next_order_id,\n",
    "                             ordersPriority = 'Patient',\n",
    "                             transmit = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we are not in regular trading hours...\n",
      "['AAPL', 'ABBV', 'AGNC', 'ALB', 'ALL', 'ALTR', 'AMD', 'AMZN', 'AON', 'ARE', 'ATVI', 'BABA', 'CAKE', 'CBRL', 'CHTR', 'CINF', 'CLB', 'CMA', 'CREE', 'CTRE', 'CWT', 'D', 'DD', 'EA', 'EBS', 'EQH', 'FB', 'HRL', 'IBM', 'ISRG', 'KBH', 'KEY', 'KR', 'LEN', 'MSFT', 'NCLH', 'NEM', 'NSP', 'NXST', 'OHI', 'OI', 'PANW', 'PFE', 'PHM', 'PTEN', 'QRVO', 'RCL', 'REGN', 'RES', 'RNST', 'SHAK', 'SYNA', 'TCBI', 'TLRY', 'TSLA', 'TXRH', 'TXT', 'UAA', 'WDAY', 'WELL']\n",
      "The orders above are not placed. please check manually or retry to run the functions...\n"
     ]
    }
   ],
   "source": [
    "if rth:\n",
    "    print ('we are in regular trading hours...')\n",
    "    open_orders_all = AM.get_openorders()\n",
    "    if list(open_orders_all.values) == []:\n",
    "        portfolio = AM.read_positions(subscribe = True, acctCode = account_number)\n",
    "        not_executed = portfolio.index ^ action_final.index\n",
    "        if list(not_executed)==[]:\n",
    "            print ('all orders are executed')\n",
    "        else:\n",
    "            print ('some orders still not executed')\n",
    "            print (not_executed)\n",
    "    \n",
    "else:\n",
    "    print ('we are not in regular trading hours...')\n",
    "    open_orders_all = AM.get_openorders()    \n",
    "    not_executed = open_orders_all.index ^ action_conc.index\n",
    "    \n",
    "    if list(not_executed)==[]:\n",
    "        print ('all orders are placed and ready to be executed...')\n",
    "    \n",
    "    else:\n",
    "        print (list(not_executed))\n",
    "        print ('The orders above are not placed. please check manually or retry to run the functions...')\n",
    "    \n",
    "    table = pd.concat([action_conc, open_orders_all[['open orders']]],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>portfolio_shares</th>\n",
       "      <th>balance_lev_shares</th>\n",
       "      <th>target_shares_not_balanced</th>\n",
       "      <th>final_action_shares</th>\n",
       "      <th>open orders</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AGNC</th>\n",
       "      <td>-58.000001</td>\n",
       "      <td>-11.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALL</th>\n",
       "      <td>59.000000</td>\n",
       "      <td>11.36</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMD</th>\n",
       "      <td>12.000000</td>\n",
       "      <td>2.32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.013073</td>\n",
       "      <td>-1.176927</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AON</th>\n",
       "      <td>-5.000025</td>\n",
       "      <td>-0.96</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TLRY</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-35.008881</td>\n",
       "      <td>-35.008881</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.918137</td>\n",
       "      <td>1.918137</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TXRH</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-8.194729</td>\n",
       "      <td>-8.194729</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TXT</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-20.544959</td>\n",
       "      <td>-20.544959</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UAA</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-3.134285</td>\n",
       "      <td>-3.134285</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>61 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      portfolio_shares  balance_lev_shares  target_shares_not_balanced  \\\n",
       "AGNC        -58.000001              -11.25                         NaN   \n",
       "ALL          59.000000               11.36                         NaN   \n",
       "AMD          12.000000                2.32                         NaN   \n",
       "AMZN          1.000000                0.19                    0.013073   \n",
       "AON          -5.000025               -0.96                         NaN   \n",
       "...                ...                 ...                         ...   \n",
       "TLRY               NaN                 NaN                  -35.008881   \n",
       "TSLA               NaN                 NaN                    1.918137   \n",
       "TXRH               NaN                 NaN                   -8.194729   \n",
       "TXT                NaN                 NaN                  -20.544959   \n",
       "UAA                NaN                 NaN                   -3.134285   \n",
       "\n",
       "      final_action_shares open orders  \n",
       "AGNC                  NaN         NaN  \n",
       "ALL                   NaN         NaN  \n",
       "AMD                   NaN         NaN  \n",
       "AMZN            -1.176927         NaN  \n",
       "AON                   NaN         NaN  \n",
       "...                   ...         ...  \n",
       "TLRY           -35.008881         NaN  \n",
       "TSLA             1.918137         NaN  \n",
       "TXRH            -8.194729         NaN  \n",
       "TXT            -20.544959         NaN  \n",
       "UAA             -3.134285         NaN  \n",
       "\n",
       "[61 rows x 5 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Commission report of last realized trades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "com = AM.commission_report(acctCode = account_number, time= '')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ticker</th>\n",
       "      <th>shares</th>\n",
       "      <th>action</th>\n",
       "      <th>price</th>\n",
       "      <th>marketValue</th>\n",
       "      <th>RealizedPNL</th>\n",
       "      <th>commission</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:11:45</th>\n",
       "      <td>JCI</td>\n",
       "      <td>100</td>\n",
       "      <td>BOT</td>\n",
       "      <td>42.42</td>\n",
       "      <td>4242</td>\n",
       "      <td>-216.021</td>\n",
       "      <td>0.670257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:11:45</th>\n",
       "      <td>JCI</td>\n",
       "      <td>100</td>\n",
       "      <td>BOT</td>\n",
       "      <td>42.42</td>\n",
       "      <td>4242</td>\n",
       "      <td>-216.021</td>\n",
       "      <td>0.670257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:11:45</th>\n",
       "      <td>JCI</td>\n",
       "      <td>5</td>\n",
       "      <td>BOT</td>\n",
       "      <td>42.42</td>\n",
       "      <td>212.1</td>\n",
       "      <td>-10.8011</td>\n",
       "      <td>0.033513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:11:53</th>\n",
       "      <td>EL</td>\n",
       "      <td>19</td>\n",
       "      <td>BOT</td>\n",
       "      <td>220.19</td>\n",
       "      <td>4183.61</td>\n",
       "      <td>-278.531</td>\n",
       "      <td>0.331257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:00</th>\n",
       "      <td>DE</td>\n",
       "      <td>49</td>\n",
       "      <td>BOT</td>\n",
       "      <td>229.76</td>\n",
       "      <td>11258.2</td>\n",
       "      <td>-801.009</td>\n",
       "      <td>0.301257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:06</th>\n",
       "      <td>SQ</td>\n",
       "      <td>10</td>\n",
       "      <td>BOT</td>\n",
       "      <td>180.91</td>\n",
       "      <td>1809.1</td>\n",
       "      <td>-293.106</td>\n",
       "      <td>0.340257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:13</th>\n",
       "      <td>ES</td>\n",
       "      <td>100</td>\n",
       "      <td>SLD</td>\n",
       "      <td>91.03</td>\n",
       "      <td>9103</td>\n",
       "      <td>1253.29</td>\n",
       "      <td>0.463334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:13</th>\n",
       "      <td>ES</td>\n",
       "      <td>100</td>\n",
       "      <td>SLD</td>\n",
       "      <td>91.03</td>\n",
       "      <td>9103</td>\n",
       "      <td>1253.29</td>\n",
       "      <td>0.463334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:15</th>\n",
       "      <td>VLO</td>\n",
       "      <td>100</td>\n",
       "      <td>SLD</td>\n",
       "      <td>44.15</td>\n",
       "      <td>4415</td>\n",
       "      <td>17.5189</td>\n",
       "      <td>0.359729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:15</th>\n",
       "      <td>VLO</td>\n",
       "      <td>63</td>\n",
       "      <td>SLD</td>\n",
       "      <td>44.15</td>\n",
       "      <td>2781.45</td>\n",
       "      <td>11.0369</td>\n",
       "      <td>0.226629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:16</th>\n",
       "      <td>GLW</td>\n",
       "      <td>200</td>\n",
       "      <td>BOT</td>\n",
       "      <td>34.16</td>\n",
       "      <td>6832</td>\n",
       "      <td>-421.494</td>\n",
       "      <td>1.34051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:16</th>\n",
       "      <td>GLW</td>\n",
       "      <td>300</td>\n",
       "      <td>BOT</td>\n",
       "      <td>34.16</td>\n",
       "      <td>10248</td>\n",
       "      <td>-632.241</td>\n",
       "      <td>2.01077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:16</th>\n",
       "      <td>GLW</td>\n",
       "      <td>200</td>\n",
       "      <td>BOT</td>\n",
       "      <td>34.16</td>\n",
       "      <td>6832</td>\n",
       "      <td>-421.494</td>\n",
       "      <td>1.34051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:16</th>\n",
       "      <td>GLW</td>\n",
       "      <td>3</td>\n",
       "      <td>BOT</td>\n",
       "      <td>34.16</td>\n",
       "      <td>102.48</td>\n",
       "      <td>-6.32241</td>\n",
       "      <td>0.020108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:19</th>\n",
       "      <td>ADP</td>\n",
       "      <td>100</td>\n",
       "      <td>SLD</td>\n",
       "      <td>144.15</td>\n",
       "      <td>14415</td>\n",
       "      <td>646.575</td>\n",
       "      <td>0.490729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:19</th>\n",
       "      <td>ADP</td>\n",
       "      <td>72</td>\n",
       "      <td>SLD</td>\n",
       "      <td>144.15</td>\n",
       "      <td>10378.8</td>\n",
       "      <td>465.534</td>\n",
       "      <td>0.353325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:25</th>\n",
       "      <td>K</td>\n",
       "      <td>100</td>\n",
       "      <td>SLD</td>\n",
       "      <td>65.63</td>\n",
       "      <td>6563</td>\n",
       "      <td>458.923</td>\n",
       "      <td>0.8272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:28</th>\n",
       "      <td>ES</td>\n",
       "      <td>100</td>\n",
       "      <td>SLD</td>\n",
       "      <td>91.03</td>\n",
       "      <td>9103</td>\n",
       "      <td>1253.29</td>\n",
       "      <td>0.463334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:41</th>\n",
       "      <td>WDAY</td>\n",
       "      <td>8</td>\n",
       "      <td>BOT</td>\n",
       "      <td>220.66</td>\n",
       "      <td>1765.28</td>\n",
       "      <td>-21.8752</td>\n",
       "      <td>0.335057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:12:50</th>\n",
       "      <td>ES</td>\n",
       "      <td>1</td>\n",
       "      <td>SLD</td>\n",
       "      <td>91.06</td>\n",
       "      <td>91.06</td>\n",
       "      <td>12.5629</td>\n",
       "      <td>0.004634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:13:02</th>\n",
       "      <td>LMT</td>\n",
       "      <td>12</td>\n",
       "      <td>SLD</td>\n",
       "      <td>384.83</td>\n",
       "      <td>4617.96</td>\n",
       "      <td>-103.31</td>\n",
       "      <td>0.441742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:13:08</th>\n",
       "      <td>Z</td>\n",
       "      <td>21</td>\n",
       "      <td>BOT</td>\n",
       "      <td>108.82</td>\n",
       "      <td>2285.22</td>\n",
       "      <td>-310.734</td>\n",
       "      <td>0.310357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:13:13</th>\n",
       "      <td>LRCX</td>\n",
       "      <td>1</td>\n",
       "      <td>SLD</td>\n",
       "      <td>348.54</td>\n",
       "      <td>348.54</td>\n",
       "      <td>32.4423</td>\n",
       "      <td>0.356179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:13:18</th>\n",
       "      <td>K</td>\n",
       "      <td>52</td>\n",
       "      <td>SLD</td>\n",
       "      <td>65.64</td>\n",
       "      <td>3413.28</td>\n",
       "      <td>239.378</td>\n",
       "      <td>0.211755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:13:31</th>\n",
       "      <td>ROK</td>\n",
       "      <td>2</td>\n",
       "      <td>SLD</td>\n",
       "      <td>236.37</td>\n",
       "      <td>472.74</td>\n",
       "      <td>48.0746</td>\n",
       "      <td>0.358943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:13:39</th>\n",
       "      <td>STT</td>\n",
       "      <td>15</td>\n",
       "      <td>SLD</td>\n",
       "      <td>62.24</td>\n",
       "      <td>933.6</td>\n",
       "      <td>65.007</td>\n",
       "      <td>0.357675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:13:50</th>\n",
       "      <td>TMO</td>\n",
       "      <td>27</td>\n",
       "      <td>BOT</td>\n",
       "      <td>448.07</td>\n",
       "      <td>12097.9</td>\n",
       "      <td>-674.187</td>\n",
       "      <td>0.323257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:14:01</th>\n",
       "      <td>KLAC</td>\n",
       "      <td>31</td>\n",
       "      <td>SLD</td>\n",
       "      <td>202.35</td>\n",
       "      <td>6272.85</td>\n",
       "      <td>691.967</td>\n",
       "      <td>0.433676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:14:01</th>\n",
       "      <td>FE</td>\n",
       "      <td>100</td>\n",
       "      <td>BOT</td>\n",
       "      <td>30.64</td>\n",
       "      <td>3064</td>\n",
       "      <td>-5.9329</td>\n",
       "      <td>0.320257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:14:01</th>\n",
       "      <td>FE</td>\n",
       "      <td>200</td>\n",
       "      <td>BOT</td>\n",
       "      <td>30.64</td>\n",
       "      <td>6128</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>1.34051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:14:31</th>\n",
       "      <td>INTC</td>\n",
       "      <td>85</td>\n",
       "      <td>BOT</td>\n",
       "      <td>52.31</td>\n",
       "      <td>4446.35</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.544219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:14:34</th>\n",
       "      <td>RCL</td>\n",
       "      <td>13</td>\n",
       "      <td>SLD</td>\n",
       "      <td>69.18</td>\n",
       "      <td>899.34</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.35868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:14:39</th>\n",
       "      <td>CNP</td>\n",
       "      <td>200</td>\n",
       "      <td>SLD</td>\n",
       "      <td>20.76</td>\n",
       "      <td>4152</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>1.45607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:14:39</th>\n",
       "      <td>CNP</td>\n",
       "      <td>898</td>\n",
       "      <td>SLD</td>\n",
       "      <td>20.76</td>\n",
       "      <td>18642.5</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>6.53777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:14:39</th>\n",
       "      <td>CNP</td>\n",
       "      <td>100</td>\n",
       "      <td>SLD</td>\n",
       "      <td>20.76</td>\n",
       "      <td>2076</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.728037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:14:43</th>\n",
       "      <td>GM</td>\n",
       "      <td>300</td>\n",
       "      <td>SLD</td>\n",
       "      <td>31.36</td>\n",
       "      <td>9408</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.994389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:14:43</th>\n",
       "      <td>GM</td>\n",
       "      <td>200</td>\n",
       "      <td>SLD</td>\n",
       "      <td>31.36</td>\n",
       "      <td>6272</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>1.44293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:14:43</th>\n",
       "      <td>GM</td>\n",
       "      <td>23</td>\n",
       "      <td>SLD</td>\n",
       "      <td>31.36</td>\n",
       "      <td>721.28</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.172836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:15:12</th>\n",
       "      <td>WYNN</td>\n",
       "      <td>100</td>\n",
       "      <td>BOT</td>\n",
       "      <td>77.07</td>\n",
       "      <td>7707</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.160257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:15:14</th>\n",
       "      <td>WYNN</td>\n",
       "      <td>100</td>\n",
       "      <td>BOT</td>\n",
       "      <td>77.07</td>\n",
       "      <td>7707</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.160257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:15:14</th>\n",
       "      <td>WYNN</td>\n",
       "      <td>66</td>\n",
       "      <td>BOT</td>\n",
       "      <td>77.07</td>\n",
       "      <td>5086.62</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.10577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:15:29</th>\n",
       "      <td>CTXS</td>\n",
       "      <td>44</td>\n",
       "      <td>BOT</td>\n",
       "      <td>135.4</td>\n",
       "      <td>5957.6</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.266657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:15:30</th>\n",
       "      <td>AXP</td>\n",
       "      <td>16</td>\n",
       "      <td>SLD</td>\n",
       "      <td>104.95</td>\n",
       "      <td>1679.2</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.373272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:15:48</th>\n",
       "      <td>NKE</td>\n",
       "      <td>36</td>\n",
       "      <td>BOT</td>\n",
       "      <td>130.33</td>\n",
       "      <td>4691.88</td>\n",
       "      <td>-177.133</td>\n",
       "      <td>0.314257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:16:01</th>\n",
       "      <td>CRM</td>\n",
       "      <td>37</td>\n",
       "      <td>SLD</td>\n",
       "      <td>254.14</td>\n",
       "      <td>9403.18</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.525471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:16:11</th>\n",
       "      <td>GE</td>\n",
       "      <td>345</td>\n",
       "      <td>SLD</td>\n",
       "      <td>6.53</td>\n",
       "      <td>2252.85</td>\n",
       "      <td>-2.12813</td>\n",
       "      <td>1.36823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:16:12</th>\n",
       "      <td>BDX</td>\n",
       "      <td>84</td>\n",
       "      <td>BOT</td>\n",
       "      <td>238.36</td>\n",
       "      <td>20022.2</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.266257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:16:30</th>\n",
       "      <td>SRE</td>\n",
       "      <td>100</td>\n",
       "      <td>BOT</td>\n",
       "      <td>123.75</td>\n",
       "      <td>12375</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.670257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:16:30</th>\n",
       "      <td>SRE</td>\n",
       "      <td>100</td>\n",
       "      <td>BOT</td>\n",
       "      <td>123.75</td>\n",
       "      <td>12375</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.640257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:16:48</th>\n",
       "      <td>PSA</td>\n",
       "      <td>100</td>\n",
       "      <td>BOT</td>\n",
       "      <td>230.34</td>\n",
       "      <td>23034</td>\n",
       "      <td>-1653.89</td>\n",
       "      <td>0.250257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:17:11</th>\n",
       "      <td>SRE</td>\n",
       "      <td>41</td>\n",
       "      <td>BOT</td>\n",
       "      <td>123.7</td>\n",
       "      <td>5071.7</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.102605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:17:47</th>\n",
       "      <td>SIRI</td>\n",
       "      <td>200</td>\n",
       "      <td>SLD</td>\n",
       "      <td>5.66</td>\n",
       "      <td>1132</td>\n",
       "      <td>130.202</td>\n",
       "      <td>0.469332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:18:29</th>\n",
       "      <td>SYY</td>\n",
       "      <td>14</td>\n",
       "      <td>BOT</td>\n",
       "      <td>65</td>\n",
       "      <td>910</td>\n",
       "      <td>-73.6327</td>\n",
       "      <td>0.336257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:18:30</th>\n",
       "      <td>SIRI</td>\n",
       "      <td>200</td>\n",
       "      <td>SLD</td>\n",
       "      <td>5.66</td>\n",
       "      <td>1132</td>\n",
       "      <td>130.202</td>\n",
       "      <td>0.469332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:18:47</th>\n",
       "      <td>SIRI</td>\n",
       "      <td>4307</td>\n",
       "      <td>SLD</td>\n",
       "      <td>5.65</td>\n",
       "      <td>24334.6</td>\n",
       "      <td>2742.3</td>\n",
       "      <td>28.6262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:19:22</th>\n",
       "      <td>DHR</td>\n",
       "      <td>100</td>\n",
       "      <td>SLD</td>\n",
       "      <td>218.55</td>\n",
       "      <td>21855</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.745153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:19:22</th>\n",
       "      <td>DHR</td>\n",
       "      <td>100</td>\n",
       "      <td>SLD</td>\n",
       "      <td>218.55</td>\n",
       "      <td>21855</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.745153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:19:22</th>\n",
       "      <td>DHR</td>\n",
       "      <td>19</td>\n",
       "      <td>SLD</td>\n",
       "      <td>218.55</td>\n",
       "      <td>4152.45</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.141579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:20:23</th>\n",
       "      <td>PSA</td>\n",
       "      <td>10</td>\n",
       "      <td>BOT</td>\n",
       "      <td>230.34</td>\n",
       "      <td>2303.4</td>\n",
       "      <td>-165.389</td>\n",
       "      <td>0.025026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-06 13:21:18</th>\n",
       "      <td>ISRG</td>\n",
       "      <td>5</td>\n",
       "      <td>BOT</td>\n",
       "      <td>709.15</td>\n",
       "      <td>3545.75</td>\n",
       "      <td>42.6668</td>\n",
       "      <td>0.340757</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>69 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    ticker shares action   price marketValue RealizedPNL  \\\n",
       "time                                                                       \n",
       "2020-10-06 13:11:45    JCI    100    BOT   42.42        4242    -216.021   \n",
       "2020-10-06 13:11:45    JCI    100    BOT   42.42        4242    -216.021   \n",
       "2020-10-06 13:11:45    JCI      5    BOT   42.42       212.1    -10.8011   \n",
       "2020-10-06 13:11:53     EL     19    BOT  220.19     4183.61    -278.531   \n",
       "2020-10-06 13:12:00     DE     49    BOT  229.76     11258.2    -801.009   \n",
       "2020-10-06 13:12:06     SQ     10    BOT  180.91      1809.1    -293.106   \n",
       "2020-10-06 13:12:13     ES    100    SLD   91.03        9103     1253.29   \n",
       "2020-10-06 13:12:13     ES    100    SLD   91.03        9103     1253.29   \n",
       "2020-10-06 13:12:15    VLO    100    SLD   44.15        4415     17.5189   \n",
       "2020-10-06 13:12:15    VLO     63    SLD   44.15     2781.45     11.0369   \n",
       "2020-10-06 13:12:16    GLW    200    BOT   34.16        6832    -421.494   \n",
       "2020-10-06 13:12:16    GLW    300    BOT   34.16       10248    -632.241   \n",
       "2020-10-06 13:12:16    GLW    200    BOT   34.16        6832    -421.494   \n",
       "2020-10-06 13:12:16    GLW      3    BOT   34.16      102.48    -6.32241   \n",
       "2020-10-06 13:12:19    ADP    100    SLD  144.15       14415     646.575   \n",
       "2020-10-06 13:12:19    ADP     72    SLD  144.15     10378.8     465.534   \n",
       "2020-10-06 13:12:25      K    100    SLD   65.63        6563     458.923   \n",
       "2020-10-06 13:12:28     ES    100    SLD   91.03        9103     1253.29   \n",
       "2020-10-06 13:12:41   WDAY      8    BOT  220.66     1765.28    -21.8752   \n",
       "2020-10-06 13:12:50     ES      1    SLD   91.06       91.06     12.5629   \n",
       "2020-10-06 13:13:02    LMT     12    SLD  384.83     4617.96     -103.31   \n",
       "2020-10-06 13:13:08      Z     21    BOT  108.82     2285.22    -310.734   \n",
       "2020-10-06 13:13:13   LRCX      1    SLD  348.54      348.54     32.4423   \n",
       "2020-10-06 13:13:18      K     52    SLD   65.64     3413.28     239.378   \n",
       "2020-10-06 13:13:31    ROK      2    SLD  236.37      472.74     48.0746   \n",
       "2020-10-06 13:13:39    STT     15    SLD   62.24       933.6      65.007   \n",
       "2020-10-06 13:13:50    TMO     27    BOT  448.07     12097.9    -674.187   \n",
       "2020-10-06 13:14:01   KLAC     31    SLD  202.35     6272.85     691.967   \n",
       "2020-10-06 13:14:01     FE    100    BOT   30.64        3064     -5.9329   \n",
       "2020-10-06 13:14:01     FE    200    BOT   30.64        6128        OPEN   \n",
       "...                    ...    ...    ...     ...         ...         ...   \n",
       "2020-10-06 13:14:31   INTC     85    BOT   52.31     4446.35        OPEN   \n",
       "2020-10-06 13:14:34    RCL     13    SLD   69.18      899.34        OPEN   \n",
       "2020-10-06 13:14:39    CNP    200    SLD   20.76        4152        OPEN   \n",
       "2020-10-06 13:14:39    CNP    898    SLD   20.76     18642.5        OPEN   \n",
       "2020-10-06 13:14:39    CNP    100    SLD   20.76        2076        OPEN   \n",
       "2020-10-06 13:14:43     GM    300    SLD   31.36        9408        OPEN   \n",
       "2020-10-06 13:14:43     GM    200    SLD   31.36        6272        OPEN   \n",
       "2020-10-06 13:14:43     GM     23    SLD   31.36      721.28        OPEN   \n",
       "2020-10-06 13:15:12   WYNN    100    BOT   77.07        7707        OPEN   \n",
       "2020-10-06 13:15:14   WYNN    100    BOT   77.07        7707        OPEN   \n",
       "2020-10-06 13:15:14   WYNN     66    BOT   77.07     5086.62        OPEN   \n",
       "2020-10-06 13:15:29   CTXS     44    BOT   135.4      5957.6        OPEN   \n",
       "2020-10-06 13:15:30    AXP     16    SLD  104.95      1679.2        OPEN   \n",
       "2020-10-06 13:15:48    NKE     36    BOT  130.33     4691.88    -177.133   \n",
       "2020-10-06 13:16:01    CRM     37    SLD  254.14     9403.18        OPEN   \n",
       "2020-10-06 13:16:11     GE    345    SLD    6.53     2252.85    -2.12813   \n",
       "2020-10-06 13:16:12    BDX     84    BOT  238.36     20022.2        OPEN   \n",
       "2020-10-06 13:16:30    SRE    100    BOT  123.75       12375        OPEN   \n",
       "2020-10-06 13:16:30    SRE    100    BOT  123.75       12375        OPEN   \n",
       "2020-10-06 13:16:48    PSA    100    BOT  230.34       23034    -1653.89   \n",
       "2020-10-06 13:17:11    SRE     41    BOT   123.7      5071.7        OPEN   \n",
       "2020-10-06 13:17:47   SIRI    200    SLD    5.66        1132     130.202   \n",
       "2020-10-06 13:18:29    SYY     14    BOT      65         910    -73.6327   \n",
       "2020-10-06 13:18:30   SIRI    200    SLD    5.66        1132     130.202   \n",
       "2020-10-06 13:18:47   SIRI   4307    SLD    5.65     24334.6      2742.3   \n",
       "2020-10-06 13:19:22    DHR    100    SLD  218.55       21855        OPEN   \n",
       "2020-10-06 13:19:22    DHR    100    SLD  218.55       21855        OPEN   \n",
       "2020-10-06 13:19:22    DHR     19    SLD  218.55     4152.45        OPEN   \n",
       "2020-10-06 13:20:23    PSA     10    BOT  230.34      2303.4    -165.389   \n",
       "2020-10-06 13:21:18   ISRG      5    BOT  709.15     3545.75     42.6668   \n",
       "\n",
       "                    commission  \n",
       "time                            \n",
       "2020-10-06 13:11:45   0.670257  \n",
       "2020-10-06 13:11:45   0.670257  \n",
       "2020-10-06 13:11:45   0.033513  \n",
       "2020-10-06 13:11:53   0.331257  \n",
       "2020-10-06 13:12:00   0.301257  \n",
       "2020-10-06 13:12:06   0.340257  \n",
       "2020-10-06 13:12:13   0.463334  \n",
       "2020-10-06 13:12:13   0.463334  \n",
       "2020-10-06 13:12:15   0.359729  \n",
       "2020-10-06 13:12:15   0.226629  \n",
       "2020-10-06 13:12:16    1.34051  \n",
       "2020-10-06 13:12:16    2.01077  \n",
       "2020-10-06 13:12:16    1.34051  \n",
       "2020-10-06 13:12:16   0.020108  \n",
       "2020-10-06 13:12:19   0.490729  \n",
       "2020-10-06 13:12:19   0.353325  \n",
       "2020-10-06 13:12:25     0.8272  \n",
       "2020-10-06 13:12:28   0.463334  \n",
       "2020-10-06 13:12:41   0.335057  \n",
       "2020-10-06 13:12:50   0.004634  \n",
       "2020-10-06 13:13:02   0.441742  \n",
       "2020-10-06 13:13:08   0.310357  \n",
       "2020-10-06 13:13:13   0.356179  \n",
       "2020-10-06 13:13:18   0.211755  \n",
       "2020-10-06 13:13:31   0.358943  \n",
       "2020-10-06 13:13:39   0.357675  \n",
       "2020-10-06 13:13:50   0.323257  \n",
       "2020-10-06 13:14:01   0.433676  \n",
       "2020-10-06 13:14:01   0.320257  \n",
       "2020-10-06 13:14:01    1.34051  \n",
       "...                        ...  \n",
       "2020-10-06 13:14:31   0.544219  \n",
       "2020-10-06 13:14:34    0.35868  \n",
       "2020-10-06 13:14:39    1.45607  \n",
       "2020-10-06 13:14:39    6.53777  \n",
       "2020-10-06 13:14:39   0.728037  \n",
       "2020-10-06 13:14:43   0.994389  \n",
       "2020-10-06 13:14:43    1.44293  \n",
       "2020-10-06 13:14:43   0.172836  \n",
       "2020-10-06 13:15:12   0.160257  \n",
       "2020-10-06 13:15:14   0.160257  \n",
       "2020-10-06 13:15:14    0.10577  \n",
       "2020-10-06 13:15:29   0.266657  \n",
       "2020-10-06 13:15:30   0.373272  \n",
       "2020-10-06 13:15:48   0.314257  \n",
       "2020-10-06 13:16:01   0.525471  \n",
       "2020-10-06 13:16:11    1.36823  \n",
       "2020-10-06 13:16:12   0.266257  \n",
       "2020-10-06 13:16:30   0.670257  \n",
       "2020-10-06 13:16:30   0.640257  \n",
       "2020-10-06 13:16:48   0.250257  \n",
       "2020-10-06 13:17:11   0.102605  \n",
       "2020-10-06 13:17:47   0.469332  \n",
       "2020-10-06 13:18:29   0.336257  \n",
       "2020-10-06 13:18:30   0.469332  \n",
       "2020-10-06 13:18:47    28.6262  \n",
       "2020-10-06 13:19:22   0.745153  \n",
       "2020-10-06 13:19:22   0.745153  \n",
       "2020-10-06 13:19:22   0.141579  \n",
       "2020-10-06 13:20:23   0.025026  \n",
       "2020-10-06 13:21:18   0.340757  \n",
       "\n",
       "[69 rows x 7 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "com"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "execution_date = com.index[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Report for 2020-10-06:\n",
      " Market Value: 460891.62 $\n",
      " Total Commission: 69.68 $\n",
      " Total Realized PNL: 2459.23 $\n"
     ]
    }
   ],
   "source": [
    "RealizedPNL = np.round(pd.to_numeric(com.loc[slice(execution_date)]['RealizedPNL'], errors='coerce').sum(),2)\n",
    "#Total_Realized_Return = np.round((RealizedPNL/net_liq)*100,2)\n",
    "print ('Report for {}:'.format(execution_date.date()))\n",
    "print (' Market Value: {} $'.format(np.round(com.loc[slice(execution_date)]['marketValue'].sum(),2)))\n",
    "print (' Total Commission: {} $'.format(np.round(com.loc[slice(execution_date)]['commission'].sum(),2)))\n",
    "print (' Total Realized PNL: {} $'.format(RealizedPNL))  \n",
    "#print (' Total Realized Return: {} %'.format(Total_Realized_Return))  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "creating report file...\n",
      "creating report file...\n",
      "creating report file...\n",
      "creating report file...\n",
      "creating report file...\n",
      "creating report file...\n",
      "creating report file...\n",
      "creating report file...\n",
      "creating report file...\n",
      "creating report file...\n",
      "creating report file...\n",
      "creating report file...\n",
      "creating report file...\n",
      "report file exist...\n",
      "creating report file...\n",
      "creating report file...\n",
      "creating report file...\n"
     ]
    }
   ],
   "source": [
    "rootdir = 'data'\n",
    "if account_number == availabe_accounts.values[0][0]:\n",
    "    for subdir, dirs, files in os.walk(rootdir):\n",
    "        for item in files:\n",
    "\n",
    "            if item.endswith('.csv') and item.split('_')[0] == 'commission' and item.split('_')[1] == 'report.csv':\n",
    "                \n",
    "                print ('report file exist...')\n",
    "                p = os.path.join('data/', item)\n",
    "                report = pd.read_csv(p, index_col= 'date')\n",
    "                report.loc[execution_date.date(),'market value'] = np.round(com.loc[slice(execution_date)]['marketValue'].sum(),2)\n",
    "                report.loc[execution_date.date(),'total commission'] = np.round(com.loc[slice(execution_date)]['commission'].sum(),2)\n",
    "                report.loc[execution_date.date(),'total realized pnl'] = RealizedPNL\n",
    "\n",
    "            else:\n",
    "\n",
    "                print ('creating report file...')\n",
    "                report = pd.DataFrame(columns = ['market value','total commission','total realized pnl'], \n",
    "                              index = [execution_date.date()])\n",
    "                report.index.name = 'date'\n",
    "                report.loc[:,'market value'] = np.round(com.loc[slice(execution_date)]['marketValue'].sum(),2)\n",
    "                report.loc[:,'total commission'] = np.round(com.loc[slice(execution_date)]['commission'].sum(),2)\n",
    "                report.loc[:,'total realized pnl'] = RealizedPNL\n",
    "    report.to_csv('data/commission_report.csv')\n",
    "    com_rep = pd.read_csv('data/commission_report.csv', index_col= 'date')\n",
    "    \n",
    "elif account_number == availabe_accounts.values[1][0]:\n",
    "    for subdir, dirs, files in os.walk(rootdir):\n",
    "        for item in files:\n",
    "            if item.endswith('.csv') and item.split('_')[0] == 'commission' and item.split('_')[1] == 'reportSA.csv' :\n",
    "                print ('report file exist...')\n",
    "                p = os.path.join('data/', item)\n",
    "                report = pd.read_csv(p, index_col= 'date')\n",
    "                report.loc[execution_date.date(),'market value'] = np.round(com.loc[slice(execution_date)]['marketValue'].sum(),2)\n",
    "                report.loc[execution_date.date(),'total commission'] = np.round(com.loc[slice(execution_date)]['commission'].sum(),2)\n",
    "                report.loc[execution_date.date(),'total realized pnl'] = RealizedPNL\n",
    "\n",
    "            else:\n",
    "                print ('creating report file...')\n",
    "                report = pd.DataFrame(columns = ['market value','total commission','total realized pnl'], \n",
    "                                      index = [execution_date.date()])\n",
    "                report.index.name = 'date'\n",
    "                report.loc[:,'market value'] = np.round(com.loc[slice(execution_date)]['marketValue'].sum(),2)\n",
    "                report.loc[:,'total commission'] = np.round(com.loc[slice(execution_date)]['commission'].sum(),2)\n",
    "                report.loc[:,'total realized pnl'] = RealizedPNL\n",
    "                \n",
    "    report.to_csv('data/commission_reportSA.csv')\n",
    "    com_rep = pd.read_csv('data/commission_reportSA.csv', index_col = 'date')\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>market value</th>\n",
       "      <th>total commission</th>\n",
       "      <th>total realized pnl</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-10-06</th>\n",
       "      <td>460891.62</td>\n",
       "      <td>69.68</td>\n",
       "      <td>2459.23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            market value  total commission  total realized pnl\n",
       "date                                                          \n",
       "2020-10-06     460891.62             69.68             2459.23"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "com_rep "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>market value</th>\n",
       "      <th>total commission</th>\n",
       "      <th>total realized pnl</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-10-06</th>\n",
       "      <td>460891.62</td>\n",
       "      <td>69.68</td>\n",
       "      <td>2459.23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            market value total commission total realized pnl\n",
       "date                                                        \n",
       "2020-10-06     460891.62            69.68            2459.23"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "next_rebalance_date = execution_date.date() + datetime.timedelta(days = 14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The next rebalance date for DU1440139 is set to: 2020-10-20\n"
     ]
    }
   ],
   "source": [
    "print ('The next rebalance date for {} is set to: {}'.format(account_number,next_rebalance_date))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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