52 Week Break Out Trendfollowing Notebook for Public Use.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot\n",
    "from pylab import mpl, plt\n",
    "import time\n",
    "\n",
    "from IPython.display import set_matplotlib_formats\n",
    "set_matplotlib_formats('png', 'pdf')\n",
    "\n",
    "pd.set_option('display.max_columns',110)\n",
    "pd.set_option('display.max_rows',1000)\n",
    "mpl.rcParams['font.family'] = 'serif'\n",
    "\n",
    "#import all of the equity price data from csv from Sharadar or you can access your own price data\n",
    "equity_prices = pd.read_csv('Equity Prices')\n",
    "#get ticker meta data\n",
    "tickers_df = pd.read_csv('Equity Tickers', low_memory=False)    \n",
    "\n",
    "#filter out companies not based in USA\n",
    "tickers_df1 = tickers_df[tickers_df['location'].notnull()]\n",
    "tickers_df1 = tickers_df1[tickers_df1['location'].str.contains(\"U.S.\")]\n",
    "\n",
    "#select needed columns to filter out sector\n",
    "tickers_df1 = tickers_df1[['ticker','sector','name','industry','scalemarketcap']]\n",
    "\n",
    "#create set and list of all tickers\n",
    "myset_ticker = set(tickers_df1.ticker)\n",
    "list_tickers = list(myset_ticker)\n",
    "\n",
    "#if you want to sort out certain market cap size for liquidity\n",
    "sector_stocks = tickers_df1[(tickers_df1['scalemarketcap'] == '3 - Small') | \\\n",
    "                (tickers_df1['scalemarketcap'] == '4 - Medium') | \\\n",
    "                (tickers_df1['scalemarketcap'] == '5 - Large') | \\\n",
    "                (tickers_df1['scalemarketcap'] == '6 - Mega')]\n",
    "\n",
    "#put tickers to list from sector specified\n",
    "sector_tickers = sector_stocks['ticker'].tolist()\n",
    "len(sector_tickers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>ticker</th>\n",
       "      <th>AACE</th>\n",
       "      <th>AAII</th>\n",
       "      <th>ABCD</th>\n",
       "      <th>ABCW</th>\n",
       "      <th>ABTX</th>\n",
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       "      <th>ACME</th>\n",
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       "      <th>AEA</th>\n",
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       "      <th>AES</th>\n",
       "      <th>AFS.A</th>\n",
       "      <th>AGCCQ</th>\n",
       "      <th>AGIXQ</th>\n",
       "      <th>AHH</th>\n",
       "      <th>AIPC</th>\n",
       "      <th>ALAB</th>\n",
       "      <th>ALDW</th>\n",
       "      <th>ALGO</th>\n",
       "      <th>ALNT</th>\n",
       "      <th>AME</th>\n",
       "      <th>AMIS</th>\n",
       "      <th>AMMB</th>\n",
       "      <th>AMN1</th>\n",
       "      <th>AMRN1</th>\n",
       "      <th>ANCR</th>\n",
       "      <th>AOS</th>\n",
       "      <th>APEX1</th>\n",
       "      <th>APOG</th>\n",
       "      <th>APRE</th>\n",
       "      <th>APWR1</th>\n",
       "      <th>ARAY</th>\n",
       "      <th>ARCL</th>\n",
       "      <th>ARDT</th>\n",
       "      <th>ART1</th>\n",
       "      <th>ARXT</th>\n",
       "      <th>AS</th>\n",
       "      <th>AST</th>\n",
       "      <th>ASTX1</th>\n",
       "      <th>ATAC1</th>\n",
       "      <th>ATKR</th>\n",
       "      <th>ATRN</th>\n",
       "      <th>AVDO</th>\n",
       "      <th>AWK</th>\n",
       "      <th>BCOR</th>\n",
       "      <th>BCRX</th>\n",
       "      <th>BDT1</th>\n",
       "      <th>BEV</th>\n",
       "      <th>BHLB</th>\n",
       "      <th>BKR1</th>\n",
       "      <th>BKUNQ</th>\n",
       "      <th>BMC</th>\n",
       "      <th>BMRN</th>\n",
       "      <th>BNE</th>\n",
       "      <th>...</th>\n",
       "      <th>TSY</th>\n",
       "      <th>TUMI</th>\n",
       "      <th>TWTR</th>\n",
       "      <th>TXM</th>\n",
       "      <th>TYL</th>\n",
       "      <th>TZOO</th>\n",
       "      <th>UAL</th>\n",
       "      <th>UBH</th>\n",
       "      <th>UBID</th>\n",
       "      <th>UEIC</th>\n",
       "      <th>ULUR</th>\n",
       "      <th>UNP</th>\n",
       "      <th>UPUP</th>\n",
       "      <th>URX</th>\n",
       "      <th>USSPQ</th>\n",
       "      <th>USW</th>\n",
       "      <th>UTCI</th>\n",
       "      <th>VAS</th>\n",
       "      <th>VC1</th>\n",
       "      <th>VCEL</th>\n",
       "      <th>VEC</th>\n",
       "      <th>VIAD</th>\n",
       "      <th>VL</th>\n",
       "      <th>VLNK</th>\n",
       "      <th>VNBCQ</th>\n",
       "      <th>VNRRQ</th>\n",
       "      <th>VNUS</th>\n",
       "      <th>VOCS</th>\n",
       "      <th>VRGE</th>\n",
       "      <th>VRSO</th>\n",
       "      <th>VRTU</th>\n",
       "      <th>VYSI</th>\n",
       "      <th>W</th>\n",
       "      <th>WAMUQ</th>\n",
       "      <th>WCG1</th>\n",
       "      <th>WFC</th>\n",
       "      <th>WINK</th>\n",
       "      <th>WINMQ</th>\n",
       "      <th>WJCO</th>\n",
       "      <th>WLBA</th>\n",
       "      <th>WLFC</th>\n",
       "      <th>WLK</th>\n",
       "      <th>WLSC</th>\n",
       "      <th>WM</th>\n",
       "      <th>WOMN1</th>\n",
       "      <th>WORK1</th>\n",
       "      <th>WPZ</th>\n",
       "      <th>WSBF</th>\n",
       "      <th>XBIT</th>\n",
       "      <th>XMCM</th>\n",
       "      <th>XOMA</th>\n",
       "      <th>XOMD</th>\n",
       "      <th>XRAY</th>\n",
       "      <th>XRX</th>\n",
       "      <th>ZTS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>1997-12-31</th>\n",
       "      <td>11.375</td>\n",
       "      <td>11.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.049</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.250</td>\n",
       "      <td>9.250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.75</td>\n",
       "      <td>23.315</td>\n",
       "      <td>35.594</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.000</td>\n",
       "      <td>26.375</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>31.375</td>\n",
       "      <td>4.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>151.250</td>\n",
       "      <td>30.374</td>\n",
       "      <td>28.000</td>\n",
       "      <td>4.313</td>\n",
       "      <td>4.694</td>\n",
       "      <td>14.750</td>\n",
       "      <td>11.88</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.000</td>\n",
       "      <td>24.375</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.938</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.250</td>\n",
       "      <td>18.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>541.176</td>\n",
       "      <td>13.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.000</td>\n",
       "      <td>18.250</td>\n",
       "      <td>13.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.750</td>\n",
       "      <td>15.375</td>\n",
       "      <td>32.813</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.338</td>\n",
       "      <td>...</td>\n",
       "      <td>23.938</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.938</td>\n",
       "      <td>5.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.423</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.658</td>\n",
       "      <td>12.833</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45.125</td>\n",
       "      <td>3.156</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>700.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.875</td>\n",
       "      <td>2.214</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.750</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.361</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.375</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39.21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1668.9</td>\n",
       "      <td>16.000</td>\n",
       "      <td>10.167</td>\n",
       "      <td>147.76</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998-01-02</th>\n",
       "      <td>11.250</td>\n",
       "      <td>11.500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.174</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.375</td>\n",
       "      <td>9.375</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.00</td>\n",
       "      <td>22.655</td>\n",
       "      <td>35.313</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.938</td>\n",
       "      <td>26.500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29.00</td>\n",
       "      <td>30.750</td>\n",
       "      <td>3.917</td>\n",
       "      <td>0.0</td>\n",
       "      <td>147.500</td>\n",
       "      <td>29.924</td>\n",
       "      <td>27.125</td>\n",
       "      <td>5.313</td>\n",
       "      <td>4.764</td>\n",
       "      <td>14.521</td>\n",
       "      <td>11.88</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.875</td>\n",
       "      <td>23.750</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.500</td>\n",
       "      <td>18.625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>487.059</td>\n",
       "      <td>13.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.125</td>\n",
       "      <td>18.500</td>\n",
       "      <td>13.063</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.000</td>\n",
       "      <td>15.375</td>\n",
       "      <td>32.469</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.977</td>\n",
       "      <td>...</td>\n",
       "      <td>23.938</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.125</td>\n",
       "      <td>5.69</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.563</td>\n",
       "      <td>12.583</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.125</td>\n",
       "      <td>3.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>760.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.875</td>\n",
       "      <td>2.214</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.375</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.944</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.095</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.63</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.71</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1706.4</td>\n",
       "      <td>16.000</td>\n",
       "      <td>9.917</td>\n",
       "      <td>149.76</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998-01-05</th>\n",
       "      <td>11.375</td>\n",
       "      <td>11.375</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.296</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.563</td>\n",
       "      <td>9.563</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.06</td>\n",
       "      <td>23.000</td>\n",
       "      <td>35.594</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.125</td>\n",
       "      <td>26.250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.00</td>\n",
       "      <td>32.563</td>\n",
       "      <td>3.908</td>\n",
       "      <td>0.0</td>\n",
       "      <td>145.000</td>\n",
       "      <td>29.594</td>\n",
       "      <td>27.000</td>\n",
       "      <td>5.125</td>\n",
       "      <td>4.736</td>\n",
       "      <td>16.104</td>\n",
       "      <td>12.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.875</td>\n",
       "      <td>23.250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.500</td>\n",
       "      <td>21.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>487.059</td>\n",
       "      <td>13.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.125</td>\n",
       "      <td>18.313</td>\n",
       "      <td>13.625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.500</td>\n",
       "      <td>15.250</td>\n",
       "      <td>31.844</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.037</td>\n",
       "      <td>...</td>\n",
       "      <td>24.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.875</td>\n",
       "      <td>5.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.678</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.578</td>\n",
       "      <td>12.583</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45.375</td>\n",
       "      <td>3.094</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>780.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.875</td>\n",
       "      <td>2.214</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.750</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.778</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.38</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1762.5</td>\n",
       "      <td>15.333</td>\n",
       "      <td>9.543</td>\n",
       "      <td>151.88</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998-01-06</th>\n",
       "      <td>11.625</td>\n",
       "      <td>11.333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.148</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.500</td>\n",
       "      <td>9.845</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.88</td>\n",
       "      <td>22.875</td>\n",
       "      <td>35.344</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.063</td>\n",
       "      <td>26.875</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.75</td>\n",
       "      <td>31.750</td>\n",
       "      <td>4.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>136.875</td>\n",
       "      <td>29.203</td>\n",
       "      <td>27.125</td>\n",
       "      <td>5.750</td>\n",
       "      <td>4.716</td>\n",
       "      <td>16.583</td>\n",
       "      <td>12.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.688</td>\n",
       "      <td>23.188</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.813</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.750</td>\n",
       "      <td>20.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>493.824</td>\n",
       "      <td>12.750</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.625</td>\n",
       "      <td>18.438</td>\n",
       "      <td>13.375</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.375</td>\n",
       "      <td>15.125</td>\n",
       "      <td>31.938</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.766</td>\n",
       "      <td>...</td>\n",
       "      <td>23.875</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.000</td>\n",
       "      <td>5.62</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.318</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.938</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.422</td>\n",
       "      <td>12.167</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45.563</td>\n",
       "      <td>3.063</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>790.08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.875</td>\n",
       "      <td>2.214</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29.375</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.972</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.720</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>37.750</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.63</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.78</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1762.5</td>\n",
       "      <td>15.333</td>\n",
       "      <td>9.710</td>\n",
       "      <td>150.62</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998-01-07</th>\n",
       "      <td>10.875</td>\n",
       "      <td>11.417</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.148</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.500</td>\n",
       "      <td>9.500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.00</td>\n",
       "      <td>23.125</td>\n",
       "      <td>35.750</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.875</td>\n",
       "      <td>26.875</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.25</td>\n",
       "      <td>29.750</td>\n",
       "      <td>3.889</td>\n",
       "      <td>0.0</td>\n",
       "      <td>131.250</td>\n",
       "      <td>28.693</td>\n",
       "      <td>27.063</td>\n",
       "      <td>5.625</td>\n",
       "      <td>4.680</td>\n",
       "      <td>16.333</td>\n",
       "      <td>12.03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.875</td>\n",
       "      <td>22.313</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.750</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.125</td>\n",
       "      <td>19.500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>493.824</td>\n",
       "      <td>11.938</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.438</td>\n",
       "      <td>18.563</td>\n",
       "      <td>13.250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.188</td>\n",
       "      <td>14.750</td>\n",
       "      <td>30.656</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.555</td>\n",
       "      <td>...</td>\n",
       "      <td>24.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.063</td>\n",
       "      <td>5.62</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.338</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.065</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.845</td>\n",
       "      <td>12.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.438</td>\n",
       "      <td>3.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>820.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.906</td>\n",
       "      <td>2.699</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.222</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.405</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>37.563</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.53</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1687.5</td>\n",
       "      <td>15.833</td>\n",
       "      <td>9.543</td>\n",
       "      <td>145.38</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 486 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "ticker        AACE    AAII  ABCD  ABCW  ABTX   ACET  ACME   ACVC   ADSK  AEA  \\\n",
       "date                                                                           \n",
       "1997-12-31  11.375  11.000   0.0   0.0   0.0  4.049   0.0  6.250  9.250  0.0   \n",
       "1998-01-02  11.250  11.500   0.0   0.0   0.0  4.174   0.0  6.375  9.375  0.0   \n",
       "1998-01-05  11.375  11.375   0.0   0.0   0.0  4.296   0.0  6.563  9.563  0.0   \n",
       "1998-01-06  11.625  11.333   0.0   0.0   0.0  4.148   0.0  6.500  9.845  0.0   \n",
       "1998-01-07  10.875  11.417   0.0   0.0   0.0  4.148   0.0  6.500  9.500  0.0   \n",
       "\n",
       "ticker        AEC     AES   AFS.A  AGCCQ  AGIXQ  AHH    AIPC    ALAB  ALDW  \\\n",
       "date                                                                         \n",
       "1997-12-31  23.75  23.315  35.594    0.0    0.0  0.0  25.000  26.375   0.0   \n",
       "1998-01-02  24.00  22.655  35.313    0.0    0.0  0.0  24.938  26.500   0.0   \n",
       "1998-01-05  24.06  23.000  35.594    0.0    0.0  0.0  25.125  26.250   0.0   \n",
       "1998-01-06  23.88  22.875  35.344    0.0    0.0  0.0  25.063  26.875   0.0   \n",
       "1998-01-07  24.00  23.125  35.750    0.0    0.0  0.0  24.875  26.875   0.0   \n",
       "\n",
       "ticker       ALGO    ALNT    AME  AMIS     AMMB    AMN1   AMRN1   ANCR    AOS  \\\n",
       "date                                                                            \n",
       "1997-12-31  30.00  31.375  4.000   0.0  151.250  30.374  28.000  4.313  4.694   \n",
       "1998-01-02  29.00  30.750  3.917   0.0  147.500  29.924  27.125  5.313  4.764   \n",
       "1998-01-05  28.00  32.563  3.908   0.0  145.000  29.594  27.000  5.125  4.736   \n",
       "1998-01-06  28.75  31.750  4.000   0.0  136.875  29.203  27.125  5.750  4.716   \n",
       "1998-01-07  28.25  29.750  3.889   0.0  131.250  28.693  27.063  5.625  4.680   \n",
       "\n",
       "ticker       APEX1   APOG  APRE  APWR1  ARAY  ARCL   ARDT    ART1  ARXT  \\\n",
       "date                                                                      \n",
       "1997-12-31  14.750  11.88   0.0    0.0   0.0   0.0  8.000  24.375   0.0   \n",
       "1998-01-02  14.521  11.88   0.0    0.0   0.0   0.0  7.875  23.750   0.0   \n",
       "1998-01-05  16.104  12.00   0.0    0.0   0.0   0.0  7.875  23.250   0.0   \n",
       "1998-01-06  16.583  12.00   0.0    0.0   0.0   0.0  7.688  23.188   0.0   \n",
       "1998-01-07  16.333  12.03   0.0    0.0   0.0   0.0  7.875  22.313   0.0   \n",
       "\n",
       "ticker         AS  AST   ASTX1   ATAC1  ATKR     ATRN    AVDO  AWK  BCOR  \\\n",
       "date                                                                       \n",
       "1997-12-31  4.938  0.0  11.250  18.125   0.0  541.176  13.125  0.0   0.0   \n",
       "1998-01-02  5.000  0.0  11.500  18.625   0.0  487.059  13.000  0.0   0.0   \n",
       "1998-01-05  5.000  0.0  10.500  21.000   0.0  487.059  13.000  0.0   0.0   \n",
       "1998-01-06  4.813  0.0  10.750  20.000   0.0  493.824  12.750  0.0   0.0   \n",
       "1998-01-07  4.750  0.0  11.125  19.500   0.0  493.824  11.938  0.0   0.0   \n",
       "\n",
       "ticker       BCRX    BDT1     BEV  BHLB    BKR1   BKUNQ     BMC  BMRN     BNE  \\\n",
       "date                                                                            \n",
       "1997-12-31  7.000  18.250  13.000   0.0   9.750  15.375  32.813   0.0  19.338   \n",
       "1998-01-02  7.125  18.500  13.063   0.0  10.000  15.375  32.469   0.0  18.977   \n",
       "1998-01-05  7.125  18.313  13.625   0.0  10.500  15.250  31.844   0.0  19.037   \n",
       "1998-01-06  7.625  18.438  13.375   0.0  10.375  15.125  31.938   0.0  18.766   \n",
       "1998-01-07  8.438  18.563  13.250   0.0  10.188  14.750  30.656   0.0  18.555   \n",
       "\n",
       "ticker      ...     TSY  TUMI  TWTR     TXM   TYL  TZOO  UAL     UBH  UBID  \\\n",
       "date        ...                                                              \n",
       "1997-12-31  ...  23.938   0.0   0.0  13.938  5.50   0.0  0.0  17.423   0.0   \n",
       "1998-01-02  ...  23.938   0.0   0.0  14.125  5.69   0.0  0.0  17.593   0.0   \n",
       "1998-01-05  ...  24.000   0.0   0.0  14.875  5.50   0.0  0.0  17.678   0.0   \n",
       "1998-01-06  ...  23.875   0.0   0.0  15.000  5.62   0.0  0.0  16.318   0.0   \n",
       "1998-01-07  ...  24.125   0.0   0.0  15.063  5.62   0.0  0.0  17.338   0.0   \n",
       "\n",
       "ticker       UEIC  ULUR     UNP    UPUP  URX  USSPQ     USW   UTCI  VAS  VC1  \\\n",
       "date                                                                           \n",
       "1997-12-31  5.000   0.0  15.658  12.833  0.0    0.0  45.125  3.156  0.0  0.0   \n",
       "1998-01-02  5.000   0.0  15.563  12.583  0.0    0.0  46.125  3.125  0.0  0.0   \n",
       "1998-01-05  5.000   0.0  15.578  12.583  0.0    0.0  45.375  3.094  0.0  0.0   \n",
       "1998-01-06  4.938   0.0  15.422  12.167  0.0    0.0  45.563  3.063  0.0  0.0   \n",
       "1998-01-07  5.065   0.0  15.845  12.000  0.0    0.0  46.438  3.000  0.0  0.0   \n",
       "\n",
       "ticker        VCEL  VEC  VIAD   VL   VLNK  VNBCQ  VNRRQ  VNUS  VOCS  VRGE  \\\n",
       "date                                                                        \n",
       "1997-12-31  700.00  0.0   0.0  0.0  0.875  2.214    0.0   0.0   0.0   0.0   \n",
       "1998-01-02  760.00  0.0   0.0  0.0  0.875  2.214    0.0   0.0   0.0   0.0   \n",
       "1998-01-05  780.00  0.0   0.0  0.0  0.875  2.214    0.0   0.0   0.0   0.0   \n",
       "1998-01-06  790.08  0.0   0.0  0.0  0.875  2.214    0.0   0.0   0.0   0.0   \n",
       "1998-01-07  820.00  0.0   0.0  0.0  0.906  2.699    0.0   0.0   0.0   0.0   \n",
       "\n",
       "ticker        VRSO  VRTU  VYSI    W   WAMUQ  WCG1     WFC  WINK  WINMQ  \\\n",
       "date                                                                     \n",
       "1997-12-31  23.750   0.0   0.0  0.0  28.361   0.0  19.375   0.0    0.0   \n",
       "1998-01-02  24.375   0.0   0.0  0.0  28.944   0.0  19.095   0.0    0.0   \n",
       "1998-01-05  28.750   0.0   0.0  0.0  28.778   0.0  18.905   0.0    0.0   \n",
       "1998-01-06  29.375   0.0   0.0  0.0  27.972   0.0  18.720   0.0    0.0   \n",
       "1998-01-07  28.125   0.0   0.0  0.0  27.222   0.0  18.405   0.0    0.0   \n",
       "\n",
       "ticker        WJCO  WLBA   WLFC  WLK  WLSC     WM  WOMN1  WORK1  WPZ  WSBF  \\\n",
       "date                                                                         \n",
       "1997-12-31  39.000   0.0  17.50  0.0   0.0  39.21    0.0    0.0  0.0   0.0   \n",
       "1998-01-02  38.250   0.0  17.63  0.0   0.0  38.71    0.0    0.0  0.0   0.0   \n",
       "1998-01-05  38.000   0.0  17.38  0.0   0.0  38.34    0.0    0.0  0.0   0.0   \n",
       "1998-01-06  37.750   0.0  17.63  0.0   0.0  38.78    0.0    0.0  0.0   0.0   \n",
       "1998-01-07  37.563   0.0  18.25  0.0   0.0  38.53    0.0    0.0  0.0   0.0   \n",
       "\n",
       "ticker      XBIT  XMCM    XOMA    XOMD    XRAY     XRX  ZTS  \n",
       "date                                                         \n",
       "1997-12-31   0.0   0.0  1668.9  16.000  10.167  147.76  0.0  \n",
       "1998-01-02   0.0   0.0  1706.4  16.000   9.917  149.76  0.0  \n",
       "1998-01-05   0.0   0.0  1762.5  15.333   9.543  151.88  0.0  \n",
       "1998-01-06   0.0   0.0  1762.5  15.333   9.710  150.62  0.0  \n",
       "1998-01-07   0.0   0.0  1687.5  15.833   9.543  145.38  0.0  \n",
       "\n",
       "[5 rows x 486 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Random_Stocks = np.random.choice(sector_tickers, size = 500, replace = False)\n",
    "\n",
    "#sort out Sector Prices\n",
    "Sector_stock_prices = equity_prices.loc  \\\n",
    "    [equity_prices['ticker'].isin(Random_Stocks)]\n",
    "\n",
    "Sector_stock_prices.head()\n",
    "\n",
    "#filter the price date by the list of tickers\n",
    "#Sector_stock_prices = Sector_stock_prices.loc[Sector_stock_prices['ticker'].isin(Sector_stocks_cheapest_tickers)]\n",
    "  \n",
    "#get date, ticker, and close(adjusted) columns\n",
    "Sector_stock_prices_1 = Sector_stock_prices.iloc[:,[0,1,5]]\n",
    "\n",
    "Sector_stock_prices_2 = Sector_stock_prices_1.pivot(index='date', columns='ticker', values='close')\n",
    "Sector_stock_prices_3 = Sector_stock_prices_2.fillna(0)\n",
    "\n",
    "Sector_stock_prices_3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "%config InlineBackend.figure_format = 'retina'\n",
    "plt.rcParams['figure.figsize'] = [6, 5] #set size of graph in inches\n",
    "plt.style.use('seaborn-poster')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5558, 486)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Sector_stock_prices_3.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Backtest a strategy (simple trend following)\n",
    "1. Buy when at 52 week high\n",
    "5. Sell on 52 week low\n",
    "'''\n",
    "\n",
    "##############Using One Symbol#############################\n",
    "\n",
    "symbol = 'AEA'\n",
    "\n",
    "data = pd.DataFrame(Sector_stock_prices_3[symbol])\n",
    "data.dropna(inplace = True)\n",
    "data['Returns'] = data[symbol].pct_change()\n",
    "data.dropna(inplace = True)\n",
    "\n",
    "\n",
    "data['52 week high'] = data[symbol].rolling(252).max()\n",
    "data['52 week low'] = data[symbol].rolling(252).min()\n",
    "\n",
    "data.dropna(inplace = True)\n",
    "\n",
    "data['Signal'] = ''\n",
    "data.iloc[0,4] = 'Flat'\n",
    "\n",
    "for i in range(1, len(data)):\n",
    "    data.iloc[i, 4] = np.where(data.iloc[i,0] > data.iloc[i-1,2], 'Long',\\\n",
    "             np.where(data.iloc[i,0] < data.iloc[i-1,3], 'Sell', \\\n",
    "             np.where(data.iloc[i-1,4] == 'Long', 'Long','Flat')))\n",
    "\n",
    "data['Position'] = np.where(data['Signal'] == 'Long',1,0)\n",
    "data['Strategy'] = data['Position'].shift(1) * data['Returns']\n",
    "data.dropna(inplace = True)\n",
    "D = len(data)\n",
    "perf = data[['Returns', 'Strategy']].add(1).prod() ** (252 / D) - 1 \n",
    "\n",
    "#1. Compute the buy and hold returns\n",
    "print(\"Buy and hold returns annualized \" + str(round(perf[0], 4)))\n",
    "\n",
    "#2. Compute the strategy returns and compare it with the buy and hold returns\n",
    "print(\"strategy returns annualized \" + str(round(perf[1], 4)) + \\\n",
    "      \" resulting in outperformance of \" + str(round(perf[1]-perf[0], 4)))\n",
    "\n",
    "#3. Plot buy and hold returns and strategy returns in a single chart\n",
    "portfolio_index = (1 + data[['Strategy','Returns']]).cumprod()\n",
    "portfolio_index.plot()\n",
    "\n",
    "#4. Compute the Sharpe ratio\n",
    "std = data[['Returns', 'Strategy']].std() * 252 ** 0.5\n",
    "Sharpe = perf/std\n",
    "print(\"The Strategy Sharpe Ratio is \" + str(round(Sharpe[1], 4)))\n",
    "print(\"The Buy and Hold Sharpe Ratio is \" + str(round(Sharpe[0], 4)))\n",
    "\n",
    "#5. Compute and plot the drawdown of the strategy\n",
    "def Max_Drawdown_Chart(x):\n",
    "    # We are going to use a trailing 252 trading day window\n",
    "    Roll_Max = x.expanding().max()\n",
    "    Daily_Drawdown = x/Roll_Max - 1.0\n",
    "    # Next we calculate the minimum (negative) daily drawdown in that window.\n",
    "    # Again, use min_periods=1 if you want to allow the expanding window\n",
    "    Max_Daily_Drawdown = Daily_Drawdown.expanding().min()\n",
    "    # Plot the results\n",
    "    Daily_Drawdown.plot()\n",
    "    Max_Daily_Drawdown.plot()\n",
    "    \n",
    "def Max_Drawdown(x):\n",
    "    Roll_Max = x.expanding().max()\n",
    "    Daily_Drawdown = x/Roll_Max - 1.0\n",
    "    return Daily_Drawdown.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max Drawdown is -0.3322148736275289\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 921.6x633.6 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 540,
       "width": 788
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Max_Drawdown_Chart(portfolio_index['Strategy'])\n",
    "print(\"Max Drawdown is \" + str(Max_Drawdown(portfolio_index['Strategy'])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "It took 17.01 minutes to run the code\n"
     ]
    }
   ],
   "source": [
    "##############Run Through Different Stocks#################################\n",
    "t0 = time.time()\n",
    "\n",
    "tickers_index = Sector_stock_prices_3.columns\n",
    "ticker_list = tickers_index.tolist()\n",
    "number_stocks = Sector_stock_prices_3.shape[1]\n",
    "dayhigh = 252\n",
    "\n",
    "\n",
    "results = pd.DataFrame()\n",
    "for symbol in ticker_list:\n",
    "   data = pd.DataFrame(Sector_stock_prices_3[symbol])\n",
    "   data.dropna(inplace = True)\n",
    "   data['Returns'] = data.pct_change()\n",
    "   data.dropna(inplace = True)\n",
    "   data['52 week high'] = data[symbol].rolling(dayhigh).max()\n",
    "   data['52 week low'] = data[symbol].rolling(dayhigh).min()\n",
    "   data.dropna(inplace = True)\n",
    "   data['Signal'] = ''\n",
    "   if data.empty == True: #some stocks don't have 252 days of data and can be dropped\n",
    "       pass\n",
    "   else:\n",
    "       data.iloc[0,4] = 'Flat'\n",
    "       for i in range(1, len(data)):\n",
    "           data.iloc[i, 4] = np.where(data.iloc[i,0] > data.iloc[i-1,2], 'Long',\\\n",
    "             np.where(data.iloc[i,0] < data.iloc[i-1,3], 'Sell', \\\n",
    "             np.where(data.iloc[i-1,4] == 'Long', 'Long','Flat')))\n",
    "       data['Position'] = np.where(data['Signal'] == 'Long',1,0)\n",
    "       data['Strategy'] = data['Position'].shift(1) * data['Returns']\n",
    "       data.dropna(inplace = True)\n",
    "       Days = len(data)\n",
    "       perf = data[['Returns', 'Strategy']].add(1).prod() ** (252 / Days) - 1\n",
    "       portfolio_index = (1 + data[['Returns','Strategy']]).cumprod()\n",
    "       Max_DD = Max_Drawdown(portfolio_index)\n",
    "       std = data[['Returns', 'Strategy']].std() * 252 ** 0.5\n",
    "       Sharpe = perf/std\n",
    "       results = results.append(pd.DataFrame(\n",
    "                {'Symbol': symbol,\n",
    "                 'MARKET Returns': perf['Returns'],\n",
    "                 'STRATEGY Returns': perf['Strategy'],\n",
    "                 'Market Sharpe': Sharpe[0],\n",
    "                 'Strategy Sharpe': Sharpe[1],\n",
    "                 'Market Max DD': Max_DD[0],\n",
    "                 'Strategy Max DD': Max_DD[1],\n",
    "                 'Sharpe OUT': Sharpe['Strategy'] - Sharpe['Returns'],\n",
    "                 'Strategy Alpha': perf['Strategy'] - perf['Returns']},\n",
    "                 index = [0]), ignore_index = True)\n",
    "\n",
    "t1 = time.time()\n",
    "\n",
    "total = t1-t0\n",
    "print('It took ' + str(np.round(total/60,2)) + ' minutes to run the code')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>Symbol</th>\n",
       "      <th>MARKET Returns</th>\n",
       "      <th>STRATEGY Returns</th>\n",
       "      <th>Market Sharpe</th>\n",
       "      <th>Strategy Sharpe</th>\n",
       "      <th>Market Max DD</th>\n",
       "      <th>Strategy Max DD</th>\n",
       "      <th>Sharpe OUT</th>\n",
       "      <th>Strategy Alpha</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AACE</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.841229</td>\n",
       "      <td>-2.223837</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.382608</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AAII</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.223149</td>\n",
       "      <td>-0.747362</td>\n",
       "      <td>-0.426274</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.876610</td>\n",
       "      <td>0.321088</td>\n",
       "      <td>0.776851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ABCD</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.470167</td>\n",
       "      <td>-1.846307</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.376140</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ABCW</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.714041</td>\n",
       "      <td>-0.717071</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.003030</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ABTX</td>\n",
       "      <td>0.105020</td>\n",
       "      <td>0.043618</td>\n",
       "      <td>0.423443</td>\n",
       "      <td>0.230944</td>\n",
       "      <td>-0.356579</td>\n",
       "      <td>-0.226974</td>\n",
       "      <td>-0.192500</td>\n",
       "      <td>-0.061401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ACET</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.035744</td>\n",
       "      <td>-1.551532</td>\n",
       "      <td>0.107261</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.714150</td>\n",
       "      <td>1.658794</td>\n",
       "      <td>1.035744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>ACME</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.772346</td>\n",
       "      <td>-1.493771</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.721425</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ACVC</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.852294</td>\n",
       "      <td>-0.889075</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.036781</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>ADSK</td>\n",
       "      <td>0.149169</td>\n",
       "      <td>0.067901</td>\n",
       "      <td>0.350604</td>\n",
       "      <td>0.215615</td>\n",
       "      <td>-0.769201</td>\n",
       "      <td>-0.636662</td>\n",
       "      <td>-0.134989</td>\n",
       "      <td>-0.081268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AEA</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.261436</td>\n",
       "      <td>-1.899980</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.638544</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Symbol  MARKET Returns  STRATEGY Returns  Market Sharpe  Strategy Sharpe  \\\n",
       "0   AACE       -1.000000         -1.000000      -1.841229        -2.223837   \n",
       "1   AAII       -1.000000         -0.223149      -0.747362        -0.426274   \n",
       "2   ABCD       -1.000000         -1.000000      -1.470167        -1.846307   \n",
       "3   ABCW       -1.000000         -1.000000      -0.714041        -0.717071   \n",
       "4   ABTX        0.105020          0.043618       0.423443         0.230944   \n",
       "5   ACET       -1.000000          0.035744      -1.551532         0.107261   \n",
       "6   ACME       -1.000000         -1.000000      -0.772346        -1.493771   \n",
       "7   ACVC       -1.000000         -1.000000      -0.852294        -0.889075   \n",
       "8   ADSK        0.149169          0.067901       0.350604         0.215615   \n",
       "9    AEA       -1.000000         -1.000000      -1.261436        -1.899980   \n",
       "\n",
       "   Market Max DD  Strategy Max DD  Sharpe OUT  Strategy Alpha  \n",
       "0      -1.000000        -1.000000   -0.382608        0.000000  \n",
       "1      -1.000000        -0.876610    0.321088        0.776851  \n",
       "2      -1.000000        -1.000000   -0.376140        0.000000  \n",
       "3      -1.000000        -1.000000   -0.003030        0.000000  \n",
       "4      -0.356579        -0.226974   -0.192500       -0.061401  \n",
       "5      -1.000000        -0.714150    1.658794        1.035744  \n",
       "6      -1.000000        -1.000000   -0.721425        0.000000  \n",
       "7      -1.000000        -1.000000   -0.036781        0.000000  \n",
       "8      -0.769201        -0.636662   -0.134989       -0.081268  \n",
       "9      -1.000000        -1.000000   -0.638544        0.000000  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results.sort_values('Sharpe OUT', ascending = False).head(20)\n",
    "results.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Strategy Relative Sharpe Random Stocks Trend Strategy')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 388,
       "width": 614
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[10,6])\n",
    "n, bins, patches = pyplot.hist(results['Sharpe OUT'], bins = 50, rwidth = 3)\n",
    "plt.title('Strategy Relative Sharpe Random Stocks Trend Strategy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Strategy Alpha Sharpe Random Stocks Trend Strategy')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 388,
       "width": 620
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[10,6])\n",
    "n, bins, patches = pyplot.hist(results['Strategy Alpha'], bins = 50, rwidth = 3)\n",
    "plt.title('Strategy Alpha Sharpe Random Stocks Trend Strategy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Max Drawdown of Random Stocks Trend Strategy')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 388,
       "width": 614
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[10,6])\n",
    "n, bins, patches = pyplot.hist(results['Strategy Max DD'], bins = 50, rwidth = 3)\n",
    "n, bins, patches = pyplot.hist(results['Market Max DD'], bins = 50, rwidth = 3)\n",
    "plt.title('Max Drawdown of Random Stocks Trend Strategy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0\n",
      "0.2799862702485402\n",
      "-1.0\n",
      "-0.06667085580841581\n",
      "-0.07130489322797695\n"
     ]
    }
   ],
   "source": [
    "print(results['Strategy Alpha'].median())\n",
    "print(results['Strategy Alpha'].mean())\n",
    "print(results['MARKET Returns'].median())\n",
    "print(results['STRATEGY Returns'].median())\n",
    "print(results['Sharpe OUT'].median())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t = 8.55101408627195\n",
      "p = 2.4901874405001317e-17\n",
      "The Strategy Alpha is significant at the 0.0 level.\n"
     ]
    }
   ],
   "source": [
    "from scipy import stats\n",
    "## Cross Checking with the internal scipy function\n",
    "t2, p2 = stats.ttest_ind(results['STRATEGY Returns'],results['MARKET Returns'])\n",
    "print(\"t = \" + str(t2))\n",
    "print(\"p = \" + str(p2/2)) #one sided t test\n",
    "\n",
    "print('The Strategy Alpha is significant at the ' + str(round(p2/2, 6)) + ' level.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t = 0.0046263701545186655\n",
      "p = 0.498154917301623\n",
      "The Strategy Sharpe is significant at the 0.498155 level.\n"
     ]
    }
   ],
   "source": [
    "sharpe_results = results[['Strategy Sharpe','Market Sharpe']].dropna()\n",
    "t3, p3 = stats.ttest_ind(sharpe_results['Strategy Sharpe'],sharpe_results['Market Sharpe'])\n",
    "print(\"t = \" + str(t3))\n",
    "print(\"p = \" + str(p3/2)) #one sided t test\n",
    "\n",
    "print('The Strategy Sharpe is significant at the ' + str(round(p3/2, 6)) + ' level.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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