backtesting-crypto-trading-strategies.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# Imports and settings\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [],
   "source": [
    "import cryptocompare as cryptos\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from itertools import product\n",
    "from scipy.stats import t\n",
    "import pickle\n",
    "import os\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "load_dotenv()\n",
    "result = cryptos.cryptocompare._set_api_key_parameter(os.getenv('API_KEY'))  # set your own API key in a .env file"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# Get data"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [],
   "source": [
    "symbol = 'BTC'  # set symbol here\n",
    "reload = False  # set to True for new API call, otherwise load saved data\n",
    "if reload:\n",
    "    raw = cryptos.get_historical_price_day(symbol, currency='EUR', limit=2000)\n",
    "    with open('raw', 'wb') as handle:\n",
    "        pickle.dump(raw, handle)\n",
    "else:\n",
    "    with open('raw', 'rb') as handle:\n",
    "        raw = pickle.load(handle)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "data": {
      "text/plain": "                 BTC\ntime                \n2022-11-11  16486.68\n2022-11-12  16262.21\n2022-11-13  15805.96\n2022-11-14  16085.94\n2022-11-15  16086.74",
      "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>BTC</th>\n    </tr>\n    <tr>\n      <th>time</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2022-11-11</th>\n      <td>16486.68</td>\n    </tr>\n    <tr>\n      <th>2022-11-12</th>\n      <td>16262.21</td>\n    </tr>\n    <tr>\n      <th>2022-11-13</th>\n      <td>15805.96</td>\n    </tr>\n    <tr>\n      <th>2022-11-14</th>\n      <td>16085.94</td>\n    </tr>\n    <tr>\n      <th>2022-11-15</th>\n      <td>16086.74</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.DataFrame(raw)\n",
    "data['time'] = pd.to_datetime(data['time'], unit='s')\n",
    "data.index = pd.DatetimeIndex(data['time'])\n",
    "data = data[['close']]\n",
    "data.columns = [symbol]\n",
    "data.tail()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# Simple moving average trading strategy"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "data": {
      "text/plain": "                 BTC  SMA_SHORT_TERM  SMA_LONG_TERM\ntime                                               \n2022-10-17  19865.60     19972.94600   22238.983813\n2022-10-18  19606.10     19980.47650   22189.332250\n2022-10-19  19587.23     19940.07750   22137.535313\n2022-10-20  19479.37     19888.56375   22083.527438\n2022-10-21  19441.38     19832.57075   22024.379812\n2022-10-22  19480.55     19766.83275   21958.014875\n2022-10-23  19838.43     19757.15675   21903.297937\n2022-10-24  19557.63     19739.40475   21845.224187\n2022-10-25  20156.82     19749.92225   21799.993125\n2022-10-26  20580.78     19769.87825   21749.626000\n2022-10-27  20359.34     19776.41350   21704.099250\n2022-10-28  20682.01     19808.88350   21659.289875\n2022-10-29  20880.89     19843.62750   21610.794750\n2022-10-30  20725.89     19888.34950   21570.146500\n2022-10-31  20733.15     19936.62075   21527.142563\n2022-11-01  20745.58     19962.31850   21484.139875\n2022-11-02  20536.06     19978.28750   21442.428188\n2022-11-03  20730.29     20008.65750   21405.471438\n2022-11-04  21252.78     20054.68450   21369.260375\n2022-11-05  21400.90     20089.92250   21331.429250\n2022-11-06  21087.79     20119.76700   21279.188187\n2022-11-07  20569.71     20134.17150   21222.695062\n2022-11-08  18454.65     20097.17400   21163.231125\n2022-11-09  15881.30     19998.67950   21085.452313\n2022-11-10  17272.75     19937.64225   21020.178875\n2022-11-11  16486.68     19863.28100   20949.048125\n2022-11-12  16262.21     19770.79625   20876.363188\n2022-11-13  15805.96     19656.47975   20791.817687\n2022-11-14  16085.94     19549.92900   20710.636000\n2022-11-15  16086.74     19442.44400   20635.065312",
      "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>BTC</th>\n      <th>SMA_SHORT_TERM</th>\n      <th>SMA_LONG_TERM</th>\n    </tr>\n    <tr>\n      <th>time</th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2022-10-17</th>\n      <td>19865.60</td>\n      <td>19972.94600</td>\n      <td>22238.983813</td>\n    </tr>\n    <tr>\n      <th>2022-10-18</th>\n      <td>19606.10</td>\n      <td>19980.47650</td>\n      <td>22189.332250</td>\n    </tr>\n    <tr>\n      <th>2022-10-19</th>\n      <td>19587.23</td>\n      <td>19940.07750</td>\n      <td>22137.535313</td>\n    </tr>\n    <tr>\n      <th>2022-10-20</th>\n      <td>19479.37</td>\n      <td>19888.56375</td>\n      <td>22083.527438</td>\n    </tr>\n    <tr>\n      <th>2022-10-21</th>\n      <td>19441.38</td>\n      <td>19832.57075</td>\n      <td>22024.379812</td>\n    </tr>\n    <tr>\n      <th>2022-10-22</th>\n      <td>19480.55</td>\n      <td>19766.83275</td>\n      <td>21958.014875</td>\n    </tr>\n    <tr>\n      <th>2022-10-23</th>\n      <td>19838.43</td>\n      <td>19757.15675</td>\n      <td>21903.297937</td>\n    </tr>\n    <tr>\n      <th>2022-10-24</th>\n      <td>19557.63</td>\n      <td>19739.40475</td>\n      <td>21845.224187</td>\n    </tr>\n    <tr>\n      <th>2022-10-25</th>\n      <td>20156.82</td>\n      <td>19749.92225</td>\n      <td>21799.993125</td>\n    </tr>\n    <tr>\n      <th>2022-10-26</th>\n      <td>20580.78</td>\n      <td>19769.87825</td>\n      <td>21749.626000</td>\n    </tr>\n    <tr>\n      <th>2022-10-27</th>\n      <td>20359.34</td>\n      <td>19776.41350</td>\n      <td>21704.099250</td>\n    </tr>\n    <tr>\n      <th>2022-10-28</th>\n      <td>20682.01</td>\n      <td>19808.88350</td>\n      <td>21659.289875</td>\n    </tr>\n    <tr>\n      <th>2022-10-29</th>\n      <td>20880.89</td>\n      <td>19843.62750</td>\n      <td>21610.794750</td>\n    </tr>\n    <tr>\n      <th>2022-10-30</th>\n      <td>20725.89</td>\n      <td>19888.34950</td>\n      <td>21570.146500</td>\n    </tr>\n    <tr>\n      <th>2022-10-31</th>\n      <td>20733.15</td>\n      <td>19936.62075</td>\n      <td>21527.142563</td>\n    </tr>\n    <tr>\n      <th>2022-11-01</th>\n      <td>20745.58</td>\n      <td>19962.31850</td>\n      <td>21484.139875</td>\n    </tr>\n    <tr>\n      <th>2022-11-02</th>\n      <td>20536.06</td>\n      <td>19978.28750</td>\n      <td>21442.428188</td>\n    </tr>\n    <tr>\n      <th>2022-11-03</th>\n      <td>20730.29</td>\n      <td>20008.65750</td>\n      <td>21405.471438</td>\n    </tr>\n    <tr>\n      <th>2022-11-04</th>\n      <td>21252.78</td>\n      <td>20054.68450</td>\n      <td>21369.260375</td>\n    </tr>\n    <tr>\n      <th>2022-11-05</th>\n      <td>21400.90</td>\n      <td>20089.92250</td>\n      <td>21331.429250</td>\n    </tr>\n    <tr>\n      <th>2022-11-06</th>\n      <td>21087.79</td>\n      <td>20119.76700</td>\n      <td>21279.188187</td>\n    </tr>\n    <tr>\n      <th>2022-11-07</th>\n      <td>20569.71</td>\n      <td>20134.17150</td>\n      <td>21222.695062</td>\n    </tr>\n    <tr>\n      <th>2022-11-08</th>\n      <td>18454.65</td>\n      <td>20097.17400</td>\n      <td>21163.231125</td>\n    </tr>\n    <tr>\n      <th>2022-11-09</th>\n      <td>15881.30</td>\n      <td>19998.67950</td>\n      <td>21085.452313</td>\n    </tr>\n    <tr>\n      <th>2022-11-10</th>\n      <td>17272.75</td>\n      <td>19937.64225</td>\n      <td>21020.178875</td>\n    </tr>\n    <tr>\n      <th>2022-11-11</th>\n      <td>16486.68</td>\n      <td>19863.28100</td>\n      <td>20949.048125</td>\n    </tr>\n    <tr>\n      <th>2022-11-12</th>\n      <td>16262.21</td>\n      <td>19770.79625</td>\n      <td>20876.363188</td>\n    </tr>\n    <tr>\n      <th>2022-11-13</th>\n      <td>15805.96</td>\n      <td>19656.47975</td>\n      <td>20791.817687</td>\n    </tr>\n    <tr>\n      <th>2022-11-14</th>\n      <td>16085.94</td>\n      <td>19549.92900</td>\n      <td>20710.636000</td>\n    </tr>\n    <tr>\n      <th>2022-11-15</th>\n      <td>16086.74</td>\n      <td>19442.44400</td>\n      <td>20635.065312</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "days_short_term_window = 40\n",
    "days_long_term_window = 160\n",
    "\n",
    "data['SMA_SHORT_TERM'] = data[symbol].rolling(days_short_term_window).mean()\n",
    "data['SMA_LONG_TERM'] = data[symbol].rolling(days_long_term_window).mean()\n",
    "\n",
    "data.tail(n=30)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1000x600 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot(figsize=(10, 6));"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [],
   "source": [
    "data.dropna(inplace=True)\n",
    "data['position'] = np.where(data['SMA_SHORT_TERM'] > data['SMA_LONG_TERM'], 1, -1)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [
    {
     "data": {
      "text/plain": "                 BTC  SMA_SHORT_TERM  SMA_LONG_TERM  position\ntime                                                         \n2022-10-17  19865.60     19972.94600   22238.983813        -1\n2022-10-18  19606.10     19980.47650   22189.332250        -1\n2022-10-19  19587.23     19940.07750   22137.535313        -1\n2022-10-20  19479.37     19888.56375   22083.527438        -1\n2022-10-21  19441.38     19832.57075   22024.379812        -1\n2022-10-22  19480.55     19766.83275   21958.014875        -1\n2022-10-23  19838.43     19757.15675   21903.297937        -1\n2022-10-24  19557.63     19739.40475   21845.224187        -1\n2022-10-25  20156.82     19749.92225   21799.993125        -1\n2022-10-26  20580.78     19769.87825   21749.626000        -1\n2022-10-27  20359.34     19776.41350   21704.099250        -1\n2022-10-28  20682.01     19808.88350   21659.289875        -1\n2022-10-29  20880.89     19843.62750   21610.794750        -1\n2022-10-30  20725.89     19888.34950   21570.146500        -1\n2022-10-31  20733.15     19936.62075   21527.142563        -1\n2022-11-01  20745.58     19962.31850   21484.139875        -1\n2022-11-02  20536.06     19978.28750   21442.428188        -1\n2022-11-03  20730.29     20008.65750   21405.471438        -1\n2022-11-04  21252.78     20054.68450   21369.260375        -1\n2022-11-05  21400.90     20089.92250   21331.429250        -1\n2022-11-06  21087.79     20119.76700   21279.188187        -1\n2022-11-07  20569.71     20134.17150   21222.695062        -1\n2022-11-08  18454.65     20097.17400   21163.231125        -1\n2022-11-09  15881.30     19998.67950   21085.452313        -1\n2022-11-10  17272.75     19937.64225   21020.178875        -1\n2022-11-11  16486.68     19863.28100   20949.048125        -1\n2022-11-12  16262.21     19770.79625   20876.363188        -1\n2022-11-13  15805.96     19656.47975   20791.817687        -1\n2022-11-14  16085.94     19549.92900   20710.636000        -1\n2022-11-15  16086.74     19442.44400   20635.065312        -1",
      "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>BTC</th>\n      <th>SMA_SHORT_TERM</th>\n      <th>SMA_LONG_TERM</th>\n      <th>position</th>\n    </tr>\n    <tr>\n      <th>time</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2022-10-17</th>\n      <td>19865.60</td>\n      <td>19972.94600</td>\n      <td>22238.983813</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-18</th>\n      <td>19606.10</td>\n      <td>19980.47650</td>\n      <td>22189.332250</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-19</th>\n      <td>19587.23</td>\n      <td>19940.07750</td>\n      <td>22137.535313</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-20</th>\n      <td>19479.37</td>\n      <td>19888.56375</td>\n      <td>22083.527438</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-21</th>\n      <td>19441.38</td>\n      <td>19832.57075</td>\n      <td>22024.379812</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-22</th>\n      <td>19480.55</td>\n      <td>19766.83275</td>\n      <td>21958.014875</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-23</th>\n      <td>19838.43</td>\n      <td>19757.15675</td>\n      <td>21903.297937</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-24</th>\n      <td>19557.63</td>\n      <td>19739.40475</td>\n      <td>21845.224187</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-25</th>\n      <td>20156.82</td>\n      <td>19749.92225</td>\n      <td>21799.993125</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-26</th>\n      <td>20580.78</td>\n      <td>19769.87825</td>\n      <td>21749.626000</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-27</th>\n      <td>20359.34</td>\n      <td>19776.41350</td>\n      <td>21704.099250</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-28</th>\n      <td>20682.01</td>\n      <td>19808.88350</td>\n      <td>21659.289875</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-29</th>\n      <td>20880.89</td>\n      <td>19843.62750</td>\n      <td>21610.794750</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-30</th>\n      <td>20725.89</td>\n      <td>19888.34950</td>\n      <td>21570.146500</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-10-31</th>\n      <td>20733.15</td>\n      <td>19936.62075</td>\n      <td>21527.142563</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-01</th>\n      <td>20745.58</td>\n      <td>19962.31850</td>\n      <td>21484.139875</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-02</th>\n      <td>20536.06</td>\n      <td>19978.28750</td>\n      <td>21442.428188</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-03</th>\n      <td>20730.29</td>\n      <td>20008.65750</td>\n      <td>21405.471438</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-04</th>\n      <td>21252.78</td>\n      <td>20054.68450</td>\n      <td>21369.260375</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-05</th>\n      <td>21400.90</td>\n      <td>20089.92250</td>\n      <td>21331.429250</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-06</th>\n      <td>21087.79</td>\n      <td>20119.76700</td>\n      <td>21279.188187</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-07</th>\n      <td>20569.71</td>\n      <td>20134.17150</td>\n      <td>21222.695062</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-08</th>\n      <td>18454.65</td>\n      <td>20097.17400</td>\n      <td>21163.231125</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-09</th>\n      <td>15881.30</td>\n      <td>19998.67950</td>\n      <td>21085.452313</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-10</th>\n      <td>17272.75</td>\n      <td>19937.64225</td>\n      <td>21020.178875</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-11</th>\n      <td>16486.68</td>\n      <td>19863.28100</td>\n      <td>20949.048125</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-12</th>\n      <td>16262.21</td>\n      <td>19770.79625</td>\n      <td>20876.363188</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-13</th>\n      <td>15805.96</td>\n      <td>19656.47975</td>\n      <td>20791.817687</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-14</th>\n      <td>16085.94</td>\n      <td>19549.92900</td>\n      <td>20710.636000</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>2022-11-15</th>\n      <td>16086.74</td>\n      <td>19442.44400</td>\n      <td>20635.065312</td>\n      <td>-1</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail(n=30)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1000x600 with 2 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = data.plot(secondary_y='position', figsize=(10, 6))\n",
    "ax.get_legend();"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# Backtesting"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [],
   "source": [
    "data['buy_hold'] = np.log(data[symbol] / data[symbol].shift(1))\n",
    "data['strategy'] = data['position'].shift(1) * data['buy_hold']\n",
    "data.dropna(inplace=True)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [
    {
     "data": {
      "text/plain": "            position  buy_hold  strategy\ntime                                    \n2022-11-11        -1 -0.046577  0.046577\n2022-11-12        -1 -0.013709  0.013709\n2022-11-13        -1 -0.028457  0.028457\n2022-11-14        -1  0.017559 -0.017559\n2022-11-15        -1  0.000050 -0.000050",
      "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>buy_hold</th>\n      <th>strategy</th>\n    </tr>\n    <tr>\n      <th>time</th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2022-11-11</th>\n      <td>-1</td>\n      <td>-0.046577</td>\n      <td>0.046577</td>\n    </tr>\n    <tr>\n      <th>2022-11-12</th>\n      <td>-1</td>\n      <td>-0.013709</td>\n      <td>0.013709</td>\n    </tr>\n    <tr>\n      <th>2022-11-13</th>\n      <td>-1</td>\n      <td>-0.028457</td>\n      <td>0.028457</td>\n    </tr>\n    <tr>\n      <th>2022-11-14</th>\n      <td>-1</td>\n      <td>0.017559</td>\n      <td>-0.017559</td>\n    </tr>\n    <tr>\n      <th>2022-11-15</th>\n      <td>-1</td>\n      <td>0.000050</td>\n      <td>-0.000050</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['position', 'buy_hold', 'strategy']].tail()  # daily returns"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "data": {
      "text/plain": "buy_hold    0.211334\nstrategy    0.532407\ndtype: float64"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['buy_hold', 'strategy']].mean() * 365  # annualized return"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "data": {
      "text/plain": "buy_hold    0.783172\nstrategy    0.782754\ndtype: float64"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['buy_hold', 'strategy']].std() * 365 ** 0.5  # annualized volatility"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "data": {
      "text/plain": "buy_hold    0.269843\nstrategy    0.680172\ndtype: float64"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sharpe_ratio = (data[['buy_hold', 'strategy']].mean() * 365) / (data[['buy_hold', 'strategy']].std() * 365 ** 0.5)  # annualized Sharpe ratio\n",
    "sharpe_ratio"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [
    {
     "data": {
      "text/plain": "buy_hold    0.606027\nstrategy    1.527563\ndtype: float64"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t_statistic = (data[['buy_hold', 'strategy']].mean() / data[['buy_hold', 'strategy']].std()) * len(data) ** 0.5\n",
    "t_statistic"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [
    {
     "data": {
      "text/plain": "buy_hold    0.544572\nstrategy    0.126793\ndtype: float64"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p_s = pd.Series(t.sf(t_statistic, len(data) - 1) * 2)  # H0: sharpe_ratio == 0; two-sided test\n",
    "p_s.index = t_statistic.index\n",
    "p_s"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# Optimization"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [],
   "source": [
    "days_short_term_window = range(10, 95, 5)\n",
    "days_long_term_window = range(100, 500, 5)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [
    {
     "data": {
      "text/plain": "[10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90]"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(days_short_term_window)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [
    {
     "data": {
      "text/plain": "[100,\n 105,\n 110,\n 115,\n 120,\n 125,\n 130,\n 135,\n 140,\n 145,\n 150,\n 155,\n 160,\n 165,\n 170,\n 175,\n 180,\n 185,\n 190,\n 195,\n 200,\n 205,\n 210,\n 215,\n 220,\n 225,\n 230,\n 235,\n 240,\n 245,\n 250,\n 255,\n 260,\n 265,\n 270,\n 275,\n 280,\n 285,\n 290,\n 295,\n 300,\n 305,\n 310,\n 315,\n 320,\n 325,\n 330,\n 335,\n 340,\n 345,\n 350,\n 355,\n 360,\n 365,\n 370,\n 375,\n 380,\n 385,\n 390,\n 395,\n 400,\n 405,\n 410,\n 415,\n 420,\n 425,\n 430,\n 435,\n 440,\n 445,\n 450,\n 455,\n 460,\n 465,\n 470,\n 475,\n 480,\n 485,\n 490,\n 495]"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(days_long_term_window)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [
    {
     "data": {
      "text/plain": "      NUM_OBS  SMA_SHORT_TERM  SMA_LONG_TERM  SHARPE_RATIO_ANNUALIZED  \\\n0        1901              10            100                 0.912284   \n1285     1876              90            125                 0.881054   \n1286     1871              90            130                 0.869336   \n1349     1556              90            445                 0.838269   \n1272     1541              85            460                 0.814630   \n...       ...             ...            ...                      ...   \n509      1756              40            245                -0.168413   \n681      1696              50            305                -0.178091   \n265      1776              25            225                -0.202638   \n267      1766              25            235                -0.206142   \n266      1771              25            230                -0.373318   \n\n      T-STATISTIC   P-VALUE  \n0        2.081971  0.037479  \n1285     1.997435  0.045922  \n1286     1.968239  0.049188  \n1349     1.730780  0.083689  \n1272     1.673846  0.094364  \n...           ...       ...  \n509     -0.369395  0.711878  \n681     -0.383891  0.701108  \n265     -0.446988  0.654938  \n267     -0.453436  0.650290  \n266     -0.822321  0.411005  \n\n[1360 rows x 6 columns]",
      "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>NUM_OBS</th>\n      <th>SMA_SHORT_TERM</th>\n      <th>SMA_LONG_TERM</th>\n      <th>SHARPE_RATIO_ANNUALIZED</th>\n      <th>T-STATISTIC</th>\n      <th>P-VALUE</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1901</td>\n      <td>10</td>\n      <td>100</td>\n      <td>0.912284</td>\n      <td>2.081971</td>\n      <td>0.037479</td>\n    </tr>\n    <tr>\n      <th>1285</th>\n      <td>1876</td>\n      <td>90</td>\n      <td>125</td>\n      <td>0.881054</td>\n      <td>1.997435</td>\n      <td>0.045922</td>\n    </tr>\n    <tr>\n      <th>1286</th>\n      <td>1871</td>\n      <td>90</td>\n      <td>130</td>\n      <td>0.869336</td>\n      <td>1.968239</td>\n      <td>0.049188</td>\n    </tr>\n    <tr>\n      <th>1349</th>\n      <td>1556</td>\n      <td>90</td>\n      <td>445</td>\n      <td>0.838269</td>\n      <td>1.730780</td>\n      <td>0.083689</td>\n    </tr>\n    <tr>\n      <th>1272</th>\n      <td>1541</td>\n      <td>85</td>\n      <td>460</td>\n      <td>0.814630</td>\n      <td>1.673846</td>\n      <td>0.094364</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    </tr>\n    <tr>\n      <th>509</th>\n      <td>1756</td>\n      <td>40</td>\n      <td>245</td>\n      <td>-0.168413</td>\n      <td>-0.369395</td>\n      <td>0.711878</td>\n    </tr>\n    <tr>\n      <th>681</th>\n      <td>1696</td>\n      <td>50</td>\n      <td>305</td>\n      <td>-0.178091</td>\n      <td>-0.383891</td>\n      <td>0.701108</td>\n    </tr>\n    <tr>\n      <th>265</th>\n      <td>1776</td>\n      <td>25</td>\n      <td>225</td>\n      <td>-0.202638</td>\n      <td>-0.446988</td>\n      <td>0.654938</td>\n    </tr>\n    <tr>\n      <th>267</th>\n      <td>1766</td>\n      <td>25</td>\n      <td>235</td>\n      <td>-0.206142</td>\n      <td>-0.453436</td>\n      <td>0.650290</td>\n    </tr>\n    <tr>\n      <th>266</th>\n      <td>1771</td>\n      <td>25</td>\n      <td>230</td>\n      <td>-0.373318</td>\n      <td>-0.822321</td>\n      <td>0.411005</td>\n    </tr>\n  </tbody>\n</table>\n<p>1360 rows × 6 columns</p>\n</div>"
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_list = list()\n",
    "for days_short, days_long in product(days_short_term_window, days_long_term_window):\n",
    "    data = pd.DataFrame(raw)\n",
    "    data['time'] = pd.to_datetime(data['time'], unit='s')\n",
    "    data.index = pd.DatetimeIndex(data['time'])\n",
    "    data = data[['close']]\n",
    "    data.columns = [symbol]\n",
    "    data.dropna(inplace=True)\n",
    "    data['SMA_SHORT_TERM'] = data[symbol].rolling(days_short).mean()\n",
    "    data['SMA_LONG_TERM'] = data[symbol].rolling(days_long).mean()\n",
    "    data.dropna(inplace=True)\n",
    "    data['position'] = np.where(data['SMA_SHORT_TERM'] > data['SMA_LONG_TERM'], 1, -1)\n",
    "    data['buy_hold'] = np.log(data[symbol] / data[symbol].shift(1))\n",
    "    data['strategy'] = data['position'].shift(1) * data['buy_hold']\n",
    "    data.dropna(inplace=True)\n",
    "    num_obs = len(data)\n",
    "    sharpe_ratio = data[['buy_hold', 'strategy']].mean() / data[['buy_hold', 'strategy']].std()\n",
    "    sharpe_ratio_annualized = sharpe_ratio * 365 ** 0.5\n",
    "    t_statistic = sharpe_ratio[['buy_hold', 'strategy']] * num_obs ** 0.5\n",
    "    p_s = pd.Series(t.sf(abs(t_statistic), num_obs - 1) * 2)\n",
    "    p_s.index = t_statistic.index\n",
    "\n",
    "    results_list.append([num_obs, days_short, days_long, sharpe_ratio_annualized['strategy'], t_statistic['strategy'], p_s['strategy']])\n",
    "\n",
    "results = pd.DataFrame(results_list, columns=['NUM_OBS', 'SMA_SHORT_TERM', 'SMA_LONG_TERM', 'SHARPE_RATIO_ANNUALIZED', 'T-STATISTIC', 'P-VALUE'])\n",
    "results.sort_values('SHARPE_RATIO_ANNUALIZED', ascending=False)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "outputs": [
    {
     "data": {
      "text/plain": "1360"
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "number_tests_conducted = len(days_short_term_window) * len(days_long_term_window)\n",
    "number_tests_conducted"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "outputs": [
    {
     "data": {
      "text/plain": "0.037478674946799705"
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index_max_sharpe_ratio = results['SHARPE_RATIO_ANNUALIZED'] == results['SHARPE_RATIO_ANNUALIZED'].max()\n",
    "p_s = results['P-VALUE'].loc[index_max_sharpe_ratio].item()\n",
    "p_s"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "outputs": [
    {
     "data": {
      "text/plain": "1.0"
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p_m = 1 - (1 - p_s) ** number_tests_conducted\n",
    "p_m"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# Haircut Sharpe ratio"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "outputs": [
    {
     "data": {
      "text/plain": "-2.909036069395466e-17"
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_obs = results['NUM_OBS'].loc[index_max_sharpe_ratio].item()\n",
    "haircut_sharpe_ratio_annualized = t.isf(p_m/2, num_obs - 1) / (num_obs ** 0.5) * 365 ** 0.5\n",
    "haircut_sharpe_ratio_annualized"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
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  "language_info": {
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   "file_extension": ".py",
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