xbtusd-weighted-depth-orderbook-price-simple-backtest-hedge.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy.stats as stats\n",
    "from sklearn.model_selection import GridSearchCV, RandomizedSearchCV\n",
    "from numba import njit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# bid = map(lambda x: (x['price'], x['size']), sorted(filter(lambda x: x['side'] == 'Buy', market_depth), key=lambda x: -x['price']))\n",
    "# ask = map(lambda x: (x['price'], x['size']), sorted(filter(lambda x: x['side'] == 'Sell', market_depth), key=lambda x: x['price']))\n",
    "\n",
    "# bid = pd.DataFrame(bid, columns=['price', 'size'])\n",
    "# bid = bid[bid['size'].cumsum() <= 50M]\n",
    "\n",
    "# ask = pd.DataFrame(ask, columns=['price', 'size'])\n",
    "# ask = ask[ask['size'].cumsum() <= 50M]\n",
    "\n",
    "# weighted_price = ((bid['price'] * bid['size']).sum() + (ask['price'] * ask['size']).sum()) / (bid['size'].sum() + ask['size'].sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_pickle('data_wp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <th>2019-04-01 00:00:15</th>\n",
       "      <td>4091.0</td>\n",
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       "      <th>2021-03-16 23:59:40</th>\n",
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       "    <tr>\n",
       "      <th>2021-03-16 23:59:50</th>\n",
       "      <td>57000.0</td>\n",
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       "      <th>2021-03-16 23:59:55</th>\n",
       "      <td>57003.0</td>\n",
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       "      <th>2021-03-17 00:00:00</th>\n",
       "      <td>57009.5</td>\n",
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      ],
      "text/plain": [
       "                        open     high      low    close           50M  \\\n",
       "timestamp                                                               \n",
       "2019-04-01 00:00:00   4091.0   4091.0   4091.0   4091.0   4085.571400   \n",
       "2019-04-01 00:00:05   4091.0   4091.0   4091.0   4091.0   4085.399523   \n",
       "2019-04-01 00:00:10   4091.0   4091.5   4089.0   4091.5   4082.529929   \n",
       "2019-04-01 00:00:15   4091.0   4091.0   4090.0   4090.0   4082.530385   \n",
       "2019-04-01 00:00:20   4090.0   4090.0   4089.5   4089.5   4082.625409   \n",
       "...                      ...      ...      ...      ...           ...   \n",
       "2021-03-16 23:59:40  56982.5  56984.0  56982.0  56984.0  56933.358259   \n",
       "2021-03-16 23:59:45  56984.5  57000.5  56984.5  56999.5  56927.318710   \n",
       "2021-03-16 23:59:50  57000.0  57003.5  57000.0  57003.5  56933.382341   \n",
       "2021-03-16 23:59:55  57003.0  57010.0  57003.0  57009.5  56926.418830   \n",
       "2021-03-17 00:00:00  57009.5  57010.0  57009.5  57009.5  56925.911347   \n",
       "\n",
       "                              60M           70M           80M           90M  \\\n",
       "timestamp                                                                     \n",
       "2019-04-01 00:00:00   4085.130774   4087.437362   4084.554931   4084.907248   \n",
       "2019-04-01 00:00:05   4084.791366   4087.413743   4084.522832   4084.187821   \n",
       "2019-04-01 00:00:10   4083.166928   4083.417778   4083.459346   4082.776234   \n",
       "2019-04-01 00:00:15   4083.167300   4083.418102   4083.459627   4082.776490   \n",
       "2019-04-01 00:00:20   4083.132137   4083.597657   4083.434033   4082.852947   \n",
       "...                           ...           ...           ...           ...   \n",
       "2021-03-16 23:59:40  56905.529823  56891.109569  56884.600594  56846.962940   \n",
       "2021-03-16 23:59:45  56900.524021  56897.526770  56887.541229  56853.438592   \n",
       "2021-03-16 23:59:50  56902.808522  56893.980914  56897.732631  56862.060212   \n",
       "2021-03-16 23:59:55  56904.008264  56896.136176  56890.536831  56768.946557   \n",
       "2021-03-17 00:00:00  56897.355664  56884.153274  56874.590364  56827.321433   \n",
       "\n",
       "                             100M          110M          120M          130M  \\\n",
       "timestamp                                                                     \n",
       "2019-04-01 00:00:00   4084.204241   4084.122591   4084.557309   4085.346957   \n",
       "2019-04-01 00:00:05   4084.176147   4084.155550   4084.534677   4085.222487   \n",
       "2019-04-01 00:00:10   4082.616253   4082.332862   4082.124100   4083.247482   \n",
       "2019-04-01 00:00:15   4082.616484   4082.339690   4082.139391   4083.247656   \n",
       "2019-04-01 00:00:20   4082.594677   4082.461301   4082.380484   4083.224374   \n",
       "...                           ...           ...           ...           ...   \n",
       "2021-03-16 23:59:40  56787.134872  56684.219557  56614.056547  56557.341366   \n",
       "2021-03-16 23:59:45  56797.369961  56699.554637  56617.588829  56578.474896   \n",
       "2021-03-16 23:59:50  56761.454735  56680.456887  56626.673234  56556.217750   \n",
       "2021-03-16 23:59:55  56745.722303  56689.983891  56555.407082  56563.762076   \n",
       "2021-03-17 00:00:00  56760.300537  56670.393411  56607.416416  56546.248607   \n",
       "\n",
       "                             140M          150M  \n",
       "timestamp                                        \n",
       "2019-04-01 00:00:00   4086.800757   4090.625193  \n",
       "2019-04-01 00:00:05   4087.068056   4090.805397  \n",
       "2019-04-01 00:00:10   4084.769454   4087.996800  \n",
       "2019-04-01 00:00:15   4084.769610   4087.996931  \n",
       "2019-04-01 00:00:20   4085.025355   4087.980490  \n",
       "...                           ...           ...  \n",
       "2021-03-16 23:59:40  56528.962572  56501.849834  \n",
       "2021-03-16 23:59:45  56534.045808  56505.978890  \n",
       "2021-03-16 23:59:50  56519.648433  56487.811176  \n",
       "2021-03-16 23:59:55  56505.361199  56486.417928  \n",
       "2021-03-17 00:00:00  56497.609782  56466.330698  \n",
       "\n",
       "[12372482 rows x 15 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "@njit\n",
    "def predict_njit(start_equity, threshold, max_position, X, imbalance):\n",
    "    tick_size = 0.5\n",
    "    running_qty = 0\n",
    "    static_equity = start_equity\n",
    "    fee = 0\n",
    "    equity = []\n",
    "    running_qty_ = []\n",
    "    order_qty = 100\n",
    "    new_bid = np.nan\n",
    "    new_ask = np.nan\n",
    "    high = 1\n",
    "    low = 2\n",
    "    close = 3\n",
    "    for row in X:\n",
    "        if new_bid > row[low]:\n",
    "            running_qty += order_qty\n",
    "            static_equity += order_qty / new_bid\n",
    "            fee += order_qty / new_bid * -0.00025    \n",
    "        if new_ask < row[high]:\n",
    "            running_qty -= order_qty\n",
    "            static_equity -= order_qty / new_ask\n",
    "            fee += order_qty / new_ask * -0.00025    \n",
    "        equity.append(static_equity * row[close] - running_qty - fee * row[close])\n",
    "        running_qty_.append(running_qty)\n",
    "        running_qty_hedged = running_qty + equity[-1]\n",
    "        ind = row[imbalance] - row[close]\n",
    "        if ind > threshold and running_qty_hedged < max_position:\n",
    "            new_bid = row[close] - tick_size\n",
    "        else:\n",
    "            new_bid = np.nan\n",
    "        if ind < -threshold and running_qty_hedged > -max_position:\n",
    "            new_ask = row[close] + tick_size\n",
    "        else:\n",
    "            new_ask = np.nan\n",
    "    return equity, running_qty_\n",
    "\n",
    "class Backtest:\n",
    "    def __init__(self, equity=None, max_position=None, threshold=None, imbalance=None):\n",
    "        self.equity = equity\n",
    "        self.max_position = max_position\n",
    "        self.threshold = threshold\n",
    "        self.imbalance = imbalance\n",
    "        \n",
    "    def set_params(self, threshold, imbalance):\n",
    "        self.threshold = threshold\n",
    "        self.imbalance = imbalance\n",
    "        return self\n",
    "        \n",
    "    def get_params(self, deep=True):\n",
    "        return { 'equity': self.equity, 'max_position': self.max_position, 'threshold': self.threshold, 'imbalance': self.imbalance }\n",
    "        \n",
    "    def fit(self, X, y=None):\n",
    "        return self\n",
    "    \n",
    "    def predict(self, X):\n",
    "        equity, running_qty = predict_njit(self.equity, self.threshold, self.max_position, X, self.imbalance)\n",
    "        return equity, running_qty\n",
    "    \n",
    "    def score(self, X):\n",
    "        equity, running_qty = self.predict(X)\n",
    "        returns = pd.Series(equity).pct_change().fillna(0)\n",
    "        return np.divide(returns.mean(), returns.std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = df[(df.index >= '2019-7-1') & (df.index < '2020-1-1')]\n",
    "valid = df[(df.index >= '2020-1-1') & (df.index < '2021-1-8')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 1 folds for each of 1000 candidates, totalling 1000 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=8)]: Using backend LokyBackend with 8 concurrent workers.\n",
      "[Parallel(n_jobs=8)]: Done  34 tasks      | elapsed:   10.1s\n",
      "[Parallel(n_jobs=8)]: Done 184 tasks      | elapsed:   45.5s\n",
      "[Parallel(n_jobs=8)]: Done 434 tasks      | elapsed:  1.7min\n",
      "[Parallel(n_jobs=8)]: Done 784 tasks      | elapsed:  3.1min\n",
      "[Parallel(n_jobs=8)]: Done 1000 out of 1000 | elapsed:  3.9min finished\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "RandomizedSearchCV(cv=[(array([      0,       1,       2, ..., 3179517, 3179518, 3179519]),\n",
       "                        array([      0,       1,       2, ..., 3179517, 3179518, 3179519]))],\n",
       "                   estimator=<__main__.Backtest object at 0x7f8c295944d0>,\n",
       "                   n_iter=1000, n_jobs=8,\n",
       "                   param_distributions={'imbalance': array([ 4,  5,  6,  7,  8,  9, 10]),\n",
       "                                        'threshold': <scipy.stats._distn_infrastructure.rv_frozen object at 0x7f8c29594610>},\n",
       "                   verbose=1)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "param_dist = { 'threshold': stats.uniform(0, 100), 'imbalance': np.arange(4, 11) }\n",
    "search = RandomizedSearchCV(Backtest(1, 10000),\n",
    "                            cv=[(np.arange(len(train)), np.arange(len(train)))],\n",
    "                            param_distributions=param_dist,\n",
    "                            verbose=1,\n",
    "                            n_iter=1000,\n",
    "                            n_jobs=8)\n",
    "search.fit(train.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# v2.1 params\n",
    "# search.best_params_ = { 'imbalance': 8, 'threshold': 0.10407176816108477 }\n",
    "# search.best_estimator_.set_params(**{ 'imbalance': 8, 'threshold': 0.10407176816108477 })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'imbalance': 8, 'threshold': 0.10407176816108477}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.001782320649711738"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search.best_estimator_.score(train.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "equity, running_qty = search.best_estimator_.predict(train.values)\n",
    "equity = pd.Series(equity, index=train.index)\n",
    "running_qty = pd.Series(running_qty, index=train.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timestamp'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "equity.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timestamp'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "train[\"close\"].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timestamp'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "running_qty.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Start date            2019-07-01\n",
      "End date              2019-12-31\n",
      "Time period (days)           183\n",
      "Sharpe Ratio            3.059045\n",
      "CAGR                    3.373504\n",
      "Max Daily Drawdown      0.111965\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "returns = equity.resample('1d').last().pct_change() \n",
    "bm_returns = train['close'].resample('1d').last().pct_change()\n",
    "# returns_ = returns - bm_returns\n",
    "returns_ = returns\n",
    "sr = np.divide(returns_.mean(), returns_.std()) * np.sqrt(252)\n",
    "\n",
    "equity_1d = equity.resample('1d').last()\n",
    "Roll_Max = equity_1d.cummax()\n",
    "Daily_Drawdown = np.divide(equity_1d, Roll_Max) - 1.0\n",
    "Max_Daily_Drawdown = Daily_Drawdown.cummin()\n",
    "\n",
    "period = (equity.index[-1] - equity.index[0]).days\n",
    "\n",
    "print(pd.Series({\n",
    "    'Start date': equity.index[0].strftime('%Y-%m-%d'),\n",
    "    'End date': equity.index[-1].strftime('%Y-%m-%d'),\n",
    "    'Time period (days)': period,\n",
    "    'Sharpe Ratio': sr,\n",
    "    'CAGR': (equity[-1] / equity[0]) ** (365 / period) - 1,\n",
    "    'Max Daily Drawdown': -Max_Daily_Drawdown.min(),\n",
    "}))\n",
    "\n",
    "equity.resample('1d').last().pct_change().hist(bins=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "equity, running_qty = search.best_estimator_.predict(valid.values)\n",
    "equity = pd.Series(equity, index=valid.index)\n",
    "running_qty = pd.Series(running_qty, index=valid.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timestamp'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "equity.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timestamp'>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "valid[\"close\"].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timestamp'>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "running_qty.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Start date            2020-01-01\n",
      "End date              2021-01-07\n",
      "Time period (days)           372\n",
      "Sharpe Ratio            2.542195\n",
      "CAGR                    3.703228\n",
      "Max Daily Drawdown      0.239429\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "returns = equity.resample('1d').last().pct_change() \n",
    "bm_returns = valid['close'].resample('1d').last().pct_change()\n",
    "#returns_ = returns - bm_returns\n",
    "returns_ = returns\n",
    "sr = np.divide(returns_.mean(), returns_.std()) * np.sqrt(252)\n",
    "\n",
    "equity_1d = equity.resample('1d').last()\n",
    "Roll_Max = equity_1d.cummax()\n",
    "Daily_Drawdown = np.divide(equity_1d, Roll_Max) - 1.0\n",
    "Max_Daily_Drawdown = Daily_Drawdown.cummin()\n",
    "\n",
    "period = (equity.index[-1] - equity.index[0]).days\n",
    "\n",
    "print(pd.Series({\n",
    "    'Start date': equity.index[0].strftime('%Y-%m-%d'),\n",
    "    'End date': equity.index[-1].strftime('%Y-%m-%d'),\n",
    "    'Time period (days)': period,\n",
    "    'Sharpe Ratio': sr,\n",
    "    'CAGR': (equity[-1] / equity[0]) ** (365 / period) - 1,\n",
    "    'Max Daily Drawdown': -Max_Daily_Drawdown.min(),\n",
    "}))\n",
    "\n",
    "equity.resample('1d').last().pct_change().hist(bins=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Start date                         2019-04-01\n",
      "End date                           2021-03-17\n",
      "Time period (days)                        716\n",
      "Train period          2019-07-01 - 2019-12-31\n",
      "Valid period          2020-01-01 - 2021-01-07\n",
      "Sharpe ratio                         3.410437\n",
      "CAGR                                 2.931762\n",
      "RRR                                 23.478288\n",
      "Maximum drawdown                     0.124871\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "equity, running_qty = search.best_estimator_.predict(df.values)\n",
    "equity = pd.Series(equity, index=df.index)\n",
    "running_qty = pd.Series(running_qty, index=df.index)\n",
    "\n",
    "\n",
    "returns = equity.resample('1d').last().pct_change() \n",
    "bm_returns = valid['close'].resample('1d').last().pct_change()\n",
    "#returns_ = returns - bm_returns\n",
    "returns_ = returns\n",
    "sr = np.divide(returns_.mean(), returns_.std()) * np.sqrt(252)\n",
    "\n",
    "equity_1d = equity.resample('1d').last()\n",
    "Roll_Max = equity_1d.cummax()\n",
    "Daily_Drawdown = np.divide(equity_1d, Roll_Max) - 1.0\n",
    "Max_Daily_Drawdown = Daily_Drawdown.cummin()\n",
    "\n",
    "period = (equity.index[-1] - equity.index[0]).days\n",
    "\n",
    "print(pd.Series({\n",
    "    'Start date': equity.index[0].strftime('%Y-%m-%d'),\n",
    "    'End date': equity.index[-1].strftime('%Y-%m-%d'),\n",
    "    'Time period (days)': period,\n",
    "    'Train period': '%s - %s' % (train.index[0].strftime('%Y-%m-%d'), train.index[-1].strftime('%Y-%m-%d')),\n",
    "    'Valid period': '%s - %s' % (valid.index[0].strftime('%Y-%m-%d'), valid.index[-1].strftime('%Y-%m-%d')),\n",
    "    'Sharpe ratio': sr,\n",
    "    'CAGR': (equity[-1] / equity[0]) ** (365 / period) - 1,\n",
    "    'RRR': ((equity[-1] / equity[0]) ** (365 / period) - 1) / -Max_Daily_Drawdown.min(),\n",
    "    'Maximum drawdown': -Max_Daily_Drawdown.min(),\n",
    "}))\n",
    "\n",
    "# equity.resample('1d').last().pct_change().hist(bins=20)\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(8, 8))\n",
    "ax1 = ((equity / equity[0] - 1) * 100).plot()\n",
    "ax2 = ((df['close'] / df['close'][0] - 1) * 100).plot()\n",
    "ax1.set_ylabel('Cumulative Returns (%)')\n",
    "ax1.legend([\"Strategy's equity in USD\", 'BitMEX XBTUSD perpetual'])\n",
    "ax1.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timestamp'>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Daily_Drawdown.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timestamp'>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(equity / equity[0] - 1).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}