24_alpha_factor_library/01_sample_selection.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Prep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:43:49.209438Z",
     "start_time": "2021-04-16T04:43:49.206368Z"
    }
   },
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:43:49.718392Z",
     "start_time": "2021-04-16T04:43:49.213710Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:43:49.721292Z",
     "start_time": "2021-04-16T04:43:49.719291Z"
    }
   },
   "outputs": [],
   "source": [
    "sns.set_style('whitegrid')\n",
    "idx = pd.IndexSlice\n",
    "deciles = np.arange(.1, 1, .1).round(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:43:49.735163Z",
     "start_time": "2021-04-16T04:43:49.722317Z"
    }
   },
   "outputs": [],
   "source": [
    "DATA_STORE = Path('..', 'data', 'assets.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:43:57.006315Z",
     "start_time": "2021-04-16T04:43:49.736203Z"
    }
   },
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    data = (store['quandl/wiki/prices']\n",
    "            .loc[idx['2007':'2016', :],\n",
    "                 ['adj_open', 'adj_high', 'adj_low', 'adj_close', 'adj_volume']]\n",
    "            .dropna()\n",
    "            .swaplevel()\n",
    "            .sort_index()\n",
    "            .rename(columns=lambda x: x.replace('adj_', '')))\n",
    "    metadata = store['us_equities/stocks'].loc[:, ['marketcap', 'sector']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:43:57.144354Z",
     "start_time": "2021-04-16T04:43:57.007191Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "MultiIndex: 6951874 entries, ('A', Timestamp('2007-01-03 00:00:00')) to ('ZUMZ', Timestamp('2016-12-30 00:00:00'))\n",
      "Data columns (total 5 columns):\n",
      " #   Column  Non-Null Count    Dtype  \n",
      "---  ------  --------------    -----  \n",
      " 0   open    6951874 non-null  float64\n",
      " 1   high    6951874 non-null  float64\n",
      " 2   low     6951874 non-null  float64\n",
      " 3   close   6951874 non-null  float64\n",
      " 4   volume  6951874 non-null  float64\n",
      "dtypes: float64(5)\n",
      "memory usage: 292.5+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info(null_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:43:57.152798Z",
     "start_time": "2021-04-16T04:43:57.145264Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 6834 entries, PIH to ZYME\n",
      "Data columns (total 2 columns):\n",
      " #   Column     Non-Null Count  Dtype  \n",
      "---  ------     --------------  -----  \n",
      " 0   marketcap  5766 non-null   float64\n",
      " 1   sector     6834 non-null   int64  \n",
      "dtypes: float64(1), int64(1)\n",
      "memory usage: 160.2+ KB\n"
     ]
    }
   ],
   "source": [
    "metadata.sector = pd.factorize(metadata.sector)[0]\n",
    "metadata.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:43:57.551366Z",
     "start_time": "2021-04-16T04:43:57.153657Z"
    }
   },
   "outputs": [],
   "source": [
    "data = data.join(metadata).dropna(subset=['sector'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:43:57.667187Z",
     "start_time": "2021-04-16T04:43:57.552737Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "MultiIndex: 5395695 entries, ('A', Timestamp('2007-01-03 00:00:00')) to ('ZUMZ', Timestamp('2016-12-30 00:00:00'))\n",
      "Data columns (total 7 columns):\n",
      " #   Column     Non-Null Count    Dtype  \n",
      "---  ------     --------------    -----  \n",
      " 0   open       5395695 non-null  float64\n",
      " 1   high       5395695 non-null  float64\n",
      " 2   low        5395695 non-null  float64\n",
      " 3   close      5395695 non-null  float64\n",
      " 4   volume     5395695 non-null  float64\n",
      " 5   marketcap  5385154 non-null  float64\n",
      " 6   sector     5395695 non-null  float64\n",
      "dtypes: float64(7)\n",
      "memory usage: 309.5+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info(null_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:43:57.731249Z",
     "start_time": "2021-04-16T04:43:57.668307Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Tickers: 2,399 | # Dates: 2,547\n"
     ]
    }
   ],
   "source": [
    "print(f\"# Tickers: {len(data.index.unique('ticker')):,.0f} | # Dates: {len(data.index.unique('date')):,.0f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Select 500 most-traded stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:43:57.742092Z",
     "start_time": "2021-04-16T04:43:57.732173Z"
    }
   },
   "outputs": [],
   "source": [
    "dv = data.close.mul(data.volume)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:00.453581Z",
     "start_time": "2021-04-16T04:43:57.743088Z"
    }
   },
   "outputs": [],
   "source": [
    "top500 = (dv.groupby(level='date')\n",
    "          .rank(ascending=False)\n",
    "          .unstack('ticker')\n",
    "          .dropna(thresh=8*252, axis=1)\n",
    "          .mean()\n",
    "          .nsmallest(500))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize the 200 most liquid stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:03.749823Z",
     "start_time": "2021-04-16T04:44:00.454390Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top200 = (data.close\n",
    "          .mul(data.volume)\n",
    "          .unstack('ticker')\n",
    "          .dropna(thresh=8*252, axis=1)\n",
    "          .mean()\n",
    "          .div(1e6)\n",
    "          .nlargest(200))\n",
    "cutoffs = [0, 50, 100, 150, 200]\n",
    "fig, axes = plt.subplots(ncols=4, figsize=(20, 10), sharex=True)\n",
    "axes = axes.flatten()\n",
    "\n",
    "for i, cutoff in enumerate(cutoffs[1:], 1):\n",
    "    top200.iloc[cutoffs[i-1]:cutoffs[i]\n",
    "                ].sort_values().plot.barh(logx=True, ax=axes[i-1])\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:03.780671Z",
     "start_time": "2021-04-16T04:44:03.750706Z"
    }
   },
   "outputs": [],
   "source": [
    "to_drop = data.index.unique('ticker').difference(top500.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:03.783912Z",
     "start_time": "2021-04-16T04:44:03.781548Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1899"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(to_drop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:08.989478Z",
     "start_time": "2021-04-16T04:44:03.785057Z"
    }
   },
   "outputs": [],
   "source": [
    "data = data.drop(to_drop, level='ticker')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:09.022941Z",
     "start_time": "2021-04-16T04:44:08.990382Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "MultiIndex: 1256095 entries, ('A', Timestamp('2007-01-03 00:00:00')) to ('ZION', Timestamp('2016-12-30 00:00:00'))\n",
      "Data columns (total 7 columns):\n",
      " #   Column     Non-Null Count    Dtype  \n",
      "---  ------     --------------    -----  \n",
      " 0   open       1256095 non-null  float64\n",
      " 1   high       1256095 non-null  float64\n",
      " 2   low        1256095 non-null  float64\n",
      " 3   close      1256095 non-null  float64\n",
      " 4   volume     1256095 non-null  float64\n",
      " 5   marketcap  1253855 non-null  float64\n",
      " 6   sector     1256095 non-null  float64\n",
      "dtypes: float64(7)\n",
      "memory usage: 72.6+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info(null_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:09.045563Z",
     "start_time": "2021-04-16T04:44:09.023994Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Tickers: 500 | # Dates: 2,518\n"
     ]
    }
   ],
   "source": [
    "print(f\"# Tickers: {len(data.index.unique('ticker')):,.0f} | # Dates: {len(data.index.unique('date')):,.0f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Remove outlier observations based on daily returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:09.228707Z",
     "start_time": "2021-04-16T04:44:09.046832Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dropped 502\n"
     ]
    }
   ],
   "source": [
    "before = len(data)\n",
    "data['ret'] = data.groupby('ticker').close.pct_change()\n",
    "data = data[data.ret.between(-1, 1)].drop('ret', axis=1)\n",
    "print(f'Dropped {before-len(data):,.0f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:09.247556Z",
     "start_time": "2021-04-16T04:44:09.229607Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Tickers: 500 | # Dates: 2,517\n"
     ]
    }
   ],
   "source": [
    "tickers = data.index.unique('ticker')\n",
    "print(f\"# Tickers: {len(tickers):,.0f} | # Dates: {len(data.index.unique('date')):,.0f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sample price data for illustration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:09.260665Z",
     "start_time": "2021-04-16T04:44:09.248436Z"
    }
   },
   "outputs": [],
   "source": [
    "ticker = 'AAPL'\n",
    "# alternative\n",
    "# ticker = np.random.choice(tickers)\n",
    "price_sample = data.loc[idx[ticker, :], :].reset_index('ticker', drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:09.268597Z",
     "start_time": "2021-04-16T04:44:09.261775Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 2517 entries, 2007-01-04 to 2016-12-30\n",
      "Data columns (total 7 columns):\n",
      " #   Column     Non-Null Count  Dtype  \n",
      "---  ------     --------------  -----  \n",
      " 0   open       2517 non-null   float64\n",
      " 1   high       2517 non-null   float64\n",
      " 2   low        2517 non-null   float64\n",
      " 3   close      2517 non-null   float64\n",
      " 4   volume     2517 non-null   float64\n",
      " 5   marketcap  2517 non-null   float64\n",
      " 6   sector     2517 non-null   float64\n",
      "dtypes: float64(7)\n",
      "memory usage: 157.3 KB\n"
     ]
    }
   ],
   "source": [
    "price_sample.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:09.278269Z",
     "start_time": "2021-04-16T04:44:09.270335Z"
    }
   },
   "outputs": [],
   "source": [
    "price_sample.to_hdf('data.h5', 'data/sample')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute returns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Group data by ticker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:09.306943Z",
     "start_time": "2021-04-16T04:44:09.280490Z"
    }
   },
   "outputs": [],
   "source": [
    "by_ticker = data.groupby(level='ticker')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Historical returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:09.315466Z",
     "start_time": "2021-04-16T04:44:09.310205Z"
    }
   },
   "outputs": [],
   "source": [
    "T = [1, 2, 3, 4, 5, 10, 21, 42, 63, 126, 252]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:09.777872Z",
     "start_time": "2021-04-16T04:44:09.319201Z"
    }
   },
   "outputs": [],
   "source": [
    "for t in T:\n",
    "    data[f'ret_{t:02}'] = by_ticker.close.pct_change(t)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Forward returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:09.908413Z",
     "start_time": "2021-04-16T04:44:09.778722Z"
    }
   },
   "outputs": [],
   "source": [
    "data['ret_fwd'] = by_ticker.ret_01.shift(-1)\n",
    "data = data.dropna(subset=['ret_fwd'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Persist results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:09.959921Z",
     "start_time": "2021-04-16T04:44:09.909278Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "MultiIndex: 1255093 entries, ('A', Timestamp('2007-01-04 00:00:00')) to ('ZION', Timestamp('2016-12-29 00:00:00'))\n",
      "Data columns (total 19 columns):\n",
      " #   Column     Non-Null Count    Dtype  \n",
      "---  ------     --------------    -----  \n",
      " 0   open       1255093 non-null  float64\n",
      " 1   high       1255093 non-null  float64\n",
      " 2   low        1255093 non-null  float64\n",
      " 3   close      1255093 non-null  float64\n",
      " 4   volume     1255093 non-null  float64\n",
      " 5   marketcap  1252855 non-null  float64\n",
      " 6   sector     1255093 non-null  float64\n",
      " 7   ret_01     1254593 non-null  float64\n",
      " 8   ret_02     1254093 non-null  float64\n",
      " 9   ret_03     1253593 non-null  float64\n",
      " 10  ret_04     1253093 non-null  float64\n",
      " 11  ret_05     1252593 non-null  float64\n",
      " 12  ret_10     1250093 non-null  float64\n",
      " 13  ret_21     1244593 non-null  float64\n",
      " 14  ret_42     1234093 non-null  float64\n",
      " 15  ret_63     1223593 non-null  float64\n",
      " 16  ret_126    1192093 non-null  float64\n",
      " 17  ret_252    1129093 non-null  float64\n",
      " 18  ret_fwd    1255093 non-null  float64\n",
      "dtypes: float64(19)\n",
      "memory usage: 187.5+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info(null_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-16T04:44:10.119416Z",
     "start_time": "2021-04-16T04:44:09.960904Z"
    }
   },
   "outputs": [],
   "source": [
    "data.to_hdf('data.h5', 'data/top500')"
   ]
  }
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