reinforcement_learning_for_share_trading\run

run.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime as dt\n",
    "import pandas as pd\n",
    "\n",
    "from strategy_learner import *\n",
    "from indicators import *\n",
    "from utils import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "entity_symbol = \"AAPL\"\n",
    "sv = 100000\n",
    "comm = 0.0\n",
    "imp = 0.0\n",
    "\n",
    "pd_prices = get_price(entity_symbol)\n",
    "pd_features = get_indicator(pd_prices)\n",
    "\n",
    "slr = StrategyLearner(impact=imp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# in-sample\n",
    "sd = dt.datetime(2010, 1, 4)\n",
    "ed = dt.datetime(2019, 12, 31)\n",
    "\n",
    "pd_train_trades = slr.addEvidence(entity_symbol, pd_prices, pd_features,\n",
    "                                  sd=sd, ed=ed, sv=sv)\n",
    "#print(pd_train_trades)\n",
    "\n",
    "pd_train_bench = pd.DataFrame(data=[(pd_train_trades.index.min(), entity_symbol, 'BUY', sv / pd_prices.loc[sd, 'adj_close']),\n",
    "                                    (pd_train_trades.index.max(), entity_symbol, 'SELL', sv / pd_prices.loc[sd, 'adj_close'])],\n",
    "                              columns=['date', 'entity_symbol', 'order', 'shares'])\n",
    "\n",
    "pd_train_bench = pd_train_bench.set_index('date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# out-of-sample\n",
    "sd = dt.datetime(2020, 1, 2)\n",
    "ed = dt.datetime(2020, 4, 9)\n",
    "\n",
    "pd_test_trades = slr.testPolicy(entity_symbol, pd_prices, pd_features,\n",
    "                                sd=sd, ed=ed, sv=sv)\n",
    "#print(pd_test_trades)\n",
    "\n",
    "pd_test_bench = pd.DataFrame(data=[(pd_test_trades.index.min(), entity_symbol, 'BUY', sv / pd_prices.loc[sd, 'adj_close']),\n",
    "                                   (pd_test_trades.index.max(), entity_symbol, 'SELL', sv / pd_prices.loc[sd, 'adj_close'])],\n",
    "                             columns=['date', 'entity_symbol', 'order', 'shares'])\n",
    "\n",
    "pd_test_bench = pd_test_bench.set_index('date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "market_simulator(pd_train_trades, pd_train_bench, pd_prices,\n",
    "                 sv=sv, comm=comm, imp=imp,\n",
    "                 save_fig=True, gen_stats=True,\n",
    "                 fig_name='AAPL_sl_train_plot.png',\n",
    "                 stats_name='AAPL_sl_train_stats.tsv')\n",
    "\n",
    "market_simulator(pd_test_trades, pd_test_bench, pd_prices,\n",
    "                 sv=sv, comm=comm, imp=imp,\n",
    "                 save_fig=True, gen_stats=True,\n",
    "                 fig_name='AAPL_sl_test_plot.png',\n",
    "                 stats_name='AAPL_sl_test_stats.tsv')"
   ]
  }
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