05_strategy_evaluation/02_backtest_with_pf_optimization.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MeanReversion backtest with Portfolio Optimization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the chapter 04, we introduced `zipline` to simulate the computation of alpha factors from trailing cross-sectional market, fundamental, and alternative data. \n",
    "\n",
    "Now we will exploit the alpha factors to derive and act on buy and sell signals using the custom MeanReversion factor developed in the last chapter."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:50.924009Z",
     "start_time": "2021-04-15T19:49:50.922066Z"
    }
   },
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:52.141883Z",
     "start_time": "2021-04-15T19:49:50.925252Z"
    }
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "from pytz import UTC\n",
    "import logbook\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from logbook import (NestedSetup, NullHandler, Logger, \n",
    "                     StreamHandler, StderrHandler, \n",
    "                     INFO, WARNING, DEBUG, ERROR)\n",
    "\n",
    "from zipline import run_algorithm\n",
    "from zipline.api import (attach_pipeline,\n",
    "                         date_rules,\n",
    "                         time_rules,\n",
    "                         get_datetime,\n",
    "                         order_target_percent,\n",
    "                         pipeline_output,\n",
    "                         record, schedule_function,\n",
    "                         get_open_orders,\n",
    "                         calendars,\n",
    "                         set_commission, \n",
    "                         set_slippage)\n",
    "from zipline.finance import commission, slippage\n",
    "from zipline.pipeline import Pipeline, CustomFactor\n",
    "from zipline.pipeline.factors import Returns, AverageDollarVolume\n",
    "\n",
    "from pypfopt.efficient_frontier import EfficientFrontier\n",
    "from pypfopt import risk_models, objective_functions\n",
    "from pypfopt import expected_returns\n",
    "from pypfopt.exceptions import OptimizationError\n",
    "\n",
    "from pyfolio.utils import extract_rets_pos_txn_from_zipline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:52.144743Z",
     "start_time": "2021-04-15T19:49:52.142874Z"
    }
   },
   "outputs": [],
   "source": [
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Logging Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:52.159076Z",
     "start_time": "2021-04-15T19:49:52.145590Z"
    }
   },
   "outputs": [],
   "source": [
    "# setup stdout logging\n",
    "format_string = '[{record.time: %H:%M:%S.%f}]: {record.level_name}: {record.message}'\n",
    "zipline_logging = NestedSetup([NullHandler(level=DEBUG),\n",
    "                               StreamHandler(sys.stdout, format_string=format_string, level=INFO),\n",
    "                               StreamHandler(sys.stdout, format_string=format_string, level=WARNING),\n",
    "                               StreamHandler(sys.stderr, level=ERROR)])\n",
    "zipline_logging.push_application()\n",
    "log = Logger('Algorithm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Algo Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:52.166662Z",
     "start_time": "2021-04-15T19:49:52.159964Z"
    }
   },
   "outputs": [],
   "source": [
    "# Settings\n",
    "MONTH = 21\n",
    "YEAR = 12 * MONTH\n",
    "N_LONGS = 50\n",
    "N_SHORTS = 50\n",
    "MIN_POS = 5\n",
    "VOL_SCREEN = 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:52.174450Z",
     "start_time": "2021-04-15T19:49:52.167433Z"
    }
   },
   "outputs": [],
   "source": [
    "start = pd.Timestamp('2013-01-01', tz=UTC)\n",
    "end = pd.Timestamp('2017-01-01', tz=UTC)\n",
    "capital_base = 1e7"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mean Reversion Factor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:52.182556Z",
     "start_time": "2021-04-15T19:49:52.175707Z"
    }
   },
   "outputs": [],
   "source": [
    "class MeanReversion(CustomFactor):\n",
    "    \"\"\"Compute ratio of latest monthly return to 12m average,\n",
    "       normalized by std dev of monthly returns\"\"\"\n",
    "    inputs = [Returns(window_length=MONTH)]\n",
    "    window_length = YEAR\n",
    "\n",
    "    def compute(self, today, assets, out, monthly_returns):\n",
    "        df = pd.DataFrame(monthly_returns)\n",
    "        factor = df.iloc[-1].sub(df.mean()).div(df.std())\n",
    "        out[:] = factor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Pipeline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Pipeline created by the `compute_factors()` method returns a table with a long and a short column for the 25 stocks with the largest negative and positive deviations of their last monthly return from its annual average, normalized by the standard deviation. It also limited the universe to the 500 stocks with the highest average trading volume over the last 30 trading days. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:52.193519Z",
     "start_time": "2021-04-15T19:49:52.183446Z"
    }
   },
   "outputs": [],
   "source": [
    "def compute_factors():\n",
    "    \"\"\"Create factor pipeline incl. mean reversion,\n",
    "        filtered by 30d Dollar Volume; capture factor ranks\"\"\"\n",
    "    mean_reversion = MeanReversion()\n",
    "    dollar_volume = AverageDollarVolume(window_length=30)\n",
    "    return Pipeline(columns={'longs'  : mean_reversion.bottom(N_LONGS),\n",
    "                             'shorts' : mean_reversion.top(N_SHORTS),\n",
    "                             'ranking': mean_reversion.rank(ascending=False)},\n",
    "                    screen=dollar_volume.top(VOL_SCREEN))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`Before_trading_start()` ensures the daily execution of the pipeline and the recording of the results, including the current prices."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:52.201905Z",
     "start_time": "2021-04-15T19:49:52.194448Z"
    }
   },
   "outputs": [],
   "source": [
    "def before_trading_start(context, data):\n",
    "    \"\"\"Run factor pipeline\"\"\"\n",
    "    context.factor_data = pipeline_output('factor_pipeline')\n",
    "    record(factor_data=context.factor_data.ranking)\n",
    "    assets = context.factor_data.index\n",
    "    record(prices=data.current(assets, 'price'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set up Rebalancing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The new `rebalance()` method submits trade orders to the `exec_trades()` method for the assets flagged for long and short positions by the pipeline with equal positive and negative weights. \n",
    "\n",
    "It also divests any current holdings that are no longer included in the factor signals:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:52.223739Z",
     "start_time": "2021-04-15T19:49:52.202994Z"
    }
   },
   "outputs": [],
   "source": [
    "def exec_trades(data, positions):\n",
    "    \"\"\"Place orders for assets using target portfolio percentage\"\"\"\n",
    "    for asset, target_percent in positions.items():\n",
    "        if data.can_trade(asset) and not get_open_orders(asset):\n",
    "            order_target_percent(asset, target_percent)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:52.242961Z",
     "start_time": "2021-04-15T19:49:52.224954Z"
    }
   },
   "outputs": [],
   "source": [
    "def rebalance(context, data):\n",
    "    \"\"\"Compute long, short and obsolete holdings; place orders\"\"\"\n",
    "\n",
    "    factor_data = context.factor_data\n",
    "    assets = factor_data.index\n",
    "\n",
    "    longs = assets[factor_data.longs]\n",
    "    shorts = assets[factor_data.shorts]\n",
    "    \n",
    "    divest = context.portfolio.positions.keys() - longs.union(shorts)\n",
    "    exec_trades(data, positions={asset: 0 for asset in divest})\n",
    "    log.info('{} | {:11,.0f}'.format(get_datetime().date(), \n",
    "                                   context.portfolio.portfolio_value))\n",
    "\n",
    "    # get price history\n",
    "    prices = data.history(assets, fields='price',\n",
    "                          bar_count=252+1, # for 1 year of returns \n",
    "                          frequency='1d')\n",
    "    \n",
    "    # get optimal weights if sufficient candidates\n",
    "    if len(longs) > MIN_POS and len(shorts) > MIN_POS:\n",
    "        try:\n",
    "            long_weights = optimize_weights(prices.loc[:, longs])\n",
    "            short_weights = optimize_weights(prices.loc[:, shorts], short=True)\n",
    "            \n",
    "            exec_trades(data, positions=long_weights)\n",
    "            exec_trades(data, positions=short_weights)\n",
    "        except Exception as e:\n",
    "            log.warn('{} {}'.format(get_datetime().date(), e))\n",
    "    # exit remaining positions\n",
    "    divest_pf = {asset: 0 for asset in context.portfolio.positions.keys()}\n",
    "    exec_trades(data, positions=divest_pf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimize Portfolio Weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:52.253389Z",
     "start_time": "2021-04-15T19:49:52.243903Z"
    }
   },
   "outputs": [],
   "source": [
    "def optimize_weights(prices, short=False):\n",
    "\n",
    "    returns = expected_returns.mean_historical_return(\n",
    "        prices=prices, frequency=252)\n",
    "    cov = risk_models.sample_cov(prices=prices, frequency=252)\n",
    "\n",
    "    # get weights that maximize the Sharpe ratio\n",
    "    ef = EfficientFrontier(expected_returns=returns,\n",
    "                           cov_matrix=cov,\n",
    "                           weight_bounds=(0, 1),\n",
    "                           solver='SCS')\n",
    "    ef.max_sharpe()\n",
    "    if short:\n",
    "        return {asset: -weight for asset, weight in ef.clean_weights().items()}\n",
    "    else:\n",
    "        return ef.clean_weights()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize Backtest"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `rebalance()` method runs according to `date_rules` and `time_rules` set by the `schedule_function()` utility at the beginning of the week, right after `market_open` as stipulated by the built-in `US_EQUITIES` calendar (see docs for details on rules). \n",
    "\n",
    "You can also specify a trade commission both in relative terms and as a minimum amount. There is also an option to define slippage, which is the cost of an adverse change in price between trade decision and execution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:49:52.261143Z",
     "start_time": "2021-04-15T19:49:52.254205Z"
    }
   },
   "outputs": [],
   "source": [
    "def initialize(context):\n",
    "    \"\"\"Setup: register pipeline, schedule rebalancing,\n",
    "        and set trading params\"\"\"\n",
    "    attach_pipeline(compute_factors(), 'factor_pipeline')\n",
    "    schedule_function(rebalance,\n",
    "                      date_rules.week_start(),\n",
    "                      time_rules.market_open(),\n",
    "                      calendar=calendars.US_EQUITIES)\n",
    "\n",
    "    set_commission(us_equities=commission.PerShare(cost=0.00075, min_trade_cost=.01))\n",
    "    set_slippage(us_equities=slippage.VolumeShareSlippage(volume_limit=0.0025, price_impact=0.01))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run Algorithm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The algorithm executes upon calling the `run_algorithm()` function and returns the backtest performance `DataFrame`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:59:47.818235Z",
     "start_time": "2021-04-15T19:49:52.262074Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 19:49:55.661120]: INFO: 2013-01-07 |  10,000,000\n",
      "[ 19:50:02.961404]: INFO: 2013-01-14 |   9,922,439\n",
      "[ 19:50:06.101723]: INFO: 2013-01-22 |   9,913,612\n",
      "[ 19:50:09.110052]: INFO: 2013-01-28 |   9,968,656\n",
      "[ 19:50:12.293743]: INFO: 2013-02-04 |  10,079,391\n",
      "[ 19:50:15.636407]: INFO: 2013-02-11 |  10,103,535\n",
      "[ 19:50:19.025936]: INFO: 2013-02-19 |   9,771,077\n",
      "[ 19:50:22.454159]: INFO: 2013-02-25 |  10,061,824\n",
      "[ 19:50:26.025560]: INFO: 2013-03-04 |  10,162,312\n",
      "[ 19:50:29.300896]: INFO: 2013-03-11 |   9,563,302\n",
      "[ 19:50:33.294339]: INFO: 2013-03-18 |   9,311,865\n",
      "[ 19:50:36.611748]: INFO: 2013-03-25 |   9,064,119\n",
      "[ 19:50:39.810862]: INFO: 2013-04-01 |   8,643,936\n",
      "[ 19:50:43.357770]: INFO: 2013-04-08 |   8,721,979\n",
      "[ 19:50:47.126182]: INFO: 2013-04-15 |   8,552,107\n",
      "[ 19:50:51.070580]: INFO: 2013-04-22 |   8,186,845\n",
      "[ 19:50:55.027566]: INFO: 2013-04-29 |   9,080,169\n",
      "[ 19:50:58.655614]: INFO: 2013-05-06 |   8,277,424\n",
      "[ 19:51:02.617136]: INFO: 2013-05-13 |   8,018,122\n",
      "[ 19:51:06.524561]: INFO: after split: asset: Equity(189 [AOS]), amount: 62678, cost_basis: 36.54, last_sale_price: 79.9\n",
      "[ 19:51:06.524914]: INFO: returning cash: 0.0\n",
      "[ 19:51:07.067627]: INFO: 2013-05-20 |   7,805,480\n",
      "[ 19:51:11.239217]: INFO: 2013-05-28 |   6,806,488\n",
      "[ 19:51:15.113238]: INFO: 2013-06-03 |   7,034,540\n",
      "[ 19:51:19.219741]: INFO: 2013-06-10 |   7,315,434\n",
      "[ 19:51:23.416837]: INFO: 2013-06-17 |   7,620,513\n",
      "[ 19:51:27.623110]: INFO: 2013-06-24 |   6,403,342\n",
      "[ 19:51:31.930314]: INFO: 2013-07-01 |   5,958,489\n",
      "[ 19:51:36.417751]: INFO: 2013-07-08 |   5,427,714\n",
      "[ 19:51:42.579167]: INFO: 2013-07-15 |   5,956,660\n",
      "[ 19:51:47.402413]: INFO: 2013-07-22 |   6,237,875\n",
      "[ 19:51:51.883184]: INFO: 2013-07-29 |   6,059,791\n",
      "[ 19:51:55.834086]: INFO: 2013-08-05 |   6,454,247\n",
      "[ 19:52:00.032541]: INFO: 2013-08-12 |   6,968,293\n",
      "[ 19:52:04.023979]: INFO: 2013-08-19 |   5,543,339\n",
      "[ 19:52:07.863710]: INFO: 2013-08-26 |   6,377,059\n",
      "[ 19:52:12.136057]: INFO: 2013-09-03 |   6,426,491\n",
      "[ 19:52:15.910429]: INFO: 2013-09-09 |   7,392,591\n",
      "[ 19:52:20.035565]: INFO: 2013-09-16 |   7,315,055\n",
      "[ 19:52:25.921373]: INFO: 2013-09-23 |   7,812,821\n",
      "[ 19:52:30.754606]: INFO: 2013-09-30 |   6,988,949\n",
      "[ 19:52:34.801378]: INFO: 2013-10-07 |   6,107,561\n",
      "[ 19:52:38.671079]: INFO: 2013-10-14 |   6,255,426\n",
      "[ 19:52:42.044195]: INFO: 2013-10-21 |   7,069,346\n",
      "[ 19:52:45.102026]: INFO: 2013-10-28 |   7,059,135\n",
      "[ 19:52:48.383666]: INFO: 2013-11-04 |   7,314,434\n",
      "[ 19:52:51.121046]: INFO: 2013-11-11 |   6,430,076\n",
      "[ 19:52:54.211109]: INFO: 2013-11-18 |   6,851,219\n",
      "[ 19:52:57.926595]: INFO: 2013-11-25 |   6,795,541\n",
      "[ 19:53:00.937046]: INFO: 2013-12-02 |   7,138,853\n",
      "[ 19:53:03.877547]: INFO: 2013-12-09 |   6,881,797\n",
      "[ 19:53:07.190402]: INFO: 2013-12-16 |   6,543,537\n",
      "[ 19:53:10.698781]: INFO: 2013-12-23 |   7,439,189\n",
      "[ 19:53:14.008429]: INFO: 2013-12-30 |   7,441,863\n",
      "[ 19:53:17.436756]: INFO: 2014-01-06 |   7,369,341\n",
      "[ 19:53:20.990705]: INFO: 2014-01-13 |   7,079,246\n",
      "[ 19:53:26.130491]: INFO: 2014-01-21 |   6,746,705\n",
      "[ 19:53:29.472657]: INFO: 2014-01-27 |   6,519,510\n",
      "[ 19:53:32.492814]: INFO: 2014-02-03 |   6,583,762\n",
      "[ 19:53:35.400119]: INFO: 2014-02-10 |   7,061,039\n",
      "[ 19:53:38.446365]: INFO: 2014-02-18 |   7,884,748\n",
      "[ 19:53:41.424621]: INFO: 2014-02-24 |   7,668,098\n",
      "[ 19:53:43.864251]: INFO: 2014-03-03 |   8,758,089\n",
      "[ 19:53:46.280781]: INFO: 2014-03-10 |   8,835,178\n",
      "[ 19:53:48.517062]: INFO: 2014-03-17 |   8,778,877\n",
      "[ 19:53:51.167632]: INFO: 2014-03-24 |   8,370,815\n",
      "[ 19:53:54.435749]: INFO: 2014-03-31 |   8,441,825\n",
      "[ 19:53:57.105086]: INFO: 2014-04-07 |   7,674,570\n",
      "[ 19:54:00.153841]: INFO: 2014-04-14 |   7,078,187\n",
      "[ 19:54:02.991366]: INFO: 2014-04-21 |   7,688,825\n",
      "[ 19:54:05.843967]: INFO: 2014-04-28 |   7,589,755\n",
      "[ 19:54:08.687119]: INFO: 2014-05-05 |   7,968,224\n",
      "[ 19:54:11.282235]: INFO: 2014-05-12 |   8,181,812\n",
      "[ 19:54:13.907430]: INFO: 2014-05-19 |   7,101,661\n",
      "[ 19:54:16.504037]: INFO: 2014-05-27 |   7,566,057\n",
      "[ 19:54:19.270873]: INFO: 2014-06-02 |   7,396,299\n",
      "[ 19:54:21.679662]: INFO: 2014-06-09 |   7,720,697\n",
      "[ 19:54:24.253035]: INFO: 2014-06-16 |   7,469,853\n",
      "[ 19:54:27.093635]: INFO: 2014-06-23 |   7,480,065\n",
      "[ 19:54:29.915811]: INFO: 2014-06-30 |   7,816,351\n",
      "[ 19:54:32.576913]: INFO: 2014-07-07 |   8,052,165\n",
      "[ 19:54:35.525930]: INFO: 2014-07-14 |   7,970,295\n",
      "[ 19:54:40.430470]: INFO: 2014-07-21 |   8,376,080\n",
      "[ 19:54:43.443027]: INFO: 2014-07-28 |   8,244,746\n",
      "[ 19:54:46.840045]: INFO: 2014-08-04 |   8,341,610\n",
      "[ 19:54:49.967235]: INFO: 2014-08-11 |   8,860,966\n",
      "[ 19:54:53.727961]: INFO: 2014-08-18 |   9,366,271\n",
      "[ 19:54:56.397549]: INFO: 2014-08-25 |   9,410,676\n",
      "[ 19:54:58.717063]: INFO: 2014-09-02 |   9,513,942\n",
      "[ 19:55:00.885053]: INFO: 2014-09-08 |   8,991,093\n",
      "[ 19:55:03.514441]: INFO: 2014-09-15 |   9,269,792\n",
      "[ 19:55:06.189510]: INFO: 2014-09-22 |   9,231,904\n",
      "[ 19:55:08.703271]: INFO: 2014-09-29 |   8,066,988\n",
      "[ 19:55:12.292468]: INFO: 2014-10-06 |   6,258,677\n",
      "[ 19:55:15.435277]: INFO: 2014-10-13 |   4,441,940\n",
      "[ 19:55:18.151838]: INFO: 2014-10-20 |   5,541,794\n",
      "[ 19:55:20.750519]: INFO: 2014-10-27 |   6,187,174\n",
      "[ 19:55:23.280320]: INFO: 2014-11-03 |   7,400,147\n",
      "[ 19:55:25.680151]: INFO: 2014-11-10 |   7,287,218\n",
      "[ 19:55:28.012422]: INFO: 2014-11-17 |   7,684,538\n",
      "[ 19:55:30.227017]: INFO: 2014-11-24 |   8,245,927\n",
      "[ 19:55:32.100307]: INFO: 2014-12-01 |   7,381,184\n",
      "[ 19:55:34.806464]: INFO: 2014-12-08 |   7,766,157\n",
      "[ 19:55:36.782542]: INFO: 2014-12-15 |   7,681,728\n",
      "[ 19:55:38.733397]: INFO: 2014-12-22 |   8,411,340\n",
      "[ 19:55:40.649713]: INFO: 2014-12-29 |   8,317,332\n",
      "[ 19:55:42.647684]: INFO: 2015-01-05 |   7,382,470\n",
      "[ 19:55:45.148846]: INFO: 2015-01-12 |   7,575,066\n",
      "[ 19:55:49.376307]: INFO: 2015-01-20 |   7,916,220\n",
      "[ 19:55:51.376484]: INFO: 2015-01-26 |   8,261,115\n",
      "[ 19:55:54.002615]: INFO: 2015-02-02 |   7,365,550\n",
      "[ 19:55:56.778925]: INFO: 2015-02-09 |   7,536,988\n",
      "[ 19:55:58.952506]: INFO: 2015-02-17 |   7,765,648\n",
      "[ 19:56:00.905802]: INFO: 2015-02-23 |   7,499,103\n",
      "[ 19:56:03.030776]: INFO: 2015-03-02 |   6,865,120\n",
      "[ 19:56:05.550942]: INFO: 2015-03-09 |   6,105,947\n",
      "[ 19:56:08.617395]: INFO: 2015-03-16 |   5,998,193\n",
      "[ 19:56:12.668770]: INFO: 2015-03-23 |   6,102,339\n",
      "[ 19:56:16.999381]: INFO: 2015-03-30 |   5,852,169\n",
      "[ 19:56:20.316627]: INFO: 2015-04-06 |   5,839,392\n",
      "[ 19:56:24.030473]: INFO: 2015-04-13 |   6,002,854\n",
      "[ 19:56:25.876552]: INFO: 2015-04-20 |   5,858,690\n",
      "[ 19:56:27.481938]: INFO: 2015-04-27 |   5,578,378\n",
      "[ 19:56:29.033304]: INFO: 2015-05-04 |   5,727,009\n",
      "[ 19:56:30.560601]: INFO: 2015-05-11 |   5,876,390\n",
      "[ 19:56:32.108828]: INFO: 2015-05-18 |   5,926,198\n",
      "[ 19:56:33.658631]: INFO: 2015-05-26 |   5,870,281\n",
      "[ 19:56:34.898588]: INFO: 2015-06-01 |   6,357,525\n",
      "[ 19:56:36.288508]: INFO: 2015-06-08 |   6,563,835\n",
      "[ 19:56:37.974627]: INFO: 2015-06-15 |   6,356,822\n",
      "[ 19:56:39.385081]: INFO: 2015-06-22 |   7,143,691\n",
      "[ 19:56:40.777906]: INFO: 2015-06-29 |   6,302,243\n",
      "[ 19:56:41.858567]: INFO: 2015-07-06 |   6,485,967\n",
      "[ 19:56:43.265941]: INFO: 2015-07-13 |   6,928,867\n",
      "[ 19:56:45.021742]: INFO: 2015-07-20 |   7,051,650\n",
      "[ 19:56:48.614537]: INFO: 2015-07-27 |   7,044,274\n",
      "[ 19:56:50.681199]: INFO: 2015-08-03 |   7,323,573\n",
      "[ 19:56:52.769434]: INFO: 2015-08-10 |   7,568,364\n",
      "[ 19:56:55.288387]: INFO: 2015-08-17 |   7,658,959\n",
      "[ 19:56:57.335410]: INFO: 2015-08-24 |   5,970,305\n",
      "[ 19:56:59.408318]: INFO: 2015-08-31 |   6,637,912\n",
      "[ 19:57:01.459935]: INFO: 2015-09-08 |   7,096,752\n",
      "[ 19:57:03.360521]: INFO: 2015-09-14 |   7,078,391\n",
      "[ 19:57:05.419445]: INFO: 2015-09-21 |   7,109,001\n",
      "[ 19:57:07.657716]: INFO: 2015-09-28 |   6,892,548\n",
      "[ 19:57:09.713700]: INFO: 2015-10-05 |   7,432,601\n",
      "[ 19:57:11.782813]: INFO: 2015-10-12 |   8,110,083\n",
      "[ 19:57:14.358990]: INFO: 2015-10-19 |   8,164,760\n",
      "[ 19:57:16.437731]: INFO: 2015-10-26 |   8,446,339\n",
      "[ 19:57:18.547980]: INFO: 2015-11-02 |   9,391,155\n",
      "[ 19:57:20.661324]: INFO: 2015-11-09 |   8,829,317\n",
      "[ 19:57:22.917628]: INFO: 2015-11-16 |   8,434,693\n",
      "[ 19:57:24.462049]: INFO: after split: asset: Equity(406 [BOFI]), amount: 32844, cost_basis: 22.22, last_sale_price: 83.29\n",
      "[ 19:57:24.462437]: INFO: returning cash: 0.0\n",
      "[ 19:57:25.152353]: INFO: 2015-11-23 |   9,203,580\n",
      "[ 19:57:27.240601]: INFO: 2015-11-30 |   9,555,485\n",
      "[ 19:57:29.486857]: INFO: 2015-12-07 |   9,152,902\n",
      "[ 19:57:31.896704]: INFO: 2015-12-14 |   8,799,672\n",
      "[ 19:57:34.736330]: INFO: 2015-12-21 |   9,181,258\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 19:57:36.855101]: INFO: 2015-12-28 |   9,167,269\n",
      "[ 19:57:38.942283]: INFO: 2016-01-04 |   8,890,359\n",
      "[ 19:57:41.091240]: INFO: 2016-01-11 |   7,867,946\n",
      "[ 19:57:43.371758]: INFO: 2016-01-19 |   7,562,504\n",
      "[ 19:57:47.218014]: INFO: 2016-01-25 |   7,257,377\n",
      "[ 19:57:48.692725]: WARNING: 2016-01-25 ('Please check your objectives/constraints or use a different solver.', 'Solver status: infeasible')\n",
      "[ 19:57:49.570712]: INFO: 2016-02-01 |   7,359,763\n",
      "[ 19:57:51.939493]: INFO: 2016-02-08 |   4,641,970\n",
      "[ 19:57:54.339881]: INFO: 2016-02-16 |   5,248,988\n",
      "[ 19:57:56.978133]: INFO: 2016-02-22 |   7,136,137\n",
      "[ 19:57:59.381385]: INFO: 2016-02-29 |   6,489,040\n",
      "[ 19:58:01.786348]: INFO: 2016-03-07 |   7,469,882\n",
      "[ 19:58:04.176099]: INFO: 2016-03-14 |   8,954,946\n",
      "[ 19:58:06.530112]: INFO: 2016-03-21 |   9,471,995\n",
      "[ 19:58:08.022997]: WARNING: 2016-03-21 ('Please check your objectives/constraints or use a different solver.', 'Solver status: infeasible')\n",
      "[ 19:58:08.684584]: INFO: 2016-03-28 |   9,328,094\n",
      "[ 19:58:11.034063]: INFO: 2016-04-04 |   9,743,417\n",
      "[ 19:58:13.371768]: INFO: 2016-04-11 |  10,087,318\n",
      "[ 19:58:15.804977]: INFO: 2016-04-18 |  10,745,639\n",
      "[ 19:58:18.945575]: INFO: 2016-04-25 |  10,806,461\n",
      "[ 19:58:21.691592]: INFO: 2016-05-02 |  11,879,697\n",
      "[ 19:58:24.474339]: INFO: 2016-05-09 |  12,908,341\n",
      "[ 19:58:27.379225]: INFO: 2016-05-16 |  12,124,789\n",
      "[ 19:58:30.108167]: INFO: 2016-05-23 |  10,192,441\n",
      "[ 19:58:31.905902]: WARNING: 2016-05-23 ('Please check your objectives/constraints or use a different solver.', 'Solver status: infeasible')\n",
      "[ 19:58:32.783601]: INFO: 2016-05-31 |  11,063,885\n",
      "[ 19:58:35.369845]: INFO: 2016-06-06 |  11,275,450\n",
      "[ 19:58:38.090709]: INFO: 2016-06-13 |  11,089,536\n",
      "[ 19:58:40.802084]: INFO: 2016-06-20 |  11,424,829\n",
      "[ 19:58:43.010284]: WARNING: 2016-06-20 ('Please check your objectives/constraints or use a different solver.', 'Solver status: infeasible')\n",
      "[ 19:58:43.850453]: INFO: 2016-06-27 |  10,402,124\n",
      "[ 19:58:46.382454]: INFO: 2016-07-05 |  10,926,853\n",
      "[ 19:58:48.428655]: INFO: 2016-07-11 |  11,208,081\n",
      "[ 19:58:50.795378]: INFO: 2016-07-18 |  10,898,410\n",
      "[ 19:58:57.111404]: INFO: 2016-07-25 |  10,671,246\n",
      "[ 19:58:59.400699]: INFO: 2016-08-01 |  11,244,511\n",
      "[ 19:59:01.682477]: INFO: 2016-08-08 |  10,974,343\n",
      "[ 19:59:03.996200]: INFO: 2016-08-15 |  10,499,160\n",
      "[ 19:59:06.331738]: INFO: 2016-08-22 |  10,103,598\n",
      "[ 19:59:08.921478]: INFO: 2016-08-29 |   9,995,782\n",
      "[ 19:59:11.135088]: INFO: 2016-09-06 |   9,708,339\n",
      "[ 19:59:13.118201]: INFO: 2016-09-12 |  10,138,554\n",
      "[ 19:59:15.280128]: INFO: 2016-09-19 |   9,888,820\n",
      "[ 19:59:17.487149]: INFO: 2016-09-26 |  10,384,830\n",
      "[ 19:59:19.692916]: INFO: 2016-10-03 |   9,870,885\n",
      "[ 19:59:21.863634]: INFO: 2016-10-10 |   9,007,649\n",
      "[ 19:59:24.064888]: INFO: 2016-10-17 |   8,642,711\n",
      "[ 19:59:26.447127]: INFO: 2016-10-24 |   8,723,289\n",
      "[ 19:59:29.274611]: INFO: 2016-10-31 |   9,861,873\n",
      "[ 19:59:31.524188]: INFO: 2016-11-07 |  10,512,150\n",
      "[ 19:59:33.752999]: INFO: 2016-11-14 |   9,782,800\n",
      "[ 19:59:36.172179]: INFO: 2016-11-21 |   7,302,885\n",
      "[ 19:59:38.165779]: INFO: 2016-11-28 |   8,179,329\n",
      "[ 19:59:40.247054]: INFO: 2016-12-05 |   6,719,502\n",
      "[ 19:59:42.224743]: INFO: 2016-12-12 |   6,428,943\n",
      "[ 19:59:43.996133]: INFO: 2016-12-19 |   4,324,427\n",
      "[ 19:59:45.862659]: INFO: 2016-12-27 |   3,500,602\n",
      "[ 19:59:47.796972]: INFO: Simulated 1008 trading days\n",
      "first open: 2013-01-02 14:31:00+00:00\n",
      "last close: 2016-12-30 21:00:00+00:00\n"
     ]
    }
   ],
   "source": [
    "backtest = run_algorithm(start=start,\n",
    "                         end=end,\n",
    "                         initialize=initialize,\n",
    "                         before_trading_start=before_trading_start,\n",
    "                         bundle='quandl',\n",
    "                         capital_base=capital_base)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract pyfolio Inputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `extract_rets_pos_txn_from_zipline` utility provided by `pyfolio` extracts the data used to compute performance metrics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:59:48.896101Z",
     "start_time": "2021-04-15T19:59:47.819858Z"
    }
   },
   "outputs": [],
   "source": [
    "returns, positions, transactions = extract_rets_pos_txn_from_zipline(backtest)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Persist Results for use with `pyfolio`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:59:48.930171Z",
     "start_time": "2021-04-15T19:59:48.897706Z"
    }
   },
   "outputs": [],
   "source": [
    "with pd.HDFStore('backtests.h5') as store:\n",
    "    store.put('returns/pf_opt', returns)\n",
    "    store.put('transactions/pf_opt', transactions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:59:49.064963Z",
     "start_time": "2021-04-15T19:59:48.931263Z"
    }
   },
   "outputs": [],
   "source": [
    "with pd.HDFStore('backtests.h5') as store:\n",
    "    returns_pf = store['returns/pf_opt']\n",
    "    tx_pf = store['transactions/pf_opt']\n",
    "    returns_ew = store['returns/equal_weight']\n",
    "    tx_ew = store['transactions/equal_weight']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:59:49.417803Z",
     "start_time": "2021-04-15T19:59:49.066143Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes= plt.subplots(nrows=2, figsize=(14,6))\n",
    "returns.add(1).cumprod().sub(1).plot(ax=axes[0], title='Cumulative Returns')\n",
    "transactions.groupby(transactions.dt.dt.day).txn_dollars.sum().cumsum().plot(ax=axes[1], title='Cumulative Transactions')\n",
    "sns.despine()\n",
    "fig.tight_layout();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:59:50.077791Z",
     "start_time": "2021-04-15T19:59:49.418674Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(16, 8), sharey='col')\n",
    "returns_ew.add(1).cumprod().sub(1).plot(ax=axes[0][0],\n",
    "                                        title='Cumulative Returns - Equal Weight')\n",
    "returns_pf.add(1).cumprod().sub(1).plot(ax=axes[1][0],\n",
    "                                        title='Cumulative Returns - Mean-Variance Optimization')\n",
    "tx_ew.groupby(tx_ew.dt.dt.day).txn_dollars.sum().cumsum().plot(ax=axes[0][1],\n",
    "                                                               title='Cumulative Transactions - Equal Weight')\n",
    "tx_pf.groupby(tx_pf.dt.dt.day).txn_dollars.sum().cumsum().plot(ax=axes[1][1],\n",
    "                                                               title='Cumulative Transactions - Mean-Variance Optimization')\n",
    "fig.suptitle('Equal Weight vs Mean-Variance Optimization', fontsize=16)\n",
    "sns.despine()\n",
    "fig.tight_layout()\n",
    "fig.subplots_adjust(top=.9)"
   ]
  },
  {
   "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"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": true,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "252.628px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}