FinRL_compare_eRL_RLlib_stablebaseline.ipynb

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      "name": "FinRL_compare_eRL_RLlib_stablebaseline.ipynb",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/AI4Finance-LLC/FinRL/blob/master/FinRL_compare_eRL_RLlib_stablebaseline.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "skemZ68ZZMdx"
      },
      "source": [
        "# FinRL: Compare ElegantRL, RLlib, and Stablebaselines3"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c3XX4MO9UxNx"
      },
      "source": [
        "## Install DRL libraries: FinRL, ElegantRL, RLlib"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VtxFMjnLDy3Q",
        "outputId": "4e5001ea-58a9-4977-af3e-2ae2ed9a6ced"
      },
      "source": [
        "## install elegantrl library\n",
        "!pip install git+https://github.com/AI4Finance-LLC/ElegantRL.git\n",
        "## install rllib/ray library\n",
        "!pip install ray[default]\n",
        "## install finrl library\n",
        "!pip install git+https://github.com/AI4Finance-LLC/FinRL-Library.git"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
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            "\u001b[?25hBuilding wheels for collected packages: finrl, pyfolio, empyrical, yfinance\n",
            "  Building wheel for finrl (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for finrl: filename=finrl-0.3.0-py3-none-any.whl size=66435 sha256=ef616cf22b1637160bfa5bddafa2d49b77ea9402571c2d6c8c18455e29200f2e\n",
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            "  Created wheel for empyrical: filename=empyrical-0.5.5-py3-none-any.whl size=39777 sha256=1b5cfc6df1731a9c34beafb9282357c1122b3248f8f8bb87a56fd140bddf7d1c\n",
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            "  Created wheel for yfinance: filename=yfinance-0.1.63-py2.py3-none-any.whl size=23918 sha256=1496434ae79bc544c66db909d80e7b13bdeadcc328253cc1d7250d7870775c87\n",
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            "Successfully built finrl pyfolio empyrical yfinance\n",
            "Installing collected packages: lxml, stable-baselines3, int-date, empyrical, yfinance, stockstats, pyfolio, finrl\n",
            "  Attempting uninstall: lxml\n",
            "    Found existing installation: lxml 4.2.6\n",
            "    Uninstalling lxml-4.2.6:\n",
            "      Successfully uninstalled lxml-4.2.6\n",
            "Successfully installed empyrical-0.5.5 finrl-0.3.0 int-date-0.1.8 lxml-4.6.3 pyfolio-0.9.2+75.g4b901f6 stable-baselines3-1.1.0 stockstats-0.3.2 yfinance-0.1.63\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cMCwv41eVVDJ"
      },
      "source": [
        "## Install additional packages"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P446vin0EGSC",
        "outputId": "4b79eccb-7b05-48c1-aa78-44252caee6b3"
      },
      "source": [
        "!pip install trading_calendars\n",
        "!pip install alpaca_trade_api\n",
        "!pip install ccxt\n",
        "!pip install jqdatasdk\n",
        "!pip install wrds\n",
        "\n",
        "!pip install lz4\n",
        "!pip install ray[tune]\n",
        "!pip install tensorboardX\n",
        "!pip install gputil"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting trading_calendars\n",
            "  Downloading trading_calendars-2.1.1.tar.gz (108 kB)\n",
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            "Building wheels for collected packages: trading-calendars\n",
            "  Building wheel for trading-calendars (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for trading-calendars: filename=trading_calendars-2.1.1-py3-none-any.whl size=140937 sha256=8199c413ee7fdf4cf47e6df0a2a16155f93d31a9259ec10735220e27f612395a\n",
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            "Successfully built trading-calendars\n",
            "Installing collected packages: trading-calendars\n",
            "Successfully installed trading-calendars-2.1.1\n",
            "Collecting alpaca_trade_api\n",
            "  Downloading alpaca_trade_api-1.2.3-py3-none-any.whl (40 kB)\n",
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            "Installing collected packages: websockets, websocket-client, alpaca-trade-api\n",
            "Successfully installed alpaca-trade-api-1.2.3 websocket-client-1.2.1 websockets-9.1\n",
            "Collecting ccxt\n",
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            "Installing collected packages: pycares, cryptography, aiodns, ccxt\n",
            "Successfully installed aiodns-3.0.0 ccxt-1.55.9 cryptography-3.4.7 pycares-4.0.0\n",
            "Collecting jqdatasdk\n",
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            "Building wheels for collected packages: thriftpy2\n",
            "  Building wheel for thriftpy2 (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for thriftpy2: filename=thriftpy2-0.4.14-cp37-cp37m-linux_x86_64.whl size=940432 sha256=27dc2d5afa92066139e4e3d681c41e28444db7272731a709f9e79f3dfe613502\n",
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            "Successfully installed jqdatasdk-1.8.10 ply-3.11 pymysql-1.0.2 thriftpy2-0.4.14\n",
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            "Installing collected packages: psycopg2-binary, mock, wrds\n",
            "Successfully installed mock-4.0.3 psycopg2-binary-2.9.1 wrds-3.0.10\n",
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            "  Downloading lz4-3.1.3-cp37-cp37m-manylinux2010_x86_64.whl (1.8 MB)\n",
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            "Collecting tensorboardX>=1.9\n",
            "  Downloading tensorboardX-2.4-py2.py3-none-any.whl (124 kB)\n",
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            "Installing collected packages: tensorboardX\n",
            "Successfully installed tensorboardX-2.4\n",
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            "Collecting gputil\n",
            "  Downloading GPUtil-1.4.0.tar.gz (5.5 kB)\n",
            "Building wheels for collected packages: gputil\n",
            "  Building wheel for gputil (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for gputil: filename=GPUtil-1.4.0-py3-none-any.whl size=7411 sha256=f5b21702659a674a03662a6e38e2728e6aac5e329eb1cdbcc68656e650413f1d\n",
            "  Stored in directory: /root/.cache/pip/wheels/6e/f8/83/534c52482d6da64622ddbf72cd93c35d2ef2881b78fd08ff0c\n",
            "Successfully built gputil\n",
            "Installing collected packages: gputil\n",
            "Successfully installed gputil-1.4.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HLZjsQH-VcOU"
      },
      "source": [
        "## Import packages"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N7bN2cdIDugz",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5124c5d8-918e-4ce0-9722-02b464634fcc"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "\n",
        "# matplotlib.use('Agg')\n",
        "import datetime\n",
        "\n",
        "from elegantrl.agent import *\n",
        "from elegantrl.run import *\n",
        "import torch \n",
        "import ray\n",
        "from finrl.apps import config\n",
        "from finrl.neo_finrl.data_processor import DataProcessor\n",
        "from finrl.plot import backtest_stats, backtest_plot, get_daily_return, get_baseline\n",
        "\n"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pyfolio/pos.py:27: UserWarning: Module \"zipline.assets\" not found; multipliers will not be applied to position notionals.\n",
            "  'Module \"zipline.assets\" not found; multipliers will not be applied'\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I0OVWiVfXRsi"
      },
      "source": [
        "## Train"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "knHkXNilDug5"
      },
      "source": [
        "def train(start_date, end_date, ticker_list, data_source, time_interval, \n",
        "          technical_indicator_list, drl_lib, env, agent, if_vix = True,\n",
        "          **kwargs):\n",
        "    \n",
        "    #fetch data\n",
        "    DP = DataProcessor(data_source, **kwargs)\n",
        "    data = DP.download_data(ticker_list, start_date, end_date, time_interval)\n",
        "    data = DP.clean_data(data)\n",
        "    data = DP.add_technical_indicator(data, technical_indicator_list)\n",
        "    if if_vix:\n",
        "        data = DP.add_vix(data)\n",
        "    price_array, tech_array, turbulence_array = DP.df_to_array(data, if_vix)\n",
        "    \n",
        "    #read parameters\n",
        "    env_config = {'price_array':price_array,\n",
        "            'tech_array':tech_array,\n",
        "            'turbulence_array':turbulence_array,\n",
        "            'if_train':True}\n",
        "    env_instance = env(config=env_config)\n",
        "    \n",
        "    learning_rate = kwargs.get('learning_rate', 0.00025)\n",
        "    batch_size = kwargs.get('batch_size', 2**7)\n",
        "    gamma = kwargs.get('gamma', 0.99)\n",
        "    seed = kwargs.get('seed', 312)\n",
        "    total_timesteps = kwargs.get('total_timesteps', 1e6)\n",
        "    net_dimension = kwargs.get('net_dimension', 2**7)\n",
        "    cwd = kwargs.get('cwd','./'+str(agent))\n",
        "    \n",
        "    #train using different libraries\n",
        "    if drl_lib == 'elegantrl':\n",
        "        \n",
        "        if agent == 'ppo':\n",
        "            args = Arguments(agent=AgentPPO(), env=env_instance, if_on_policy=True)\n",
        "        else:\n",
        "            raise ValueError('Invalid agent input or the agent input is not \\\n",
        "                             supported yet.')\n",
        "        try:\n",
        "            args.cwd = cwd\n",
        "            args.learning_rate = learning_rate\n",
        "            args.batch_size = batch_size\n",
        "            args.gamma = gamma\n",
        "            args.seed = seed\n",
        "            args.break_step = total_timesteps\n",
        "            args.net_dimension = net_dimension\n",
        "        except:\n",
        "            print('Invalid parameters input! Use default value.')\n",
        "            args.learning_rate = 0.00025\n",
        "            args.batch_size = 128\n",
        "            args.gamma = 0.99\n",
        "            args.seed = 312\n",
        "            args.break_step = 1e6\n",
        "            args.net_dimension = 2**7\n",
        "            \n",
        "        train_and_evaluate(args)\n",
        "        \n",
        "    elif drl_lib == 'rllib':\n",
        "        ray.init(ignore_reinit_error=True)\n",
        "        if agent == 'ppo':\n",
        "            from ray.rllib.agents import ppo\n",
        "            from ray.rllib.agents.ppo.ppo import PPOTrainer\n",
        "            try:\n",
        "                total_episodes = kwargs.get('total_episodes')\n",
        "            except:\n",
        "                print('total training episodes is not given! Use default value 1000')\n",
        "                total_episodes = 1000\n",
        "            config = ppo.DEFAULT_CONFIG.copy()\n",
        "            config['env'] = env\n",
        "            config[\"log_level\"] = \"WARN\"\n",
        "            config['env_config'] = {'price_array':price_array,\n",
        "                                    'tech_array':tech_array,\n",
        "                                    'turbulence_array':turbulence_array,\n",
        "                                    'if_train':True}\n",
        "            trainer = PPOTrainer(env=env, config=config)\n",
        "            for i in range(total_episodes):\n",
        "                trainer.train()\n",
        "            trainer.save(cwd)\n",
        "        \n",
        "        else:\n",
        "            raise ValueError('Invalid agent input or the agent input is not \\\n",
        "                 supported yet.')\n",
        "            \n",
        "    elif drl_lib == 'stable_baselines3':\n",
        "        \n",
        "        if agent == 'ppo':\n",
        "            from stable_baselines3 import PPO\n",
        "            from stable_baselines3.common.vec_env import DummyVecEnv\n",
        "            \n",
        "            env_train = DummyVecEnv([lambda : env_instance])\n",
        "            model = PPO(\"MlpPolicy\", env_train, learning_rate=learning_rate, \n",
        "                        n_steps=2048, batch_size=batch_size, ent_coef=0.0, \n",
        "                        gamma=gamma, seed=seed)\n",
        "            model.learn(total_timesteps=total_timesteps, tb_log_name = 'ppo')\n",
        "            print('Training finished!')\n",
        "            model.save(cwd)\n",
        "            print('Trained model saved in ' + str(cwd))\n",
        "    \n",
        "    else:\n",
        "        raise ValueError('DRL library input is NOT supported. Please check.')"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FCwCJKoyXYCk"
      },
      "source": [
        "## Test"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lNKwj7lE04UG"
      },
      "source": [
        "def test(start_date, end_date, ticker_list, data_source, time_interval, \n",
        "         technical_indicator_list, drl_lib, env, agent, if_vix = True,\n",
        "         **kwargs):\n",
        "    #fetch data\n",
        "    DP = DataProcessor(data_source, **kwargs)\n",
        "    data = DP.download_data(ticker_list, start_date, end_date, time_interval)\n",
        "    data = DP.clean_data(data)\n",
        "    data = DP.add_technical_indicator(data, technical_indicator_list)\n",
        "\n",
        "    if if_vix:\n",
        "        data = DP.add_vix(data)\n",
        "    price_array, tech_array, turbulence_array = DP.df_to_array(data, if_vix)\n",
        "    \n",
        "    env_config = {'price_array':price_array,\n",
        "            'tech_array':tech_array,\n",
        "            'turbulence_array':turbulence_array,\n",
        "            'if_train':False}\n",
        "    env_instance = env(config=env_config)\n",
        "    \n",
        "    net_dimension = kwargs.get('net_dimension', 2**7)\n",
        "    cwd = kwargs.get('cwd','./'+str(agent))\n",
        "    print(\"price_array: \",len(price_array))\n",
        "    #test on elegantrl\n",
        "    if drl_lib == 'elegantrl':\n",
        "        \n",
        "        #select agent\n",
        "        if agent == 'ppo':\n",
        "            args = Arguments(agent=AgentPPO(), env=env_instance, if_on_policy=True)\n",
        "        else:\n",
        "            raise ValueError('Invalid agent input or the agent input is not \\\n",
        "                             supported yet.')\n",
        "        \n",
        "        #load agent\n",
        "        try:\n",
        "            state_dim = env_instance.state_dim\n",
        "            action_dim = env_instance.action_dim\n",
        "    \n",
        "            agent = args.agent\n",
        "            net_dim = net_dimension\n",
        "    \n",
        "            agent.init(net_dim, state_dim, action_dim)\n",
        "            agent.save_load_model(cwd=cwd, if_save=False)\n",
        "            act = agent.act\n",
        "            device = agent.device\n",
        "    \n",
        "        except:\n",
        "            raise ValueError('Fail to load agent!')\n",
        "        \n",
        "        #test on the testing env\n",
        "        _torch = torch\n",
        "        state = env_instance.reset()\n",
        "        episode_returns = list()  # the cumulative_return / initial_account\n",
        "        episode_total_assets = list()\n",
        "        episode_total_assets.append(env_instance.initial_total_asset)\n",
        "        with _torch.no_grad():\n",
        "            for i in range(env_instance.max_step):\n",
        "                s_tensor = _torch.as_tensor((state,), device=device)\n",
        "                a_tensor = act(s_tensor)  # action_tanh = act.forward()\n",
        "                action = a_tensor.detach().cpu().numpy()[0]  # not need detach(), because with torch.no_grad() outside\n",
        "                state, reward, done, _ = env_instance.step(action)\n",
        "\n",
        "                total_asset = env_instance.amount + (env_instance.price_ary[env_instance.day] * env_instance.stocks).sum()\n",
        "                episode_total_assets.append(total_asset)\n",
        "                episode_return = total_asset / env_instance.initial_total_asset\n",
        "                episode_returns.append(episode_return)\n",
        "                if done:\n",
        "                    break\n",
        "                ##print(i)\n",
        "        print('Test Finished!')\n",
        "        #return episode returns on testing data\n",
        "        print('episode_return', episode_return)\n",
        "        return episode_total_assets\n",
        "    \n",
        "    #test using rllib\n",
        "    elif drl_lib == 'rllib':\n",
        "        #load agent\n",
        "        from ray.rllib.agents import ppo\n",
        "        from ray.rllib.agents.ppo.ppo import PPOTrainer\n",
        "        config = ppo.DEFAULT_CONFIG.copy()\n",
        "        config['env'] = env\n",
        "        config[\"log_level\"] = \"WARN\"\n",
        "        config['env_config'] = {'price_array':price_array,\n",
        "                                'tech_array':tech_array,\n",
        "                                'turbulence_array':turbulence_array,\n",
        "                                'if_train':False}\n",
        "        \n",
        "        trainer = PPOTrainer(env=env, config=config)\n",
        "        try:\n",
        "            trainer.restore(cwd)\n",
        "            print(\"Restoring from checkpoint path\", cwd)\n",
        "        except:\n",
        "            raise ValueError('Fail to load agent!')\n",
        "        \n",
        "        #test on the testing env\n",
        "        state = env_instance.reset()\n",
        "        episode_returns = list()  # the cumulative_return / initial_account\n",
        "        episode_total_assets = list()\n",
        "        episode_total_assets.append(env_instance.initial_total_asset)\n",
        "        done = False\n",
        "        while not done:\n",
        "            action = trainer.compute_single_action(state)\n",
        "            state, reward, done, _ = env_instance.step(action)\n",
        "    \n",
        "            total_asset = env_instance.amount + (env_instance.price_ary[env_instance.day] * env_instance.stocks).sum()\n",
        "            episode_total_assets.append(total_asset)\n",
        "            episode_return = total_asset / env_instance.initial_total_asset\n",
        "            episode_returns.append(episode_return)\n",
        "        print('episode return: ' + str(episode_return))\n",
        "        print('Test Finished!')   \n",
        "        return episode_total_assets\n",
        "\n",
        "          #test using stable baselines3\n",
        "    elif drl_lib == 'stable_baselines3':\n",
        "        from stable_baselines3 import PPO\n",
        "\n",
        "        try:\n",
        "            #load agent\n",
        "            model = PPO.load(cwd)\n",
        "            print(\"Successfully load model\", cwd)\n",
        "        except:\n",
        "            raise ValueError('Fail to load agent!')\n",
        "        \n",
        "        #test on the testing env\n",
        "        state = env_instance.reset()\n",
        "        episode_returns = list()  # the cumulative_return / initial_account\n",
        "        episode_total_assets = list()\n",
        "        episode_total_assets.append(env_instance.initial_total_asset)\n",
        "        done = False\n",
        "        while not done:\n",
        "            action = model.predict(state)[0]\n",
        "            state, reward, done, _ = env_instance.step(action)\n",
        "    \n",
        "            total_asset = env_instance.amount + (env_instance.price_ary[env_instance.day] * env_instance.stocks).sum()\n",
        "            episode_total_assets.append(total_asset)\n",
        "            episode_return = total_asset / env_instance.initial_total_asset\n",
        "            episode_returns.append(episode_return)\n",
        "        \n",
        "        print('episode_return', episode_return)\n",
        "        print('Test Finished!')   \n",
        "        return episode_total_assets\n",
        "    \n",
        "    else:\n",
        "        raise ValueError('DRL library input is NOT supported yet. Please check.')"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VzS1DtvaXzCB"
      },
      "source": [
        "## DRL Environment"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wcvNObPnDug_"
      },
      "source": [
        "from finrl.neo_finrl.env_stock_trading.env_stocktrading_np import StockTradingEnv"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "exdnEQ8eSQxZ"
      },
      "source": [
        "import numpy as np\n",
        "import os\n",
        "import gym\n",
        "from numpy import random as rd\n",
        "\n",
        "class StockTradingEnv(gym.Env):\n",
        "\n",
        "    def __init__(self, config, initial_account=1e6,\n",
        "                 gamma=0.99, turbulence_thresh=80, min_stock_rate=0.1,\n",
        "                 max_stock=1e2, initial_capital=1e6, buy_cost_pct=1e-3, \n",
        "                 sell_cost_pct=1e-3,reward_scaling=2 ** -11,  initial_stocks=None,\n",
        "                 ):\n",
        "        price_ary = config['price_array']\n",
        "        tech_ary = config['tech_array']\n",
        "        tech_nan_positions = np.isnan(tech_ary)\n",
        "        tech_ary[tech_nan_positions] = 0\n",
        "        turbulence_ary = config['turbulence_array']\n",
        "        if_train = config['if_train']\n",
        "        n = price_ary.shape[0]\n",
        "        self.price_ary =  price_ary.astype(np.float32)\n",
        "        self.tech_ary = tech_ary.astype(np.float32)\n",
        "        self.turbulence_ary = turbulence_ary\n",
        "        \n",
        "        self.tech_ary = self.tech_ary * 2 ** -7\n",
        "        self.turbulence_bool = (turbulence_ary > turbulence_thresh).astype(np.float32)\n",
        "        self.turbulence_ary = (self.sigmoid_sign(turbulence_ary, turbulence_thresh) * 2 ** -5).astype(np.float32)\n",
        "\n",
        "        stock_dim = self.price_ary.shape[1]\n",
        "        self.gamma = gamma\n",
        "        self.max_stock = max_stock\n",
        "        self.min_stock_rate = min_stock_rate\n",
        "        self.buy_cost_pct = buy_cost_pct\n",
        "        self.sell_cost_pct = sell_cost_pct\n",
        "        self.reward_scaling = reward_scaling\n",
        "        self.initial_capital = initial_capital\n",
        "        self.initial_stocks = np.zeros(stock_dim, dtype=np.float32) if initial_stocks is None else initial_stocks\n",
        "\n",
        "        # reset()\n",
        "        self.day = None\n",
        "        self.amount = None\n",
        "        self.stocks = None\n",
        "        self.total_asset = None\n",
        "        self.gamma_reward = None\n",
        "        self.initial_total_asset = None\n",
        "\n",
        "        # environment information\n",
        "        self.env_name = 'StockEnv'\n",
        "        # self.state_dim = 1 + 2 + 2 * stock_dim + self.tech_ary.shape[1]\n",
        "        # # amount + (turbulence, turbulence_bool) + (price, stock) * stock_dim + tech_dim\n",
        "        self.state_dim = 1 + 2 + 3 * stock_dim + self.tech_ary.shape[1]\n",
        "        # amount + (turbulence, turbulence_bool) + (price, stock) * stock_dim + tech_dim\n",
        "        self.stocks_cd = None\n",
        "        self.action_dim = stock_dim\n",
        "        self.max_step = self.price_ary.shape[0] - 1\n",
        "        self.if_train = if_train\n",
        "        self.if_discrete = False\n",
        "        self.target_return = 2.2\n",
        "        self.episode_return = 0.0\n",
        "        \n",
        "        self.observation_space = gym.spaces.Box(low=-3000, high=3000, shape=(self.state_dim,), dtype=np.float32)\n",
        "        self.action_space = gym.spaces.Box(low=-1, high=1, shape=(self.action_dim,), dtype=np.float32)\n",
        "        \n",
        "    def reset(self):\n",
        "        self.day = 0\n",
        "        price = self.price_ary[self.day]\n",
        "        \n",
        "        if self.if_train:\n",
        "            self.stocks = (self.initial_stocks + rd.randint(0, 64, size=self.initial_stocks.shape)).astype(np.float32)\n",
        "            self.stocks_cd = np.zeros_like(self.stocks)\n",
        "            self.amount = self.initial_capital * rd.uniform(0.95, 1.05) - (self.stocks * price).sum()\n",
        "        else:\n",
        "            self.stocks = self.initial_stocks.astype(np.float32)\n",
        "            self.stocks_cd = np.zeros_like(self.stocks)\n",
        "            self.amount = self.initial_capital\n",
        "\n",
        "        self.total_asset = self.amount + (self.stocks * price).sum()\n",
        "        self.initial_total_asset = self.total_asset\n",
        "        self.gamma_reward = 0.0\n",
        "        return self.get_state(price)  # state\n",
        "\n",
        "    def step(self, actions):\n",
        "        actions = (actions * self.max_stock).astype(int)\n",
        "\n",
        "        self.day += 1\n",
        "        price = self.price_ary[self.day]\n",
        "        self.stocks_cd += 1\n",
        "\n",
        "        if self.turbulence_bool[self.day] == 0:\n",
        "            min_action = int(self.max_stock * self.min_stock_rate)  # stock_cd\n",
        "            for index in np.where(actions < -min_action)[0]:  # sell_index:\n",
        "                if price[index] > 0:  # Sell only if current asset is > 0\n",
        "                    sell_num_shares = min(self.stocks[index], -actions[index])\n",
        "                    self.stocks[index] -= sell_num_shares\n",
        "                    self.amount += price[index] * sell_num_shares * (1 - self.sell_cost_pct)\n",
        "                    self.stocks_cd[index] = 0\n",
        "            for index in np.where(actions > min_action)[0]:  # buy_index:\n",
        "                if price[index] > 0:  # Buy only if the price is > 0 (no missing data in this particular date)\n",
        "                    buy_num_shares = min(self.amount // price[index], actions[index])\n",
        "                    self.stocks[index] += buy_num_shares\n",
        "                    self.amount -= price[index] * buy_num_shares * (1 + self.buy_cost_pct)\n",
        "                    self.stocks_cd[index] = 0\n",
        "\n",
        "        else:  # sell all when turbulence\n",
        "            self.amount += (self.stocks * price).sum() * (1 - self.sell_cost_pct)\n",
        "            self.stocks[:] = 0\n",
        "            self.stocks_cd[:] = 0\n",
        "\n",
        "        state = self.get_state(price)\n",
        "        total_asset = self.amount + (self.stocks * price).sum()\n",
        "        reward = (total_asset - self.total_asset) * self.reward_scaling\n",
        "        self.total_asset = total_asset\n",
        "\n",
        "        self.gamma_reward = self.gamma_reward * self.gamma + reward\n",
        "        done = self.day == self.max_step\n",
        "        if done:\n",
        "            reward = self.gamma_reward\n",
        "            self.episode_return = total_asset / self.initial_total_asset\n",
        "\n",
        "        return state, reward, done, dict()\n",
        "\n",
        "    def get_state(self, price):\n",
        "        amount = np.array(max(self.amount, 1e4) * (2 ** -12), dtype=np.float32)\n",
        "        scale = np.array(2 ** -6, dtype=np.float32)\n",
        "        return np.hstack((amount,\n",
        "                          self.turbulence_ary[self.day],\n",
        "                          self.turbulence_bool[self.day],\n",
        "                          price * scale,\n",
        "                          self.stocks * scale,\n",
        "                          self.stocks_cd,\n",
        "                          self.tech_ary[self.day],\n",
        "                          ))  # state.astype(np.float32)\n",
        "    \n",
        "    @staticmethod\n",
        "    def sigmoid_sign(ary, thresh):\n",
        "        def sigmoid(x):\n",
        "            return 1 / (1 + np.exp(-x * np.e)) - 0.5\n",
        "\n",
        "        return sigmoid(ary / thresh) * thresh"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LcbH9Ah9X7vw"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lM3lVwmQX8GA"
      },
      "source": [
        "## Set parameters"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l5dYmiPpDug_"
      },
      "source": [
        "env = StockTradingEnv"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NXgk2XftXwoR"
      },
      "source": [
        "TRAIN_START_DATE = '2014-01-01'\n",
        "TRAIN_END_DATE = '2020-06-30'\n",
        "\n",
        "TEST_START_DATE = '2020-07-01'\n",
        "TEST_END_DATE = '2021-07-03'\n",
        "TECHNICAL_INDICATORS_LIST = ['macd',\n",
        " 'boll_ub',\n",
        " 'boll_lb',\n",
        " 'rsi_30',\n",
        " 'dx_30',\n",
        " 'close_30_sma',\n",
        " 'close_60_sma']"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1TC8cMZaYAG1"
      },
      "source": [
        "## eRL"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tO1sXcIJZdtE"
      },
      "source": [
        "### Train"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JodM4Qn3Dug_",
        "outputId": "d2dad1e1-161d-47cb-93da-ab82d37ae8da"
      },
      "source": [
        "#demo for elegantrl\n",
        "train(start_date = TRAIN_START_DATE, \n",
        "      end_date = TRAIN_END_DATE,\n",
        "      ticker_list = config.DOW_30_TICKER, \n",
        "      data_source = 'yahoofinance',\n",
        "      time_interval= '1D', \n",
        "      technical_indicator_list= TECHNICAL_INDICATORS_LIST,\n",
        "      drl_lib='elegantrl', \n",
        "      env=env, \n",
        "      agent='ppo', \n",
        "      cwd='./test_ppo'\n",
        "      ,total_timesteps=6e4)"
      ],
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (49050, 9)\n",
            "Clean data for AAPL\n",
            "Data clean for AAPL is finished.\n",
            "Clean data for AXP\n",
            "Data clean for AXP is finished.\n",
            "Clean data for BA\n",
            "Data clean for BA is finished.\n",
            "Clean data for CAT\n",
            "Data clean for CAT is finished.\n",
            "Clean data for CSCO\n",
            "Data clean for CSCO is finished.\n",
            "Clean data for CVX\n",
            "Data clean for CVX is finished.\n",
            "Clean data for DD\n",
            "Data clean for DD is finished.\n",
            "Clean data for DIS\n",
            "Data clean for DIS is finished.\n",
            "Clean data for GS\n",
            "Data clean for GS is finished.\n",
            "Clean data for HD\n",
            "Data clean for HD is finished.\n",
            "Clean data for IBM\n",
            "Data clean for IBM is finished.\n",
            "Clean data for INTC\n",
            "Data clean for INTC is finished.\n",
            "Clean data for JNJ\n",
            "Data clean for JNJ is finished.\n",
            "Clean data for JPM\n",
            "Data clean for JPM is finished.\n",
            "Clean data for KO\n",
            "Data clean for KO is finished.\n",
            "Clean data for MCD\n",
            "Data clean for MCD is finished.\n",
            "Clean data for MMM\n",
            "Data clean for MMM is finished.\n",
            "Clean data for MRK\n",
            "Data clean for MRK is finished.\n",
            "Clean data for MSFT\n",
            "Data clean for MSFT is finished.\n",
            "Clean data for NKE\n",
            "Data clean for NKE is finished.\n",
            "Clean data for PFE\n",
            "Data clean for PFE is finished.\n",
            "Clean data for PG\n",
            "Data clean for PG is finished.\n",
            "Clean data for RTX\n",
            "Data clean for RTX is finished.\n",
            "Clean data for TRV\n",
            "Data clean for TRV is finished.\n",
            "Clean data for UNH\n",
            "Data clean for UNH is finished.\n",
            "Clean data for V\n",
            "Data clean for V is finished.\n",
            "Clean data for VZ\n",
            "Data clean for VZ is finished.\n",
            "Clean data for WBA\n",
            "Data clean for WBA is finished.\n",
            "Clean data for WMT\n",
            "Data clean for WMT is finished.\n",
            "Clean data for XOM\n",
            "Data clean for XOM is finished.\n",
            "Data clean all finished!\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (1635, 9)\n",
            "Clean data for ^VIX\n",
            "Data clean for ^VIX is finished.\n",
            "Data clean all finished!\n",
            "['AAPL' 'AXP' 'BA' 'CAT' 'CSCO' 'CVX' 'DD' 'DIS' 'GS' 'HD' 'IBM' 'INTC'\n",
            " 'JNJ' 'JPM' 'KO' 'MCD' 'MMM' 'MRK' 'MSFT' 'NKE' 'PFE' 'PG' 'RTX' 'TRV'\n",
            " 'UNH' 'V' 'VZ' 'WBA' 'WMT' 'XOM']\n",
            "Successfully transformed into array\n",
            "| GPU id: 0, cwd: ./test_ppo\n",
            "| Remove history\n",
            "ID      Step      MaxR |    avgR      stdR       objA      objC |  avgS  stdS\n",
            "0   4.90e+03      1.32 |\n",
            "0   4.90e+03      1.32 |    1.32      0.10      -0.15      7.32 |  1635     0\n",
            "0   9.81e+03      1.84 |\n",
            "0   9.81e+03      1.84 |    1.84      0.06      -0.20      4.91 |  1635     0\n",
            "0   1.47e+04      1.84 |    1.71      0.08      -0.10      5.78 |  1635     0\n",
            "0   1.96e+04      2.05 |\n",
            "0   1.96e+04      2.05 |    2.05      0.08       0.06     13.37 |  1635     0\n",
            "0   2.45e+04      2.05 |    2.01      0.05      -0.16      6.53 |  1635     0\n",
            "0   2.94e+04      2.36 |\n",
            "ID      Step   TargetR |    avgR      stdR   UsedTime  ########\n",
            "0   2.94e+04      2.20 |    2.36      0.27        373  ########\n",
            "0   2.94e+04      2.36 |    2.36      0.27      -0.01      9.64 |  1635     0\n",
            "| SavedDir: ./test_ppo\n",
            "| UsedTime: 374\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9eSQ64_nZhJ1"
      },
      "source": [
        "### Test"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZOdNzZnoYhH3",
        "outputId": "02490091-3755-4e66-aa9a-632f2eb5903a"
      },
      "source": [
        "account_value_erl=test(start_date = TEST_START_DATE, \n",
        "                        end_date = TEST_END_DATE,\n",
        "                        ticker_list = config.DOW_30_TICKER, \n",
        "                        data_source = 'yahoofinance',\n",
        "                        time_interval= '1D', \n",
        "                        technical_indicator_list= TECHNICAL_INDICATORS_LIST,\n",
        "                        drl_lib='elegantrl', \n",
        "                        env=env, \n",
        "                        agent='ppo', \n",
        "                        cwd='./test_ppo', \n",
        "                        net_dimension = 2 ** 9)"
      ],
      "execution_count": 149,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (7620, 9)\n",
            "Clean data for AAPL\n",
            "Data clean for AAPL is finished.\n",
            "Clean data for AXP\n",
            "Data clean for AXP is finished.\n",
            "Clean data for BA\n",
            "Data clean for BA is finished.\n",
            "Clean data for CAT\n",
            "Data clean for CAT is finished.\n",
            "Clean data for CSCO\n",
            "Data clean for CSCO is finished.\n",
            "Clean data for CVX\n",
            "Data clean for CVX is finished.\n",
            "Clean data for DD\n",
            "Data clean for DD is finished.\n",
            "Clean data for DIS\n",
            "Data clean for DIS is finished.\n",
            "Clean data for GS\n",
            "Data clean for GS is finished.\n",
            "Clean data for HD\n",
            "Data clean for HD is finished.\n",
            "Clean data for IBM\n",
            "Data clean for IBM is finished.\n",
            "Clean data for INTC\n",
            "Data clean for INTC is finished.\n",
            "Clean data for JNJ\n",
            "Data clean for JNJ is finished.\n",
            "Clean data for JPM\n",
            "Data clean for JPM is finished.\n",
            "Clean data for KO\n",
            "Data clean for KO is finished.\n",
            "Clean data for MCD\n",
            "Data clean for MCD is finished.\n",
            "Clean data for MMM\n",
            "Data clean for MMM is finished.\n",
            "Clean data for MRK\n",
            "Data clean for MRK is finished.\n",
            "Clean data for MSFT\n",
            "Data clean for MSFT is finished.\n",
            "Clean data for NKE\n",
            "Data clean for NKE is finished.\n",
            "Clean data for PFE\n",
            "Data clean for PFE is finished.\n",
            "Clean data for PG\n",
            "Data clean for PG is finished.\n",
            "Clean data for RTX\n",
            "Data clean for RTX is finished.\n",
            "Clean data for TRV\n",
            "Data clean for TRV is finished.\n",
            "Clean data for UNH\n",
            "Data clean for UNH is finished.\n",
            "Clean data for V\n",
            "Data clean for V is finished.\n",
            "Clean data for VZ\n",
            "Data clean for VZ is finished.\n",
            "Clean data for WBA\n",
            "Data clean for WBA is finished.\n",
            "Clean data for WMT\n",
            "Data clean for WMT is finished.\n",
            "Clean data for XOM\n",
            "Data clean for XOM is finished.\n",
            "Data clean all finished!\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (253, 9)\n",
            "Clean data for ^VIX\n",
            "Data clean for ^VIX is finished.\n",
            "Data clean all finished!\n",
            "['AAPL' 'AXP' 'BA' 'CAT' 'CSCO' 'CVX' 'DD' 'DIS' 'GS' 'HD' 'IBM' 'INTC'\n",
            " 'JNJ' 'JPM' 'KO' 'MCD' 'MMM' 'MRK' 'MSFT' 'NKE' 'PFE' 'PG' 'RTX' 'TRV'\n",
            " 'UNH' 'V' 'VZ' 'WBA' 'WMT' 'XOM']\n",
            "Successfully transformed into array\n",
            "price_array:  254\n",
            "Loaded act: ./test_ppo\n",
            "Test Finished!\n",
            "episode_return 1.392604708194965\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8F8Xqq6rjgly"
      },
      "source": [
        "### Plot"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "Koa7NilB7-Ge",
        "outputId": "1f4bb496-33bc-49f9-ed35-dda6e0e6802f"
      },
      "source": [
        "TEST_END_DATE"
      ],
      "execution_count": 150,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'2021-07-03'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 150
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uzlZfeHucDIh",
        "outputId": "7cf71b5b-a18b-4176-efa5-92ca130ee775"
      },
      "source": [
        "baseline_df =  DataProcessor('yahoofinance').download_data(ticker_list = [\"^DJI\"], \n",
        "                                                            start_date = TEST_START_DATE, \n",
        "                                                            end_date = TEST_END_DATE, \n",
        "                                                            time_interval = \"1D\")\n",
        "stats = backtest_stats(baseline_df, value_col_name = 'close')\n"
      ],
      "execution_count": 161,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (254, 9)\n",
            "Annual return          0.348511\n",
            "Cumulative returns     0.351715\n",
            "Annual volatility      0.145303\n",
            "Sharpe ratio           2.139596\n",
            "Calmar ratio           3.902364\n",
            "Stability              0.946267\n",
            "Max drawdown          -0.089308\n",
            "Omega ratio            1.427764\n",
            "Sortino ratio          3.204934\n",
            "Skew                        NaN\n",
            "Kurtosis                    NaN\n",
            "Tail ratio             1.082606\n",
            "Daily value at risk   -0.017073\n",
            "dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VNkvXLnEeu0u"
      },
      "source": [
        "account_value_erl = pd.DataFrame({'date':baseline_df.date,'account_value':account_value_erl})"
      ],
      "execution_count": 152,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "EoHB3xzY6GrR",
        "outputId": "5c8a8c82-f593-4446-9c4f-593a38d31428"
      },
      "source": [
        "account_value_erl.tail()"
      ],
      "execution_count": 154,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "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>date</th>\n",
              "      <th>account_value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>249</th>\n",
              "      <td>2021-06-28</td>\n",
              "      <td>1.377610e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>250</th>\n",
              "      <td>2021-06-29</td>\n",
              "      <td>1.380438e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>251</th>\n",
              "      <td>2021-06-30</td>\n",
              "      <td>1.385402e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>252</th>\n",
              "      <td>2021-07-01</td>\n",
              "      <td>1.392498e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>253</th>\n",
              "      <td>2021-07-02</td>\n",
              "      <td>1.392605e+06</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           date  account_value\n",
              "249  2021-06-28   1.377610e+06\n",
              "250  2021-06-29   1.380438e+06\n",
              "251  2021-06-30   1.385402e+06\n",
              "252  2021-07-01   1.392498e+06\n",
              "253  2021-07-02   1.392605e+06"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 154
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3lZjaI5fbLQC",
        "outputId": "9a7cbabb-3165-478d-d6c0-c3989813b4d3"
      },
      "source": [
        "print(\"==============Get Backtest Results===========\")\n",
        "now = datetime.datetime.now().strftime('%Y%m%d-%Hh%M')\n",
        "\n",
        "perf_stats_all = backtest_stats(account_value=account_value_erl)\n",
        "perf_stats_all = pd.DataFrame(perf_stats_all)\n",
        "perf_stats_all.to_csv(\"./\"+\"/perf_stats_all_\"+now+'.csv')"
      ],
      "execution_count": 156,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Get Backtest Results===========\n",
            "Annual return          0.388978\n",
            "Cumulative returns     0.392605\n",
            "Annual volatility      0.163635\n",
            "Sharpe ratio           2.098776\n",
            "Calmar ratio           3.839873\n",
            "Stability              0.946142\n",
            "Max drawdown          -0.101300\n",
            "Omega ratio            1.441199\n",
            "Sortino ratio          3.165952\n",
            "Skew                        NaN\n",
            "Kurtosis                    NaN\n",
            "Tail ratio             1.189944\n",
            "Daily value at risk   -0.019253\n",
            "dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9qJUg0KTBIGw"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "wZ1A4lB7jZ2r",
        "outputId": "2da0d1e9-8225-4a2f-b604-e372a4a30608"
      },
      "source": [
        "print(\"==============Compare to DJIA===========\")\n",
        "%matplotlib inline\n",
        "# S&P 500: ^GSPC\n",
        "# Dow Jones Index: ^DJI\n",
        "# NASDAQ 100: ^NDX\n",
        "backtest_plot(account_value_erl, \n",
        "             baseline_ticker = '^DJI', \n",
        "             baseline_start = account_value_erl.loc[0,'date'],\n",
        "             baseline_end = account_value_erl.loc[len(account_value_erl)-1,'date'])"
      ],
      "execution_count": 157,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Compare to DJIA===========\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (253, 8)\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\"><th>Start date</th><td colspan=2>2020-07-01</td></tr>\n",
              "    <tr style=\"text-align: right;\"><th>End date</th><td colspan=2>2021-07-01</td></tr>\n",
              "    <tr style=\"text-align: right;\"><th>Total months</th><td colspan=2>12</td></tr>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Backtest</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Annual return</th>\n",
              "      <td>39.068%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Cumulative returns</th>\n",
              "      <td>39.25%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Annual volatility</th>\n",
              "      <td>16.396%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sharpe ratio</th>\n",
              "      <td>2.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Calmar ratio</th>\n",
              "      <td>3.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Stability</th>\n",
              "      <td>0.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Max drawdown</th>\n",
              "      <td>-10.13%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Omega ratio</th>\n",
              "      <td>1.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sortino ratio</th>\n",
              "      <td>3.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Skew</th>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kurtosis</th>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tail ratio</th>\n",
              "      <td>1.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Daily value at risk</th>\n",
              "      <td>-1.929%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alpha</th>\n",
              "      <td>0.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Beta</th>\n",
              "      <td>1.01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>Worst drawdown periods</th>\n",
              "      <th>Net drawdown in %</th>\n",
              "      <th>Peak date</th>\n",
              "      <th>Valley date</th>\n",
              "      <th>Recovery date</th>\n",
              "      <th>Duration</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>10.13</td>\n",
              "      <td>2020-09-02</td>\n",
              "      <td>2020-10-30</td>\n",
              "      <td>2020-11-09</td>\n",
              "      <td>49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4.71</td>\n",
              "      <td>2021-01-21</td>\n",
              "      <td>2021-01-29</td>\n",
              "      <td>2021-02-08</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3.92</td>\n",
              "      <td>2021-05-07</td>\n",
              "      <td>2021-05-12</td>\n",
              "      <td>2021-06-04</td>\n",
              "      <td>21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2.75</td>\n",
              "      <td>2021-02-24</td>\n",
              "      <td>2021-02-26</td>\n",
              "      <td>2021-03-05</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2.53</td>\n",
              "      <td>2021-06-15</td>\n",
              "      <td>2021-06-18</td>\n",
              "      <td>2021-06-24</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pyfolio/tears.py:907: UserWarning: Passed returns do not overlap with anyinteresting times.\n",
            "  'interesting times.', UserWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x5184 with 13 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VzTdYfbNCKiE"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aq6QHtD4YuE5"
      },
      "source": [
        "## RLlib"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OVMEflpTZjc0"
      },
      "source": [
        "### Train"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "MOuD9mdLDuhA",
        "outputId": "d93f3081-1eb3-4289-f015-feb88cf895b3"
      },
      "source": [
        "#demo for rllib\n",
        "train(start_date = TEST_START_DATE, \n",
        "      end_date = TEST_END_DATE,\n",
        "      ticker_list = config.DOW_30_TICKER, \n",
        "      data_source = 'yahoofinance',\n",
        "      time_interval= '1D', \n",
        "      technical_indicator_list= TECHNICAL_INDICATORS_LIST,\n",
        "      drl_lib='rllib', \n",
        "      env=env, \n",
        "      agent='ppo', \n",
        "      cwd='./test_ppo'\n",
        "      ,total_episodes=10)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (7620, 9)\n",
            "Clean data for AAPL\n",
            "Data clean for AAPL is finished.\n",
            "Clean data for AXP\n",
            "Data clean for AXP is finished.\n",
            "Clean data for BA\n",
            "Data clean for BA is finished.\n",
            "Clean data for CAT\n",
            "Data clean for CAT is finished.\n",
            "Clean data for CSCO\n",
            "Data clean for CSCO is finished.\n",
            "Clean data for CVX\n",
            "Data clean for CVX is finished.\n",
            "Clean data for DD\n",
            "Data clean for DD is finished.\n",
            "Clean data for DIS\n",
            "Data clean for DIS is finished.\n",
            "Clean data for GS\n",
            "Data clean for GS is finished.\n",
            "Clean data for HD\n",
            "Data clean for HD is finished.\n",
            "Clean data for IBM\n",
            "Data clean for IBM is finished.\n",
            "Clean data for INTC\n",
            "Data clean for INTC is finished.\n",
            "Clean data for JNJ\n",
            "Data clean for JNJ is finished.\n",
            "Clean data for JPM\n",
            "Data clean for JPM is finished.\n",
            "Clean data for KO\n",
            "Data clean for KO is finished.\n",
            "Clean data for MCD\n",
            "Data clean for MCD is finished.\n",
            "Clean data for MMM\n",
            "Data clean for MMM is finished.\n",
            "Clean data for MRK\n",
            "Data clean for MRK is finished.\n",
            "Clean data for MSFT\n",
            "Data clean for MSFT is finished.\n",
            "Clean data for NKE\n",
            "Data clean for NKE is finished.\n",
            "Clean data for PFE\n",
            "Data clean for PFE is finished.\n",
            "Clean data for PG\n",
            "Data clean for PG is finished.\n",
            "Clean data for RTX\n",
            "Data clean for RTX is finished.\n",
            "Clean data for TRV\n",
            "Data clean for TRV is finished.\n",
            "Clean data for UNH\n",
            "Data clean for UNH is finished.\n",
            "Clean data for V\n",
            "Data clean for V is finished.\n",
            "Clean data for VZ\n",
            "Data clean for VZ is finished.\n",
            "Clean data for WBA\n",
            "Data clean for WBA is finished.\n",
            "Clean data for WMT\n",
            "Data clean for WMT is finished.\n",
            "Clean data for XOM\n",
            "Data clean for XOM is finished.\n",
            "Data clean all finished!\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (253, 9)\n",
            "Clean data for ^VIX\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "2021-08-17 16:57:12,016\tINFO worker.py:811 -- Calling ray.init() again after it has already been called.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Data clean for ^VIX is finished.\n",
            "Data clean all finished!\n",
            "['AAPL' 'AXP' 'BA' 'CAT' 'CSCO' 'CVX' 'DD' 'DIS' 'GS' 'HD' 'IBM' 'INTC'\n",
            " 'JNJ' 'JPM' 'KO' 'MCD' 'MMM' 'MRK' 'MSFT' 'NKE' 'PFE' 'PG' 'RTX' 'TRV'\n",
            " 'UNH' 'V' 'VZ' 'WBA' 'WMT' 'XOM']\n",
            "Successfully transformed into array\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "\u001b[2m\u001b[36m(pid=1567)\u001b[0m 2021-08-17 16:57:20,136\tERROR worker.py:421 -- Exception raised in creation task: The actor died because of an error raised in its creation task, \u001b[36mray::RolloutWorker.__init__()\u001b[39m (pid=1567, ip=172.28.0.2)\n",
            "\u001b[2m\u001b[36m(pid=1567)\u001b[0m   File \"python/ray/_raylet.pyx\", line 534, in ray._raylet.execute_task\n",
            "\u001b[2m\u001b[36m(pid=1567)\u001b[0m   File \"python/ray/_raylet.pyx\", line 484, in ray._raylet.execute_task.function_executor\n",
            "\u001b[2m\u001b[36m(pid=1567)\u001b[0m   File \"/usr/local/lib/python3.7/dist-packages/ray/_private/function_manager.py\", line 563, in actor_method_executor\n",
            "\u001b[2m\u001b[36m(pid=1567)\u001b[0m     return method(__ray_actor, *args, **kwargs)\n",
            "\u001b[2m\u001b[36m(pid=1567)\u001b[0m   File \"/usr/local/lib/python3.7/dist-packages/ray/rllib/evaluation/rollout_worker.py\", line 393, in __init__\n",
            "\u001b[2m\u001b[36m(pid=1567)\u001b[0m     self.env = env_creator(env_context)\n",
            "\u001b[2m\u001b[36m(pid=1567)\u001b[0m   File \"/usr/local/lib/python3.7/dist-packages/ray/rllib/agents/trainer.py\", line 1564, in <lambda>\n",
            "\u001b[2m\u001b[36m(pid=1567)\u001b[0m     register_env(name, lambda config: env_object(config))\n",
            "\u001b[2m\u001b[36m(pid=1567)\u001b[0m   File \"<ipython-input-7-d982572da633>\", line 16, in __init__\n",
            "\u001b[2m\u001b[36m(pid=1567)\u001b[0m ValueError: assignment destination is read-only\n",
            "\u001b[2m\u001b[36m(pid=1568)\u001b[0m 2021-08-17 16:57:20,159\tERROR worker.py:421 -- Exception raised in creation task: The actor died because of an error raised in its creation task, \u001b[36mray::RolloutWorker.__init__()\u001b[39m (pid=1568, ip=172.28.0.2)\n",
            "\u001b[2m\u001b[36m(pid=1568)\u001b[0m   File \"python/ray/_raylet.pyx\", line 534, in ray._raylet.execute_task\n",
            "\u001b[2m\u001b[36m(pid=1568)\u001b[0m   File \"python/ray/_raylet.pyx\", line 484, in ray._raylet.execute_task.function_executor\n",
            "\u001b[2m\u001b[36m(pid=1568)\u001b[0m   File \"/usr/local/lib/python3.7/dist-packages/ray/_private/function_manager.py\", line 563, in actor_method_executor\n",
            "\u001b[2m\u001b[36m(pid=1568)\u001b[0m     return method(__ray_actor, *args, **kwargs)\n",
            "\u001b[2m\u001b[36m(pid=1568)\u001b[0m   File \"/usr/local/lib/python3.7/dist-packages/ray/rllib/evaluation/rollout_worker.py\", line 393, in __init__\n",
            "\u001b[2m\u001b[36m(pid=1568)\u001b[0m     self.env = env_creator(env_context)\n",
            "\u001b[2m\u001b[36m(pid=1568)\u001b[0m   File \"/usr/local/lib/python3.7/dist-packages/ray/rllib/agents/trainer.py\", line 1564, in <lambda>\n",
            "\u001b[2m\u001b[36m(pid=1568)\u001b[0m     register_env(name, lambda config: env_object(config))\n",
            "\u001b[2m\u001b[36m(pid=1568)\u001b[0m   File \"<ipython-input-7-d982572da633>\", line 16, in __init__\n",
            "\u001b[2m\u001b[36m(pid=1568)\u001b[0m ValueError: assignment destination is read-only\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "error",
          "ename": "RayActorError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mRayActorError\u001b[0m                             Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-11-20cfbca7f68b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     10\u001b[0m       \u001b[0magent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'ppo'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m       \u001b[0mcwd\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'./test_ppo'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m       ,total_episodes=10)\n\u001b[0m",
            "\u001b[0;32m<ipython-input-4-3766bb88ea99>\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(start_date, end_date, ticker_list, data_source, time_interval, technical_indicator_list, drl_lib, env, agent, if_vix, **kwargs)\u001b[0m\n\u001b[1;32m     70\u001b[0m                                     \u001b[0;34m'turbulence_array'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mturbulence_array\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     71\u001b[0m                                     'if_train':True}\n\u001b[0;32m---> 72\u001b[0;31m             \u001b[0mtrainer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPPOTrainer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0menv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0menv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     73\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtotal_episodes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     74\u001b[0m                 \u001b[0mtrainer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ray/rllib/agents/trainer_template.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, config, env, logger_creator)\u001b[0m\n\u001b[1;32m    121\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    122\u001b[0m         \u001b[0;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0menv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlogger_creator\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 123\u001b[0;31m             \u001b[0mTrainer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0menv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlogger_creator\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    124\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    125\u001b[0m         def _init(self, config: TrainerConfigDict,\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ray/rllib/agents/trainer.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, config, env, logger_creator)\u001b[0m\n\u001b[1;32m    582\u001b[0m             \u001b[0mlogger_creator\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdefault_logger_creator\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    583\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 584\u001b[0;31m         \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlogger_creator\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    585\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    586\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mclassmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ray/tune/trainable.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, config, logger_creator)\u001b[0m\n\u001b[1;32m    101\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    102\u001b[0m         \u001b[0mstart_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 103\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetup\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdeepcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    104\u001b[0m         \u001b[0msetup_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mstart_time\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    105\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0msetup_time\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0mSETUP_TIME_THRESHOLD\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ray/rllib/agents/trainer.py\u001b[0m in \u001b[0;36msetup\u001b[0;34m(self, config)\u001b[0m\n\u001b[1;32m    729\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    730\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mget_scope\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 731\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_init\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0menv_creator\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    732\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    733\u001b[0m             \u001b[0;31m# Evaluation setup.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ray/rllib/agents/trainer_template.py\u001b[0m in \u001b[0;36m_init\u001b[0;34m(self, config, env_creator)\u001b[0m\n\u001b[1;32m    150\u001b[0m                 \u001b[0mpolicy_class\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_policy_class\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    151\u001b[0m                 \u001b[0mconfig\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 152\u001b[0;31m                 num_workers=self.config[\"num_workers\"])\n\u001b[0m\u001b[1;32m    153\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecution_plan\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mexecution_plan\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    154\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain_exec_impl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mexecution_plan\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mworkers\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ray/rllib/agents/trainer.py\u001b[0m in \u001b[0;36m_make_workers\u001b[0;34m(self, env_creator, validate_env, policy_class, config, num_workers)\u001b[0m\n\u001b[1;32m    817\u001b[0m             \u001b[0mtrainer_config\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    818\u001b[0m             \u001b[0mnum_workers\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_workers\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 819\u001b[0;31m             logdir=self.logdir)\n\u001b[0m\u001b[1;32m    820\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    821\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mDeveloperAPI\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ray/rllib/evaluation/worker_set.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, env_creator, validate_env, policy_class, trainer_config, num_workers, logdir, _setup)\u001b[0m\n\u001b[1;32m     84\u001b[0m                 remote_spaces = ray.get(self.remote_workers(\n\u001b[1;32m     85\u001b[0m                 \u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mforeach_policy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mremote\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 86\u001b[0;31m                     lambda p, pid: (pid, p.observation_space, p.action_space)))\n\u001b[0m\u001b[1;32m     87\u001b[0m                 spaces = {\n\u001b[1;32m     88\u001b[0m                     \u001b[0me\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"original_space\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ray/_private/client_mode_hook.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     80\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mclient_mode_should_convert\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     81\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 82\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     83\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     84\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ray/worker.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(object_refs, timeout)\u001b[0m\n\u001b[1;32m   1564\u001b[0m                     \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mas_instanceof_cause\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1565\u001b[0m                 \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1566\u001b[0;31m                     \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1567\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1568\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mis_individual_id\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32mpython/ray/_raylet.pyx\u001b[0m in \u001b[0;36mray._raylet.task_execution_handler\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpython/ray/_raylet.pyx\u001b[0m in \u001b[0;36mray._raylet.execute_task\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpython/ray/_raylet.pyx\u001b[0m in \u001b[0;36mray._raylet.execute_task\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;31mRayActorError\u001b[0m: The actor died because of an error raised in its creation task, \u001b[36mray::RolloutWorker.__init__()\u001b[39m (pid=1567, ip=172.28.0.2)\n  File \"python/ray/_raylet.pyx\", line 534, in ray._raylet.execute_task\n  File \"python/ray/_raylet.pyx\", line 484, in ray._raylet.execute_task.function_executor\n  File \"/usr/local/lib/python3.7/dist-packages/ray/_private/function_manager.py\", line 563, in actor_method_executor\n    return method(__ray_actor, *args, **kwargs)\n  File \"/usr/local/lib/python3.7/dist-packages/ray/rllib/evaluation/rollout_worker.py\", line 393, in __init__\n    self.env = env_creator(env_context)\n  File \"/usr/local/lib/python3.7/dist-packages/ray/rllib/agents/trainer.py\", line 1564, in <lambda>\n    register_env(name, lambda config: env_object(config))\n  File \"<ipython-input-7-d982572da633>\", line 16, in __init__\nValueError: assignment destination is read-only"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lpMmJAkfZlMx"
      },
      "source": [
        "### Test"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 922
        },
        "id": "XtDjEqTcYwXQ",
        "outputId": "a59587fd-075f-42a6-c0c8-ed883dc3d6f6"
      },
      "source": [
        "account_value_rllib = test(start_date = TEST_START_DATE, \n",
        "     end_date = TEST_END_DATE,\n",
        "     ticker_list = config.DOW_30_TICKER, \n",
        "     data_source = 'yahoofinance',\n",
        "     time_interval= '1D', \n",
        "     technical_indicator_list= TECHNICAL_INDICATORS_LIST,\n",
        "     drl_lib='rllib', \n",
        "     env=env, \n",
        "     agent='ppo', \n",
        "     cwd='./test_ppo/checkpoint_000100/checkpoint-100')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (1255, 9)\n",
            "Clean data for AAPL\n",
            "Data clean for AAPL is finished.\n",
            "Clean data for AMZN\n",
            "Data clean for AMZN is finished.\n",
            "Clean data for FB\n",
            "Data clean for FB is finished.\n",
            "Clean data for GOOG\n",
            "Data clean for GOOG is finished.\n",
            "Clean data for NFLX\n",
            "Data clean for NFLX is finished.\n",
            "Data clean all finished!\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (250, 9)\n",
            "Clean data for ^VIX\n",
            "Data clean for ^VIX is finished.\n",
            "Data clean all finished!\n",
            "['AAPL' 'AMZN' 'FB' 'GOOG' 'NFLX']\n",
            "Successfully transformed into array\n",
            "price_array:  251\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "2021-08-16 16:16:33,828\tINFO trainable.py:109 -- Trainable.setup took 16.473 seconds. If your trainable is slow to initialize, consider setting reuse_actors=True to reduce actor creation overheads.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-79-f08ab2179a73>\u001b[0m in \u001b[0;36mtest\u001b[0;34m(start_date, end_date, ticker_list, data_source, time_interval, technical_indicator_list, drl_lib, env, agent, if_vix, **kwargs)\u001b[0m\n\u001b[1;32m     86\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 87\u001b[0;31m             \u001b[0mtrainer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrestore\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcwd\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     88\u001b[0m             \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Restoring from checkpoint path\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcwd\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ray/tune/trainable.py\u001b[0m in \u001b[0;36mrestore\u001b[0;34m(self, checkpoint_path)\u001b[0m\n\u001b[1;32m    362\u001b[0m         \"\"\"\n\u001b[0;32m--> 363\u001b[0;31m         \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcheckpoint_path\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\".tune_metadata\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"rb\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    364\u001b[0m             \u001b[0mmetadata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: './test_ppo/checkpoint_000100/checkpoint-100.tune_metadata'",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-114-f4533dc030bc>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      8\u001b[0m      \u001b[0menv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0menv\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m      \u001b[0magent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'ppo'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m      cwd='./test_ppo/checkpoint_000100/checkpoint-100')\n\u001b[0m",
            "\u001b[0;32m<ipython-input-79-f08ab2179a73>\u001b[0m in \u001b[0;36mtest\u001b[0;34m(start_date, end_date, ticker_list, data_source, time_interval, technical_indicator_list, drl_lib, env, agent, if_vix, **kwargs)\u001b[0m\n\u001b[1;32m     88\u001b[0m             \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Restoring from checkpoint path\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcwd\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     89\u001b[0m         \u001b[0;32mexcept\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 90\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Fail to load agent!'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     91\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     92\u001b[0m         \u001b[0;31m#test on the testing env\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mValueError\u001b[0m: Fail to load agent!"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H6yq9e776g3z",
        "outputId": "8fbff441-e770-4e9d-9139-570c9fe7d677"
      },
      "source": [
        "len(account_value_erl)"
      ],
      "execution_count": 155,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "254"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 155
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B-RC3cjI2X1a"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k6ajBhvMBdsG"
      },
      "source": [
        "### Plot"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-v5aoZ10Bgky"
      },
      "source": [
        "account_value_rllib = pd.DataFrame({'date':baseline_df.date,'account_value':account_value_rllib})"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pSAgvG7CBnIJ"
      },
      "source": [
        "print(\"==============Compare to DJIA===========\")\n",
        "#%matplotlib inline\n",
        "# S&P 500: ^GSPC\n",
        "# Dow Jones Index: ^DJI\n",
        "# NASDAQ 100: ^NDX\n",
        "backtest_plot(account_value_rllib, \n",
        "             baseline_ticker = '^DJI', \n",
        "             baseline_start = account_value_rllib.loc[0,'date'],\n",
        "             baseline_end = account_value_rllib.loc[len(account_value_rllib)-1,'date'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hN_2gi3SY6U1"
      },
      "source": [
        "## Stable-baselines3"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aRBk-NDdZmx0"
      },
      "source": [
        "### Train"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2A7msCg0DuhA",
        "outputId": "535cc1bc-70f4-4bbb-c80a-882b4e2e284d"
      },
      "source": [
        "#demo for stable-baselines3\n",
        "train(start_date = TRAIN_START_DATE, \n",
        "      end_date = TRAIN_END_DATE,\n",
        "      ticker_list = config.DOW_30_TICKER, \n",
        "      data_source = 'yahoofinance',\n",
        "      time_interval= '1D', \n",
        "      technical_indicator_list= TECHNICAL_INDICATORS_LIST,\n",
        "      drl_lib='stable_baselines3', \n",
        "      env=env, \n",
        "      agent='ppo', \n",
        "      cwd='./test_ppo',\n",
        "      total_timesteps=120000)\n"
      ],
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (49050, 9)\n",
            "Clean data for AAPL\n",
            "Data clean for AAPL is finished.\n",
            "Clean data for AXP\n",
            "Data clean for AXP is finished.\n",
            "Clean data for BA\n",
            "Data clean for BA is finished.\n",
            "Clean data for CAT\n",
            "Data clean for CAT is finished.\n",
            "Clean data for CSCO\n",
            "Data clean for CSCO is finished.\n",
            "Clean data for CVX\n",
            "Data clean for CVX is finished.\n",
            "Clean data for DD\n",
            "Data clean for DD is finished.\n",
            "Clean data for DIS\n",
            "Data clean for DIS is finished.\n",
            "Clean data for GS\n",
            "Data clean for GS is finished.\n",
            "Clean data for HD\n",
            "Data clean for HD is finished.\n",
            "Clean data for IBM\n",
            "Data clean for IBM is finished.\n",
            "Clean data for INTC\n",
            "Data clean for INTC is finished.\n",
            "Clean data for JNJ\n",
            "Data clean for JNJ is finished.\n",
            "Clean data for JPM\n",
            "Data clean for JPM is finished.\n",
            "Clean data for KO\n",
            "Data clean for KO is finished.\n",
            "Clean data for MCD\n",
            "Data clean for MCD is finished.\n",
            "Clean data for MMM\n",
            "Data clean for MMM is finished.\n",
            "Clean data for MRK\n",
            "Data clean for MRK is finished.\n",
            "Clean data for MSFT\n",
            "Data clean for MSFT is finished.\n",
            "Clean data for NKE\n",
            "Data clean for NKE is finished.\n",
            "Clean data for PFE\n",
            "Data clean for PFE is finished.\n",
            "Clean data for PG\n",
            "Data clean for PG is finished.\n",
            "Clean data for RTX\n",
            "Data clean for RTX is finished.\n",
            "Clean data for TRV\n",
            "Data clean for TRV is finished.\n",
            "Clean data for UNH\n",
            "Data clean for UNH is finished.\n",
            "Clean data for V\n",
            "Data clean for V is finished.\n",
            "Clean data for VZ\n",
            "Data clean for VZ is finished.\n",
            "Clean data for WBA\n",
            "Data clean for WBA is finished.\n",
            "Clean data for WMT\n",
            "Data clean for WMT is finished.\n",
            "Clean data for XOM\n",
            "Data clean for XOM is finished.\n",
            "Data clean all finished!\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (1635, 9)\n",
            "Clean data for ^VIX\n",
            "Data clean for ^VIX is finished.\n",
            "Data clean all finished!\n",
            "['AAPL' 'AXP' 'BA' 'CAT' 'CSCO' 'CVX' 'DD' 'DIS' 'GS' 'HD' 'IBM' 'INTC'\n",
            " 'JNJ' 'JPM' 'KO' 'MCD' 'MMM' 'MRK' 'MSFT' 'NKE' 'PFE' 'PG' 'RTX' 'TRV'\n",
            " 'UNH' 'V' 'VZ' 'WBA' 'WMT' 'XOM']\n",
            "Successfully transformed into array\n",
            "Training finished!\n",
            "Trained model saved in ./test_ppo\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TsAByoEOZn6X"
      },
      "source": [
        "### Test"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fKEYTIcLQywo",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4fee476f-ffa1-477e-8c8a-2575e4c5ae69"
      },
      "source": [
        "account_value_sb3=test(start_date = TEST_START_DATE, \n",
        "     end_date = TEST_END_DATE,\n",
        "     ticker_list = config.DOW_30_TICKER, \n",
        "     data_source = 'yahoofinance',\n",
        "     time_interval= '1D', \n",
        "     technical_indicator_list= TECHNICAL_INDICATORS_LIST, \n",
        "     drl_lib='stable_baselines3', \n",
        "     env=env, \n",
        "     agent='ppo', \n",
        "     cwd='./test_ppo.zip')"
      ],
      "execution_count": 163,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (7620, 9)\n",
            "Clean data for AAPL\n",
            "Data clean for AAPL is finished.\n",
            "Clean data for AXP\n",
            "Data clean for AXP is finished.\n",
            "Clean data for BA\n",
            "Data clean for BA is finished.\n",
            "Clean data for CAT\n",
            "Data clean for CAT is finished.\n",
            "Clean data for CSCO\n",
            "Data clean for CSCO is finished.\n",
            "Clean data for CVX\n",
            "Data clean for CVX is finished.\n",
            "Clean data for DD\n",
            "Data clean for DD is finished.\n",
            "Clean data for DIS\n",
            "Data clean for DIS is finished.\n",
            "Clean data for GS\n",
            "Data clean for GS is finished.\n",
            "Clean data for HD\n",
            "Data clean for HD is finished.\n",
            "Clean data for IBM\n",
            "Data clean for IBM is finished.\n",
            "Clean data for INTC\n",
            "Data clean for INTC is finished.\n",
            "Clean data for JNJ\n",
            "Data clean for JNJ is finished.\n",
            "Clean data for JPM\n",
            "Data clean for JPM is finished.\n",
            "Clean data for KO\n",
            "Data clean for KO is finished.\n",
            "Clean data for MCD\n",
            "Data clean for MCD is finished.\n",
            "Clean data for MMM\n",
            "Data clean for MMM is finished.\n",
            "Clean data for MRK\n",
            "Data clean for MRK is finished.\n",
            "Clean data for MSFT\n",
            "Data clean for MSFT is finished.\n",
            "Clean data for NKE\n",
            "Data clean for NKE is finished.\n",
            "Clean data for PFE\n",
            "Data clean for PFE is finished.\n",
            "Clean data for PG\n",
            "Data clean for PG is finished.\n",
            "Clean data for RTX\n",
            "Data clean for RTX is finished.\n",
            "Clean data for TRV\n",
            "Data clean for TRV is finished.\n",
            "Clean data for UNH\n",
            "Data clean for UNH is finished.\n",
            "Clean data for V\n",
            "Data clean for V is finished.\n",
            "Clean data for VZ\n",
            "Data clean for VZ is finished.\n",
            "Clean data for WBA\n",
            "Data clean for WBA is finished.\n",
            "Clean data for WMT\n",
            "Data clean for WMT is finished.\n",
            "Clean data for XOM\n",
            "Data clean for XOM is finished.\n",
            "Data clean all finished!\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (253, 9)\n",
            "Clean data for ^VIX\n",
            "Data clean for ^VIX is finished.\n",
            "Data clean all finished!\n",
            "['AAPL' 'AXP' 'BA' 'CAT' 'CSCO' 'CVX' 'DD' 'DIS' 'GS' 'HD' 'IBM' 'INTC'\n",
            " 'JNJ' 'JPM' 'KO' 'MCD' 'MMM' 'MRK' 'MSFT' 'NKE' 'PFE' 'PG' 'RTX' 'TRV'\n",
            " 'UNH' 'V' 'VZ' 'WBA' 'WMT' 'XOM']\n",
            "Successfully transformed into array\n",
            "price_array:  254\n",
            "Successfully load model ./test_ppo.zip\n",
            "episode_return 1.4421040403696015\n",
            "Test Finished!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9WcLm8nYsxeU",
        "outputId": "cd201bc1-c00e-4f56-b457-5ff57b1cf5ee"
      },
      "source": [
        "len(account_value_sb3)"
      ],
      "execution_count": 160,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "254"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 160
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FC0d-lUvj0Zk"
      },
      "source": [
        "### Plot"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uWeh-OTc0i2o",
        "outputId": "1458ace8-7f3b-4ff7-e6d1-c42c6adbb883"
      },
      "source": [
        "baseline_df =  DataProcessor('yahoofinance').download_data(ticker_list = [\"^DJI\"], \n",
        "                                                            start_date = TEST_START_DATE, \n",
        "                                                            end_date = TEST_END_DATE, \n",
        "                                                            time_interval = \"1D\")\n",
        "stats = backtest_stats(baseline_df, value_col_name = 'close')\n"
      ],
      "execution_count": 164,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (254, 9)\n",
            "Annual return          0.348511\n",
            "Cumulative returns     0.351715\n",
            "Annual volatility      0.145303\n",
            "Sharpe ratio           2.139596\n",
            "Calmar ratio           3.902364\n",
            "Stability              0.946267\n",
            "Max drawdown          -0.089308\n",
            "Omega ratio            1.427764\n",
            "Sortino ratio          3.204934\n",
            "Skew                        NaN\n",
            "Kurtosis                    NaN\n",
            "Tail ratio             1.082606\n",
            "Daily value at risk   -0.017073\n",
            "dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y1g6tAIhiPAt"
      },
      "source": [
        "account_value_sb3 = pd.DataFrame({'date':baseline_df.date,'account_value':account_value_sb3})"
      ],
      "execution_count": 165,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "YS8-OOGMtIRA",
        "outputId": "6a95c3e0-116e-4730-c69a-17f3c60b8197"
      },
      "source": [
        "account_value_sb3.tail()"
      ],
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "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>date</th>\n",
              "      <th>account_value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>249</th>\n",
              "      <td>2021-06-28</td>\n",
              "      <td>1.407617e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>250</th>\n",
              "      <td>2021-06-29</td>\n",
              "      <td>1.410353e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>251</th>\n",
              "      <td>2021-06-30</td>\n",
              "      <td>1.418238e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>252</th>\n",
              "      <td>2021-07-01</td>\n",
              "      <td>1.426484e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>253</th>\n",
              "      <td>2021-07-02</td>\n",
              "      <td>1.442104e+06</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           date  account_value\n",
              "249  2021-06-28   1.407617e+06\n",
              "250  2021-06-29   1.410353e+06\n",
              "251  2021-06-30   1.418238e+06\n",
              "252  2021-07-01   1.426484e+06\n",
              "253  2021-07-02   1.442104e+06"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "WtSWdl57kDlx",
        "outputId": "48b6bbea-c320-42c3-d80f-f19b51bbec4e"
      },
      "source": [
        "print(\"==============Compare to DJIA===========\")\n",
        "#%matplotlib inline\n",
        "# S&P 500: ^GSPC\n",
        "# Dow Jones Index: ^DJI\n",
        "# NASDAQ 100: ^NDX\n",
        "backtest_plot(account_value_sb3, \n",
        "             baseline_ticker = '^DJI', \n",
        "             baseline_start = account_value_sb3.loc[0,'date'],\n",
        "             baseline_end = account_value_sb3.loc[len(account_value_sb3)-1,'date'])"
      ],
      "execution_count": 166,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Compare to DJIA===========\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (253, 8)\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\"><th>Start date</th><td colspan=2>2020-07-01</td></tr>\n",
              "    <tr style=\"text-align: right;\"><th>End date</th><td colspan=2>2021-07-01</td></tr>\n",
              "    <tr style=\"text-align: right;\"><th>Total months</th><td colspan=2>12</td></tr>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Backtest</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Annual return</th>\n",
              "      <td>42.448%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Cumulative returns</th>\n",
              "      <td>42.648%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Annual volatility</th>\n",
              "      <td>19.832%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sharpe ratio</th>\n",
              "      <td>1.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Calmar ratio</th>\n",
              "      <td>3.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Stability</th>\n",
              "      <td>0.92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Max drawdown</th>\n",
              "      <td>-12.265%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Omega ratio</th>\n",
              "      <td>1.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sortino ratio</th>\n",
              "      <td>2.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Skew</th>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kurtosis</th>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tail ratio</th>\n",
              "      <td>1.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Daily value at risk</th>\n",
              "      <td>-2.35%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alpha</th>\n",
              "      <td>0.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Beta</th>\n",
              "      <td>1.15</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>Worst drawdown periods</th>\n",
              "      <th>Net drawdown in %</th>\n",
              "      <th>Peak date</th>\n",
              "      <th>Valley date</th>\n",
              "      <th>Recovery date</th>\n",
              "      <th>Duration</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>12.26</td>\n",
              "      <td>2020-09-02</td>\n",
              "      <td>2020-10-30</td>\n",
              "      <td>2020-11-10</td>\n",
              "      <td>50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>5.58</td>\n",
              "      <td>2021-01-22</td>\n",
              "      <td>2021-01-29</td>\n",
              "      <td>2021-02-08</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>5.28</td>\n",
              "      <td>2021-03-15</td>\n",
              "      <td>2021-03-24</td>\n",
              "      <td>2021-04-05</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.83</td>\n",
              "      <td>2021-05-07</td>\n",
              "      <td>2021-05-12</td>\n",
              "      <td>2021-06-01</td>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3.90</td>\n",
              "      <td>2021-02-24</td>\n",
              "      <td>2021-02-26</td>\n",
              "      <td>2021-03-05</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pyfolio/tears.py:907: UserWarning: Passed returns do not overlap with anyinteresting times.\n",
            "  'interesting times.', UserWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x5184 with 13 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}