FinRL_single_stock_trading.ipynb

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        "<a href=\"https://colab.research.google.com/github/AI4Finance-LLC/FinRL-Library/blob/master/FinRL_single_stock_trading.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "# Deep Reinforcement Learning for Stock Trading from Scratch: Single Stock Trading\n",
        "\n",
        "Tutorials to use OpenAI DRL to trade single stock in one Jupyter Notebook | Presented at NeurIPS 2020: Deep RL Workshop\n",
        "\n",
        "* This blog is based on our paper: FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance, presented at NeurIPS 2020: Deep RL Workshop.\n",
        "* Check out medium blog for detailed explanations: https://towardsdatascience.com/finrl-for-quantitative-finance-tutorial-for-single-stock-trading-37d6d7c30aac\n",
        "* Please report any issues to our Github: https://github.com/AI4Finance-LLC/FinRL-Library/issues\n",
        "* **Pytorch Version** \n",
        "\n",
        "\n"
      ]
    },
    {
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      "source": [
        "## Content"
      ]
    },
    {
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      "metadata": {
        "id": "ex2ord116AbP"
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      "source": [
        "* [1. Problem Definition](#0)\n",
        "* [2. Getting Started - Load Python packages](#1)\n",
        "    * [2.1. Install Packages](#1.1)    \n",
        "    * [2.2. Check Additional Packages](#1.2)\n",
        "    * [2.3. Import Packages](#1.3)\n",
        "    * [2.4. Create Folders](#1.4)\n",
        "* [3. Download Data](#2)\n",
        "* [4. Preprocess Data](#3)        \n",
        "    * [4.1. Technical Indicators](#3.1)\n",
        "    * [4.2. Perform Feature Engineering](#3.2)\n",
        "* [5.Build Environment](#4)  \n",
        "    * [5.1. Training & Trade Data Split](#4.1)\n",
        "    * [5.2. User-defined Environment](#4.2)   \n",
        "    * [5.3. Initialize Environment](#4.3)    \n",
        "* [6.Implement DRL Algorithms](#5)  \n",
        "* [7.Backtesting Performance](#6)  \n",
        "    * [7.1. BackTestStats](#6.1)\n",
        "    * [7.2. BackTestPlot](#6.2)   \n",
        "    * [7.3. Baseline Stats](#6.3)   \n",
        "    * [7.3. Compare to Stock Market Index](#6.4)             "
      ]
    },
    {
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      "metadata": {
        "id": "M1eLhMW36cLi"
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      "source": [
        "<a id='0'></a>\n",
        "# Part 1. Problem Definition"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3eimeRv06YoK"
      },
      "source": [
        "This problem is to design an automated trading solution for single stock trading. We model the stock trading process as a Markov Decision Process (MDP). We then formulate our trading goal as a maximization problem.\n",
        "\n",
        "The components of the reinforcement learning environment are:\n",
        "\n",
        "\n",
        "* Action: The action space describes the allowed actions that the agent interacts with the\n",
        "environment. Normally, a ∈ A includes three actions: a ∈ {−1, 0, 1}, where −1, 0, 1 represent\n",
        "selling, holding, and buying one stock. Also, an action can be carried upon multiple shares. We use\n",
        "an action space {−k, ..., −1, 0, 1, ..., k}, where k denotes the number of shares. For example, \"Buy\n",
        "10 shares of AAPL\" or \"Sell 10 shares of AAPL\" are 10 or −10, respectively\n",
        "\n",
        "* Reward function: r(s, a, s′) is the incentive mechanism for an agent to learn a better action. The change of the portfolio value when action a is taken at state s and arriving at new state s',  i.e., r(s, a, s′) = v′ − v, where v′ and v represent the portfolio\n",
        "values at state s′ and s, respectively\n",
        "\n",
        "* State: The state space describes the observations that the agent receives from the environment. Just as a human trader needs to analyze various information before executing a trade, so\n",
        "our trading agent observes many different features to better learn in an interactive environment.\n",
        "\n",
        "* Environment: single stock trading for AAPL\n",
        "\n",
        "\n",
        "The data of the single stock that we will be using for this case study is obtained from Yahoo Finance API. The data contains Open-High-Low-Close price and volume.\n",
        "\n",
        "We use Apple Inc. stock: AAPL as an example throughout this article, because it is one of the most popular and profitable stocks."
      ]
    },
    {
      "cell_type": "markdown",
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      "source": [
        "<a id='1'></a>\n",
        "# Part 2. Getting Started- Load Python Packages"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UBUcBKap-oII"
      },
      "source": [
        "<a id='1.1'></a>\n",
        "## 2.1. Install all the packages through FinRL library\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "40axJBAP5mer",
        "outputId": "ee6aa160-1c1e-42b2-c4bc-19107f618ab5"
      },
      "source": [
        "## install finrl library\n",
        "!pip install git+https://github.com/AI4Finance-LLC/FinRL-Library.git"
      ],
      "execution_count": 1,
      "outputs": [
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            "Building wheels for collected packages: finrl, yfinance, pyfolio, empyrical\n",
            "  Building wheel for finrl (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for finrl: filename=finrl-0.0.1-cp36-none-any.whl size=26666 sha256=abb468fd26bb910eab8b7ebeb7948823c1ab39a37d6abfa0123ead84616a1c5c\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-wseqaaeo/wheels/9c/19/bf/c644def96612df1ad42c94d5304966797eaa3221dffc5efe0b\n",
            "  Building wheel for yfinance (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for yfinance: filename=yfinance-0.1.55-py2.py3-none-any.whl size=22616 sha256=0fa721f3afdbbecbd4e8c911eba1ab74528875935317f861371fa34444fc02b8\n",
            "  Stored in directory: /root/.cache/pip/wheels/04/98/cc/2702a4242d60bdc14f48b4557c427ded1fe92aedf257d4565c\n",
            "  Building wheel for pyfolio (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pyfolio: filename=pyfolio-0.9.2+75.g4b901f6-cp36-none-any.whl size=75764 sha256=a99d4fa9b215d67f0d23067c36cae9f78f7c9d5b406ea79acfaad2a552dc7aad\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-wseqaaeo/wheels/43/ce/d9/6752fb6e03205408773235435205a0519d2c608a94f1976e56\n",
            "  Building wheel for empyrical (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for empyrical: filename=empyrical-0.5.5-cp36-none-any.whl size=39765 sha256=ae96e8a3e63385c1fe7b48f6af9c525d810bed468855c32dacfb412ba907b42a\n",
            "  Stored in directory: /root/.cache/pip/wheels/ea/b2/c8/6769d8444d2f2e608fae2641833110668d0ffd1abeb2e9f3fc\n",
            "Successfully built finrl yfinance pyfolio empyrical\n",
            "Installing collected packages: int-date, stockstats, lxml, yfinance, stable-baselines3, empyrical, pyfolio, finrl\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-0.0.1 int-date-0.1.8 lxml-4.6.2 pyfolio-0.9.2+75.g4b901f6 stable-baselines3-0.10.0 stockstats-0.3.2 yfinance-0.1.55\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iXyHD6ir5sxk"
      },
      "source": [
        "\n",
        "<a id='1.2'></a>\n",
        "## 2.2. Check if the additional packages needed are present, if not install them. \n",
        "* Yahoo Finance API\n",
        "* pandas\n",
        "* numpy\n",
        "* matplotlib\n",
        "* stockstats\n",
        "* OpenAI gym\n",
        "* stable-baselines\n",
        "* tensorflow\n",
        "* pyfolio"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jeFTP-XzTnSV",
        "outputId": "4accc963-9f26-483d-fb48-361ee26964b0"
      },
      "source": [
        "import pkg_resources\n",
        "import pip\n",
        "installedPackages = {pkg.key for pkg in pkg_resources.working_set}\n",
        "required = {'yfinance', 'pandas', 'matplotlib', 'stockstats','stable-baselines','gym','tensorflow'}\n",
        "missing = required - installedPackages\n",
        "if missing:\n",
        "    !pip install yfinance\n",
        "    !pip install pandas\n",
        "    !pip install matplotlib\n",
        "    !pip install stockstats\n",
        "    !pip install gym\n",
        "    !pip install stable-baselines3[extra]\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
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            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.6/dist-packages (from importlib-metadata; python_version < \"3.8\"->markdown>=2.6.8->tensorboard<1.16.0,>=1.15.0->tensorflow==1.15.4) (3.4.0)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QG17M4JwTnSZ"
      },
      "source": [
        "<a id='1.3'></a>\n",
        "## 2.3. Import Packages"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0-0bsNMMTnSZ",
        "outputId": "27a43daa-8886-4a7e-cb75-7606404f3662"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib\n",
        "import matplotlib.pyplot as plt\n",
        "matplotlib.use('Agg')\n",
        "import datetime\n",
        "\n",
        "from finrl.config import config\n",
        "from finrl.marketdata.yahoodownloader import YahooDownloader\n",
        "from finrl.preprocessing.preprocessors import FeatureEngineer\n",
        "from finrl.preprocessing.data import data_split\n",
        "from finrl.env.environment import EnvSetup\n",
        "from finrl.env.EnvMultipleStock_train import StockEnvTrain\n",
        "from finrl.env.EnvMultipleStock_trade import StockEnvTrade\n",
        "from finrl.model.models import DRLAgent\n",
        "from finrl.trade.backtest import BackTestStats, BaselineStats, BackTestPlot\n",
        "\n"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/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": "code",
      "metadata": {
        "id": "uIPbzYs1TnSd"
      },
      "source": [
        "#Diable the warnings\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pos2IZAL54pp"
      },
      "source": [
        "<a id='1.4'></a>\n",
        "## 2.4. Create Folders"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zp6lL6dZ53rX"
      },
      "source": [
        "import os\n",
        "if not os.path.exists(\"./\" + config.DATA_SAVE_DIR):\n",
        "    os.makedirs(\"./\" + config.DATA_SAVE_DIR)\n",
        "if not os.path.exists(\"./\" + config.TRAINED_MODEL_DIR):\n",
        "    os.makedirs(\"./\" + config.TRAINED_MODEL_DIR)\n",
        "if not os.path.exists(\"./\" + config.TENSORBOARD_LOG_DIR):\n",
        "    os.makedirs(\"./\" + config.TENSORBOARD_LOG_DIR)\n",
        "if not os.path.exists(\"./\" + config.RESULTS_DIR):\n",
        "    os.makedirs(\"./\" + config.RESULTS_DIR)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SBPM0sVvTnSg"
      },
      "source": [
        "<a id='2'></a>\n",
        "# Part 3. Download Data\n",
        "Yahoo Finance is a website that provides stock data, financial news, financial reports, etc. All the data provided by Yahoo Finance is free.\n",
        "* FinRL uses a class **YahooDownloader** to fetch data from Yahoo Finance API\n",
        "* Call Limit: Using the Public API (without authentication), you are limited to 2,000 requests per hour per IP (or up to a total of 48,000 requests a day).\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GCGVmtGzjORf"
      },
      "source": [
        "\n",
        "\n",
        "-----\n",
        "class YahooDownloader:\n",
        "    Provides methods for retrieving daily stock data from\n",
        "    Yahoo Finance API\n",
        "\n",
        "    Attributes\n",
        "    ----------\n",
        "        start_date : str\n",
        "            start date of the data (modified from config.py)\n",
        "        end_date : str\n",
        "            end date of the data (modified from config.py)\n",
        "        ticker_list : list\n",
        "            a list of stock tickers (modified from config.py)\n",
        "\n",
        "    Methods\n",
        "    -------\n",
        "    fetch_data()\n",
        "        Fetches data from yahoo API\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "FBEiH5gOgMOx",
        "outputId": "de388576-0110-46f4-9257-dfe327b3eac5"
      },
      "source": [
        "# from config.py start_date is a string\n",
        "config.START_DATE"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'2009-01-01'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "sWLMNQ8CgMRx",
        "outputId": "f1864c8b-2b5c-4867-9122-ccf83ebc2902"
      },
      "source": [
        "# from config.py end_date is a string\n",
        "config.END_DATE"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'2020-09-30'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AmFpuBEZhkF3"
      },
      "source": [
        "ticker_list is a list of stock tickers, in a single stock trading case, the list contains only 1 ticker"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JtIFikNyTnSg",
        "outputId": "b0dc95d0-d502-4e85-a8ee-6269352411c1"
      },
      "source": [
        "# Download and save the data in a pandas DataFrame:\n",
        "data_df = YahooDownloader(start_date = '2009-01-01',\n",
        "                          end_date = '2020-12-01',\n",
        "                          ticker_list = ['AAPL']).fetch_data()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (2999, 7)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E8ZKQmw6TnSl",
        "outputId": "8e5ec6ec-2210-43e9-c832-dd4118d3be03"
      },
      "source": [
        "data_df.shape"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2999, 7)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "id": "Vi6D_ED6TnSs",
        "outputId": "4ae45e6c-7071-480c-fd26-b01b25d01466"
      },
      "source": [
        "data_df.head()"
      ],
      "execution_count": 7,
      "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>open</th>\n",
              "      <th>high</th>\n",
              "      <th>low</th>\n",
              "      <th>close</th>\n",
              "      <th>volume</th>\n",
              "      <th>tic</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2009-01-02</td>\n",
              "      <td>3.067143</td>\n",
              "      <td>3.251429</td>\n",
              "      <td>3.041429</td>\n",
              "      <td>2.795913</td>\n",
              "      <td>746015200</td>\n",
              "      <td>AAPL</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2009-01-05</td>\n",
              "      <td>3.327500</td>\n",
              "      <td>3.435000</td>\n",
              "      <td>3.311071</td>\n",
              "      <td>2.913912</td>\n",
              "      <td>1181608400</td>\n",
              "      <td>AAPL</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2009-01-06</td>\n",
              "      <td>3.426786</td>\n",
              "      <td>3.470357</td>\n",
              "      <td>3.299643</td>\n",
              "      <td>2.865849</td>\n",
              "      <td>1289310400</td>\n",
              "      <td>AAPL</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2009-01-07</td>\n",
              "      <td>3.278929</td>\n",
              "      <td>3.303571</td>\n",
              "      <td>3.223572</td>\n",
              "      <td>2.803923</td>\n",
              "      <td>753048800</td>\n",
              "      <td>AAPL</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2009-01-08</td>\n",
              "      <td>3.229643</td>\n",
              "      <td>3.326786</td>\n",
              "      <td>3.215714</td>\n",
              "      <td>2.855991</td>\n",
              "      <td>673500800</td>\n",
              "      <td>AAPL</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         date      open      high       low     close      volume   tic\n",
              "0  2009-01-02  3.067143  3.251429  3.041429  2.795913   746015200  AAPL\n",
              "1  2009-01-05  3.327500  3.435000  3.311071  2.913912  1181608400  AAPL\n",
              "2  2009-01-06  3.426786  3.470357  3.299643  2.865849  1289310400  AAPL\n",
              "3  2009-01-07  3.278929  3.303571  3.223572  2.803923   753048800  AAPL\n",
              "4  2009-01-08  3.229643  3.326786  3.215714  2.855991   673500800  AAPL"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oWiqgpLzTnS3"
      },
      "source": [
        "<a id='3'></a>\n",
        "# Part 4. Preprocess Data\n",
        "Data preprocessing is a crucial step for training a high quality machine learning model. We need to check for missing data and do feature engineering in order to convert the data into a model-ready state.\n",
        "* FinRL uses a class **FeatureEngineer** to preprocess the data\n",
        "* Add **technical indicators**. In practical trading, various information needs to be taken into account, for example the historical stock prices, current holding shares, technical indicators, etc.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rJ9zmxpRks41"
      },
      "source": [
        "class FeatureEngineer:\n",
        "Provides methods for preprocessing the stock price data\n",
        "\n",
        "    Attributes\n",
        "    ----------\n",
        "        df: DataFrame\n",
        "            data downloaded from Yahoo API\n",
        "        feature_number : int\n",
        "            number of features we used\n",
        "        use_technical_indicator : boolean\n",
        "            we technical indicator or not\n",
        "        use_turbulence : boolean\n",
        "            use turbulence index or not\n",
        "\n",
        "    Methods\n",
        "    -------\n",
        "    preprocess_data()\n",
        "        main method to do the feature engineering"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tHu7i-T_wRPc"
      },
      "source": [
        "<a id='3.1'></a>\n",
        "\n",
        "## 4.1 Technical Indicators\n",
        "* FinRL uses stockstats to calcualte technical indicators such as **Moving Average Convergence Divergence (MACD)**, **Relative Strength Index (RSI)**, **Average Directional Index (ADX)**, **Commodity Channel Index (CCI)** and other various indicators and stats.\n",
        "* **stockstats**: supplies a wrapper StockDataFrame based on the **pandas.DataFrame** with inline stock statistics/indicators support.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2RHwY1dHk09N",
        "outputId": "c1f338a7-7594-46ec-889b-5bfc2c328fd3"
      },
      "source": [
        "## we store the stockstats technical indicator column names in config.py\n",
        "tech_indicator_list=config.TECHNICAL_INDICATORS_LIST\n",
        "print(tech_indicator_list)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['macd', 'rsi_30', 'cci_30', 'dx_30']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rImfGAfCkR8j",
        "outputId": "459bd912-adea-43eb-c14d-71b4481a6677"
      },
      "source": [
        "## user can add more technical indicators\n",
        "## check https://github.com/jealous/stockstats for different names\n",
        "tech_indicator_list=tech_indicator_list+['kdjk','open_2_sma','boll','close_10.0_le_5_c','wr_10','dma','trix']\n",
        "print(tech_indicator_list)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['macd', 'rsi_30', 'cci_30', 'dx_30', 'kdjk', 'open_2_sma', 'boll', 'close_10.0_le_5_c', 'wr_10', 'dma', 'trix']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "etvRo2rSwZPg"
      },
      "source": [
        "<a id='3.2'></a>\n",
        "## 4.2 Perform Feature Engineering"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7EQlXSl1TnS4",
        "outputId": "493a0c60-938f-42ed-d682-ca4dc1dbf316"
      },
      "source": [
        "data_df = FeatureEngineer(data_df.copy(),\n",
        "                          use_technical_indicator=True,\n",
        "                          tech_indicator_list = tech_indicator_list,\n",
        "                          use_turbulence=False,\n",
        "                          user_defined_feature = True).preprocess_data()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Successfully added technical indicators\n",
            "Successfully added user defined features\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "wytX_qwWMHP5",
        "outputId": "30093945-735b-4c73-ccb7-35901cd32fc1"
      },
      "source": [
        "data_df.head()"
      ],
      "execution_count": 14,
      "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>open</th>\n",
              "      <th>high</th>\n",
              "      <th>low</th>\n",
              "      <th>close</th>\n",
              "      <th>volume</th>\n",
              "      <th>tic</th>\n",
              "      <th>macd</th>\n",
              "      <th>rsi_30</th>\n",
              "      <th>cci_30</th>\n",
              "      <th>dx_30</th>\n",
              "      <th>kdjk</th>\n",
              "      <th>open_2_sma</th>\n",
              "      <th>boll</th>\n",
              "      <th>close_10.0_le_5_c</th>\n",
              "      <th>wr_10</th>\n",
              "      <th>dma</th>\n",
              "      <th>trix</th>\n",
              "      <th>daily_return</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2009-01-02</td>\n",
              "      <td>3.067143</td>\n",
              "      <td>3.251429</td>\n",
              "      <td>3.041429</td>\n",
              "      <td>2.795913</td>\n",
              "      <td>746015200</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>66.666667</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>-5.637387</td>\n",
              "      <td>3.067143</td>\n",
              "      <td>2.795913</td>\n",
              "      <td>1.0</td>\n",
              "      <td>216.912162</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.670734</td>\n",
              "      <td>0.042204</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2009-01-05</td>\n",
              "      <td>3.327500</td>\n",
              "      <td>3.435000</td>\n",
              "      <td>3.311071</td>\n",
              "      <td>2.913912</td>\n",
              "      <td>1181608400</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>0.002647</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>66.666667</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>-14.558226</td>\n",
              "      <td>3.197322</td>\n",
              "      <td>2.854912</td>\n",
              "      <td>2.0</td>\n",
              "      <td>132.399904</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.670734</td>\n",
              "      <td>0.042204</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2009-01-06</td>\n",
              "      <td>3.426786</td>\n",
              "      <td>3.470357</td>\n",
              "      <td>3.299643</td>\n",
              "      <td>2.865849</td>\n",
              "      <td>1289310400</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>0.001883</td>\n",
              "      <td>70.355297</td>\n",
              "      <td>46.762875</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>-23.350262</td>\n",
              "      <td>3.377143</td>\n",
              "      <td>2.858558</td>\n",
              "      <td>3.0</td>\n",
              "      <td>140.934334</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.391303</td>\n",
              "      <td>-0.016494</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2009-01-07</td>\n",
              "      <td>3.278929</td>\n",
              "      <td>3.303571</td>\n",
              "      <td>3.223572</td>\n",
              "      <td>2.803923</td>\n",
              "      <td>753048800</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>-0.000747</td>\n",
              "      <td>50.429222</td>\n",
              "      <td>-29.787322</td>\n",
              "      <td>43.608349</td>\n",
              "      <td>-34.024085</td>\n",
              "      <td>3.352857</td>\n",
              "      <td>2.844899</td>\n",
              "      <td>4.0</td>\n",
              "      <td>155.371731</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.195391</td>\n",
              "      <td>-0.021608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2009-01-08</td>\n",
              "      <td>3.229643</td>\n",
              "      <td>3.326786</td>\n",
              "      <td>3.215714</td>\n",
              "      <td>2.855991</td>\n",
              "      <td>673500800</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>-0.000088</td>\n",
              "      <td>60.227071</td>\n",
              "      <td>-9.011779</td>\n",
              "      <td>48.358256</td>\n",
              "      <td>-37.093625</td>\n",
              "      <td>3.254286</td>\n",
              "      <td>2.847118</td>\n",
              "      <td>5.0</td>\n",
              "      <td>143.232705</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.125124</td>\n",
              "      <td>0.018570</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         date      open      high  ...  dma      trix  daily_return\n",
              "0  2009-01-02  3.067143  3.251429  ...  0.0  0.670734      0.042204\n",
              "1  2009-01-05  3.327500  3.435000  ...  0.0  0.670734      0.042204\n",
              "2  2009-01-06  3.426786  3.470357  ...  0.0  0.391303     -0.016494\n",
              "3  2009-01-07  3.278929  3.303571  ...  0.0  0.195391     -0.021608\n",
              "4  2009-01-08  3.229643  3.326786  ...  0.0  0.125124      0.018570\n",
              "\n",
              "[5 rows x 19 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bwLhXo1cTnTQ"
      },
      "source": [
        "<a id='4'></a>\n",
        "# Part 5. Build Environment\n",
        "Considering the stochastic and interactive nature of the automated stock trading tasks, a financial task is modeled as a **Markov Decision Process (MDP)** problem. The training process involves observing stock price change, taking an action and reward's calculation to have the agent adjusting its strategy accordingly. By interacting with the environment, the trading agent will derive a trading strategy with the maximized rewards as time proceeds.\n",
        "\n",
        "Our trading environments, based on OpenAI Gym framework, simulate live stock markets with real market data according to the principle of time-driven simulation.\n",
        "\n",
        "The action space describes the allowed actions that the agent interacts with the environment. Normally, action a includes three actions: {-1, 0, 1}, where -1, 0, 1 represent selling, holding, and buying one share. Also, an action can be carried upon multiple shares. We use an action space {-k,…,-1, 0, 1, …, k}, where k denotes the number of shares to buy and -k denotes the number of shares to sell. For example, \"Buy 10 shares of AAPL\" or \"Sell 10 shares of AAPL\" are 10 or -10, respectively. The continuous action space needs to be normalized to [-1, 1], since the policy is defined on a Gaussian distribution, which needs to be normalized and symmetric."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1D1FlBdOL4b3"
      },
      "source": [
        "<a id='4.1'></a>\n",
        "## 5.1 Training & Trade data split\n",
        "* Training: 2009-01-01 to 2018-12-31\n",
        "* Trade: 2019-01-01 to 2020-09-30"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xNOdqfTKL6K-"
      },
      "source": [
        "#train = data_split(data_df, start = config.START_DATE, end = config.START_TRADE_DATE)\n",
        "#trade = data_split(data_df, start = config.START_TRADE_DATE, end = config.END_DATE)\n",
        "train = data_split(data_df, start = '2009-01-01', end = '2019-01-01')\n",
        "trade = data_split(data_df, start = '2019-01-01', end = '2020-12-01')\n"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KUxOshVouLXt"
      },
      "source": [
        "## data normalization, this part is optional, have little impact\n",
        "#feaures_list = list(train.columns)\n",
        "#feaures_list.remove('date')\n",
        "#feaures_list.remove('tic')\n",
        "#feaures_list.remove('close')\n",
        "#print(feaures_list)\n",
        "#from sklearn import preprocessing\n",
        "#data_normaliser = preprocessing.StandardScaler()\n",
        "#train[feaures_list] = data_normaliser.fit_transform(train[feaures_list])\n",
        "#trade[feaures_list] = data_normaliser.transform(trade[feaures_list])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KMHyaSBBDGbe"
      },
      "source": [
        "<a id='4.2'></a>\n",
        "## 5.2 User-defined Environment: a simulation environment class "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5qqW-mnSTnTQ"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from gym.utils import seeding\n",
        "import gym\n",
        "from gym import spaces\n",
        "import matplotlib\n",
        "matplotlib.use('Agg')\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "class SingleStockEnv(gym.Env):\n",
        "    \"\"\"A single stock trading environment for OpenAI gym\n",
        "\n",
        "    Attributes\n",
        "    ----------\n",
        "        df: DataFrame\n",
        "            input data\n",
        "        stock_dim : int\n",
        "            number of unique stocks\n",
        "        hmax : int\n",
        "            maximum number of shares to trade\n",
        "        initial_amount : int\n",
        "            start money\n",
        "        transaction_cost_pct: float\n",
        "            transaction cost percentage per trade\n",
        "        reward_scaling: float\n",
        "            scaling factor for reward, good for training\n",
        "        state_space: int\n",
        "            the dimension of input features\n",
        "        action_space: int\n",
        "            equals stock dimension\n",
        "        tech_indicator_list: list\n",
        "            a list of technical indicator names\n",
        "        turbulence_threshold: int\n",
        "            a threshold to control risk aversion\n",
        "        day: int\n",
        "            an increment number to control date\n",
        "\n",
        "    Methods\n",
        "    -------\n",
        "    _sell_stock()\n",
        "        perform sell action based on the sign of the action\n",
        "    _buy_stock()\n",
        "        perform buy action based on the sign of the action\n",
        "    step()\n",
        "        at each step the agent will return actions, then \n",
        "        we will calculate the reward, and return the next observation.\n",
        "    reset()\n",
        "        reset the environment\n",
        "    render()\n",
        "        use render to return other functions\n",
        "    save_asset_memory()\n",
        "        return account value at each time step\n",
        "    save_action_memory()\n",
        "        return actions/positions at each time step\n",
        "        \n",
        "\n",
        "    \"\"\"\n",
        "    metadata = {'render.modes': ['human']}\n",
        "\n",
        "    def __init__(self, \n",
        "                df,\n",
        "                stock_dim,\n",
        "                hmax,\n",
        "                initial_amount,\n",
        "                transaction_cost_pct,\n",
        "                reward_scaling,\n",
        "                state_space,\n",
        "                action_space,\n",
        "                tech_indicator_list,\n",
        "                turbulence_threshold,\n",
        "                day = 0):\n",
        "        #super(StockEnv, self).__init__()\n",
        "        #money = 10 , scope = 1\n",
        "        self.day = day\n",
        "        self.df = df\n",
        "        self.stock_dim = stock_dim\n",
        "        self.hmax = hmax\n",
        "        self.initial_amount = initial_amount\n",
        "        self.transaction_cost_pct =transaction_cost_pct\n",
        "        self.reward_scaling = reward_scaling\n",
        "        self.state_space = state_space\n",
        "        self.action_space = action_space\n",
        "        self.tech_indicator_list = tech_indicator_list\n",
        "\n",
        "        # action_space normalization and shape is self.stock_dim\n",
        "        self.action_space = spaces.Box(low = -1, high = 1,shape = (self.action_space,)) \n",
        "        # Shape = 181: [Current Balance]+[prices 1-30]+[owned shares 1-30] \n",
        "        # +[macd 1-30]+ [rsi 1-30] + [cci 1-30] + [adx 1-30]\n",
        "        self.observation_space = spaces.Box(low=0, high=np.inf, shape = (self.state_space,))\n",
        "        # load data from a pandas dataframe\n",
        "        self.data = self.df.loc[self.day,:]\n",
        "        self.terminal = False     \n",
        "        self.turbulence_threshold = turbulence_threshold        \n",
        "        # initalize state: inital amount + close price + shares + technical indicators + other features\n",
        "        self.state = [self.initial_amount] + \\\n",
        "                      [self.data.close] + \\\n",
        "                      [0]*self.stock_dim  + \\\n",
        "                      sum([[self.data[tech]] for tech in self.tech_indicator_list ], [])+ \\\n",
        "                      [self.data.open] + \\\n",
        "                      [self.data.high] + \\\n",
        "                      [self.data.low] +\\\n",
        "                      [self.data.daily_return] \n",
        "        # initialize reward\n",
        "        self.reward = 0\n",
        "        self.cost = 0\n",
        "        # memorize all the total balance change\n",
        "        self.asset_memory = [self.initial_amount]\n",
        "        self.rewards_memory = []\n",
        "        self.actions_memory=[]\n",
        "        self.date_memory=[self.data.date]\n",
        "        self.close_price_memory = [self.data.close]\n",
        "        self.trades = 0\n",
        "        self._seed()\n",
        "\n",
        "\n",
        "    def _sell_stock(self, index, action):\n",
        "        # perform sell action based on the sign of the action\n",
        "        if self.state[index+self.stock_dim+1] > 0:\n",
        "            #update balance\n",
        "            self.state[0] += \\\n",
        "            self.state[index+1]*min(abs(action),self.state[index+self.stock_dim+1]) * \\\n",
        "             (1- self.transaction_cost_pct)\n",
        "\n",
        "            self.state[index+self.stock_dim+1] -= min(abs(action), self.state[index+self.stock_dim+1])\n",
        "            self.cost +=self.state[index+1]*min(abs(action),self.state[index+self.stock_dim+1]) * \\\n",
        "             self.transaction_cost_pct\n",
        "            self.trades+=1\n",
        "        else:\n",
        "            pass\n",
        "\n",
        "    \n",
        "    def _buy_stock(self, index, action):\n",
        "        # perform buy action based on the sign of the action\n",
        "        available_amount = self.state[0] // self.state[index+1]\n",
        "        # print('available_amount:{}'.format(available_amount))\n",
        "\n",
        "        #update balance\n",
        "        self.state[0] -= self.state[index+1]*min(available_amount, action)* \\\n",
        "                          (1+ self.transaction_cost_pct)\n",
        "\n",
        "        self.state[index+self.stock_dim+1] += min(available_amount, action)\n",
        "\n",
        "        self.cost+=self.state[index+1]*min(available_amount, action)* \\\n",
        "                          self.transaction_cost_pct\n",
        "        self.trades+=1\n",
        "        \n",
        "    def step(self, actions):\n",
        "        # print(self.day)\n",
        "        self.terminal = self.day >= len(self.df.index.unique())-1\n",
        "        # print(actions)\n",
        "\n",
        "        if self.terminal:\n",
        "            #plt.plot(self.asset_memory,'r')\n",
        "            #plt.savefig('results/account_value_train.png')\n",
        "            #plt.close()\n",
        "            end_total_asset = self.state[0]+ \\\n",
        "                sum(np.array(self.state[1:(self.stock_dim+1)])*np.array(self.state[(self.stock_dim+1):(self.stock_dim*2+1)]))\n",
        "\n",
        "            print(\"begin_total_asset:{}\".format(self.asset_memory[0]))           \n",
        "            print(\"end_total_asset:{}\".format(end_total_asset))\n",
        "            df_total_value = pd.DataFrame(self.asset_memory)\n",
        "            #df_total_value.to_csv('results/account_value_train.csv')\n",
        "            print(\"total_reward:{}\".format(self.state[0]+sum(np.array(self.state[1:(self.stock_dim+1)])*np.array(self.state[(self.stock_dim+1):(self.stock_dim*2+1)]))- self.initial_amount ))\n",
        "            print(\"total_cost: \", self.cost)\n",
        "            print(\"total_trades: \", self.trades)\n",
        "            df_total_value.columns = ['account_value']\n",
        "            df_total_value['daily_return']=df_total_value.pct_change(1)\n",
        "            if df_total_value['daily_return'].std() !=0:\n",
        "              sharpe = (252**0.5)*df_total_value['daily_return'].mean()/ \\\n",
        "                    df_total_value['daily_return'].std()\n",
        "              print(\"Sharpe: \",sharpe)\n",
        "              print(\"=================================\")\n",
        "            df_rewards = pd.DataFrame(self.rewards_memory)\n",
        "            #df_rewards.to_csv('results/account_rewards_train.csv')\n",
        "            \n",
        "            \n",
        "            return self.state, self.reward, self.terminal,{}\n",
        "\n",
        "        else:\n",
        "            #print(actions)\n",
        "            actions = actions * self.hmax\n",
        "            #print(actions)\n",
        "            self.actions_memory.append(actions)\n",
        "            #actions = (actions.astype(int))\n",
        "            \n",
        "            begin_total_asset = self.state[0]+ \\\n",
        "            sum(np.array(self.state[1:(self.stock_dim+1)])*np.array(self.state[(self.stock_dim+1):(self.stock_dim*2+1)]))\n",
        "            #print(\"begin_total_asset:{}\".format(begin_total_asset))\n",
        "            \n",
        "            argsort_actions = np.argsort(actions)\n",
        "            \n",
        "            sell_index = argsort_actions[:np.where(actions < 0)[0].shape[0]]\n",
        "            buy_index = argsort_actions[::-1][:np.where(actions > 0)[0].shape[0]]\n",
        "\n",
        "            for index in sell_index:\n",
        "                # print('take sell action'.format(actions[index]))\n",
        "                self._sell_stock(index, actions[index])\n",
        "\n",
        "            for index in buy_index:\n",
        "                # print('take buy action: {}'.format(actions[index]))\n",
        "                self._buy_stock(index, actions[index])\n",
        "\n",
        "            self.day += 1\n",
        "            self.data = self.df.loc[self.day,:]         \n",
        "            #load next state\n",
        "            # print(\"stock_shares:{}\".format(self.state[29:]))\n",
        "            self.state =  [self.state[0]] + \\\n",
        "                    [self.data.close] + \\\n",
        "                    list(self.state[(self.stock_dim+1):(self.stock_dim*2+1)]) + \\\n",
        "                      sum([[self.data[tech]] for tech in self.tech_indicator_list ], [])+ \\\n",
        "                      [self.data.open] + \\\n",
        "                      [self.data.high] + \\\n",
        "                      [self.data.low] +\\\n",
        "                      [self.data.daily_return] \n",
        "            \n",
        "            end_total_asset = self.state[0]+ \\\n",
        "            sum(np.array(self.state[1:(self.stock_dim+1)])*np.array(self.state[(self.stock_dim+1):(self.stock_dim*2+1)]))\n",
        "            self.asset_memory.append(end_total_asset)\n",
        "            self.date_memory.append(self.data.date)\n",
        "            self.close_price_memory.append(self.data.close)\n",
        "\n",
        "            #print(\"end_total_asset:{}\".format(end_total_asset))\n",
        "            \n",
        "            self.reward = end_total_asset - begin_total_asset            \n",
        "            # print(\"step_reward:{}\".format(self.reward))\n",
        "            self.rewards_memory.append(self.reward)\n",
        "            \n",
        "            self.reward = self.reward*self.reward_scaling\n",
        "\n",
        "\n",
        "\n",
        "        return self.state, self.reward, self.terminal, {}\n",
        "\n",
        "    def reset(self):\n",
        "        self.asset_memory = [self.initial_amount]\n",
        "        self.day = 0\n",
        "        self.data = self.df.loc[self.day,:]\n",
        "        self.cost = 0\n",
        "        self.trades = 0\n",
        "        self.terminal = False \n",
        "        self.rewards_memory = []\n",
        "        self.actions_memory=[]\n",
        "        self.date_memory=[self.data.date]\n",
        "        #initiate state\n",
        "        self.state = [self.initial_amount] + \\\n",
        "                      [self.data.close] + \\\n",
        "                      [0]*self.stock_dim + \\\n",
        "                      sum([[self.data[tech]] for tech in self.tech_indicator_list ], [])+ \\\n",
        "                      [self.data.open] + \\\n",
        "                      [self.data.high] + \\\n",
        "                      [self.data.low] +\\\n",
        "                      [self.data.daily_return] \n",
        "        return self.state\n",
        "    \n",
        "    def render(self, mode='human'):\n",
        "        return self.state\n",
        "    \n",
        "    def save_asset_memory(self):\n",
        "        date_list = self.date_memory\n",
        "        asset_list = self.asset_memory\n",
        "        #print(len(date_list))\n",
        "        #print(len(asset_list))\n",
        "        df_account_value = pd.DataFrame({'date':date_list,'account_value':asset_list})\n",
        "        return df_account_value\n",
        "\n",
        "    def save_action_memory(self):\n",
        "        # date and close price length must match actions length\n",
        "        date_list = self.date_memory[:-1]\n",
        "        close_price_list = self.close_price_memory[:-1]\n",
        "\n",
        "        action_list = self.actions_memory\n",
        "        df_actions = pd.DataFrame({'date':date_list,'actions':action_list,'close_price':close_price_list})\n",
        "        return df_actions\n",
        "\n",
        "    def _seed(self, seed=None):\n",
        "        self.np_random, seed = seeding.np_random(seed)\n",
        "        return [seed]"
      ],
      "execution_count": 66,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "90V3S7cpDcQs"
      },
      "source": [
        "<a id='4.3'></a>\n",
        "## 5.3 Initialize Environment\n",
        "* **stock dimension**: the number of unique stock tickers we use\n",
        "* **hmax**: the maximum amount of shares to buy or sell\n",
        "* **initial amount**: the amount of money we use to trade in the begining\n",
        "* **transaction cost percentage**: a per share rate for every share trade\n",
        "* **tech_indicator_list**: a list of technical indicator names (modified from config.py)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OiH0xO96mGcL",
        "outputId": "1961ceca-0cb8-4247-e769-311364d78564"
      },
      "source": [
        "## we store the stockstats technical indicator column names in config.py\n",
        "## check https://github.com/jealous/stockstats for different names\n",
        "tech_indicator_list"
      ],
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['macd',\n",
              " 'rsi_30',\n",
              " 'cci_30',\n",
              " 'dx_30',\n",
              " 'kdjk',\n",
              " 'open_2_sma',\n",
              " 'boll',\n",
              " 'close_10.0_le_5_c',\n",
              " 'wr_10',\n",
              " 'dma',\n",
              " 'trix']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GnWOKS7DyGM7",
        "outputId": "f5e1d575-7403-4bf2-d1e1-10093fc5311a"
      },
      "source": [
        "# the stock dimension is 1, because we only use the price data of AAPL.\n",
        "len(train.tic.unique())"
      ],
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ipJcnLvQGAba",
        "outputId": "3ee9242b-9f89-4b6d-c13f-be30c9d2e379"
      },
      "source": [
        "# account balance + close price + shares + technical indicators + open-high-low-price + 1 returns\n",
        "stock_dimension = len(train.tic.unique())\n",
        "state_space = 1 + 2*stock_dimension + len(tech_indicator_list)*stock_dimension + 4*stock_dimension\n",
        "print(state_space)\n"
      ],
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "18\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jIGqfq0FTnTT"
      },
      "source": [
        "env_setup = EnvSetup(stock_dim = stock_dimension,\n",
        "                     state_space = state_space,\n",
        "                     hmax = 200,\n",
        "                     initial_amount = 100000,\n",
        "                     transaction_cost_pct = 0.001,\n",
        "                     tech_indicator_list = tech_indicator_list)"
      ],
      "execution_count": 70,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vmyi2IPnyEkP"
      },
      "source": [
        "env_train = env_setup.create_env_training(data = train,\n",
        "                                          env_class = SingleStockEnv)"
      ],
      "execution_count": 71,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "q0Vf3NIcF1bE",
        "outputId": "e1dd0ad6-4946-449b-bd60-a88c4c7454eb"
      },
      "source": [
        "train.head()"
      ],
      "execution_count": 72,
      "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>open</th>\n",
              "      <th>high</th>\n",
              "      <th>low</th>\n",
              "      <th>close</th>\n",
              "      <th>volume</th>\n",
              "      <th>tic</th>\n",
              "      <th>macd</th>\n",
              "      <th>rsi_30</th>\n",
              "      <th>cci_30</th>\n",
              "      <th>dx_30</th>\n",
              "      <th>kdjk</th>\n",
              "      <th>open_2_sma</th>\n",
              "      <th>boll</th>\n",
              "      <th>close_10.0_le_5_c</th>\n",
              "      <th>wr_10</th>\n",
              "      <th>dma</th>\n",
              "      <th>trix</th>\n",
              "      <th>daily_return</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2009-01-02</td>\n",
              "      <td>3.067143</td>\n",
              "      <td>3.251429</td>\n",
              "      <td>3.041429</td>\n",
              "      <td>2.795913</td>\n",
              "      <td>746015200</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>66.666667</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>-5.637387</td>\n",
              "      <td>3.067143</td>\n",
              "      <td>2.795913</td>\n",
              "      <td>1.0</td>\n",
              "      <td>216.912162</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.670734</td>\n",
              "      <td>0.042204</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2009-01-05</td>\n",
              "      <td>3.327500</td>\n",
              "      <td>3.435000</td>\n",
              "      <td>3.311071</td>\n",
              "      <td>2.913912</td>\n",
              "      <td>1181608400</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>0.002647</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>66.666667</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>-14.558226</td>\n",
              "      <td>3.197322</td>\n",
              "      <td>2.854912</td>\n",
              "      <td>2.0</td>\n",
              "      <td>132.399904</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.670734</td>\n",
              "      <td>0.042204</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2009-01-06</td>\n",
              "      <td>3.426786</td>\n",
              "      <td>3.470357</td>\n",
              "      <td>3.299643</td>\n",
              "      <td>2.865849</td>\n",
              "      <td>1289310400</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>0.001883</td>\n",
              "      <td>70.355297</td>\n",
              "      <td>46.762875</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>-23.350262</td>\n",
              "      <td>3.377143</td>\n",
              "      <td>2.858558</td>\n",
              "      <td>3.0</td>\n",
              "      <td>140.934334</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.391303</td>\n",
              "      <td>-0.016494</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2009-01-07</td>\n",
              "      <td>3.278929</td>\n",
              "      <td>3.303571</td>\n",
              "      <td>3.223572</td>\n",
              "      <td>2.803923</td>\n",
              "      <td>753048800</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>-0.000747</td>\n",
              "      <td>50.429222</td>\n",
              "      <td>-29.787322</td>\n",
              "      <td>43.608349</td>\n",
              "      <td>-34.024085</td>\n",
              "      <td>3.352857</td>\n",
              "      <td>2.844899</td>\n",
              "      <td>4.0</td>\n",
              "      <td>155.371731</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.195391</td>\n",
              "      <td>-0.021608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2009-01-08</td>\n",
              "      <td>3.229643</td>\n",
              "      <td>3.326786</td>\n",
              "      <td>3.215714</td>\n",
              "      <td>2.855991</td>\n",
              "      <td>673500800</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>-0.000088</td>\n",
              "      <td>60.227071</td>\n",
              "      <td>-9.011779</td>\n",
              "      <td>48.358256</td>\n",
              "      <td>-37.093625</td>\n",
              "      <td>3.254286</td>\n",
              "      <td>2.847118</td>\n",
              "      <td>5.0</td>\n",
              "      <td>143.232705</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.125124</td>\n",
              "      <td>0.018570</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         date      open      high  ...  dma      trix  daily_return\n",
              "0  2009-01-02  3.067143  3.251429  ...  0.0  0.670734      0.042204\n",
              "1  2009-01-05  3.327500  3.435000  ...  0.0  0.670734      0.042204\n",
              "2  2009-01-06  3.426786  3.470357  ...  0.0  0.391303     -0.016494\n",
              "3  2009-01-07  3.278929  3.303571  ...  0.0  0.195391     -0.021608\n",
              "4  2009-01-08  3.229643  3.326786  ...  0.0  0.125124      0.018570\n",
              "\n",
              "[5 rows x 19 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mdnzYtM1TnTW"
      },
      "source": [
        "<a id='5'></a>\n",
        "# Part 6: Implement DRL Algorithms\n",
        "* The implementation of the DRL algorithms are based on **OpenAI Baselines** and **Stable Baselines**. Stable Baselines is a fork of OpenAI Baselines, with a major structural refactoring, and code cleanups.\n",
        "* FinRL library includes fine-tuned standard DRL algorithms, such as DQN, DDPG,\n",
        "Multi-Agent DDPG, PPO, SAC, A2C and TD3. We also allow users to\n",
        "design their own DRL algorithms by adapting these DRL algorithms."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BRFIZDw8TnTX"
      },
      "source": [
        "agent = DRLAgent(env = env_train)"
      ],
      "execution_count": 63,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zD1NHzGyTnTc"
      },
      "source": [
        "### Model Training: 5 models, A2C DDPG, PPO, TD3, SAC\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y9CM5DeIr9GC"
      },
      "source": [
        "### Model 1: A2C"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YTMEM4Or02Rj",
        "outputId": "c96eb7d0-d9d1-4a31-d443-753d0bc73e6a"
      },
      "source": [
        "## default hyperparameters in config file\n",
        "config.A2C_PARAMS"
      ],
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'ent_coef': 0.01,\n",
              " 'learning_rate': 0.0007,\n",
              " 'n_steps': 5,\n",
              " 'timesteps': 20000,\n",
              " 'verbose': 0}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UJs0N4dGTnTd",
        "scrolled": true,
        "outputId": "107cbc3e-c229-4891-ea29-94e4853ef272"
      },
      "source": [
        "agent = DRLAgent(env = env_train)\n",
        "env_train = env_setup.create_env_training(data = train,\n",
        "                                          env_class = SingleStockEnv)\n",
        "print(\"==============Model Training===========\")\n",
        "now = datetime.datetime.now().strftime('%Y%m%d-%Hh%M')\n",
        "a2c_params_tuning = {'n_steps':5, \n",
        "\t\t\t  'ent_coef':0.005, \n",
        "\t\t\t  'learning_rate':0.0007,\n",
        "\t\t\t  'verbose':0,\n",
        "\t\t\t  'timesteps':100000}\n",
        "model_a2c = agent.train_A2C(model_name = \"A2C_{}\".format(now), model_params = a2c_params_tuning)"
      ],
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Model Training===========\n",
            "begin_total_asset:100000\n",
            "end_total_asset:611492.7541078237\n",
            "total_reward:511492.7541078237\n",
            "total_cost:  322.60986899462847\n",
            "total_trades:  2450\n",
            "Sharpe:  0.87177434323028\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1072165.8801696813\n",
            "total_reward:972165.8801696813\n",
            "total_cost:  129.31661476881496\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0679832379610341\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1078655.7895236432\n",
            "total_reward:978655.7895236432\n",
            "total_cost:  159.90065296319816\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0699731096892475\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1076290.1882644019\n",
            "total_reward:976290.1882644019\n",
            "total_cost:  101.76128208433319\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0692054027655564\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080112.253876325\n",
            "total_reward:980112.253876325\n",
            "total_cost:  102.7606940965527\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0704093593382875\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1078893.0848852054\n",
            "total_reward:978893.0848852054\n",
            "total_cost:  101.7430892866765\n",
            "total_trades:  2515\n",
            "Sharpe:  1.07002887737259\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1078370.3256258212\n",
            "total_reward:978370.3256258212\n",
            "total_cost:  146.5280706147913\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0698804176315126\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1079096.564956451\n",
            "total_reward:979096.5649564511\n",
            "total_cost:  2214.8319620184957\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0715813326172543\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1046403.4166768813\n",
            "total_reward:946403.4166768813\n",
            "total_cost:  949.7660273249629\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0600330236527324\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1061590.0259131396\n",
            "total_reward:961590.0259131396\n",
            "total_cost:  667.7052243771135\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0648129554807884\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1076603.350559632\n",
            "total_reward:976603.3505596321\n",
            "total_cost:  192.82516071852748\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0693661917614825\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1078547.8138840555\n",
            "total_reward:978547.8138840555\n",
            "total_cost:  117.21320929880704\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0699201363805237\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1078417.103618979\n",
            "total_reward:978417.103618979\n",
            "total_cost:  275.91351302909624\n",
            "total_trades:  2515\n",
            "Sharpe:  1.069869015983433\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1070124.0893360784\n",
            "total_reward:970124.0893360784\n",
            "total_cost:  122.8488813073724\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0673645995457337\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1079887.6014468032\n",
            "total_reward:979887.6014468032\n",
            "total_cost:  385.43282438894033\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0703645619370543\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1069964.7362118287\n",
            "total_reward:969964.7362118287\n",
            "total_cost:  1843.068144777611\n",
            "total_trades:  2515\n",
            "Sharpe:  1.067682957247675\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1021350.5115517647\n",
            "total_reward:921350.5115517647\n",
            "total_cost:  5160.372763097004\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0545854262321706\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:910389.3314204997\n",
            "total_reward:810389.3314204997\n",
            "total_cost:  5678.308004236088\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0375773744084174\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:991448.9813358743\n",
            "total_reward:891448.9813358743\n",
            "total_cost:  5552.036583940451\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0461526581787266\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:902545.090365888\n",
            "total_reward:802545.090365888\n",
            "total_cost:  7337.608338602808\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0454956651817187\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:758006.6020651585\n",
            "total_reward:658006.6020651585\n",
            "total_cost:  7317.507388132133\n",
            "total_trades:  2514\n",
            "Sharpe:  0.9942333838312234\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:782745.7326449289\n",
            "total_reward:682745.7326449289\n",
            "total_cost:  7536.600139700735\n",
            "total_trades:  2515\n",
            "Sharpe:  0.9961764077161382\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:944061.0429287256\n",
            "total_reward:844061.0429287256\n",
            "total_cost:  7521.598648024924\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0477126855790184\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:693326.546419904\n",
            "total_reward:593326.546419904\n",
            "total_cost:  7523.079772105463\n",
            "total_trades:  2515\n",
            "Sharpe:  0.9619719764585509\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:912924.6876130179\n",
            "total_reward:812924.6876130179\n",
            "total_cost:  7559.589450613441\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0381810519063672\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:846080.5662968591\n",
            "total_reward:746080.5662968591\n",
            "total_cost:  7590.229454081989\n",
            "total_trades:  2515\n",
            "Sharpe:  1.038832938352312\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:854454.3075735918\n",
            "total_reward:754454.3075735918\n",
            "total_cost:  7727.31426848205\n",
            "total_trades:  2515\n",
            "Sharpe:  1.025522795645929\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:877042.2227844094\n",
            "total_reward:777042.2227844094\n",
            "total_cost:  7760.81577582115\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0387522172504244\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:796983.2999718642\n",
            "total_reward:696983.2999718642\n",
            "total_cost:  8079.09703396829\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0192979829154671\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:832606.2639126861\n",
            "total_reward:732606.2639126861\n",
            "total_cost:  7976.539407133701\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0279932650564014\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:837187.7871583133\n",
            "total_reward:737187.7871583133\n",
            "total_cost:  8090.127847795154\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0277130597442417\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:852120.2930635924\n",
            "total_reward:752120.2930635924\n",
            "total_cost:  8460.193172912088\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0282740584426358\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:931836.5977180862\n",
            "total_reward:831836.5977180862\n",
            "total_cost:  8698.622202258432\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0480578121197242\n",
            "=================================\n",
            "Training time (A2C):  3.7859551548957824  minutes\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9upN8FI2r_X1"
      },
      "source": [
        "### Model 2: DDPG"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pb8YIdvFzHe9",
        "outputId": "f88728ff-52a9-4350-a4d8-9b2ee15cf528"
      },
      "source": [
        "## default hyperparameters in config file\n",
        "config.DDPG_PARAMS"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'batch_size': 128,\n",
              " 'buffer_size': 50000,\n",
              " 'learning_rate': 0.001,\n",
              " 'timesteps': 20000,\n",
              " 'verbose': 0}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "im7iec5_zJVk",
        "outputId": "d22cb725-562c-41d3-da36-17eed084c2d7"
      },
      "source": [
        "agent = DRLAgent(env = env_train)\n",
        "env_train = env_setup.create_env_training(data = train,\n",
        "                                          env_class = SingleStockEnv)\n",
        "print(\"==============Model Training===========\")\n",
        "now = datetime.datetime.now().strftime('%Y%m%d-%Hh%M')\n",
        "ddpg_params_tuning = {\n",
        "                     'batch_size': 128,\n",
        "\t\t\t               'buffer_size':100000, \n",
        "                     'learning_rate':0.0003,\n",
        "\t\t\t               'verbose':0,\n",
        "\t\t\t               'timesteps':30000}\n",
        "model_ddpg = agent.train_DDPG(model_name = \"DDPG_{}\".format(now), model_params = ddpg_params_tuning)"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Model Training===========\n",
            "begin_total_asset:100000\n",
            "end_total_asset:686971.5165633885\n",
            "total_reward:586971.5165633885\n",
            "total_cost:  10111.38556382456\n",
            "total_trades:  2514\n",
            "Sharpe:  0.9326658593874367\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1067520.3198762233\n",
            "total_reward:967520.3198762233\n",
            "total_cost:  99.89765015568229\n",
            "total_trades:  2515\n",
            "Sharpe:  1.066534069569284\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1068041.5737455192\n",
            "total_reward:968041.5737455192\n",
            "total_cost:  99.89551995446926\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0667420634920257\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1068217.6418047766\n",
            "total_reward:968217.6418047766\n",
            "total_cost:  99.89790394197078\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0667649396101613\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1068136.2638591528\n",
            "total_reward:968136.2638591528\n",
            "total_cost:  99.89531320484079\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0667173392989593\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1066709.851551336\n",
            "total_reward:966709.851551336\n",
            "total_cost:  99.89546097612946\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0662989567629697\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1070820.1113471743\n",
            "total_reward:970820.1113471743\n",
            "total_cost:  99.89813429373933\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0675754183576942\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1065506.9309677833\n",
            "total_reward:965506.9309677833\n",
            "total_cost:  99.89825751915998\n",
            "total_trades:  2515\n",
            "Sharpe:  1.065903152619106\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1069689.2089983781\n",
            "total_reward:969689.2089983781\n",
            "total_cost:  99.89584321219209\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0672420381658732\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1065896.188453721\n",
            "total_reward:965896.1884537211\n",
            "total_cost:  99.89872654307256\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0660646420210584\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1069654.9879151303\n",
            "total_reward:969654.9879151303\n",
            "total_cost:  99.8969718973871\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0672235307858031\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1068839.2818672697\n",
            "total_reward:968839.2818672697\n",
            "total_cost:  99.89587111022172\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0669710696672352\n",
            "=================================\n",
            "Training time (DDPG):  10.579627295335134  minutes\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1sve9WGvsC__"
      },
      "source": [
        "### Model 3: PPO"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TavJs-xXydY5",
        "outputId": "ea664af7-3be0-404b-915e-3d2a1ad103b6"
      },
      "source": [
        "config.PPO_PARAMS"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'batch_size': 64,\n",
              " 'ent_coef': 0.01,\n",
              " 'learning_rate': 0.00025,\n",
              " 'n_steps': 2048,\n",
              " 'timesteps': 20000,\n",
              " 'verbose': 0}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hzvm6xu9ySZ0",
        "outputId": "6d461717-9994-4d16-f00d-aa3e0f835e48"
      },
      "source": [
        "agent = DRLAgent(env = env_train)\n",
        "env_train = env_setup.create_env_training(data = train,\n",
        "                                          env_class = SingleStockEnv)\n",
        "\n",
        "print(\"==============Model Training===========\")\n",
        "now = datetime.datetime.now().strftime('%Y%m%d-%Hh%M')\n",
        "ppo_params_tuning = {'n_steps':128, \n",
        "                     'batch_size': 64,\n",
        "\t\t\t               'ent_coef':0.005, \n",
        "\t\t\t               'learning_rate':0.00025,\n",
        "\t\t\t              'verbose':0,\n",
        "\t\t\t              'timesteps':50000}\n",
        "model_ppo = agent.train_PPO(model_name = \"PPO_{}\".format(now), model_params = ppo_params_tuning)"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Model Training===========\n",
            "begin_total_asset:100000\n",
            "end_total_asset:479977.2430245385\n",
            "total_reward:379977.2430245385\n",
            "total_cost:  6391.018892968369\n",
            "total_trades:  2501\n",
            "Sharpe:  0.8198570781570106\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:248565.56078843185\n",
            "total_reward:148565.56078843185\n",
            "total_cost:  6125.000287580477\n",
            "total_trades:  2463\n",
            "Sharpe:  0.7246250444911498\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:504354.306477595\n",
            "total_reward:404354.306477595\n",
            "total_cost:  6899.194529210106\n",
            "total_trades:  2514\n",
            "Sharpe:  0.8614286811673606\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:633168.1288004767\n",
            "total_reward:533168.1288004767\n",
            "total_cost:  6886.988848122515\n",
            "total_trades:  2515\n",
            "Sharpe:  0.9434009788024951\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:599802.3368500102\n",
            "total_reward:499802.3368500102\n",
            "total_cost:  6892.306094781234\n",
            "total_trades:  2515\n",
            "Sharpe:  0.9577362075562244\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:438530.4520191314\n",
            "total_reward:338530.4520191314\n",
            "total_cost:  6866.817671028566\n",
            "total_trades:  2515\n",
            "Sharpe:  0.8373186240902029\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:573245.9854822684\n",
            "total_reward:473245.9854822684\n",
            "total_cost:  6656.642878550021\n",
            "total_trades:  2515\n",
            "Sharpe:  0.9544177776142304\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:486040.45594165544\n",
            "total_reward:386040.45594165544\n",
            "total_cost:  6825.006007349398\n",
            "total_trades:  2515\n",
            "Sharpe:  0.9266123141741883\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:427531.48456633673\n",
            "total_reward:327531.48456633673\n",
            "total_cost:  6989.625680770247\n",
            "total_trades:  2514\n",
            "Sharpe:  0.8902037587433915\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:406615.83287489996\n",
            "total_reward:306615.83287489996\n",
            "total_cost:  6869.925488681218\n",
            "total_trades:  2514\n",
            "Sharpe:  0.8735751098242878\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:384919.4355557128\n",
            "total_reward:284919.4355557128\n",
            "total_cost:  7061.505324195383\n",
            "total_trades:  2515\n",
            "Sharpe:  0.8168987947660198\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:565075.7519859241\n",
            "total_reward:465075.7519859241\n",
            "total_cost:  6966.976559446332\n",
            "total_trades:  2515\n",
            "Sharpe:  0.946575928966108\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:596704.4817529134\n",
            "total_reward:496704.48175291345\n",
            "total_cost:  6829.101735119388\n",
            "total_trades:  2515\n",
            "Sharpe:  0.9457669747131224\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:683807.263099186\n",
            "total_reward:583807.263099186\n",
            "total_cost:  6848.941160919415\n",
            "total_trades:  2515\n",
            "Sharpe:  0.9738543068172891\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:664879.460592505\n",
            "total_reward:564879.460592505\n",
            "total_cost:  6987.31560567299\n",
            "total_trades:  2515\n",
            "Sharpe:  0.9850908075362844\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:584100.4384548264\n",
            "total_reward:484100.43845482636\n",
            "total_cost:  6798.963851332113\n",
            "total_trades:  2515\n",
            "Sharpe:  0.9456697454511505\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:593111.2550146048\n",
            "total_reward:493111.2550146048\n",
            "total_cost:  6679.273111726417\n",
            "total_trades:  2515\n",
            "Sharpe:  0.9501486473730443\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:735307.1529878502\n",
            "total_reward:635307.1529878502\n",
            "total_cost:  6523.53331997358\n",
            "total_trades:  2515\n",
            "Sharpe:  0.9835269056542661\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:654448.944062525\n",
            "total_reward:554448.944062525\n",
            "total_cost:  6590.05029386914\n",
            "total_trades:  2515\n",
            "Sharpe:  0.945669077148301\n",
            "=================================\n",
            "Training time (PPO):  1.69747367699941  minutes\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CiBG2ZknsG73"
      },
      "source": [
        "### Model 4: TD3"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PDUOfp6hiSuz",
        "outputId": "bb37e7a6-ffca-4d2f-9d3f-6288c9acb88d"
      },
      "source": [
        "## default hyperparameters in config file\n",
        "config.TD3_PARAMS"
      ],
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'batch_size': 128,\n",
              " 'buffer_size': 50000,\n",
              " 'learning_rate': 0.0001,\n",
              " 'timesteps': 20000,\n",
              " 'verbose': 0}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i5nbOm-xiTUk",
        "outputId": "db238ed3-6a85-43b0-b8b8-615bfd8a009a"
      },
      "source": [
        "agent = DRLAgent(env = env_train)\n",
        "env_train = env_setup.create_env_training(data = train,\n",
        "                                          env_class = SingleStockEnv)\n",
        "\n",
        "print(\"==============Model Training===========\")\n",
        "now = datetime.datetime.now().strftime('%Y%m%d-%Hh%M')\n",
        "td3_params_tuning = {\n",
        "                     'batch_size': 100,\n",
        "\t\t\t               'buffer_size':1000000, \n",
        "                     'learning_rate': 0.001,\n",
        "\t\t\t               'verbose':0,\n",
        "\t\t\t               'timesteps':30000}\n",
        "model_td3 = agent.train_TD3(model_name = \"TD3_{}\".format(now), model_params = td3_params_tuning)"
      ],
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Model Training===========\n",
            "begin_total_asset:100000\n",
            "end_total_asset:541877.1050630751\n",
            "total_reward:441877.1050630751\n",
            "total_cost:  10111.428388564602\n",
            "total_trades:  2495\n",
            "Sharpe:  0.903128814397228\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1066375.2996303637\n",
            "total_reward:966375.2996303637\n",
            "total_cost:  99.89666552485846\n",
            "total_trades:  2515\n",
            "Sharpe:  1.06616564532884\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1067431.63209483\n",
            "total_reward:967431.63209483\n",
            "total_cost:  99.8965558317135\n",
            "total_trades:  2515\n",
            "Sharpe:  1.066517940007831\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1067468.7161440752\n",
            "total_reward:967468.7161440752\n",
            "total_cost:  99.90007142897299\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0665037191184636\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1068887.7495602723\n",
            "total_reward:968887.7495602723\n",
            "total_cost:  99.89935882435643\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0669727273963356\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1068983.8112070507\n",
            "total_reward:968983.8112070507\n",
            "total_cost:  99.89543316680655\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0670405008582486\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1068137.4178865382\n",
            "total_reward:968137.4178865382\n",
            "total_cost:  99.89855198641347\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0667521258998063\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1064544.5656638776\n",
            "total_reward:964544.5656638776\n",
            "total_cost:  99.89736184136626\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0656053753378463\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1066122.363011554\n",
            "total_reward:966122.3630115541\n",
            "total_cost:  99.89919219111339\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0661130312392262\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1067886.1984941673\n",
            "total_reward:967886.1984941673\n",
            "total_cost:  99.89635165877867\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0666924096909105\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1068838.303238533\n",
            "total_reward:968838.303238533\n",
            "total_cost:  99.89805159149682\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0669754201829644\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1068735.4549684525\n",
            "total_reward:968735.4549684525\n",
            "total_cost:  99.89751353563142\n",
            "total_trades:  2515\n",
            "Sharpe:  1.0669109490822402\n",
            "=================================\n",
            "Training time (DDPG):  10.493100504080454  minutes\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oDk2qrlTLZCp"
      },
      "source": [
        "### Model 4: SAC"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pGzSevCzLcsR",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "64eac474-6203-434b-aed5-6832a354dd7c"
      },
      "source": [
        "## default hyperparameters in config file\n",
        "config.SAC_PARAMS"
      ],
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'batch_size': 64,\n",
              " 'buffer_size': 100000,\n",
              " 'ent_coef': 'auto_0.1',\n",
              " 'learning_rate': 0.0001,\n",
              " 'learning_starts': 100,\n",
              " 'timesteps': 50000,\n",
              " 'verbose': 0}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1JZA0RTpIW6h",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d53b8a99-619d-444a-eadc-aac26f1e141a"
      },
      "source": [
        "agent = DRLAgent(env = env_train)\n",
        "env_train = env_setup.create_env_training(data = train,\n",
        "                                          env_class = SingleStockEnv)\n",
        "\n",
        "print(\"==============Model Training===========\")\n",
        "now = datetime.datetime.now().strftime('%Y%m%d-%Hh%M')\n",
        "sac_params_tuning={\n",
        "  'batch_size': 64,\n",
        " 'buffer_size': 100000,\n",
        "  'ent_coef':'auto_0.1',\n",
        " 'learning_rate': 0.0001,\n",
        " 'learning_starts':200,\n",
        " 'timesteps': 30000,\n",
        " 'verbose': 0}\n",
        "model_sac = agent.train_SAC(model_name = \"SAC_{}\".format(now), model_params = sac_params_tuning)"
      ],
      "execution_count": 77,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Model Training===========\n",
            "begin_total_asset:100000\n",
            "end_total_asset:632503.865279473\n",
            "total_reward:532503.865279473\n",
            "total_cost:  174.2452735088114\n",
            "total_trades:  2509\n",
            "Sharpe:  0.8814063177792701\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "begin_total_asset:100000\n",
            "end_total_asset:1080102.0841213865\n",
            "total_reward:980102.0841213865\n",
            "total_cost:  99.89841397571567\n",
            "total_trades:  2515\n",
            "Sharpe:  1.070404809709619\n",
            "=================================\n",
            "Training time (SAC):  9.072016612688701  minutes\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KE1Xm9N9TnTn"
      },
      "source": [
        "### Trading\n",
        "* we use the environment class we initialized at 5.3 to create a stock trading environment\n",
        "* Assume that we have $100,000 initial capital at 2019-01-01. \n",
        "* We use the trained model of PPO to trade AAPL."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 199
        },
        "id": "kLFUwxhCoHN_",
        "outputId": "693cc5db-1057-46dc-f540-c44668ea22fa"
      },
      "source": [
        "trade.head()"
      ],
      "execution_count": null,
      "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",
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              "\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>open</th>\n",
              "      <th>high</th>\n",
              "      <th>low</th>\n",
              "      <th>close</th>\n",
              "      <th>volume</th>\n",
              "      <th>tic</th>\n",
              "      <th>macd</th>\n",
              "      <th>rsi_30</th>\n",
              "      <th>cci_30</th>\n",
              "      <th>dx_30</th>\n",
              "      <th>kdjk</th>\n",
              "      <th>open_2_sma</th>\n",
              "      <th>boll</th>\n",
              "      <th>close_10.0_le_5_c</th>\n",
              "      <th>wr_10</th>\n",
              "      <th>dma</th>\n",
              "      <th>trix</th>\n",
              "      <th>daily_return</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2019-01-02</td>\n",
              "      <td>1.259187</td>\n",
              "      <td>1.311140</td>\n",
              "      <td>1.273863</td>\n",
              "      <td>38.249401</td>\n",
              "      <td>-0.796071</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>-4.623404</td>\n",
              "      <td>-1.879233</td>\n",
              "      <td>-1.130976</td>\n",
              "      <td>0.936711</td>\n",
              "      <td>1.584543</td>\n",
              "      <td>1.296077</td>\n",
              "      <td>1.535902</td>\n",
              "      <td>-0.509749</td>\n",
              "      <td>-1.478527</td>\n",
              "      <td>-5.464510</td>\n",
              "      <td>-2.953890</td>\n",
              "      <td>-0.003511</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2019-01-03</td>\n",
              "      <td>1.042136</td>\n",
              "      <td>1.052042</td>\n",
              "      <td>1.028504</td>\n",
              "      <td>34.439476</td>\n",
              "      <td>0.080554</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>-5.020681</td>\n",
              "      <td>-2.419562</td>\n",
              "      <td>-1.918796</td>\n",
              "      <td>1.654691</td>\n",
              "      <td>1.409904</td>\n",
              "      <td>1.151332</td>\n",
              "      <td>1.493971</td>\n",
              "      <td>-0.509749</td>\n",
              "      <td>-0.930227</td>\n",
              "      <td>-5.623870</td>\n",
              "      <td>-2.960046</td>\n",
              "      <td>-6.012728</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019-01-04</td>\n",
              "      <td>1.053078</td>\n",
              "      <td>1.107887</td>\n",
              "      <td>1.064615</td>\n",
              "      <td>35.909672</td>\n",
              "      <td>-0.447708</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>-5.020959</td>\n",
              "      <td>-2.056112</td>\n",
              "      <td>-1.570256</td>\n",
              "      <td>1.202432</td>\n",
              "      <td>1.418700</td>\n",
              "      <td>1.048269</td>\n",
              "      <td>1.466007</td>\n",
              "      <td>-0.509749</td>\n",
              "      <td>-1.218098</td>\n",
              "      <td>-5.592501</td>\n",
              "      <td>-2.968936</td>\n",
              "      <td>2.474654</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2019-01-07</td>\n",
              "      <td>1.136039</td>\n",
              "      <td>1.113412</td>\n",
              "      <td>1.106746</td>\n",
              "      <td>35.829746</td>\n",
              "      <td>-0.509560</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>-4.980654</td>\n",
              "      <td>-2.067081</td>\n",
              "      <td>-1.415251</td>\n",
              "      <td>1.157374</td>\n",
              "      <td>1.417011</td>\n",
              "      <td>1.095224</td>\n",
              "      <td>1.439656</td>\n",
              "      <td>-0.509749</td>\n",
              "      <td>-1.211709</td>\n",
              "      <td>-5.483187</td>\n",
              "      <td>-2.973126</td>\n",
              "      <td>-0.204331</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2019-01-08</td>\n",
              "      <td>1.153148</td>\n",
              "      <td>1.172415</td>\n",
              "      <td>1.159309</td>\n",
              "      <td>36.512772</td>\n",
              "      <td>-0.731694</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>-4.775895</td>\n",
              "      <td>-1.900079</td>\n",
              "      <td>-1.162272</td>\n",
              "      <td>0.676332</td>\n",
              "      <td>1.480427</td>\n",
              "      <td>1.145263</td>\n",
              "      <td>1.422207</td>\n",
              "      <td>-0.509749</td>\n",
              "      <td>-1.394265</td>\n",
              "      <td>-5.247375</td>\n",
              "      <td>-2.945117</td>\n",
              "      <td>1.065455</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         date      open      high  ...       dma      trix  daily_return\n",
              "0  2019-01-02  1.259187  1.311140  ... -5.464510 -2.953890     -0.003511\n",
              "1  2019-01-03  1.042136  1.052042  ... -5.623870 -2.960046     -6.012728\n",
              "2  2019-01-04  1.053078  1.107887  ... -5.592501 -2.968936      2.474654\n",
              "3  2019-01-07  1.136039  1.113412  ... -5.483187 -2.973126     -0.204331\n",
              "4  2019-01-08  1.153148  1.172415  ... -5.247375 -2.945117      1.065455\n",
              "\n",
              "[5 rows x 19 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g1KlgP0FTnTn"
      },
      "source": [
        "# create trading env\n",
        "trade = data_split(data_df, start = '2019-01-01', end = '2020-12-01')\n",
        "\n",
        "env_trade, obs_trade = env_setup.create_env_trading(data = trade,\n",
        "                                                    env_class = SingleStockEnv) "
      ],
      "execution_count": 81,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bLHl6V7eqV6_",
        "outputId": "c358d3ba-ea28-4a27-862a-60824efbe6ff"
      },
      "source": [
        "## make a prediction and get the account value change\n",
        "df_account_value, df_actions = DRLAgent.DRL_prediction(model=model_td3,\n",
        "                                           test_data = trade,\n",
        "                                           test_env = env_trade,\n",
        "                                           test_obs = obs_trade)"
      ],
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "begin_total_asset:100000\n",
            "end_total_asset:320134.14018198394\n",
            "total_reward:220134.14018198394\n",
            "total_cost:  99.8914265975952\n",
            "total_trades:  482\n",
            "Sharpe:  1.8184634817437642\n",
            "=================================\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qYXxFzD5TnTw"
      },
      "source": [
        "<a id='6'></a>\n",
        "# Part 7: Backtesting Performance\n",
        "Backtesting plays a key role in evaluating the performance of a trading strategy. Automated backtesting tool is preferred because it reduces the human error. We usually use the Quantopian pyfolio package to backtest our trading strategies. It is easy to use and consists of various individual plots that provide a comprehensive image of the performance of a trading strategy."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8GwqOO-v1NVz"
      },
      "source": [
        "<a id='6.1'></a>\n",
        "## 7.1 BackTestStats\n",
        "pass in df_account_value, this information is stored in env class\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C9cpPm9YYxHC",
        "outputId": "60c90961-994b-44f7-88c3-1a4353be4d2f"
      },
      "source": [
        "print(\"==============Get Backtest Results===========\")\n",
        "perf_stats_all = BackTestStats(account_value=df_account_value)\n",
        "perf_stats_all = pd.DataFrame(perf_stats_all)\n",
        "perf_stats_all.to_csv(\"./\"+config.RESULTS_DIR+\"/perf_stats_all_\"+now+'.csv')"
      ],
      "execution_count": 83,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Get Backtest Results===========\n",
            "annual return:  96.93629100776415\n",
            "sharpe ratio:  1.8184634817437642\n",
            "Annual return          0.835065\n",
            "Cumulative returns     2.201341\n",
            "Annual volatility      0.373184\n",
            "Sharpe ratio           1.818463\n",
            "Calmar ratio           2.657241\n",
            "Stability              0.930231\n",
            "Max drawdown          -0.314260\n",
            "Omega ratio            1.409390\n",
            "Sortino ratio          2.744132\n",
            "Skew                        NaN\n",
            "Kurtosis                    NaN\n",
            "Tail ratio             1.089659\n",
            "Daily value at risk   -0.044324\n",
            "Alpha                  0.000000\n",
            "Beta                   1.000000\n",
            "dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y4Gw3HNr1TDU"
      },
      "source": [
        "<a id='6.2'></a>\n",
        "## 7.2 BackTestPlot"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "MA_8LuZE1J3X",
        "outputId": "c0684da9-c9cf-4054-9423-7f46d9934e05"
      },
      "source": [
        "print(\"==============Compare to AAPL itself buy-and-hold===========\")\n",
        "%matplotlib inline\n",
        "BackTestPlot(account_value=df_account_value, baseline_ticker = 'AAPL')"
      ],
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Compare to AAPL itself buy-and-hold===========\n",
            "annual return:  96.93629100776415\n",
            "sharpe ratio:  1.8184634817437642\n",
            "\r[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (483, 7)\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>2019-01-03</td></tr>\n",
              "    <tr style=\"text-align: right;\"><th>End date</th><td colspan=2>2020-11-30</td></tr>\n",
              "    <tr style=\"text-align: right;\"><th>Total months</th><td colspan=2>22</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>83.738%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Cumulative returns</th>\n",
              "      <td>220.134%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Annual volatility</th>\n",
              "      <td>37.318%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sharpe ratio</th>\n",
              "      <td>1.82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Calmar ratio</th>\n",
              "      <td>2.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Stability</th>\n",
              "      <td>0.93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Max drawdown</th>\n",
              "      <td>-31.426%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Omega ratio</th>\n",
              "      <td>1.41</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sortino ratio</th>\n",
              "      <td>2.74</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Skew</th>\n",
              "      <td>-0.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kurtosis</th>\n",
              "      <td>5.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tail ratio</th>\n",
              "      <td>1.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Daily value at risk</th>\n",
              "      <td>-4.432%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alpha</th>\n",
              "      <td>0.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Beta</th>\n",
              "      <td>0.96</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
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              "<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>31.43</td>\n",
              "      <td>2020-02-12</td>\n",
              "      <td>2020-03-23</td>\n",
              "      <td>2020-06-05</td>\n",
              "      <td>83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20.38</td>\n",
              "      <td>2020-09-01</td>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>NaT</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>17.84</td>\n",
              "      <td>2019-05-03</td>\n",
              "      <td>2019-06-03</td>\n",
              "      <td>2019-07-31</td>\n",
              "      <td>64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>9.25</td>\n",
              "      <td>2019-07-31</td>\n",
              "      <td>2019-08-05</td>\n",
              "      <td>2019-08-21</td>\n",
              "      <td>16</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.84</td>\n",
              "      <td>2020-07-20</td>\n",
              "      <td>2020-07-24</td>\n",
              "      <td>2020-07-31</td>\n",
              "      <td>10</td>\n",
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\n",
            "text/plain": [
              "<Figure size 1008x5184 with 13 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qSFMdgCJE4O-"
      },
      "source": [
        "<a id='6.3'></a>\n",
        "## 7.3 Baseline Stats"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MpR7aQIwqdC4",
        "outputId": "2cc44841-172e-4cbc-abda-f9eb0b4f84a5"
      },
      "source": [
        "print(\"==============Get Baseline Stats===========\")\n",
        "baesline_perf_stats=BaselineStats('AAPL')"
      ],
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Get Baseline Stats===========\n",
            "\r[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (483, 7)\n",
            "Annual return          0.800630\n",
            "Cumulative returns     2.087191\n",
            "Annual volatility      0.382201\n",
            "Sharpe ratio           1.735128\n",
            "Calmar ratio           2.547565\n",
            "Stability              0.930285\n",
            "Max drawdown          -0.314273\n",
            "Omega ratio            1.387241\n",
            "Sortino ratio          2.572655\n",
            "Skew                        NaN\n",
            "Kurtosis                    NaN\n",
            "Tail ratio             1.081315\n",
            "Daily value at risk   -0.045521\n",
            "Alpha                  0.000000\n",
            "Beta                   1.000000\n",
            "dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vSFRXQfYFTQf",
        "outputId": "c2a1d0ef-768a-49f5-fe06-6810e45f5398"
      },
      "source": [
        "print(\"==============Get Baseline Stats===========\")\n",
        "baesline_perf_stats=BaselineStats('^GSPC')"
      ],
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Get Baseline Stats===========\n",
            "\r[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (483, 7)\n",
            "Annual return          0.210804\n",
            "Cumulative returns     0.442863\n",
            "Annual volatility      0.264385\n",
            "Sharpe ratio           0.858377\n",
            "Calmar ratio           0.621384\n",
            "Stability              0.467075\n",
            "Max drawdown          -0.339250\n",
            "Omega ratio            1.200929\n",
            "Sortino ratio          1.183069\n",
            "Skew                        NaN\n",
            "Kurtosis                    NaN\n",
            "Tail ratio             0.726400\n",
            "Daily value at risk   -0.032409\n",
            "Alpha                  0.000000\n",
            "Beta                   1.000000\n",
            "dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tunrA4mjE9la"
      },
      "source": [
        "<a id='6.4'></a>\n",
        "## 7.4 Compare to Stock Market Index"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "5Ca2gHxi1gzX",
        "outputId": "06278d38-a1c0-4f37-e502-9b2eba55c59c"
      },
      "source": [
        "print(\"==============Compare to S&P 500===========\")\n",
        "%matplotlib inline\n",
        "# S&P 500: ^GSPC\n",
        "# Dow Jones Index: ^DJI\n",
        "# NASDAQ 100: ^NDX\n",
        "BackTestPlot(df_account_value, baseline_ticker = '^GSPC')"
      ],
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "==============Compare to S&P 500===========\n",
            "annual return:  96.93629100776415\n",
            "sharpe ratio:  1.8184634817437642\n",
            "\r[*********************100%***********************]  1 of 1 completed\n",
            "Shape of DataFrame:  (483, 7)\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>2019-01-03</td></tr>\n",
              "    <tr style=\"text-align: right;\"><th>End date</th><td colspan=2>2020-11-30</td></tr>\n",
              "    <tr style=\"text-align: right;\"><th>Total months</th><td colspan=2>22</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>83.738%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Cumulative returns</th>\n",
              "      <td>220.134%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Annual volatility</th>\n",
              "      <td>37.318%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sharpe ratio</th>\n",
              "      <td>1.82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Calmar ratio</th>\n",
              "      <td>2.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Stability</th>\n",
              "      <td>0.93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Max drawdown</th>\n",
              "      <td>-31.426%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Omega ratio</th>\n",
              "      <td>1.41</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sortino ratio</th>\n",
              "      <td>2.74</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Skew</th>\n",
              "      <td>-0.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kurtosis</th>\n",
              "      <td>5.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tail ratio</th>\n",
              "      <td>1.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Daily value at risk</th>\n",
              "      <td>-4.432%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alpha</th>\n",
              "      <td>0.52</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Beta</th>\n",
              "      <td>1.14</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
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              "<IPython.core.display.HTML object>"
            ]
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            "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>31.43</td>\n",
              "      <td>2020-02-12</td>\n",
              "      <td>2020-03-23</td>\n",
              "      <td>2020-06-05</td>\n",
              "      <td>83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20.38</td>\n",
              "      <td>2020-09-01</td>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>NaT</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>17.84</td>\n",
              "      <td>2019-05-03</td>\n",
              "      <td>2019-06-03</td>\n",
              "      <td>2019-07-31</td>\n",
              "      <td>64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>9.25</td>\n",
              "      <td>2019-07-31</td>\n",
              "      <td>2019-08-05</td>\n",
              "      <td>2019-08-21</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.84</td>\n",
              "      <td>2020-07-20</td>\n",
              "      <td>2020-07-24</td>\n",
              "      <td>2020-07-31</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
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\n",
            "text/plain": [
              "<Figure size 1008x5184 with 13 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3_aHGEOTCluG"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}