BacktestTrial.ipynb

backtesttrial.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "BacktestTrial.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyPH0f4GJgLpDjZ4zMOvsruT",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/nagishin/3f6dade186a11719e33da19632b9ef9c/backtesttrial.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SrjL_0ZFOHbA"
      },
      "source": [
        "# 【評価版】BacktestAssist & ChartCreator\n",
        "\n",
        "Bybit WSOT 2021期間中(～2021/9/17)は各ツールを公開します。<br>\n",
        "<br>\n",
        "< 使用方法 >\n",
        "* 本notebookをコピーして使用する\n",
        "* GitHubリポジトリ [BacktestTrial](https://github.com/nagishin/BacktestTrial) をクローンして使用する<br>\n",
        "\n",
        "（ツール全機能を使用可能ですが、評価版ではソースコード非公開となりますのでご了承ください。）<br>\n",
        "<br>\n",
        "\n",
        "各ツールの詳細は以下のnoteを参照してください。\n",
        "* [バックテスト補助ツール「BacktestAssistant」](https://note.com/nagi7692/n/n0c874a0cf2b2) -> backtest_assistant.py\n",
        "* [時系列データ可視化ツール「ChartCreator」](https://note.com/nagi7692/n/n401a95653ad0) -> chart_creator.py"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gTb56Ka7Fwao"
      },
      "source": [
        "# Google Colab 環境確認"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VAWPa9q7hYbw",
        "outputId": "5e1e6efc-fffc-4220-cf0c-8e5914d1cdd9"
      },
      "source": [
        "!cat /etc/issue\n",
        "!python --version"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Ubuntu 18.04.5 LTS \\n \\l\n",
            "\n",
            "Python 3.7.11\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O832DZWzGhDm"
      },
      "source": [
        "# 1. 環境構築\n",
        "Google Colaboratoryでテストを実行するために必要なセットアップです。\n",
        "* 1-1. GitHubリポジトリクローン & zip解凍<br>\n",
        "  * backtest_assistant.py (バックテストツール)\n",
        "  * chart_creator.py (チャート作成ツール) \n",
        "\n",
        "* 1-2. 必要パッケージのインストール\n",
        "\n",
        "* 1-3. 評価版ライセンス 有効期限チェック\n",
        "<br>\n",
        "\n",
        "【構築するディレクトリ/ファイル構造】\n",
        "```\n",
        "./dist\n",
        "   ∟__init__.py\n",
        "   ∟backtest_assistant.py\n",
        "   ∟chart_creator.py\n",
        "   ∟/pytransform\n",
        "      ∟__init__.py\n",
        "      ∟_pytransform.so\n",
        "```"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BblnvE-pIKE2"
      },
      "source": [
        "## 【1-1. GitHubリポジトリクローン & zip解凍】\n",
        "GitHubリポジトリ [BacktestTrial](https://github.com/nagishin/BacktestTrial) をクローンします。<br>\n",
        "テスト実行に必要な環境を解凍します。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-Pm7xJ_QDeyn"
      },
      "source": [
        "# GitHubリポジトリクローン\n",
        "!git clone https://github.com/nagishin/BacktestTrial.git\n",
        "\n",
        "# Colab環境に合わせてLinux python3.7 distを解凍\n",
        "!unzip BacktestTrial/dist_for_linux_py37.zip\n",
        "\n",
        "# ファイルコピー\n",
        "!cp BacktestTrial/requirements.txt requirements.txt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "S5BF8m_WGY8P"
      },
      "source": [
        "## 【1-2. 必要パッケージインストール】\n",
        "上記ツールを使用するために必要なパッケージをインストールします。<br>\n",
        "また、テストデータの取得や加工に便利な以下のツールもインストールします。\n",
        "* [テストデータ取得＆加工ツール【DataUtility】](https://gist.github.com/nagishin/1677ffa401476e9e98191a04012ac189)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kJQb0daZ77qy"
      },
      "source": [
        "!pip install -r requirements.txt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TaX0KpanJPx2"
      },
      "source": [
        "## 【1-3. 評価版ライセンス 有効期限チェック】\n",
        "Bybit WSOT期間中(～2021/9/17)は使用可能"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qQMf73Lf8Azq",
        "outputId": "5fbcc62e-19d7-4b95-dd72-9c6a69953fd3"
      },
      "source": [
        "from dist import pyarmor_init, get_license_info, get_expired_days\n",
        "try:\n",
        "    pyarmor_init(path=None, is_runtime=1, suffix='', advanced=0)\n",
        "    code = get_license_info()['CODE']\n",
        "    left_days = get_expired_days()\n",
        "    if left_days == -1:\n",
        "        print('This license for %s is never expired' % code)\n",
        "    else:\n",
        "        print('This license for %s will be expired in %d days' % (code, left_days))\n",
        "except Exception as e:\n",
        "    print(e)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "This license for lic_for_wsot will be expired in 23 days\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hyIpsAQMSC7g"
      },
      "source": [
        "# 2. バックテスト\n",
        "\n",
        "<b>ロジック</b><br>\n",
        "* RSIから売買過熱を判断して逆張りする<br>\n",
        "* RSIが20未満で買いエントリー / 80より大きいと売りエントリー\n",
        "* RSIが50に到達したらイグジット\n",
        "\n",
        "<b>対象データ</b>\n",
        "* tickデータ ：　BitMEX 1h OHLCV\n",
        "\n",
        "<b>対象期間</b>\n",
        "* 2020/08/01 ～ 2020/08/31 (JST)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J_moXZhbSQeu"
      },
      "source": [
        "## 【2-1. バックテスト準備】\n",
        "テストを実施するための前準備を行います。\n",
        "* テスト期間の設定\n",
        "* テストデータの取得・加工"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HOhHxWjx8O9x",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "outputId": "b9dd5525-92d6-43be-c704-fd1fdf772d67"
      },
      "source": [
        "import requests\n",
        "from datetime import datetime\n",
        "from collections import OrderedDict\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import DataUtility as du\n",
        "\n",
        "#テスト期間\n",
        "TEST_START = '2020/08/01 09:00:00'\n",
        "TEST_END   = '2020/08/31 09:00:00'\n",
        "\n",
        "# テスト期間の日付文字列をUnix Timeに変換\n",
        "start_ut = int(du.Time(TEST_START, 'JST').unixtime()) # テスト開始時刻 (UnixTime)\n",
        "end_ut   = int(du.Time(TEST_END, 'JST').unixtime())   # テスト終了時刻 (UnixTime)\n",
        "\n",
        "# DataUtilityを使用してBitMEX OHLCVを取得\n",
        "df_ohlcv = du.Tool.get_ohlcv_from_bitmex(\n",
        "                    start_ut         = start_ut - 3600 * 24,  # 取得開始(UnixTime)\n",
        "                    end_ut           = end_ut,                # 取得終了(UnixTime)\n",
        "                    period           = 60,                    # 時間足期間(分)\n",
        "                    csv_path         = './data/ohlcv_1h.csv', # 取得結果保存先(CSVパス)\n",
        "                    request_interval = 1.0)                   # RESTリクエスト待機時間(秒)\n",
        "\n",
        "# RSI計算\n",
        "rsi_term = 12\n",
        "diff = df_ohlcv['close'].diff()\n",
        "diff = diff[1:]\n",
        "up, down = diff.copy(), diff.copy()\n",
        "up[up < 0] = 0\n",
        "down[down > 0] = 0\n",
        "up_sma = up.rolling(window=rsi_term, center=False).mean()\n",
        "down_sma = down.abs().rolling(window=rsi_term, center=False).mean()\n",
        "rs = up_sma / down_sma\n",
        "df_ohlcv['rsi'] = 100.0 - (100.0 / (1.0 + rs))\n",
        "\n",
        "# OHLCVをテスト期間でfiltering\n",
        "df_ohlcv = df_ohlcv[((df_ohlcv['unixtime'] >= start_ut) & (df_ohlcv['unixtime'] <= end_ut))]\n",
        "\n",
        "np_ut = df_ohlcv['unixtime'].values\n",
        "np_rsi = df_ohlcv['rsi'].values\n",
        "\n",
        "display(df_ohlcv) # 確認表示"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "read csv: 1596186000 - 1598860800 (len=744)\n",
            "get  df : 1596153600 - 1598828400 (len=744)\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>unixtime</th>\n",
              "      <th>open</th>\n",
              "      <th>high</th>\n",
              "      <th>low</th>\n",
              "      <th>close</th>\n",
              "      <th>volume</th>\n",
              "      <th>rsi</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>1596240000</td>\n",
              "      <td>11361.0</td>\n",
              "      <td>11410.0</td>\n",
              "      <td>11246.0</td>\n",
              "      <td>11272.5</td>\n",
              "      <td>117023163</td>\n",
              "      <td>51.249199</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>1596243600</td>\n",
              "      <td>11272.5</td>\n",
              "      <td>11317.0</td>\n",
              "      <td>11256.5</td>\n",
              "      <td>11288.5</td>\n",
              "      <td>33841509</td>\n",
              "      <td>58.550317</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>1596247200</td>\n",
              "      <td>11288.5</td>\n",
              "      <td>11359.0</td>\n",
              "      <td>11283.5</td>\n",
              "      <td>11354.0</td>\n",
              "      <td>33731851</td>\n",
              "      <td>56.338028</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>1596250800</td>\n",
              "      <td>11354.0</td>\n",
              "      <td>11422.5</td>\n",
              "      <td>11342.0</td>\n",
              "      <td>11388.0</td>\n",
              "      <td>52346538</td>\n",
              "      <td>51.442704</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>1596254400</td>\n",
              "      <td>11388.0</td>\n",
              "      <td>11446.0</td>\n",
              "      <td>11353.5</td>\n",
              "      <td>11413.5</td>\n",
              "      <td>68915003</td>\n",
              "      <td>53.956835</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>739</th>\n",
              "      <td>1598814000</td>\n",
              "      <td>11649.0</td>\n",
              "      <td>11654.0</td>\n",
              "      <td>11644.5</td>\n",
              "      <td>11646.5</td>\n",
              "      <td>10491656</td>\n",
              "      <td>60.762332</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>740</th>\n",
              "      <td>1598817600</td>\n",
              "      <td>11646.5</td>\n",
              "      <td>11663.0</td>\n",
              "      <td>11627.5</td>\n",
              "      <td>11642.0</td>\n",
              "      <td>27056472</td>\n",
              "      <td>70.572917</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>741</th>\n",
              "      <td>1598821200</td>\n",
              "      <td>11642.0</td>\n",
              "      <td>11646.5</td>\n",
              "      <td>11605.5</td>\n",
              "      <td>11610.0</td>\n",
              "      <td>30006695</td>\n",
              "      <td>54.846939</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>742</th>\n",
              "      <td>1598824800</td>\n",
              "      <td>11610.0</td>\n",
              "      <td>11665.0</td>\n",
              "      <td>11599.5</td>\n",
              "      <td>11662.0</td>\n",
              "      <td>34962238</td>\n",
              "      <td>69.347826</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>743</th>\n",
              "      <td>1598828400</td>\n",
              "      <td>11662.0</td>\n",
              "      <td>11724.0</td>\n",
              "      <td>11655.0</td>\n",
              "      <td>11719.0</td>\n",
              "      <td>92285660</td>\n",
              "      <td>72.023810</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>720 rows × 7 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       unixtime     open     high      low    close     volume        rsi\n",
              "24   1596240000  11361.0  11410.0  11246.0  11272.5  117023163  51.249199\n",
              "25   1596243600  11272.5  11317.0  11256.5  11288.5   33841509  58.550317\n",
              "26   1596247200  11288.5  11359.0  11283.5  11354.0   33731851  56.338028\n",
              "27   1596250800  11354.0  11422.5  11342.0  11388.0   52346538  51.442704\n",
              "28   1596254400  11388.0  11446.0  11353.5  11413.5   68915003  53.956835\n",
              "..          ...      ...      ...      ...      ...        ...        ...\n",
              "739  1598814000  11649.0  11654.0  11644.5  11646.5   10491656  60.762332\n",
              "740  1598817600  11646.5  11663.0  11627.5  11642.0   27056472  70.572917\n",
              "741  1598821200  11642.0  11646.5  11605.5  11610.0   30006695  54.846939\n",
              "742  1598824800  11610.0  11665.0  11599.5  11662.0   34962238  69.347826\n",
              "743  1598828400  11662.0  11724.0  11655.0  11719.0   92285660  72.023810\n",
              "\n",
              "[720 rows x 7 columns]"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pnHRqGW1T8Tp"
      },
      "source": [
        "## 【2-2. バックテスト実行】"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8s1rlsrm8CJB",
        "outputId": "fbaa0bfb-f89b-4508-f05d-224dab6452f0"
      },
      "source": [
        "from dist import BacktestAssistant\n",
        "\n",
        "start_balance = 1.0   # テスト開始時の残高(BTC)\n",
        "leverage      = 0     # 取引時のレバレッジ(0:クロスマージン, 1～:分離マージン)\n",
        "lot           = 10000 # 取引ロットサイズ($)\n",
        "rsi_line      = 20    # RSI閾値\n",
        "\n",
        "# BacktestAssistant生成\n",
        "# (BitMEX/bybit : BTC/USD設定)\n",
        "test = BacktestAssistant(\n",
        "       balance           = start_balance, # 初期証拠金\n",
        "       trade_leverage    = leverage       # 取引 レバレッジ (0:クロスマージン, 1～:分離マージン)\n",
        "       #max_leverage      = 100,          # 取引所 最大レバレッジ\n",
        "       #losscut           = 50,           # 最低証拠金維持率(%) ロスカットライン\n",
        "       #taker             = 0.075,        # テイカー手数料(%)\n",
        "       #maker             = -0.025,       # メイカー手数料(%)\n",
        "       #tick_mode         = 'ltp',        # ティックモード ('ltp' or 'bidask')\n",
        "       #take_cost         = 0.5,          # 'ltp'の場合のみ 成行注文時の取引コスト(スプレッド)\n",
        "       #contract_type     = 'inverse',    # 契約タイプ (inverse:BTC/USD, linear:BTC/JPY etc.)\n",
        "       #trans_digits      = 8,            # 取引通貨 小数桁数 (BTC:8桁)\n",
        "       #settle_digits     = 1,            # 決済通貨 小数桁数 (USD:1桁)\n",
        "       #sharpe_ratio_unit = 86400         # シャープレシオ期間単位 (秒)\n",
        ")\n",
        "# コメントアウトは初期値 (必要に応じて設定変更する)\n",
        "\n",
        "# Funding Rate設定\n",
        "test.set_funding_rate(rate = 0.01)\n",
        "\n",
        "# 出力オプション設定\n",
        "test.set_output_option(\n",
        "        disp_progress = True    # 進捗表示\n",
        "        #tick_csv      = False, # tick履歴csv出力\n",
        "        #order_csv     = True,  # 注文履歴csv出力\n",
        "        #execution_csv = True,  # 約定履歴csv出力\n",
        "        #position_csv  = True,  # ポジション履歴csv出力\n",
        "        #balance_csv   = True,  # 残高履歴csv出力\n",
        "        #chart_data    = True   # チャート連携データ出力\n",
        ")\n",
        "# コメントアウトは初期値 (履歴csvが不要ならFalseを設定)\n",
        "\n",
        "# tickデータ設定 (1時間足OHLCVのopen, high, low, close価格をtickデータに展開)\n",
        "test.preset_ltp_ticks_from_ohlcv_df(df_ohlcv)\n",
        "\n",
        "# 初期処理 (テスト開始時刻を設定)\n",
        "test.initialize(start_time = start_ut)\n",
        "\n",
        "# テストループ\n",
        "for i, t in enumerate(np_ut):\n",
        "\n",
        "    # 指定時刻まで進める\n",
        "    if test.time() < t:\n",
        "        test.sleep_to_time(t)\n",
        "\n",
        "    # 直前足RSI\n",
        "    rsi = np_rsi[i-1] if i > 0 else 50\n",
        "\n",
        "    # データ取得\n",
        "    price   = test.get_price()       # 現在価格       : {ltp, bid, ask}\n",
        "    pos     = test.get_position()    # 現在建玉       : {size, avr_entry, margin, etc.}\n",
        "    orders  = test.get_open_orders() # アクティブ注文 : [{id, timestamp, status, etc.}, {},...]\n",
        "    balance = test.get_balance()     # 現在残高       : float\n",
        "\n",
        "    # ノーポジション\n",
        "    if pos['size'] == 0:\n",
        "        # 買われ過ぎ\n",
        "        if rsi > 100 - rsi_line:\n",
        "            res = test.market_order('Sell', lot) # 売りでエントリー\n",
        "            if res['status_code'] == 400:\n",
        "                print(res['message'])\n",
        "        # 売られ過ぎ\n",
        "        elif rsi < rsi_line:\n",
        "            res = test.market_order('Buy', lot)  # 買いでエントリー\n",
        "            if res['status_code'] == 400:\n",
        "                print(res['message'])\n",
        "\n",
        "    # ロングポジション\n",
        "    elif pos['size'] > 0:\n",
        "        # 売られ過ぎ解消\n",
        "        if rsi > 50:\n",
        "            res = test.market_order('Sell', abs(pos['size'])) # 売りでイグジット\n",
        "            if res['status_code'] == 400:\n",
        "                print(res['message'])\n",
        "\n",
        "    # ショートポジション\n",
        "    elif pos['size'] < 0:\n",
        "        # 買われ過ぎ解消\n",
        "        if rsi < 50:\n",
        "            res = test.market_order('Buy', abs(pos['size'])) # 買いでイグジット\n",
        "            if res['status_code'] == 400:\n",
        "                print(res['message'])\n",
        "\n",
        "# 建玉があればクローズ\n",
        "pos = test.get_position()\n",
        "if pos['size'] < 0:\n",
        "    test.market_order('Buy', abs(pos['size']))\n",
        "elif pos['size'] > 0:\n",
        "    test.market_order('Sell', abs(pos['size']))\n",
        "\n",
        "# 終了処理\n",
        "results = test.terminate()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Now initializing...\n",
            "Completed initialize process.\n",
            "[Start] time:1596240000.0  ltp:11361.0  balance:1.0  [Fee] taker:0.075  maker:-0.025  fr:0.01\n",
            "preset ticks period: 1596240000.0 - 1598831100.0 (2116)\n",
            "0% complete. (1 / 2,116)\n",
            "10% complete. (212 / 2,116)\n",
            "20% complete. (424 / 2,116)\n",
            "30% complete. (635 / 2,116)\n",
            "40% complete. (847 / 2,116)\n",
            "50% complete. (1,059 / 2,116)\n",
            "60% complete. (1,270 / 2,116)\n",
            "70% complete. (1,482 / 2,116)\n",
            "80% complete. (1,693 / 2,116)\n",
            "90% complete. (1,905 / 2,116)\n",
            "Now terminating...\n",
            "Save order_history 28 records.(./result/orders.csv)\n",
            "Save executions 117 records.(./result/executions.csv)\n",
            "Save position_history 548 records.(./result/positions.csv)\n",
            "Save balance_history 637 records.(./result/balances.csv)\n",
            "\n",
            "[Result]\n",
            "  [Time    ] 2020/08/01 09:00:00 - 2020/08/31 08:00:00\n",
            "  [Balance ] 1.0 -> 1.0201 (+2.01%)  Sharpe Ratio:-0.0463\n",
            "  [Orders  ] Total:28 (Open:0  Executed:28  Canceled:0)\n",
            "  [Position] Max Long:10,000.0  Max Short:-10,000.0  Min Margin:11115.76%\n",
            "\n",
            "[Execution statistics]  PF:1.58\n",
            "  [Total   ] Count:28(Size:280,000)  PnL:+0.0354  Avr:+0.0013  Price Range:+497.5\n",
            "  [Profit  ] Count:6(42.86%)  Sum:+0.096  Avr:+0.016  Max:+0.0388  MaxLen:2(+0.0464)\n",
            "  [Loss    ] Count:8(57.14%)  Sum:-0.0607  Avr:-0.0076  Max:-0.0181  MaxLen:3(-0.0261)\n",
            "  [Fee     ] Trade:0.018  Funding:-0.0027\n",
            "  [Max risk]\n",
            "    Drawdown       :-2.79%(-0.0293) 2020/08/31 00:00:00\n",
            "    Unrealised loss:-4.28%(-0.0449) 2020/08/12 15:30:00\n",
            "\n",
            "[Fiat balance]\n",
            "  [Start ] 11,361.0 (Balance:1.0 Price:11361.0)\n",
            "  [End   ] 11,860.7 (Balance:1.0201 Price:11627.0)\n",
            "  [Result] 499.7 (+4.40%)  Sharpe Ratio:-0.2182\n",
            "\n",
            "[Fiat execution statistics]  PF:1.08\n",
            "  [Total   ] Count:28(Size:0)  PnL:+179  Avr:+6.0  Price Range:+0\n",
            "  [Profit  ] Count:11(42.31%)  Sum:+2,481  Avr:+226.0  Max:+678  MaxLen:3(+176)\n",
            "  [Loss    ] Count:15(57.69%)  Sum:-2,302  Avr:-153.0  Max:-939  MaxLen:3(-520)\n",
            "  [Fee     ] Trade:0  Funding:0\n",
            "  [Max risk]\n",
            "    Drawdown       :-8.87%(-1,138) 2020/08/26 14:00:00\n",
            "    Unrealised loss:-4.28%(-497) 2020/08/12 15:30:00\n",
            "\n",
            "Completed terminate process.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X2ojvvayUNm9"
      },
      "source": [
        "## 【2-3. バックテスト 結果チャート作成】"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JlS6lqJc8vcH"
      },
      "source": [
        "from dist import ChartCreator as cc\n",
        "\n",
        "dict_data = results['data']\n",
        "dict_statistics = results['statistics']\n",
        "dict_chart = results['chart']\n",
        "\n",
        "# レイアウトカスタマイズ\n",
        "cc.initialize()\n",
        "cc.settings['title'] = 'Result chart'\n",
        "\n",
        "# X軸設定\n",
        "cc.set_xaxis(start=0, end=0, is_unixtime=True)\n",
        "\n",
        "# メインチャート(ax:0)\n",
        "cc.add_subchart(ax=0, label=\"USD\", grid=True)\n",
        "\n",
        "# ローソクバー設定(OHLCV)\n",
        "cc.set_ohlcv_df(df_ohlcv)\n",
        "\n",
        "# 買い注文ポイント設定\n",
        "cc.set_marker(dict_chart['buy']['timestamp'], dict_chart['buy']['price'], ax=0, color='blue', size=30.0, mark='^', name='Buy')\n",
        "\n",
        "# 売り注文ポイント設定\n",
        "cc.set_marker(dict_chart['sell']['timestamp'], dict_chart['sell']['price'], ax=0, color='red', size=30.0, mark='v', name='Sell')\n",
        "\n",
        "# 清算注文ポイント設定\n",
        "if len(dict_chart['liquid']['timestamp']) > 0:\n",
        "    cc.set_marker(dict_chart['liquid']['timestamp'], dict_chart['liquid']['price'], ax=0, color='magenta', size=30.0, mark='D', name='Liquidation')\n",
        "\n",
        "# RSIサブチャート(ax:1)\n",
        "cc.add_subchart(ax=1, label=\"RSI\", grid=True)\n",
        "\n",
        "# RSI設定\n",
        "cc.set_line(np_ut, np_rsi, ax=1, color='green', width=1.0, name='RSI')\n",
        "cc.set_line([np_ut[0], np_ut[-1]], [rsi_line, rsi_line], ax=1, color='red', width=1.0, name='RSI_20')\n",
        "cc.set_line([np_ut[0], np_ut[-1]], [100-rsi_line, 100-rsi_line], ax=1, color='blue', width=1.0, name='RSI_80')\n",
        "\n",
        "# ポジション推移サブチャート(ax:2)\n",
        "cc.add_subchart(ax=2, label=\"Position\", grid=True)\n",
        "\n",
        "# ポジション設定\n",
        "cc.set_band(dict_chart['position']['unixtime'], dict_chart['position']['size'], dict_chart['position']['zero'], ax=2, up_color='blue', down_color='red',\n",
        "            alpha=0.5, edge_width=1.0, edge_color='dimgray', line_mode='hv', name='Position')\n",
        "\n",
        "# 損益推移サブチャート(ax:3)\n",
        "cc.add_subchart(ax=3, label='PnL', grid=True)\n",
        "\n",
        "# 損益設定\n",
        "cc.set_line(dict_chart['pnl']['unixtime'], dict_chart['pnl']['unrealised_pnl'], ax=3, color='green', width=0.8, name='Unrealised')\n",
        "cc.set_band(dict_chart['pnl']['unixtime'], dict_chart['pnl']['pnl'], dict_chart['pnl']['zero'], ax=3, up_color='skyblue', down_color='red',\n",
        "           alpha=0.2, edge_width=1.0, edge_color='dimgray', name='PL')\n",
        "\n",
        "# フィアット損益推移サブチャート(ax:4)\n",
        "cc.add_subchart(ax=4, label='Fiat PnL', grid=True)\n",
        "\n",
        "# フィアット損益設定\n",
        "fiat_blc = dict_chart['pnl']['balance'] * dict_chart['pnl']['price']\n",
        "fiat_start = fiat_blc[0]\n",
        "fiat_blc = fiat_blc - fiat_start\n",
        "fiat_unrel_blc = dict_chart['pnl']['unrealised_balance'] * dict_chart['pnl']['price']\n",
        "fiat_unrel_blc = fiat_unrel_blc - fiat_start\n",
        "cc.set_line(dict_chart['pnl']['unixtime'], fiat_unrel_blc, ax=4, color='green', width=0.8, name='Include unrealised')\n",
        "cc.set_band(dict_chart['pnl']['unixtime'], fiat_blc, dict_chart['pnl']['zero'],\n",
        "            ax=4, up_color='orange', down_color='red',\n",
        "            alpha=0.2, edge_width=1.0, edge_color='dimgray', name='Balance')\n",
        "\n",
        "# チャート生成\n",
        "file_path = './result/result_chart'\n",
        "cc.create_chart(file_path + \".png\", \"png\")\n",
        "cc.create_chart(file_path + \".html\", \"html\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UghAvPyCF56_"
      },
      "source": [
        "## 【2-4. チャート画像表示 (matplotlib)】"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 649
        },
        "id": "SX0BK6c4FDSV",
        "outputId": "fa17fa5d-7ad6-4f2a-8325-26fbd4c32ee0"
      },
      "source": [
        "from IPython.display import Image, display_png\n",
        "display_png(Image(file_path + '.png'))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gKWJrcskF-ZH"
      },
      "source": [
        "## 【2-5. インタラクティブチャート表示 (plotly)】"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 817
        },
        "id": "S0oIM1clFd6P",
        "outputId": "73b9e6db-1a6a-445e-b62f-33866615d0b5"
      },
      "source": [
        "from IPython.display import HTML, display_html\n",
        "display_html(HTML(filename=file_path + '.html'))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<html>\n",
              "<head><script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script><meta charset=\"utf-8\"/></head>\n",
              "<body>\n",
              "<div>\n",
              "<div class=\"plotly-graph-div\" id=\"b46303b8-09bb-4afe-b6ad-c7aa57dd4b8d\" style=\"height:800px; width:1200px;\"></div>\n",
              "<script type=\"text/javascript\">\n",
              "                \n",
              "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
              "                    \n",
              "                if (document.getElementById(\"b46303b8-09bb-4afe-b6ad-c7aa57dd4b8d\")) {\n",
              "                    Plotly.newPlot(\n",
              "                        'b46303b8-09bb-4afe-b6ad-c7aa57dd4b8d',\n",
              "                        [{\"close\": [11272.5, 11288.5, 11354.0, 11388.0, 11413.5, 11632.0, 11664.5, 11680.0, 11694.0, 11724.0, 11640.0, 11663.5, 11689.0, 11544.0, 11618.5, 11647.5, 11655.5, 11759.5, 11691.0, 11800.0, 11867.0, 11798.5, 11816.5, 11827.5, 11808.0, 11963.0, 11949.5, 12036.0, 11181.5, 11260.0, 11303.5, 11338.0, 11290.0, 11308.5, 11260.0, 11109.5, 11004.0, 11127.0, 11141.5, 11100.5, 11210.0, 11274.0, 11238.5, 11200.0, 11100.5, 11142.5, 11125.0, 11072.0, 11132.0, 11122.0, 11186.5, 11139.0, 11182.0, 11202.0, 11199.0, 11210.0, 11210.5, 11142.0, 11213.5, 11242.0, 11233.0, 11295.0, 11309.5, 11394.5, 11363.0, 11437.0, 11429.5, 11422.0, 11386.5, 11214.5, 11230.0, 11244.0, 11380.0, 11350.0, 11294.5, 11273.5, 11324.0, 11292.0, 11258.0, 11303.5, 11256.5, 11262.5, 11229.5, 11120.5, 11162.0, 11134.0, 11208.0, 11214.0, 11170.5, 11258.5, 11226.0, 11230.5, 11212.0, 11238.5, 11232.0, 11188.0, 11171.0, 11179.5, 11192.5, 11239.0, 11244.0, 11293.0, 11282.5, 11279.5, 11301.0, 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\"arial, sans-selif\", \"size\": 10}, \"tickprefix\": \" \", \"title\": {\"text\": \"Volume\"}}, \"yaxis3\": {\"anchor\": \"x\", \"autorange\": false, \"domain\": [0.42857142857142855, 0.5714285714285714], \"exponentformat\": \"none\", \"fixedrange\": false, \"gridcolor\": \"dimgray\", \"range\": [8.590583580423733, 101.39097445428548], \"showgrid\": true, \"showspikes\": true, \"showticklabels\": true, \"spikecolor\": \"dimgray\", \"spikedash\": \"solid\", \"spikemode\": \"toaxis+across\", \"spikesnap\": \"data\", \"spikethickness\": 1.5, \"tickcolor\": \"dimgray\", \"tickfont\": {\"family\": \"arial, sans-selif\", \"size\": 10}, \"ticksuffix\": \" \", \"title\": {\"text\": \"RSI\"}}, \"yaxis4\": {\"anchor\": \"x\", \"autorange\": false, \"domain\": [0.42857142857142855, 0.5714285714285714], \"fixedrange\": false, \"overlaying\": \"y3\", \"showgrid\": false, \"showspikes\": true, \"showticklabels\": true, \"side\": \"right\", \"spikecolor\": \"dimgray\", \"spikedash\": \"solid\", \"spikemode\": \"toaxis+across\", \"spikesnap\": \"data\", \"spikethickness\": 1.5, \"tickcolor\": \"dimgray\", \"tickfont\": {\"family\": \"arial, sans-selif\", \"size\": 10}, \"tickprefix\": \" \", \"title\": {\"text\": \"Volume\"}}, \"yaxis5\": {\"anchor\": \"x\", \"autorange\": false, \"domain\": [0.2857142857142857, 0.42857142857142855], \"exponentformat\": \"none\", \"fixedrange\": false, \"gridcolor\": \"dimgray\", \"range\": [-11000.0, 11000.0], \"showgrid\": true, \"showspikes\": true, \"showticklabels\": true, \"spikecolor\": \"dimgray\", \"spikedash\": \"solid\", \"spikemode\": \"toaxis+across\", \"spikesnap\": \"data\", \"spikethickness\": 1.5, \"tickcolor\": \"dimgray\", \"tickfont\": {\"family\": \"arial, sans-selif\", \"size\": 10}, \"ticksuffix\": \" \", \"title\": {\"text\": \"Position\"}}, \"yaxis6\": {\"anchor\": \"x\", \"autorange\": false, \"domain\": [0.2857142857142857, 0.42857142857142855], \"fixedrange\": false, \"overlaying\": \"y5\", \"showgrid\": false, \"showspikes\": true, \"showticklabels\": true, \"side\": \"right\", \"spikecolor\": \"dimgray\", \"spikedash\": \"solid\", \"spikemode\": \"toaxis+across\", \"spikesnap\": \"data\", \"spikethickness\": 1.5, \"tickcolor\": \"dimgray\", \"tickfont\": {\"family\": \"arial, sans-selif\", \"size\": 10}, \"tickprefix\": \" \", \"title\": {\"text\": \"Volume\"}}, \"yaxis7\": {\"anchor\": \"x\", \"autorange\": false, \"domain\": [0.14285714285714285, 0.2857142857142857], \"exponentformat\": \"none\", \"fixedrange\": false, \"gridcolor\": \"dimgray\", \"range\": [-0.039951245500000024, 0.09737045549999998], \"showgrid\": true, \"showspikes\": true, \"showticklabels\": true, \"spikecolor\": \"dimgray\", \"spikedash\": \"solid\", \"spikemode\": \"toaxis+across\", \"spikesnap\": \"data\", \"spikethickness\": 1.5, \"tickcolor\": \"dimgray\", \"tickfont\": {\"family\": \"arial, sans-selif\", \"size\": 10}, \"ticksuffix\": \" \", \"title\": {\"text\": \"PnL\"}}, \"yaxis8\": {\"anchor\": \"x\", \"autorange\": false, \"domain\": [0.14285714285714285, 0.2857142857142857], \"fixedrange\": false, \"overlaying\": \"y7\", \"showgrid\": false, \"showspikes\": true, \"showticklabels\": true, \"side\": \"right\", \"spikecolor\": \"dimgray\", \"spikedash\": \"solid\", \"spikemode\": \"toaxis+across\", \"spikesnap\": \"data\", \"spikethickness\": 1.5, \"tickcolor\": \"dimgray\", \"tickfont\": {\"family\": \"arial, sans-selif\", \"size\": 10}, \"tickprefix\": \" \", \"title\": {\"text\": \"Volume\"}}, \"yaxis9\": {\"anchor\": \"x\", \"autorange\": false, \"domain\": [0.0, 0.14285714285714285], \"exponentformat\": \"none\", \"fixedrange\": false, \"gridcolor\": \"dimgray\", \"range\": [-920.114277060001, 1630.8501798600018], \"showgrid\": true, \"showspikes\": true, \"showticklabels\": true, \"spikecolor\": \"dimgray\", \"spikedash\": \"solid\", \"spikemode\": \"toaxis+across\", \"spikesnap\": \"data\", \"spikethickness\": 1.5, \"tickcolor\": \"dimgray\", \"tickfont\": {\"family\": \"arial, sans-selif\", \"size\": 10}, \"ticksuffix\": \" \", \"title\": {\"text\": \"Fiat PnL\"}}},\n",
              "                        {\"scrollZoom\": true, \"displayModeBar\": true, \"responsive\": true}\n",
              "                    )\n",
              "                };\n",
              "                \n",
              "            </script>\n",
              "</div>\n",
              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Cu_gayzUpxYx"
      },
      "source": [
        "# 3. 公開ロジックのバックテスト\n",
        "* [平均様 バックテスト](https://gist.github.com/nagishin/06edb1244ca10d44041ad2c2c8d9a8ab)<br>\n",
        "【参考】[れたすさん著 【BTC自動取引bot】HEIKIN_ORACLE_ver2.0](https://note.com/letasun/n/n9366d3055824)<br>\n",
        "<br>\n",
        "\n",
        "* [時刻アノマリー バックテスト](https://gist.github.com/nagishin/e79ec81cdef8a9b1dafed7eb65383fc1)<br>\n",
        "【参考】[Hohetoさん著 ビットコイン価格における時刻アノマリーの存在](https://note.com/hht/n/nc0caf98477db)<br>\n",
        "<br>\n",
        "\n",
        "* [ドテンくん バックテスト](https://gist.github.com/nagishin/5804a8c07a21e7f4914e0f2389be513c)<br>\n",
        "【参考】[ビットコイン自動売買bot「ドテンくん」の特徴と評判](https://jitekineko.com/investment-trade-bitcoin-dotenkun/)<br>\n",
        "<br>\n",
        "\n",
        "* [バブル相場用の回転ボット バックテスト](https://gist.github.com/nagishin/5a96bb2480d37582c33263f00c6f0717)<br>\n",
        "【参考】[Hohetoさん著 バブル相場用の回転ボットのコンセプトとQuantZoneロジック](https://note.com/hht/n/n63022edc4610)<br>\n",
        "<br>\n",
        "\n",
        "* [養分ロングbot バックテスト](https://gist.github.com/nagishin/9f5fda6485d5d2f3c1d134e7028c4d0e)<br>\n",
        "【参考】[ともいさん著 養分ロングbot【bybit用】](https://note.com/tomoiyuma/n/n35018ec09b4f)<br>\n",
        "<br>"
      ]
    }
  ]
}