nagishin/backtest_hourly_2021.ipynb

## backtest_hourly_2021.ipynb
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  "metadata": {
    "colab": {
      "name": "backtest_hourly_2021.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyOYI5/e1WzVPT/8sTGumZad",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/nagishin/b173d1a9fce37500e764e0a6a3f8a55a/backtest_hourly_2021.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IT8KDp1hQmYv"
      },
      "source": [
        "---\n",
        "# 【時刻アノマリーバックテスト】\n",
        "<b>タイプ</b>\n",
        "* 特定時刻 定期トレード\n",
        "\n",
        "<b>ロジック</b><br>\n",
        "　日本時間 AM9:01において\n",
        "* 直前の5分間の値動きがプラスであれば売りエントリー\n",
        "* 直前の5分間の値動きがマイナスであれば買いエントリー\n",
        "* エントリーした場合、28分後に決済<br>\n",
        "本家ロジックでは毎時1分の検証・考察をされていますが、取引手数料をカバーする値幅が取れないため、特性が顕著なAM9:00に限定してバックテストを実施します。\n",
        "\n",
        "<b>対象データ</b>\n",
        "* tickデータ ： BitMEX 1m OHLCV\n",
        "\n",
        "<b>対象期間</b>\n",
        "* 2021-01-01 ～ 2021-11-01\n",
        "\n",
        "<b>[参考]</b><br>\n",
        "[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)\n",
        "<br>\n",
        "<br>\n",
        "<b>[注意]</b><br>\n",
        "本バックテストは上記noteにて公開されているロジックを参考にテストコードを作成していますが、動作を忠実に再現しているものではないことをご了承ください。\n",
        "\n",
        "---\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y_9-OuvGNvWW"
      },
      "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",
        "* backtest_assistant.py (バックテストツール)、chart_creator.py (チャート作成ツール) をアップロード\n",
        "* 必要パッケージのインストール"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9qvSZ0v3zeks"
      },
      "source": [
        "## 1-1. バックテストに必要なファイルをアップロード\n",
        "以下のツールに同梱されているpythonスクリプトファイルをアップロードします。<br>\n",
        "(本notebookは以下のファイルがないと動作しません。)\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": "code",
      "metadata": {
        "id": "mMMxBUEPzbEr"
      },
      "source": [
        "from google.colab import files\n",
        "files.upload()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2avmQKiAw5Ps"
      },
      "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": "RzalryYnwxue"
      },
      "source": [
        "# 共通\n",
        "!pip install numpy\n",
        "!pip install pandas\n",
        "!pip install datetime\n",
        "!pip install pytz\n",
        "# ChartCreator\n",
        "!pip install matplotlib\n",
        "!pip install mpl_finance\n",
        "!pip install plotly\n",
        "!pip install webcolors\n",
        "!pip install beautifulsoup4\n",
        "!pip install lxml\n",
        "# DataUtility\n",
        "!pip install git+https://github.com/nagishin/DataUtility.git"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2NS_ZXf9N244"
      },
      "source": [
        "# 2. 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": "markdown",
      "metadata": {
        "id": "STbU1X9uYkFy"
      },
      "source": [
        "## 2-1. バックテスト期間の設定\n",
        "2020年の年初から現在までをテスト期間として設定します。<br>\n",
        "ここで設定した期間を基にテストに必要なデータ取得を行います。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LT5IYePqzY_7"
      },
      "source": [
        "# coding: utf-8\n",
        "from datetime import datetime\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import DataUtility as du\n",
        "from backtest_assistant import BacktestAssistant\n",
        "\n",
        "#テスト期間\n",
        "TEST_START = '2021/01/01 09:00:00+0900'\n",
        "TEST_END   = '2021/11/01 09:00:00+0900'\n",
        "\n",
        "# テスト期間の日付文字列をUnix Timeに変換\n",
        "start_date  = datetime.strptime(TEST_START, '%Y/%m/%d %H:%M:%S%z') # テスト開始時刻 (datetime)\n",
        "end_date    = datetime.strptime(TEST_END, '%Y/%m/%d %H:%M:%S%z')   # テスト終了時刻 (datetime)\n",
        "start_ut    = int(start_date.timestamp()) # テスト開始時刻 (UnixTime)\n",
        "end_ut      = int(end_date.timestamp())   # テスト終了時刻 (UnixTime)"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ClYxRtnRZsX_"
      },
      "source": [
        "## 2-2. バックテストデータの取得・加工\n",
        "ロジック判定および注文は毎時処理ですが、途中の決済注文、含み損益の可視化、ファンディング手数料計算の観点からバックテストに設定するtickデータは1m OHLCVとします。<br>\n",
        "(tickデータに沿って含み損益や証拠金維持率、ロスカット判定、ファンディング手数料etc.が執行されます。)<br>\n",
        "\n",
        "* 1m OHLCVを取得 (tickデータ df_ohlcv_1m)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oMtkc78OMjnI"
      },
      "source": [
        "### BitMEX OHLCV 1分足取得"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rWmpYDCj10IJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "outputId": "e412a675-27f8-46f2-e0bd-944d99ea3407"
      },
      "source": [
        "# DataUtilityを使用してBitMEX OHLCV(1m)を取得\n",
        "df_ohlcv_1m = du.Tool.get_ohlcv_from_bitmex(\n",
        "                    start_ut         = start_ut,         # 取得開始(UnixTime)\n",
        "                    end_ut           = end_ut,           # 取得終了(UnixTime)\n",
        "                    period           = 1,                # 時間足期間(分)\n",
        "                    csv_path         = './ohlcv_1m.csv', # 取得結果保存先(CSVパス)\n",
        "                    request_interval = 0.5)              # RESTリクエスト待機時間(秒)\n",
        "display(df_ohlcv_1m) # 確認表示"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "save csv: 1609459200 - 1635724740 (len=437760)\n",
            "get  df : 1609459200 - 1635724740 (len=437760)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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              "<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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1609459200</td>\n",
              "      <td>28951.0</td>\n",
              "      <td>29004.0</td>\n",
              "      <td>28950.5</td>\n",
              "      <td>29004.0</td>\n",
              "      <td>995031</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1609459260</td>\n",
              "      <td>29004.0</td>\n",
              "      <td>29050.0</td>\n",
              "      <td>29003.5</td>\n",
              "      <td>29043.5</td>\n",
              "      <td>3328855</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1609459320</td>\n",
              "      <td>29043.5</td>\n",
              "      <td>29044.0</td>\n",
              "      <td>29016.5</td>\n",
              "      <td>29017.0</td>\n",
              "      <td>1220460</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1609459380</td>\n",
              "      <td>29017.0</td>\n",
              "      <td>29026.0</td>\n",
              "      <td>29000.0</td>\n",
              "      <td>29016.0</td>\n",
              "      <td>691254</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1609459440</td>\n",
              "      <td>29016.0</td>\n",
              "      <td>29016.5</td>\n",
              "      <td>29015.0</td>\n",
              "      <td>29015.0</td>\n",
              "      <td>463692</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>437755</th>\n",
              "      <td>1635724500</td>\n",
              "      <td>61358.5</td>\n",
              "      <td>61389.0</td>\n",
              "      <td>61350.5</td>\n",
              "      <td>61389.0</td>\n",
              "      <td>346800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>437756</th>\n",
              "      <td>1635724560</td>\n",
              "      <td>61389.0</td>\n",
              "      <td>61388.5</td>\n",
              "      <td>61370.0</td>\n",
              "      <td>61370.0</td>\n",
              "      <td>109500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>437757</th>\n",
              "      <td>1635724620</td>\n",
              "      <td>61370.0</td>\n",
              "      <td>61370.0</td>\n",
              "      <td>61345.5</td>\n",
              "      <td>61345.5</td>\n",
              "      <td>80300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>437758</th>\n",
              "      <td>1635724680</td>\n",
              "      <td>61345.5</td>\n",
              "      <td>61351.0</td>\n",
              "      <td>61345.5</td>\n",
              "      <td>61351.0</td>\n",
              "      <td>65400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>437759</th>\n",
              "      <td>1635724740</td>\n",
              "      <td>61351.0</td>\n",
              "      <td>61351.0</td>\n",
              "      <td>61343.5</td>\n",
              "      <td>61344.0</td>\n",
              "      <td>256500</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>437760 rows × 6 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          unixtime     open     high      low    close   volume\n",
              "0       1609459200  28951.0  29004.0  28950.5  29004.0   995031\n",
              "1       1609459260  29004.0  29050.0  29003.5  29043.5  3328855\n",
              "2       1609459320  29043.5  29044.0  29016.5  29017.0  1220460\n",
              "3       1609459380  29017.0  29026.0  29000.0  29016.0   691254\n",
              "4       1609459440  29016.0  29016.5  29015.0  29015.0   463692\n",
              "...            ...      ...      ...      ...      ...      ...\n",
              "437755  1635724500  61358.5  61389.0  61350.5  61389.0   346800\n",
              "437756  1635724560  61389.0  61388.5  61370.0  61370.0   109500\n",
              "437757  1635724620  61370.0  61370.0  61345.5  61345.5    80300\n",
              "437758  1635724680  61345.5  61351.0  61345.5  61351.0    65400\n",
              "437759  1635724740  61351.0  61351.0  61343.5  61344.0   256500\n",
              "\n",
              "[437760 rows x 6 columns]"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1kna4sNd3AcU"
      },
      "source": [
        "# 1分足DataFrameからテストに使用する列をndarrayに変換\n",
        "np_ut = df_ohlcv_1m['unixtime'].values\n",
        "np_open = df_ohlcv_1m['open'].values"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "20KNI_OxfZSG"
      },
      "source": [
        "# 3. バックテスト実行"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kQqcfZ3R3dAm",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b679f215-dc58-4b8f-e9f4-b4bda9fe416f"
      },
      "source": [
        "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",
        "\n",
        "# BacktestAssistant生成\n",
        "test = BacktestAssistant(\n",
        "        balance        = start_balance,\n",
        "        trade_leverage = leverage,\n",
        "        tick_mode      = 'ltp', # tick_mode='ltp'のため、\n",
        "        take_cost      = 0.5)  # 成行注文時の取引コスト(スプレッド)を$0.5に設定\n",
        "\n",
        "test.set_output_option(disp_progress = True)      # 出力オプション設定 (進捗率表示ON)\n",
        "test.preset_ltp_ticks_from_ohlcv_df(df_ohlcv_1m) # tickデータ設定 (1分足OHLCVのopen, high, low, close価格をtickデータに展開)\n",
        "\n",
        "# バックテスト初期処理 (テスト開始時刻を設定)\n",
        "test.initialize(start_time = np_ut[0])\n",
        "\n",
        "# テストループ (1時間毎)--------------------------------------------------------\n",
        "for i, unixtime in enumerate(np_ut):\n",
        "    if test.time() < unixtime:\n",
        "        test.sleep_to_time(unixtime) # 指定時刻(unixtime)までtickを進める\n",
        "    if i < 5:\n",
        "        continue\n",
        "\n",
        "    now_utc = test.nowutc()          # 現在時刻(datetime UTC)取得\n",
        "    now_price = test.get_price()['ltp'] # 現在価格取得\n",
        "\n",
        "    if now_utc.hour != 0:              # UTC　0時でない場合は読み飛ばし\n",
        "        continue\n",
        "\n",
        "    # エントリー判定\n",
        "    if now_utc.minute == 1:         # 時刻 1分\n",
        "        pre_5_min = np_open[i - 5] # 5分前の価格を取得\n",
        "        if now_price < pre_5_min:   # 値動きがマイナス\n",
        "            test.market_order(side='Buy', size=lot)  # 買いエントリー\n",
        "        else:                         # 値動きがプラス\n",
        "            test.market_order(side='Sell', size=lot) # 売りエントリー\n",
        "    # イグジット判定\n",
        "    elif now_utc.minute == 28:      # 時刻 28分\n",
        "        pos = test.get_position()    # 現在のポジションを取得し、クローズ\n",
        "        if pos['size'] > 0:\n",
        "            test.market_order(side='Sell', size=abs(pos['size']))\n",
        "        elif pos['size'] < 0:\n",
        "            test.market_order(side='Buy', size=abs(pos['size']))\n",
        "#-------------------------------------------------------------------------------\n",
        "\n",
        "pos = test.get_position() # テスト終了時にポジションがあればクローズ\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",
        "# バックテスト終了処理\n",
        "results = test.terminate()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Now initializing...\n",
            "Completed initialize process.\n",
            "[Start] time:1609459200.0  ltp:28951.0  balance:1.0  [Fee] taker:0.075  maker:-0.025  fr:0\n",
            "preset ticks period: 1609459200.0 - 1635724785.0 (1127373)\n",
            "0% complete. (1 / 1,127,373)\n",
            "10% complete. (112,738 / 1,127,373)\n",
            "20% complete. (225,475 / 1,127,373)\n",
            "30% complete. (338,212 / 1,127,373)\n",
            "40% complete. (450,950 / 1,127,373)\n",
            "50% complete. (563,687 / 1,127,373)\n",
            "60% complete. (676,424 / 1,127,373)\n",
            "70% complete. (789,162 / 1,127,373)\n",
            "80% complete. (901,899 / 1,127,373)\n",
            "90% complete. (1,014,636 / 1,127,373)\n",
            "Now terminating...\n",
            "Save order_history 606 records.(./result/orders.csv)\n",
            "Save executions 606 records.(./result/executions.csv)\n",
            "Save position_history 19761 records.(./result/positions.csv)\n",
            "Save balance_history 19761 records.(./result/balances.csv)\n",
            "\n",
            "[Result]\n",
            "  [Time    ] 2021/01/01 09:00:00 - 2021/11/01 08:59:00\n",
            "  [Balance ] 1.0 -> 0.914 (-8.60%)  Sharpe Ratio:-0.1259\n",
            "  [Orders  ] Total:606 (Open:0  Executed:606  Canceled:0)\n",
            "  [Position] Max Long:10,000.0  Max Short:-10,000.0  Min Margin:27018.31%\n",
            "\n",
            "[Execution statistics]  PF:1.08\n",
            "  [Total   ] Count:606(Size:6,060,000)  PnL:+0.0176  Avr:+0.0  Price Range:+4,542.0\n",
            "  [Profit  ] Count:160(53.16%)  Sum:+0.2283  Avr:+0.0014  Max:+0.0117  MaxLen:7(+0.0089)\n",
            "  [Loss    ] Count:141(46.84%)  Sum:-0.2107  Avr:-0.0015  Max:-0.0133  MaxLen:7(-0.0073)\n",
            "  [Fee     ] Trade:0.1037  Funding:0.0\n",
            "  [Max risk]\n",
            "    Drawdown       :-9.25%(-0.0925) 2021/09/18 09:01:00\n",
            "    Unrealised loss:-2.23%(-0.0209) 2021/05/13 09:01:30\n",
            "\n",
            "[Fiat balance]\n",
            "  [Start ] 28,951.0 (Balance:1.0 Price:28951.0)\n",
            "  [End   ] 56,907.9 (Balance:0.914 Price:62262.5)\n",
            "  [Result] 27,956.9 (+96.57%)  Sharpe Ratio:0.0712\n",
            "\n",
            "[Fiat execution statistics]  PF:1.12\n",
            "  [Total   ] Count:606(Size:0)  PnL:+27,543  Avr:+45.0  Price Range:+0\n",
            "  [Profit  ] Count:298(49.26%)  Sum:+261,087  Avr:+876.0  Max:+7,513  MaxLen:6(+5,674)\n",
            "  [Loss    ] Count:307(50.74%)  Sum:-233,544  Avr:-761.0  Max:-7,371  MaxLen:8(-7,976)\n",
            "  [Fee     ] Trade:0  Funding:0\n",
            "  [Max risk]\n",
            "    Drawdown       :-55.24%(-33,336) 2021/07/21 09:28:00\n",
            "    Unrealised loss:-2.23%(-933) 2021/05/13 09:01:30\n",
            "\n",
            "Completed terminate process.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bSfpX3JyBWv4"
      },
      "source": [
        "## 4. バックテスト結果\n",
        "バックテスト終了処理で各履歴CSVが出力されます。\n",
        "* 注文履歴 (orders.csv)<br>\n",
        "注文の発行、キャンセル、約定など注文データに変更があると記録されます。\n",
        "\n",
        "* 約定履歴 (executions.csv)<br>\n",
        "注文の約定、ファンディング手数料発生など資産変動に関わる履歴が記録されます。\n",
        "\n",
        "* 建玉履歴 (positions.csv)<br>\n",
        "注文の約定、未実現損益の変動など建玉変動に関わる履歴が記録されます。\n",
        "\n",
        "* 残高履歴 (balances.csv)<br>\n",
        "残高に変更があると記録されます。\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9QfrSGDB-ykd"
      },
      "source": [
        "## 5. バックテスト結果をチャート化\n",
        "バックテスト終了処理のresultsにはチャート作成向けデータが出力されます。<br>\n",
        "このデータからチャート作成ツール「ChartCreator」を使用してテスト結果を可視化します。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MCDYfTdM4BTd"
      },
      "source": [
        "from chart_creator import ChartCreator as cc\n",
        "\n",
        "dict_data = results['data']\n",
        "dict_statistics = results['statistics']\n",
        "dict_chart = results['chart']\n",
        "\n",
        "#-------------------------------------------------------------------------------\n",
        "# レイアウトカスタマイズ\n",
        "#-------------------------------------------------------------------------------\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",
        "#-------------------------------------------------------------------------------\n",
        "# メインチャート(ax:0)\n",
        "#-------------------------------------------------------------------------------\n",
        "cc.add_subchart(ax=0, label=\"USD\", grid=True)\n",
        "\n",
        "# DataUtilityを使用してOHLCVをダウンサンプリング(1m→1d)\n",
        "df_ohlcv_1d = du.Tool.downsample_ohlcv(df_ohlcv_1m, period='1D')\n",
        "# ローソクバー設定(OHLCV)\n",
        "cc.set_ohlcv_df(df_ohlcv_1d)\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",
        "# 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",
        "# 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",
        "#-------------------------------------------------------------------------------\n",
        "# ポジション推移サブチャート(ax:1)\n",
        "#-------------------------------------------------------------------------------\n",
        "cc.add_subchart(ax=1, 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=1, up_color='blue', down_color='red',\n",
        "            alpha=0.5, edge_width=1.0, edge_color='dimgray', line_mode='hv', name='Position')\n",
        "\n",
        "#-------------------------------------------------------------------------------\n",
        "# 損益推移サブチャート(ax:2)\n",
        "#-------------------------------------------------------------------------------\n",
        "cc.add_subchart(ax=2, label='PnL', grid=True)\n",
        "\n",
        "# 損益設定\n",
        "cc.set_line(dict_chart['pnl']['unixtime'], dict_chart['pnl']['unrealised_pnl'], ax=2, color='green', width=0.8, name='Unrealised')\n",
        "cc.set_band(dict_chart['pnl']['unixtime'], dict_chart['pnl']['pnl'], dict_chart['pnl']['zero'], ax=2, up_color='skyblue', down_color='red',\n",
        "           alpha=0.2, edge_width=1.0, edge_color='dimgray', name='PL')\n",
        "\n",
        "#-------------------------------------------------------------------------------\n",
        "# チャート生成\n",
        "#-------------------------------------------------------------------------------\n",
        "file_path = './result_chart'\n",
        "cc.create_chart(file_path + \".png\", \"png\")\n",
        "cc.create_chart(file_path + \".html\", \"html\")"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ka8uIr9vR6jr"
      },
      "source": [
        "### チャート画像表示 (matplotlib)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m2DZLkdB4KZc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 601
        },
        "outputId": "61857d62-f21d-4668-eebd-dcc6b9863c29"
      },
      "source": [
        "from IPython.display import Image, display_png\n",
        "\n",
        "# チャート画像表示\n",
        "file_name = file_path + '.png'\n",
        "display_png(Image(file_name))"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tLbin79-SBOK"
      },
      "source": [
        "### インタラクティブチャート表示 (plotly)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yqalYwNT4b5s",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 837
        },
        "outputId": "8b2c5adb-d3b6-46d0-fe39-81cc15d7cb5a"
      },
      "source": [
        "from IPython.display import HTML, display_html\n",
        "\n",
        "# HTMLチャート表示\n",
        "file_name = file_path + '.html'\n",
        "display_html(HTML(filename=file_name))"
      ],
      "execution_count": 8,
      "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=\"d9c365c7-c842-403b-9900-d804c92c3431\" style=\"height:800px; width:1200px;\"></div>\n",
              "<script type=\"text/javascript\">\n",
              "                \n",
              "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
              "                    \n",
              "                if (document.getElementById(\"d9c365c7-c842-403b-9900-d804c92c3431\")) {\n",
              "                    Plotly.newPlot(\n",
              "                        'd9c365c7-c842-403b-9900-d804c92c3431',\n",
              "                        [{\"close\": [29402.5, 32185.0, 33062.5, 32044.5, 34107.5, 36883.0, 39487.0, 40600.0, 40291.5, 38225.0, 35390.0, 34026.0, 37390.5, 39143.5, 36734.5, 36007.0, 35870.0, 36684.5, 35898.0, 35489.0, 30810.5, 33003.0, 32090.0, 32290.5, 32221.0, 32500.0, 30381.0, 33446.0, 34230.0, 34310.5, 33101.0, 33550.5, 35544.5, 37700.0, 37030.0, 38361.5, 39318.5, 38900.5, 46417.5, 46513.5, 44888.0, 48082.0, 47485.0, 47265.5, 48690.5, 48018.5, 49199.5, 52209.5, 51613.0, 55934.0, 55934.5, 57542.5, 54122.5, 48923.5, 49691.0, 47110.0, 46320.0, 46171.5, 45211.0, 49664.5, 48483.5, 50346.0, 48333.0, 48768.5, 48904.5, 51027.0, 52480.0, 54960.0, 55975.5, 57909.5, 57315.0, 61280.5, 59029.0, 55627.5, 57009.5, 59015.5, 57620.0, 58073.5, 58146.5, 57421.5, 54090.0, 54394.0, 52244.5, 51321.5, 55081.5, 55869.5, 55788.5, 57680.5, 58812.0, 58876.0, 58806.0, 59020.0, 57126.5, 58258.0, 59330.0, 58064.0, 55937.5, 58149.0, 58123.0, 59790.5, 60076.0, 59880.5, 63674.0, 63071.5, 63323.5, 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