nagishin/maxdrawdown.ipynb

## maxdrawdown.ipynb
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    "colab": {
      "name": "MaxDrawdown.ipynb",
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      "authorship_tag": "ABX9TyN8ra//Mm180wUsIJA1KhaR",
      "include_colab_link": true
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      "name": "python3",
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    "language_info": {
      "name": "python"
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/nagishin/1fa738aa914c6395064576f96dc86c50/maxdrawdown.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import random\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib.ticker import FuncFormatter\n",
        "\n",
        "# 残高変動率:-10～+15%での推移\n",
        "num = 200\n",
        "bal = 100\n",
        "pnl = np.zeros(num)\n",
        "for i in range(num):\n",
        "    pnl[i] = bal * random.randint(-10, 15) * 0.01\n",
        "    bal += pnl[i]\n",
        "\n",
        "# 残高(損益)データ作成\n",
        "pnl[0] = 0\n",
        "df_base = pd.DataFrame({'balance':pnl.cumsum() + 100, 'pnl':pnl})\n",
        "display(df_base)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "VhlLrvHYuxoP",
        "outputId": "b5195385-43a9-40c5-b03b-db95b9dc7705"
      },
      "execution_count": 103,
      "outputs": [
        {
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          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>balance</th>\n",
              "      <th>pnl</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>89.600000</td>\n",
              "      <td>-10.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>83.984000</td>\n",
              "      <td>-5.616000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>77.825120</td>\n",
              "      <td>-6.158880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>86.825883</td>\n",
              "      <td>9.000763</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>195</th>\n",
              "      <td>6337.888402</td>\n",
              "      <td>301.994686</td>\n",
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              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>5957.375098</td>\n",
              "      <td>-380.513304</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>197</th>\n",
              "      <td>5838.147596</td>\n",
              "      <td>-119.227502</td>\n",
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              "    <tr>\n",
              "      <th>198</th>\n",
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              "      <td>701.057711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>199</th>\n",
              "      <td>6342.909148</td>\n",
              "      <td>-196.296159</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>200 rows × 2 columns</p>\n",
              "</div>\n",
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              "          document.querySelector('#df-0083c4de-511b-4db9-9256-40c831b82d13 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0083c4de-511b-4db9-9256-40c831b82d13');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "        }\n",
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              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "         balance         pnl\n",
              "0     100.000000    0.000000\n",
              "1      89.600000  -10.400000\n",
              "2      83.984000   -5.616000\n",
              "3      77.825120   -6.158880\n",
              "4      86.825883    9.000763\n",
              "..           ...         ...\n",
              "195  6337.888402  301.994686\n",
              "196  5957.375098 -380.513304\n",
              "197  5838.147596 -119.227502\n",
              "198  6539.205307  701.057711\n",
              "199  6342.909148 -196.296159\n",
              "\n",
              "[200 rows x 2 columns]"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = df_base.copy()\n",
        "\n",
        "# 残高変動値でのドローダウン\n",
        "df['dd_val'] = df['balance'].cummax() - df['balance']\n",
        "# 最大ドローダウン範囲\n",
        "dd_end = df['dd_val'].idxmax()\n",
        "dd_start = df['balance'].cummax()[:dd_end].idxmax()\n",
        "\n",
        "# 残高下落率でのドローダウン\n",
        "df['dd_ratio'] = df['dd_val'] / (df['balance'] + df['dd_val'])\n",
        "# 最大ドローダウン範囲\n",
        "ratio_end = df['dd_ratio'].idxmax()\n",
        "ratio_start = df['balance'].cummax()[:ratio_end].idxmax()\n",
        "\n",
        "display(df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "edyhvpkX3RIW",
        "outputId": "744f1466-c952-4c6d-819f-431446ca102e"
      },
      "execution_count": 113,
      "outputs": [
        {
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          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>balance</th>\n",
              "      <th>pnl</th>\n",
              "      <th>dd_val</th>\n",
              "      <th>dd_ratio</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>89.600000</td>\n",
              "      <td>-10.400000</td>\n",
              "      <td>10.400000</td>\n",
              "      <td>0.104000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>83.984000</td>\n",
              "      <td>-5.616000</td>\n",
              "      <td>16.016000</td>\n",
              "      <td>0.160160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>77.825120</td>\n",
              "      <td>-6.158880</td>\n",
              "      <td>22.174880</td>\n",
              "      <td>0.221749</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>86.825883</td>\n",
              "      <td>9.000763</td>\n",
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              "      <td>0.131741</td>\n",
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              "      <th>195</th>\n",
              "      <td>6337.888402</td>\n",
              "      <td>301.994686</td>\n",
              "      <td>1097.412139</td>\n",
              "      <td>0.147595</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>5957.375098</td>\n",
              "      <td>-380.513304</td>\n",
              "      <td>1477.925443</td>\n",
              "      <td>0.198771</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>197</th>\n",
              "      <td>5838.147596</td>\n",
              "      <td>-119.227502</td>\n",
              "      <td>1597.152945</td>\n",
              "      <td>0.214807</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>6539.205307</td>\n",
              "      <td>701.057711</td>\n",
              "      <td>896.095233</td>\n",
              "      <td>0.120519</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>199</th>\n",
              "      <td>6342.909148</td>\n",
              "      <td>-196.296159</td>\n",
              "      <td>1092.391393</td>\n",
              "      <td>0.146920</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>200 rows × 4 columns</p>\n",
              "</div>\n",
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              "          const element = document.querySelector('#df-86c5b1a3-02d4-446c-b138-d97746541787');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  "
            ],
            "text/plain": [
              "         balance         pnl       dd_val  dd_ratio\n",
              "0     100.000000    0.000000     0.000000  0.000000\n",
              "1      89.600000  -10.400000    10.400000  0.104000\n",
              "2      83.984000   -5.616000    16.016000  0.160160\n",
              "3      77.825120   -6.158880    22.174880  0.221749\n",
              "4      86.825883    9.000763    13.174117  0.131741\n",
              "..           ...         ...          ...       ...\n",
              "195  6337.888402  301.994686  1097.412139  0.147595\n",
              "196  5957.375098 -380.513304  1477.925443  0.198771\n",
              "197  5838.147596 -119.227502  1597.152945  0.214807\n",
              "198  6539.205307  701.057711   896.095233  0.120519\n",
              "199  6342.909148 -196.296159  1092.391393  0.146920\n",
              "\n",
              "[200 rows x 4 columns]"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# DataFrameプロット\n",
        "fig, axes = plt.subplots(nrows=4, ncols=1, sharex=True, figsize=(12.0, 8.0))\n",
        "\n",
        "for ax, col in zip(axes.ravel(), df.columns):\n",
        "    ax.axhline(y=0, color='dimgray', linewidth=0.8)\n",
        "    df[col].plot(ax=ax, ylabel=col)\n",
        "    if col != 'dd_ratio':\n",
        "        df[col][dd_start:dd_end+1].plot(ax=ax, color='red')\n",
        "    if col != 'dd_val':\n",
        "        df[col][ratio_start:ratio_end+1].plot(ax=ax, color='green')\n",
        "axes[3].yaxis.set_major_formatter(FuncFormatter(lambda y, _: '{:.0%}'.format(y))) "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 483
        },
        "id": "2eg9S8uTrJYe",
        "outputId": "57533ae3-d900-4338-dee0-dd544410629d"
      },
      "execution_count": 112,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 864x576 with 4 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}