Monte_Carlo_Simulation.ipynb

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    "colab": {
      "name": "Monte-Carlo Simulation.ipynb",
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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      "cell_type": "markdown",
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        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/tylee33/DLforFinance/blob/master/Monte_Carlo_Simulation.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
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        "id": "YDlaJxPaAusl",
        "colab_type": "code",
        "colab": {
          "resources": {
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              "ok": true,
              "headers": [
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                  "content-type",
                  "application/javascript"
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              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 96
        },
        "outputId": "7aa24bb8-8fa2-4bbe-9222-3f752e60cf66"
      },
      "source": [
        "from google.colab import files\n",
        "uploaded = files.upload()\n",
        "\n",
        "for fn in uploaded.keys():\n",
        "  print('User uploaded file \"{name}\" with length {length} bytes'.format(\n",
        "    name = fn, length = len(uploaded[fn])))"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-6dfdbafd-d035-4ec2-8951-576aa5f609d1\" name=\"files[]\" multiple disabled />\n",
              "     <output id=\"result-6dfdbafd-d035-4ec2-8951-576aa5f609d1\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving stocks.csv to stocks.csv\n",
            "User uploaded file \"stocks.csv\" with length 61230 bytes\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Zwz7s0vWBDYR",
        "colab_type": "text"
      },
      "source": [
        "# **금융상품들의 포트폴리오 평가**\n",
        "**몬테카를로 시뮬레이션 금융에 적용하기**\n",
        "\n",
        "평균수익\n",
        "주가변동성 (std)\n",
        "Sharpe ratio"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kJImrEkpBjJb",
        "colab_type": "text"
      },
      "source": [
        "# **Data Loading**\n",
        "\n",
        "pandas datareader"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-Yt-r8rpA2jR",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 179
        },
        "outputId": "a50c78dd-40a3-4f5e-a11a-c527f4afa903"
      },
      "source": [
        "# 저장된 CSV 파일을 사용한다\n",
        "\n",
        "import pandas as pd\n",
        "prices = pd.read_csv('stocks.csv')\n",
        "prices = prices.set_index('Date')\n",
        "prices.head(3)\n",
        "prices.index = pd.DatetimeIndex(prices.index)\n",
        "prices.info()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "DatetimeIndex: 1419 entries, 2013-01-02 to NaT\n",
            "Data columns (total 4 columns):\n",
            "KOSPI      1337 non-null float64\n",
            "SP         1337 non-null float64\n",
            "MSCI_EM    1337 non-null float64\n",
            "MSCI_WI    1337 non-null float64\n",
            "dtypes: float64(4)\n",
            "memory usage: 55.4 KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yUy85u9MB2Cy",
        "colab_type": "text"
      },
      "source": [
        "# **임의의 확률에 근거한 포트폴리오 수익률 계산**\n",
        "\n",
        "Portfolio Rate"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g9OeqaR7BLaf",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0mrUej1OBUSY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "d2b9259c-dd42-4f53-eab7-e6ab27c285b2"
      },
      "source": [
        "portfolio_rate     = [0.5, 0.2, 0.2, 0.1]\n",
        "portfolio_rate"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.5, 0.2, 0.2, 0.1]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q_OLSG2BCCuo",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "fd0302c0-13df-4bd3-9ea2-a98663f92a04"
      },
      "source": [
        "returns            = prices.pct_change()\n",
        "returns.head(4)"
      ],
      "execution_count": 9,
      "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>KOSPI</th>\n",
              "      <th>SP</th>\n",
              "      <th>MSCI_EM</th>\n",
              "      <th>MSCI_WI</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2013-01-02</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2013-01-03</th>\n",
              "      <td>-0.005756</td>\n",
              "      <td>-0.002086</td>\n",
              "      <td>0.004192</td>\n",
              "      <td>-0.002192</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2013-01-04</th>\n",
              "      <td>-0.003699</td>\n",
              "      <td>0.004865</td>\n",
              "      <td>-0.004422</td>\n",
              "      <td>0.004195</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2013-01-07</th>\n",
              "      <td>-0.000343</td>\n",
              "      <td>-0.003123</td>\n",
              "      <td>-0.001978</td>\n",
              "      <td>-0.002338</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               KOSPI        SP   MSCI_EM   MSCI_WI\n",
              "Date                                              \n",
              "2013-01-02       NaN       NaN       NaN       NaN\n",
              "2013-01-03 -0.005756 -0.002086  0.004192 -0.002192\n",
              "2013-01-04 -0.003699  0.004865 -0.004422  0.004195\n",
              "2013-01-07 -0.000343 -0.003123 -0.001978 -0.002338"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cUTAtlELCJna",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "61b7fbf3-cea6-4aca-b639-ff386443ccc3"
      },
      "source": [
        "cov_returns        = returns.cov()\n",
        "cov_returns"
      ],
      "execution_count": 10,
      "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>KOSPI</th>\n",
              "      <th>SP</th>\n",
              "      <th>MSCI_EM</th>\n",
              "      <th>MSCI_WI</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>KOSPI</th>\n",
              "      <td>0.000050</td>\n",
              "      <td>2.140566e-06</td>\n",
              "      <td>-0.000004</td>\n",
              "      <td>-3.295739e-06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SP</th>\n",
              "      <td>0.000002</td>\n",
              "      <td>5.761824e-05</td>\n",
              "      <td>0.000001</td>\n",
              "      <td>-2.457716e-07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MSCI_EM</th>\n",
              "      <td>-0.000004</td>\n",
              "      <td>1.488472e-06</td>\n",
              "      <td>0.000069</td>\n",
              "      <td>3.364095e-05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MSCI_WI</th>\n",
              "      <td>-0.000003</td>\n",
              "      <td>-2.457716e-07</td>\n",
              "      <td>0.000034</td>\n",
              "      <td>4.107121e-05</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            KOSPI            SP   MSCI_EM       MSCI_WI\n",
              "KOSPI    0.000050  2.140566e-06 -0.000004 -3.295739e-06\n",
              "SP       0.000002  5.761824e-05  0.000001 -2.457716e-07\n",
              "MSCI_EM -0.000004  1.488472e-06  0.000069  3.364095e-05\n",
              "MSCI_WI -0.000003 -2.457716e-07  0.000034  4.107121e-05"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ncaR4EQ2CK3R",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 107
        },
        "outputId": "a4b87a4b-8320-42e7-a766-d886fa2c16c4"
      },
      "source": [
        "mean_daily_returns = returns.mean()\n",
        "mean_daily_returns"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "KOSPI      0.000163\n",
              "SP         0.000444\n",
              "MSCI_EM    0.000112\n",
              "MSCI_WI    0.000334\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RmTq5KlCCQIo",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "20524743-ed53-4ea1-b711-0835043b401c"
      },
      "source": [
        "weights            = np.asarray(portfolio_rate)\n",
        "weights "
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.5, 0.2, 0.2, 0.1])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HhPpiNrPCTJZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "0400f949-401d-4293-dadb-17faec33180c"
      },
      "source": [
        "portfolio_return   = round(np.sum(\n",
        "    mean_daily_returns * weights) * 252, 2)   \n",
        "portfolio_return"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.06"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F7ywpngGCX5C",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "1165f95c-9364-4c59-9b4e-3ce54b0a5041"
      },
      "source": [
        "portfolio_std_dev  = round(np.sqrt(\n",
        "    np.dot(weights.T, \n",
        "           np.dot(cov_returns, weights)) ) * np.sqrt(252), 2) \n",
        "portfolio_std_dev"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.07"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OIp4GRRyCbpB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 71
        },
        "outputId": "8d2c4831-f712-4887-ee8b-16038fd3b562"
      },
      "source": [
        "print(' 분산비율 : {} \\n1) 연간 수익 : +- {} \\n2) 변동률 : {}'.format(\n",
        "    portfolio_rate, portfolio_return, portfolio_std_dev))"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            " 분산비율 : [0.5, 0.2, 0.2, 0.1] \n",
            "1) 연간 수익 : +- 0.06 \n",
            "2) 변동률 : 0.07\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NtqiJoRbChC5",
        "colab_type": "text"
      },
      "source": [
        "# **몬테카를로 시뮬레이션을 활용한 포트폴리오 평가**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QUJTinnTCilr",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "returns            = prices.pct_change()\n",
        "cov_returns        = returns.cov()      \n",
        "mean_daily_returns = returns.mean()\n",
        "num_portfolios     = 25000   "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "keqyQ2E4Cl5i",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "f0f11b28-7774-479c-e192-e045c685cd97"
      },
      "source": [
        "results            = np.zeros((3 + len(prices.columns), num_portfolios))\n",
        "results"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0., 0., 0., ..., 0., 0., 0.],\n",
              "       [0., 0., 0., ..., 0., 0., 0.],\n",
              "       [0., 0., 0., ..., 0., 0., 0.],\n",
              "       ...,\n",
              "       [0., 0., 0., ..., 0., 0., 0.],\n",
              "       [0., 0., 0., ..., 0., 0., 0.],\n",
              "       [0., 0., 0., ..., 0., 0., 0.]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LjyS-2y2CosT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "8f79e6ff-910c-4730-ff9a-024b4bbd5537"
      },
      "source": [
        "weights  = np.random.random(len(prices.columns))\n",
        "weights"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.6362392 , 0.57200257, 0.34816079, 0.82766411])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YTdH2JxMCrlZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "8e48383b-1150-4ae5-f09b-dc0ab2d9ab57"
      },
      "source": [
        "for i in range(num_portfolios):\n",
        "    weights  = np.random.random(len(prices.columns))\n",
        "    weights /= np.sum(weights)             \n",
        "    \n",
        "    portfolio_return  = np.sum(\n",
        "        mean_daily_returns * weights) * 252       \n",
        "\n",
        "    portfolio_std_dev = np.sqrt(              \n",
        "        np.dot(weights.T, np.dot(cov_returns, weights))) * np.sqrt(252)   \n",
        "\n",
        "    results[0,i] = portfolio_return\n",
        "    results[1,i] = portfolio_std_dev\n",
        "    results[2,i] = results[0,i]/results[1,i]\n",
        "\n",
        "    for j in range(len(weights)):           \n",
        "        results[j+3, i] = weights[j]           \n",
        "    \n",
        "results_frame = pd.DataFrame(results.T, \n",
        "                             columns = ['ret','stdev','sharpe', \n",
        "                                        prices.columns[0], \n",
        "                                        prices.columns[1], \n",
        "                                        prices.columns[2], \n",
        "                                        prices.columns[3]])\n",
        "results_frame.head()"
      ],
      "execution_count": 19,
      "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>ret</th>\n",
              "      <th>stdev</th>\n",
              "      <th>sharpe</th>\n",
              "      <th>KOSPI</th>\n",
              "      <th>SP</th>\n",
              "      <th>MSCI_EM</th>\n",
              "      <th>MSCI_WI</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.075460</td>\n",
              "      <td>0.065471</td>\n",
              "      <td>1.152583</td>\n",
              "      <td>0.322651</td>\n",
              "      <td>0.378031</td>\n",
              "      <td>0.094219</td>\n",
              "      <td>0.205099</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.072935</td>\n",
              "      <td>0.072807</td>\n",
              "      <td>1.001761</td>\n",
              "      <td>0.203696</td>\n",
              "      <td>0.101630</td>\n",
              "      <td>0.093035</td>\n",
              "      <td>0.601639</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.067838</td>\n",
              "      <td>0.064644</td>\n",
              "      <td>1.049401</td>\n",
              "      <td>0.445574</td>\n",
              "      <td>0.203694</td>\n",
              "      <td>0.049266</td>\n",
              "      <td>0.301467</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.071018</td>\n",
              "      <td>0.067240</td>\n",
              "      <td>1.056175</td>\n",
              "      <td>0.365275</td>\n",
              "      <td>0.376656</td>\n",
              "      <td>0.140298</td>\n",
              "      <td>0.117771</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.075413</td>\n",
              "      <td>0.073796</td>\n",
              "      <td>1.021912</td>\n",
              "      <td>0.300513</td>\n",
              "      <td>0.497098</td>\n",
              "      <td>0.171441</td>\n",
              "      <td>0.030948</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        ret     stdev    sharpe     KOSPI        SP   MSCI_EM   MSCI_WI\n",
              "0  0.075460  0.065471  1.152583  0.322651  0.378031  0.094219  0.205099\n",
              "1  0.072935  0.072807  1.001761  0.203696  0.101630  0.093035  0.601639\n",
              "2  0.067838  0.064644  1.049401  0.445574  0.203694  0.049266  0.301467\n",
              "3  0.071018  0.067240  1.056175  0.365275  0.376656  0.140298  0.117771\n",
              "4  0.075413  0.073796  1.021912  0.300513  0.497098  0.171441  0.030948"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KgXwesVyCxj5",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "e1315d6c-8b89-480a-a30f-790c2405d499"
      },
      "source": [
        "results_frame.shape"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(25000, 7)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5Ez0b1W9C1Ug",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 396
        },
        "outputId": "37d4406a-38ba-4372-b65f-b77a93f0eca9"
      },
      "source": [
        "%matplotlib inline\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "plt.figure(figsize=(12,6))\n",
        "plt.scatter(results_frame.stdev, \n",
        "            results_frame.ret,  \n",
        "            c = results_frame.sharpe)\n",
        "plt.grid(); plt.colorbar()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.colorbar.Colorbar at 0x7f4de9319f28>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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JRIYQkkQRHE0EgCWEWG5kCw+wtuuVjG97P7uy1+MF2xA80lClGKOsWGI3L4BD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g1dJcfpq6JFISyJvipstJzWjTOXE8oK7r+CuCeFJclbr6mrWtz++z11gyw43twWCIOd8uM5OM\njPqamsdFaoaXwSO6M/K6U/ht5p+kpLkpL7WLRo/XzXUPnsWCWav4beZKHE6Nsy7vzUU37r0+o6Zp\nPPHxv/jX6U+xPVJCJyqgXW4nKxdtpMeAtnsdS7HvDLm8D0W7S3jv0UkJH0/Uui8YCHLrqf9j2/od\nkbjWT5+bypKfV/LklDsRQrBq4XpbSaAwTpeDjStyaNCsTtxjCkUylGBUKI4isrKqMjAma/K5167g\n688X8O5bP1FRHqBpsyzOGdGdOT+vZmvObtp3asTw808gs3p8XOKShRvxJeiz63BorFm5jeyGNWhg\nZv+mpXtp1KRWZJ/shjV494ubWLksh6I95bRu34AqVVNs41x186n88dsGyst8ET3rcju49f6hcVY7\nb4qb5z8YzZTPFjL7hz+pUi2FYSN60Kn7cRTvKePDV2baBKPmEFTNTGPt8lx7lrM0srkD/qgIXr00\nhz27Sxn/451JCyv3H9KRNp0aMXPKYspL/XTv25KW7RsghODWh86mZ7+WfPv57+ghnQHDOnHSqW3i\nxKCUkk/HzWTCaz9QXuqnamYaV9wxmIHndE045xW3n87S+esJJLAURpOLjHjJ2jXTeWvm3ZE5e/Rv\nTY2squRt2R2Jc3S6HWTVz6Tf0M4MONuYc+bMmfTt2zfh/IlISfPQsefxTM/ZFZc9LnVJ1czk8a2K\nv4YQgpFjhrBlTR6zv/ndJvI8KW4uvC3eBf7r5D/Iz9llKynlrwiwdvEmlv+6hra9mtO4dX1+/3FF\nXNmpUEgn+7is2CEVh5OjMOlFCUaF4hjgzOFdOXO4XZT07ttqr8c1aFQjYYaxlFC7TtW9Hq9pgtaV\nFKzOblCDV8b/i/Fv/cSyRZupUy+TC67sTbskmbopqR7OuaQX51xi76GbUTWVp94ZxVP3fc6mtdsR\nAtp3acLt/z2Ha4Y9Z69LmChBJaRTuLOYZQs20v6E5MWQs+plcsFVfeO2CyHo2b81PffSS/nTcTP5\n8MXpkazXgp3FvPR/n5Oa7uHE0+LLozRtk02j42qzdllOpeOCUQqooswf6cvscDoYO/EG3nlqKj9N\nWYwQgr5ndOSyMYMSutD3hzMuOYmZk363l1bSBFVrpNMyiVVVceDc+tylERhecAAAD+5JREFUpKR5\n+H78r0gpychM41+PjqBdr+Zx+65csJ5ys3SSlWAgyOpFG2nbqzlnXtWPr17/wSYYXW4nTds35Lh2\nB6/QvGI/kdFWsEcTSjAqFP9ghpzTlUmf/GYTjA6nRp161WjVrv5BmaNOvUxuuW/YAY/TpFkdXppw\nHcVF5cxfMJer/tUPgFOGdmLqxN9s7foSOYElkL8tQRLOQULXdSa8+kNcTT1fRYB3x05LKBjBKNuz\nL7hcjrhYzIyqqdz48Dnc+PA5f23RSWjatj43PXo+L973KUIIQiGdrPqZ/Oet0Sqb9hDi9ri46emL\nufaRCygrLqdKjfSkFvG6jWvhSXXji7FOu9wuajcwqh3UrJfJU1P+zXO3vMfaPzbhcDo4eXg3rnvi\nokN+Loq9oCyMCoXiaCKrbjUeef5inv7Pl+TvKEJKaN+5EXc+NPxvKwwyqqTYsoOvvOVU1q7IZf3K\nPIJ+vxGPKURcXUg9pNPiILTvy92Qz4fPfcuKhRuoVS+TEdcNoMvJLako81ORoEg4wI5w//BE51M1\nld17acnm8boYNKI7DmfijO9DQf+zu3LS6R1YtzyX1CpeGjbN+tu+Jo413F5X0iSYMH3P7c47D32G\nj+hrTtMEqeleug+Kloo6vl1Dnp9xH35fAIfTccDWZ8U/FyUYFYp/OG07NuStz2+kYFcpbo+T9Azv\nkV7SfuFNdfP0+1fz4UszmPDyDCOb2iEi2eFgCK4e/VtT3xKD+VfIWb+Dm4Y+g6/Cjx6SbM8p4OGl\nb3Pdf4Yz8NwTyKiamjCLuOHxyePFzh7Vh3efmpqw3qI3xU1I1+k9pAOjzKLqhxO310WrLo0P+7yK\nvZNeLZWnpt3F46PHsWV1HkhJs46NufONqxOWRtrXdoiKw8TRZ2BUglGhUJjle2oevckMQgimfzo/\nKrpCOphWSIdT48oxgxhy4YG3tfvgmWn4yv22ZBBfeYDXH/mKU87uyhV3DOblB7+wxf55vC6uvHNI\n0jGHj+rDjtwCpn48Fz2ko+uS6rWrcMfYC6mSmUatutX+cR1WFPtG49b1eWX2QxTuLMKhaWQkSGxT\n/D05Gju9KMGoUCiOCeLiE82e06GQzpkX9Two7tRl8zck7Dsd9IfI31bIqed2IyXVzXvPfkv+1kLq\nH1+bUXcOoWPP+BZtYTRN47oHz+aSW04jd2M+WdnVyayVccBrVRw9bN+0kz9/W0v1OlVpe2KLpHGL\nyahW88DaUyqOAEowKhQKxZGhdt1qbM+NjxWsXa/aQYu9q5FVhV3b44tth3SdjGppAPQe3IHelbQb\nTEZGtVRadlQZyP8kpJS8eMu7fPvuTzjdDpBQtWYGj0+7mzqNDix8QvE3RmI0JjjKUNGvCoXimODy\n20+Pa2fo8bq47LZBB22OEdcPjPTsDeP2ODnp9A6kHWWxn4ojzw/j5zD9g18I+AKUF1dQXlLBjs07\neeiC54700hSKOJRgVCgUxwR9z+jILf87l6z6mQghqJ2dyU3/PYf+wzoftDl6ntqWK+4YTEqah5Q0\nDy63k16ntePmR887aHMo/jl89cp0fGX2Woq6Ltmyeit5G3ccoVUpDjUCiZB//edIoVzSCoXimKHv\nmZ3oe2anQzrHsCv6cPrIXuzI2U3VmulkVFUJKYq/RllJRcLtDoeDitL4otyHgu2b8tF1nTqNa6uy\nSYeTQyz8hBCDgOcAB/CGlPKxJPudA3wKdJNSLqhsTCUYFQqFYj9xe5zUPz6+v69CsT/0PrsbEzfs\niOv37Pa6aNAy+5DOvWHZZv57wVjyNuYjgJr1q3Pf+Nto2qnJXo9VHAQOoWAUQjiAl4CBQA4wXwjx\nlZRyRcx+GcDNwLx9GVe5pBUKhUKhOAKcc/NgajeogTfVbPfocuBJcXP761cf0gLbFWU+xvT9Pzb/\nmYu/3I+v3E/umjxu7/8gpXtKD9m8CpNw0stf/dk7JwBrpZTrpZR+YDyQqN3Ww8DjQGJTdwzKwqhQ\nKBQKxREgrUoKL839Lz+Mn8PC75dSu0ENzhh9CtlN6xzSeX/+bC5BS3/pMMFAiJkT5jDk6oGHdH7F\nIScb2GL5Owfobt1BCNEZaCClnCyEuGNfBlWCUaFQKBSKI4Q31cPgK/sx+Mp+h23OXVsL8FfEt7H0\nlfnYuXX3YVvHP5kDTF6pKYSwxhuOk1KO2+e5hdCAscDl+zOpEowKhUKhUPyDaNWjGS6Pi1DQnljj\nTffSukfzI7SqfxgHJhh3Sim7VvJ4LtDA8nd9c1uYDKAtMNNMdKoDfCWEGFpZ4ouKYVQoFAqF4h9E\n+z6tadGtqa2mqDvFTZO2Dehy6v4XnVfsL9IQjH/1Z+/MB5oJIZoIIdzACOCryOxS7pFS1pRSNpZS\nNgbmApWKRVAWRoVCoVAo/lEIIfjf1Hv58oWpfPvWD0gpOfWyvpx98+D9bkuo+PshpQwKIW4AvsUo\nq/OWlHK5EOIhYIGU8qvKR0iMEowKhUKhUPzDcHtcnH/7UM6/feiRXso/D8khr8MopZwCTInZ9kCS\nffvuy5hKMCoUCoVCoVAcTo7CXtJKMCoUCoVCoVAcRo5ki7+/ihKMCoVCoVAoFIeTo1AwquhWhUKh\nUCgUCkWlKAujQqFQKBQKxeFCAvrRZ2FUglGhUCgUCoXisLHP9RT/VijBqFAoFAqFQnE4UYJRoVAo\nFAqFQlEpR6FgVEkvCoVCoVAoFIpKURZGhUKhUCgUisOFSnpRKBQKhUKhUFSOBHn0tXpRglGhUCgU\nCoXicKJiGBUKhUKhUCgUxxrKwqhQKBQKhUJxuFAxjAqFQqFQKBSKvXIUuqSVYFQoFAqFQqE4nCjB\nqFAoFAqFQqFIztHZGlAlvSgUCoVCoVAoKkVZGBUKhUKhUCgOFxLQVR1GhUKhUCgUCkVlHIUuaSUY\nFQqFQqFQKA4nSjAqFAqFQqFQKJIjj8o6jCrpRaFQKBQKhUJRKcrCqFAoFAqFQnG4kCClSnpRKBQK\nhUKhUFTGseqSFkIMEkKsEkKsFULcleBxjxBigvn4PCFEY3P7QCHEQiHEUvPf/gd3+QqFQqFQKBRH\nGVL+9Z8jxF4FoxDCAbwEnA60Bi4UQrSO2W0UUCClbAo8Azxubt8JnCmlbAdcBrx/sBauUCgUCoVC\noTg87IuF8QRgrZRyvZTSD4wHhsXsMwx41/z9U+AUIYSQUi6SUm41ty8HUoQQnoOxcIVCoVAoFIqj\nDimNwt1/9ecIsS+CMRvY8v/t3d2LXdUdxvHvo9NUjWjGqKFtxEQaQUUbNEYvpA5KoxSaXBhrqmLQ\nCy/UmxYUi+CFeFX6B5SAivbClwaEoCGDGgbF1jYqSXSMLzPBl6igiW+N8W3sz4u9AqeHyXGfs8/Z\na5+Z5wOb7LP32sxvPWSYddY6Z++W1/vSsVnbRMQM8DmwuK3NVcDLEfFNb6WamZmZzQFDuCRdy5de\nJJ1DsUy95gjnbwZuBliyZAkTExN1lNWTgwcPNrq+JnFW5Tmr7jiv8pxVec6qO86rdzFHHw34PnBa\ny+ul6dhsbfZJGgFOBA4ASFoKPA7cEBHTs/2AiNgEbAJYtWpVjI2NddGFek1MTNDk+prEWZXnrLrj\nvMpzVuU5q+44r17lnSnsVZkl6R3ACknLJS0ANgBb2tpsofhSC8B6YHtEhKRFwJPAnRHxfL+KNjMz\nM7P6/OiAMX0m8TZgHNgDPBYRk5LukbQ2NbsPWCxpCvgTcPjWO7cBvwTulrQzbaf2vRdmZmZmwyAo\n7sPY65ZJqc8wRsRWYGvbsbtb9r8Grp7lunuBeyvWaGZmZjZ3+EkvZmZmZnYkAcQQPunFA0YzMzOz\nukQM5QxjqUcDmpmZmdn85RlGMzMzsxp5SdrMzMzMOhvCJWlFw24eKelj4J3cdXRwMrA/dxFDwlmV\n56y647zKc1blOavuDFtep0fEKbmLkLSNIrte7Y+IK/tVT1mNGzA2naQXI2JV7jqGgbMqz1l1x3mV\n56zKc1bdcV7zi7/0YmZmZmYdecBoZmZmZh15wNi9TbkLGCLOqjxn1R3nVZ6zKs9Zdcd5zSP+DKOZ\nmZmZdeQZRjMzMzPryAPGRNKVkt6QNCXpzlnO/1TSo+n8vyUtazl3nqR/SZqU9IqkY+qsPYde85J0\nnaSdLdv/JK2su/46VcjqJ5IeTP+n9kj6c921161CVgskPZCy2iVprObSsyiR168lvSxpRtL6tnMb\nJb2Vto31VZ1Hxay2SfpM0hP1VZxPr1lJWtnyt3C3pGvqrdwGKiLm/QYcDUwDZwALgF3A2W1tbgH+\nlvY3AI+m/RFgN/Cr9HoxcHTuPjU1r7Y25wLTufvT1KyAa4FH0v5xwNvAstx9amhWtwIPpP1TgZeA\no3L3qQF5LQPOAx4C1rccPwnYm/4dTfujufvUxKzSucuB3wFP5O5Lk7MCzgRWpP2fAx8Ci3L3yVt/\nNs8wFlYDUxGxNyK+BR4B1rW1WQc8mPY3A5dLErAG2B0RuwAi4kBEfF9T3blUyavVH9K1c1mVrAJY\nKGkEOBb4FviinrKzqJLV2cB2gIj4CPgMmOv3h/vRvCLi7YjYDbQ/VuIK4KmI+CQiPgWeAmq/EXCN\nqmRFRDwD/LeWSvPrOauIeDMi3kr7HwAfAdlvlG394QFj4RfAey2v96Vjs7aJiBngc4rZxDOBkDSe\npujvqKHe3Krk1eoa4OEB1dgUVbLaDHxJ8S79XeCvEfHJoAvOqEpWu4C1kkYkLQcuAE4beMV5lclr\nENcOo/nW3yr6kpWk1RQzlNN9qssy87OkqxsBLgEuBA4Bz0h6Kb0jtSOQdBFwKCJezV1Lg60GvqdY\n2hkFnpP0dETszVtWI90PnAW8SPFo0X9SZGdmNZP0M+DvwMaIIXxoss3KM4yF9/n/2Yil6disbdIS\n4YnAAYp3X89GxP6IOARsBc4feMV5VcnrsA3M/dlFqJbVtcC2iPguLbM+z9xeZu05q4iYiYg/RsTK\niFgHLALerKHmnMrkNYhrh9F8628VlbKSdALwJHBXRLzQ59osIw8YCzuAFZKWS1pAMZjZ0tZmC3D4\nm4Trge0REcA4cK6k49IfsEuB12qqO5cqeSHpKOD3zP3PL0K1rN4FLgOQtBC4GHi9lqrz6Dmr9Pu3\nEEDSb4CZiPDv4ZGNA2skjUoapfgs9viA6myCKlnNNz1nldo/DjwUEZsHWKPlkPtbN03ZgN9SzEhM\nU7wzArgHWJv2jwH+AUwB/wHOaLn2emASeBX4S+6+DEFeY8ALufvQ9KyA49PxSYo3Ibfn7kuDs1oG\nvAHsAZ4GTs/dl4bkdSHFKsiXFLPWky3X3pRynAJuzN2Xhmf1HPAx8FVqc0Xu/jQxq/S38DtgZ8u2\nMnd/vPVn85NezMzMzKwjL0mbmZmZWUceMJqZmZlZRx4wmpmZmVlHHjCamZmZWUceMJqZmZlZRx4w\nmpmZmVlHHjCamZmZWUceMJqZmZlZRz8Atww/eJkFUh8AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LSRDk5PVC4kB",
        "colab_type": "text"
      },
      "source": [
        "# **몬테카를로 포트폴리오 최적값 계산**\n",
        "\n",
        "*   샤프지수 최대인 포트폴리오\n",
        "*   표준편차 최소인 포트폴리오\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P03X_F5OC-WB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "1b98d4a2-efa5-46e6-fc89-f0a7a481a843"
      },
      "source": [
        "results_frame.head()"
      ],
      "execution_count": 22,
      "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>ret</th>\n",
              "      <th>stdev</th>\n",
              "      <th>sharpe</th>\n",
              "      <th>KOSPI</th>\n",
              "      <th>SP</th>\n",
              "      <th>MSCI_EM</th>\n",
              "      <th>MSCI_WI</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.075460</td>\n",
              "      <td>0.065471</td>\n",
              "      <td>1.152583</td>\n",
              "      <td>0.322651</td>\n",
              "      <td>0.378031</td>\n",
              "      <td>0.094219</td>\n",
              "      <td>0.205099</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.072935</td>\n",
              "      <td>0.072807</td>\n",
              "      <td>1.001761</td>\n",
              "      <td>0.203696</td>\n",
              "      <td>0.101630</td>\n",
              "      <td>0.093035</td>\n",
              "      <td>0.601639</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.067838</td>\n",
              "      <td>0.064644</td>\n",
              "      <td>1.049401</td>\n",
              "      <td>0.445574</td>\n",
              "      <td>0.203694</td>\n",
              "      <td>0.049266</td>\n",
              "      <td>0.301467</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.071018</td>\n",
              "      <td>0.067240</td>\n",
              "      <td>1.056175</td>\n",
              "      <td>0.365275</td>\n",
              "      <td>0.376656</td>\n",
              "      <td>0.140298</td>\n",
              "      <td>0.117771</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.075413</td>\n",
              "      <td>0.073796</td>\n",
              "      <td>1.021912</td>\n",
              "      <td>0.300513</td>\n",
              "      <td>0.497098</td>\n",
              "      <td>0.171441</td>\n",
              "      <td>0.030948</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        ret     stdev    sharpe     KOSPI        SP   MSCI_EM   MSCI_WI\n",
              "0  0.075460  0.065471  1.152583  0.322651  0.378031  0.094219  0.205099\n",
              "1  0.072935  0.072807  1.001761  0.203696  0.101630  0.093035  0.601639\n",
              "2  0.067838  0.064644  1.049401  0.445574  0.203694  0.049266  0.301467\n",
              "3  0.071018  0.067240  1.056175  0.365275  0.376656  0.140298  0.117771\n",
              "4  0.075413  0.073796  1.021912  0.300513  0.497098  0.171441  0.030948"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pXj5qJmMDBXJ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "81e56a5c-83da-46ef-b556-854c576f369a"
      },
      "source": [
        "results_frame['sharpe'].idxmax()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "6558"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UDtIKEmeDFid",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 161
        },
        "outputId": "1a686760-8b4a-4d46-98a7-9edf64b46113"
      },
      "source": [
        "results_frame.iloc[results_frame['sharpe'].idxmax() , :]"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ret        0.087220\n",
              "stdev      0.066843\n",
              "sharpe     1.304844\n",
              "KOSPI      0.176923\n",
              "SP         0.389204\n",
              "MSCI_EM    0.001290\n",
              "MSCI_WI    0.432583\n",
              "Name: 6558, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_rVb-7qBDIML",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 161
        },
        "outputId": "d5f7d57f-3b27-4501-bdcd-4b2c80e56e3e"
      },
      "source": [
        "max_sharpe_port = results_frame.iloc[results_frame['sharpe'].idxmax()]\n",
        "min_vol_port    = results_frame.iloc[results_frame['stdev'].idxmin()] \n",
        "min_vol_port  "
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ret        0.073899\n",
              "stdev      0.062504\n",
              "sharpe     1.182302\n",
              "KOSPI      0.325262\n",
              "SP         0.253117\n",
              "MSCI_EM    0.057880\n",
              "MSCI_WI    0.363741\n",
              "Name: 22317, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IdyxK5zTDL1K",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 410
        },
        "outputId": "b55b5419-1466-4de5-cd97-53d9632ffd08"
      },
      "source": [
        "plt.figure(figsize=(12,6)); plt.grid()\n",
        "plt.scatter(results_frame.stdev, \n",
        "            results_frame.ret,\n",
        "            c = results_frame.sharpe)\n",
        "plt.xlabel('Volatility')\n",
        "plt.ylabel('Returns')\n",
        "plt.colorbar()\n",
        "\n",
        "plt.scatter(max_sharpe_port[1], max_sharpe_port[0],\n",
        "            marker = (5,1,0), color = 'r', s = 1000)\n",
        "\n",
        "plt.scatter(min_vol_port[1],  min_vol_port[0],\n",
        "            marker = (5,1,0), color = 'g', s = 1000)"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7f4de52079e8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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jp/+HZAZuwAs7oyhsk0BkACFJ5GnSRABYQohlSrZwP+s7X8bYtvexJ3sdXrAD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o5Z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\n",
            "text/plain": [
              "<Figure size 864x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HIkO3nZGDNs5",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 161
        },
        "outputId": "e6d069f1-4426-42bc-cc89-4c6840d729ce"
      },
      "source": [
        "print(max_sharpe_port)"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ret        0.087220\n",
            "stdev      0.066843\n",
            "sharpe     1.304844\n",
            "KOSPI      0.176923\n",
            "SP         0.389204\n",
            "MSCI_EM    0.001290\n",
            "MSCI_WI    0.432583\n",
            "Name: 6558, dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lzmiralLDSnS",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 161
        },
        "outputId": "27bd4a5a-44ad-400a-f037-0b1bad40ce75"
      },
      "source": [
        "print(min_vol_port)"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ret        0.073899\n",
            "stdev      0.062504\n",
            "sharpe     1.182302\n",
            "KOSPI      0.325262\n",
            "SP         0.253117\n",
            "MSCI_EM    0.057880\n",
            "MSCI_WI    0.363741\n",
            "Name: 22317, dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}