model.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "최현태HW102.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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",
              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 109
        },
        "id": "ZtOEphhrVgMd",
        "outputId": "0ea9ce3c-efc0-4a17-ff07-83720b28681b"
      },
      "source": [
        "from google.colab import files\n",
        "files.upload()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-03288394-020a-423e-be84-e52ec6574992\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-03288394-020a-423e-be84-e52ec6574992\">\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 kospi200_20090601_20090710.csv to kospi200_20090601_20090710.csv\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'kospi200_20090601_20090710.csv': b'\\xc0\\xcf\\xc0\\xda,\\xc1\\xbe\\xb0\\xa1,\\xb4\\xeb\\xba\\xf1,\\xb5\\xee\\xb6\\xf4\\xb7\\xfc,\\xbd\\xc3\\xb0\\xa1,\\xb0\\xed\\xb0\\xa1,\\xc0\\xfa\\xb0\\xa1,\\xb0\\xc5\\xb7\\xa1\\xb7\\xae,\\xb0\\xc5\\xb7\\xa1\\xb4\\xeb\\xb1\\xdd,\\xbb\\xf3\\xc0\\xe5\\xbd\\xc3\\xb0\\xa1\\xc3\\xd1\\xbe\\xd7\\n\"2009/07/10\",\"184.56\",\"-0.16\",\"-0.09\",\"185.27\",\"185.43\",\"182.84\",\"121806.0\",\"3654547.0\",\"6.4262035E8\"\\n\"2009/07/09\",\"184.72\",\"-0.01\",\"-0.01\",\"184.26\",\"186.51\",\"183.94\",\"147954.0\",\"4720080.0\",\"6.43629513E8\"\\n\"2009/07/08\",\"184.73\",\"-0.38\",\"-0.21\",\"183.86\",\"184.73\",\"182.28\",\"152507.0\",\"4179328.0\",\"6.43918886E8\"\\n\"2009/07/07\",\"185.11\",\"0.61\",\"0.33\",\"185.18\",\"186.02\",\"184.20\",\"163708.0\",\"4110109.0\",\"6.45156637E8\"\\n\"2009/07/06\",\"184.50\",\"1.58\",\"0.86\",\"182.78\",\"185.04\",\"182.36\",\"140128.0\",\"3748011.0\",\"6.42849362E8\"\\n\"2009/07/03\",\"182.92\",\"1.07\",\"0.59\",\"179.11\",\"182.92\",\"179.02\",\"139037.0\",\"3355239.0\",\"6.37968002E8\"\\n\"2009/07/02\",\"181.85\",\"-0.10\",\"-0.05\",\"182.92\",\"182.96\",\"180.80\",\"163024.0\",\"3813533.0\",\"6.3419248E8\"\\n\"2009/07/01\",\"181.95\",\"2.96\",\"1.65\",\"178.53\",\"182.50\",\"177.75\",\"162551.0\",\"4167307.0\",\"6.34480439E8\"\\n\"2009/06/30\",\"178.99\",\"0.18\",\"0.10\",\"180.65\",\"181.65\",\"178.69\",\"184365.0\",\"3872781.0\",\"6.24522098E8\"\\n\"2009/06/29\",\"178.81\",\"-0.47\",\"-0.26\",\"179.92\",\"181.42\",\"178.40\",\"151341.0\",\"3212268.0\",\"6.23581584E8\"\\n\"2009/06/26\",\"179.28\",\"0.42\",\"0.23\",\"180.04\",\"180.41\",\"178.45\",\"145231.0\",\"3984605.0\",\"6.25761926E8\"\\n\"2009/06/25\",\"178.86\",\"3.78\",\"2.16\",\"175.50\",\"180.46\",\"175.50\",\"188813.0\",\"4302987.0\",\"6.24837502E8\"\\n\"2009/06/24\",\"175.08\",\"0.76\",\"0.44\",\"174.96\",\"176.00\",\"173.22\",\"166005.0\",\"3645179.0\",\"6.11718937E8\"\\n\"2009/06/23\",\"174.32\",\"-4.70\",\"-2.63\",\"175.17\",\"175.81\",\"173.52\",\"216749.0\",\"4077385.0\",\"6.09420973E8\"\\n\"2009/06/22\",\"179.02\",\"2.39\",\"1.35\",\"176.46\",\"179.11\",\"176.12\",\"124457.0\",\"3429218.0\",\"6.27313063E8\"\\n\"2009/06/19\",\"176.63\",\"1.09\",\"0.62\",\"176.96\",\"177.38\",\"174.94\",\"149326.0\",\"3394472.0\",\"6.1943963E8\"\\n\"2009/06/18\",\"175.54\",\"-2.26\",\"-1.27\",\"177.56\",\"178.34\",\"174.90\",\"134104.0\",\"3538589.0\",\"6.15957748E8\"\\n\"2009/06/17\",\"177.80\",\"-1.08\",\"-0.60\",\"177.90\",\"178.65\",\"176.85\",\"143869.0\",\"3625019.0\",\"6.23502299E8\"\\n\"2009/06/16\",\"178.88\",\"-1.78\",\"-0.99\",\"178.27\",\"180.32\",\"177.58\",\"151070.0\",\"3585369.0\",\"6.27260437E8\"\\n\"2009/06/15\",\"180.66\",\"-2.03\",\"-1.11\",\"182.59\",\"182.64\",\"178.97\",\"136812.0\",\"3865872.0\",\"6.33815178E8\"\\n\"2009/06/12\",\"182.69\",\"1.26\",\"0.69\",\"182.74\",\"183.72\",\"181.23\",\"144430.0\",\"4163888.0\",\"6.41359788E8\"\\n\"2009/06/11\",\"181.43\",\"0.52\",\"0.29\",\"180.49\",\"183.84\",\"179.90\",\"193481.0\",\"5809853.0\",\"6.27031509E8\"\\n\"2009/06/10\",\"180.91\",\"6.00\",\"3.43\",\"176.01\",\"180.96\",\"175.52\",\"184735.0\",\"4729206.0\",\"6.24941442E8\"\\n\"2009/06/09\",\"174.91\",\"-2.76\",\"-1.55\",\"179.49\",\"180.00\",\"174.87\",\"173017.0\",\"4665716.0\",\"6.04551299E8\"\\n\"2009/06/08\",\"177.67\",\"-0.10\",\"-0.06\",\"177.65\",\"180.00\",\"176.87\",\"176062.0\",\"4226010.0\",\"6.14281494E8\"\\n\"2009/06/05\",\"177.77\",\"2.02\",\"1.15\",\"177.43\",\"177.77\",\"175.12\",\"175532.0\",\"4706980.0\",\"6.14723104E8\"\\n\"2009/06/04\",\"175.75\",\"-4.56\",\"-2.53\",\"179.55\",\"179.75\",\"175.35\",\"230558.0\",\"5425332.0\",\"6.07236207E8\"\\n\"2009/06/03\",\"180.31\",\"-0.16\",\"-0.09\",\"181.78\",\"182.25\",\"178.93\",\"276109.0\",\"5647738.0\",\"6.23493742E8\"\\n\"2009/06/02\",\"180.47\",\"-0.43\",\"-0.24\",\"183.64\",\"183.71\",\"180.30\",\"224413.0\",\"6205222.0\",\"6.23506344E8\"\\n\"2009/06/01\",\"180.90\",\"2.20\",\"1.23\",\"178.42\",\"180.90\",\"176.92\",\"189986.0\",\"5002028.0\",\"6.24475114E8\"'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pW7IJ6T8VrVW",
        "outputId": "784cf322-f800-4c2c-a952-a61ac05ed670"
      },
      "source": [
        "import pandas as pd\n",
        "dfKS200 = pd.read_csv('kospi200_20090601_20090710.csv', header=0, encoding= 'unicode_escape', \n",
        "                      names=['일자', '종가', '대비', '등락율','시가', '고가', '저가', '거래량', '거래대금', '상장시가총액'], index_col='일자')\n",
        "dfKS200['종가'].describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count     30.000000\n",
              "mean     179.900667\n",
              "std        3.174971\n",
              "min      174.320000\n",
              "25%      177.777500\n",
              "50%      179.795000\n",
              "75%      181.925000\n",
              "max      185.110000\n",
              "Name: 종가, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        },
        "id": "9QbE6b1AWY7t",
        "outputId": "3a8bc677-5ec1-4169-f4d2-ca865320152c"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "plt.hist(dfKS200['종가'], density=True, alpha=0.5)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0.09267841, 0.0617856 , 0.0308928 , 0.09267841, 0.18535681,\n",
              "        0.09267841, 0.12357121, 0.09267841, 0.        , 0.15446401]),\n",
              " array([174.32 , 175.399, 176.478, 177.557, 178.636, 179.715, 180.794,\n",
              "        181.873, 182.952, 184.031, 185.11 ]),\n",
              " <a list of 10 Patch objects>)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ru_XEyOrYpu8",
        "outputId": "ee3ed47c-d07d-424b-e0ed-d8d898e8a1a7"
      },
      "source": [
        "dfKS200['등락율'].describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    30.000000\n",
              "mean      0.114333\n",
              "std       1.258263\n",
              "min      -2.630000\n",
              "25%      -0.255000\n",
              "50%       0.045000\n",
              "75%       0.672500\n",
              "max       3.430000\n",
              "Name: 등락율, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oXY4Bd54ZSqK"
      },
      "source": [
        "import numpy as np\n",
        "dfKS200['log_return'] = np.log(dfKS200['종가']) - np.log(dfKS200['종가'].shift(1))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "X5j3jzytZjmk",
        "outputId": "b25d48d8-a3e6-4cc0-80a7-09e767372346"
      },
      "source": [
        "dfKS200.log_return.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    29.000000\n",
              "mean     -0.000691\n",
              "std       0.012608\n",
              "min      -0.033728\n",
              "25%      -0.006190\n",
              "50%       0.000054\n",
              "75%       0.002625\n",
              "max       0.026605\n",
              "Name: log_return, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SQ6xBbkKZoDD"
      },
      "source": [
        "r = (1+dfKS200.log_return.describe()['mean']) ** 27"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ig4wbtAFZv1V"
      },
      "source": [
        "K = 426.36 * r"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jKs9sENXaYP0",
        "outputId": "17088a2f-2536-41d4-d25d-8c04b33c2910"
      },
      "source": [
        "K"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "418.47987050718865"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "91fwSEeWq8dS",
        "outputId": "5b12f4f8-4dde-49fe-bbf5-38f58252b063"
      },
      "source": [
        "r"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9815176623210166"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fk4qlcKkaZaq"
      },
      "source": [
        "import seaborn"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9NxJ0URrrlOv",
        "outputId": "34946d1f-40f9-4dd8-c938-bde56d59773d"
      },
      "source": [
        "7.81 / 426.36 + 1"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.0183178534571724"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2xQQ9t3Arnui",
        "outputId": "6f7a71b8-7778-4c8f-8b8c-90ab13b849db"
      },
      "source": [
        "1 - 9.60 / 426.36"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9774838164931045"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "79Y2l3RearNE"
      },
      "source": [
        "spot_price = 426.36\n",
        "# Short put\n",
        "strike_price_short_put = spot_price * r\n",
        "premium_short_put = 9.60\n",
        "# Short call\n",
        "strike_price_short_call = strike_price_short_put\n",
        "premium_short_call = 7.81\n",
        "# Stock price range at expiration of the put\n",
        "sT = np.arange(300, 500, 1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "id": "g5X87dh7bl_I",
        "outputId": "60e20a15-74d6-42fe-86e9-b2f201e57b6c"
      },
      "source": [
        "def short_call_payoff(sT, strike_price, premium):\n",
        "    return np.where(sT > strike_price, strike_price - sT, 0) + premium\n",
        "\n",
        "payoff_short_call = short_call_payoff (sT, strike_price_short_call, premium_short_call)\n",
        "fig, ax = plt.subplots()\n",
        "ax.spines['top'].set_visible(False) # Top border removed \n",
        "ax.spines['right'].set_visible(False) # Right border removed\n",
        "ax.spines['bottom'].set_position('zero') # Sets the X-axis in the center\n",
        "ax.plot(sT, payoff_short_call,label='Short Call',color='r')\n",
        "plt.xlabel('Stock Price')\n",
        "plt.ylabel('Profit and loss')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "id": "IXv8UDQMcZeU",
        "outputId": "fc5dfbe1-ceea-4977-b795-7cb1424d85df"
      },
      "source": [
        "def short_put_payoff(sT, strike_price, premium):\n",
        "    return np.where(sT < strike_price, sT - strike_price, 0) + premium \n",
        "\n",
        "payoff_short_put = short_put_payoff(sT, strike_price_short_put, premium_short_put)\n",
        "# Plot\n",
        "fig, ax = plt.subplots()\n",
        "ax.spines['top'].set_visible(False) # Top border removed \n",
        "ax.spines['right'].set_visible(False) # Right border removed\n",
        "ax.spines['bottom'].set_position('zero') # Sets the X-axis in the center\n",
        "ax.plot(sT,payoff_short_put,label='Short Put',color='g')\n",
        "plt.xlabel('Stock Price')\n",
        "plt.ylabel('Profit and loss')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "gYcF4BFJc5hH",
        "outputId": "c461e384-743a-4cb7-d92b-10cdd482e82e"
      },
      "source": [
        "payoff_straddle = payoff_short_call + payoff_short_put\n",
        "\n",
        "print (f'Max Profit: {payoff_straddle.max()}')\n",
        "print (\"Max Loss:\", \"Unlimited\")\n",
        "# Plot\n",
        "fig, ax = plt.subplots()\n",
        "ax.spines['top'].set_visible(False) # Top border removed \n",
        "ax.spines['right'].set_visible(False) # Right border removed\n",
        "ax.spines['bottom'].set_position('zero') # Sets the X-axis in the center\n",
        "\n",
        "ax.plot(sT,payoff_short_call,'--',label='Short Call',color='r')\n",
        "ax.plot(sT,payoff_short_put,'--',label='Short Put',color='g')\n",
        "\n",
        "ax.plot(sT,payoff_straddle,label='Straddle')\n",
        "plt.xlabel('Stock Price', ha='left')\n",
        "plt.ylabel('Profit and loss')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Max Profit: 16.93012949281135\n",
            "Max Loss: Unlimited\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YDkTR_DGdGbR"
      },
      "source": [
        "from scipy.stats import norm\n",
        "stddev = 0.012608\n",
        "mean = 0.9815176623210166"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "AXQSUYkgmy47",
        "outputId": "2e02daac-9d56-4caa-d236-4b24348d8d5c"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "x=np.linspace(0.5, 1.5,1000)\n",
        "plt.plot(x, norm.pdf(x, mean, stddev))\n",
        "plt.show()\n",
        "# pl.plot(x,dist.cdf(x))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "De8p6QppnK8E",
        "outputId": "592e550b-17b3-430a-9e77-549c25215b72"
      },
      "source": [
        "norm.cdf(1.0183178534571724, mean, stddev) - norm.cdf(0.9774838164931045, mean, stddev)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.6237374391082874"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yh0W-09nphjk"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}