{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Jacques-Mock-Schindler/WR_I_21-24/blob/main/docs/230912/Optionen.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NT_Mdd7x3RC9"
      },
      "source": [
        "# Optionsgeschäfte\n",
        "\n",
        "Bei einem Optionsgeschäft, kauft der Optionär vom Stillhalter das Recht, ein Geschäft während eines bestimmten Zeitraums zu im Voraus definierten Bedingungen abzuschliessen. Im Gegensatz zum Termingeschäft ist der Optionär allerdings nicht verpflichtet, das Geschäft tatsächlich zu tätigen.\n",
        "\n",
        "Es werden verschiedene Arten von Optionsgeschäften unterschieden:\n",
        "\n",
        "* Ein **Long Call** ist der Kauf einer Kaufoption, die einem Käufer das Recht gibt, einen Basiswert während einer bestimmten Laufzeit zu einem vorher festgelegten Strike zu kaufen.\n",
        "\n",
        "* Ein **Long Put** ist der Kauf einer Verkaufsoption (Put-Option). Diese gewährt dem Käufer das Recht, eine Aktie zum Strike Preis zu verkaufen."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2BWePrhIlgEl"
      },
      "source": [
        "## Payoff-Diagramm zeichnen\n",
        "\n",
        "Gewinn und Verlust bei Optionsgeschäften werden in sogenannen Payoff-Diagrammen dargestellt."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uKnHabW0Bp3z"
      },
      "source": [
        "| Put Option | Call Option |\n",
        "| ---------- | ----------- |\n",
        "| ![Put Option](https://github.com/Jacques-Mock-Schindler/WR_I_21-24/blob/main/docs/230912/Payoff_put_option.svg?raw=1) | ![Call Option](https://github.com/Jacques-Mock-Schindler/WR_I_21-24/blob/main/docs/230912/Payoff_call_option.svg?raw=1) |"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Fp7HWa005X3O"
      },
      "source": [
        "Dabei wird auf der x-Achse der Preis des Basiswertes abgebildet. Auf der y-Achse können Gewinn und Verlust abgelesen werden.\n",
        "\n",
        "In der Folge geht es darum, bei gegebenen Options- und Ausübungspreisen selber Payoff-Diagramme zeichnen zu können."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4pgpPJTJwsqp"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "id": "VI_87W5RP4kO",
        "outputId": "c3759b26-978a-437c-95ed-eecaf44b5088"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<function matplotlib.pyplot.show(close=None, block=None)>"
            ]
          },
          "execution_count": 2,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "x = np.array([0 , 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120])\n",
        "y = np.array([-5, -5, -5, -5,  0,  5, 10, 15, 20, 25,  30,  35,  40])\n",
        "\n",
        "plt.suptitle(\"Payoff Diagramm\")\n",
        "plt.title(\"Optionstyp\")\n",
        "plt.xlabel(\"Preis Basiswert\")\n",
        "plt.ylabel(\"Payoff/Loss\")\n",
        "plt.hlines(y=0, xmin=0, xmax=130, linewidth=1, color='black')\n",
        "\n",
        "plt.plot(x,y)\n",
        "plt.fill_between(x, y, color='green', alpha=0.1, where= (x >=  40))\n",
        "plt.fill_between(x, y, color='red', alpha=0.1, where= (x <= 40))\n",
        "plt.grid()\n",
        "\n",
        "plt.show"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# TODO: hier eine Funktion schreiben, die für eine call option den\n",
        "# Ausübungspreis und die Optionsgebühr als Parmeter entgengennimmt"
      ],
      "metadata": {
        "id": "QEb8DckzB1Zy"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.11.5"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}