finlib/notebooks/historical_var.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-02-14T22:39:48.773873Z",
     "start_time": "2025-02-14T22:39:43.097057Z"
    }
   },
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from openbb import obb\n",
    "import pyfinlib\n"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-02-14T22:39:50.185368Z",
     "start_time": "2025-02-14T22:39:49.569809Z"
    }
   },
   "cell_type": "code",
   "source": "aapl = obb.equity.price.historical(symbol='AAPL', provider='yfinance')",
   "id": "e5573366e39b2962",
   "outputs": [],
   "execution_count": 2
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-02-14T22:39:50.886767Z",
     "start_time": "2025-02-14T22:39:50.882363Z"
    }
   },
   "cell_type": "code",
   "source": "data = [i.open for i in aapl.results]",
   "id": "481bc5b5742518f7",
   "outputs": [],
   "execution_count": 4
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-02-14T22:42:35.170044Z",
     "start_time": "2025-02-14T22:42:35.165964Z"
    }
   },
   "cell_type": "code",
   "source": [
    "VaR_historical = pyfinlib.risk.var.historical(data, 0.05)\n",
    "VaR_historical_10 = pyfinlib.risk.var.historical(data, 0.1)\n",
    "VaR_historical, VaR_historical_10"
   ],
   "id": "2cc84cfff89a39a1",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.023037706582264946, -0.016547437981254933)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 19
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-02-14T22:42:37.039118Z",
     "start_time": "2025-02-14T22:42:37.034625Z"
    }
   },
   "cell_type": "code",
   "source": "returns = pyfinlib.util.rates_of_change(data)",
   "id": "28a68dea99911874",
   "outputs": [],
   "execution_count": 20
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-02-14T22:42:37.361381Z",
     "start_time": "2025-02-14T22:42:37.264945Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# Plot the historical returns and VaR threshold\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.hist(returns, bins=50, alpha=0.75, color='blue', edgecolor='black')\n",
    "plt.axvline(VaR_historical, color='red', linestyle='--', label=f'VaR (95%): {VaR_historical:.2%}')\n",
    "plt.axvline(VaR_historical_10, color='orange', linestyle='--', label=f'VaR (90%): {VaR_historical_10:.2%}')\n",
    "plt.title('Historical Returns of AAPL')\n",
    "plt.xlabel('Returns')\n",
    "plt.ylabel('Frequency')\n",
    "plt.legend()\n",
    "plt.show()"
   ],
   "id": "5ab5e055a23f28ed",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 21
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": "",
   "id": "ddeb6ada3ab526b5"
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}