Delta Covar.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Load-Data\" data-toc-modified-id=\"Load-Data-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Load Data</a></span></li><li><span><a href=\"#covar-calculations\" data-toc-modified-id=\"covar-calculations-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>covar calculations</a></span><ul class=\"toc-item\"><li><ul class=\"toc-item\"><li><span><a href=\"#Normal-period---sector-wise\" data-toc-modified-id=\"Normal-period---sector-wise-2.0.1\"><span class=\"toc-item-num\">2.0.1&nbsp;&nbsp;</span>Normal period - sector wise</a></span></li><li><span><a href=\"#Shock-period---sector-wise\" data-toc-modified-id=\"Shock-period---sector-wise-2.0.2\"><span class=\"toc-item-num\">2.0.2&nbsp;&nbsp;</span>Shock period - sector wise</a></span></li></ul></li><li><span><a href=\"#State-Space-regression\" data-toc-modified-id=\"State-Space-regression-2.1\"><span class=\"toc-item-num\">2.1&nbsp;&nbsp;</span>State Space regression</a></span></li></ul></li></ul></div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\amand\\anaconda3\\lib\\site-packages\\pandas_datareader\\compat\\__init__.py:7: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
      "  from pandas.util.testing import assert_frame_equal\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime as dt\n",
    "from datetime import datetime\n",
    "import yfinance as yf\n",
    "from yahoofinancials import YahooFinancials\n",
    "import pandas_datareader.data as web\n",
    "from scipy import stats\n",
    "from statsmodels.regression.quantile_regression import QuantReg as qr\n",
    "import statsmodels.api as sma\n",
    "import pickle\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1927-12-30</th>\n",
       "      <td>17.660000</td>\n",
       "      <td>17.660000</td>\n",
       "      <td>17.660000</td>\n",
       "      <td>17.660000</td>\n",
       "      <td>17.660000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1928-01-03</th>\n",
       "      <td>17.760000</td>\n",
       "      <td>17.760000</td>\n",
       "      <td>17.760000</td>\n",
       "      <td>17.760000</td>\n",
       "      <td>17.760000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1928-01-04</th>\n",
       "      <td>17.719999</td>\n",
       "      <td>17.719999</td>\n",
       "      <td>17.719999</td>\n",
       "      <td>17.719999</td>\n",
       "      <td>17.719999</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1928-01-05</th>\n",
       "      <td>17.549999</td>\n",
       "      <td>17.549999</td>\n",
       "      <td>17.549999</td>\n",
       "      <td>17.549999</td>\n",
       "      <td>17.549999</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1928-01-06</th>\n",
       "      <td>17.660000</td>\n",
       "      <td>17.660000</td>\n",
       "      <td>17.660000</td>\n",
       "      <td>17.660000</td>\n",
       "      <td>17.660000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close  Adj Close  Volume\n",
       "Date                                                                     \n",
       "1927-12-30  17.660000  17.660000  17.660000  17.660000  17.660000       0\n",
       "1928-01-03  17.760000  17.760000  17.760000  17.760000  17.760000       0\n",
       "1928-01-04  17.719999  17.719999  17.719999  17.719999  17.719999       0\n",
       "1928-01-05  17.549999  17.549999  17.549999  17.549999  17.549999       0\n",
       "1928-01-06  17.660000  17.660000  17.660000  17.660000  17.660000       0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "system = yf.download('^GSPC', \n",
    "                      progress=False)\n",
    "system.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x18200eae508>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "system['Adj Close'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "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>Security</th>\n",
       "      <th>SEC filings</th>\n",
       "      <th>GICS Sector</th>\n",
       "      <th>GICS Sub Industry</th>\n",
       "      <th>Headquarters Location</th>\n",
       "      <th>Date first added</th>\n",
       "      <th>CIK</th>\n",
       "      <th>Founded</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MMM</th>\n",
       "      <td>3M Company</td>\n",
       "      <td>reports</td>\n",
       "      <td>Industrials</td>\n",
       "      <td>Industrial Conglomerates</td>\n",
       "      <td>St. Paul, Minnesota</td>\n",
       "      <td>8/9/1976</td>\n",
       "      <td>66740.0</td>\n",
       "      <td>1902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABT</th>\n",
       "      <td>Abbott Laboratories</td>\n",
       "      <td>reports</td>\n",
       "      <td>Health Care</td>\n",
       "      <td>Health Care Equipment</td>\n",
       "      <td>North Chicago, Illinois</td>\n",
       "      <td>3/31/1964</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>1888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABBV</th>\n",
       "      <td>AbbVie Inc.</td>\n",
       "      <td>reports</td>\n",
       "      <td>Health Care</td>\n",
       "      <td>Pharmaceuticals</td>\n",
       "      <td>North Chicago, Illinois</td>\n",
       "      <td>12/31/2012</td>\n",
       "      <td>1551152.0</td>\n",
       "      <td>2013 (1888)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABMD</th>\n",
       "      <td>ABIOMED Inc</td>\n",
       "      <td>reports</td>\n",
       "      <td>Health Care</td>\n",
       "      <td>Health Care Equipment</td>\n",
       "      <td>Danvers, Massachusetts</td>\n",
       "      <td>5/31/2018</td>\n",
       "      <td>815094.0</td>\n",
       "      <td>1981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACN</th>\n",
       "      <td>Accenture plc</td>\n",
       "      <td>reports</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Consulting &amp; Other Services</td>\n",
       "      <td>Dublin, Ireland</td>\n",
       "      <td>7/6/2011</td>\n",
       "      <td>1467373.0</td>\n",
       "      <td>1989</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Security SEC filings             GICS Sector  \\\n",
       "Symbol                                                            \n",
       "MMM              3M Company     reports             Industrials   \n",
       "ABT     Abbott Laboratories     reports             Health Care   \n",
       "ABBV            AbbVie Inc.     reports             Health Care   \n",
       "ABMD            ABIOMED Inc     reports             Health Care   \n",
       "ACN           Accenture plc     reports  Information Technology   \n",
       "\n",
       "                     GICS Sub Industry    Headquarters Location  \\\n",
       "Symbol                                                            \n",
       "MMM           Industrial Conglomerates      St. Paul, Minnesota   \n",
       "ABT              Health Care Equipment  North Chicago, Illinois   \n",
       "ABBV                   Pharmaceuticals  North Chicago, Illinois   \n",
       "ABMD             Health Care Equipment   Danvers, Massachusetts   \n",
       "ACN     IT Consulting & Other Services          Dublin, Ireland   \n",
       "\n",
       "       Date first added        CIK      Founded  \n",
       "Symbol                                           \n",
       "MMM            8/9/1976    66740.0         1902  \n",
       "ABT           3/31/1964     1800.0         1888  \n",
       "ABBV         12/31/2012  1551152.0  2013 (1888)  \n",
       "ABMD          5/31/2018   815094.0         1981  \n",
       "ACN            7/6/2011  1467373.0         1989  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sector = pd.read_csv('./Data/snp_tickers_sectors.csv',index_col = 0)\n",
    "col_name = sector.columns[2]\n",
    "sector.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "505"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snp_stocks = list(sector.index)\n",
    "len(snp_stocks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def download_stock(stock):\n",
    "    \"\"\" try to query the iex for a stock, if failed note with print \"\"\"\n",
    "    try:\n",
    "        #print(stock)\n",
    "        stock_df = web.DataReader(stock,'yahoo',start=dt.date(1970,1,1))\n",
    "        stock_df['Name'] = stock\n",
    "        output_name = stock + '_data.csv'\n",
    "        #stock_df.to_csv(output_name)\n",
    "        return stock_df\n",
    "    except:\n",
    "        bad_names.append(stock)\n",
    "        print('bad: %s' % (stock))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MMM\n",
      "ABT\n",
      "ABBV\n",
      "ABMD\n",
      "ACN\n",
      "ATVI\n",
      "ADBE\n",
      "AMD\n",
      "AAP\n",
      "AES\n",
      "AFL\n",
      "A\n",
      "APD\n",
      "AKAM\n",
      "ALK\n",
      "ALB\n",
      "ARE\n",
      "ALXN\n",
      "ALGN\n",
      "ALLE\n",
      "LNT\n",
      "ALL\n",
      "GOOGL\n",
      "GOOG\n",
      "MO\n",
      "AMZN\n",
      "AMCR\n",
      "AEE\n",
      "AAL\n",
      "AEP\n",
      "AXP\n",
      "AIG\n",
      "AMT\n",
      "AWK\n",
      "AMP\n",
      "ABC\n",
      "AME\n",
      "AMGN\n",
      "APH\n",
      "ADI\n",
      "ANSS\n",
      "ANTM\n",
      "AON\n",
      "AOS\n",
      "APA\n",
      "AIV\n",
      "AAPL\n",
      "AMAT\n",
      "APTV\n",
      "ADM\n",
      "ANET\n",
      "AJG\n",
      "AIZ\n",
      "T\n",
      "ATO\n",
      "ADSK\n",
      "ADP\n",
      "AZO\n",
      "AVB\n",
      "AVY\n",
      "BKR\n",
      "BLL\n",
      "BAC\n",
      "BK\n",
      "BAX\n",
      "BDX\n",
      "BRK.B\n",
      "bad: BRK.B\n",
      "BBY\n",
      "BIO\n",
      "BIIB\n",
      "BLK\n",
      "BA\n",
      "BKNG\n",
      "BWA\n",
      "BXP\n",
      "BSX\n",
      "BMY\n",
      "AVGO\n",
      "BR\n",
      "BF.B\n",
      "bad: BF.B\n",
      "CHRW\n",
      "COG\n",
      "CDNS\n",
      "CPB\n",
      "COF\n",
      "CAH\n",
      "KMX\n",
      "CCL\n",
      "CARR\n",
      "CTLT\n",
      "CAT\n",
      "CBOE\n",
      "CBRE\n",
      "CDW\n",
      "CE\n",
      "CNC\n",
      "CNP\n",
      "CERN\n",
      "CF\n",
      "SCHW\n",
      "CHTR\n",
      "CVX\n",
      "CMG\n",
      "CB\n",
      "CHD\n",
      "CI\n",
      "CINF\n",
      "CTAS\n",
      "CSCO\n",
      "C\n",
      "CFG\n",
      "CTXS\n",
      "CLX\n",
      "CME\n",
      "CMS\n",
      "KO\n",
      "CTSH\n",
      "CL\n",
      "CMCSA\n",
      "CMA\n",
      "CAG\n",
      "CXO\n",
      "COP\n",
      "ED\n",
      "STZ\n",
      "COO\n",
      "CPRT\n",
      "GLW\n",
      "CTVA\n",
      "COST\n",
      "CCI\n",
      "CSX\n",
      "CMI\n",
      "CVS\n",
      "DHI\n",
      "DHR\n",
      "DRI\n",
      "DVA\n",
      "DE\n",
      "DAL\n",
      "XRAY\n",
      "DVN\n",
      "DXCM\n",
      "FANG\n",
      "DLR\n",
      "DFS\n",
      "DISCA\n",
      "DISCK\n",
      "DISH\n",
      "DG\n",
      "DLTR\n",
      "D\n",
      "DPZ\n",
      "DOV\n",
      "DOW\n",
      "DTE\n",
      "DUK\n",
      "DRE\n",
      "DD\n",
      "DXC\n",
      "EMN\n",
      "ETN\n",
      "EBAY\n",
      "ECL\n",
      "EIX\n",
      "EW\n",
      "EA\n",
      "EMR\n",
      "ETR\n",
      "EOG\n",
      "EFX\n",
      "EQIX\n",
      "EQR\n",
      "ESS\n",
      "EL\n",
      "ETSY\n",
      "EVRG\n",
      "ES\n",
      "RE\n",
      "EXC\n",
      "EXPE\n",
      "EXPD\n",
      "EXR\n",
      "XOM\n",
      "FFIV\n",
      "FB\n",
      "FAST\n",
      "FRT\n",
      "FDX\n",
      "FIS\n",
      "FITB\n",
      "FE\n",
      "FRC\n",
      "FISV\n",
      "FLT\n",
      "FLIR\n",
      "FLS\n",
      "FMC\n",
      "F\n",
      "FTNT\n",
      "FTV\n",
      "FBHS\n",
      "FOXA\n",
      "FOX\n",
      "BEN\n",
      "FCX\n",
      "GPS\n",
      "GRMN\n",
      "IT\n",
      "GD\n",
      "GE\n",
      "GIS\n",
      "GM\n",
      "GPC\n",
      "GILD\n",
      "GL\n",
      "GPN\n",
      "GS\n",
      "GWW\n",
      "HAL\n",
      "HBI\n",
      "HIG\n",
      "HAS\n",
      "HCA\n",
      "PEAK\n",
      "HSIC\n",
      "HSY\n",
      "HES\n",
      "HPE\n",
      "HLT\n",
      "HFC\n",
      "HOLX\n",
      "HD\n",
      "HON\n",
      "HRL\n",
      "HST\n",
      "HWM\n",
      "HPQ\n",
      "HUM\n",
      "HBAN\n",
      "HII\n",
      "IEX\n",
      "IDXX\n",
      "INFO\n",
      "ITW\n",
      "ILMN\n",
      "INCY\n",
      "IR\n",
      "INTC\n",
      "ICE\n",
      "IBM\n",
      "IP\n",
      "IPG\n",
      "IFF\n",
      "INTU\n",
      "ISRG\n",
      "IVZ\n",
      "IPGP\n",
      "IQV\n",
      "IRM\n",
      "JKHY\n",
      "J\n",
      "JBHT\n",
      "SJM\n",
      "JNJ\n",
      "JCI\n",
      "JPM\n",
      "JNPR\n",
      "KSU\n",
      "K\n",
      "KEY\n",
      "KEYS\n",
      "KMB\n",
      "KIM\n",
      "KMI\n",
      "KLAC\n",
      "KHC\n",
      "KR\n",
      "LB\n",
      "LHX\n",
      "LH\n",
      "LRCX\n",
      "LW\n",
      "LVS\n",
      "LEG\n",
      "LDOS\n",
      "LEN\n",
      "LLY\n",
      "LNC\n",
      "LIN\n",
      "LYV\n",
      "LKQ\n",
      "LMT\n",
      "L\n",
      "LOW\n",
      "LUMN\n",
      "LYB\n",
      "MTB\n",
      "MRO\n",
      "MPC\n",
      "MKTX\n",
      "MAR\n",
      "MMC\n",
      "MLM\n",
      "MAS\n",
      "MA\n",
      "MKC\n",
      "MXIM\n",
      "MCD\n",
      "MCK\n",
      "MDT\n",
      "MRK\n",
      "MET\n",
      "MTD\n",
      "MGM\n",
      "MCHP\n",
      "MU\n",
      "MSFT\n",
      "MAA\n",
      "MHK\n",
      "TAP\n",
      "MDLZ\n",
      "MNST\n",
      "MCO\n",
      "MS\n",
      "MOS\n",
      "MSI\n",
      "MSCI\n",
      "MYL\n",
      "NDAQ\n",
      "NOV\n",
      "NTAP\n",
      "NFLX\n",
      "NWL\n",
      "NEM\n",
      "NWSA\n",
      "NWS\n",
      "NEE\n",
      "NLSN\n",
      "NKE\n",
      "NI\n",
      "NSC\n",
      "NTRS\n",
      "NOC\n",
      "NLOK\n",
      "NCLH\n",
      "NRG\n",
      "NUE\n",
      "NVDA\n",
      "NVR\n",
      "ORLY\n",
      "OXY\n",
      "ODFL\n",
      "OMC\n",
      "OKE\n",
      "ORCL\n",
      "OTIS\n",
      "PCAR\n",
      "PKG\n",
      "PH\n",
      "PAYX\n",
      "PAYC\n",
      "PYPL\n",
      "PNR\n",
      "PBCT\n",
      "PEP\n",
      "PKI\n",
      "PRGO\n",
      "PFE\n",
      "PM\n",
      "PSX\n",
      "PNW\n",
      "PXD\n",
      "PNC\n",
      "POOL\n",
      "PPG\n",
      "PPL\n",
      "PFG\n",
      "PG\n",
      "PGR\n",
      "PLD\n",
      "PRU\n",
      "PEG\n",
      "PSA\n",
      "PHM\n",
      "PVH\n",
      "QRVO\n",
      "PWR\n",
      "QCOM\n",
      "DGX\n",
      "RL\n",
      "RJF\n",
      "RTX\n",
      "O\n",
      "REG\n",
      "REGN\n",
      "RF\n",
      "RSG\n",
      "RMD\n",
      "RHI\n",
      "ROK\n",
      "ROL\n",
      "ROP\n",
      "ROST\n",
      "RCL\n",
      "SPGI\n",
      "CRM\n",
      "SBAC\n",
      "SLB\n",
      "STX\n",
      "SEE\n",
      "SRE\n",
      "NOW\n",
      "SHW\n",
      "SPG\n",
      "SWKS\n",
      "SLG\n",
      "SNA\n",
      "SO\n",
      "LUV\n",
      "SWK\n",
      "SBUX\n",
      "STT\n",
      "STE\n",
      "SYK\n",
      "SIVB\n",
      "SYF\n",
      "SNPS\n",
      "SYY\n",
      "TMUS\n",
      "TROW\n",
      "TTWO\n",
      "TPR\n",
      "TGT\n",
      "TEL\n",
      "FTI\n",
      "TDY\n",
      "TFX\n",
      "TER\n",
      "TXN\n",
      "TXT\n",
      "TMO\n",
      "TIF\n",
      "TJX\n",
      "TSCO\n",
      "TT\n",
      "TDG\n",
      "TRV\n",
      "TFC\n",
      "TWTR\n",
      "TYL\n",
      "TSN\n",
      "UDR\n",
      "ULTA\n",
      "USB\n",
      "UAA\n",
      "UA\n",
      "UNP\n",
      "UAL\n",
      "UNH\n",
      "UPS\n",
      "URI\n",
      "UHS\n",
      "UNM\n",
      "VFC\n",
      "VLO\n",
      "VAR\n",
      "VTR\n",
      "VRSN\n",
      "VRSK\n",
      "VZ\n",
      "VRTX\n",
      "VIAC\n",
      "V\n",
      "VNT\n",
      "VNO\n",
      "VMC\n",
      "WRB\n",
      "WAB\n",
      "WMT\n",
      "WBA\n",
      "DIS\n",
      "WM\n",
      "WAT\n",
      "WEC\n",
      "WFC\n",
      "WELL\n",
      "WST\n",
      "WDC\n",
      "WU\n",
      "WRK\n",
      "WY\n",
      "WHR\n",
      "WMB\n",
      "WLTW\n",
      "WYNN\n",
      "XEL\n",
      "XRX\n",
      "XLNX\n",
      "XYL\n",
      "YUM\n",
      "ZBRA\n",
      "ZBH\n",
      "ZION\n",
      "ZTS\n"
     ]
    }
   ],
   "source": [
    "# bad_names = []\n",
    "# stock_data = {}\n",
    "# for sym in snp_stocks:\n",
    "#     print(sym)\n",
    "#     try:\n",
    "#         stock_data[sym] = download_stock(sym)\n",
    "#     except:\n",
    "#         pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# with open('./Data/stock_data','wb') as f:\n",
    "#     pickle.dump(stock_data,f,pickle.HIGHEST_PROTOCOL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "for sym in bad_names:\n",
    "    stock_data.pop(sym)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('./Data/stock_data','rb') as f:\n",
    "    stock_data = pickle.load(f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# covar calculations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 342,
   "metadata": {},
   "outputs": [],
   "source": [
    "def quantile_reg(system_losses,roll_var,q):\n",
    "    Y = system_losses.copy()\n",
    "    X = roll_var.copy()\n",
    "    common_index = X.dropna().index.intersection(Y.dropna().index)\n",
    "    X = X.loc[common_index]\n",
    "    Y = Y.loc[common_index]\n",
    "    model = qr(Y,sma.add_constant(X)).fit(q)\n",
    "    return model\n",
    "    \n",
    "    \n",
    "    \n",
    "    \n",
    "\n",
    "def est_delta_covar(system_losses,stock_losses,q,roll_window,method='emp'):\n",
    "    if((method != 'emp')and(method!='norm')):\n",
    "        raise Exception('Wrong input for method')\n",
    "    \n",
    "    if(method == 'emp'):\n",
    "        roll_var = stock_losses.rolling(window = roll_window,min_periods = int(0.8*roll_window))\\\n",
    "                                    .apply(lambda x: np.quantile(x,q))\n",
    "        \n",
    "        roll_median = stock_losses.rolling(window = roll_window,min_periods = int(0.8*roll_window)).median()\n",
    "        \n",
    "    else:\n",
    "        roll_median = stock_losses.rolling(window = roll_window,min_periods = int(0.8*roll_window)).mean()\n",
    "        std = stock_losses.rolling(window = roll_window,min_periods = int(0.8*roll_window)).std()\n",
    "        \n",
    "        roll_var = roll_median + stats.norm.ppf(q) * std\n",
    "        \n",
    "    model_q = quantile_reg(system_losses,roll_var,q)\n",
    "    model_median = quantile_reg(system_losses,roll_median,q)\n",
    "        \n",
    "        #import pdb;pdb.set_trace()\n",
    "        \n",
    "    delta_covar =  (model_q.fittedvalues - model_median.fittedvalues)\n",
    "\n",
    "        \n",
    "    return delta_covar,roll_var\n",
    "\n",
    "        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [],
   "source": [
    "stock_losses = {}\n",
    "for sym in stock_data.keys():\n",
    "        adj_close = stock_data[sym]['Adj Close'].resample('1W').last().dropna()\n",
    "        stock_losses[sym] = 100* (adj_close.shift(1) - adj_close)/adj_close.shift(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [],
   "source": [
    "system_close = system['Adj Close'].resample('1W').last().dropna()\n",
    "system_losses = 100* (system_close.shift(1) - system_close)/system_close.shift(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CARR\n",
      "CTVA\n",
      "DOW\n",
      "FTV\n",
      "FOXA\n",
      "FOX\n",
      "HWM\n",
      "IR\n",
      "LW\n",
      "LUMN\n",
      "OTIS\n",
      "VIAC\n",
      "VNT\n"
     ]
    }
   ],
   "source": [
    "delta_covar_dict = {}\n",
    "roll_var_dict = {}\n",
    "shock_df = pd.DataFrame()\n",
    "normal_df = pd.DataFrame()\n",
    "roll_window = 52*3\n",
    "normal_date = dt.date(2018,5,13)\n",
    "q = 0.99\n",
    "\n",
    "for sym in stock_data.keys():\n",
    "    \n",
    "    try:\n",
    "        delta_covar_dict[sym],roll_var_dict[sym] = est_delta_covar(system_losses,stock_losses[sym],q,roll_window)\n",
    "        shock_df.loc[sym,'Delta Covar'] = delta_covar_dict[sym][-1]\n",
    "        shock_df.loc[sym,'VaR'] = roll_var_dict[sym][-1]\n",
    "        shock_df.loc[sym,'Sector'] = sector.loc[sym,col_name]\n",
    "\n",
    "        normal_df.loc[sym,'Delta Covar'] = delta_covar_dict[sym].loc[normal_date]\n",
    "        normal_df.loc[sym,'VaR'] = roll_var_dict[sym].loc[normal_date]\n",
    "        normal_df.loc[sym,'Sector'] = sector.loc[sym,col_name]\n",
    "    except:\n",
    "        print(sym)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'VaR')"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,axs = plt.subplots(1,2,figsize = (20,6))\n",
    "axs[0].scatter(shock_df['VaR']*(13**0.5),shock_df['Delta Covar']*(13**0.5))\n",
    "axs[1].scatter(normal_df['VaR']*(13**0.5),normal_df['Delta Covar']*(13**0.5))\n",
    "axs[1].set_title('Normal Period')\n",
    "axs[0].set_title('Shock Period')\n",
    "\n",
    "axs[0].set_ylabel('$\\Delta$CoVaR')\n",
    "axs[0].set_xlabel('VaR')\n",
    "\n",
    "axs[1].set_ylabel('$\\Delta$CoVaR')\n",
    "axs[1].set_xlabel('VaR')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Normal period - sector wise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x2592 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sector_names = list(set(list(sector[col_name])))\n",
    "fig,axs = plt.subplots(6,2,figsize = (20,36))\n",
    "axs = np.reshape(axs,12)\n",
    "for i,sec in enumerate(sector_names):\n",
    "    tp = normal_df.loc[normal_df['Sector'] == sec]\n",
    "    axs[i].scatter(tp['VaR']*(13**0.5),tp['Delta Covar']*(13**0.5))\n",
    "    axs[i].set_ylabel('$\\Delta$CoVaR')\n",
    "    axs[i].set_xlabel('VaR')\n",
    "    axs[i].set_title(sec,fontsize = 15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Shock period - sector wise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x2592 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sector_names = list(set(list(sector[col_name])))\n",
    "fig,axs = plt.subplots(6,2,figsize = (20,36))\n",
    "axs = np.reshape(axs,12)\n",
    "for i,sec in enumerate(sector_names):\n",
    "    tp = shock_df.loc[shock_df['Sector'] == sec]\n",
    "    axs[i].scatter(tp['VaR']*(13**0.5),tp['Delta Covar']*(13**0.5))\n",
    "    axs[i].set_ylabel('$\\Delta$CoVaR')\n",
    "    axs[i].set_xlabel('VaR')\n",
    "    axs[i].set_title(sec,fontsize = 15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "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>Corr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MMM</th>\n",
       "      <td>0.988049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABT</th>\n",
       "      <td>0.973913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABBV</th>\n",
       "      <td>0.848704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABMD</th>\n",
       "      <td>0.143228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACN</th>\n",
       "      <td>0.996370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YUM</th>\n",
       "      <td>0.603499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZBRA</th>\n",
       "      <td>0.591857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZBH</th>\n",
       "      <td>0.671909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZION</th>\n",
       "      <td>0.342774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZTS</th>\n",
       "      <td>0.913085</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>493 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Corr\n",
       "MMM   0.988049\n",
       "ABT   0.973913\n",
       "ABBV  0.848704\n",
       "ABMD  0.143228\n",
       "ACN   0.996370\n",
       "...        ...\n",
       "YUM   0.603499\n",
       "ZBRA  0.591857\n",
       "ZBH   0.671909\n",
       "ZION  0.342774\n",
       "ZTS   0.913085\n",
       "\n",
       "[493 rows x 1 columns]"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "correlation = pd.DataFrame()\n",
    "for sym in delta_covar_dict.keys():\n",
    "    tp = pd.DataFrame()\n",
    "    tp['1'] = delta_covar_dict[sym]\n",
    "    tp['2'] = roll_var_dict[sym]\n",
    "    correlation.loc[sym,'Corr'] = tp.corr().iloc[0,1]\n",
    "correlation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## State Space regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 385,
   "metadata": {},
   "outputs": [],
   "source": [
    "M = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 386,
   "metadata": {},
   "outputs": [
    {
     "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>Value</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1954-01-04</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1954-01-05</th>\n",
       "      <td>-0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1954-01-06</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1954-01-07</th>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1954-01-08</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Value\n",
       "DATE             \n",
       "1954-01-04    NaN\n",
       "1954-01-05  -0.05\n",
       "1954-01-06   0.00\n",
       "1954-01-07   0.03\n",
       "1954-01-08   0.00"
      ]
     },
     "execution_count": 386,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "delta_yield = pd.read_csv('./Data/Chng_3month_yield.csv',index_col = 0,parse_dates = True)\n",
    "delta_yield.replace('.',np.nan,inplace = True)\n",
    "delta_yield = delta_yield.astype(float)\n",
    "delta_yield.columns = ['Value']\n",
    "delta_yield.index  = pd.to_datetime(delta_yield.index)\n",
    "M['Delta_yield'] = delta_yield['Value']\n",
    "delta_yield.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 387,
   "metadata": {},
   "outputs": [
    {
     "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>Value</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1954-01-04</th>\n",
       "      <td>1.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1954-01-05</th>\n",
       "      <td>1.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1954-01-06</th>\n",
       "      <td>1.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1954-01-07</th>\n",
       "      <td>1.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1954-01-08</th>\n",
       "      <td>1.31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Value\n",
       "Date             \n",
       "1954-01-04   1.33\n",
       "1954-01-05   1.28\n",
       "1954-01-06   1.28\n",
       "1954-01-07   1.31\n",
       "1954-01-08   1.31"
      ]
     },
     "execution_count": 387,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tbill_rate = pd.read_csv('./Data/FRED-DTB3.csv',index_col = 0,parse_dates = True)\n",
    "tbill_rate = tbill_rate.iloc[::-1]\n",
    "tbill_rate = tbill_rate.astype(float)\n",
    "tbill_rate.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 388,
   "metadata": {},
   "outputs": [
    {
     "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>Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1981-07-01</th>\n",
       "      <td>12.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-07-02</th>\n",
       "      <td>12.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-07-03</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-07-06</th>\n",
       "      <td>12.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-07-07</th>\n",
       "      <td>12.91</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Value\n",
       "1981-07-01  12.92\n",
       "1981-07-02  12.82\n",
       "1981-07-03    NaN\n",
       "1981-07-06  12.68\n",
       "1981-07-07  12.91"
      ]
     },
     "execution_count": 388,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lterm_rate = pd.DataFrame()\n",
    "data1 = pd.read_csv('./Data/DLTBOARD.csv',index_col = 0,parse_dates = True)\n",
    "data1.replace('.',np.nan,inplace = True)\n",
    "data1 = data1.astype(float)\n",
    "data1 = data1[data1.columns[0]]\n",
    "\n",
    "data2 = pd.read_csv('./Data/USTREASURY-LONGTERMRATES.csv',index_col = 0,parse_dates = True)\n",
    "data2 = data2[data2.columns[0]]\n",
    "data2 = data2.iloc[::-1]\n",
    "data2 = data2.astype(float)\n",
    "\n",
    "tp = data1.append(data2)\n",
    "lterm_rate['Value'] = tp\n",
    "lterm_rate.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 389,
   "metadata": {},
   "outputs": [
    {
     "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>Delta_yield</th>\n",
       "      <th>Delta_slope</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1981-07-01</th>\n",
       "      <td>0.37</td>\n",
       "      <td>1.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-07-02</th>\n",
       "      <td>-0.17</td>\n",
       "      <td>1.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-07-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-07-07</th>\n",
       "      <td>0.54</td>\n",
       "      <td>1.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981-07-08</th>\n",
       "      <td>0.09</td>\n",
       "      <td>2.04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Delta_yield  Delta_slope\n",
       "1981-07-01         0.37         1.73\n",
       "1981-07-02        -0.17         1.66\n",
       "1981-07-06          NaN         1.67\n",
       "1981-07-07         0.54         1.98\n",
       "1981-07-08         0.09         2.04"
      ]
     },
     "execution_count": 389,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "delta_slope = pd.DataFrame()\n",
    "delta_slope['Delta_slope'] = tbill_rate['Value'] - lterm_rate['Value']\n",
    "delta_slope.dropna(inplace = True)\n",
    "delta_slope.index  = pd.to_datetime(delta_slope.index)\n",
    "M = pd.concat([M,delta_slope],axis = 1,join='inner')\n",
    "M.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 390,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9907"
      ]
     },
     "execution_count": 390,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(M)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 391,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "        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>Delta_yield</th>\n",
       "      <th>Delta_slope</th>\n",
       "      <th>TED_spread</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-08-25</th>\n",
       "      <td>-0.01</td>\n",
       "      <td>-1.12</td>\n",
       "      <td>0.14100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-26</th>\n",
       "      <td>0.00</td>\n",
       "      <td>-1.14</td>\n",
       "      <td>0.14588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-27</th>\n",
       "      <td>0.00</td>\n",
       "      <td>-1.22</td>\n",
       "      <td>0.13600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-28</th>\n",
       "      <td>-0.01</td>\n",
       "      <td>-1.25</td>\n",
       "      <td>0.14088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-31</th>\n",
       "      <td>0.01</td>\n",
       "      <td>-1.20</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Delta_yield  Delta_slope  TED_spread\n",
       "2020-08-25        -0.01        -1.12     0.14100\n",
       "2020-08-26         0.00        -1.14     0.14588\n",
       "2020-08-27         0.00        -1.22     0.13600\n",
       "2020-08-28        -0.01        -1.25     0.14088\n",
       "2020-08-31         0.01        -1.20         NaN"
      ]
     },
     "execution_count": 391,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "libor = pd.read_csv('./Data/USD3MTD156N.csv',index_col = 0,parse_dates=True)\n",
    "libor.replace('.',np.nan,inplace = True)\n",
    "libor = libor.astype(float)\n",
    "ted_spread = pd.DataFrame()\n",
    "ted_spread['TED_spread'] = libor[libor.columns[0]] - tbill_rate['Value'] \n",
    "ted_spread.dropna(inplace=True)\n",
    "M['TED_spread'] = ted_spread['TED_spread']\n",
    "M.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 392,
   "metadata": {},
   "outputs": [
    {
     "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>Delta_yield</th>\n",
       "      <th>Delta_slope</th>\n",
       "      <th>TED_spread</th>\n",
       "      <th>Delta_cs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-08-25</th>\n",
       "      <td>-0.01</td>\n",
       "      <td>-1.12</td>\n",
       "      <td>0.14100</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-26</th>\n",
       "      <td>0.00</td>\n",
       "      <td>-1.14</td>\n",
       "      <td>0.14588</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-27</th>\n",
       "      <td>0.00</td>\n",
       "      <td>-1.22</td>\n",
       "      <td>0.13600</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-28</th>\n",
       "      <td>-0.01</td>\n",
       "      <td>-1.25</td>\n",
       "      <td>0.14088</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-31</th>\n",
       "      <td>0.01</td>\n",
       "      <td>-1.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Delta_yield  Delta_slope  TED_spread  Delta_cs\n",
       "2020-08-25        -0.01        -1.12     0.14100      0.00\n",
       "2020-08-26         0.00        -1.14     0.14588      0.03\n",
       "2020-08-27         0.00        -1.22     0.13600      0.05\n",
       "2020-08-28        -0.01        -1.25     0.14088      0.00\n",
       "2020-08-31         0.01        -1.20         NaN     -0.04"
      ]
     },
     "execution_count": 392,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "delta_credit_spread = pd.read_csv('./Data/Chng_CrediT_Spread.csv',index_col = 0,parse_dates=True)\n",
    "delta_credit_spread.replace('.',np.nan,inplace = True)\n",
    "delta_credit_spread = delta_credit_spread.astype(float)\n",
    "delta_credit_spread.columns = ['Value']\n",
    "M['Delta_cs'] = delta_credit_spread['Value']\n",
    "M.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 393,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "    }\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>Delta_yield</th>\n",
       "      <th>Delta_slope</th>\n",
       "      <th>TED_spread</th>\n",
       "      <th>Delta_cs</th>\n",
       "      <th>vol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-08-25</th>\n",
       "      <td>-0.01</td>\n",
       "      <td>-1.12</td>\n",
       "      <td>0.14100</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.005750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-26</th>\n",
       "      <td>0.00</td>\n",
       "      <td>-1.14</td>\n",
       "      <td>0.14588</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.005879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-27</th>\n",
       "      <td>0.00</td>\n",
       "      <td>-1.22</td>\n",
       "      <td>0.13600</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.005479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-28</th>\n",
       "      <td>-0.01</td>\n",
       "      <td>-1.25</td>\n",
       "      <td>0.14088</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.005169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-31</th>\n",
       "      <td>0.01</td>\n",
       "      <td>-1.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>0.005077</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Delta_yield  Delta_slope  TED_spread  Delta_cs       vol\n",
       "2020-08-25        -0.01        -1.12     0.14100      0.00  0.005750\n",
       "2020-08-26         0.00        -1.14     0.14588      0.03  0.005879\n",
       "2020-08-27         0.00        -1.22     0.13600      0.05  0.005479\n",
       "2020-08-28        -0.01        -1.25     0.14088      0.00  0.005169\n",
       "2020-08-31         0.01        -1.20         NaN     -0.04  0.005077"
      ]
     },
     "execution_count": 393,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "system_close = system['Adj Close']\n",
    "rets = (system_close - system_close.shift(1))/system_close.shift(1)\n",
    "vol = rets.rolling(window = 22).std()\n",
    "M['vol'] = vol\n",
    "M.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 412,
   "metadata": {},
   "outputs": [
    {
     "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>Delta_yield</th>\n",
       "      <th>Delta_slope</th>\n",
       "      <th>TED_spread</th>\n",
       "      <th>Delta_cs</th>\n",
       "      <th>vol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1809.000000</td>\n",
       "      <td>1809.000000</td>\n",
       "      <td>1809.000000</td>\n",
       "      <td>1809.000000</td>\n",
       "      <td>1809.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-0.007330</td>\n",
       "      <td>-2.217697</td>\n",
       "      <td>0.567426</td>\n",
       "      <td>0.001360</td>\n",
       "      <td>0.009790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.044255</td>\n",
       "      <td>1.224277</td>\n",
       "      <td>0.432739</td>\n",
       "      <td>0.035161</td>\n",
       "      <td>0.006406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-0.420000</td>\n",
       "      <td>-4.490000</td>\n",
       "      <td>0.097030</td>\n",
       "      <td>-0.210000</td>\n",
       "      <td>0.002171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.020000</td>\n",
       "      <td>-3.220000</td>\n",
       "      <td>0.258750</td>\n",
       "      <td>-0.020000</td>\n",
       "      <td>0.006118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-2.220000</td>\n",
       "      <td>0.444750</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.010000</td>\n",
       "      <td>-1.150000</td>\n",
       "      <td>0.717500</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.011437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.340000</td>\n",
       "      <td>4.170000</td>\n",
       "      <td>0.260000</td>\n",
       "      <td>0.058503</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Delta_yield  Delta_slope   TED_spread     Delta_cs          vol\n",
       "count  1809.000000  1809.000000  1809.000000  1809.000000  1809.000000\n",
       "mean     -0.007330    -2.217697     0.567426     0.001360     0.009790\n",
       "std       0.044255     1.224277     0.432739     0.035161     0.006406\n",
       "min      -0.420000    -4.490000     0.097030    -0.210000     0.002171\n",
       "25%      -0.020000    -3.220000     0.258750    -0.020000     0.006118\n",
       "50%       0.000000    -2.220000     0.444750     0.000000     0.008220\n",
       "75%       0.010000    -1.150000     0.717500     0.020000     0.011437\n",
       "max       0.250000     0.340000     4.170000     0.260000     0.058503"
      ]
     },
     "execution_count": 412,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 394,
   "metadata": {},
   "outputs": [],
   "source": [
    "M_daily = M.copy()\n",
    "M = M.shift(1)\n",
    "M = M.resample('1W').last().dropna()\n",
    "M.dropna(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 395,
   "metadata": {},
   "outputs": [],
   "source": [
    "def state_reg(system_losses,stock_losses,M,q):\n",
    "    \n",
    "    model_var = quantile_reg(stock_losses,M,q)\n",
    "    model_var_med = quantile_reg(stock_losses,M,0.5)\n",
    "    \n",
    "    X = model_var.fittedvalues\n",
    "    model_q = quantile_reg(system_losses,X,q)\n",
    "    \n",
    "    X2 = model_var_med.fittedvalues\n",
    "    model_q_med = quantile_reg(system_losses,X2,q)\n",
    "    \n",
    "    delta_covar = model_q.fittedvalues - model_q_med.fittedvalues\n",
    "    \n",
    "    return delta_covar,X\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 413,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LUMN\n",
      "VNT\n"
     ]
    }
   ],
   "source": [
    "delta_covar_dict = {}\n",
    "roll_var_dict = {}\n",
    "q = 0.99\n",
    "\n",
    "for sym in stock_data.keys():\n",
    "    \n",
    "    try:\n",
    "        delta_covar_dict[sym],roll_var_dict[sym] = state_reg(system_losses,stock_losses[sym],M,q)\n",
    "    except:\n",
    "        print(sym)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 427,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1822ffe7c48>"
      ]
     },
     "execution_count": 427,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,axs = plt.subplots(1,1,figsize = (15,6))\n",
    "axs.plot(delta_covar_dict['WELL'])\n",
    "axs.plot(roll_var_dict['WELL'])\n",
    "axs.set_title('Delta Covar and Var for WELL')\n",
    "axs.legend(['$\\Delta$CoVaR','VaR'])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.7"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": true,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}