007-efficient-frontier.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "54dfd1e9",
   "metadata": {},
   "source": [
    "# Efficient Frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5979d863",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "ind = pd.read_csv(\"data/ind30_m_vw_rets.csv\", header=0, index_col=0, parse_dates=True)/100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1ef77360",
   "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>Food</th>\n",
       "      <th>Beer</th>\n",
       "      <th>Smoke</th>\n",
       "      <th>Games</th>\n",
       "      <th>Books</th>\n",
       "      <th>Hshld</th>\n",
       "      <th>Clths</th>\n",
       "      <th>Hlth</th>\n",
       "      <th>Chems</th>\n",
       "      <th>Txtls</th>\n",
       "      <th>...</th>\n",
       "      <th>Telcm</th>\n",
       "      <th>Servs</th>\n",
       "      <th>BusEq</th>\n",
       "      <th>Paper</th>\n",
       "      <th>Trans</th>\n",
       "      <th>Whlsl</th>\n",
       "      <th>Rtail</th>\n",
       "      <th>Meals</th>\n",
       "      <th>Fin</th>\n",
       "      <th>Other</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>192607</th>\n",
       "      <td>0.0056</td>\n",
       "      <td>-0.0519</td>\n",
       "      <td>0.0129</td>\n",
       "      <td>0.0293</td>\n",
       "      <td>0.1097</td>\n",
       "      <td>-0.0048</td>\n",
       "      <td>0.0808</td>\n",
       "      <td>0.0177</td>\n",
       "      <td>0.0814</td>\n",
       "      <td>0.0039</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0083</td>\n",
       "      <td>0.0922</td>\n",
       "      <td>0.0206</td>\n",
       "      <td>0.0770</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>-0.2379</td>\n",
       "      <td>0.0007</td>\n",
       "      <td>0.0187</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.0520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192608</th>\n",
       "      <td>0.0259</td>\n",
       "      <td>0.2703</td>\n",
       "      <td>0.0650</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.1001</td>\n",
       "      <td>-0.0358</td>\n",
       "      <td>-0.0251</td>\n",
       "      <td>0.0425</td>\n",
       "      <td>0.0550</td>\n",
       "      <td>0.0814</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0217</td>\n",
       "      <td>0.0202</td>\n",
       "      <td>0.0439</td>\n",
       "      <td>-0.0238</td>\n",
       "      <td>0.0488</td>\n",
       "      <td>0.0539</td>\n",
       "      <td>-0.0075</td>\n",
       "      <td>-0.0013</td>\n",
       "      <td>0.0446</td>\n",
       "      <td>0.0676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192609</th>\n",
       "      <td>0.0116</td>\n",
       "      <td>0.0402</td>\n",
       "      <td>0.0126</td>\n",
       "      <td>0.0658</td>\n",
       "      <td>-0.0099</td>\n",
       "      <td>0.0073</td>\n",
       "      <td>-0.0051</td>\n",
       "      <td>0.0069</td>\n",
       "      <td>0.0533</td>\n",
       "      <td>0.0231</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0241</td>\n",
       "      <td>0.0225</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>-0.0554</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>-0.0787</td>\n",
       "      <td>0.0025</td>\n",
       "      <td>-0.0056</td>\n",
       "      <td>-0.0123</td>\n",
       "      <td>-0.0386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192610</th>\n",
       "      <td>-0.0306</td>\n",
       "      <td>-0.0331</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>-0.0476</td>\n",
       "      <td>0.0947</td>\n",
       "      <td>-0.0468</td>\n",
       "      <td>0.0012</td>\n",
       "      <td>-0.0057</td>\n",
       "      <td>-0.0476</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0011</td>\n",
       "      <td>-0.0200</td>\n",
       "      <td>-0.0109</td>\n",
       "      <td>-0.0508</td>\n",
       "      <td>-0.0264</td>\n",
       "      <td>-0.1538</td>\n",
       "      <td>-0.0220</td>\n",
       "      <td>-0.0411</td>\n",
       "      <td>-0.0516</td>\n",
       "      <td>-0.0849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192611</th>\n",
       "      <td>0.0635</td>\n",
       "      <td>0.0729</td>\n",
       "      <td>0.0455</td>\n",
       "      <td>0.0166</td>\n",
       "      <td>-0.0580</td>\n",
       "      <td>-0.0054</td>\n",
       "      <td>0.0187</td>\n",
       "      <td>0.0542</td>\n",
       "      <td>0.0520</td>\n",
       "      <td>0.0311</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0163</td>\n",
       "      <td>0.0377</td>\n",
       "      <td>0.0364</td>\n",
       "      <td>0.0384</td>\n",
       "      <td>0.0160</td>\n",
       "      <td>0.0467</td>\n",
       "      <td>0.0652</td>\n",
       "      <td>0.0433</td>\n",
       "      <td>0.0224</td>\n",
       "      <td>0.0400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Food    Beer    Smoke   Games   Books   Hshld   Clths   Hlth   \\\n",
       "192607  0.0056 -0.0519  0.0129  0.0293  0.1097 -0.0048  0.0808  0.0177   \n",
       "192608  0.0259  0.2703  0.0650  0.0055  0.1001 -0.0358 -0.0251  0.0425   \n",
       "192609  0.0116  0.0402  0.0126  0.0658 -0.0099  0.0073 -0.0051  0.0069   \n",
       "192610 -0.0306 -0.0331  0.0106 -0.0476  0.0947 -0.0468  0.0012 -0.0057   \n",
       "192611  0.0635  0.0729  0.0455  0.0166 -0.0580 -0.0054  0.0187  0.0542   \n",
       "\n",
       "         Chems   Txtls  ...   Telcm   Servs   BusEq   Paper   Trans   Whlsl  \\\n",
       "192607  0.0814  0.0039  ...  0.0083  0.0922  0.0206  0.0770  0.0193 -0.2379   \n",
       "192608  0.0550  0.0814  ...  0.0217  0.0202  0.0439 -0.0238  0.0488  0.0539   \n",
       "192609  0.0533  0.0231  ...  0.0241  0.0225  0.0019 -0.0554  0.0005 -0.0787   \n",
       "192610 -0.0476  0.0100  ... -0.0011 -0.0200 -0.0109 -0.0508 -0.0264 -0.1538   \n",
       "192611  0.0520  0.0311  ...  0.0163  0.0377  0.0364  0.0384  0.0160  0.0467   \n",
       "\n",
       "         Rtail   Meals   Fin     Other  \n",
       "192607  0.0007  0.0187  0.0037  0.0520  \n",
       "192608 -0.0075 -0.0013  0.0446  0.0676  \n",
       "192609  0.0025 -0.0056 -0.0123 -0.0386  \n",
       "192610 -0.0220 -0.0411 -0.0516 -0.0849  \n",
       "192611  0.0652  0.0433  0.0224  0.0400  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ind.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d35b8ea7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([192607, 192608, 192609, 192610, 192611, 192612, 192701, 192702,\n",
       "            192703, 192704,\n",
       "            ...\n",
       "            201803, 201804, 201805, 201806, 201807, 201808, 201809, 201810,\n",
       "            201811, 201812],\n",
       "           dtype='int64', length=1110)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ind.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "03dd97d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "ind.index = pd.to_datetime(ind.index, format='%Y%m').to_period('M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "da34e406",
   "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>Food</th>\n",
       "      <th>Beer</th>\n",
       "      <th>Smoke</th>\n",
       "      <th>Games</th>\n",
       "      <th>Books</th>\n",
       "      <th>Hshld</th>\n",
       "      <th>Clths</th>\n",
       "      <th>Hlth</th>\n",
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       "      <th>Txtls</th>\n",
       "      <th>...</th>\n",
       "      <th>Telcm</th>\n",
       "      <th>Servs</th>\n",
       "      <th>BusEq</th>\n",
       "      <th>Paper</th>\n",
       "      <th>Trans</th>\n",
       "      <th>Whlsl</th>\n",
       "      <th>Rtail</th>\n",
       "      <th>Meals</th>\n",
       "      <th>Fin</th>\n",
       "      <th>Other</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1926-07</th>\n",
       "      <td>0.0056</td>\n",
       "      <td>-0.0519</td>\n",
       "      <td>0.0129</td>\n",
       "      <td>0.0293</td>\n",
       "      <td>0.1097</td>\n",
       "      <td>-0.0048</td>\n",
       "      <td>0.0808</td>\n",
       "      <td>0.0177</td>\n",
       "      <td>0.0814</td>\n",
       "      <td>0.0039</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0083</td>\n",
       "      <td>0.0922</td>\n",
       "      <td>0.0206</td>\n",
       "      <td>0.0770</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>-0.2379</td>\n",
       "      <td>0.0007</td>\n",
       "      <td>0.0187</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.0520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1926-08</th>\n",
       "      <td>0.0259</td>\n",
       "      <td>0.2703</td>\n",
       "      <td>0.0650</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.1001</td>\n",
       "      <td>-0.0358</td>\n",
       "      <td>-0.0251</td>\n",
       "      <td>0.0425</td>\n",
       "      <td>0.0550</td>\n",
       "      <td>0.0814</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0217</td>\n",
       "      <td>0.0202</td>\n",
       "      <td>0.0439</td>\n",
       "      <td>-0.0238</td>\n",
       "      <td>0.0488</td>\n",
       "      <td>0.0539</td>\n",
       "      <td>-0.0075</td>\n",
       "      <td>-0.0013</td>\n",
       "      <td>0.0446</td>\n",
       "      <td>0.0676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1926-09</th>\n",
       "      <td>0.0116</td>\n",
       "      <td>0.0402</td>\n",
       "      <td>0.0126</td>\n",
       "      <td>0.0658</td>\n",
       "      <td>-0.0099</td>\n",
       "      <td>0.0073</td>\n",
       "      <td>-0.0051</td>\n",
       "      <td>0.0069</td>\n",
       "      <td>0.0533</td>\n",
       "      <td>0.0231</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0241</td>\n",
       "      <td>0.0225</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>-0.0554</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>-0.0787</td>\n",
       "      <td>0.0025</td>\n",
       "      <td>-0.0056</td>\n",
       "      <td>-0.0123</td>\n",
       "      <td>-0.0386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1926-10</th>\n",
       "      <td>-0.0306</td>\n",
       "      <td>-0.0331</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>-0.0476</td>\n",
       "      <td>0.0947</td>\n",
       "      <td>-0.0468</td>\n",
       "      <td>0.0012</td>\n",
       "      <td>-0.0057</td>\n",
       "      <td>-0.0476</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0011</td>\n",
       "      <td>-0.0200</td>\n",
       "      <td>-0.0109</td>\n",
       "      <td>-0.0508</td>\n",
       "      <td>-0.0264</td>\n",
       "      <td>-0.1538</td>\n",
       "      <td>-0.0220</td>\n",
       "      <td>-0.0411</td>\n",
       "      <td>-0.0516</td>\n",
       "      <td>-0.0849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1926-11</th>\n",
       "      <td>0.0635</td>\n",
       "      <td>0.0729</td>\n",
       "      <td>0.0455</td>\n",
       "      <td>0.0166</td>\n",
       "      <td>-0.0580</td>\n",
       "      <td>-0.0054</td>\n",
       "      <td>0.0187</td>\n",
       "      <td>0.0542</td>\n",
       "      <td>0.0520</td>\n",
       "      <td>0.0311</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0163</td>\n",
       "      <td>0.0377</td>\n",
       "      <td>0.0364</td>\n",
       "      <td>0.0384</td>\n",
       "      <td>0.0160</td>\n",
       "      <td>0.0467</td>\n",
       "      <td>0.0652</td>\n",
       "      <td>0.0433</td>\n",
       "      <td>0.0224</td>\n",
       "      <td>0.0400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Food    Beer    Smoke   Games   Books   Hshld   Clths   Hlth   \\\n",
       "1926-07  0.0056 -0.0519  0.0129  0.0293  0.1097 -0.0048  0.0808  0.0177   \n",
       "1926-08  0.0259  0.2703  0.0650  0.0055  0.1001 -0.0358 -0.0251  0.0425   \n",
       "1926-09  0.0116  0.0402  0.0126  0.0658 -0.0099  0.0073 -0.0051  0.0069   \n",
       "1926-10 -0.0306 -0.0331  0.0106 -0.0476  0.0947 -0.0468  0.0012 -0.0057   \n",
       "1926-11  0.0635  0.0729  0.0455  0.0166 -0.0580 -0.0054  0.0187  0.0542   \n",
       "\n",
       "          Chems   Txtls  ...   Telcm   Servs   BusEq   Paper   Trans   Whlsl  \\\n",
       "1926-07  0.0814  0.0039  ...  0.0083  0.0922  0.0206  0.0770  0.0193 -0.2379   \n",
       "1926-08  0.0550  0.0814  ...  0.0217  0.0202  0.0439 -0.0238  0.0488  0.0539   \n",
       "1926-09  0.0533  0.0231  ...  0.0241  0.0225  0.0019 -0.0554  0.0005 -0.0787   \n",
       "1926-10 -0.0476  0.0100  ... -0.0011 -0.0200 -0.0109 -0.0508 -0.0264 -0.1538   \n",
       "1926-11  0.0520  0.0311  ...  0.0163  0.0377  0.0364  0.0384  0.0160  0.0467   \n",
       "\n",
       "          Rtail   Meals   Fin     Other  \n",
       "1926-07  0.0007  0.0187  0.0037  0.0520  \n",
       "1926-08 -0.0075 -0.0013  0.0446  0.0676  \n",
       "1926-09  0.0025 -0.0056 -0.0123 -0.0386  \n",
       "1926-10 -0.0220 -0.0411 -0.0516 -0.0849  \n",
       "1926-11  0.0652  0.0433  0.0224  0.0400  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ind.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8c0ddae2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Food ', 'Beer ', 'Smoke', 'Games', 'Books', 'Hshld', 'Clths', 'Hlth ',\n",
       "       'Chems', 'Txtls', 'Cnstr', 'Steel', 'FabPr', 'ElcEq', 'Autos', 'Carry',\n",
       "       'Mines', 'Coal ', 'Oil  ', 'Util ', 'Telcm', 'Servs', 'BusEq', 'Paper',\n",
       "       'Trans', 'Whlsl', 'Rtail', 'Meals', 'Fin  ', 'Other'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ind.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3ed70010",
   "metadata": {},
   "outputs": [],
   "source": [
    "ind.columns = ind.columns.str.strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f7d7fca9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Food', 'Beer', 'Smoke', 'Games', 'Books', 'Hshld', 'Clths', 'Hlth',\n",
       "       'Chems', 'Txtls', 'Cnstr', 'Steel', 'FabPr', 'ElcEq', 'Autos', 'Carry',\n",
       "       'Mines', 'Coal', 'Oil', 'Util', 'Telcm', 'Servs', 'BusEq', 'Paper',\n",
       "       'Trans', 'Whlsl', 'Rtail', 'Meals', 'Fin', 'Other'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ind.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e187c192",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1110, 30)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ind.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "38d86833",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ec5f72c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import edhec_risk_kit as erk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "be968c92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1110, 30)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ind = erk.get_ind_returns()\n",
    "ind.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "25ec1cdc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "erk.drawdown(ind['Food'])[\"Drawdown\"].plot.line(figsize=(12, 6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "63cf5d58",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Food     0.061207\n",
       "Smoke    0.080292\n",
       "Coal     0.047359\n",
       "Beer     0.033881\n",
       "Fin      0.075199\n",
       "dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols_of_interest = [\"Food\", \"Smoke\", \"Coal\", \"Beer\", \"Fin\"]\n",
    "erk.var_gaussian(ind[cols_of_interest], modified=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ab5c693f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Carry    0.094527\n",
       "Meals    0.098403\n",
       "BusEq    0.099377\n",
       "Games    0.100701\n",
       "Mines    0.102782\n",
       "dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "erk.var_gaussian(ind, modified=True).sort_values().tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2c183150",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Beer     0.033881\n",
       "Coal     0.047359\n",
       "Food     0.061207\n",
       "Telcm    0.064719\n",
       "Hshld    0.064886\n",
       "dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "erk.var_gaussian(ind, modified=True).sort_values().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "329261c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "erk.var_gaussian(ind, modified=True).sort_values().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1a61a0ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Industry Sharpe Ratios 1926-2018'}>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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GFbp5RLGSNmbhYZOLMcZ0BCt0Y4zpCFboxhjTEazQjTGmI1ihG2NMR7BCN8aYjmCFbowxHcEK3RhjOoIVujHGdAQrdGOM6QhW6MYY0xGs0I0xpiNYoRtjTEewQjfGmI5ghW6MMR3B86GbBcZznBszPbBCN+OoU9BgJW3MdMcmF2OM6QhW6MYY0xGs0I0xpiNYoRtjTEewQjfGmI7gKJdHCY5cMab7uIVujDEdwQrdGGM6ghW6McZ0hFYKXdI2kq6UdJWkD9Vs31XSRWU5Q9JGk19UY4wxgxiq0CXNAA4GtgU2BHaWtGGf2DXA1hHxTGA/4NDJLqgxxpjBtGmhbwZcFRFXR8R9wFHA9lWBiDgjIm4tq2cBa0xuMY0xxgyjjUJfHbiusj63pDXxFuDkug2S9pA0R9KcefPmtS+lMcaYobRR6HUBzLXBy5JeQCr0D9Ztj4hDI2J2RMyeNWtW+1IaY4wZSpuBRXOBNSvrawA39AtJeibwLWDbiLh5cor36GOUAUAeLGSMqdJGoZ8DrCdpXeB6YCdgl6qApLWA44DdIuKPk17KRRx/AMIY80gwVKFHxAOS9gJ+AcwADo+ISyXtWbYfAnwMWBX4H0kAD0TE7IVXbGOMMf20msslIk4CTupLO6Ty/63AWye3aMYYY0bBI0WNMaYjWKEbY0xHsEI3xpiOYIVujDEdwR+4mCAORTTGTDfcQjfGmI5ghW6MMR3BCt0YYzqCFboxxnQEK3RjjOkIVujGGNMRrNCNMaYjOA694LnFjTGLOm6hG2NMR7BCN8aYjmCFbowxHcEK3RhjOoIVujHGdAQrdGOM6QhW6MYY0xE6HYfu2HJjzKMJt9CNMaYjWKEbY0xHsEI3xpiOYIVujDEdwQrdGGM6ghW6McZ0BCt0Y4zpCItcHLpjy40xph630I0xpiNYoRtjTEewQjfGmI5ghW6MMR3BCt0YYzqCFboxxnQEK3RjjOkIrRS6pG0kXSnpKkkfqtm+gaQzJf1L0vsmv5jGGGOGMXRgkaQZwMHAS4C5wDmSToiIyypitwDvAl65MAppjDFmOG1a6JsBV0XE1RFxH3AUsH1VICL+ERHnAPcvhDIaY4xpQRuFvjpwXWV9bkkbGUl7SJojac68efMmkoUxxpgG2ij0uslTJjRxSkQcGhGzI2L2rFmzJpKFMcaYBtoo9LnAmpX1NYAbFk5xjDHGTJQ2Cv0cYD1J60paEtgJOGHhFssYY8yoDI1yiYgHJO0F/AKYARweEZdK2rNsP0TS44A5wArAQ5L2ATaMiNsXXtGNMcZUaTUfekScBJzUl3ZI5f+NpCnGGGPMFOGRosYY0xGs0I0xpiNMi0/Q+bNyxhiz4LiFbowxHcEK3RhjOoIVujHGdAQrdGOM6QhW6MYY0xGs0I0xpiNYoRtjTEewQjfGmI5ghW6MMR3BCt0YYzqCFboxxnQEK3RjjOkIVujGGNMRrNCNMaYjWKEbY0xHsEI3xpiOYIVujDEdwQrdGGM6ghW6McZ0BCt0Y4zpCFboxhjTEazQjTGmI1ihG2NMR7BCN8aYjmCFbowxHcEK3RhjOoIVujHGdAQrdGOM6QhW6MYY0xGs0I0xpiNYoRtjTEewQjfGmI5ghW6MMR3BCt0YYzpCK4UuaRtJV0q6StKHarZL0gFl+0WSNpn8ohpjjBnEUIUuaQZwMLAtsCGws6QN+8S2BdYryx7A1ye5nMYYY4bQpoW+GXBVRFwdEfcBRwHb98lsD3w3krOAlSQ9fpLLaowxZgCKiMEC0quBbSLirWV9N+A5EbFXReZE4HMR8buy/ivggxExpy+vPcgWPMBTgCtrDjkTuKll+Rc12elSjukgO13KMR1kp0s5FjXZ6VKOR1p27YiYVbtHRAxcgNcA36qs7wYc2CfzM2DLyvqvgGcPy7vheHO6KjtdyjEdZKdLOaaD7HQpx6ImO13KMR1ke0sbk8tcYM3K+hrADROQMcYYsxBpo9DPAdaTtK6kJYGdgBP6ZE4Adi/RLpsDt0XE3ya5rMYYYwaw+DCBiHhA0l7AL4AZwOERcamkPcv2Q4CTgJcDVwF3A29agDId2mHZ6VKO6SA7XcoxHWSnSzkWNdnpUo7pIAu0cIoaY4xZNPBIUWOM6QhW6MYY0xGs0I0xpiNYoQOSFpP03KkuxyhIWlbSYuX/+pJeIWmJBtl3S1qhRCEdJuk8SS+dhDLMkPSeEeQndJ3LfiuMup+Z/izMZ6/U9zWHS4KklSS9S9KXy7xUB0g6YGGUa2GyyDhFJb1q0PaIOG4UuZr8z4yILVqW5TXAzyPiDkn/DWwCfCoizmuQXxa4JyIekrQ+sAFwckTcPxG5Insu8DxgZeAsYA5wd0TsWiN7YURsJOllwDuBjwJHRMS4SdQkvRs4ArgD+BbwLOBDEXFKw7mdFhHPr9vWIN/qOkv6AbAn8CBwLrAi8OWI+OKAfZ4LrEMleisivlsjtz95/pe2KEfr+tSmXkhaZUh+t/Qd/71D5L9c5A4EGh/miHhXXbqkJwFzI+Jfkp4PPJOcxuOfNbIDJ93rO8/Wz8gIdeKnDD7HV9Tsc25EPLtF3meQz9HFwEOVPL/TIL8+8H5gbcbWtxfWyK4GfAZ4QkRsW+bC2iIiDqvIXDzk3J457BygRdjiwkLSHdSfgICIiP4W2XYDsgvguBHl+jlF0o7AcTH8LffRiDhG0pbAy4D9yQnJntMgfzrwPEkrk6No5wCvA/qVb1s5yJfx3ZLeQo7c/YKk8xuOr/L7clKRXShJDbJvjoivFeU/iwxBPQKoVejA7yUdBPwvcFcvsenlRvvrvGFE3C5pVzIs9oOkYq9V6JKOBJ4EXEC+BCDv9ziFDlwBHCpp8XJuP4yI2xrK8RbgucCvy/oLgNOA2xhfn9rUi3PLfnXXP4An9qUtX36fAmzK/DEg25H1pceYaTZG4FhgtqQnA4eV/H9A1pV+/odUzBeR5X8GcDZwfyl7VZmN8oy0rRP7j3JihbMkbRoR5wyRWzoiBr48+zgGOAT4JvPrWxPfJuvZR8r6H8nn5bCKzH+U33eW3yPL765kKHg7Rh1a2tWFbJE+RFbO28v67Q2y55ffzwK7VNMa5M8rv3sDH2iSbyvXSwe2IFsVTytpFzfI9hTyn4DHkEri3AbZi8rv14AdWpzbqTXLr1tc5/sGXWfgUmAJ8sHZuqRdOCDfyyk9zhHu+VOAzwHXkkrsBTUyJwKPr6w/nlQ8C1wvRizrKcDylfXlyRbwgubbq3PvB/YeUueOAp5RWX868O0FvRajPHsTOL/LSIX7Z/JFdHGvjvfJvQd4W7m/q/SWAfnWPj8Nsuf0nz9wQYPs79ukNS1T1kLvR9JjgaV76xHx1wa5od2XIlc1HXyTbFk0mg4iYvm69Aaul/QN4MXA5yUtxWB/hCRtQb5t31LS6q59WzmAfYAPA8dHDvR6IqlM63gLsDFwdWSrflWaB3+dK+kUYF3gw5KWp9IFrcs7Iq7uO4n+VubDjHCdvwH8BbgQOF3S2uTD3sQlwOOAViOUy7TQG5TlpnKc90p6e0TsVBFdJ8aOev47sH5DtkPrhaQNIuKKJvNFNPds1iJfgj3uI81LvXy/GhH7NJklosYcUbhf0s7AG5jfu631xQAbRMTFlTwvkbRxg2zrZ6RtnZB0dES8tsk8EfVmiW3b5E1ezy+Srehe3uN6TBWT2U8lvQM4HvhXpQxjTGaFu8ozFyWPzckeXh3LStoy5k90+Fxg2ZbnMPUtdOAVZMvxLuAaUnlcOkD+ZOC1lNYaqfDGtUwr219GdiM3orRGGvIV8Hqyqwg5N81mDbKPAV4FrFfWHw+8dEDeW5UyfLCsPxE4oEZu6zZyE7zOq5Omg616S4PcYuTLb6WyvirwzAH5jrum1LReyLnyf0Iq3h8Aqw8p74ya+7P4APlTgVvJEc0n9JYG2S+XOveN/nsMXNm3flDJ842k0juZvsnpRqkXwKGV8o7Ss/kI+dL5OLAvaVr6r8r2Z5ffbcke3juBbUqd2npAvhsCBwA7l/V1yYZPnewPSb/K80u+3yTNVQv0jNDy2aP0lEi79bhlwDluCbyp/J8FrFsj82dgZovn6Brg6vLbv1zdsM8mwO9JJf570uRS+0wBzy73+S9luQDYZFi5esuUO0UlXUja3v4vIp4l6QVk5dqjQf6ciNhU0vkR8aySdkFEbNwnd1FEPFPS14DTIuL46j41+X6dfJm8MCKeWuzYp0TEpg3yW5KV9QhJs4DlIuKaBtl1IuIvfWmNdj1Jy0bEXQ3bJuIY+jxpi+91P4tofatN0itIpQ/wm4j4aY3MBsDTgC+Q3fUeKwDvj4in9cn/lrRnn06+xLeIiEaHo6S/Aj8nbY2/jiEVVdLWdekR8Zs+OQH/DXwpIsbZJiWtGH32dEk7MP96nB4Rxw8oxwxgNcY6ysb1NiUtHRH3Dkvr274J6QjvleP8yrYlgE8Dbwb+SirJNUj77X9FjWN9VCQtDfwnlWsBfL2pzOUZWpOx16LOKTrSszdimfcFZgNPiYj1JT0BOCYi/q1P7gRgp7o60ZBv6/snaR1yAsOnkPflSmDjpue/7LMCaUJsasnX01bzL6yFMkUk+VZarPw/e4D8aWSrsWf725xUOv1yR9DSblzke/mdX0mrtdmSLaSfAn8s609ggJ2LdIStXlnfmvpexRak0v1rWd8I+J8+ma0HLQ3HvxJYquX9+BzpkH1zWX4JfLZGbvtyjW8uv73lAOC5NfIX1F3vAeVYhuyJHUe2VA6iMkXzAta5ofZP0rzQ+79U37bNG/bZmzTfXEraamvttU3n35C2yqClIvcVsvVctbOvQM4H8tWafC8mbcq1S5/sCgOu01oN6fsB15HP68AeyCjPXu/6k5MG3kmaSh6k2d91AalEq3nX2dCPJ1vO3yh1+AAG9I7b3r9efWPs878Vzf6uFcke5JyyfAlYsXXdXpAHYzIW4P+A5coD+0PSGXfGAPlW3RdGNx38gZx8rFe5ZtHsxGlVSSrbNi0V8HFk9MAFwJoNZVizL99LGvJ8d5u0kn4y2YNocz8uorxYy/qMIee2Rct8ryBDIDcpy+XV9SH7rky27h+s2fa78nsHaWPvLYOc2gcDmw455nl1/+vWK+lXAasOyfdxZLf68sq12IQ0Y1xRI9/fxb+6sn51Re5P1DiFy/37U0362oOWAdfiVy2vxZXAki3rRutnr2yfAzyZDAyYQfqDPt0ge3a1nKQ9uk6hv6FuGXL/qvW59v6VfVo9/0X2WOATpLn1iWTjsdYJX7dMB6fo9sC9pJNvV/IN9ckm4Yg4r3SvH+6+RKU7WeNsemJzhN4YDiDf0o+V9Gng1WTXvI77IiIkRTnmQKdFRJwj6V1kj+Fe4CURMa9B9rq+8jaFRL2BfPlVeWNNGmTY0wXKL0lVHTi1scnASkDPubNig0yPHSRdCtxDmkg2AvaJiO/1yf2NbHn0uLGyHowNeQMeNqO8jrQLn0O22PvZtZzLKE7tFwBvl3Qt6bvphcpWnWpq+F+33uM6mp1dPV5G3qc1GBuGdwfwX/3CEbHukPwqoqkR+hIf7NXTvvRrW+YLY8+3P46+6VpcQtajf7TIv/fsrdbi2QMgIq6SNCMiHgSOKHHkdRxdnLMrSXob2ev8Zo3cj4B7S34909lSNXLV+1etz7X3r5S19fMPPCkidqysf0LSBQ2y45hyhR4Rd5XIlU3J7vvJEXFzk7ykxwDvJVsRb5O0nqSnRMSJReRLgw5HjeIo5fi+crDOi8hK+sqIuLwhn1aVpMbe/RjygT9MEjHehn1d8WqHcu75d5EtgWqeOwO7AOsWu1+P5cnrV0fPSdiGzwLnSzqVvA5b0VBRCy+NiA8UO/Nc8gtXpwJjFHpEvKDl8QGQdA3ZkjmatMnX+hRIRbBJ2efYvoehLl+RA5aGKbRo+D9uXfMH/1wNnCbpZ4x9cVYf/JlkKGSvvgYwj+xpXDOk7KszfiBLLxb9Mkm7R99AKkmvJ3tHTXluDhwIPBVYkmzx3hVjx4G0vhYVevXoEsZei3F+mxGfPYC7y/NxgaQvkI2F2kZVROwv6SVkr2194GMR8csa0V+RETl3lvVlSAU8ZhRr5ECj70jaMSKOHVDGiTz/APf0Rbn8G9lYasWUK3RJryXDhU4jb+aBkt4fET9q2OUI0ibVG1k2l4xVPhFGVxx9/Im88YuXsq0VNQ6tvkryFJoryagDIfYkW9irk+d1CvMHGvQ4g6zAMxn78rqDNJeMIxpGuzXI/lDSaeQLVmTEzY0DdumFuL2cjHi4ZVCPqDjW3kFGHgTwW+CQqDiTSuvoiIho7KlVs6z8bwyX7FF6Vl+J4aMH11AO/Vblf+94q/fJ9noHfy3LkmWB8QpvuZpjrQ18RNLHI+KousI0ObaZP7joncBxkt7M/MFLm5KKaYcB53kQ+dGaY0jn4e6kOaPKY8tLS5X/lPX6b1vCd4DP0zfycgAzyZHOR0iaJWndAS+43UiT6l5k/PiaZERNExeT1yHK/zqWjoieMici7iyNxzFUzr12FG/fy3siA6H+k3xhrEhe31vI3ngrpkuUy0si4h9lfRYZ8bJRg/yciJjdF+VyYZ28Wg4FL7J7k/aqv5MPTF03fMJUeiGQdr02XdFB+W0YEZf1pT0/Ik6rkV2PbDFtyNhY/3EKUNKvIuJFw9Iq2z4HvJJsRWxGdrNPjIjaUbOSjiZfPr0W/M7AyhHxmj65U9u8nCWdF2UKg+r/IfscTA6IGRRlMPAhqntJSnpNRBwzLK3heKuQ9b62/JKuJH1A/6rbXpF7IRl9JDL891dD5HvP00W9ui7pjIh4bkVm30F5RMQnavL9TURsPWi/vvyHRqJU5N8dEV8bllbS3wp8jBzpKzJ44JMRcXif3O/JgVXnlfVnAwdF35QEE7kWZb+Rnv8S5UJEDBp7UVuAKV3o8/aSb95aD3DZfgb5tu05OZ5ETVQMOXT2DHK48oFlGeS1HurQqsi+imzN30aLkW2k7fdastXyXdKh9eoauXVJu9xxDI+lvgT4AFlJlynnd2aD7O/I7uxFZGvw48An+mSWJu2jF5JOyF4kxTrA5UOux8qUuHGyW/m4AbLjohca0j5Nth6fR8V5WCP3YOUePEA7p+hlRXbg6MEJ1OXWkQ8N+58/YFtrx/aIZT6d7E18lwxBfU/d/ZhAvl8mGxFbDLp/RfYCRgsyqLvOtdeOdM6uWllflb6xBiV901IffluWq5jgh+5r8m71/BfZFVmAKJcpN7kAP5f0CzLCBbJbedIA+Y+Tzrc1JX0f+DfqRz3OJucDadsFaePQ6vEFYLsYbOer8hEyqmJML4R0xFT5MTm/w08Z3k19DtmlPYPs8veuRR3LRMSvJCnSGfZxZVx4tbXxdtIx/QSgGit8OxkVMoinAuso50bpUdsTIu2qm0fEWQCSnkNGK/XTayFWzS7jfCARMWNI2epoO3oQSb8EXhNlsipljPRREfGyisy2pMlpdY2doW8F8sXR5jgvJAdG9af3Jt0a1bHdljrzRa0fotirP8VwBzhkBAhkiOHDxaXeh9UqyGCC/qO55Mu9xx3ksz6GSMflBswPtrgi6ifFO6A/rS+fuvvR9vkHOJxsrPUCAHYjzcyDTEoPM5WTcz0ZWC0i3q+c0W5L8kKeSSqnWiLilOJA2bzIvzsibqoRbTUUfESHVo+/j6DMIcMAq12sm6kfBn1vRAysMBXuJx+sZcjW9TUR0fQSuFc51e6flN+HvR54bFUgsrv6NUl7R8SBLcuAWk6KpfnDtZcgPyj+17K+NtliHkMsmC9kIOWlhvqmm2hgVlRmHoyIW8t+VW4g7davKL897iCV5MOoftj6KiWP3WuO35t061zaO7ZbExHXSlqGHIVZay6o0MoBXvId5f61jUQZ2X9E1vU/SPoJed23B86uPPd/adhvveK47J/Mr3p/P8HYRlETbZ9/WMAolymzoUs6kRzBdlFf+mxg34ionTVxmI234llenpy/5GwGeNmH2MQiahxzytGnjyNb1NW8m6bm/SI5LWm1F3JRRHywT24Xcoj8KX35VqclXTzyw90XkkPp9yO7kd8A7o+IV9ccf1MyWmalIr8C8MVeK7lPtk6pEM2+h8tp0RNSzsXSSPSF0anlnD0TQTkS9ktkb+Qf5Evl8ugb3VpkzyUnKftr5TyOj/qphxePiIEt8prrEMDN0RzFU5fHymQcc5MSa42k7Ujn3ZIRsa5ybpZP9j8nRfbSiHiapG8Cx0bEzwf4r0a6f8ogg5eSjbRfRH2QQdM5zCBHeY5rCA6zeVOZD6eGiIg3Dzju+dEw8rxPru75vzgiPlAjeyYZ1VWNctk/2k7tPYUK/ZKIeHrDtosj4hl9aUuT9tlTySD+XnTDCmSo41OL3HvInsf5ZCt2DNE3FLySf2uHlqQjarIYdvOrvZDa4eOSPkt2sf7MfJNLRGWO5Z7jT9LsiJjTt/9uEXFkX9oM4HMRUR2e30jp4vdYmrS9n1f3oijyxwDvirETWLU5zsDJ2CSdTJlyNHIu98VJO+kzWEA0wnQTkrYhR1v26s1WwB4R8YuKzKTMZT2kzKeRPYDFyd7QPHKE9LhIixHzPZe8FqfF/CCDi+rKrBEc4BO9f5Jmki+4cdezOArfSUYZnUCOYn4nOfXEBRGxfdvzngzU0glfZHckTaKNz3+R24js3fbGf9xKDnBq9/KOEQ38k7UAV42yDXg36Uz4F/NHy11NOvH2qsjtT3bNbiVDIT8D/DsDpsKMZkdLa4dWi/NdjZzN7j+AxzbIXMGQ0XWMMB0rZTIriod/guVekQbHbNl+Ki0nxSryrSZjY4QpRydwTqNONzGz3LftqJnAiexVbcn4EZdbAU+epDKfX37fSnFoMzmO3D/UXOdBDslWDvA29480m55GBgE8izST3kj2mrapyfMn5Nw0byfHJ/ySfNFuPKC8s8iw6JPKc/BraqYgKM/nYWTjEDIi7C1Drt1I+oFsfPaCDVbp27ZWjWzjlAtNy1Q6Rc+R9LaIGGMrU36w4dwa+TPIm/jqiDhQGVa2I2kD+0FPKCLeV/JZknSMPpdik5P0z4jYsO94rR1akj4Q+SGJnqNqDNH8VZi2sfYXMnx03SwN+IpNjLX5n01GF5wP/KS0pqsfoWj62EeVu6mZLrbnAyGd1FW2Ju2WTexHPshjWsc1cqNMOToq/5S0HBnh8X1J/2D8ve5ved1QftdSjk+oOo6/QpoP+81Gs8q2QR9dacvikh5POss+Mkx4BC4ppr4ZyvDWd5HP2jiq5jiNHWtQZ45rc/8OIgetrUgq2m0j4iylc/KHpOO1yhOjtPAlfYucN2etiLiDZr5PTvD2H+Q4jzeQvZt+vs3wj1CgsR/meYykXlhhL8y5/8M8SHo76dy/h2zAiPFT8/6YEQbINTGVCn0f4HjlF2l6Cnw2GUJVNxDiG8CLizLfigyJ2pu0kx9KDheusgyplFcsyw3UDyq4gXQ8vYa8iUE69/5On0OL+aM2R/06TFsv92rAFZLOodnuP4McnNJqPoPCKqQj5oXw8NdygpqvN2ns6LYZZATL0TV5fpV6H8hdpKOoydZ9f0TcrPyW5GIRcapy0Ew/7yVb+09SxgjPYvw9HonKS2h78uF6Dzl1wNpkXaoyyojjdfqvA0BEzFHOtDcZfJLsBf0uMiLjiWRPZ0HZm6yf/yKV6C/Il24d1dkPHzbHUa/Q29y/xaN8n0DSJ6P4dCLni687/sMm1MgpDa4ZoswhQxYPU8ap/wb4jaSHza4Vv8fMiDha0odL/g9IGjftRow2xUSP95EfoakL3ni4KJX/QwfINTFlCj0i/g48t7TQerb0n0XErxt2mRHzJ49/HTmv9LHAsap4gSUdSg6suIOc9OcM8luU40LCCpeRD/WSZEteZOjWEcwfnt0r80/Lb+uRl4W2Xu42HvO/RbsRlDB/VN8lzFfkPZpsvtXRbQ+Ufepa0BNVYgNbx8WBe13Mn7Pn7WRP7BQysmJB+Cr5Eur1Uh4iR+XNJnsaD7ekY7QojUGRMsuMWMZaIn05x1TWr6YhvHDEfO8mFfrQVn9EjHnpKUczHtkgO3DOpUI1Kqt/eHtd/dyor0W8TFlvbB0z/yXwN0n/Tjbg1qhs7/ViF2aP8M8M/4xcNPwfiSmPQ4+IU2n+0k6VGZW36YuAqgOreh5rkZPq/Ins+s8F/jkg3y+QLd61e2/74nzZvyzv7glqbOxr3bk0fRWmVax9NDhs+xilZT6oNV9baSLiN8pIh13I7v015Axw/YykxDR/GoX+1vGKjI01733lBtJc9hEG98RGofVLqGdeK//HOMclfSYiqvPbjGo+bE2Tea9S9gnFoS9AXa5yN+k/aGIz5o/U3kQZBlhtzW9UUcjL9CnrcfUrJjbm4FPlxfP/yMF3KzC25917Nia9R1jhw8AZkv5A8xiCQdei6WU1jikf+t8WSR8hbd03kUp7k4iI0o3+TlSGCSv7a08jFcJzyR7ALeRIyn378v0TsH70XYgSHXJFRKxXSZtHDkr4Idn6H6MoBylktYtyGTpRkqRVov4zV3XHHMULvz45p8fOZA/if4H3RURtuKGkH5LOpTol9tKIeF1TWQbZCFUJg1MO0Z8XER8v6xdE34dMRkHSVRHRP09J7TYNmFKgZn01cpKw+6gxH8bguXCGlfkNldVxcc8T6C328h25LveZ4xYjHYdHR8SHamRrxydM9AU0KsqouD3JeWkuBg6LmpBSSXOZP2viYmRjUKTifTDqx6GMWpazydHaY+a1mei9G8SUt9DbEhGfVo6Sezz5NZNqxdq7TzZIZ88/yW7TbaRTZDPGmzWiX5mXxLppRx8HvIRUersAPyMnpLq0RfmPIydPmknzqLa6iZLGtIDaKvPCKK35K8ghz9tFxFXwcAhoE/swmg+krY2wbU9sIozSklbD/3HrEzAftqb60EvaZxKVwETqcr857tqIaDKDjTpSe7L5Dmlu+S05MnhDKr3tCk292HETcy0AD8QChpe2JiYhpGo6LaSX/iiy9XE1aeN7BzlMebEa+R8Du9ekv57B4XdLkfMiz6N8Lb1GZtSwrF443UWVtMaPfbS4FgNDNftkdyBb5deRo/ReRI4+HbbfC8gX6t7kJ8Sa5Bo/GNEn9xFyKoCfkNE5vV7kkxnh6+cNea9G+lROI52eXyLD3s6kL/xuUHkHlX8h1+2Fctw2dblmn5m9e9Ow/RjKN0Cn6FpdXPm/eNO1eyTuJTkv0R5kY7Q2bHGylkXG5NIWSV8mH9rfR4vBLso5po8j7brjph2NiOv75Jci49p3Ju2DJwCH98sV2TnMD8s6lL6wrOgbZSbpdNJ+fBg5xPlvwBujYebJhYFyHo1Xkuf3QrKlc3yUaIQFyPdB5n9MYhnmO4nG2QiL6anXE7urpK1PTk417puUEyhLtSV9adS0pIeUd+mIWKJ/n4XNKCa0lvm1qsvlfnyONFvuRzaSZpK9490j4ucV2ZFGai8shpnJKunn9z+HC6Es15S/Y5Rt1Mx2usDH6ppCnyhqMe2opO+QiuBkcoKmS4bkeUEUm6+ky6OMZi3r4yqSclj430mzxXtIB87Xo5hAHmmUU7q+BnhdVEarmkcO9cU9M+BFOGK+revyKA0T5Vwsq5GmjipbA9fHJEzd0IbKCxnGvpTHXLdRfFITKEMvYuvGsl4dO/PxhXFcK/QRkPQQ8ytJ9cLVPlxtHWuStgfWiIiDy/ofyMmzAvhANH/sw5gJMUpdHqVhognO0dRFJJ1Hjp25RTl25ijmR2w9NRqm01gQFhmn6HQgIppmSGuibVjWB0hnaI+lyA/RLkfGw1uhm0llxLo8Srz4Ov3KvBxvMgdZLSq0GjszmVihL0SifdzskhFRnaP5d6Ui3KIhH6A25hFglHjxhT7IahFiYUZs1WKFPj1YuboSEXtVVpu+2WjMI8IIDRNYiIOsFkF+SE41cBPZs/kt0JuCYrJGoY7BNvRpgPLLS6fVPARvB54fEXVD742ZdizMQVaLIgs7Ymvc8azQpx7l3OA/JsO7ejf52aQt/ZWRA1eMWWRoExpqJh8r9GlEJXQS/BAYY0bECt0YYzrCqGF4xhhjpilW6MYY0xGs0I0xpiNYoRtjTEf4/4w3f65XGhHuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "erk.sharpe_ratio(ind, 0.03, 12).sort_values().plot.bar(title='Industry Sharpe Ratios 1926-2018', color='green')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "22b2c093",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Industry Sharpe Ratios 2000-2018'}>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "erk.sharpe_ratio(ind['2000':], 0.03, 12).sort_values().plot.bar(title='Industry Sharpe Ratios 2000-2018', figsize=(12,5), color='goldenrod')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "da911831",
   "metadata": {},
   "outputs": [],
   "source": [
    "er = erk.annualize_rets(ind[\"1995\":\"2000\"], 12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "bcd0fd23",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "er.sort_values().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "dc472919",
   "metadata": {},
   "outputs": [],
   "source": [
    "cov = ind[\"1995\":\"2000\"].cov()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1c58a688",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(30, 30)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cov.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c3e62b67",
   "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>Food</th>\n",
       "      <th>Beer</th>\n",
       "      <th>Smoke</th>\n",
       "      <th>Games</th>\n",
       "      <th>Books</th>\n",
       "      <th>Hshld</th>\n",
       "      <th>Clths</th>\n",
       "      <th>Hlth</th>\n",
       "      <th>Chems</th>\n",
       "      <th>Txtls</th>\n",
       "      <th>...</th>\n",
       "      <th>Telcm</th>\n",
       "      <th>Servs</th>\n",
       "      <th>BusEq</th>\n",
       "      <th>Paper</th>\n",
       "      <th>Trans</th>\n",
       "      <th>Whlsl</th>\n",
       "      <th>Rtail</th>\n",
       "      <th>Meals</th>\n",
       "      <th>Fin</th>\n",
       "      <th>Other</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Food</th>\n",
       "      <td>0.002287</td>\n",
       "      <td>0.002077</td>\n",
       "      <td>0.001757</td>\n",
       "      <td>0.000701</td>\n",
       "      <td>0.000886</td>\n",
       "      <td>0.001208</td>\n",
       "      <td>0.001474</td>\n",
       "      <td>0.001105</td>\n",
       "      <td>0.001253</td>\n",
       "      <td>0.001021</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000610</td>\n",
       "      <td>0.000211</td>\n",
       "      <td>-0.000280</td>\n",
       "      <td>0.001205</td>\n",
       "      <td>0.001312</td>\n",
       "      <td>0.000633</td>\n",
       "      <td>0.001165</td>\n",
       "      <td>0.001085</td>\n",
       "      <td>0.001839</td>\n",
       "      <td>0.000898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Beer</th>\n",
       "      <td>0.002077</td>\n",
       "      <td>0.004599</td>\n",
       "      <td>0.001143</td>\n",
       "      <td>0.001147</td>\n",
       "      <td>0.000765</td>\n",
       "      <td>0.002447</td>\n",
       "      <td>0.001415</td>\n",
       "      <td>0.001689</td>\n",
       "      <td>0.001292</td>\n",
       "      <td>0.001721</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000978</td>\n",
       "      <td>0.000400</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>0.001455</td>\n",
       "      <td>0.001974</td>\n",
       "      <td>0.000609</td>\n",
       "      <td>0.001442</td>\n",
       "      <td>0.001634</td>\n",
       "      <td>0.002236</td>\n",
       "      <td>0.001196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Smoke</th>\n",
       "      <td>0.001757</td>\n",
       "      <td>0.001143</td>\n",
       "      <td>0.007130</td>\n",
       "      <td>0.000296</td>\n",
       "      <td>-0.000099</td>\n",
       "      <td>0.000981</td>\n",
       "      <td>0.000761</td>\n",
       "      <td>0.000877</td>\n",
       "      <td>0.000687</td>\n",
       "      <td>0.000555</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000057</td>\n",
       "      <td>-0.000266</td>\n",
       "      <td>-0.000300</td>\n",
       "      <td>0.001061</td>\n",
       "      <td>0.000241</td>\n",
       "      <td>0.001363</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>0.000590</td>\n",
       "      <td>0.001117</td>\n",
       "      <td>0.001418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Games</th>\n",
       "      <td>0.000701</td>\n",
       "      <td>0.001147</td>\n",
       "      <td>0.000296</td>\n",
       "      <td>0.003271</td>\n",
       "      <td>0.001485</td>\n",
       "      <td>0.001018</td>\n",
       "      <td>0.001814</td>\n",
       "      <td>0.001219</td>\n",
       "      <td>0.001547</td>\n",
       "      <td>0.001291</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001615</td>\n",
       "      <td>0.002399</td>\n",
       "      <td>0.002935</td>\n",
       "      <td>0.001615</td>\n",
       "      <td>0.001438</td>\n",
       "      <td>0.001681</td>\n",
       "      <td>0.001649</td>\n",
       "      <td>0.001383</td>\n",
       "      <td>0.002080</td>\n",
       "      <td>0.002088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Books</th>\n",
       "      <td>0.000886</td>\n",
       "      <td>0.000765</td>\n",
       "      <td>-0.000099</td>\n",
       "      <td>0.001485</td>\n",
       "      <td>0.002302</td>\n",
       "      <td>0.000876</td>\n",
       "      <td>0.002037</td>\n",
       "      <td>0.000657</td>\n",
       "      <td>0.001559</td>\n",
       "      <td>0.001362</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001627</td>\n",
       "      <td>0.001996</td>\n",
       "      <td>0.001624</td>\n",
       "      <td>0.001481</td>\n",
       "      <td>0.001576</td>\n",
       "      <td>0.001205</td>\n",
       "      <td>0.001995</td>\n",
       "      <td>0.001026</td>\n",
       "      <td>0.001979</td>\n",
       "      <td>0.001283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hshld</th>\n",
       "      <td>0.001208</td>\n",
       "      <td>0.002447</td>\n",
       "      <td>0.000981</td>\n",
       "      <td>0.001018</td>\n",
       "      <td>0.000876</td>\n",
       "      <td>0.002849</td>\n",
       "      <td>0.001046</td>\n",
       "      <td>0.001253</td>\n",
       "      <td>0.001226</td>\n",
       "      <td>0.001172</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000889</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>0.000906</td>\n",
       "      <td>0.001594</td>\n",
       "      <td>0.001366</td>\n",
       "      <td>0.000578</td>\n",
       "      <td>0.001157</td>\n",
       "      <td>0.001076</td>\n",
       "      <td>0.001652</td>\n",
       "      <td>0.001322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clths</th>\n",
       "      <td>0.001474</td>\n",
       "      <td>0.001415</td>\n",
       "      <td>0.000761</td>\n",
       "      <td>0.001814</td>\n",
       "      <td>0.002037</td>\n",
       "      <td>0.001046</td>\n",
       "      <td>0.004896</td>\n",
       "      <td>0.000759</td>\n",
       "      <td>0.002547</td>\n",
       "      <td>0.002105</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001263</td>\n",
       "      <td>0.001401</td>\n",
       "      <td>0.000746</td>\n",
       "      <td>0.002683</td>\n",
       "      <td>0.002466</td>\n",
       "      <td>0.001654</td>\n",
       "      <td>0.002607</td>\n",
       "      <td>0.002229</td>\n",
       "      <td>0.002699</td>\n",
       "      <td>0.001974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hlth</th>\n",
       "      <td>0.001105</td>\n",
       "      <td>0.001689</td>\n",
       "      <td>0.000877</td>\n",
       "      <td>0.001219</td>\n",
       "      <td>0.000657</td>\n",
       "      <td>0.001253</td>\n",
       "      <td>0.000759</td>\n",
       "      <td>0.002252</td>\n",
       "      <td>0.000444</td>\n",
       "      <td>0.000538</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001093</td>\n",
       "      <td>0.001390</td>\n",
       "      <td>0.001264</td>\n",
       "      <td>0.000552</td>\n",
       "      <td>0.000880</td>\n",
       "      <td>0.000907</td>\n",
       "      <td>0.000770</td>\n",
       "      <td>0.000900</td>\n",
       "      <td>0.001412</td>\n",
       "      <td>0.001099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chems</th>\n",
       "      <td>0.001253</td>\n",
       "      <td>0.001292</td>\n",
       "      <td>0.000687</td>\n",
       "      <td>0.001547</td>\n",
       "      <td>0.001559</td>\n",
       "      <td>0.001226</td>\n",
       "      <td>0.002547</td>\n",
       "      <td>0.000444</td>\n",
       "      <td>0.002944</td>\n",
       "      <td>0.001705</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000860</td>\n",
       "      <td>0.001072</td>\n",
       "      <td>0.000935</td>\n",
       "      <td>0.002581</td>\n",
       "      <td>0.001966</td>\n",
       "      <td>0.001257</td>\n",
       "      <td>0.001661</td>\n",
       "      <td>0.001425</td>\n",
       "      <td>0.002143</td>\n",
       "      <td>0.001832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Txtls</th>\n",
       "      <td>0.001021</td>\n",
       "      <td>0.001721</td>\n",
       "      <td>0.000555</td>\n",
       "      <td>0.001291</td>\n",
       "      <td>0.001362</td>\n",
       "      <td>0.001172</td>\n",
       "      <td>0.002105</td>\n",
       "      <td>0.000538</td>\n",
       "      <td>0.001705</td>\n",
       "      <td>0.002882</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000790</td>\n",
       "      <td>0.000582</td>\n",
       "      <td>0.000685</td>\n",
       "      <td>0.001869</td>\n",
       "      <td>0.001760</td>\n",
       "      <td>0.001426</td>\n",
       "      <td>0.001696</td>\n",
       "      <td>0.001126</td>\n",
       "      <td>0.001789</td>\n",
       "      <td>0.001668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cnstr</th>\n",
       "      <td>0.001282</td>\n",
       "      <td>0.001945</td>\n",
       "      <td>0.001181</td>\n",
       "      <td>0.001723</td>\n",
       "      <td>0.001531</td>\n",
       "      <td>0.001770</td>\n",
       "      <td>0.002486</td>\n",
       "      <td>0.001217</td>\n",
       "      <td>0.001829</td>\n",
       "      <td>0.001648</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001488</td>\n",
       "      <td>0.002169</td>\n",
       "      <td>0.001968</td>\n",
       "      <td>0.001922</td>\n",
       "      <td>0.002030</td>\n",
       "      <td>0.001453</td>\n",
       "      <td>0.001852</td>\n",
       "      <td>0.001810</td>\n",
       "      <td>0.002331</td>\n",
       "      <td>0.001573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steel</th>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.000131</td>\n",
       "      <td>0.000167</td>\n",
       "      <td>0.002670</td>\n",
       "      <td>0.001797</td>\n",
       "      <td>0.001050</td>\n",
       "      <td>0.001702</td>\n",
       "      <td>0.000836</td>\n",
       "      <td>0.002327</td>\n",
       "      <td>0.001321</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001987</td>\n",
       "      <td>0.003934</td>\n",
       "      <td>0.005049</td>\n",
       "      <td>0.002306</td>\n",
       "      <td>0.001528</td>\n",
       "      <td>0.002210</td>\n",
       "      <td>0.001423</td>\n",
       "      <td>0.000553</td>\n",
       "      <td>0.001851</td>\n",
       "      <td>0.003370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FabPr</th>\n",
       "      <td>0.000613</td>\n",
       "      <td>0.000666</td>\n",
       "      <td>0.000668</td>\n",
       "      <td>0.002498</td>\n",
       "      <td>0.001704</td>\n",
       "      <td>0.001125</td>\n",
       "      <td>0.002430</td>\n",
       "      <td>0.000768</td>\n",
       "      <td>0.002273</td>\n",
       "      <td>0.001576</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001428</td>\n",
       "      <td>0.002647</td>\n",
       "      <td>0.003732</td>\n",
       "      <td>0.002367</td>\n",
       "      <td>0.001949</td>\n",
       "      <td>0.002082</td>\n",
       "      <td>0.001669</td>\n",
       "      <td>0.001507</td>\n",
       "      <td>0.001985</td>\n",
       "      <td>0.002458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ElcEq</th>\n",
       "      <td>0.001146</td>\n",
       "      <td>0.001107</td>\n",
       "      <td>-0.000013</td>\n",
       "      <td>0.001980</td>\n",
       "      <td>0.002084</td>\n",
       "      <td>0.001426</td>\n",
       "      <td>0.002239</td>\n",
       "      <td>0.001108</td>\n",
       "      <td>0.001560</td>\n",
       "      <td>0.001102</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002058</td>\n",
       "      <td>0.003312</td>\n",
       "      <td>0.002968</td>\n",
       "      <td>0.001540</td>\n",
       "      <td>0.001623</td>\n",
       "      <td>0.001080</td>\n",
       "      <td>0.002326</td>\n",
       "      <td>0.001300</td>\n",
       "      <td>0.002323</td>\n",
       "      <td>0.001556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Autos</th>\n",
       "      <td>0.000547</td>\n",
       "      <td>0.001296</td>\n",
       "      <td>0.000223</td>\n",
       "      <td>0.001994</td>\n",
       "      <td>0.001550</td>\n",
       "      <td>0.001466</td>\n",
       "      <td>0.002521</td>\n",
       "      <td>0.000851</td>\n",
       "      <td>0.001882</td>\n",
       "      <td>0.001811</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001544</td>\n",
       "      <td>0.001800</td>\n",
       "      <td>0.002273</td>\n",
       "      <td>0.001957</td>\n",
       "      <td>0.001963</td>\n",
       "      <td>0.001543</td>\n",
       "      <td>0.001792</td>\n",
       "      <td>0.001624</td>\n",
       "      <td>0.002226</td>\n",
       "      <td>0.002055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Carry</th>\n",
       "      <td>0.001419</td>\n",
       "      <td>0.001804</td>\n",
       "      <td>0.001485</td>\n",
       "      <td>0.001644</td>\n",
       "      <td>0.001301</td>\n",
       "      <td>0.001704</td>\n",
       "      <td>0.002873</td>\n",
       "      <td>0.000755</td>\n",
       "      <td>0.002374</td>\n",
       "      <td>0.001842</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000845</td>\n",
       "      <td>0.001082</td>\n",
       "      <td>0.001261</td>\n",
       "      <td>0.002619</td>\n",
       "      <td>0.002232</td>\n",
       "      <td>0.001461</td>\n",
       "      <td>0.001702</td>\n",
       "      <td>0.001868</td>\n",
       "      <td>0.002368</td>\n",
       "      <td>0.002159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mines</th>\n",
       "      <td>0.000829</td>\n",
       "      <td>0.000272</td>\n",
       "      <td>0.001311</td>\n",
       "      <td>0.001600</td>\n",
       "      <td>0.001281</td>\n",
       "      <td>0.000598</td>\n",
       "      <td>0.002467</td>\n",
       "      <td>0.001103</td>\n",
       "      <td>0.002345</td>\n",
       "      <td>0.001274</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001456</td>\n",
       "      <td>0.002260</td>\n",
       "      <td>0.002199</td>\n",
       "      <td>0.002562</td>\n",
       "      <td>0.001623</td>\n",
       "      <td>0.001991</td>\n",
       "      <td>0.001537</td>\n",
       "      <td>0.001218</td>\n",
       "      <td>0.001757</td>\n",
       "      <td>0.002606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coal</th>\n",
       "      <td>0.000034</td>\n",
       "      <td>0.001261</td>\n",
       "      <td>-0.000544</td>\n",
       "      <td>0.001557</td>\n",
       "      <td>0.002051</td>\n",
       "      <td>0.001787</td>\n",
       "      <td>0.002433</td>\n",
       "      <td>0.001549</td>\n",
       "      <td>0.001910</td>\n",
       "      <td>0.000652</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000912</td>\n",
       "      <td>0.002373</td>\n",
       "      <td>0.002643</td>\n",
       "      <td>0.002099</td>\n",
       "      <td>0.001213</td>\n",
       "      <td>0.001793</td>\n",
       "      <td>0.000597</td>\n",
       "      <td>0.000382</td>\n",
       "      <td>0.002425</td>\n",
       "      <td>0.001443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oil</th>\n",
       "      <td>0.000933</td>\n",
       "      <td>0.000672</td>\n",
       "      <td>0.000849</td>\n",
       "      <td>0.000968</td>\n",
       "      <td>0.000868</td>\n",
       "      <td>0.000541</td>\n",
       "      <td>0.001646</td>\n",
       "      <td>0.000523</td>\n",
       "      <td>0.001843</td>\n",
       "      <td>0.001104</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000394</td>\n",
       "      <td>0.001002</td>\n",
       "      <td>0.000920</td>\n",
       "      <td>0.001570</td>\n",
       "      <td>0.001280</td>\n",
       "      <td>0.001423</td>\n",
       "      <td>0.000806</td>\n",
       "      <td>0.001091</td>\n",
       "      <td>0.001608</td>\n",
       "      <td>0.001688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Util</th>\n",
       "      <td>0.000858</td>\n",
       "      <td>0.000631</td>\n",
       "      <td>0.001118</td>\n",
       "      <td>0.000023</td>\n",
       "      <td>0.000455</td>\n",
       "      <td>0.000350</td>\n",
       "      <td>0.000646</td>\n",
       "      <td>0.000543</td>\n",
       "      <td>0.000545</td>\n",
       "      <td>0.000777</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000136</td>\n",
       "      <td>-0.000596</td>\n",
       "      <td>-0.001000</td>\n",
       "      <td>0.000387</td>\n",
       "      <td>0.000468</td>\n",
       "      <td>0.000719</td>\n",
       "      <td>-0.000099</td>\n",
       "      <td>0.000315</td>\n",
       "      <td>0.000978</td>\n",
       "      <td>0.000840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Telcm</th>\n",
       "      <td>0.000610</td>\n",
       "      <td>0.000978</td>\n",
       "      <td>0.000057</td>\n",
       "      <td>0.001615</td>\n",
       "      <td>0.001627</td>\n",
       "      <td>0.000889</td>\n",
       "      <td>0.001263</td>\n",
       "      <td>0.001093</td>\n",
       "      <td>0.000860</td>\n",
       "      <td>0.000790</td>\n",
       "      <td>...</td>\n",
       "      <td>0.003065</td>\n",
       "      <td>0.002971</td>\n",
       "      <td>0.002708</td>\n",
       "      <td>0.001097</td>\n",
       "      <td>0.001366</td>\n",
       "      <td>0.001001</td>\n",
       "      <td>0.001718</td>\n",
       "      <td>0.001013</td>\n",
       "      <td>0.001560</td>\n",
       "      <td>0.001129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Servs</th>\n",
       "      <td>0.000211</td>\n",
       "      <td>0.000400</td>\n",
       "      <td>-0.000266</td>\n",
       "      <td>0.002399</td>\n",
       "      <td>0.001996</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>0.001401</td>\n",
       "      <td>0.001390</td>\n",
       "      <td>0.001072</td>\n",
       "      <td>0.000582</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002971</td>\n",
       "      <td>0.006484</td>\n",
       "      <td>0.006079</td>\n",
       "      <td>0.001173</td>\n",
       "      <td>0.001299</td>\n",
       "      <td>0.001794</td>\n",
       "      <td>0.002447</td>\n",
       "      <td>0.000964</td>\n",
       "      <td>0.001630</td>\n",
       "      <td>0.002029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BusEq</th>\n",
       "      <td>-0.000280</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>-0.000300</td>\n",
       "      <td>0.002935</td>\n",
       "      <td>0.001624</td>\n",
       "      <td>0.000906</td>\n",
       "      <td>0.000746</td>\n",
       "      <td>0.001264</td>\n",
       "      <td>0.000935</td>\n",
       "      <td>0.000685</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002708</td>\n",
       "      <td>0.006079</td>\n",
       "      <td>0.008346</td>\n",
       "      <td>0.001267</td>\n",
       "      <td>0.001225</td>\n",
       "      <td>0.002178</td>\n",
       "      <td>0.001756</td>\n",
       "      <td>0.000630</td>\n",
       "      <td>0.001395</td>\n",
       "      <td>0.002305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paper</th>\n",
       "      <td>0.001205</td>\n",
       "      <td>0.001455</td>\n",
       "      <td>0.001061</td>\n",
       "      <td>0.001615</td>\n",
       "      <td>0.001481</td>\n",
       "      <td>0.001594</td>\n",
       "      <td>0.002683</td>\n",
       "      <td>0.000552</td>\n",
       "      <td>0.002581</td>\n",
       "      <td>0.001869</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001097</td>\n",
       "      <td>0.001173</td>\n",
       "      <td>0.001267</td>\n",
       "      <td>0.003004</td>\n",
       "      <td>0.002107</td>\n",
       "      <td>0.001396</td>\n",
       "      <td>0.001644</td>\n",
       "      <td>0.001420</td>\n",
       "      <td>0.002150</td>\n",
       "      <td>0.001686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trans</th>\n",
       "      <td>0.001312</td>\n",
       "      <td>0.001974</td>\n",
       "      <td>0.000241</td>\n",
       "      <td>0.001438</td>\n",
       "      <td>0.001576</td>\n",
       "      <td>0.001366</td>\n",
       "      <td>0.002466</td>\n",
       "      <td>0.000880</td>\n",
       "      <td>0.001966</td>\n",
       "      <td>0.001760</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001366</td>\n",
       "      <td>0.001299</td>\n",
       "      <td>0.001225</td>\n",
       "      <td>0.002107</td>\n",
       "      <td>0.002633</td>\n",
       "      <td>0.001084</td>\n",
       "      <td>0.001831</td>\n",
       "      <td>0.001741</td>\n",
       "      <td>0.002270</td>\n",
       "      <td>0.001557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Whlsl</th>\n",
       "      <td>0.000633</td>\n",
       "      <td>0.000609</td>\n",
       "      <td>0.001363</td>\n",
       "      <td>0.001681</td>\n",
       "      <td>0.001205</td>\n",
       "      <td>0.000578</td>\n",
       "      <td>0.001654</td>\n",
       "      <td>0.000907</td>\n",
       "      <td>0.001257</td>\n",
       "      <td>0.001426</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001001</td>\n",
       "      <td>0.001794</td>\n",
       "      <td>0.002178</td>\n",
       "      <td>0.001396</td>\n",
       "      <td>0.001084</td>\n",
       "      <td>0.002341</td>\n",
       "      <td>0.001061</td>\n",
       "      <td>0.000848</td>\n",
       "      <td>0.001594</td>\n",
       "      <td>0.001896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rtail</th>\n",
       "      <td>0.001165</td>\n",
       "      <td>0.001442</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>0.001649</td>\n",
       "      <td>0.001995</td>\n",
       "      <td>0.001157</td>\n",
       "      <td>0.002607</td>\n",
       "      <td>0.000770</td>\n",
       "      <td>0.001661</td>\n",
       "      <td>0.001696</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001718</td>\n",
       "      <td>0.002447</td>\n",
       "      <td>0.001756</td>\n",
       "      <td>0.001644</td>\n",
       "      <td>0.001831</td>\n",
       "      <td>0.001061</td>\n",
       "      <td>0.003197</td>\n",
       "      <td>0.001890</td>\n",
       "      <td>0.002010</td>\n",
       "      <td>0.001314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meals</th>\n",
       "      <td>0.001085</td>\n",
       "      <td>0.001634</td>\n",
       "      <td>0.000590</td>\n",
       "      <td>0.001383</td>\n",
       "      <td>0.001026</td>\n",
       "      <td>0.001076</td>\n",
       "      <td>0.002229</td>\n",
       "      <td>0.000900</td>\n",
       "      <td>0.001425</td>\n",
       "      <td>0.001126</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001013</td>\n",
       "      <td>0.000964</td>\n",
       "      <td>0.000630</td>\n",
       "      <td>0.001420</td>\n",
       "      <td>0.001741</td>\n",
       "      <td>0.000848</td>\n",
       "      <td>0.001890</td>\n",
       "      <td>0.002630</td>\n",
       "      <td>0.001765</td>\n",
       "      <td>0.001129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fin</th>\n",
       "      <td>0.001839</td>\n",
       "      <td>0.002236</td>\n",
       "      <td>0.001117</td>\n",
       "      <td>0.002080</td>\n",
       "      <td>0.001979</td>\n",
       "      <td>0.001652</td>\n",
       "      <td>0.002699</td>\n",
       "      <td>0.001412</td>\n",
       "      <td>0.002143</td>\n",
       "      <td>0.001789</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001560</td>\n",
       "      <td>0.001630</td>\n",
       "      <td>0.001395</td>\n",
       "      <td>0.002150</td>\n",
       "      <td>0.002270</td>\n",
       "      <td>0.001594</td>\n",
       "      <td>0.002010</td>\n",
       "      <td>0.001765</td>\n",
       "      <td>0.003459</td>\n",
       "      <td>0.001945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other</th>\n",
       "      <td>0.000898</td>\n",
       "      <td>0.001196</td>\n",
       "      <td>0.001418</td>\n",
       "      <td>0.002088</td>\n",
       "      <td>0.001283</td>\n",
       "      <td>0.001322</td>\n",
       "      <td>0.001974</td>\n",
       "      <td>0.001099</td>\n",
       "      <td>0.001832</td>\n",
       "      <td>0.001668</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001129</td>\n",
       "      <td>0.002029</td>\n",
       "      <td>0.002305</td>\n",
       "      <td>0.001686</td>\n",
       "      <td>0.001557</td>\n",
       "      <td>0.001896</td>\n",
       "      <td>0.001314</td>\n",
       "      <td>0.001129</td>\n",
       "      <td>0.001945</td>\n",
       "      <td>0.003655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>30 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Food      Beer     Smoke     Games     Books     Hshld     Clths  \\\n",
       "Food   0.002287  0.002077  0.001757  0.000701  0.000886  0.001208  0.001474   \n",
       "Beer   0.002077  0.004599  0.001143  0.001147  0.000765  0.002447  0.001415   \n",
       "Smoke  0.001757  0.001143  0.007130  0.000296 -0.000099  0.000981  0.000761   \n",
       "Games  0.000701  0.001147  0.000296  0.003271  0.001485  0.001018  0.001814   \n",
       "Books  0.000886  0.000765 -0.000099  0.001485  0.002302  0.000876  0.002037   \n",
       "Hshld  0.001208  0.002447  0.000981  0.001018  0.000876  0.002849  0.001046   \n",
       "Clths  0.001474  0.001415  0.000761  0.001814  0.002037  0.001046  0.004896   \n",
       "Hlth   0.001105  0.001689  0.000877  0.001219  0.000657  0.001253  0.000759   \n",
       "Chems  0.001253  0.001292  0.000687  0.001547  0.001559  0.001226  0.002547   \n",
       "Txtls  0.001021  0.001721  0.000555  0.001291  0.001362  0.001172  0.002105   \n",
       "Cnstr  0.001282  0.001945  0.001181  0.001723  0.001531  0.001770  0.002486   \n",
       "Steel  0.000027  0.000131  0.000167  0.002670  0.001797  0.001050  0.001702   \n",
       "FabPr  0.000613  0.000666  0.000668  0.002498  0.001704  0.001125  0.002430   \n",
       "ElcEq  0.001146  0.001107 -0.000013  0.001980  0.002084  0.001426  0.002239   \n",
       "Autos  0.000547  0.001296  0.000223  0.001994  0.001550  0.001466  0.002521   \n",
       "Carry  0.001419  0.001804  0.001485  0.001644  0.001301  0.001704  0.002873   \n",
       "Mines  0.000829  0.000272  0.001311  0.001600  0.001281  0.000598  0.002467   \n",
       "Coal   0.000034  0.001261 -0.000544  0.001557  0.002051  0.001787  0.002433   \n",
       "Oil    0.000933  0.000672  0.000849  0.000968  0.000868  0.000541  0.001646   \n",
       "Util   0.000858  0.000631  0.001118  0.000023  0.000455  0.000350  0.000646   \n",
       "Telcm  0.000610  0.000978  0.000057  0.001615  0.001627  0.000889  0.001263   \n",
       "Servs  0.000211  0.000400 -0.000266  0.002399  0.001996  0.001111  0.001401   \n",
       "BusEq -0.000280  0.000028 -0.000300  0.002935  0.001624  0.000906  0.000746   \n",
       "Paper  0.001205  0.001455  0.001061  0.001615  0.001481  0.001594  0.002683   \n",
       "Trans  0.001312  0.001974  0.000241  0.001438  0.001576  0.001366  0.002466   \n",
       "Whlsl  0.000633  0.000609  0.001363  0.001681  0.001205  0.000578  0.001654   \n",
       "Rtail  0.001165  0.001442  0.000069  0.001649  0.001995  0.001157  0.002607   \n",
       "Meals  0.001085  0.001634  0.000590  0.001383  0.001026  0.001076  0.002229   \n",
       "Fin    0.001839  0.002236  0.001117  0.002080  0.001979  0.001652  0.002699   \n",
       "Other  0.000898  0.001196  0.001418  0.002088  0.001283  0.001322  0.001974   \n",
       "\n",
       "           Hlth     Chems     Txtls  ...     Telcm     Servs     BusEq  \\\n",
       "Food   0.001105  0.001253  0.001021  ...  0.000610  0.000211 -0.000280   \n",
       "Beer   0.001689  0.001292  0.001721  ...  0.000978  0.000400  0.000028   \n",
       "Smoke  0.000877  0.000687  0.000555  ...  0.000057 -0.000266 -0.000300   \n",
       "Games  0.001219  0.001547  0.001291  ...  0.001615  0.002399  0.002935   \n",
       "Books  0.000657  0.001559  0.001362  ...  0.001627  0.001996  0.001624   \n",
       "Hshld  0.001253  0.001226  0.001172  ...  0.000889  0.001111  0.000906   \n",
       "Clths  0.000759  0.002547  0.002105  ...  0.001263  0.001401  0.000746   \n",
       "Hlth   0.002252  0.000444  0.000538  ...  0.001093  0.001390  0.001264   \n",
       "Chems  0.000444  0.002944  0.001705  ...  0.000860  0.001072  0.000935   \n",
       "Txtls  0.000538  0.001705  0.002882  ...  0.000790  0.000582  0.000685   \n",
       "Cnstr  0.001217  0.001829  0.001648  ...  0.001488  0.002169  0.001968   \n",
       "Steel  0.000836  0.002327  0.001321  ...  0.001987  0.003934  0.005049   \n",
       "FabPr  0.000768  0.002273  0.001576  ...  0.001428  0.002647  0.003732   \n",
       "ElcEq  0.001108  0.001560  0.001102  ...  0.002058  0.003312  0.002968   \n",
       "Autos  0.000851  0.001882  0.001811  ...  0.001544  0.001800  0.002273   \n",
       "Carry  0.000755  0.002374  0.001842  ...  0.000845  0.001082  0.001261   \n",
       "Mines  0.001103  0.002345  0.001274  ...  0.001456  0.002260  0.002199   \n",
       "Coal   0.001549  0.001910  0.000652  ...  0.000912  0.002373  0.002643   \n",
       "Oil    0.000523  0.001843  0.001104  ...  0.000394  0.001002  0.000920   \n",
       "Util   0.000543  0.000545  0.000777  ...  0.000136 -0.000596 -0.001000   \n",
       "Telcm  0.001093  0.000860  0.000790  ...  0.003065  0.002971  0.002708   \n",
       "Servs  0.001390  0.001072  0.000582  ...  0.002971  0.006484  0.006079   \n",
       "BusEq  0.001264  0.000935  0.000685  ...  0.002708  0.006079  0.008346   \n",
       "Paper  0.000552  0.002581  0.001869  ...  0.001097  0.001173  0.001267   \n",
       "Trans  0.000880  0.001966  0.001760  ...  0.001366  0.001299  0.001225   \n",
       "Whlsl  0.000907  0.001257  0.001426  ...  0.001001  0.001794  0.002178   \n",
       "Rtail  0.000770  0.001661  0.001696  ...  0.001718  0.002447  0.001756   \n",
       "Meals  0.000900  0.001425  0.001126  ...  0.001013  0.000964  0.000630   \n",
       "Fin    0.001412  0.002143  0.001789  ...  0.001560  0.001630  0.001395   \n",
       "Other  0.001099  0.001832  0.001668  ...  0.001129  0.002029  0.002305   \n",
       "\n",
       "          Paper     Trans     Whlsl     Rtail     Meals       Fin     Other  \n",
       "Food   0.001205  0.001312  0.000633  0.001165  0.001085  0.001839  0.000898  \n",
       "Beer   0.001455  0.001974  0.000609  0.001442  0.001634  0.002236  0.001196  \n",
       "Smoke  0.001061  0.000241  0.001363  0.000069  0.000590  0.001117  0.001418  \n",
       "Games  0.001615  0.001438  0.001681  0.001649  0.001383  0.002080  0.002088  \n",
       "Books  0.001481  0.001576  0.001205  0.001995  0.001026  0.001979  0.001283  \n",
       "Hshld  0.001594  0.001366  0.000578  0.001157  0.001076  0.001652  0.001322  \n",
       "Clths  0.002683  0.002466  0.001654  0.002607  0.002229  0.002699  0.001974  \n",
       "Hlth   0.000552  0.000880  0.000907  0.000770  0.000900  0.001412  0.001099  \n",
       "Chems  0.002581  0.001966  0.001257  0.001661  0.001425  0.002143  0.001832  \n",
       "Txtls  0.001869  0.001760  0.001426  0.001696  0.001126  0.001789  0.001668  \n",
       "Cnstr  0.001922  0.002030  0.001453  0.001852  0.001810  0.002331  0.001573  \n",
       "Steel  0.002306  0.001528  0.002210  0.001423  0.000553  0.001851  0.003370  \n",
       "FabPr  0.002367  0.001949  0.002082  0.001669  0.001507  0.001985  0.002458  \n",
       "ElcEq  0.001540  0.001623  0.001080  0.002326  0.001300  0.002323  0.001556  \n",
       "Autos  0.001957  0.001963  0.001543  0.001792  0.001624  0.002226  0.002055  \n",
       "Carry  0.002619  0.002232  0.001461  0.001702  0.001868  0.002368  0.002159  \n",
       "Mines  0.002562  0.001623  0.001991  0.001537  0.001218  0.001757  0.002606  \n",
       "Coal   0.002099  0.001213  0.001793  0.000597  0.000382  0.002425  0.001443  \n",
       "Oil    0.001570  0.001280  0.001423  0.000806  0.001091  0.001608  0.001688  \n",
       "Util   0.000387  0.000468  0.000719 -0.000099  0.000315  0.000978  0.000840  \n",
       "Telcm  0.001097  0.001366  0.001001  0.001718  0.001013  0.001560  0.001129  \n",
       "Servs  0.001173  0.001299  0.001794  0.002447  0.000964  0.001630  0.002029  \n",
       "BusEq  0.001267  0.001225  0.002178  0.001756  0.000630  0.001395  0.002305  \n",
       "Paper  0.003004  0.002107  0.001396  0.001644  0.001420  0.002150  0.001686  \n",
       "Trans  0.002107  0.002633  0.001084  0.001831  0.001741  0.002270  0.001557  \n",
       "Whlsl  0.001396  0.001084  0.002341  0.001061  0.000848  0.001594  0.001896  \n",
       "Rtail  0.001644  0.001831  0.001061  0.003197  0.001890  0.002010  0.001314  \n",
       "Meals  0.001420  0.001741  0.000848  0.001890  0.002630  0.001765  0.001129  \n",
       "Fin    0.002150  0.002270  0.001594  0.002010  0.001765  0.003459  0.001945  \n",
       "Other  0.001686  0.001557  0.001896  0.001314  0.001129  0.001945  0.003655  \n",
       "\n",
       "[30 rows x 30 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f329d752",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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