{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Riskfolio-Lib Tutorial: \n",
    "<br>__[Financionerioncios](https://financioneroncios.wordpress.com)__\n",
    "<br>__[Orenji](https://www.orenj-i.net)__\n",
    "<br>__[Riskfolio-Lib](https://riskfolio-lib.readthedocs.io/en/latest/)__\n",
    "<br>__[Dany Cajas](https://www.linkedin.com/in/dany-cajas/)__\n",
    "<a href='https://ko-fi.com/B0B833SXD' target='_blank'><img height='36' style='border:0px;height:36px;' src='https://cdn.ko-fi.com/cdn/kofi1.png?v=2' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a> \n",
    "\n",
    "## Tutorial 2: Portfolio Optimization with Risk Factors using Stepwise Regression\n",
    "\n",
    "## 1. Downloading the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  30 of 30 completed\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import yfinance as yf\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "pd.options.display.float_format = '{:.4%}'.format\n",
    "\n",
    "# Date range\n",
    "start = '2016-01-01'\n",
    "end = '2019-12-30'\n",
    "\n",
    "# Tickers of assets\n",
    "assets = ['JCI', 'TGT', 'CMCSA', 'CPB', 'MO', 'APA', 'MMC', 'JPM',\n",
    "          'ZION', 'PSA', 'BAX', 'BMY', 'LUV', 'PCAR', 'TXT', 'TMO',\n",
    "          'DE', 'MSFT', 'HPQ', 'SEE', 'VZ', 'CNP', 'NI', 'T', 'BA']\n",
    "\n",
    "assets.sort()\n",
    "\n",
    "# Tickers of factors\n",
    "\n",
    "factors = ['MTUM', 'QUAL', 'VLUE', 'SIZE', 'USMV']\n",
    "factors.sort()\n",
    "\n",
    "tickers = assets + factors\n",
    "tickers.sort()\n",
    "\n",
    "# Downloading data\n",
    "data = yf.download(tickers, start = start, end = end)\n",
    "data = data.loc[:,('Adj Close', slice(None))]\n",
    "data.columns = tickers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>MTUM</th>\n",
       "      <th>QUAL</th>\n",
       "      <th>SIZE</th>\n",
       "      <th>USMV</th>\n",
       "      <th>VLUE</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-05 00:00:00-05:00</th>\n",
       "      <td>0.4735%</td>\n",
       "      <td>0.2672%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.6780%</td>\n",
       "      <td>0.1635%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-06 00:00:00-05:00</th>\n",
       "      <td>-0.5267%</td>\n",
       "      <td>-1.1914%</td>\n",
       "      <td>-0.5380%</td>\n",
       "      <td>-0.6253%</td>\n",
       "      <td>-1.8277%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-07 00:00:00-05:00</th>\n",
       "      <td>-2.2293%</td>\n",
       "      <td>-2.3798%</td>\n",
       "      <td>-1.7181%</td>\n",
       "      <td>-1.6215%</td>\n",
       "      <td>-2.1609%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-08 00:00:00-05:00</th>\n",
       "      <td>-0.9549%</td>\n",
       "      <td>-1.1376%</td>\n",
       "      <td>-1.1978%</td>\n",
       "      <td>-1.0086%</td>\n",
       "      <td>-1.0873%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11 00:00:00-05:00</th>\n",
       "      <td>0.6043%</td>\n",
       "      <td>0.1479%</td>\n",
       "      <td>-0.5898%</td>\n",
       "      <td>0.1491%</td>\n",
       "      <td>-0.6183%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              MTUM     QUAL     SIZE     USMV     VLUE\n",
       "Date                                                                  \n",
       "2016-01-05 00:00:00-05:00  0.4735%  0.2672%  0.0000%  0.6780%  0.1635%\n",
       "2016-01-06 00:00:00-05:00 -0.5267% -1.1914% -0.5380% -0.6253% -1.8277%\n",
       "2016-01-07 00:00:00-05:00 -2.2293% -2.3798% -1.7181% -1.6215% -2.1609%\n",
       "2016-01-08 00:00:00-05:00 -0.9549% -1.1376% -1.1978% -1.0086% -1.0873%\n",
       "2016-01-11 00:00:00-05:00  0.6043%  0.1479% -0.5898%  0.1491% -0.6183%"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculating returns\n",
    "\n",
    "X = data[factors].pct_change().dropna()\n",
    "Y = data[assets].pct_change().dropna()\n",
    "\n",
    "display(X.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Estimating Mean Variance Portfolios\n",
    "\n",
    "### 2.1 Estimating the loadings matrix.\n",
    "\n",
    "This part is just to visualize how Riskfolio-Lib calculates a loadings matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_2b4a3_row0_col0, #T_2b4a3_row0_col1, #T_2b4a3_row6_col2, #T_2b4a3_row17_col5, #T_2b4a3_row19_col3, #T_2b4a3_row23_col3, #T_2b4a3_row24_col4 {\n",
       "  background-color: #a50026;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row0_col2, #T_2b4a3_row2_col2, #T_2b4a3_row7_col2, #T_2b4a3_row8_col2, #T_2b4a3_row9_col2, #T_2b4a3_row11_col2, #T_2b4a3_row13_col2, #T_2b4a3_row17_col2, #T_2b4a3_row18_col2, #T_2b4a3_row20_col2, #T_2b4a3_row24_col2 {\n",
       "  background-color: #fdc171;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row0_col3, #T_2b4a3_row0_col5, #T_2b4a3_row1_col2, #T_2b4a3_row10_col0, #T_2b4a3_row14_col1, #T_2b4a3_row15_col4 {\n",
       "  background-color: #006837;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row0_col4 {\n",
       "  background-color: #a90426;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row1_col0 {\n",
       "  background-color: #06733d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row1_col1, #T_2b4a3_row3_col1, #T_2b4a3_row4_col1, #T_2b4a3_row7_col1, #T_2b4a3_row8_col1, #T_2b4a3_row9_col1, #T_2b4a3_row10_col1, #T_2b4a3_row11_col1, #T_2b4a3_row20_col1, #T_2b4a3_row22_col1 {\n",
       "  background-color: #feda86;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row1_col3, #T_2b4a3_row7_col3, #T_2b4a3_row11_col5 {\n",
       "  background-color: #f4fab0;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row1_col4 {\n",
       "  background-color: #dd3d2d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row1_col5, #T_2b4a3_row2_col5, #T_2b4a3_row3_col5, #T_2b4a3_row4_col5, #T_2b4a3_row5_col5, #T_2b4a3_row6_col5, #T_2b4a3_row12_col5, #T_2b4a3_row13_col5, #T_2b4a3_row14_col5, #T_2b4a3_row21_col5 {\n",
       "  background-color: #f67a49;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row2_col0 {\n",
       "  background-color: #60ba62;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row2_col1 {\n",
       "  background-color: #e2f397;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row2_col3, #T_2b4a3_row3_col3, #T_2b4a3_row4_col3, #T_2b4a3_row5_col3, #T_2b4a3_row6_col3, #T_2b4a3_row8_col3, #T_2b4a3_row10_col3, #T_2b4a3_row12_col3, #T_2b4a3_row13_col3, #T_2b4a3_row15_col3, #T_2b4a3_row17_col3, #T_2b4a3_row20_col3, #T_2b4a3_row21_col3 {\n",
       "  background-color: #f7844e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row2_col4 {\n",
       "  background-color: #fdfebc;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row3_col0 {\n",
       "  background-color: #fcaa5f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row3_col2 {\n",
       "  background-color: #69be63;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row3_col4, #T_2b4a3_row7_col4, #T_2b4a3_row8_col4, #T_2b4a3_row9_col4, #T_2b4a3_row11_col4, #T_2b4a3_row20_col4 {\n",
       "  background-color: #f99355;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row4_col0 {\n",
       "  background-color: #d3ec87;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row4_col2 {\n",
       "  background-color: #cfeb85;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row4_col4 {\n",
       "  background-color: #fee695;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row5_col0 {\n",
       "  background-color: #d7ee8a;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row5_col1, #T_2b4a3_row22_col4 {\n",
       "  background-color: #c01a27;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row5_col2, #T_2b4a3_row22_col0 {\n",
       "  background-color: #f57748;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row5_col4 {\n",
       "  background-color: #45ad5b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row6_col0 {\n",
       "  background-color: #f8864f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row6_col1 {\n",
       "  background-color: #d83128;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row6_col4, #T_2b4a3_row16_col2 {\n",
       "  background-color: #148e4b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row7_col0 {\n",
       "  background-color: #0f8446;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row7_col5, #T_2b4a3_row9_col0, #T_2b4a3_row22_col5 {\n",
       "  background-color: #ddf191;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row8_col0 {\n",
       "  background-color: #93d168;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row8_col5 {\n",
       "  background-color: #6ec064;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row9_col3 {\n",
       "  background-color: #fafdb8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row9_col5, #T_2b4a3_row18_col4 {\n",
       "  background-color: #fffab6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row10_col2 {\n",
       "  background-color: #fbfdba;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row10_col4, #T_2b4a3_row23_col1 {\n",
       "  background-color: #d02927;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row10_col5 {\n",
       "  background-color: #8ccd67;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row11_col0 {\n",
       "  background-color: #feeda1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row11_col3 {\n",
       "  background-color: #f2faae;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row12_col0 {\n",
       "  background-color: #5db961;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row12_col1 {\n",
       "  background-color: #f67f4b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row12_col2 {\n",
       "  background-color: #98d368;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row12_col4 {\n",
       "  background-color: #fff1a8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row13_col0 {\n",
       "  background-color: #f46d43;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row13_col1 {\n",
       "  background-color: #dc3b2c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row13_col4 {\n",
       "  background-color: #9bd469;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row14_col0 {\n",
       "  background-color: #05713c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row14_col2 {\n",
       "  background-color: #a2d76a;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row14_col3 {\n",
       "  background-color: #af0926;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row14_col4 {\n",
       "  background-color: #ed5f3c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row15_col0 {\n",
       "  background-color: #fffdbc;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row15_col1, #T_2b4a3_row18_col0 {\n",
       "  background-color: #da362a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row15_col2 {\n",
       "  background-color: #ca2427;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row15_col5 {\n",
       "  background-color: #c21c27;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row16_col0 {\n",
       "  background-color: #78c565;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row16_col1, #T_2b4a3_row19_col1 {\n",
       "  background-color: #de402e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row16_col3, #T_2b4a3_row23_col5 {\n",
       "  background-color: #fee593;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row16_col4 {\n",
       "  background-color: #d93429;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row16_col5, #T_2b4a3_row21_col1, #T_2b4a3_row23_col0 {\n",
       "  background-color: #e8f59f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row17_col0 {\n",
       "  background-color: #e44c34;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row17_col1, #T_2b4a3_row18_col1 {\n",
       "  background-color: #f26841;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row17_col4 {\n",
       "  background-color: #63bc62;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row18_col3 {\n",
       "  background-color: #feefa3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row18_col5 {\n",
       "  background-color: #feec9f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row19_col0 {\n",
       "  background-color: #e9f6a1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row19_col2 {\n",
       "  background-color: #e0422f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row19_col4 {\n",
       "  background-color: #b5df74;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row19_col5, #T_2b4a3_row20_col5 {\n",
       "  background-color: #e6f59d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row20_col0 {\n",
       "  background-color: #07753e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row21_col0 {\n",
       "  background-color: #7fc866;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row21_col2 {\n",
       "  background-color: #c3e67d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row21_col4 {\n",
       "  background-color: #fed884;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row22_col2 {\n",
       "  background-color: #dcf08f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row22_col3 {\n",
       "  background-color: #daf08d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row23_col2 {\n",
       "  background-color: #b91326;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row23_col4 {\n",
       "  background-color: #36a657;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row24_col0 {\n",
       "  background-color: #0d8044;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row24_col1 {\n",
       "  background-color: #f88c51;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_2b4a3_row24_col3 {\n",
       "  background-color: #f5fbb2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_2b4a3_row24_col5 {\n",
       "  background-color: #097940;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_2b4a3\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_2b4a3_level0_col0\" class=\"col_heading level0 col0\" >const</th>\n",
       "      <th id=\"T_2b4a3_level0_col1\" class=\"col_heading level0 col1\" >MTUM</th>\n",
       "      <th id=\"T_2b4a3_level0_col2\" class=\"col_heading level0 col2\" >QUAL</th>\n",
       "      <th id=\"T_2b4a3_level0_col3\" class=\"col_heading level0 col3\" >SIZE</th>\n",
       "      <th id=\"T_2b4a3_level0_col4\" class=\"col_heading level0 col4\" >USMV</th>\n",
       "      <th id=\"T_2b4a3_level0_col5\" class=\"col_heading level0 col5\" >VLUE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row0\" class=\"row_heading level0 row0\" >APA</th>\n",
       "      <td id=\"T_2b4a3_row0_col0\" class=\"data row0 col0\" >-0.0006</td>\n",
       "      <td id=\"T_2b4a3_row0_col1\" class=\"data row0 col1\" >-0.6551</td>\n",
       "      <td id=\"T_2b4a3_row0_col2\" class=\"data row0 col2\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row0_col3\" class=\"data row0 col3\" >0.9406</td>\n",
       "      <td id=\"T_2b4a3_row0_col4\" class=\"data row0 col4\" >-0.7883</td>\n",
       "      <td id=\"T_2b4a3_row0_col5\" class=\"data row0 col5\" >1.7237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row1\" class=\"row_heading level0 row1\" >BA</th>\n",
       "      <td id=\"T_2b4a3_row1_col0\" class=\"data row1 col0\" >0.0005</td>\n",
       "      <td id=\"T_2b4a3_row1_col1\" class=\"data row1 col1\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row1_col2\" class=\"data row1 col2\" >1.1744</td>\n",
       "      <td id=\"T_2b4a3_row1_col3\" class=\"data row1 col3\" >0.3616</td>\n",
       "      <td id=\"T_2b4a3_row1_col4\" class=\"data row1 col4\" >-0.4322</td>\n",
       "      <td id=\"T_2b4a3_row1_col5\" class=\"data row1 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row2\" class=\"row_heading level0 row2\" >BAX</th>\n",
       "      <td id=\"T_2b4a3_row2_col0\" class=\"data row2 col0\" >0.0003</td>\n",
       "      <td id=\"T_2b4a3_row2_col1\" class=\"data row2 col1\" >0.3146</td>\n",
       "      <td id=\"T_2b4a3_row2_col2\" class=\"data row2 col2\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row2_col3\" class=\"data row2 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row2_col4\" class=\"data row2 col4\" >0.7717</td>\n",
       "      <td id=\"T_2b4a3_row2_col5\" class=\"data row2 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row3\" class=\"row_heading level0 row3\" >BMY</th>\n",
       "      <td id=\"T_2b4a3_row3_col0\" class=\"data row3 col0\" >-0.0003</td>\n",
       "      <td id=\"T_2b4a3_row3_col1\" class=\"data row3 col1\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row3_col2\" class=\"data row3 col2\" >0.8123</td>\n",
       "      <td id=\"T_2b4a3_row3_col3\" class=\"data row3 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row3_col4\" class=\"data row3 col4\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row3_col5\" class=\"data row3 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row4\" class=\"row_heading level0 row4\" >CMCSA</th>\n",
       "      <td id=\"T_2b4a3_row4_col0\" class=\"data row4 col0\" >0.0001</td>\n",
       "      <td id=\"T_2b4a3_row4_col1\" class=\"data row4 col1\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row4_col2\" class=\"data row4 col2\" >0.4958</td>\n",
       "      <td id=\"T_2b4a3_row4_col3\" class=\"data row4 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row4_col4\" class=\"data row4 col4\" >0.4962</td>\n",
       "      <td id=\"T_2b4a3_row4_col5\" class=\"data row4 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row5\" class=\"row_heading level0 row5\" >CNP</th>\n",
       "      <td id=\"T_2b4a3_row5_col0\" class=\"data row5 col0\" >0.0001</td>\n",
       "      <td id=\"T_2b4a3_row5_col1\" class=\"data row5 col1\" >-0.5595</td>\n",
       "      <td id=\"T_2b4a3_row5_col2\" class=\"data row5 col2\" >-0.2157</td>\n",
       "      <td id=\"T_2b4a3_row5_col3\" class=\"data row5 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row5_col4\" class=\"data row5 col4\" >1.8341</td>\n",
       "      <td id=\"T_2b4a3_row5_col5\" class=\"data row5 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row6\" class=\"row_heading level0 row6\" >CPB</th>\n",
       "      <td id=\"T_2b4a3_row6_col0\" class=\"data row6 col0\" >-0.0003</td>\n",
       "      <td id=\"T_2b4a3_row6_col1\" class=\"data row6 col1\" >-0.4782</td>\n",
       "      <td id=\"T_2b4a3_row6_col2\" class=\"data row6 col2\" >-0.5993</td>\n",
       "      <td id=\"T_2b4a3_row6_col3\" class=\"data row6 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row6_col4\" class=\"data row6 col4\" >2.0793</td>\n",
       "      <td id=\"T_2b4a3_row6_col5\" class=\"data row6 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row7\" class=\"row_heading level0 row7\" >DE</th>\n",
       "      <td id=\"T_2b4a3_row7_col0\" class=\"data row7 col0\" >0.0004</td>\n",
       "      <td id=\"T_2b4a3_row7_col1\" class=\"data row7 col1\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row7_col2\" class=\"data row7 col2\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row7_col3\" class=\"data row7 col3\" >0.3631</td>\n",
       "      <td id=\"T_2b4a3_row7_col4\" class=\"data row7 col4\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row7_col5\" class=\"data row7 col5\" >0.8090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row8\" class=\"row_heading level0 row8\" >HPQ</th>\n",
       "      <td id=\"T_2b4a3_row8_col0\" class=\"data row8 col0\" >0.0002</td>\n",
       "      <td id=\"T_2b4a3_row8_col1\" class=\"data row8 col1\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row8_col2\" class=\"data row8 col2\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row8_col3\" class=\"data row8 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row8_col4\" class=\"data row8 col4\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row8_col5\" class=\"data row8 col5\" >1.2514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row9\" class=\"row_heading level0 row9\" >JCI</th>\n",
       "      <td id=\"T_2b4a3_row9_col0\" class=\"data row9 col0\" >0.0001</td>\n",
       "      <td id=\"T_2b4a3_row9_col1\" class=\"data row9 col1\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row9_col2\" class=\"data row9 col2\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row9_col3\" class=\"data row9 col3\" >0.3412</td>\n",
       "      <td id=\"T_2b4a3_row9_col4\" class=\"data row9 col4\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row9_col5\" class=\"data row9 col5\" >0.5797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row10\" class=\"row_heading level0 row10\" >JPM</th>\n",
       "      <td id=\"T_2b4a3_row10_col0\" class=\"data row10 col0\" >0.0005</td>\n",
       "      <td id=\"T_2b4a3_row10_col1\" class=\"data row10 col1\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row10_col2\" class=\"data row10 col2\" >0.3076</td>\n",
       "      <td id=\"T_2b4a3_row10_col3\" class=\"data row10 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row10_col4\" class=\"data row10 col4\" >-0.5485</td>\n",
       "      <td id=\"T_2b4a3_row10_col5\" class=\"data row10 col5\" >1.1512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row11\" class=\"row_heading level0 row11\" >LUV</th>\n",
       "      <td id=\"T_2b4a3_row11_col0\" class=\"data row11 col0\" >-0.0001</td>\n",
       "      <td id=\"T_2b4a3_row11_col1\" class=\"data row11 col1\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row11_col2\" class=\"data row11 col2\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row11_col3\" class=\"data row11 col3\" >0.3642</td>\n",
       "      <td id=\"T_2b4a3_row11_col4\" class=\"data row11 col4\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row11_col5\" class=\"data row11 col5\" >0.6767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row12\" class=\"row_heading level0 row12\" >MMC</th>\n",
       "      <td id=\"T_2b4a3_row12_col0\" class=\"data row12 col0\" >0.0003</td>\n",
       "      <td id=\"T_2b4a3_row12_col1\" class=\"data row12 col1\" >-0.2693</td>\n",
       "      <td id=\"T_2b4a3_row12_col2\" class=\"data row12 col2\" >0.6808</td>\n",
       "      <td id=\"T_2b4a3_row12_col3\" class=\"data row12 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row12_col4\" class=\"data row12 col4\" >0.6066</td>\n",
       "      <td id=\"T_2b4a3_row12_col5\" class=\"data row12 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row13\" class=\"row_heading level0 row13\" >MO</th>\n",
       "      <td id=\"T_2b4a3_row13_col0\" class=\"data row13 col0\" >-0.0004</td>\n",
       "      <td id=\"T_2b4a3_row13_col1\" class=\"data row13 col1\" >-0.4572</td>\n",
       "      <td id=\"T_2b4a3_row13_col2\" class=\"data row13 col2\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row13_col3\" class=\"data row13 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row13_col4\" class=\"data row13 col4\" >1.4359</td>\n",
       "      <td id=\"T_2b4a3_row13_col5\" class=\"data row13 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row14\" class=\"row_heading level0 row14\" >MSFT</th>\n",
       "      <td id=\"T_2b4a3_row14_col0\" class=\"data row14 col0\" >0.0005</td>\n",
       "      <td id=\"T_2b4a3_row14_col1\" class=\"data row14 col1\" >1.0302</td>\n",
       "      <td id=\"T_2b4a3_row14_col2\" class=\"data row14 col2\" >0.6530</td>\n",
       "      <td id=\"T_2b4a3_row14_col3\" class=\"data row14 col3\" >-0.2640</td>\n",
       "      <td id=\"T_2b4a3_row14_col4\" class=\"data row14 col4\" >-0.2595</td>\n",
       "      <td id=\"T_2b4a3_row14_col5\" class=\"data row14 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row15\" class=\"row_heading level0 row15\" >NI</th>\n",
       "      <td id=\"T_2b4a3_row15_col0\" class=\"data row15 col0\" >-0.0000</td>\n",
       "      <td id=\"T_2b4a3_row15_col1\" class=\"data row15 col1\" >-0.4649</td>\n",
       "      <td id=\"T_2b4a3_row15_col2\" class=\"data row15 col2\" >-0.4611</td>\n",
       "      <td id=\"T_2b4a3_row15_col3\" class=\"data row15 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row15_col4\" class=\"data row15 col4\" >2.3257</td>\n",
       "      <td id=\"T_2b4a3_row15_col5\" class=\"data row15 col5\" >-0.3532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row16\" class=\"row_heading level0 row16\" >PCAR</th>\n",
       "      <td id=\"T_2b4a3_row16_col0\" class=\"data row16 col0\" >0.0003</td>\n",
       "      <td id=\"T_2b4a3_row16_col1\" class=\"data row16 col1\" >-0.4420</td>\n",
       "      <td id=\"T_2b4a3_row16_col2\" class=\"data row16 col2\" >1.0319</td>\n",
       "      <td id=\"T_2b4a3_row16_col3\" class=\"data row16 col3\" >0.2217</td>\n",
       "      <td id=\"T_2b4a3_row16_col4\" class=\"data row16 col4\" >-0.4831</td>\n",
       "      <td id=\"T_2b4a3_row16_col5\" class=\"data row16 col5\" >0.7536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row17\" class=\"row_heading level0 row17\" >PSA</th>\n",
       "      <td id=\"T_2b4a3_row17_col0\" class=\"data row17 col0\" >-0.0004</td>\n",
       "      <td id=\"T_2b4a3_row17_col1\" class=\"data row17 col1\" >-0.3311</td>\n",
       "      <td id=\"T_2b4a3_row17_col2\" class=\"data row17 col2\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row17_col3\" class=\"data row17 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row17_col4\" class=\"data row17 col4\" >1.7073</td>\n",
       "      <td id=\"T_2b4a3_row17_col5\" class=\"data row17 col5\" >-0.4915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row18\" class=\"row_heading level0 row18\" >SEE</th>\n",
       "      <td id=\"T_2b4a3_row18_col0\" class=\"data row18 col0\" >-0.0005</td>\n",
       "      <td id=\"T_2b4a3_row18_col1\" class=\"data row18 col1\" >-0.3267</td>\n",
       "      <td id=\"T_2b4a3_row18_col2\" class=\"data row18 col2\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row18_col3\" class=\"data row18 col3\" >0.2594</td>\n",
       "      <td id=\"T_2b4a3_row18_col4\" class=\"data row18 col4\" >0.6973</td>\n",
       "      <td id=\"T_2b4a3_row18_col5\" class=\"data row18 col5\" >0.4801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row19\" class=\"row_heading level0 row19\" >T</th>\n",
       "      <td id=\"T_2b4a3_row19_col0\" class=\"data row19 col0\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row19_col1\" class=\"data row19 col1\" >-0.4414</td>\n",
       "      <td id=\"T_2b4a3_row19_col2\" class=\"data row19 col2\" >-0.3693</td>\n",
       "      <td id=\"T_2b4a3_row19_col3\" class=\"data row19 col3\" >-0.2898</td>\n",
       "      <td id=\"T_2b4a3_row19_col4\" class=\"data row19 col4\" >1.2928</td>\n",
       "      <td id=\"T_2b4a3_row19_col5\" class=\"data row19 col5\" >0.7563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row20\" class=\"row_heading level0 row20\" >TGT</th>\n",
       "      <td id=\"T_2b4a3_row20_col0\" class=\"data row20 col0\" >0.0005</td>\n",
       "      <td id=\"T_2b4a3_row20_col1\" class=\"data row20 col1\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row20_col2\" class=\"data row20 col2\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row20_col3\" class=\"data row20 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row20_col4\" class=\"data row20 col4\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row20_col5\" class=\"data row20 col5\" >0.7562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row21\" class=\"row_heading level0 row21\" >TMO</th>\n",
       "      <td id=\"T_2b4a3_row21_col0\" class=\"data row21 col0\" >0.0002</td>\n",
       "      <td id=\"T_2b4a3_row21_col1\" class=\"data row21 col1\" >0.2867</td>\n",
       "      <td id=\"T_2b4a3_row21_col2\" class=\"data row21 col2\" >0.5400</td>\n",
       "      <td id=\"T_2b4a3_row21_col3\" class=\"data row21 col3\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row21_col4\" class=\"data row21 col4\" >0.3864</td>\n",
       "      <td id=\"T_2b4a3_row21_col5\" class=\"data row21 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row22\" class=\"row_heading level0 row22\" >TXT</th>\n",
       "      <td id=\"T_2b4a3_row22_col0\" class=\"data row22 col0\" >-0.0003</td>\n",
       "      <td id=\"T_2b4a3_row22_col1\" class=\"data row22 col1\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row22_col2\" class=\"data row22 col2\" >0.4485</td>\n",
       "      <td id=\"T_2b4a3_row22_col3\" class=\"data row22 col3\" >0.4429</td>\n",
       "      <td id=\"T_2b4a3_row22_col4\" class=\"data row22 col4\" >-0.6363</td>\n",
       "      <td id=\"T_2b4a3_row22_col5\" class=\"data row22 col5\" >0.8108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row23\" class=\"row_heading level0 row23\" >VZ</th>\n",
       "      <td id=\"T_2b4a3_row23_col0\" class=\"data row23 col0\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row23_col1\" class=\"data row23 col1\" >-0.5099</td>\n",
       "      <td id=\"T_2b4a3_row23_col2\" class=\"data row23 col2\" >-0.5271</td>\n",
       "      <td id=\"T_2b4a3_row23_col3\" class=\"data row23 col3\" >-0.2886</td>\n",
       "      <td id=\"T_2b4a3_row23_col4\" class=\"data row23 col4\" >1.8941</td>\n",
       "      <td id=\"T_2b4a3_row23_col5\" class=\"data row23 col5\" >0.4321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2b4a3_level0_row24\" class=\"row_heading level0 row24\" >ZION</th>\n",
       "      <td id=\"T_2b4a3_row24_col0\" class=\"data row24 col0\" >0.0004</td>\n",
       "      <td id=\"T_2b4a3_row24_col1\" class=\"data row24 col1\" >-0.2371</td>\n",
       "      <td id=\"T_2b4a3_row24_col2\" class=\"data row24 col2\" >0.0000</td>\n",
       "      <td id=\"T_2b4a3_row24_col3\" class=\"data row24 col3\" >0.3554</td>\n",
       "      <td id=\"T_2b4a3_row24_col4\" class=\"data row24 col4\" >-0.8203</td>\n",
       "      <td id=\"T_2b4a3_row24_col5\" class=\"data row24 col5\" >1.6431</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f8b104846d0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import riskfolio as rp\n",
    "\n",
    "step = 'Forward' # Could be Forward or Backward stepwise regression\n",
    "loadings = rp.loadings_matrix(X=X, Y=Y, stepwise=step)\n",
    "\n",
    "loadings.style.format(\"{:.4f}\").background_gradient(cmap='RdYlGn')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Calculating the portfolio that maximizes Sharpe ratio."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1004, 25)\n"
     ]
    },
    {
     "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>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>weights</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.9508%</td>\n",
       "      <td>11.8691%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.7091%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.3627%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>10.4798%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.5106%</td>\n",
       "      <td>1.3023%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.0977%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            APA      BA      BAX     BMY   CMCSA     CNP     CPB      DE  \\\n",
       "weights 0.0000% 5.9508% 11.8691% 0.0000% 0.0000% 9.7091% 0.0000% 4.3627%   \n",
       "\n",
       "            HPQ     JCI  ...       NI    PCAR     PSA     SEE       T     TGT  \\\n",
       "weights 0.0000% 0.0000%  ... 10.4798% 0.0000% 0.0000% 0.0000% 0.0000% 5.5106%   \n",
       "\n",
       "            TMO     TXT      VZ    ZION  \n",
       "weights 1.3023% 0.0000% 4.0977% 0.0000%  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Building the portfolio object\n",
    "port = rp.Portfolio(returns=Y)\n",
    "\n",
    "# Calculating optimal portfolio\n",
    "\n",
    "# Select method and estimate input parameters:\n",
    "\n",
    "method_mu='hist' # Method to estimate expected returns based on historical data.\n",
    "method_cov='hist' # Method to estimate covariance matrix based on historical data.\n",
    "\n",
    "port.assets_stats(method_mu=method_mu, method_cov=method_cov, d=0.94)\n",
    "\n",
    "port.factors = X\n",
    "port.factors_stats(method_mu=method_mu, method_cov=method_cov, d=0.94)\n",
    "\n",
    "# Estimate optimal portfolio:\n",
    "\n",
    "port.alpha = 0.05\n",
    "model='FM' # Factor Model\n",
    "rm = 'MV' # Risk measure used, this time will be variance\n",
    "obj = 'Sharpe' # Objective function, could be MinRisk, MaxRet, Utility or Sharpe\n",
    "hist = False # Use historical scenarios for risk measures that depend on scenarios\n",
    "rf = 0 # Risk free rate\n",
    "l = 0 # Risk aversion factor, only useful when obj is 'Utility'\n",
    "\n",
    "w = port.optimization(model=model, rm=rm, obj=obj, rf=rf, l=l, hist=hist)\n",
    "\n",
    "display(w.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Plotting portfolio composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the composition of the portfolio\n",
    "\n",
    "ax = rp.plot_pie(w=w, title='Sharpe FM Mean Variance', others=0.05, nrow=25, cmap = \"tab20\",\n",
    "                 height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Calculate efficient frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.9915%</td>\n",
       "      <td>4.4203%</td>\n",
       "      <td>3.5982%</td>\n",
       "      <td>8.4947%</td>\n",
       "      <td>5.0090%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.4340%</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0935%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>13.3196%</td>\n",
       "      <td>1.0089%</td>\n",
       "      <td>8.3014%</td>\n",
       "      <td>4.0842%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.3131%</td>\n",
       "      <td>1.6678%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.6589%</td>\n",
       "      <td>6.2599%</td>\n",
       "      <td>1.2538%</td>\n",
       "      <td>3.4251%</td>\n",
       "      <td>10.4170%</td>\n",
       "      <td>3.1168%</td>\n",
       "      <td>0.3986%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.5870%</td>\n",
       "      <td>...</td>\n",
       "      <td>13.7067%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.7369%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.7067%</td>\n",
       "      <td>4.9334%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.5792%</td>\n",
       "      <td>1.6507%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.3022%</td>\n",
       "      <td>7.3158%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.0350%</td>\n",
       "      <td>11.1001%</td>\n",
       "      <td>2.4078%</td>\n",
       "      <td>0.9815%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.6503%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.3023%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.5454%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.0226%</td>\n",
       "      <td>5.1519%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.6635%</td>\n",
       "      <td>1.4140%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.8523%</td>\n",
       "      <td>8.2124%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.5287%</td>\n",
       "      <td>11.5853%</td>\n",
       "      <td>1.6264%</td>\n",
       "      <td>1.4954%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.6300%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.6708%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.1895%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.2024%</td>\n",
       "      <td>5.3156%</td>\n",
       "      <td>0.0757%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.5638%</td>\n",
       "      <td>1.1082%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.3061%</td>\n",
       "      <td>8.9457%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.0093%</td>\n",
       "      <td>11.9269%</td>\n",
       "      <td>0.8759%</td>\n",
       "      <td>1.9173%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.8951%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.9663%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.3810%</td>\n",
       "      <td>5.4380%</td>\n",
       "      <td>0.4388%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.3772%</td>\n",
       "      <td>0.7801%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      APA      BA     BAX     BMY   CMCSA      CNP     CPB      DE     HPQ  \\\n",
       "0 0.0000% 0.0000% 1.9915% 4.4203% 3.5982%  8.4947% 5.0090% 0.0000% 0.0000%   \n",
       "1 0.0000% 1.6589% 6.2599% 1.2538% 3.4251% 10.4170% 3.1168% 0.3986% 0.0000%   \n",
       "2 0.0000% 2.3022% 7.3158% 0.0000% 3.0350% 11.1001% 2.4078% 0.9815% 0.0000%   \n",
       "3 0.0000% 2.8523% 8.2124% 0.0000% 2.5287% 11.5853% 1.6264% 1.4954% 0.0000%   \n",
       "4 0.0000% 3.3061% 8.9457% 0.0000% 2.0093% 11.9269% 0.8759% 1.9173% 0.0000%   \n",
       "\n",
       "      JCI  ...       NI    PCAR      PSA     SEE       T     TGT     TMO  \\\n",
       "0 4.4340%  ... 12.0935% 0.0000% 13.3196% 1.0089% 8.3014% 4.0842% 0.0000%   \n",
       "1 2.5870%  ... 13.7067% 0.0000%  7.7369% 0.0000% 6.7067% 4.9334% 0.0000%   \n",
       "2 1.6503%  ... 14.3023% 0.0000%  5.5454% 0.0000% 6.0226% 5.1519% 0.0000%   \n",
       "3 0.6300%  ... 14.6708% 0.0000%  3.1895% 0.0000% 5.2024% 5.3156% 0.0757%   \n",
       "4 0.0000%  ... 14.8951% 0.0000%  0.9663% 0.0000% 4.3810% 5.4380% 0.4388%   \n",
       "\n",
       "      TXT       VZ    ZION  \n",
       "0 0.0000% 10.3131% 1.6678%  \n",
       "1 0.0000% 10.5792% 1.6507%  \n",
       "2 0.0000% 10.6635% 1.4140%  \n",
       "3 0.0000% 10.5638% 1.1082%  \n",
       "4 0.0000% 10.3772% 0.7801%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points = 50 # Number of points of the frontier\n",
    "\n",
    "frontier = port.efficient_frontier(model=model, rm=rm, points=points, rf=rf, hist=hist)\n",
    "\n",
    "display(frontier.T.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the efficient frontier\n",
    "\n",
    "label = 'Max Risk Adjusted Return Portfolio' # Title of point\n",
    "mu = port.mu_fm # Expected returns\n",
    "cov = port.cov_fm # Covariance matrix\n",
    "returns = port.returns_fm # Returns of the assets\n",
    "\n",
    "ax = rp.plot_frontier(w_frontier=frontier, mu=mu, cov=cov, returns=returns, rm=rm,\n",
    "                      rf=rf, alpha=0.05, cmap='viridis', w=w, label=label,\n",
    "                      marker='*', s=16, c='r', height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting efficient frontier composition\n",
    "\n",
    "ax = rp.plot_frontier_area(w_frontier=frontier, cmap=\"tab20\", height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Optimization with Constraints on Risk Factors"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1 Statistics of Risk Factors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "const    -0.0583%\n",
       "MTUM    -65.5125%\n",
       "QUAL    -59.9324%\n",
       "SIZE    -28.9796%\n",
       "USMV    -82.0310%\n",
       "VLUE    -49.1495%\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "const     0.0504%\n",
       "MTUM    103.0208%\n",
       "QUAL    117.4359%\n",
       "SIZE     94.0633%\n",
       "USMV    232.5675%\n",
       "VLUE    172.3667%\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>MTUM</th>\n",
       "      <th>QUAL</th>\n",
       "      <th>SIZE</th>\n",
       "      <th>USMV</th>\n",
       "      <th>VLUE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MTUM</th>\n",
       "      <td>100.0000%</td>\n",
       "      <td>90.4264%</td>\n",
       "      <td>79.1173%</td>\n",
       "      <td>87.2320%</td>\n",
       "      <td>78.5394%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QUAL</th>\n",
       "      <td>90.4264%</td>\n",
       "      <td>100.0000%</td>\n",
       "      <td>89.8169%</td>\n",
       "      <td>89.9554%</td>\n",
       "      <td>91.6580%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SIZE</th>\n",
       "      <td>79.1173%</td>\n",
       "      <td>89.8169%</td>\n",
       "      <td>100.0000%</td>\n",
       "      <td>82.5080%</td>\n",
       "      <td>87.9112%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USMV</th>\n",
       "      <td>87.2320%</td>\n",
       "      <td>89.9554%</td>\n",
       "      <td>82.5080%</td>\n",
       "      <td>100.0000%</td>\n",
       "      <td>76.9678%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VLUE</th>\n",
       "      <td>78.5394%</td>\n",
       "      <td>91.6580%</td>\n",
       "      <td>87.9112%</td>\n",
       "      <td>76.9678%</td>\n",
       "      <td>100.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          MTUM      QUAL      SIZE      USMV      VLUE\n",
       "MTUM 100.0000%  90.4264%  79.1173%  87.2320%  78.5394%\n",
       "QUAL  90.4264% 100.0000%  89.8169%  89.9554%  91.6580%\n",
       "SIZE  79.1173%  89.8169% 100.0000%  82.5080%  87.9112%\n",
       "USMV  87.2320%  89.9554%  82.5080% 100.0000%  76.9678%\n",
       "VLUE  78.5394%  91.6580%  87.9112%  76.9678% 100.0000%"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Displaying factors statistics\n",
    "\n",
    "display(loadings.min())\n",
    "display(loadings.max())\n",
    "display(X.corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 Creating Constraints on Risk Factors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Disabled</th>\n",
       "      <th>Factor</th>\n",
       "      <th>Sign</th>\n",
       "      <th>Value</th>\n",
       "      <th>Relative Factor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>False</td>\n",
       "      <td>MTUM</td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>-30.0000%</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>False</td>\n",
       "      <td>QUAL</td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>80.0000%</td>\n",
       "      <td>USMV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>False</td>\n",
       "      <td>SIZE</td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>40.0000%</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>False</td>\n",
       "      <td>USMV</td>\n",
       "      <td>&gt;=</td>\n",
       "      <td>80.0000%</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>VLUE</td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>90.0000%</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Disabled Factor Sign     Value Relative Factor\n",
       "0     False   MTUM   <= -30.0000%                \n",
       "1     False   QUAL   <=  80.0000%            USMV\n",
       "2     False   SIZE   <=  40.0000%                \n",
       "3     False   USMV   >=  80.0000%                \n",
       "4     False   VLUE   <=  90.0000%                "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating risk factors constraints\n",
    "\n",
    "constraints = {'Disabled': [False, False, False, False, False],\n",
    "               'Factor': ['MTUM', 'QUAL', 'SIZE', 'USMV', 'VLUE'],\n",
    "               'Sign': ['<=', '<=', '<=', '>=', '<='],\n",
    "               'Value': [-0.3, 0.8, 0.4, 0.8 , 0.9],\n",
    "               'Relative Factor': ['', 'USMV', '', '', '']}\n",
    "\n",
    "constraints = pd.DataFrame(constraints)\n",
    "\n",
    "display(constraints)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "C, D = rp.factors_constraints(constraints, loadings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>weights</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.5843%</td>\n",
       "      <td>1.4896%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>17.4848%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.0876%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>13.9652%</td>\n",
       "      <td>1.3789%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.3064%</td>\n",
       "      <td>4.4149%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.5778%</td>\n",
       "      <td>2.0946%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            APA      BA     BAX     BMY   CMCSA      CNP     CPB      DE  \\\n",
       "weights 0.0000% 6.5843% 1.4896% 0.0000% 0.0000% 17.4848% 0.0000% 4.0876%   \n",
       "\n",
       "            HPQ     JCI  ...       NI    PCAR     PSA     SEE       T     TGT  \\\n",
       "weights 0.0000% 0.0000%  ... 13.9652% 1.3789% 0.0000% 0.0000% 0.3064% 4.4149%   \n",
       "\n",
       "            TMO     TXT       VZ    ZION  \n",
       "weights 0.0000% 0.0000% 10.5778% 2.0946%  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "port.ainequality = C\n",
    "port.binequality = D\n",
    "\n",
    "w = port.optimization(model=model, rm=rm, obj=obj, rf=rf, l=l, hist=hist)\n",
    "\n",
    "display(w.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To check if the constraints are verified, I will make a regression among the portfolio returns and risk factors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "const     0.0229%\n",
      "MTUM    -30.0000%\n",
      "QUAL     15.3036%\n",
      "SIZE      1.7736%\n",
      "USMV     92.6900%\n",
      "VLUE     21.9835%\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "\n",
    "X1 = sm.add_constant(X)\n",
    "y = np.matrix(returns) * np.matrix(w)\n",
    "results = sm.OLS(y, X1).fit()\n",
    "coefs = results.params\n",
    "\n",
    "print(coefs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 Plotting portfolio composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = rp.plot_pie(w=w, title='Sharpe FM Mean Variance', others=0.05, nrow=25, cmap = \"tab20\",\n",
    "                 height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.4 Calculate efficient frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.9926%</td>\n",
       "      <td>4.4202%</td>\n",
       "      <td>3.5980%</td>\n",
       "      <td>8.4936%</td>\n",
       "      <td>5.0087%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.4337%</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0932%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>13.3197%</td>\n",
       "      <td>1.0130%</td>\n",
       "      <td>8.3001%</td>\n",
       "      <td>4.0840%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.3121%</td>\n",
       "      <td>1.6674%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.0475%</td>\n",
       "      <td>4.5030%</td>\n",
       "      <td>1.9695%</td>\n",
       "      <td>3.3300%</td>\n",
       "      <td>10.3898%</td>\n",
       "      <td>3.6703%</td>\n",
       "      <td>0.0001%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.9604%</td>\n",
       "      <td>...</td>\n",
       "      <td>13.4551%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.0989%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.4172%</td>\n",
       "      <td>4.6595%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.8691%</td>\n",
       "      <td>1.9813%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.7533%</td>\n",
       "      <td>4.8601%</td>\n",
       "      <td>0.7459%</td>\n",
       "      <td>2.9456%</td>\n",
       "      <td>11.4506%</td>\n",
       "      <td>3.1270%</td>\n",
       "      <td>0.3774%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.0699%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.1330%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.2013%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.1319%</td>\n",
       "      <td>4.7870%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.2907%</td>\n",
       "      <td>2.0815%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.2850%</td>\n",
       "      <td>5.0718%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.6007%</td>\n",
       "      <td>12.3054%</td>\n",
       "      <td>2.6939%</td>\n",
       "      <td>0.7947%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.3267%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.6720%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.6643%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.8992%</td>\n",
       "      <td>4.8726%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.6306%</td>\n",
       "      <td>2.1410%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.7534%</td>\n",
       "      <td>5.1132%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.1862%</td>\n",
       "      <td>13.1588%</td>\n",
       "      <td>2.2596%</td>\n",
       "      <td>1.1574%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.5350%</td>\n",
       "      <td>...</td>\n",
       "      <td>15.1825%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.1051%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.6679%</td>\n",
       "      <td>4.9234%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.9726%</td>\n",
       "      <td>2.1890%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      APA      BA     BAX     BMY   CMCSA      CNP     CPB      DE     HPQ  \\\n",
       "0 0.0000% 0.0000% 1.9926% 4.4202% 3.5980%  8.4936% 5.0087% 0.0000% 0.0000%   \n",
       "1 0.0000% 1.0475% 4.5030% 1.9695% 3.3300% 10.3898% 3.6703% 0.0001% 0.0000%   \n",
       "2 0.0000% 1.7533% 4.8601% 0.7459% 2.9456% 11.4506% 3.1270% 0.3774% 0.0000%   \n",
       "3 0.0000% 2.2850% 5.0718% 0.0000% 2.6007% 12.3054% 2.6939% 0.7947% 0.0000%   \n",
       "4 0.0000% 2.7534% 5.1132% 0.0000% 2.1862% 13.1588% 2.2596% 1.1574% 0.0000%   \n",
       "\n",
       "      JCI  ...       NI    PCAR      PSA     SEE       T     TGT     TMO  \\\n",
       "0 4.4337%  ... 12.0932% 0.0000% 13.3197% 1.0130% 8.3001% 4.0840% 0.0000%   \n",
       "1 2.9604%  ... 13.4551% 0.0000%  9.0989% 0.0000% 7.4172% 4.6595% 0.0000%   \n",
       "2 2.0699%  ... 14.1330% 0.0000%  7.2013% 0.0000% 7.1319% 4.7870% 0.0000%   \n",
       "3 1.3267%  ... 14.6720% 0.0000%  5.6643% 0.0000% 6.8992% 4.8726% 0.0000%   \n",
       "4 0.5350%  ... 15.1825% 0.0000%  4.1051% 0.0000% 6.6679% 4.9234% 0.0000%   \n",
       "\n",
       "      TXT       VZ    ZION  \n",
       "0 0.0000% 10.3121% 1.6674%  \n",
       "1 0.0000% 10.8691% 1.9813%  \n",
       "2 0.0000% 11.2907% 2.0815%  \n",
       "3 0.0000% 11.6306% 2.1410%  \n",
       "4 0.0000% 11.9726% 2.1890%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points = 50 # Number of points of the frontier\n",
    "\n",
    "frontier = port.efficient_frontier(model=model, rm=rm, points=points, rf=rf, hist=hist)\n",
    "\n",
    "display(frontier.T.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting efficient frontier composition\n",
    "\n",
    "ax = rp.plot_frontier(w_frontier=frontier, mu=mu, cov=cov, returns=returns, rm=rm,\n",
    "                      rf=rf, alpha=0.05, cmap='viridis', w=w, label=label,\n",
    "                      marker='*', s=16, c='r', height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting efficient frontier composition\n",
    "\n",
    "ax = rp.plot_frontier_area(w_frontier=frontier, cmap=\"tab20\", height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-05 00:00:00-05:00</th>\n",
       "      <td>-0.6212%</td>\n",
       "      <td>0.0684%</td>\n",
       "      <td>0.7015%</td>\n",
       "      <td>0.1909%</td>\n",
       "      <td>0.4772%</td>\n",
       "      <td>0.9283%</td>\n",
       "      <td>0.9912%</td>\n",
       "      <td>0.1761%</td>\n",
       "      <td>0.2252%</td>\n",
       "      <td>0.1002%</td>\n",
       "      <td>...</td>\n",
       "      <td>1.1712%</td>\n",
       "      <td>-0.1122%</td>\n",
       "      <td>0.8782%</td>\n",
       "      <td>0.3502%</td>\n",
       "      <td>0.6946%</td>\n",
       "      <td>0.1709%</td>\n",
       "      <td>0.5662%</td>\n",
       "      <td>-0.2137%</td>\n",
       "      <td>0.9753%</td>\n",
       "      <td>-0.3551%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-06 00:00:00-05:00</th>\n",
       "      <td>-2.8766%</td>\n",
       "      <td>-1.2758%</td>\n",
       "      <td>-0.6189%</td>\n",
       "      <td>-0.9939%</td>\n",
       "      <td>-0.8928%</td>\n",
       "      <td>-0.5879%</td>\n",
       "      <td>-0.3663%</td>\n",
       "      <td>-1.6301%</td>\n",
       "      <td>-2.2664%</td>\n",
       "      <td>-1.2376%</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0189%</td>\n",
       "      <td>-2.1655%</td>\n",
       "      <td>-0.0371%</td>\n",
       "      <td>-1.3275%</td>\n",
       "      <td>-1.3599%</td>\n",
       "      <td>-1.3348%</td>\n",
       "      <td>-1.0117%</td>\n",
       "      <td>-1.8914%</td>\n",
       "      <td>-0.9195%</td>\n",
       "      <td>-2.5117%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-07 00:00:00-05:00</th>\n",
       "      <td>-2.6603%</td>\n",
       "      <td>-2.6676%</td>\n",
       "      <td>-1.9233%</td>\n",
       "      <td>-1.9591%</td>\n",
       "      <td>-1.9763%</td>\n",
       "      <td>-1.2059%</td>\n",
       "      <td>-0.9113%</td>\n",
       "      <td>-2.3282%</td>\n",
       "      <td>-2.6834%</td>\n",
       "      <td>-1.8334%</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.8785%</td>\n",
       "      <td>-2.6708%</td>\n",
       "      <td>-1.0103%</td>\n",
       "      <td>-1.9321%</td>\n",
       "      <td>-1.3673%</td>\n",
       "      <td>-1.5868%</td>\n",
       "      <td>-2.5264%</td>\n",
       "      <td>-2.5833%</td>\n",
       "      <td>-1.1151%</td>\n",
       "      <td>-2.2578%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-08 00:00:00-05:00</th>\n",
       "      <td>-1.6385%</td>\n",
       "      <td>-1.2855%</td>\n",
       "      <td>-1.0494%</td>\n",
       "      <td>-0.9502%</td>\n",
       "      <td>-1.0563%</td>\n",
       "      <td>-1.0629%</td>\n",
       "      <td>-0.9909%</td>\n",
       "      <td>-1.2707%</td>\n",
       "      <td>-1.3400%</td>\n",
       "      <td>-1.0335%</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.9977%</td>\n",
       "      <td>-1.3239%</td>\n",
       "      <td>-0.9137%</td>\n",
       "      <td>-1.2706%</td>\n",
       "      <td>-0.9353%</td>\n",
       "      <td>-0.7750%</td>\n",
       "      <td>-1.2535%</td>\n",
       "      <td>-1.3153%</td>\n",
       "      <td>-0.9453%</td>\n",
       "      <td>-1.1138%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11 00:00:00-05:00</th>\n",
       "      <td>-2.1923%</td>\n",
       "      <td>-0.0564%</td>\n",
       "      <td>0.3345%</td>\n",
       "      <td>0.0940%</td>\n",
       "      <td>0.1556%</td>\n",
       "      <td>-0.0892%</td>\n",
       "      <td>-0.0996%</td>\n",
       "      <td>-0.6705%</td>\n",
       "      <td>-0.7531%</td>\n",
       "      <td>-0.5542%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2116%</td>\n",
       "      <td>-0.7575%</td>\n",
       "      <td>0.3162%</td>\n",
       "      <td>-0.5897%</td>\n",
       "      <td>-0.4231%</td>\n",
       "      <td>-0.4203%</td>\n",
       "      <td>0.3350%</td>\n",
       "      <td>-0.8259%</td>\n",
       "      <td>-0.1979%</td>\n",
       "      <td>-1.4465%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-23 00:00:00-05:00</th>\n",
       "      <td>0.6972%</td>\n",
       "      <td>0.2476%</td>\n",
       "      <td>-0.4231%</td>\n",
       "      <td>-0.0181%</td>\n",
       "      <td>-0.1988%</td>\n",
       "      <td>-0.5600%</td>\n",
       "      <td>-0.7397%</td>\n",
       "      <td>0.1196%</td>\n",
       "      <td>0.1321%</td>\n",
       "      <td>0.0606%</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.8527%</td>\n",
       "      <td>0.4842%</td>\n",
       "      <td>-0.6862%</td>\n",
       "      <td>-0.1714%</td>\n",
       "      <td>-0.3171%</td>\n",
       "      <td>0.1146%</td>\n",
       "      <td>-0.2473%</td>\n",
       "      <td>0.3183%</td>\n",
       "      <td>-0.5772%</td>\n",
       "      <td>0.6376%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-24 00:00:00-05:00</th>\n",
       "      <td>-0.1965%</td>\n",
       "      <td>0.0028%</td>\n",
       "      <td>0.1506%</td>\n",
       "      <td>-0.0503%</td>\n",
       "      <td>0.0391%</td>\n",
       "      <td>0.0929%</td>\n",
       "      <td>0.1005%</td>\n",
       "      <td>0.0557%</td>\n",
       "      <td>-0.0072%</td>\n",
       "      <td>0.0206%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1566%</td>\n",
       "      <td>-0.1185%</td>\n",
       "      <td>0.0728%</td>\n",
       "      <td>-0.0238%</td>\n",
       "      <td>0.0208%</td>\n",
       "      <td>0.0304%</td>\n",
       "      <td>0.0896%</td>\n",
       "      <td>-0.0882%</td>\n",
       "      <td>0.0777%</td>\n",
       "      <td>-0.0760%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-26 00:00:00-05:00</th>\n",
       "      <td>0.0839%</td>\n",
       "      <td>0.3934%</td>\n",
       "      <td>0.3568%</td>\n",
       "      <td>0.2717%</td>\n",
       "      <td>0.3344%</td>\n",
       "      <td>0.2787%</td>\n",
       "      <td>0.1966%</td>\n",
       "      <td>0.3099%</td>\n",
       "      <td>0.3689%</td>\n",
       "      <td>0.2053%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2526%</td>\n",
       "      <td>0.3537%</td>\n",
       "      <td>0.2094%</td>\n",
       "      <td>0.2125%</td>\n",
       "      <td>0.2761%</td>\n",
       "      <td>0.2577%</td>\n",
       "      <td>0.4284%</td>\n",
       "      <td>0.2202%</td>\n",
       "      <td>0.2812%</td>\n",
       "      <td>0.2258%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-27 00:00:00-05:00</th>\n",
       "      <td>-0.7229%</td>\n",
       "      <td>-0.0384%</td>\n",
       "      <td>0.2654%</td>\n",
       "      <td>-0.0101%</td>\n",
       "      <td>0.1392%</td>\n",
       "      <td>0.3665%</td>\n",
       "      <td>0.3917%</td>\n",
       "      <td>-0.1305%</td>\n",
       "      <td>-0.2432%</td>\n",
       "      <td>-0.1203%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5586%</td>\n",
       "      <td>-0.2999%</td>\n",
       "      <td>0.4284%</td>\n",
       "      <td>-0.0293%</td>\n",
       "      <td>0.0874%</td>\n",
       "      <td>-0.1122%</td>\n",
       "      <td>0.1726%</td>\n",
       "      <td>-0.3568%</td>\n",
       "      <td>0.2897%</td>\n",
       "      <td>-0.5416%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-30 00:00:00-05:00</th>\n",
       "      <td>-0.0583%</td>\n",
       "      <td>0.0476%</td>\n",
       "      <td>0.0293%</td>\n",
       "      <td>-0.0261%</td>\n",
       "      <td>0.0082%</td>\n",
       "      <td>0.0074%</td>\n",
       "      <td>-0.0320%</td>\n",
       "      <td>0.0439%</td>\n",
       "      <td>0.0207%</td>\n",
       "      <td>0.0054%</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0045%</td>\n",
       "      <td>0.0257%</td>\n",
       "      <td>-0.0422%</td>\n",
       "      <td>-0.0464%</td>\n",
       "      <td>0.0022%</td>\n",
       "      <td>0.0473%</td>\n",
       "      <td>0.0243%</td>\n",
       "      <td>-0.0347%</td>\n",
       "      <td>0.0028%</td>\n",
       "      <td>0.0447%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1004 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               APA       BA      BAX      BMY    CMCSA  \\\n",
       "2016-01-05 00:00:00-05:00 -0.6212%  0.0684%  0.7015%  0.1909%  0.4772%   \n",
       "2016-01-06 00:00:00-05:00 -2.8766% -1.2758% -0.6189% -0.9939% -0.8928%   \n",
       "2016-01-07 00:00:00-05:00 -2.6603% -2.6676% -1.9233% -1.9591% -1.9763%   \n",
       "2016-01-08 00:00:00-05:00 -1.6385% -1.2855% -1.0494% -0.9502% -1.0563%   \n",
       "2016-01-11 00:00:00-05:00 -2.1923% -0.0564%  0.3345%  0.0940%  0.1556%   \n",
       "...                            ...      ...      ...      ...      ...   \n",
       "2019-12-23 00:00:00-05:00  0.6972%  0.2476% -0.4231% -0.0181% -0.1988%   \n",
       "2019-12-24 00:00:00-05:00 -0.1965%  0.0028%  0.1506% -0.0503%  0.0391%   \n",
       "2019-12-26 00:00:00-05:00  0.0839%  0.3934%  0.3568%  0.2717%  0.3344%   \n",
       "2019-12-27 00:00:00-05:00 -0.7229% -0.0384%  0.2654% -0.0101%  0.1392%   \n",
       "2019-12-30 00:00:00-05:00 -0.0583%  0.0476%  0.0293% -0.0261%  0.0082%   \n",
       "\n",
       "                               CNP      CPB       DE      HPQ      JCI  ...  \\\n",
       "2016-01-05 00:00:00-05:00  0.9283%  0.9912%  0.1761%  0.2252%  0.1002%  ...   \n",
       "2016-01-06 00:00:00-05:00 -0.5879% -0.3663% -1.6301% -2.2664% -1.2376%  ...   \n",
       "2016-01-07 00:00:00-05:00 -1.2059% -0.9113% -2.3282% -2.6834% -1.8334%  ...   \n",
       "2016-01-08 00:00:00-05:00 -1.0629% -0.9909% -1.2707% -1.3400% -1.0335%  ...   \n",
       "2016-01-11 00:00:00-05:00 -0.0892% -0.0996% -0.6705% -0.7531% -0.5542%  ...   \n",
       "...                            ...      ...      ...      ...      ...  ...   \n",
       "2019-12-23 00:00:00-05:00 -0.5600% -0.7397%  0.1196%  0.1321%  0.0606%  ...   \n",
       "2019-12-24 00:00:00-05:00  0.0929%  0.1005%  0.0557% -0.0072%  0.0206%  ...   \n",
       "2019-12-26 00:00:00-05:00  0.2787%  0.1966%  0.3099%  0.3689%  0.2053%  ...   \n",
       "2019-12-27 00:00:00-05:00  0.3665%  0.3917% -0.1305% -0.2432% -0.1203%  ...   \n",
       "2019-12-30 00:00:00-05:00  0.0074% -0.0320%  0.0439%  0.0207%  0.0054%  ...   \n",
       "\n",
       "                                NI     PCAR      PSA      SEE        T  \\\n",
       "2016-01-05 00:00:00-05:00  1.1712% -0.1122%  0.8782%  0.3502%  0.6946%   \n",
       "2016-01-06 00:00:00-05:00 -0.0189% -2.1655% -0.0371% -1.3275% -1.3599%   \n",
       "2016-01-07 00:00:00-05:00 -0.8785% -2.6708% -1.0103% -1.9321% -1.3673%   \n",
       "2016-01-08 00:00:00-05:00 -0.9977% -1.3239% -0.9137% -1.2706% -0.9353%   \n",
       "2016-01-11 00:00:00-05:00  0.2116% -0.7575%  0.3162% -0.5897% -0.4231%   \n",
       "...                            ...      ...      ...      ...      ...   \n",
       "2019-12-23 00:00:00-05:00 -0.8527%  0.4842% -0.6862% -0.1714% -0.3171%   \n",
       "2019-12-24 00:00:00-05:00  0.1566% -0.1185%  0.0728% -0.0238%  0.0208%   \n",
       "2019-12-26 00:00:00-05:00  0.2526%  0.3537%  0.2094%  0.2125%  0.2761%   \n",
       "2019-12-27 00:00:00-05:00  0.5586% -0.2999%  0.4284% -0.0293%  0.0874%   \n",
       "2019-12-30 00:00:00-05:00 -0.0045%  0.0257% -0.0422% -0.0464%  0.0022%   \n",
       "\n",
       "                               TGT      TMO      TXT       VZ     ZION  \n",
       "2016-01-05 00:00:00-05:00  0.1709%  0.5662% -0.2137%  0.9753% -0.3551%  \n",
       "2016-01-06 00:00:00-05:00 -1.3348% -1.0117% -1.8914% -0.9195% -2.5117%  \n",
       "2016-01-07 00:00:00-05:00 -1.5868% -2.5264% -2.5833% -1.1151% -2.2578%  \n",
       "2016-01-08 00:00:00-05:00 -0.7750% -1.2535% -1.3153% -0.9453% -1.1138%  \n",
       "2016-01-11 00:00:00-05:00 -0.4203%  0.3350% -0.8259% -0.1979% -1.4465%  \n",
       "...                            ...      ...      ...      ...      ...  \n",
       "2019-12-23 00:00:00-05:00  0.1146% -0.2473%  0.3183% -0.5772%  0.6376%  \n",
       "2019-12-24 00:00:00-05:00  0.0304%  0.0896% -0.0882%  0.0777% -0.0760%  \n",
       "2019-12-26 00:00:00-05:00  0.2577%  0.4284%  0.2202%  0.2812%  0.2258%  \n",
       "2019-12-27 00:00:00-05:00 -0.1122%  0.1726% -0.3568%  0.2897% -0.5416%  \n",
       "2019-12-30 00:00:00-05:00  0.0473%  0.0243% -0.0347%  0.0028%  0.0447%  \n",
       "\n",
       "[1004 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(returns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Estimating Portfolios Using Risk Factors with Other Risk Measures\n",
    "\n",
    "In this part I will calculate optimal portfolios for several risk measures. I will find the portfolios that maximize the risk adjusted return for all available risk measures.\n",
    "\n",
    "### 4.1 Calculate Optimal Portfolios for Several Risk Measures.\n",
    "\n",
    "I will mantain the constraints on risk factors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Risk Measures available:\n",
    "#\n",
    "# 'MV': Standard Deviation.\n",
    "# 'MAD': Mean Absolute Deviation.\n",
    "# 'MSV': Semi Standard Deviation.\n",
    "# 'FLPM': First Lower Partial Moment (Omega Ratio).\n",
    "# 'SLPM': Second Lower Partial Moment (Sortino Ratio).\n",
    "# 'CVaR': Conditional Value at Risk.\n",
    "# 'EVaR': Entropic Value at Risk.\n",
    "# 'WR': Worst Realization (Minimax)\n",
    "# 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).\n",
    "# 'ADD': Average Drawdown of uncompounded cumulative returns.\n",
    "# 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.\n",
    "# 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.\n",
    "# 'UCI': Ulcer Index of uncompounded cumulative returns.\n",
    "\n",
    "# port.reset_linear_constraints() # To reset linear constraints (factor constraints)\n",
    "\n",
    "rms = ['MV', 'MAD', 'MSV', 'FLPM', 'SLPM', 'CVaR',\n",
    "       'EVaR', 'WR', 'MDD', 'ADD', 'CDaR', 'UCI', 'EDaR']\n",
    "\n",
    "w_s = pd.DataFrame([])\n",
    "\n",
    "# When we use hist = True the risk measures all calculated\n",
    "# using historical returns, while when hist = False the\n",
    "# risk measures are calculated using the expected returns \n",
    "#  based on risk factor model: R = a + B * F\n",
    "\n",
    "hist = False\n",
    "for i in rms:\n",
    "    w = port.optimization(model=model, rm=i, obj=obj, rf=rf, l=l, hist=hist)\n",
    "    w_s = pd.concat([w_s, w], axis=1)\n",
    "    \n",
    "w_s.columns = rms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_aa9f6_row0_col0, #T_aa9f6_row0_col1, #T_aa9f6_row0_col2, #T_aa9f6_row0_col3, #T_aa9f6_row0_col4, #T_aa9f6_row0_col5, #T_aa9f6_row0_col6, #T_aa9f6_row0_col7, #T_aa9f6_row0_col8, #T_aa9f6_row0_col9, #T_aa9f6_row0_col10, #T_aa9f6_row0_col11, #T_aa9f6_row0_col12, #T_aa9f6_row1_col1, #T_aa9f6_row1_col2, #T_aa9f6_row1_col3, #T_aa9f6_row1_col4, #T_aa9f6_row1_col5, #T_aa9f6_row1_col6, #T_aa9f6_row1_col7, #T_aa9f6_row1_col8, #T_aa9f6_row1_col9, #T_aa9f6_row1_col10, #T_aa9f6_row1_col11, #T_aa9f6_row1_col12, #T_aa9f6_row2_col1, #T_aa9f6_row2_col2, #T_aa9f6_row2_col3, #T_aa9f6_row2_col4, #T_aa9f6_row2_col5, #T_aa9f6_row2_col6, #T_aa9f6_row2_col7, #T_aa9f6_row2_col8, #T_aa9f6_row2_col9, #T_aa9f6_row2_col10, #T_aa9f6_row2_col11, #T_aa9f6_row2_col12, #T_aa9f6_row3_col0, #T_aa9f6_row3_col1, #T_aa9f6_row3_col2, #T_aa9f6_row3_col3, #T_aa9f6_row3_col4, #T_aa9f6_row3_col5, #T_aa9f6_row3_col6, #T_aa9f6_row3_col7, #T_aa9f6_row3_col8, #T_aa9f6_row3_col9, #T_aa9f6_row3_col10, #T_aa9f6_row3_col11, #T_aa9f6_row3_col12, #T_aa9f6_row4_col0, #T_aa9f6_row4_col1, #T_aa9f6_row4_col2, #T_aa9f6_row4_col3, #T_aa9f6_row4_col4, #T_aa9f6_row4_col5, #T_aa9f6_row4_col6, #T_aa9f6_row4_col7, #T_aa9f6_row4_col8, #T_aa9f6_row4_col9, #T_aa9f6_row4_col10, #T_aa9f6_row4_col11, #T_aa9f6_row4_col12, #T_aa9f6_row5_col8, #T_aa9f6_row6_col0, #T_aa9f6_row6_col1, #T_aa9f6_row6_col2, #T_aa9f6_row6_col3, #T_aa9f6_row6_col4, #T_aa9f6_row6_col5, #T_aa9f6_row6_col6, #T_aa9f6_row6_col7, #T_aa9f6_row6_col8, #T_aa9f6_row6_col9, #T_aa9f6_row6_col10, #T_aa9f6_row6_col11, #T_aa9f6_row6_col12, #T_aa9f6_row7_col1, #T_aa9f6_row7_col2, #T_aa9f6_row7_col3, #T_aa9f6_row7_col4, #T_aa9f6_row7_col5, #T_aa9f6_row7_col6, #T_aa9f6_row7_col7, #T_aa9f6_row7_col8, #T_aa9f6_row7_col9, #T_aa9f6_row7_col10, #T_aa9f6_row7_col11, #T_aa9f6_row7_col12, #T_aa9f6_row8_col0, #T_aa9f6_row8_col1, #T_aa9f6_row8_col2, #T_aa9f6_row8_col3, #T_aa9f6_row8_col4, #T_aa9f6_row8_col5, #T_aa9f6_row8_col6, #T_aa9f6_row8_col7, #T_aa9f6_row8_col8, #T_aa9f6_row8_col9, #T_aa9f6_row8_col10, #T_aa9f6_row8_col11, #T_aa9f6_row8_col12, #T_aa9f6_row9_col0, #T_aa9f6_row9_col1, #T_aa9f6_row9_col2, #T_aa9f6_row9_col3, #T_aa9f6_row9_col4, #T_aa9f6_row9_col5, #T_aa9f6_row9_col6, #T_aa9f6_row9_col7, #T_aa9f6_row9_col8, #T_aa9f6_row9_col9, #T_aa9f6_row9_col10, #T_aa9f6_row9_col11, #T_aa9f6_row9_col12, #T_aa9f6_row10_col1, #T_aa9f6_row10_col2, #T_aa9f6_row10_col3, #T_aa9f6_row10_col4, #T_aa9f6_row10_col5, #T_aa9f6_row10_col6, #T_aa9f6_row10_col7, #T_aa9f6_row10_col8, #T_aa9f6_row10_col9, #T_aa9f6_row10_col10, #T_aa9f6_row10_col11, #T_aa9f6_row10_col12, #T_aa9f6_row11_col0, #T_aa9f6_row11_col1, #T_aa9f6_row11_col2, #T_aa9f6_row11_col3, #T_aa9f6_row11_col4, #T_aa9f6_row11_col5, #T_aa9f6_row11_col6, #T_aa9f6_row11_col7, #T_aa9f6_row11_col8, #T_aa9f6_row11_col9, #T_aa9f6_row11_col10, #T_aa9f6_row11_col11, #T_aa9f6_row11_col12, #T_aa9f6_row12_col2, #T_aa9f6_row12_col4, #T_aa9f6_row12_col5, #T_aa9f6_row12_col6, #T_aa9f6_row12_col7, #T_aa9f6_row12_col8, #T_aa9f6_row12_col12, #T_aa9f6_row13_col0, #T_aa9f6_row13_col1, #T_aa9f6_row13_col2, #T_aa9f6_row13_col3, #T_aa9f6_row13_col4, #T_aa9f6_row13_col5, #T_aa9f6_row13_col6, #T_aa9f6_row13_col7, #T_aa9f6_row13_col8, #T_aa9f6_row13_col9, #T_aa9f6_row13_col10, #T_aa9f6_row13_col11, #T_aa9f6_row13_col12, #T_aa9f6_row14_col0, #T_aa9f6_row14_col1, #T_aa9f6_row14_col2, #T_aa9f6_row14_col3, #T_aa9f6_row14_col4, #T_aa9f6_row14_col5, #T_aa9f6_row14_col6, #T_aa9f6_row14_col7, #T_aa9f6_row14_col8, #T_aa9f6_row14_col9, #T_aa9f6_row14_col10, #T_aa9f6_row14_col11, #T_aa9f6_row14_col12, #T_aa9f6_row15_col1, #T_aa9f6_row15_col2, #T_aa9f6_row15_col3, #T_aa9f6_row15_col4, #T_aa9f6_row15_col6, #T_aa9f6_row15_col7, #T_aa9f6_row15_col9, #T_aa9f6_row15_col10, #T_aa9f6_row15_col11, #T_aa9f6_row16_col1, #T_aa9f6_row16_col2, #T_aa9f6_row16_col3, #T_aa9f6_row16_col4, #T_aa9f6_row16_col5, #T_aa9f6_row16_col6, #T_aa9f6_row16_col7, #T_aa9f6_row16_col8, #T_aa9f6_row16_col9, #T_aa9f6_row16_col10, #T_aa9f6_row16_col11, #T_aa9f6_row16_col12, #T_aa9f6_row17_col0, #T_aa9f6_row17_col1, #T_aa9f6_row17_col2, #T_aa9f6_row17_col3, #T_aa9f6_row17_col4, #T_aa9f6_row17_col5, #T_aa9f6_row17_col6, #T_aa9f6_row17_col7, #T_aa9f6_row17_col8, #T_aa9f6_row17_col9, #T_aa9f6_row17_col10, #T_aa9f6_row17_col11, #T_aa9f6_row17_col12, #T_aa9f6_row18_col0, #T_aa9f6_row18_col1, #T_aa9f6_row18_col2, #T_aa9f6_row18_col3, #T_aa9f6_row18_col4, #T_aa9f6_row18_col5, #T_aa9f6_row18_col6, #T_aa9f6_row18_col7, #T_aa9f6_row18_col8, #T_aa9f6_row18_col9, #T_aa9f6_row18_col10, #T_aa9f6_row18_col11, #T_aa9f6_row18_col12, #T_aa9f6_row19_col1, #T_aa9f6_row19_col2, #T_aa9f6_row19_col3, #T_aa9f6_row19_col4, #T_aa9f6_row19_col5, #T_aa9f6_row19_col6, #T_aa9f6_row19_col7, #T_aa9f6_row19_col8, #T_aa9f6_row19_col9, #T_aa9f6_row19_col10, #T_aa9f6_row19_col11, #T_aa9f6_row19_col12, #T_aa9f6_row21_col0, #T_aa9f6_row21_col1, #T_aa9f6_row21_col2, #T_aa9f6_row21_col3, #T_aa9f6_row21_col4, #T_aa9f6_row21_col5, #T_aa9f6_row21_col6, #T_aa9f6_row21_col7, #T_aa9f6_row21_col8, #T_aa9f6_row21_col9, #T_aa9f6_row21_col10, #T_aa9f6_row21_col11, #T_aa9f6_row21_col12, #T_aa9f6_row22_col0, #T_aa9f6_row22_col1, #T_aa9f6_row22_col2, #T_aa9f6_row22_col3, #T_aa9f6_row22_col4, #T_aa9f6_row22_col5, #T_aa9f6_row22_col6, #T_aa9f6_row22_col7, #T_aa9f6_row22_col8, #T_aa9f6_row22_col9, #T_aa9f6_row22_col10, #T_aa9f6_row22_col11, #T_aa9f6_row22_col12, #T_aa9f6_row23_col1, #T_aa9f6_row23_col2, #T_aa9f6_row23_col3, #T_aa9f6_row23_col4, #T_aa9f6_row23_col5, #T_aa9f6_row23_col6, #T_aa9f6_row23_col7, #T_aa9f6_row23_col8, #T_aa9f6_row23_col9, #T_aa9f6_row23_col10, #T_aa9f6_row23_col11, #T_aa9f6_row23_col12, #T_aa9f6_row24_col1, #T_aa9f6_row24_col2, #T_aa9f6_row24_col3, #T_aa9f6_row24_col4, #T_aa9f6_row24_col5, #T_aa9f6_row24_col6, #T_aa9f6_row24_col8, #T_aa9f6_row24_col9, #T_aa9f6_row24_col10, #T_aa9f6_row24_col11, #T_aa9f6_row24_col12 {\n",
       "  background-color: #ffffe5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row1_col0, #T_aa9f6_row24_col7 {\n",
       "  background-color: #ddf1a6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row2_col0 {\n",
       "  background-color: #fcfed3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row5_col0 {\n",
       "  background-color: #42ab5d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_aa9f6_row5_col1, #T_aa9f6_row5_col2, #T_aa9f6_row5_col3, #T_aa9f6_row5_col4, #T_aa9f6_row5_col6, #T_aa9f6_row5_col7, #T_aa9f6_row5_col9, #T_aa9f6_row5_col11, #T_aa9f6_row5_col12, #T_aa9f6_row12_col0, #T_aa9f6_row12_col10, #T_aa9f6_row15_col8, #T_aa9f6_row20_col5 {\n",
       "  background-color: #004529;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_aa9f6_row5_col5 {\n",
       "  background-color: #00542f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_aa9f6_row5_col10 {\n",
       "  background-color: #a7db8c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row7_col0 {\n",
       "  background-color: #f2fab5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row10_col0 {\n",
       "  background-color: #b9e294;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row12_col1 {\n",
       "  background-color: #5fba6c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_aa9f6_row12_col3 {\n",
       "  background-color: #56b568;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_aa9f6_row12_col9 {\n",
       "  background-color: #c9e99c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row12_col11 {\n",
       "  background-color: #c0e597;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row15_col0 {\n",
       "  background-color: #79c679;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row15_col5 {\n",
       "  background-color: #bae394;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row15_col12 {\n",
       "  background-color: #f7fcba;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row16_col0 {\n",
       "  background-color: #fcfed4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row19_col0 {\n",
       "  background-color: #feffe2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row20_col0 {\n",
       "  background-color: #eff9b3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row20_col1, #T_aa9f6_row20_col3 {\n",
       "  background-color: #13773d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_aa9f6_row20_col2, #T_aa9f6_row20_col4, #T_aa9f6_row20_col6 {\n",
       "  background-color: #026a38;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_aa9f6_row20_col7 {\n",
       "  background-color: #11753d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_aa9f6_row20_col8 {\n",
       "  background-color: #62bb6e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_aa9f6_row20_col9, #T_aa9f6_row20_col11 {\n",
       "  background-color: #0b713b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_aa9f6_row20_col10 {\n",
       "  background-color: #ddf2a6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row20_col12 {\n",
       "  background-color: #005830;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_aa9f6_row23_col0 {\n",
       "  background-color: #acdd8e;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_aa9f6_row24_col0 {\n",
       "  background-color: #fafdcb;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_aa9f6\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_aa9f6_level0_col0\" class=\"col_heading level0 col0\" >MV</th>\n",
       "      <th id=\"T_aa9f6_level0_col1\" class=\"col_heading level0 col1\" >MAD</th>\n",
       "      <th id=\"T_aa9f6_level0_col2\" class=\"col_heading level0 col2\" >MSV</th>\n",
       "      <th id=\"T_aa9f6_level0_col3\" class=\"col_heading level0 col3\" >FLPM</th>\n",
       "      <th id=\"T_aa9f6_level0_col4\" class=\"col_heading level0 col4\" >SLPM</th>\n",
       "      <th id=\"T_aa9f6_level0_col5\" class=\"col_heading level0 col5\" >CVaR</th>\n",
       "      <th id=\"T_aa9f6_level0_col6\" class=\"col_heading level0 col6\" >EVaR</th>\n",
       "      <th id=\"T_aa9f6_level0_col7\" class=\"col_heading level0 col7\" >WR</th>\n",
       "      <th id=\"T_aa9f6_level0_col8\" class=\"col_heading level0 col8\" >MDD</th>\n",
       "      <th id=\"T_aa9f6_level0_col9\" class=\"col_heading level0 col9\" >ADD</th>\n",
       "      <th id=\"T_aa9f6_level0_col10\" class=\"col_heading level0 col10\" >CDaR</th>\n",
       "      <th id=\"T_aa9f6_level0_col11\" class=\"col_heading level0 col11\" >UCI</th>\n",
       "      <th id=\"T_aa9f6_level0_col12\" class=\"col_heading level0 col12\" >EDaR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row0\" class=\"row_heading level0 row0\" >APA</th>\n",
       "      <td id=\"T_aa9f6_row0_col0\" class=\"data row0 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row0_col1\" class=\"data row0 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row0_col2\" class=\"data row0 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row0_col3\" class=\"data row0 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row0_col4\" class=\"data row0 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row0_col5\" class=\"data row0 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row0_col6\" class=\"data row0 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row0_col7\" class=\"data row0 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row0_col8\" class=\"data row0 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row0_col9\" class=\"data row0 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row0_col10\" class=\"data row0 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row0_col11\" class=\"data row0 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row0_col12\" class=\"data row0 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row1\" class=\"row_heading level0 row1\" >BA</th>\n",
       "      <td id=\"T_aa9f6_row1_col0\" class=\"data row1 col0\" >6.58%</td>\n",
       "      <td id=\"T_aa9f6_row1_col1\" class=\"data row1 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row1_col2\" class=\"data row1 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row1_col3\" class=\"data row1 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row1_col4\" class=\"data row1 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row1_col5\" class=\"data row1 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row1_col6\" class=\"data row1 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row1_col7\" class=\"data row1 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row1_col8\" class=\"data row1 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row1_col9\" class=\"data row1 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row1_col10\" class=\"data row1 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row1_col11\" class=\"data row1 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row1_col12\" class=\"data row1 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row2\" class=\"row_heading level0 row2\" >BAX</th>\n",
       "      <td id=\"T_aa9f6_row2_col0\" class=\"data row2 col0\" >1.49%</td>\n",
       "      <td id=\"T_aa9f6_row2_col1\" class=\"data row2 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row2_col2\" class=\"data row2 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row2_col3\" class=\"data row2 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row2_col4\" class=\"data row2 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row2_col5\" class=\"data row2 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row2_col6\" class=\"data row2 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row2_col7\" class=\"data row2 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row2_col8\" class=\"data row2 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row2_col9\" class=\"data row2 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row2_col10\" class=\"data row2 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row2_col11\" class=\"data row2 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row2_col12\" class=\"data row2 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row3\" class=\"row_heading level0 row3\" >BMY</th>\n",
       "      <td id=\"T_aa9f6_row3_col0\" class=\"data row3 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row3_col1\" class=\"data row3 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row3_col2\" class=\"data row3 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row3_col3\" class=\"data row3 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row3_col4\" class=\"data row3 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row3_col5\" class=\"data row3 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row3_col6\" class=\"data row3 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row3_col7\" class=\"data row3 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row3_col8\" class=\"data row3 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row3_col9\" class=\"data row3 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row3_col10\" class=\"data row3 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row3_col11\" class=\"data row3 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row3_col12\" class=\"data row3 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row4\" class=\"row_heading level0 row4\" >CMCSA</th>\n",
       "      <td id=\"T_aa9f6_row4_col0\" class=\"data row4 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row4_col1\" class=\"data row4 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row4_col2\" class=\"data row4 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row4_col3\" class=\"data row4 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row4_col4\" class=\"data row4 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row4_col5\" class=\"data row4 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row4_col6\" class=\"data row4 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row4_col7\" class=\"data row4 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row4_col8\" class=\"data row4 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row4_col9\" class=\"data row4 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row4_col10\" class=\"data row4 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row4_col11\" class=\"data row4 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row4_col12\" class=\"data row4 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row5\" class=\"row_heading level0 row5\" >CNP</th>\n",
       "      <td id=\"T_aa9f6_row5_col0\" class=\"data row5 col0\" >17.48%</td>\n",
       "      <td id=\"T_aa9f6_row5_col1\" class=\"data row5 col1\" >42.32%</td>\n",
       "      <td id=\"T_aa9f6_row5_col2\" class=\"data row5 col2\" >53.62%</td>\n",
       "      <td id=\"T_aa9f6_row5_col3\" class=\"data row5 col3\" >41.97%</td>\n",
       "      <td id=\"T_aa9f6_row5_col4\" class=\"data row5 col4\" >53.62%</td>\n",
       "      <td id=\"T_aa9f6_row5_col5\" class=\"data row5 col5\" >41.32%</td>\n",
       "      <td id=\"T_aa9f6_row5_col6\" class=\"data row5 col6\" >53.62%</td>\n",
       "      <td id=\"T_aa9f6_row5_col7\" class=\"data row5 col7\" >48.75%</td>\n",
       "      <td id=\"T_aa9f6_row5_col8\" class=\"data row5 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row5_col9\" class=\"data row5 col9\" >46.96%</td>\n",
       "      <td id=\"T_aa9f6_row5_col10\" class=\"data row5 col10\" >23.97%</td>\n",
       "      <td id=\"T_aa9f6_row5_col11\" class=\"data row5 col11\" >46.45%</td>\n",
       "      <td id=\"T_aa9f6_row5_col12\" class=\"data row5 col12\" >48.69%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row6\" class=\"row_heading level0 row6\" >CPB</th>\n",
       "      <td id=\"T_aa9f6_row6_col0\" class=\"data row6 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row6_col1\" class=\"data row6 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row6_col2\" class=\"data row6 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row6_col3\" class=\"data row6 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row6_col4\" class=\"data row6 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row6_col5\" class=\"data row6 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row6_col6\" class=\"data row6 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row6_col7\" class=\"data row6 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row6_col8\" class=\"data row6 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row6_col9\" class=\"data row6 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row6_col10\" class=\"data row6 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row6_col11\" class=\"data row6 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row6_col12\" class=\"data row6 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row7\" class=\"row_heading level0 row7\" >DE</th>\n",
       "      <td id=\"T_aa9f6_row7_col0\" class=\"data row7 col0\" >4.09%</td>\n",
       "      <td id=\"T_aa9f6_row7_col1\" class=\"data row7 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row7_col2\" class=\"data row7 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row7_col3\" class=\"data row7 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row7_col4\" class=\"data row7 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row7_col5\" class=\"data row7 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row7_col6\" class=\"data row7 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row7_col7\" class=\"data row7 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row7_col8\" class=\"data row7 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row7_col9\" class=\"data row7 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row7_col10\" class=\"data row7 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row7_col11\" class=\"data row7 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row7_col12\" class=\"data row7 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row8\" class=\"row_heading level0 row8\" >HPQ</th>\n",
       "      <td id=\"T_aa9f6_row8_col0\" class=\"data row8 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row8_col1\" class=\"data row8 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row8_col2\" class=\"data row8 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row8_col3\" class=\"data row8 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row8_col4\" class=\"data row8 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row8_col5\" class=\"data row8 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row8_col6\" class=\"data row8 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row8_col7\" class=\"data row8 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row8_col8\" class=\"data row8 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row8_col9\" class=\"data row8 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row8_col10\" class=\"data row8 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row8_col11\" class=\"data row8 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row8_col12\" class=\"data row8 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row9\" class=\"row_heading level0 row9\" >JCI</th>\n",
       "      <td id=\"T_aa9f6_row9_col0\" class=\"data row9 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row9_col1\" class=\"data row9 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row9_col2\" class=\"data row9 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row9_col3\" class=\"data row9 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row9_col4\" class=\"data row9 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row9_col5\" class=\"data row9 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row9_col6\" class=\"data row9 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row9_col7\" class=\"data row9 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row9_col8\" class=\"data row9 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row9_col9\" class=\"data row9 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row9_col10\" class=\"data row9 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row9_col11\" class=\"data row9 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row9_col12\" class=\"data row9 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row10\" class=\"row_heading level0 row10\" >JPM</th>\n",
       "      <td id=\"T_aa9f6_row10_col0\" class=\"data row10 col0\" >9.54%</td>\n",
       "      <td id=\"T_aa9f6_row10_col1\" class=\"data row10 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row10_col2\" class=\"data row10 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row10_col3\" class=\"data row10 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row10_col4\" class=\"data row10 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row10_col5\" class=\"data row10 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row10_col6\" class=\"data row10 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row10_col7\" class=\"data row10 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row10_col8\" class=\"data row10 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row10_col9\" class=\"data row10 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row10_col10\" class=\"data row10 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row10_col11\" class=\"data row10 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row10_col12\" class=\"data row10 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row11\" class=\"row_heading level0 row11\" >LUV</th>\n",
       "      <td id=\"T_aa9f6_row11_col0\" class=\"data row11 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row11_col1\" class=\"data row11 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row11_col2\" class=\"data row11 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row11_col3\" class=\"data row11 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row11_col4\" class=\"data row11 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row11_col5\" class=\"data row11 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row11_col6\" class=\"data row11 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row11_col7\" class=\"data row11 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row11_col8\" class=\"data row11 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row11_col9\" class=\"data row11 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row11_col10\" class=\"data row11 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row11_col11\" class=\"data row11 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row11_col12\" class=\"data row11 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row12\" class=\"row_heading level0 row12\" >MMC</th>\n",
       "      <td id=\"T_aa9f6_row12_col0\" class=\"data row12 col0\" >28.07%</td>\n",
       "      <td id=\"T_aa9f6_row12_col1\" class=\"data row12 col1\" >23.48%</td>\n",
       "      <td id=\"T_aa9f6_row12_col2\" class=\"data row12 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row12_col3\" class=\"data row12 col3\" >24.20%</td>\n",
       "      <td id=\"T_aa9f6_row12_col4\" class=\"data row12 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row12_col5\" class=\"data row12 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row12_col6\" class=\"data row12 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row12_col7\" class=\"data row12 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row12_col8\" class=\"data row12 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row12_col9\" class=\"data row12 col9\" >13.82%</td>\n",
       "      <td id=\"T_aa9f6_row12_col10\" class=\"data row12 col10\" >61.60%</td>\n",
       "      <td id=\"T_aa9f6_row12_col11\" class=\"data row12 col11\" >14.88%</td>\n",
       "      <td id=\"T_aa9f6_row12_col12\" class=\"data row12 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row13\" class=\"row_heading level0 row13\" >MO</th>\n",
       "      <td id=\"T_aa9f6_row13_col0\" class=\"data row13 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row13_col1\" class=\"data row13 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row13_col2\" class=\"data row13 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row13_col3\" class=\"data row13 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row13_col4\" class=\"data row13 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row13_col5\" class=\"data row13 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row13_col6\" class=\"data row13 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row13_col7\" class=\"data row13 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row13_col8\" class=\"data row13 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row13_col9\" class=\"data row13 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row13_col10\" class=\"data row13 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row13_col11\" class=\"data row13 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row13_col12\" class=\"data row13 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row14\" class=\"row_heading level0 row14\" >MSFT</th>\n",
       "      <td id=\"T_aa9f6_row14_col0\" class=\"data row14 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row14_col1\" class=\"data row14 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row14_col2\" class=\"data row14 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row14_col3\" class=\"data row14 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row14_col4\" class=\"data row14 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row14_col5\" class=\"data row14 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row14_col6\" class=\"data row14 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row14_col7\" class=\"data row14 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row14_col8\" class=\"data row14 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row14_col9\" class=\"data row14 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row14_col10\" class=\"data row14 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row14_col11\" class=\"data row14 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row14_col12\" class=\"data row14 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row15\" class=\"row_heading level0 row15\" >NI</th>\n",
       "      <td id=\"T_aa9f6_row15_col0\" class=\"data row15 col0\" >13.97%</td>\n",
       "      <td id=\"T_aa9f6_row15_col1\" class=\"data row15 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row15_col2\" class=\"data row15 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row15_col3\" class=\"data row15 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row15_col4\" class=\"data row15 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row15_col5\" class=\"data row15 col5\" >14.80%</td>\n",
       "      <td id=\"T_aa9f6_row15_col6\" class=\"data row15 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row15_col7\" class=\"data row15 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row15_col8\" class=\"data row15 col8\" >64.54%</td>\n",
       "      <td id=\"T_aa9f6_row15_col9\" class=\"data row15 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row15_col10\" class=\"data row15 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row15_col11\" class=\"data row15 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row15_col12\" class=\"data row15 col12\" >5.93%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row16\" class=\"row_heading level0 row16\" >PCAR</th>\n",
       "      <td id=\"T_aa9f6_row16_col0\" class=\"data row16 col0\" >1.38%</td>\n",
       "      <td id=\"T_aa9f6_row16_col1\" class=\"data row16 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row16_col2\" class=\"data row16 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row16_col3\" class=\"data row16 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row16_col4\" class=\"data row16 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row16_col5\" class=\"data row16 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row16_col6\" class=\"data row16 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row16_col7\" class=\"data row16 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row16_col8\" class=\"data row16 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row16_col9\" class=\"data row16 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row16_col10\" class=\"data row16 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row16_col11\" class=\"data row16 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row16_col12\" class=\"data row16 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row17\" class=\"row_heading level0 row17\" >PSA</th>\n",
       "      <td id=\"T_aa9f6_row17_col0\" class=\"data row17 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row17_col1\" class=\"data row17 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row17_col2\" class=\"data row17 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row17_col3\" class=\"data row17 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row17_col4\" class=\"data row17 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row17_col5\" class=\"data row17 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row17_col6\" class=\"data row17 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row17_col7\" class=\"data row17 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row17_col8\" class=\"data row17 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row17_col9\" class=\"data row17 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row17_col10\" class=\"data row17 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row17_col11\" class=\"data row17 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row17_col12\" class=\"data row17 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row18\" class=\"row_heading level0 row18\" >SEE</th>\n",
       "      <td id=\"T_aa9f6_row18_col0\" class=\"data row18 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row18_col1\" class=\"data row18 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row18_col2\" class=\"data row18 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row18_col3\" class=\"data row18 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row18_col4\" class=\"data row18 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row18_col5\" class=\"data row18 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row18_col6\" class=\"data row18 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row18_col7\" class=\"data row18 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row18_col8\" class=\"data row18 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row18_col9\" class=\"data row18 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row18_col10\" class=\"data row18 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row18_col11\" class=\"data row18 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row18_col12\" class=\"data row18 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row19\" class=\"row_heading level0 row19\" >T</th>\n",
       "      <td id=\"T_aa9f6_row19_col0\" class=\"data row19 col0\" >0.31%</td>\n",
       "      <td id=\"T_aa9f6_row19_col1\" class=\"data row19 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row19_col2\" class=\"data row19 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row19_col3\" class=\"data row19 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row19_col4\" class=\"data row19 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row19_col5\" class=\"data row19 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row19_col6\" class=\"data row19 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row19_col7\" class=\"data row19 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row19_col8\" class=\"data row19 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row19_col9\" class=\"data row19 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row19_col10\" class=\"data row19 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row19_col11\" class=\"data row19 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row19_col12\" class=\"data row19 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row20\" class=\"row_heading level0 row20\" >TGT</th>\n",
       "      <td id=\"T_aa9f6_row20_col0\" class=\"data row20 col0\" >4.41%</td>\n",
       "      <td id=\"T_aa9f6_row20_col1\" class=\"data row20 col1\" >34.20%</td>\n",
       "      <td id=\"T_aa9f6_row20_col2\" class=\"data row20 col2\" >46.38%</td>\n",
       "      <td id=\"T_aa9f6_row20_col3\" class=\"data row20 col3\" >33.83%</td>\n",
       "      <td id=\"T_aa9f6_row20_col4\" class=\"data row20 col4\" >46.38%</td>\n",
       "      <td id=\"T_aa9f6_row20_col5\" class=\"data row20 col5\" >43.88%</td>\n",
       "      <td id=\"T_aa9f6_row20_col6\" class=\"data row20 col6\" >46.38%</td>\n",
       "      <td id=\"T_aa9f6_row20_col7\" class=\"data row20 col7\" >39.77%</td>\n",
       "      <td id=\"T_aa9f6_row20_col8\" class=\"data row20 col8\" >35.46%</td>\n",
       "      <td id=\"T_aa9f6_row20_col9\" class=\"data row20 col9\" >39.21%</td>\n",
       "      <td id=\"T_aa9f6_row20_col10\" class=\"data row20 col10\" >14.43%</td>\n",
       "      <td id=\"T_aa9f6_row20_col11\" class=\"data row20 col11\" >38.66%</td>\n",
       "      <td id=\"T_aa9f6_row20_col12\" class=\"data row20 col12\" >45.38%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row21\" class=\"row_heading level0 row21\" >TMO</th>\n",
       "      <td id=\"T_aa9f6_row21_col0\" class=\"data row21 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row21_col1\" class=\"data row21 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row21_col2\" class=\"data row21 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row21_col3\" class=\"data row21 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row21_col4\" class=\"data row21 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row21_col5\" class=\"data row21 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row21_col6\" class=\"data row21 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row21_col7\" class=\"data row21 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row21_col8\" class=\"data row21 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row21_col9\" class=\"data row21 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row21_col10\" class=\"data row21 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row21_col11\" class=\"data row21 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row21_col12\" class=\"data row21 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row22\" class=\"row_heading level0 row22\" >TXT</th>\n",
       "      <td id=\"T_aa9f6_row22_col0\" class=\"data row22 col0\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row22_col1\" class=\"data row22 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row22_col2\" class=\"data row22 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row22_col3\" class=\"data row22 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row22_col4\" class=\"data row22 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row22_col5\" class=\"data row22 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row22_col6\" class=\"data row22 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row22_col7\" class=\"data row22 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row22_col8\" class=\"data row22 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row22_col9\" class=\"data row22 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row22_col10\" class=\"data row22 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row22_col11\" class=\"data row22 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row22_col12\" class=\"data row22 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row23\" class=\"row_heading level0 row23\" >VZ</th>\n",
       "      <td id=\"T_aa9f6_row23_col0\" class=\"data row23 col0\" >10.58%</td>\n",
       "      <td id=\"T_aa9f6_row23_col1\" class=\"data row23 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row23_col2\" class=\"data row23 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row23_col3\" class=\"data row23 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row23_col4\" class=\"data row23 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row23_col5\" class=\"data row23 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row23_col6\" class=\"data row23 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row23_col7\" class=\"data row23 col7\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row23_col8\" class=\"data row23 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row23_col9\" class=\"data row23 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row23_col10\" class=\"data row23 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row23_col11\" class=\"data row23 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row23_col12\" class=\"data row23 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aa9f6_level0_row24\" class=\"row_heading level0 row24\" >ZION</th>\n",
       "      <td id=\"T_aa9f6_row24_col0\" class=\"data row24 col0\" >2.09%</td>\n",
       "      <td id=\"T_aa9f6_row24_col1\" class=\"data row24 col1\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row24_col2\" class=\"data row24 col2\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row24_col3\" class=\"data row24 col3\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row24_col4\" class=\"data row24 col4\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row24_col5\" class=\"data row24 col5\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row24_col6\" class=\"data row24 col6\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row24_col7\" class=\"data row24 col7\" >11.48%</td>\n",
       "      <td id=\"T_aa9f6_row24_col8\" class=\"data row24 col8\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row24_col9\" class=\"data row24 col9\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row24_col10\" class=\"data row24 col10\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row24_col11\" class=\"data row24 col11\" >0.00%</td>\n",
       "      <td id=\"T_aa9f6_row24_col12\" class=\"data row24 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f8b727cadc0>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_s.style.format(\"{:.2%}\").background_gradient(cmap='YlGn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plotting a comparison of assets weights for each portfolio\n",
    "\n",
    "fig = plt.gcf()\n",
    "fig.set_figwidth(14)\n",
    "fig.set_figheight(6)\n",
    "ax = fig.subplots(nrows=1, ncols=1)\n",
    "\n",
    "w_s.plot.bar(ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "w_s = pd.DataFrame([])\n",
    "\n",
    "# When we use hist = True the risk measures all calculated\n",
    "# using historical returns, while when hist = False the\n",
    "# risk measures are calculated using the expected returns \n",
    "#  based on risk factor model: R = a + B * F\n",
    "\n",
    "hist = True\n",
    "for i in rms:\n",
    "    w = port.optimization(model=model, rm=i, obj=obj, rf=rf, l=l, hist=hist)\n",
    "    w_s = pd.concat([w_s, w], axis=1)\n",
    "    \n",
    "w_s.columns = rms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_bdb0c_row0_col0, #T_bdb0c_row0_col1, #T_bdb0c_row0_col2, #T_bdb0c_row0_col3, #T_bdb0c_row0_col4, #T_bdb0c_row0_col5, #T_bdb0c_row0_col6, #T_bdb0c_row0_col7, #T_bdb0c_row0_col8, #T_bdb0c_row0_col9, #T_bdb0c_row0_col10, #T_bdb0c_row0_col11, #T_bdb0c_row0_col12, #T_bdb0c_row1_col7, #T_bdb0c_row2_col6, #T_bdb0c_row2_col7, #T_bdb0c_row2_col8, #T_bdb0c_row2_col9, #T_bdb0c_row2_col10, #T_bdb0c_row2_col11, #T_bdb0c_row2_col12, #T_bdb0c_row3_col0, #T_bdb0c_row3_col1, #T_bdb0c_row3_col2, #T_bdb0c_row3_col3, #T_bdb0c_row3_col4, #T_bdb0c_row3_col5, #T_bdb0c_row3_col6, #T_bdb0c_row3_col7, #T_bdb0c_row3_col8, #T_bdb0c_row3_col9, #T_bdb0c_row3_col10, #T_bdb0c_row3_col11, #T_bdb0c_row3_col12, #T_bdb0c_row4_col0, #T_bdb0c_row4_col1, #T_bdb0c_row4_col2, #T_bdb0c_row4_col3, #T_bdb0c_row4_col4, #T_bdb0c_row4_col5, #T_bdb0c_row4_col6, #T_bdb0c_row4_col7, #T_bdb0c_row4_col8, #T_bdb0c_row4_col9, #T_bdb0c_row4_col10, #T_bdb0c_row4_col11, #T_bdb0c_row4_col12, #T_bdb0c_row6_col0, #T_bdb0c_row6_col1, #T_bdb0c_row6_col2, #T_bdb0c_row6_col3, #T_bdb0c_row6_col4, #T_bdb0c_row6_col5, #T_bdb0c_row6_col6, #T_bdb0c_row6_col8, #T_bdb0c_row6_col9, #T_bdb0c_row6_col10, #T_bdb0c_row6_col11, #T_bdb0c_row6_col12, #T_bdb0c_row7_col7, #T_bdb0c_row7_col10, #T_bdb0c_row7_col12, #T_bdb0c_row8_col0, #T_bdb0c_row8_col1, #T_bdb0c_row8_col2, #T_bdb0c_row8_col3, #T_bdb0c_row8_col4, #T_bdb0c_row8_col5, #T_bdb0c_row8_col6, #T_bdb0c_row8_col7, #T_bdb0c_row8_col8, #T_bdb0c_row8_col9, #T_bdb0c_row8_col10, #T_bdb0c_row8_col11, #T_bdb0c_row8_col12, #T_bdb0c_row9_col0, #T_bdb0c_row9_col1, #T_bdb0c_row9_col2, #T_bdb0c_row9_col3, #T_bdb0c_row9_col4, #T_bdb0c_row9_col5, #T_bdb0c_row9_col6, #T_bdb0c_row9_col7, #T_bdb0c_row9_col8, #T_bdb0c_row9_col9, #T_bdb0c_row9_col10, #T_bdb0c_row9_col11, #T_bdb0c_row9_col12, #T_bdb0c_row10_col5, #T_bdb0c_row10_col6, #T_bdb0c_row10_col8, #T_bdb0c_row10_col10, #T_bdb0c_row10_col12, #T_bdb0c_row11_col0, #T_bdb0c_row11_col1, #T_bdb0c_row11_col2, #T_bdb0c_row11_col3, #T_bdb0c_row11_col4, #T_bdb0c_row11_col5, #T_bdb0c_row11_col6, #T_bdb0c_row11_col7, #T_bdb0c_row11_col8, #T_bdb0c_row11_col9, #T_bdb0c_row11_col10, #T_bdb0c_row11_col11, #T_bdb0c_row11_col12, #T_bdb0c_row13_col0, #T_bdb0c_row13_col1, #T_bdb0c_row13_col2, #T_bdb0c_row13_col3, #T_bdb0c_row13_col4, #T_bdb0c_row13_col5, #T_bdb0c_row13_col6, #T_bdb0c_row13_col7, #T_bdb0c_row13_col8, #T_bdb0c_row13_col9, #T_bdb0c_row13_col10, #T_bdb0c_row13_col11, #T_bdb0c_row13_col12, #T_bdb0c_row14_col0, #T_bdb0c_row14_col1, #T_bdb0c_row14_col2, #T_bdb0c_row14_col3, #T_bdb0c_row14_col4, #T_bdb0c_row14_col5, #T_bdb0c_row14_col6, #T_bdb0c_row14_col9, #T_bdb0c_row14_col11, #T_bdb0c_row15_col6, #T_bdb0c_row15_col7, #T_bdb0c_row15_col8, #T_bdb0c_row16_col5, #T_bdb0c_row16_col6, #T_bdb0c_row16_col11, #T_bdb0c_row17_col0, #T_bdb0c_row17_col1, #T_bdb0c_row17_col2, #T_bdb0c_row17_col3, #T_bdb0c_row17_col4, #T_bdb0c_row17_col5, #T_bdb0c_row17_col6, #T_bdb0c_row17_col7, #T_bdb0c_row17_col8, #T_bdb0c_row17_col9, #T_bdb0c_row17_col10, #T_bdb0c_row17_col11, #T_bdb0c_row17_col12, #T_bdb0c_row18_col0, #T_bdb0c_row18_col1, #T_bdb0c_row18_col2, #T_bdb0c_row18_col3, #T_bdb0c_row18_col4, #T_bdb0c_row18_col5, #T_bdb0c_row18_col6, #T_bdb0c_row18_col7, #T_bdb0c_row18_col8, #T_bdb0c_row18_col9, #T_bdb0c_row18_col10, #T_bdb0c_row18_col11, #T_bdb0c_row18_col12, #T_bdb0c_row19_col0, #T_bdb0c_row19_col2, #T_bdb0c_row19_col4, #T_bdb0c_row19_col5, #T_bdb0c_row19_col6, #T_bdb0c_row19_col7, #T_bdb0c_row19_col8, #T_bdb0c_row19_col9, #T_bdb0c_row19_col10, #T_bdb0c_row19_col12, #T_bdb0c_row20_col8, #T_bdb0c_row21_col0, #T_bdb0c_row21_col1, #T_bdb0c_row21_col2, #T_bdb0c_row21_col3, #T_bdb0c_row21_col4, #T_bdb0c_row21_col5, #T_bdb0c_row21_col6, #T_bdb0c_row21_col7, #T_bdb0c_row21_col8, #T_bdb0c_row21_col9, #T_bdb0c_row21_col10, #T_bdb0c_row21_col11, #T_bdb0c_row21_col12, #T_bdb0c_row22_col0, #T_bdb0c_row22_col1, #T_bdb0c_row22_col2, #T_bdb0c_row22_col3, #T_bdb0c_row22_col4, #T_bdb0c_row22_col5, #T_bdb0c_row22_col6, #T_bdb0c_row22_col7, #T_bdb0c_row22_col8, #T_bdb0c_row22_col9, #T_bdb0c_row22_col10, #T_bdb0c_row22_col11, #T_bdb0c_row22_col12, #T_bdb0c_row23_col6, #T_bdb0c_row23_col7, #T_bdb0c_row23_col8, #T_bdb0c_row23_col12, #T_bdb0c_row24_col0, #T_bdb0c_row24_col1, #T_bdb0c_row24_col2, #T_bdb0c_row24_col3, #T_bdb0c_row24_col4, #T_bdb0c_row24_col5, #T_bdb0c_row24_col6, #T_bdb0c_row24_col7, #T_bdb0c_row24_col8, #T_bdb0c_row24_col10, #T_bdb0c_row24_col12 {\n",
       "  background-color: #ffffe5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row1_col0, #T_bdb0c_row10_col7 {\n",
       "  background-color: #def2a7;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row1_col1 {\n",
       "  background-color: #e0f3a8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row1_col2, #T_bdb0c_row1_col5 {\n",
       "  background-color: #ddf2a6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row1_col3, #T_bdb0c_row20_col5 {\n",
       "  background-color: #e1f3a9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row1_col4, #T_bdb0c_row23_col10 {\n",
       "  background-color: #ddf1a6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row1_col6 {\n",
       "  background-color: #e8f6ae;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row1_col8 {\n",
       "  background-color: #f6fcb8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row1_col9 {\n",
       "  background-color: #aedd8e;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row1_col10 {\n",
       "  background-color: #81ca7d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row1_col11, #T_bdb0c_row23_col3 {\n",
       "  background-color: #9cd687;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row1_col12 {\n",
       "  background-color: #e6f5ac;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row2_col0, #T_bdb0c_row2_col3, #T_bdb0c_row16_col9 {\n",
       "  background-color: #fdfeda;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row2_col1 {\n",
       "  background-color: #fcfed7;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row2_col2, #T_bdb0c_row7_col9, #T_bdb0c_row16_col4 {\n",
       "  background-color: #feffe2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row2_col4, #T_bdb0c_row19_col3, #T_bdb0c_row20_col10 {\n",
       "  background-color: #ffffe4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row2_col5, #T_bdb0c_row7_col3 {\n",
       "  background-color: #f9fdc4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row5_col0 {\n",
       "  background-color: #66bd70;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bdb0c_row5_col1 {\n",
       "  background-color: #9ad587;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row5_col2 {\n",
       "  background-color: #7cc87b;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row5_col3 {\n",
       "  background-color: #97d385;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row5_col4 {\n",
       "  background-color: #77c679;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row5_col5 {\n",
       "  background-color: #56b568;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bdb0c_row5_col6 {\n",
       "  background-color: #2c8f4b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bdb0c_row5_col7 {\n",
       "  background-color: #006435;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bdb0c_row5_col8, #T_bdb0c_row5_col12, #T_bdb0c_row12_col0, #T_bdb0c_row12_col1, #T_bdb0c_row12_col2, #T_bdb0c_row12_col3, #T_bdb0c_row12_col4, #T_bdb0c_row12_col5, #T_bdb0c_row12_col6, #T_bdb0c_row12_col7, #T_bdb0c_row12_col9, #T_bdb0c_row12_col10, #T_bdb0c_row12_col11 {\n",
       "  background-color: #004529;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bdb0c_row5_col9 {\n",
       "  background-color: #bde496;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row5_col10 {\n",
       "  background-color: #14783e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bdb0c_row5_col11, #T_bdb0c_row15_col1 {\n",
       "  background-color: #8bce81;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row6_col7, #T_bdb0c_row20_col4 {\n",
       "  background-color: #e2f4aa;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row7_col0 {\n",
       "  background-color: #f8fcbd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row7_col1, #T_bdb0c_row20_col12 {\n",
       "  background-color: #fbfdcf;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row7_col2 {\n",
       "  background-color: #fafdcb;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row7_col4 {\n",
       "  background-color: #fafdc9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row7_col5, #T_bdb0c_row24_col11 {\n",
       "  background-color: #fafdc8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row7_col6 {\n",
       "  background-color: #fdfed9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row7_col8, #T_bdb0c_row14_col10, #T_bdb0c_row23_col9 {\n",
       "  background-color: #f9fdc2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row7_col11, #T_bdb0c_row14_col7 {\n",
       "  background-color: #fdfedb;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row10_col0 {\n",
       "  background-color: #dff3a8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row10_col1 {\n",
       "  background-color: #c0e597;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row10_col2, #T_bdb0c_row15_col5 {\n",
       "  background-color: #edf8b1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row10_col3 {\n",
       "  background-color: #b6e192;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row10_col4 {\n",
       "  background-color: #eff9b3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row10_col9, #T_bdb0c_row19_col11 {\n",
       "  background-color: #fcfed6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row10_col11, #T_bdb0c_row20_col9 {\n",
       "  background-color: #f8fdc1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row12_col8 {\n",
       "  background-color: #ceeb9e;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row12_col12 {\n",
       "  background-color: #5fba6c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bdb0c_row14_col8, #T_bdb0c_row16_col12 {\n",
       "  background-color: #f1fab5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row14_col12 {\n",
       "  background-color: #f0f9b4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row15_col0, #T_bdb0c_row23_col0 {\n",
       "  background-color: #b8e293;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row15_col2 {\n",
       "  background-color: #c4e799;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row15_col3 {\n",
       "  background-color: #6bc072;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row15_col4, #T_bdb0c_row23_col2 {\n",
       "  background-color: #c9e99c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row15_col9 {\n",
       "  background-color: #61bb6d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bdb0c_row15_col10 {\n",
       "  background-color: #d0ec9f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row15_col11 {\n",
       "  background-color: #9fd788;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row15_col12, #T_bdb0c_row16_col7 {\n",
       "  background-color: #f7fcba;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row16_col0, #T_bdb0c_row16_col10 {\n",
       "  background-color: #fdfedd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row16_col1, #T_bdb0c_row16_col3 {\n",
       "  background-color: #f9fdc5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row16_col2 {\n",
       "  background-color: #feffdf;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row16_col8 {\n",
       "  background-color: #f3fab6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row19_col1 {\n",
       "  background-color: #fcfed4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row20_col0 {\n",
       "  background-color: #eaf7af;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row20_col1 {\n",
       "  background-color: #f2fab5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row20_col2 {\n",
       "  background-color: #e3f4aa;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row20_col3 {\n",
       "  background-color: #edf8b2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row20_col6, #T_bdb0c_row23_col4 {\n",
       "  background-color: #ccea9d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row20_col7 {\n",
       "  background-color: #79c679;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row20_col11 {\n",
       "  background-color: #fafdcc;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row23_col1 {\n",
       "  background-color: #b1df90;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row23_col5 {\n",
       "  background-color: #bae394;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row23_col11 {\n",
       "  background-color: #f4fbb7;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bdb0c_row24_col9 {\n",
       "  background-color: #e7f6ad;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_bdb0c\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_bdb0c_level0_col0\" class=\"col_heading level0 col0\" >MV</th>\n",
       "      <th id=\"T_bdb0c_level0_col1\" class=\"col_heading level0 col1\" >MAD</th>\n",
       "      <th id=\"T_bdb0c_level0_col2\" class=\"col_heading level0 col2\" >MSV</th>\n",
       "      <th id=\"T_bdb0c_level0_col3\" class=\"col_heading level0 col3\" >FLPM</th>\n",
       "      <th id=\"T_bdb0c_level0_col4\" class=\"col_heading level0 col4\" >SLPM</th>\n",
       "      <th id=\"T_bdb0c_level0_col5\" class=\"col_heading level0 col5\" >CVaR</th>\n",
       "      <th id=\"T_bdb0c_level0_col6\" class=\"col_heading level0 col6\" >EVaR</th>\n",
       "      <th id=\"T_bdb0c_level0_col7\" class=\"col_heading level0 col7\" >WR</th>\n",
       "      <th id=\"T_bdb0c_level0_col8\" class=\"col_heading level0 col8\" >MDD</th>\n",
       "      <th id=\"T_bdb0c_level0_col9\" class=\"col_heading level0 col9\" >ADD</th>\n",
       "      <th id=\"T_bdb0c_level0_col10\" class=\"col_heading level0 col10\" >CDaR</th>\n",
       "      <th id=\"T_bdb0c_level0_col11\" class=\"col_heading level0 col11\" >UCI</th>\n",
       "      <th id=\"T_bdb0c_level0_col12\" class=\"col_heading level0 col12\" >EDaR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row0\" class=\"row_heading level0 row0\" >APA</th>\n",
       "      <td id=\"T_bdb0c_row0_col0\" class=\"data row0 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row0_col1\" class=\"data row0 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row0_col2\" class=\"data row0 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row0_col3\" class=\"data row0 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row0_col4\" class=\"data row0 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row0_col5\" class=\"data row0 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row0_col6\" class=\"data row0 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row0_col7\" class=\"data row0 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row0_col8\" class=\"data row0 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row0_col9\" class=\"data row0 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row0_col10\" class=\"data row0 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row0_col11\" class=\"data row0 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row0_col12\" class=\"data row0 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row1\" class=\"row_heading level0 row1\" >BA</th>\n",
       "      <td id=\"T_bdb0c_row1_col0\" class=\"data row1 col0\" >7.45%</td>\n",
       "      <td id=\"T_bdb0c_row1_col1\" class=\"data row1 col1\" >6.99%</td>\n",
       "      <td id=\"T_bdb0c_row1_col2\" class=\"data row1 col2\" >8.25%</td>\n",
       "      <td id=\"T_bdb0c_row1_col3\" class=\"data row1 col3\" >6.48%</td>\n",
       "      <td id=\"T_bdb0c_row1_col4\" class=\"data row1 col4\" >8.43%</td>\n",
       "      <td id=\"T_bdb0c_row1_col5\" class=\"data row1 col5\" >8.52%</td>\n",
       "      <td id=\"T_bdb0c_row1_col6\" class=\"data row1 col6\" >8.49%</td>\n",
       "      <td id=\"T_bdb0c_row1_col7\" class=\"data row1 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row1_col8\" class=\"data row1 col8\" >7.16%</td>\n",
       "      <td id=\"T_bdb0c_row1_col9\" class=\"data row1 col9\" >13.63%</td>\n",
       "      <td id=\"T_bdb0c_row1_col10\" class=\"data row1 col10\" >16.38%</td>\n",
       "      <td id=\"T_bdb0c_row1_col11\" class=\"data row1 col11\" >15.08%</td>\n",
       "      <td id=\"T_bdb0c_row1_col12\" class=\"data row1 col12\" >8.71%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row2\" class=\"row_heading level0 row2\" >BAX</th>\n",
       "      <td id=\"T_bdb0c_row2_col0\" class=\"data row2 col0\" >1.03%</td>\n",
       "      <td id=\"T_bdb0c_row2_col1\" class=\"data row2 col1\" >1.30%</td>\n",
       "      <td id=\"T_bdb0c_row2_col2\" class=\"data row2 col2\" >0.36%</td>\n",
       "      <td id=\"T_bdb0c_row2_col3\" class=\"data row2 col3\" >0.95%</td>\n",
       "      <td id=\"T_bdb0c_row2_col4\" class=\"data row2 col4\" >0.22%</td>\n",
       "      <td id=\"T_bdb0c_row2_col5\" class=\"data row2 col5\" >3.48%</td>\n",
       "      <td id=\"T_bdb0c_row2_col6\" class=\"data row2 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row2_col7\" class=\"data row2 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row2_col8\" class=\"data row2 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row2_col9\" class=\"data row2 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row2_col10\" class=\"data row2 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row2_col11\" class=\"data row2 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row2_col12\" class=\"data row2 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row3\" class=\"row_heading level0 row3\" >BMY</th>\n",
       "      <td id=\"T_bdb0c_row3_col0\" class=\"data row3 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row3_col1\" class=\"data row3 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row3_col2\" class=\"data row3 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row3_col3\" class=\"data row3 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row3_col4\" class=\"data row3 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row3_col5\" class=\"data row3 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row3_col6\" class=\"data row3 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row3_col7\" class=\"data row3 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row3_col8\" class=\"data row3 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row3_col9\" class=\"data row3 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row3_col10\" class=\"data row3 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row3_col11\" class=\"data row3 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row3_col12\" class=\"data row3 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row4\" class=\"row_heading level0 row4\" >CMCSA</th>\n",
       "      <td id=\"T_bdb0c_row4_col0\" class=\"data row4 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row4_col1\" class=\"data row4 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row4_col2\" class=\"data row4 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row4_col3\" class=\"data row4 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row4_col4\" class=\"data row4 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row4_col5\" class=\"data row4 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row4_col6\" class=\"data row4 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row4_col7\" class=\"data row4 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row4_col8\" class=\"data row4 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row4_col9\" class=\"data row4 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row4_col10\" class=\"data row4 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row4_col11\" class=\"data row4 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row4_col12\" class=\"data row4 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row5\" class=\"row_heading level0 row5\" >CNP</th>\n",
       "      <td id=\"T_bdb0c_row5_col0\" class=\"data row5 col0\" >17.82%</td>\n",
       "      <td id=\"T_bdb0c_row5_col1\" class=\"data row5 col1\" >13.25%</td>\n",
       "      <td id=\"T_bdb0c_row5_col2\" class=\"data row5 col2\" >17.50%</td>\n",
       "      <td id=\"T_bdb0c_row5_col3\" class=\"data row5 col3\" >12.81%</td>\n",
       "      <td id=\"T_bdb0c_row5_col4\" class=\"data row5 col4\" >17.98%</td>\n",
       "      <td id=\"T_bdb0c_row5_col5\" class=\"data row5 col5\" >21.30%</td>\n",
       "      <td id=\"T_bdb0c_row5_col6\" class=\"data row5 col6\" >31.96%</td>\n",
       "      <td id=\"T_bdb0c_row5_col7\" class=\"data row5 col7\" >29.80%</td>\n",
       "      <td id=\"T_bdb0c_row5_col8\" class=\"data row5 col8\" >55.32%</td>\n",
       "      <td id=\"T_bdb0c_row5_col9\" class=\"data row5 col9\" >12.02%</td>\n",
       "      <td id=\"T_bdb0c_row5_col10\" class=\"data row5 col10\" >27.50%</td>\n",
       "      <td id=\"T_bdb0c_row5_col11\" class=\"data row5 col11\" >16.60%</td>\n",
       "      <td id=\"T_bdb0c_row5_col12\" class=\"data row5 col12\" >44.54%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row6\" class=\"row_heading level0 row6\" >CPB</th>\n",
       "      <td id=\"T_bdb0c_row6_col0\" class=\"data row6 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row6_col1\" class=\"data row6 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row6_col2\" class=\"data row6 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row6_col3\" class=\"data row6 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row6_col4\" class=\"data row6 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row6_col5\" class=\"data row6 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row6_col6\" class=\"data row6 col6\" >0.10%</td>\n",
       "      <td id=\"T_bdb0c_row6_col7\" class=\"data row6 col7\" >7.20%</td>\n",
       "      <td id=\"T_bdb0c_row6_col8\" class=\"data row6 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row6_col9\" class=\"data row6 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row6_col10\" class=\"data row6 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row6_col11\" class=\"data row6 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row6_col12\" class=\"data row6 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row7\" class=\"row_heading level0 row7\" >DE</th>\n",
       "      <td id=\"T_bdb0c_row7_col0\" class=\"data row7 col0\" >3.77%</td>\n",
       "      <td id=\"T_bdb0c_row7_col1\" class=\"data row7 col1\" >1.99%</td>\n",
       "      <td id=\"T_bdb0c_row7_col2\" class=\"data row7 col2\" >2.68%</td>\n",
       "      <td id=\"T_bdb0c_row7_col3\" class=\"data row7 col3\" >2.93%</td>\n",
       "      <td id=\"T_bdb0c_row7_col4\" class=\"data row7 col4\" >2.82%</td>\n",
       "      <td id=\"T_bdb0c_row7_col5\" class=\"data row7 col5\" >3.09%</td>\n",
       "      <td id=\"T_bdb0c_row7_col6\" class=\"data row7 col6\" >1.73%</td>\n",
       "      <td id=\"T_bdb0c_row7_col7\" class=\"data row7 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row7_col8\" class=\"data row7 col8\" >5.45%</td>\n",
       "      <td id=\"T_bdb0c_row7_col9\" class=\"data row7 col9\" >0.38%</td>\n",
       "      <td id=\"T_bdb0c_row7_col10\" class=\"data row7 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row7_col11\" class=\"data row7 col11\" >1.08%</td>\n",
       "      <td id=\"T_bdb0c_row7_col12\" class=\"data row7 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row8\" class=\"row_heading level0 row8\" >HPQ</th>\n",
       "      <td id=\"T_bdb0c_row8_col0\" class=\"data row8 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row8_col1\" class=\"data row8 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row8_col2\" class=\"data row8 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row8_col3\" class=\"data row8 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row8_col4\" class=\"data row8 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row8_col5\" class=\"data row8 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row8_col6\" class=\"data row8 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row8_col7\" class=\"data row8 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row8_col8\" class=\"data row8 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row8_col9\" class=\"data row8 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row8_col10\" class=\"data row8 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row8_col11\" class=\"data row8 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row8_col12\" class=\"data row8 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row9\" class=\"row_heading level0 row9\" >JCI</th>\n",
       "      <td id=\"T_bdb0c_row9_col0\" class=\"data row9 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row9_col1\" class=\"data row9 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row9_col2\" class=\"data row9 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row9_col3\" class=\"data row9 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row9_col4\" class=\"data row9 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row9_col5\" class=\"data row9 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row9_col6\" class=\"data row9 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row9_col7\" class=\"data row9 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row9_col8\" class=\"data row9 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row9_col9\" class=\"data row9 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row9_col10\" class=\"data row9 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row9_col11\" class=\"data row9 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row9_col12\" class=\"data row9 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row10\" class=\"row_heading level0 row10\" >JPM</th>\n",
       "      <td id=\"T_bdb0c_row10_col0\" class=\"data row10 col0\" >7.34%</td>\n",
       "      <td id=\"T_bdb0c_row10_col1\" class=\"data row10 col1\" >10.09%</td>\n",
       "      <td id=\"T_bdb0c_row10_col2\" class=\"data row10 col2\" >6.11%</td>\n",
       "      <td id=\"T_bdb0c_row10_col3\" class=\"data row10 col3\" >10.54%</td>\n",
       "      <td id=\"T_bdb0c_row10_col4\" class=\"data row10 col4\" >5.68%</td>\n",
       "      <td id=\"T_bdb0c_row10_col5\" class=\"data row10 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row10_col6\" class=\"data row10 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row10_col7\" class=\"data row10 col7\" >7.70%</td>\n",
       "      <td id=\"T_bdb0c_row10_col8\" class=\"data row10 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row10_col9\" class=\"data row10 col9\" >1.62%</td>\n",
       "      <td id=\"T_bdb0c_row10_col10\" class=\"data row10 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row10_col11\" class=\"data row10 col11\" >3.72%</td>\n",
       "      <td id=\"T_bdb0c_row10_col12\" class=\"data row10 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row11\" class=\"row_heading level0 row11\" >LUV</th>\n",
       "      <td id=\"T_bdb0c_row11_col0\" class=\"data row11 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row11_col1\" class=\"data row11 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row11_col2\" class=\"data row11 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row11_col3\" class=\"data row11 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row11_col4\" class=\"data row11 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row11_col5\" class=\"data row11 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row11_col6\" class=\"data row11 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row11_col7\" class=\"data row11 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row11_col8\" class=\"data row11 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row11_col9\" class=\"data row11 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row11_col10\" class=\"data row11 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row11_col11\" class=\"data row11 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row11_col12\" class=\"data row11 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row12\" class=\"row_heading level0 row12\" >MMC</th>\n",
       "      <td id=\"T_bdb0c_row12_col0\" class=\"data row12 col0\" >32.90%</td>\n",
       "      <td id=\"T_bdb0c_row12_col1\" class=\"data row12 col1\" >31.48%</td>\n",
       "      <td id=\"T_bdb0c_row12_col2\" class=\"data row12 col2\" >35.58%</td>\n",
       "      <td id=\"T_bdb0c_row12_col3\" class=\"data row12 col3\" >30.04%</td>\n",
       "      <td id=\"T_bdb0c_row12_col4\" class=\"data row12 col4\" >35.91%</td>\n",
       "      <td id=\"T_bdb0c_row12_col5\" class=\"data row12 col5\" >36.88%</td>\n",
       "      <td id=\"T_bdb0c_row12_col6\" class=\"data row12 col6\" >44.83%</td>\n",
       "      <td id=\"T_bdb0c_row12_col7\" class=\"data row12 col7\" >33.51%</td>\n",
       "      <td id=\"T_bdb0c_row12_col8\" class=\"data row12 col8\" >15.77%</td>\n",
       "      <td id=\"T_bdb0c_row12_col9\" class=\"data row12 col9\" >36.47%</td>\n",
       "      <td id=\"T_bdb0c_row12_col10\" class=\"data row12 col10\" >34.25%</td>\n",
       "      <td id=\"T_bdb0c_row12_col11\" class=\"data row12 col11\" >36.34%</td>\n",
       "      <td id=\"T_bdb0c_row12_col12\" class=\"data row12 col12\" >24.80%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row13\" class=\"row_heading level0 row13\" >MO</th>\n",
       "      <td id=\"T_bdb0c_row13_col0\" class=\"data row13 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row13_col1\" class=\"data row13 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row13_col2\" class=\"data row13 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row13_col3\" class=\"data row13 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row13_col4\" class=\"data row13 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row13_col5\" class=\"data row13 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row13_col6\" class=\"data row13 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row13_col7\" class=\"data row13 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row13_col8\" class=\"data row13 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row13_col9\" class=\"data row13 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row13_col10\" class=\"data row13 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row13_col11\" class=\"data row13 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row13_col12\" class=\"data row13 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row14\" class=\"row_heading level0 row14\" >MSFT</th>\n",
       "      <td id=\"T_bdb0c_row14_col0\" class=\"data row14 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row14_col1\" class=\"data row14 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row14_col2\" class=\"data row14 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row14_col3\" class=\"data row14 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row14_col4\" class=\"data row14 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row14_col5\" class=\"data row14 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row14_col6\" class=\"data row14 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row14_col7\" class=\"data row14 col7\" >0.96%</td>\n",
       "      <td id=\"T_bdb0c_row14_col8\" class=\"data row14 col8\" >8.42%</td>\n",
       "      <td id=\"T_bdb0c_row14_col9\" class=\"data row14 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row14_col10\" class=\"data row14 col10\" >3.35%</td>\n",
       "      <td id=\"T_bdb0c_row14_col11\" class=\"data row14 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row14_col12\" class=\"data row14 col12\" >6.91%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row15\" class=\"row_heading level0 row15\" >NI</th>\n",
       "      <td id=\"T_bdb0c_row15_col0\" class=\"data row15 col0\" >11.40%</td>\n",
       "      <td id=\"T_bdb0c_row15_col1\" class=\"data row15 col1\" >14.37%</td>\n",
       "      <td id=\"T_bdb0c_row15_col2\" class=\"data row15 col2\" >11.04%</td>\n",
       "      <td id=\"T_bdb0c_row15_col3\" class=\"data row15 col3\" >15.88%</td>\n",
       "      <td id=\"T_bdb0c_row15_col4\" class=\"data row15 col4\" >10.64%</td>\n",
       "      <td id=\"T_bdb0c_row15_col5\" class=\"data row15 col5\" >6.20%</td>\n",
       "      <td id=\"T_bdb0c_row15_col6\" class=\"data row15 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row15_col7\" class=\"data row15 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row15_col8\" class=\"data row15 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row15_col9\" class=\"data row15 col9\" >20.22%</td>\n",
       "      <td id=\"T_bdb0c_row15_col10\" class=\"data row15 col10\" >9.44%</td>\n",
       "      <td id=\"T_bdb0c_row15_col11\" class=\"data row15 col11\" >14.85%</td>\n",
       "      <td id=\"T_bdb0c_row15_col12\" class=\"data row15 col12\" >5.47%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row16\" class=\"row_heading level0 row16\" >PCAR</th>\n",
       "      <td id=\"T_bdb0c_row16_col0\" class=\"data row16 col0\" >0.89%</td>\n",
       "      <td id=\"T_bdb0c_row16_col1\" class=\"data row16 col1\" >2.93%</td>\n",
       "      <td id=\"T_bdb0c_row16_col2\" class=\"data row16 col2\" >0.60%</td>\n",
       "      <td id=\"T_bdb0c_row16_col3\" class=\"data row16 col3\" >2.70%</td>\n",
       "      <td id=\"T_bdb0c_row16_col4\" class=\"data row16 col4\" >0.34%</td>\n",
       "      <td id=\"T_bdb0c_row16_col5\" class=\"data row16 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row16_col6\" class=\"data row16 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row16_col7\" class=\"data row16 col7\" >4.18%</td>\n",
       "      <td id=\"T_bdb0c_row16_col8\" class=\"data row16 col8\" >7.87%</td>\n",
       "      <td id=\"T_bdb0c_row16_col9\" class=\"data row16 col9\" >1.22%</td>\n",
       "      <td id=\"T_bdb0c_row16_col10\" class=\"data row16 col10\" >0.80%</td>\n",
       "      <td id=\"T_bdb0c_row16_col11\" class=\"data row16 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row16_col12\" class=\"data row16 col12\" >6.73%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row17\" class=\"row_heading level0 row17\" >PSA</th>\n",
       "      <td id=\"T_bdb0c_row17_col0\" class=\"data row17 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row17_col1\" class=\"data row17 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row17_col2\" class=\"data row17 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row17_col3\" class=\"data row17 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row17_col4\" class=\"data row17 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row17_col5\" class=\"data row17 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row17_col6\" class=\"data row17 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row17_col7\" class=\"data row17 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row17_col8\" class=\"data row17 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row17_col9\" class=\"data row17 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row17_col10\" class=\"data row17 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row17_col11\" class=\"data row17 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row17_col12\" class=\"data row17 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row18\" class=\"row_heading level0 row18\" >SEE</th>\n",
       "      <td id=\"T_bdb0c_row18_col0\" class=\"data row18 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row18_col1\" class=\"data row18 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row18_col2\" class=\"data row18 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row18_col3\" class=\"data row18 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row18_col4\" class=\"data row18 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row18_col5\" class=\"data row18 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row18_col6\" class=\"data row18 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row18_col7\" class=\"data row18 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row18_col8\" class=\"data row18 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row18_col9\" class=\"data row18 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row18_col10\" class=\"data row18 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row18_col11\" class=\"data row18 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row18_col12\" class=\"data row18 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row19\" class=\"row_heading level0 row19\" >T</th>\n",
       "      <td id=\"T_bdb0c_row19_col0\" class=\"data row19 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row19_col1\" class=\"data row19 col1\" >1.59%</td>\n",
       "      <td id=\"T_bdb0c_row19_col2\" class=\"data row19 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row19_col3\" class=\"data row19 col3\" >0.15%</td>\n",
       "      <td id=\"T_bdb0c_row19_col4\" class=\"data row19 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row19_col5\" class=\"data row19 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row19_col6\" class=\"data row19 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row19_col7\" class=\"data row19 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row19_col8\" class=\"data row19 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row19_col9\" class=\"data row19 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row19_col10\" class=\"data row19 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row19_col11\" class=\"data row19 col11\" >1.62%</td>\n",
       "      <td id=\"T_bdb0c_row19_col12\" class=\"data row19 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row20\" class=\"row_heading level0 row20\" >TGT</th>\n",
       "      <td id=\"T_bdb0c_row20_col0\" class=\"data row20 col0\" >6.02%</td>\n",
       "      <td id=\"T_bdb0c_row20_col1\" class=\"data row20 col1\" >4.56%</td>\n",
       "      <td id=\"T_bdb0c_row20_col2\" class=\"data row20 col2\" >7.40%</td>\n",
       "      <td id=\"T_bdb0c_row20_col3\" class=\"data row20 col3\" >4.97%</td>\n",
       "      <td id=\"T_bdb0c_row20_col4\" class=\"data row20 col4\" >7.70%</td>\n",
       "      <td id=\"T_bdb0c_row20_col5\" class=\"data row20 col5\" >8.05%</td>\n",
       "      <td id=\"T_bdb0c_row20_col6\" class=\"data row20 col6\" >12.90%</td>\n",
       "      <td id=\"T_bdb0c_row20_col7\" class=\"data row20 col7\" >16.64%</td>\n",
       "      <td id=\"T_bdb0c_row20_col8\" class=\"data row20 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row20_col9\" class=\"data row20 col9\" >3.79%</td>\n",
       "      <td id=\"T_bdb0c_row20_col10\" class=\"data row20 col10\" >0.25%</td>\n",
       "      <td id=\"T_bdb0c_row20_col11\" class=\"data row20 col11\" >2.60%</td>\n",
       "      <td id=\"T_bdb0c_row20_col12\" class=\"data row20 col12\" >2.84%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row21\" class=\"row_heading level0 row21\" >TMO</th>\n",
       "      <td id=\"T_bdb0c_row21_col0\" class=\"data row21 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row21_col1\" class=\"data row21 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row21_col2\" class=\"data row21 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row21_col3\" class=\"data row21 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row21_col4\" class=\"data row21 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row21_col5\" class=\"data row21 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row21_col6\" class=\"data row21 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row21_col7\" class=\"data row21 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row21_col8\" class=\"data row21 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row21_col9\" class=\"data row21 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row21_col10\" class=\"data row21 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row21_col11\" class=\"data row21 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row21_col12\" class=\"data row21 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row22\" class=\"row_heading level0 row22\" >TXT</th>\n",
       "      <td id=\"T_bdb0c_row22_col0\" class=\"data row22 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row22_col1\" class=\"data row22 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row22_col2\" class=\"data row22 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row22_col3\" class=\"data row22 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row22_col4\" class=\"data row22 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row22_col5\" class=\"data row22 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row22_col6\" class=\"data row22 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row22_col7\" class=\"data row22 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row22_col8\" class=\"data row22 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row22_col9\" class=\"data row22 col9\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row22_col10\" class=\"data row22 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row22_col11\" class=\"data row22 col11\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row22_col12\" class=\"data row22 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row23\" class=\"row_heading level0 row23\" >VZ</th>\n",
       "      <td id=\"T_bdb0c_row23_col0\" class=\"data row23 col0\" >11.37%</td>\n",
       "      <td id=\"T_bdb0c_row23_col1\" class=\"data row23 col1\" >11.46%</td>\n",
       "      <td id=\"T_bdb0c_row23_col2\" class=\"data row23 col2\" >10.48%</td>\n",
       "      <td id=\"T_bdb0c_row23_col3\" class=\"data row23 col3\" >12.54%</td>\n",
       "      <td id=\"T_bdb0c_row23_col4\" class=\"data row23 col4\" >10.28%</td>\n",
       "      <td id=\"T_bdb0c_row23_col5\" class=\"data row23 col5\" >12.48%</td>\n",
       "      <td id=\"T_bdb0c_row23_col6\" class=\"data row23 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row23_col7\" class=\"data row23 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row23_col8\" class=\"data row23 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row23_col9\" class=\"data row23 col9\" >3.63%</td>\n",
       "      <td id=\"T_bdb0c_row23_col10\" class=\"data row23 col10\" >8.03%</td>\n",
       "      <td id=\"T_bdb0c_row23_col11\" class=\"data row23 col11\" >5.08%</td>\n",
       "      <td id=\"T_bdb0c_row23_col12\" class=\"data row23 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdb0c_level0_row24\" class=\"row_heading level0 row24\" >ZION</th>\n",
       "      <td id=\"T_bdb0c_row24_col0\" class=\"data row24 col0\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row24_col1\" class=\"data row24 col1\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row24_col2\" class=\"data row24 col2\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row24_col3\" class=\"data row24 col3\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row24_col4\" class=\"data row24 col4\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row24_col5\" class=\"data row24 col5\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row24_col6\" class=\"data row24 col6\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row24_col7\" class=\"data row24 col7\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row24_col8\" class=\"data row24 col8\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row24_col9\" class=\"data row24 col9\" >7.02%</td>\n",
       "      <td id=\"T_bdb0c_row24_col10\" class=\"data row24 col10\" >0.00%</td>\n",
       "      <td id=\"T_bdb0c_row24_col11\" class=\"data row24 col11\" >3.04%</td>\n",
       "      <td id=\"T_bdb0c_row24_col12\" class=\"data row24 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f8b51f70730>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_s.style.format(\"{:.2%}\").background_gradient(cmap='YlGn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plotting a comparison of assets weights for each portfolio\n",
    "\n",
    "fig = plt.gcf()\n",
    "fig.set_figwidth(14)\n",
    "fig.set_figheight(6)\n",
    "ax = fig.subplots(nrows=1, ncols=1)\n",
    "\n",
    "w_s.plot.bar(ax=ax)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.12 ('base')",
   "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": "3.9.12"
  },
  "vscode": {
   "interpreter": {
    "hash": "6e72041bc49a6ff39e74ccd56b9391c544b799a0d2a04160b530f8b1ce965df8"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}