alt_mpt.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8683a589-49c9-41a6-9878-779a0971ca8f",
   "metadata": {},
   "source": [
    "### This code taken and/or adapted from [QuantPY](https://quantpy.com.au/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6f883726-968d-487b-94f1-726e09bdbf4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas_datareader import data as pdr\n",
    "\n",
    "# import scipy as sci\n",
    "from scipy import stats\n",
    "import scipy.optimize as sco\n",
    "\n",
    "import yfinance as yf\n",
    "\n",
    "import datetime as dt\n",
    "from datetime import date\n",
    "from datetime import timedelta\n",
    "\n",
    "import plotly.graph_objects as go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "57a2b07e-6bfd-43ab-b35e-6edff3e6dff6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Start date: 2012-10-24 06:50:07.400697 and End date: 2022-10-24 17:02:07.400697\n"
     ]
    }
   ],
   "source": [
    "# Specify date range for data\n",
    "# Set start and end dates of 5 years \"5Y\" back from your current date\n",
    "# Define the time delta (time-frame) to start with\n",
    "time_delta = 10\n",
    "\n",
    "end_date = pd.to_datetime('today')\n",
    "# 10 years\n",
    "start_date = end_date - np.timedelta64(time_delta, 'Y')\n",
    "start, end = start_date, end_date\n",
    "# Verify date range\n",
    "print(f\"Start date: {start} and End date: {end}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1019b95b-25bb-46c2-9e1d-b1f013484b3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Specify portfolio sectors - basket of market index and assets\n",
    "blend_list = ['IBM', 'TSLA','TSM', 'NVDA', 'DVN', 'OXY','CNI', 'NOC','BHF', 'AIG']\n",
    "tech_list = ['AAPL', 'IBM', 'TSLA', 'GOOGL', 'MSFT','CSCO', 'TSM', 'NVDA']\n",
    "energy_list = ['DVN', 'OXY', 'NEE', 'MRO', 'APA', 'TRGP', 'PSX', 'EQT']\n",
    "industrials_list = ['BA', 'GE', 'CNI', 'NOC', 'LPX', 'BLDR', 'AAL', 'CPA', 'CAR', 'CPA', 'HXL']\n",
    "financials_list = ['BHF', 'AIG', 'EQH', 'PFG', 'WBS', 'UNM', 'FHN', 'LPLA']\n",
    "market = ['^GSPC']   # adding S&P 500 Index (^GSPC) for use in beta weighting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7c84900d-d732-48da-90aa-84362a00af7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Basket of stocks\n",
      "['^GSPC', 'AAPL', 'IBM', 'TSLA', 'GOOGL', 'MSFT', 'CSCO', 'TSM', 'NVDA', 'DVN', 'OXY', 'NEE', 'MRO', 'APA', 'TRGP', 'PSX', 'EQT', 'BA', 'GE', 'CNI', 'NOC', 'LPX', 'BLDR', 'AAL', 'CPA', 'CAR', 'CPA', 'HXL', 'BHF', 'AIG', 'EQH', 'PFG', 'WBS', 'UNM', 'FHN', 'LPLA']\n"
     ]
    }
   ],
   "source": [
    "# Specify portfolio sectors - basket of market index and assets - S&P 500 Index (^GSPC) and Tech Stocks List\n",
    "basket_list = market + tech_list + energy_list + industrials_list + financials_list \n",
    "\n",
    "print(\"Basket of stocks\")\n",
    "print(basket_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3bff3784-4f16-491b-a7b2-6719680439b4",
   "metadata": {},
   "source": [
    "#### Get Stock Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "554f71ff-08b6-4a87-86e6-36a906cb7545",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Symbols\n",
       "^GSPC    0.000455\n",
       "AAPL     0.000928\n",
       "IBM     -0.000016\n",
       "TSLA     0.002521\n",
       "GOOGL    0.000854\n",
       "MSFT     0.001009\n",
       "CSCO     0.000493\n",
       "TSM      0.000725\n",
       "NVDA     0.001857\n",
       "DVN      0.000613\n",
       "OXY      0.000437\n",
       "NEE      0.000669\n",
       "MRO      0.000549\n",
       "APA      0.000410\n",
       "TRGP     0.000717\n",
       "PSX      0.000557\n",
       "EQT      0.000517\n",
       "BA       0.000562\n",
       "GE      -0.000097\n",
       "CNI      0.000481\n",
       "NOC      0.000916\n",
       "LPX      0.000819\n",
       "BLDR     0.001493\n",
       "AAL      0.000547\n",
       "CPA      0.000361\n",
       "CAR      0.001954\n",
       "HXL      0.000575\n",
       "BHF      0.000326\n",
       "AIG      0.000381\n",
       "EQH      0.000676\n",
       "PFG      0.000616\n",
       "WBS      0.000603\n",
       "UNM      0.000573\n",
       "FHN      0.000617\n",
       "LPLA     0.001149\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",
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Symbols</th>\n",
       "      <th>^GSPC</th>\n",
       "      <th>AAPL</th>\n",
       "      <th>IBM</th>\n",
       "      <th>TSLA</th>\n",
       "      <th>GOOGL</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>CSCO</th>\n",
       "      <th>TSM</th>\n",
       "      <th>NVDA</th>\n",
       "      <th>DVN</th>\n",
       "      <th>...</th>\n",
       "      <th>CAR</th>\n",
       "      <th>HXL</th>\n",
       "      <th>BHF</th>\n",
       "      <th>AIG</th>\n",
       "      <th>EQH</th>\n",
       "      <th>PFG</th>\n",
       "      <th>WBS</th>\n",
       "      <th>UNM</th>\n",
       "      <th>FHN</th>\n",
       "      <th>LPLA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbols</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>^GSPC</th>\n",
       "      <td>0.000120</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>0.000169</td>\n",
       "      <td>0.000134</td>\n",
       "      <td>0.000142</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>0.000191</td>\n",
       "      <td>0.000180</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000221</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.000301</td>\n",
       "      <td>0.000148</td>\n",
       "      <td>0.000276</td>\n",
       "      <td>0.000162</td>\n",
       "      <td>0.000161</td>\n",
       "      <td>0.000166</td>\n",
       "      <td>0.000141</td>\n",
       "      <td>0.000155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000333</td>\n",
       "      <td>0.000105</td>\n",
       "      <td>0.000236</td>\n",
       "      <td>0.000170</td>\n",
       "      <td>0.000187</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.000166</td>\n",
       "      <td>0.000262</td>\n",
       "      <td>0.000170</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000207</td>\n",
       "      <td>0.000127</td>\n",
       "      <td>0.000281</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.000268</td>\n",
       "      <td>0.000148</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.000146</td>\n",
       "      <td>0.000119</td>\n",
       "      <td>0.000154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBM</th>\n",
       "      <td>0.000104</td>\n",
       "      <td>0.000105</td>\n",
       "      <td>0.000219</td>\n",
       "      <td>0.000110</td>\n",
       "      <td>0.000103</td>\n",
       "      <td>0.000113</td>\n",
       "      <td>0.000124</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000136</td>\n",
       "      <td>0.000177</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000200</td>\n",
       "      <td>0.000141</td>\n",
       "      <td>0.000316</td>\n",
       "      <td>0.000147</td>\n",
       "      <td>0.000275</td>\n",
       "      <td>0.000159</td>\n",
       "      <td>0.000162</td>\n",
       "      <td>0.000181</td>\n",
       "      <td>0.000141</td>\n",
       "      <td>0.000135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA</th>\n",
       "      <td>0.000169</td>\n",
       "      <td>0.000236</td>\n",
       "      <td>0.000110</td>\n",
       "      <td>0.001270</td>\n",
       "      <td>0.000215</td>\n",
       "      <td>0.000224</td>\n",
       "      <td>0.000149</td>\n",
       "      <td>0.000222</td>\n",
       "      <td>0.000371</td>\n",
       "      <td>0.000259</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000384</td>\n",
       "      <td>0.000201</td>\n",
       "      <td>0.000358</td>\n",
       "      <td>0.000180</td>\n",
       "      <td>0.000340</td>\n",
       "      <td>0.000178</td>\n",
       "      <td>0.000184</td>\n",
       "      <td>0.000175</td>\n",
       "      <td>0.000182</td>\n",
       "      <td>0.000236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOGL</th>\n",
       "      <td>0.000134</td>\n",
       "      <td>0.000170</td>\n",
       "      <td>0.000103</td>\n",
       "      <td>0.000215</td>\n",
       "      <td>0.000278</td>\n",
       "      <td>0.000191</td>\n",
       "      <td>0.000130</td>\n",
       "      <td>0.000150</td>\n",
       "      <td>0.000248</td>\n",
       "      <td>0.000161</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000223</td>\n",
       "      <td>0.000137</td>\n",
       "      <td>0.000279</td>\n",
       "      <td>0.000137</td>\n",
       "      <td>0.000254</td>\n",
       "      <td>0.000148</td>\n",
       "      <td>0.000142</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000117</td>\n",
       "      <td>0.000159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>0.000142</td>\n",
       "      <td>0.000187</td>\n",
       "      <td>0.000113</td>\n",
       "      <td>0.000224</td>\n",
       "      <td>0.000191</td>\n",
       "      <td>0.000282</td>\n",
       "      <td>0.000152</td>\n",
       "      <td>0.000154</td>\n",
       "      <td>0.000270</td>\n",
       "      <td>0.000160</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000218</td>\n",
       "      <td>0.000130</td>\n",
       "      <td>0.000273</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.000253</td>\n",
       "      <td>0.000150</td>\n",
       "      <td>0.000141</td>\n",
       "      <td>0.000143</td>\n",
       "      <td>0.000115</td>\n",
       "      <td>0.000156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CSCO</th>\n",
       "      <td>0.000121</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.000124</td>\n",
       "      <td>0.000149</td>\n",
       "      <td>0.000130</td>\n",
       "      <td>0.000152</td>\n",
       "      <td>0.000255</td>\n",
       "      <td>0.000122</td>\n",
       "      <td>0.000198</td>\n",
       "      <td>0.000174</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000211</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.000289</td>\n",
       "      <td>0.000136</td>\n",
       "      <td>0.000256</td>\n",
       "      <td>0.000158</td>\n",
       "      <td>0.000156</td>\n",
       "      <td>0.000164</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>0.000146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSM</th>\n",
       "      <td>0.000121</td>\n",
       "      <td>0.000166</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000222</td>\n",
       "      <td>0.000150</td>\n",
       "      <td>0.000154</td>\n",
       "      <td>0.000122</td>\n",
       "      <td>0.000338</td>\n",
       "      <td>0.000274</td>\n",
       "      <td>0.000182</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000207</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000291</td>\n",
       "      <td>0.000126</td>\n",
       "      <td>0.000270</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.000147</td>\n",
       "      <td>0.000155</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>0.000155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NVDA</th>\n",
       "      <td>0.000191</td>\n",
       "      <td>0.000262</td>\n",
       "      <td>0.000136</td>\n",
       "      <td>0.000371</td>\n",
       "      <td>0.000248</td>\n",
       "      <td>0.000270</td>\n",
       "      <td>0.000198</td>\n",
       "      <td>0.000274</td>\n",
       "      <td>0.000756</td>\n",
       "      <td>0.000229</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000323</td>\n",
       "      <td>0.000188</td>\n",
       "      <td>0.000405</td>\n",
       "      <td>0.000173</td>\n",
       "      <td>0.000373</td>\n",
       "      <td>0.000196</td>\n",
       "      <td>0.000196</td>\n",
       "      <td>0.000196</td>\n",
       "      <td>0.000158</td>\n",
       "      <td>0.000222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DVN</th>\n",
       "      <td>0.000180</td>\n",
       "      <td>0.000170</td>\n",
       "      <td>0.000177</td>\n",
       "      <td>0.000259</td>\n",
       "      <td>0.000161</td>\n",
       "      <td>0.000160</td>\n",
       "      <td>0.000174</td>\n",
       "      <td>0.000182</td>\n",
       "      <td>0.000229</td>\n",
       "      <td>0.001018</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000518</td>\n",
       "      <td>0.000317</td>\n",
       "      <td>0.000669</td>\n",
       "      <td>0.000321</td>\n",
       "      <td>0.000607</td>\n",
       "      <td>0.000340</td>\n",
       "      <td>0.000363</td>\n",
       "      <td>0.000369</td>\n",
       "      <td>0.000357</td>\n",
       "      <td>0.000341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OXY</th>\n",
       "      <td>0.000157</td>\n",
       "      <td>0.000137</td>\n",
       "      <td>0.000166</td>\n",
       "      <td>0.000204</td>\n",
       "      <td>0.000139</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.000151</td>\n",
       "      <td>0.000154</td>\n",
       "      <td>0.000176</td>\n",
       "      <td>0.000703</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000406</td>\n",
       "      <td>0.000319</td>\n",
       "      <td>0.000667</td>\n",
       "      <td>0.000301</td>\n",
       "      <td>0.000619</td>\n",
       "      <td>0.000316</td>\n",
       "      <td>0.000338</td>\n",
       "      <td>0.000346</td>\n",
       "      <td>0.000337</td>\n",
       "      <td>0.000272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEE</th>\n",
       "      <td>0.000082</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>0.000092</td>\n",
       "      <td>0.000078</td>\n",
       "      <td>0.000093</td>\n",
       "      <td>0.000077</td>\n",
       "      <td>0.000066</td>\n",
       "      <td>0.000103</td>\n",
       "      <td>0.000063</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.000082</td>\n",
       "      <td>0.000180</td>\n",
       "      <td>0.000085</td>\n",
       "      <td>0.000181</td>\n",
       "      <td>0.000088</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>0.000085</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>0.000069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRO</th>\n",
       "      <td>0.000171</td>\n",
       "      <td>0.000152</td>\n",
       "      <td>0.000172</td>\n",
       "      <td>0.000228</td>\n",
       "      <td>0.000154</td>\n",
       "      <td>0.000149</td>\n",
       "      <td>0.000167</td>\n",
       "      <td>0.000174</td>\n",
       "      <td>0.000198</td>\n",
       "      <td>0.000881</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000475</td>\n",
       "      <td>0.000313</td>\n",
       "      <td>0.000621</td>\n",
       "      <td>0.000295</td>\n",
       "      <td>0.000564</td>\n",
       "      <td>0.000333</td>\n",
       "      <td>0.000363</td>\n",
       "      <td>0.000365</td>\n",
       "      <td>0.000339</td>\n",
       "      <td>0.000308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>APA</th>\n",
       "      <td>0.000185</td>\n",
       "      <td>0.000167</td>\n",
       "      <td>0.000182</td>\n",
       "      <td>0.000283</td>\n",
       "      <td>0.000168</td>\n",
       "      <td>0.000157</td>\n",
       "      <td>0.000169</td>\n",
       "      <td>0.000186</td>\n",
       "      <td>0.000231</td>\n",
       "      <td>0.000879</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000519</td>\n",
       "      <td>0.000353</td>\n",
       "      <td>0.000755</td>\n",
       "      <td>0.000346</td>\n",
       "      <td>0.000708</td>\n",
       "      <td>0.000369</td>\n",
       "      <td>0.000382</td>\n",
       "      <td>0.000402</td>\n",
       "      <td>0.000359</td>\n",
       "      <td>0.000331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRGP</th>\n",
       "      <td>0.000174</td>\n",
       "      <td>0.000165</td>\n",
       "      <td>0.000159</td>\n",
       "      <td>0.000316</td>\n",
       "      <td>0.000157</td>\n",
       "      <td>0.000152</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.000169</td>\n",
       "      <td>0.000226</td>\n",
       "      <td>0.000723</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000588</td>\n",
       "      <td>0.000331</td>\n",
       "      <td>0.000660</td>\n",
       "      <td>0.000340</td>\n",
       "      <td>0.000597</td>\n",
       "      <td>0.000336</td>\n",
       "      <td>0.000353</td>\n",
       "      <td>0.000351</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.000351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PSX</th>\n",
       "      <td>0.000139</td>\n",
       "      <td>0.000123</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000149</td>\n",
       "      <td>0.000130</td>\n",
       "      <td>0.000125</td>\n",
       "      <td>0.000134</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.000159</td>\n",
       "      <td>0.000436</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000356</td>\n",
       "      <td>0.000261</td>\n",
       "      <td>0.000500</td>\n",
       "      <td>0.000251</td>\n",
       "      <td>0.000447</td>\n",
       "      <td>0.000261</td>\n",
       "      <td>0.000272</td>\n",
       "      <td>0.000287</td>\n",
       "      <td>0.000252</td>\n",
       "      <td>0.000240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EQT</th>\n",
       "      <td>0.000112</td>\n",
       "      <td>0.000107</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>0.000143</td>\n",
       "      <td>0.000092</td>\n",
       "      <td>0.000098</td>\n",
       "      <td>0.000110</td>\n",
       "      <td>0.000110</td>\n",
       "      <td>0.000156</td>\n",
       "      <td>0.000416</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000255</td>\n",
       "      <td>0.000147</td>\n",
       "      <td>0.000365</td>\n",
       "      <td>0.000173</td>\n",
       "      <td>0.000332</td>\n",
       "      <td>0.000184</td>\n",
       "      <td>0.000210</td>\n",
       "      <td>0.000225</td>\n",
       "      <td>0.000163</td>\n",
       "      <td>0.000185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BA</th>\n",
       "      <td>0.000167</td>\n",
       "      <td>0.000171</td>\n",
       "      <td>0.000159</td>\n",
       "      <td>0.000247</td>\n",
       "      <td>0.000163</td>\n",
       "      <td>0.000157</td>\n",
       "      <td>0.000151</td>\n",
       "      <td>0.000162</td>\n",
       "      <td>0.000233</td>\n",
       "      <td>0.000335</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000472</td>\n",
       "      <td>0.000372</td>\n",
       "      <td>0.000654</td>\n",
       "      <td>0.000288</td>\n",
       "      <td>0.000584</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>0.000305</td>\n",
       "      <td>0.000334</td>\n",
       "      <td>0.000272</td>\n",
       "      <td>0.000284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GE</th>\n",
       "      <td>0.000133</td>\n",
       "      <td>0.000125</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.000162</td>\n",
       "      <td>0.000119</td>\n",
       "      <td>0.000116</td>\n",
       "      <td>0.000131</td>\n",
       "      <td>0.000122</td>\n",
       "      <td>0.000172</td>\n",
       "      <td>0.000284</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000349</td>\n",
       "      <td>0.000248</td>\n",
       "      <td>0.000509</td>\n",
       "      <td>0.000231</td>\n",
       "      <td>0.000477</td>\n",
       "      <td>0.000246</td>\n",
       "      <td>0.000261</td>\n",
       "      <td>0.000271</td>\n",
       "      <td>0.000224</td>\n",
       "      <td>0.000218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNI</th>\n",
       "      <td>0.000105</td>\n",
       "      <td>0.000112</td>\n",
       "      <td>0.000096</td>\n",
       "      <td>0.000128</td>\n",
       "      <td>0.000107</td>\n",
       "      <td>0.000114</td>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.000147</td>\n",
       "      <td>0.000202</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000213</td>\n",
       "      <td>0.000137</td>\n",
       "      <td>0.000289</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000264</td>\n",
       "      <td>0.000157</td>\n",
       "      <td>0.000155</td>\n",
       "      <td>0.000157</td>\n",
       "      <td>0.000139</td>\n",
       "      <td>0.000157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NOC</th>\n",
       "      <td>0.000086</td>\n",
       "      <td>0.000085</td>\n",
       "      <td>0.000091</td>\n",
       "      <td>0.000058</td>\n",
       "      <td>0.000080</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.000090</td>\n",
       "      <td>0.000058</td>\n",
       "      <td>0.000099</td>\n",
       "      <td>0.000114</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000115</td>\n",
       "      <td>0.000128</td>\n",
       "      <td>0.000200</td>\n",
       "      <td>0.000110</td>\n",
       "      <td>0.000188</td>\n",
       "      <td>0.000127</td>\n",
       "      <td>0.000118</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000114</td>\n",
       "      <td>0.000101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LPX</th>\n",
       "      <td>0.000168</td>\n",
       "      <td>0.000167</td>\n",
       "      <td>0.000155</td>\n",
       "      <td>0.000264</td>\n",
       "      <td>0.000167</td>\n",
       "      <td>0.000168</td>\n",
       "      <td>0.000156</td>\n",
       "      <td>0.000171</td>\n",
       "      <td>0.000254</td>\n",
       "      <td>0.000315</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000469</td>\n",
       "      <td>0.000262</td>\n",
       "      <td>0.000533</td>\n",
       "      <td>0.000259</td>\n",
       "      <td>0.000511</td>\n",
       "      <td>0.000272</td>\n",
       "      <td>0.000276</td>\n",
       "      <td>0.000273</td>\n",
       "      <td>0.000268</td>\n",
       "      <td>0.000263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BLDR</th>\n",
       "      <td>0.000187</td>\n",
       "      <td>0.000197</td>\n",
       "      <td>0.000163</td>\n",
       "      <td>0.000307</td>\n",
       "      <td>0.000188</td>\n",
       "      <td>0.000193</td>\n",
       "      <td>0.000161</td>\n",
       "      <td>0.000196</td>\n",
       "      <td>0.000302</td>\n",
       "      <td>0.000380</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000531</td>\n",
       "      <td>0.000306</td>\n",
       "      <td>0.000586</td>\n",
       "      <td>0.000304</td>\n",
       "      <td>0.000554</td>\n",
       "      <td>0.000318</td>\n",
       "      <td>0.000331</td>\n",
       "      <td>0.000307</td>\n",
       "      <td>0.000307</td>\n",
       "      <td>0.000322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAL</th>\n",
       "      <td>0.000166</td>\n",
       "      <td>0.000161</td>\n",
       "      <td>0.000160</td>\n",
       "      <td>0.000268</td>\n",
       "      <td>0.000165</td>\n",
       "      <td>0.000147</td>\n",
       "      <td>0.000155</td>\n",
       "      <td>0.000177</td>\n",
       "      <td>0.000247</td>\n",
       "      <td>0.000325</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000596</td>\n",
       "      <td>0.000376</td>\n",
       "      <td>0.000713</td>\n",
       "      <td>0.000317</td>\n",
       "      <td>0.000659</td>\n",
       "      <td>0.000339</td>\n",
       "      <td>0.000361</td>\n",
       "      <td>0.000375</td>\n",
       "      <td>0.000312</td>\n",
       "      <td>0.000325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPA</th>\n",
       "      <td>0.000146</td>\n",
       "      <td>0.000134</td>\n",
       "      <td>0.000131</td>\n",
       "      <td>0.000201</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000125</td>\n",
       "      <td>0.000158</td>\n",
       "      <td>0.000218</td>\n",
       "      <td>0.000339</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000527</td>\n",
       "      <td>0.000324</td>\n",
       "      <td>0.000611</td>\n",
       "      <td>0.000293</td>\n",
       "      <td>0.000556</td>\n",
       "      <td>0.000292</td>\n",
       "      <td>0.000294</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>0.000266</td>\n",
       "      <td>0.000290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAR</th>\n",
       "      <td>0.000221</td>\n",
       "      <td>0.000207</td>\n",
       "      <td>0.000200</td>\n",
       "      <td>0.000384</td>\n",
       "      <td>0.000223</td>\n",
       "      <td>0.000218</td>\n",
       "      <td>0.000211</td>\n",
       "      <td>0.000207</td>\n",
       "      <td>0.000323</td>\n",
       "      <td>0.000518</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002034</td>\n",
       "      <td>0.000442</td>\n",
       "      <td>0.000873</td>\n",
       "      <td>0.000407</td>\n",
       "      <td>0.000788</td>\n",
       "      <td>0.000427</td>\n",
       "      <td>0.000449</td>\n",
       "      <td>0.000448</td>\n",
       "      <td>0.000404</td>\n",
       "      <td>0.000464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HXL</th>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.000127</td>\n",
       "      <td>0.000141</td>\n",
       "      <td>0.000201</td>\n",
       "      <td>0.000137</td>\n",
       "      <td>0.000130</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000188</td>\n",
       "      <td>0.000317</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000442</td>\n",
       "      <td>0.000488</td>\n",
       "      <td>0.000565</td>\n",
       "      <td>0.000276</td>\n",
       "      <td>0.000515</td>\n",
       "      <td>0.000280</td>\n",
       "      <td>0.000304</td>\n",
       "      <td>0.000299</td>\n",
       "      <td>0.000278</td>\n",
       "      <td>0.000260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BHF</th>\n",
       "      <td>0.000301</td>\n",
       "      <td>0.000281</td>\n",
       "      <td>0.000316</td>\n",
       "      <td>0.000358</td>\n",
       "      <td>0.000279</td>\n",
       "      <td>0.000273</td>\n",
       "      <td>0.000289</td>\n",
       "      <td>0.000291</td>\n",
       "      <td>0.000405</td>\n",
       "      <td>0.000669</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000873</td>\n",
       "      <td>0.000565</td>\n",
       "      <td>0.001073</td>\n",
       "      <td>0.000636</td>\n",
       "      <td>0.000803</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>0.000683</td>\n",
       "      <td>0.000746</td>\n",
       "      <td>0.000589</td>\n",
       "      <td>0.000593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AIG</th>\n",
       "      <td>0.000148</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.000147</td>\n",
       "      <td>0.000180</td>\n",
       "      <td>0.000137</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.000136</td>\n",
       "      <td>0.000126</td>\n",
       "      <td>0.000173</td>\n",
       "      <td>0.000321</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000407</td>\n",
       "      <td>0.000276</td>\n",
       "      <td>0.000636</td>\n",
       "      <td>0.000407</td>\n",
       "      <td>0.000555</td>\n",
       "      <td>0.000308</td>\n",
       "      <td>0.000310</td>\n",
       "      <td>0.000334</td>\n",
       "      <td>0.000290</td>\n",
       "      <td>0.000274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EQH</th>\n",
       "      <td>0.000276</td>\n",
       "      <td>0.000268</td>\n",
       "      <td>0.000275</td>\n",
       "      <td>0.000340</td>\n",
       "      <td>0.000254</td>\n",
       "      <td>0.000253</td>\n",
       "      <td>0.000256</td>\n",
       "      <td>0.000270</td>\n",
       "      <td>0.000373</td>\n",
       "      <td>0.000607</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000788</td>\n",
       "      <td>0.000515</td>\n",
       "      <td>0.000803</td>\n",
       "      <td>0.000555</td>\n",
       "      <td>0.000733</td>\n",
       "      <td>0.000570</td>\n",
       "      <td>0.000597</td>\n",
       "      <td>0.000634</td>\n",
       "      <td>0.000522</td>\n",
       "      <td>0.000532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFG</th>\n",
       "      <td>0.000162</td>\n",
       "      <td>0.000148</td>\n",
       "      <td>0.000159</td>\n",
       "      <td>0.000178</td>\n",
       "      <td>0.000148</td>\n",
       "      <td>0.000150</td>\n",
       "      <td>0.000158</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.000196</td>\n",
       "      <td>0.000340</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000427</td>\n",
       "      <td>0.000280</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>0.000308</td>\n",
       "      <td>0.000570</td>\n",
       "      <td>0.000395</td>\n",
       "      <td>0.000334</td>\n",
       "      <td>0.000371</td>\n",
       "      <td>0.000302</td>\n",
       "      <td>0.000301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WBS</th>\n",
       "      <td>0.000161</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.000162</td>\n",
       "      <td>0.000184</td>\n",
       "      <td>0.000142</td>\n",
       "      <td>0.000141</td>\n",
       "      <td>0.000156</td>\n",
       "      <td>0.000147</td>\n",
       "      <td>0.000196</td>\n",
       "      <td>0.000363</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000449</td>\n",
       "      <td>0.000304</td>\n",
       "      <td>0.000683</td>\n",
       "      <td>0.000310</td>\n",
       "      <td>0.000597</td>\n",
       "      <td>0.000334</td>\n",
       "      <td>0.000516</td>\n",
       "      <td>0.000379</td>\n",
       "      <td>0.000382</td>\n",
       "      <td>0.000333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNM</th>\n",
       "      <td>0.000166</td>\n",
       "      <td>0.000146</td>\n",
       "      <td>0.000181</td>\n",
       "      <td>0.000175</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000143</td>\n",
       "      <td>0.000164</td>\n",
       "      <td>0.000155</td>\n",
       "      <td>0.000196</td>\n",
       "      <td>0.000369</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000448</td>\n",
       "      <td>0.000299</td>\n",
       "      <td>0.000746</td>\n",
       "      <td>0.000334</td>\n",
       "      <td>0.000634</td>\n",
       "      <td>0.000371</td>\n",
       "      <td>0.000379</td>\n",
       "      <td>0.000530</td>\n",
       "      <td>0.000332</td>\n",
       "      <td>0.000316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FHN</th>\n",
       "      <td>0.000141</td>\n",
       "      <td>0.000119</td>\n",
       "      <td>0.000141</td>\n",
       "      <td>0.000182</td>\n",
       "      <td>0.000117</td>\n",
       "      <td>0.000115</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>0.000158</td>\n",
       "      <td>0.000357</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000404</td>\n",
       "      <td>0.000278</td>\n",
       "      <td>0.000589</td>\n",
       "      <td>0.000290</td>\n",
       "      <td>0.000522</td>\n",
       "      <td>0.000302</td>\n",
       "      <td>0.000382</td>\n",
       "      <td>0.000332</td>\n",
       "      <td>0.000472</td>\n",
       "      <td>0.000297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LPLA</th>\n",
       "      <td>0.000155</td>\n",
       "      <td>0.000154</td>\n",
       "      <td>0.000135</td>\n",
       "      <td>0.000236</td>\n",
       "      <td>0.000159</td>\n",
       "      <td>0.000156</td>\n",
       "      <td>0.000146</td>\n",
       "      <td>0.000155</td>\n",
       "      <td>0.000222</td>\n",
       "      <td>0.000341</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000464</td>\n",
       "      <td>0.000260</td>\n",
       "      <td>0.000593</td>\n",
       "      <td>0.000274</td>\n",
       "      <td>0.000532</td>\n",
       "      <td>0.000301</td>\n",
       "      <td>0.000333</td>\n",
       "      <td>0.000316</td>\n",
       "      <td>0.000297</td>\n",
       "      <td>0.000566</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>35 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Symbols     ^GSPC      AAPL       IBM      TSLA     GOOGL      MSFT      CSCO  \\\n",
       "Symbols                                                                         \n",
       "^GSPC    0.000120  0.000140  0.000104  0.000169  0.000134  0.000142  0.000121   \n",
       "AAPL     0.000140  0.000333  0.000105  0.000236  0.000170  0.000187  0.000144   \n",
       "IBM      0.000104  0.000105  0.000219  0.000110  0.000103  0.000113  0.000124   \n",
       "TSLA     0.000169  0.000236  0.000110  0.001270  0.000215  0.000224  0.000149   \n",
       "GOOGL    0.000134  0.000170  0.000103  0.000215  0.000278  0.000191  0.000130   \n",
       "MSFT     0.000142  0.000187  0.000113  0.000224  0.000191  0.000282  0.000152   \n",
       "CSCO     0.000121  0.000144  0.000124  0.000149  0.000130  0.000152  0.000255   \n",
       "TSM      0.000121  0.000166  0.000100  0.000222  0.000150  0.000154  0.000122   \n",
       "NVDA     0.000191  0.000262  0.000136  0.000371  0.000248  0.000270  0.000198   \n",
       "DVN      0.000180  0.000170  0.000177  0.000259  0.000161  0.000160  0.000174   \n",
       "OXY      0.000157  0.000137  0.000166  0.000204  0.000139  0.000132  0.000151   \n",
       "NEE      0.000082  0.000081  0.000068  0.000092  0.000078  0.000093  0.000077   \n",
       "MRO      0.000171  0.000152  0.000172  0.000228  0.000154  0.000149  0.000167   \n",
       "APA      0.000185  0.000167  0.000182  0.000283  0.000168  0.000157  0.000169   \n",
       "TRGP     0.000174  0.000165  0.000159  0.000316  0.000157  0.000152  0.000144   \n",
       "PSX      0.000139  0.000123  0.000140  0.000149  0.000130  0.000125  0.000134   \n",
       "EQT      0.000112  0.000107  0.000097  0.000143  0.000092  0.000098  0.000110   \n",
       "BA       0.000167  0.000171  0.000159  0.000247  0.000163  0.000157  0.000151   \n",
       "GE       0.000133  0.000125  0.000144  0.000162  0.000119  0.000116  0.000131   \n",
       "CNI      0.000105  0.000112  0.000096  0.000128  0.000107  0.000114  0.000108   \n",
       "NOC      0.000086  0.000085  0.000091  0.000058  0.000080  0.000089  0.000090   \n",
       "LPX      0.000168  0.000167  0.000155  0.000264  0.000167  0.000168  0.000156   \n",
       "BLDR     0.000187  0.000197  0.000163  0.000307  0.000188  0.000193  0.000161   \n",
       "AAL      0.000166  0.000161  0.000160  0.000268  0.000165  0.000147  0.000155   \n",
       "CPA      0.000146  0.000134  0.000131  0.000201  0.000140  0.000140  0.000125   \n",
       "CAR      0.000221  0.000207  0.000200  0.000384  0.000223  0.000218  0.000211   \n",
       "HXL      0.000144  0.000127  0.000141  0.000201  0.000137  0.000130  0.000132   \n",
       "BHF      0.000301  0.000281  0.000316  0.000358  0.000279  0.000273  0.000289   \n",
       "AIG      0.000148  0.000132  0.000147  0.000180  0.000137  0.000132  0.000136   \n",
       "EQH      0.000276  0.000268  0.000275  0.000340  0.000254  0.000253  0.000256   \n",
       "PFG      0.000162  0.000148  0.000159  0.000178  0.000148  0.000150  0.000158   \n",
       "WBS      0.000161  0.000144  0.000162  0.000184  0.000142  0.000141  0.000156   \n",
       "UNM      0.000166  0.000146  0.000181  0.000175  0.000140  0.000143  0.000164   \n",
       "FHN      0.000141  0.000119  0.000141  0.000182  0.000117  0.000115  0.000133   \n",
       "LPLA     0.000155  0.000154  0.000135  0.000236  0.000159  0.000156  0.000146   \n",
       "\n",
       "Symbols       TSM      NVDA       DVN  ...       CAR       HXL       BHF  \\\n",
       "Symbols                                ...                                 \n",
       "^GSPC    0.000121  0.000191  0.000180  ...  0.000221  0.000144  0.000301   \n",
       "AAPL     0.000166  0.000262  0.000170  ...  0.000207  0.000127  0.000281   \n",
       "IBM      0.000100  0.000136  0.000177  ...  0.000200  0.000141  0.000316   \n",
       "TSLA     0.000222  0.000371  0.000259  ...  0.000384  0.000201  0.000358   \n",
       "GOOGL    0.000150  0.000248  0.000161  ...  0.000223  0.000137  0.000279   \n",
       "MSFT     0.000154  0.000270  0.000160  ...  0.000218  0.000130  0.000273   \n",
       "CSCO     0.000122  0.000198  0.000174  ...  0.000211  0.000132  0.000289   \n",
       "TSM      0.000338  0.000274  0.000182  ...  0.000207  0.000140  0.000291   \n",
       "NVDA     0.000274  0.000756  0.000229  ...  0.000323  0.000188  0.000405   \n",
       "DVN      0.000182  0.000229  0.001018  ...  0.000518  0.000317  0.000669   \n",
       "OXY      0.000154  0.000176  0.000703  ...  0.000406  0.000319  0.000667   \n",
       "NEE      0.000066  0.000103  0.000063  ...  0.000095  0.000082  0.000180   \n",
       "MRO      0.000174  0.000198  0.000881  ...  0.000475  0.000313  0.000621   \n",
       "APA      0.000186  0.000231  0.000879  ...  0.000519  0.000353  0.000755   \n",
       "TRGP     0.000169  0.000226  0.000723  ...  0.000588  0.000331  0.000660   \n",
       "PSX      0.000132  0.000159  0.000436  ...  0.000356  0.000261  0.000500   \n",
       "EQT      0.000110  0.000156  0.000416  ...  0.000255  0.000147  0.000365   \n",
       "BA       0.000162  0.000233  0.000335  ...  0.000472  0.000372  0.000654   \n",
       "GE       0.000122  0.000172  0.000284  ...  0.000349  0.000248  0.000509   \n",
       "CNI      0.000108  0.000147  0.000202  ...  0.000213  0.000137  0.000289   \n",
       "NOC      0.000058  0.000099  0.000114  ...  0.000115  0.000128  0.000200   \n",
       "LPX      0.000171  0.000254  0.000315  ...  0.000469  0.000262  0.000533   \n",
       "BLDR     0.000196  0.000302  0.000380  ...  0.000531  0.000306  0.000586   \n",
       "AAL      0.000177  0.000247  0.000325  ...  0.000596  0.000376  0.000713   \n",
       "CPA      0.000158  0.000218  0.000339  ...  0.000527  0.000324  0.000611   \n",
       "CAR      0.000207  0.000323  0.000518  ...  0.002034  0.000442  0.000873   \n",
       "HXL      0.000140  0.000188  0.000317  ...  0.000442  0.000488  0.000565   \n",
       "BHF      0.000291  0.000405  0.000669  ...  0.000873  0.000565  0.001073   \n",
       "AIG      0.000126  0.000173  0.000321  ...  0.000407  0.000276  0.000636   \n",
       "EQH      0.000270  0.000373  0.000607  ...  0.000788  0.000515  0.000803   \n",
       "PFG      0.000144  0.000196  0.000340  ...  0.000427  0.000280  0.000645   \n",
       "WBS      0.000147  0.000196  0.000363  ...  0.000449  0.000304  0.000683   \n",
       "UNM      0.000155  0.000196  0.000369  ...  0.000448  0.000299  0.000746   \n",
       "FHN      0.000121  0.000158  0.000357  ...  0.000404  0.000278  0.000589   \n",
       "LPLA     0.000155  0.000222  0.000341  ...  0.000464  0.000260  0.000593   \n",
       "\n",
       "Symbols       AIG       EQH       PFG       WBS       UNM       FHN      LPLA  \n",
       "Symbols                                                                        \n",
       "^GSPC    0.000148  0.000276  0.000162  0.000161  0.000166  0.000141  0.000155  \n",
       "AAPL     0.000132  0.000268  0.000148  0.000144  0.000146  0.000119  0.000154  \n",
       "IBM      0.000147  0.000275  0.000159  0.000162  0.000181  0.000141  0.000135  \n",
       "TSLA     0.000180  0.000340  0.000178  0.000184  0.000175  0.000182  0.000236  \n",
       "GOOGL    0.000137  0.000254  0.000148  0.000142  0.000140  0.000117  0.000159  \n",
       "MSFT     0.000132  0.000253  0.000150  0.000141  0.000143  0.000115  0.000156  \n",
       "CSCO     0.000136  0.000256  0.000158  0.000156  0.000164  0.000133  0.000146  \n",
       "TSM      0.000126  0.000270  0.000144  0.000147  0.000155  0.000121  0.000155  \n",
       "NVDA     0.000173  0.000373  0.000196  0.000196  0.000196  0.000158  0.000222  \n",
       "DVN      0.000321  0.000607  0.000340  0.000363  0.000369  0.000357  0.000341  \n",
       "OXY      0.000301  0.000619  0.000316  0.000338  0.000346  0.000337  0.000272  \n",
       "NEE      0.000085  0.000181  0.000088  0.000069  0.000085  0.000071  0.000069  \n",
       "MRO      0.000295  0.000564  0.000333  0.000363  0.000365  0.000339  0.000308  \n",
       "APA      0.000346  0.000708  0.000369  0.000382  0.000402  0.000359  0.000331  \n",
       "TRGP     0.000340  0.000597  0.000336  0.000353  0.000351  0.000343  0.000351  \n",
       "PSX      0.000251  0.000447  0.000261  0.000272  0.000287  0.000252  0.000240  \n",
       "EQT      0.000173  0.000332  0.000184  0.000210  0.000225  0.000163  0.000185  \n",
       "BA       0.000288  0.000584  0.000300  0.000305  0.000334  0.000272  0.000284  \n",
       "GE       0.000231  0.000477  0.000246  0.000261  0.000271  0.000224  0.000218  \n",
       "CNI      0.000140  0.000264  0.000157  0.000155  0.000157  0.000139  0.000157  \n",
       "NOC      0.000110  0.000188  0.000127  0.000118  0.000140  0.000114  0.000101  \n",
       "LPX      0.000259  0.000511  0.000272  0.000276  0.000273  0.000268  0.000263  \n",
       "BLDR     0.000304  0.000554  0.000318  0.000331  0.000307  0.000307  0.000322  \n",
       "AAL      0.000317  0.000659  0.000339  0.000361  0.000375  0.000312  0.000325  \n",
       "CPA      0.000293  0.000556  0.000292  0.000294  0.000300  0.000266  0.000290  \n",
       "CAR      0.000407  0.000788  0.000427  0.000449  0.000448  0.000404  0.000464  \n",
       "HXL      0.000276  0.000515  0.000280  0.000304  0.000299  0.000278  0.000260  \n",
       "BHF      0.000636  0.000803  0.000645  0.000683  0.000746  0.000589  0.000593  \n",
       "AIG      0.000407  0.000555  0.000308  0.000310  0.000334  0.000290  0.000274  \n",
       "EQH      0.000555  0.000733  0.000570  0.000597  0.000634  0.000522  0.000532  \n",
       "PFG      0.000308  0.000570  0.000395  0.000334  0.000371  0.000302  0.000301  \n",
       "WBS      0.000310  0.000597  0.000334  0.000516  0.000379  0.000382  0.000333  \n",
       "UNM      0.000334  0.000634  0.000371  0.000379  0.000530  0.000332  0.000316  \n",
       "FHN      0.000290  0.000522  0.000302  0.000382  0.000332  0.000472  0.000297  \n",
       "LPLA     0.000274  0.000532  0.000301  0.000333  0.000316  0.000297  0.000566  \n",
       "\n",
       "[35 rows x 35 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import data\n",
    "def getData(basket_list, start_date, end_date):\n",
    "    stockData = pdr.get_data_yahoo(basket_list, start = start_date, end = end_date)\n",
    "    stockData = stockData['Close']\n",
    "\n",
    "    returns = stockData.pct_change()\n",
    "    meanReturns = returns.mean()\n",
    "    covMatrix = returns.cov()\n",
    "    return meanReturns, covMatrix\n",
    "\n",
    "# call it\n",
    "meanReturns, covMatrix = getData(basket_list, start_date, end_date)\n",
    "display(meanReturns)\n",
    "display(covMatrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "299b8075-1011-4870-8c52-73d7672b19e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\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>Symbols</th>\n",
       "      <th>^GSPC</th>\n",
       "      <th>AAPL</th>\n",
       "      <th>IBM</th>\n",
       "      <th>TSLA</th>\n",
       "      <th>GOOGL</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>CSCO</th>\n",
       "      <th>TSM</th>\n",
       "      <th>NVDA</th>\n",
       "      <th>DVN</th>\n",
       "      <th>...</th>\n",
       "      <th>CAR</th>\n",
       "      <th>HXL</th>\n",
       "      <th>BHF</th>\n",
       "      <th>AIG</th>\n",
       "      <th>EQH</th>\n",
       "      <th>PFG</th>\n",
       "      <th>WBS</th>\n",
       "      <th>UNM</th>\n",
       "      <th>FHN</th>\n",
       "      <th>LPLA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-11</th>\n",
       "      <td>0.001706</td>\n",
       "      <td>-0.007659</td>\n",
       "      <td>-0.000693</td>\n",
       "      <td>-0.013068</td>\n",
       "      <td>-0.001892</td>\n",
       "      <td>-0.002147</td>\n",
       "      <td>-0.008023</td>\n",
       "      <td>0.003514</td>\n",
       "      <td>-0.021763</td>\n",
       "      <td>0.001466</td>\n",
       "      <td>...</td>\n",
       "      <td>0.007865</td>\n",
       "      <td>0.004317</td>\n",
       "      <td>-0.011573</td>\n",
       "      <td>0.001894</td>\n",
       "      <td>0.050334</td>\n",
       "      <td>0.004755</td>\n",
       "      <td>0.003458</td>\n",
       "      <td>-0.001580</td>\n",
       "      <td>0.006851</td>\n",
       "      <td>-0.001292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-14</th>\n",
       "      <td>0.000883</td>\n",
       "      <td>-0.002336</td>\n",
       "      <td>0.001109</td>\n",
       "      <td>-0.030659</td>\n",
       "      <td>0.002914</td>\n",
       "      <td>0.003372</td>\n",
       "      <td>-0.005020</td>\n",
       "      <td>0.001002</td>\n",
       "      <td>0.003256</td>\n",
       "      <td>0.008995</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004442</td>\n",
       "      <td>0.014240</td>\n",
       "      <td>0.001324</td>\n",
       "      <td>0.005129</td>\n",
       "      <td>0.001354</td>\n",
       "      <td>-0.002671</td>\n",
       "      <td>-0.001846</td>\n",
       "      <td>-0.007380</td>\n",
       "      <td>0.001436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-15</th>\n",
       "      <td>-0.006866</td>\n",
       "      <td>-0.009130</td>\n",
       "      <td>-0.003888</td>\n",
       "      <td>-0.027043</td>\n",
       "      <td>-0.019832</td>\n",
       "      <td>-0.007269</td>\n",
       "      <td>-0.004826</td>\n",
       "      <td>-0.016404</td>\n",
       "      <td>-0.039133</td>\n",
       "      <td>-0.000969</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.008330</td>\n",
       "      <td>-0.001860</td>\n",
       "      <td>-0.007817</td>\n",
       "      <td>0.005841</td>\n",
       "      <td>0.004640</td>\n",
       "      <td>0.000846</td>\n",
       "      <td>0.009084</td>\n",
       "      <td>0.006053</td>\n",
       "      <td>0.015748</td>\n",
       "      <td>0.000717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-16</th>\n",
       "      <td>0.004052</td>\n",
       "      <td>0.009289</td>\n",
       "      <td>0.006173</td>\n",
       "      <td>0.008061</td>\n",
       "      <td>-0.000719</td>\n",
       "      <td>-0.001748</td>\n",
       "      <td>-0.007061</td>\n",
       "      <td>0.012391</td>\n",
       "      <td>0.001831</td>\n",
       "      <td>0.002903</td>\n",
       "      <td>...</td>\n",
       "      <td>0.017960</td>\n",
       "      <td>0.001002</td>\n",
       "      <td>-0.017500</td>\n",
       "      <td>0.008977</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004554</td>\n",
       "      <td>0.006062</td>\n",
       "      <td>0.009402</td>\n",
       "      <td>0.013451</td>\n",
       "      <td>-0.000861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-17</th>\n",
       "      <td>-0.000856</td>\n",
       "      <td>-0.006344</td>\n",
       "      <td>-0.000899</td>\n",
       "      <td>-0.006795</td>\n",
       "      <td>-0.002614</td>\n",
       "      <td>-0.010035</td>\n",
       "      <td>-0.038371</td>\n",
       "      <td>-0.021080</td>\n",
       "      <td>0.006887</td>\n",
       "      <td>0.022924</td>\n",
       "      <td>...</td>\n",
       "      <td>0.021001</td>\n",
       "      <td>0.007697</td>\n",
       "      <td>0.008163</td>\n",
       "      <td>0.019909</td>\n",
       "      <td>0.003697</td>\n",
       "      <td>0.002689</td>\n",
       "      <td>0.005255</td>\n",
       "      <td>0.010087</td>\n",
       "      <td>0.004103</td>\n",
       "      <td>0.005438</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Symbols        ^GSPC      AAPL       IBM      TSLA     GOOGL      MSFT  \\\n",
       "Date                                                                     \n",
       "2018-05-11  0.001706 -0.007659 -0.000693 -0.013068 -0.001892 -0.002147   \n",
       "2018-05-14  0.000883 -0.002336  0.001109 -0.030659  0.002914  0.003372   \n",
       "2018-05-15 -0.006866 -0.009130 -0.003888 -0.027043 -0.019832 -0.007269   \n",
       "2018-05-16  0.004052  0.009289  0.006173  0.008061 -0.000719 -0.001748   \n",
       "2018-05-17 -0.000856 -0.006344 -0.000899 -0.006795 -0.002614 -0.010035   \n",
       "\n",
       "Symbols         CSCO       TSM      NVDA       DVN  ...       CAR       HXL  \\\n",
       "Date                                                ...                       \n",
       "2018-05-11 -0.008023  0.003514 -0.021763  0.001466  ...  0.007865  0.004317   \n",
       "2018-05-14 -0.005020  0.001002  0.003256  0.008995  ...  0.000000  0.004442   \n",
       "2018-05-15 -0.004826 -0.016404 -0.039133 -0.000969  ... -0.008330 -0.001860   \n",
       "2018-05-16 -0.007061  0.012391  0.001831  0.002903  ...  0.017960  0.001002   \n",
       "2018-05-17 -0.038371 -0.021080  0.006887  0.022924  ...  0.021001  0.007697   \n",
       "\n",
       "Symbols          BHF       AIG       EQH       PFG       WBS       UNM  \\\n",
       "Date                                                                     \n",
       "2018-05-11 -0.011573  0.001894  0.050334  0.004755  0.003458 -0.001580   \n",
       "2018-05-14  0.014240  0.001324  0.005129  0.001354 -0.002671 -0.001846   \n",
       "2018-05-15 -0.007817  0.005841  0.004640  0.000846  0.009084  0.006053   \n",
       "2018-05-16 -0.017500  0.008977  0.000000  0.004554  0.006062  0.009402   \n",
       "2018-05-17  0.008163  0.019909  0.003697  0.002689  0.005255  0.010087   \n",
       "\n",
       "Symbols          FHN      LPLA  \n",
       "Date                            \n",
       "2018-05-11  0.006851 -0.001292  \n",
       "2018-05-14 -0.007380  0.001436  \n",
       "2018-05-15  0.015748  0.000717  \n",
       "2018-05-16  0.013451 -0.000861  \n",
       "2018-05-17  0.004103  0.005438  \n",
       "\n",
       "[5 rows x 35 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pdr.get_data_yahoo(basket_list, start_date, end_date)\n",
    "log_returns = np.log(df.Close / df.Close.shift(1)).dropna()\n",
    "log_returns.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48629003-8270-44bf-870c-7d279227eea8",
   "metadata": {},
   "source": [
    "### Directly calculate beta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1e18f9a1-9af9-4dae-af62-0296e3907346",
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_beta(df):\n",
    "    np_array = df.values\n",
    "    # Market index is the first column 0\n",
    "    m = np_array[:,0] \n",
    "    beta = []\n",
    "    for ind, col in enumerate(df):\n",
    "        if ind > 0:\n",
    "            # stock returns are indexed by ind\n",
    "            s = np_array[:,ind] \n",
    "            # Calculate covariance matrix between stock and market\n",
    "            covariance = np.cov(s,m) \n",
    "            beta.append( covariance[0,1]/covariance[1,1] )\n",
    "    return pd.Series(beta, df.columns[1:], name='Beta')\n",
    "\n",
    "beta = calc_beta(log_returns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc4ebd65-7515-448f-b6bf-7da596fe74e7",
   "metadata": {},
   "source": [
    "### Define your Portfolio and make DataFrame\n",
    "Calculate Beta Weighted Portfolio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5124e6af-f7ca-4d38-accb-8226969daef3",
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "operands could not be broadcast together with shapes (5,) (34,) ",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m/var/folders/t7/x7q1pbqj4ss8841vmphkd2v00000gn/T/ipykernel_4395/3515204161.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0;34m'Price'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mprice\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m     \u001b[0;34m'Units'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0munits\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m     \u001b[0;34m'Value'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0munits\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mprice\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     16\u001b[0m     \u001b[0;34m'Weight'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m     \u001b[0;34m'Beta'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mbeta\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: operands could not be broadcast together with shapes (5,) (34,) "
     ]
    }
   ],
   "source": [
    "units = np.array([100, 250, 300, 400, 200])\n",
    "ASXprices = df.Close[-1:].values.tolist()[0]\n",
    "price = np.array([round(price,2) for price in ASXprices[1:]])\n",
    "value = [unit*pr for unit, pr in zip(units, price)]\n",
    "weight = [round(val/sum(value),2) for val in value]\n",
    "beta = round(beta,2)\n",
    "\n",
    "Portfolio = pd.DataFrame({\n",
    "    'Stock': basket_list,\n",
    "    'Direction': 'Long',\n",
    "    'Type': 'S',\n",
    "    'Stock Price': price,\n",
    "    'Price': price,\n",
    "    'Units': units,\n",
    "    'Value': units*price,\n",
    "    'Weight': weight,\n",
    "    'Beta': beta,\n",
    "    'Weighted Beta': weight*beta\n",
    "})\n",
    "Portfolio"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7edc5c4c-f9d4-4763-834a-69001a15a06c",
   "metadata": {},
   "source": [
    "### Weight the Delta’s using Beta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "57df8cf4-4256-41b0-a8ed-c84c107716d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "Portfolio['ASX200 Weighted Delta (point)'] = round(Portfolio['Beta'] * (Portfolio['Stock Price']/ASXprices[0]) * Portfolio['Delta'],2) \n",
    "Portfolio['ASX200 Weighted Delta (1%)'] = round(Portfolio['Beta'] * (Portfolio['Stock Price']) * Portfolio['Delta'] * 0.01,2) \n",
    "Portfolio"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "945ea14b-d133-417d-b46d-f77e3716c714",
   "metadata": {},
   "source": [
    "### Total the Delta’s to get Portfolio Overview"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "365b2c48-50a8-416c-b61d-58343eeecc87",
   "metadata": {},
   "outputs": [],
   "source": [
    "Portfolio.loc['Total', ['Value', 'ASX200 Weighted Delta (point)', 'ASX200 Weighted Delta (1%)']] \\\n",
    "= Portfolio[['Value','ASX200 Weighted Delta (point)', 'ASX200 Weighted Delta (1%)']].sum()\n",
    "Portfolio"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6381693-0465-4fb8-b3a9-86e35406e1f6",
   "metadata": {},
   "source": [
    "### calculate portfolioPerformance metrics. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4d61015c-9ef9-417d-985d-805f1d7494c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def portfolioPerformance(weights, meanReturns, covMatrix):\n",
    "    returns = np.sum(meanReturns*weights)*252\n",
    "    std = np.sqrt(\n",
    "            np.dot(weights.T,np.dot(covMatrix, weights))\n",
    "           )*np.sqrt(252)\n",
    "    return returns, std\n",
    "\n",
    "# call it\n",
    "returns, std = portfolioPerformance(weights, meanReturns, covMatrix)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7dca4f1e-f2a9-4c35-8f3d-8cea71c08b3f",
   "metadata": {},
   "source": [
    "### Maximium Sharpe Ratio Portfolio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "190333d5-7fd7-442f-856e-8e14d6297fcc",
   "metadata": {},
   "outputs": [],
   "source": [
    "def negativeSR(weights, meanReturns, covMatrix, riskFreeRate = 0):\n",
    "    pReturns, pStd = portfolioPerformance(weights, meanReturns, covMatrix)\n",
    "    return - (pReturns - riskFreeRate)/pStd\n",
    "\n",
    "def maxSR(meanReturns, covMatrix, riskFreeRate = 0, constraintSet=(0,1)):\n",
    "    \"Minimize the negative SR, by altering the weights of the portfolio\"\n",
    "    numAssets = len(meanReturns)\n",
    "    args = (meanReturns, covMatrix, riskFreeRate)\n",
    "    constraints = ({'type': 'eq', 'fun': lambda x: np.sum(x) - 1})\n",
    "    bound = constraintSet\n",
    "    bounds = tuple(bound for asset in range(numAssets))\n",
    "    result = sc.minimize(negativeSR, numAssets*[1./numAssets], args=args,\n",
    "                        method='SLSQP', bounds=bounds, constraints=constraints)\n",
    "    return result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3a4eb12-345a-412f-a8f6-039ec376fc1a",
   "metadata": {},
   "source": [
    "### Minimium Portfolio Variance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ea2cd87d-7308-4121-99a2-a2382b36e156",
   "metadata": {},
   "outputs": [],
   "source": [
    "def portfolioVariance(weights, meanReturns, covMatrix):\n",
    "    return portfolioPerformance(weights, meanReturns, covMatrix)[1]\n",
    "\n",
    "def minimizeVariance(meanReturns, covMatrix, constraintSet=(0,1)):\n",
    "    \"\"\"Minimize the portfolio variance by altering the \n",
    "     weights/allocation of assets in the portfolio\"\"\"\n",
    "    numAssets = len(meanReturns)\n",
    "    args = (meanReturns, covMatrix)\n",
    "    constraints = ({'type': 'eq', 'fun': lambda x: np.sum(x) - 1})\n",
    "    bound = constraintSet\n",
    "    bounds = tuple(bound for asset in range(numAssets))\n",
    "    result = sc.minimize(portfolioVariance, numAssets*[1./numAssets], args=args,\n",
    "                        method='SLSQP', bounds=bounds, constraints=constraints)\n",
    "    return result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c982d9c8-cb7b-42a2-bec4-2acd70f0bc9a",
   "metadata": {},
   "source": [
    "### Creating the Efficient Frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c7ca5cf5-c375-41f2-95ac-348563f2681c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def portfolioReturn(weights, meanReturns, covMatrix):\n",
    "        return portfolioPerformance(weights, meanReturns, covMatrix)[0]\n",
    "\n",
    "\n",
    "def efficientOpt(meanReturns, covMatrix, returnTarget, constraintSet=(0,1)):\n",
    "    \"\"\"For each returnTarget, we want to optimise the portfolio for min variance\"\"\"\n",
    "    numAssets = len(meanReturns)\n",
    "    args = (meanReturns, covMatrix)\n",
    "\n",
    "    constraints = ({'type':'eq', 'fun': lambda x: portfolioReturn(x, meanReturns, covMatrix) - returnTarget},\n",
    "                    {'type': 'eq', 'fun': lambda x: np.sum(x) - 1})\n",
    "    bound = constraintSet\n",
    "    bounds = tuple(bound for asset in range(numAssets))\n",
    "    effOpt = sc.minimize(portfolioVariance, numAssets*[1./numAssets], args=args, method = 'SLSQP', bounds=bounds, constraints=constraints)\n",
    "    return effOpt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5272deba-ae11-49ed-895a-dcc21803a415",
   "metadata": {},
   "source": [
    "### callable function for graphing package like Plotly/Dash combination"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dc42c7c8-f9af-448a-b133-1b875880a983",
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculatedResults(meanReturns, covMatrix, riskFreeRate=0.03, constraintSet=(0,1)):\n",
    "    \"\"\"Read in mean, cov matrix, and other financial information\n",
    "        Output, Max SR , Min Volatility, efficient frontier \"\"\"\n",
    "    # Max Sharpe Ratio Portfolio\n",
    "    maxSR_Portfolio = maxSR(meanReturns, covMatrix)\n",
    "    maxSR_returns, maxSR_std = portfolioPerformance(maxSR_Portfolio['x'], meanReturns, covMatrix)\n",
    "    maxSR_returns, maxSR_std = round(maxSR_returns*100,2), round(maxSR_std*100,2)\n",
    "    maxSR_allocation = pd.DataFrame(maxSR_Portfolio['x'], index=meanReturns.index, columns=['allocation'])\n",
    "    maxSR_allocation.allocation = [round(i*100,0) for i in maxSR_allocation.allocation]\n",
    "    \n",
    "    # Min Volatility Portfolio\n",
    "    minVol_Portfolio = minimizeVariance(meanReturns, covMatrix)\n",
    "    minVol_returns, minVol_std = portfolioPerformance(minVol_Portfolio['x'], meanReturns, covMatrix)\n",
    "    minVol_returns, minVol_std = round(minVol_returns*100,2), round(minVol_std*100,2)\n",
    "    minVol_allocation = pd.DataFrame(minVol_Portfolio['x'], index=meanReturns.index, columns=['allocation'])\n",
    "    minVol_allocation.allocation = [round(i*100,0) for i in minVol_allocation.allocation]\n",
    "\n",
    "    # Efficient Frontier\n",
    "    efficientList = []\n",
    "    targetReturns = np.linspace(minVol_returns, maxSR_returns, 20)\n",
    "    for target in targetReturns:\n",
    "        efficientList.append(efficientOpt(meanReturns, covMatrix, target)['fun'])\n",
    "\n",
    "    return maxSR_returns, maxSR_std, maxSR_allocation, minVol_returns, minVol_std, minVol_allocation, efficientList"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b81b3b7-c1e1-4273-a961-dd4b7c5d5fc6",
   "metadata": {},
   "source": [
    "### Visualising the Efficient Frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7fdc7e3b-eb27-4abe-8614-be1188dd7a6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def EF_graph(meanReturns, covMatrix, riskFreeRate=0, constraintSet=(0,1)):\n",
    "    \"\"\"Return a graph ploting the min vol, max sr and efficient frontier\"\"\"\n",
    "    maxSR_returns, maxSR_std, maxSR_allocation, minVol_returns, minVol_std, minVol_allocation, efficientList, targetReturns = calculatedResults(meanReturns, covMatrix, riskFreeRate, constraintSet)\n",
    "\n",
    "    #Max SR\n",
    "    MaxSharpeRatio = go.Scatter(\n",
    "        name='Maximium Sharpe Ratio',\n",
    "        mode='markers',\n",
    "        x=[maxSR_std],\n",
    "        y=[maxSR_returns],\n",
    "        marker=dict(color='red',size=14,line=dict(width=3, color='black'))\n",
    "    )\n",
    "\n",
    "    #Min Vol\n",
    "    MinVol = go.Scatter(\n",
    "        name='Mininium Volatility',\n",
    "        mode='markers',\n",
    "        x=[minVol_std],\n",
    "        y=[minVol_returns],\n",
    "        marker=dict(color='green',size=14,line=dict(width=3, color='black'))\n",
    "    )\n",
    "\n",
    "    #Efficient Frontier\n",
    "    EF_curve = go.Scatter(\n",
    "        name='Efficient Frontier',\n",
    "        mode='lines',\n",
    "        x=[round(ef_std*100, 2) for ef_std in efficientList],\n",
    "        y=[round(target*100, 2) for target in targetReturns],\n",
    "        line=dict(color='black', width=4, dash='dashdot')\n",
    "    )\n",
    "\n",
    "    data = [MaxSharpeRatio, MinVol, EF_curve]\n",
    "\n",
    "    layout = go.Layout(\n",
    "        title = 'Portfolio Optimisation with the Efficient Frontier',\n",
    "        yaxis = dict(title='Annualised Return (%)'),\n",
    "        xaxis = dict(title='Annualised Volatility (%)'),\n",
    "        showlegend = True,\n",
    "        legend = dict(\n",
    "            x = 0.75, y = 0, traceorder='normal',\n",
    "            bgcolor='#E2E2E2',\n",
    "            bordercolor='black',\n",
    "            borderwidth=2),\n",
    "        width=800,\n",
    "        height=600)\n",
    "    \n",
    "    fig = go.Figure(data=data, layout=layout)\n",
    "    return fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "003f923a-e53f-4cfe-8287-767a78ca0a7e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4b81834f-c01e-4334-90be-7c5314bbbbda",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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