python/notebooks/ch3_neutral_long-short_optimization.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "LaTeX macros (hidden cell)\n",
    "$\n",
    "\\newcommand{\\Q}{\\mathcal{Q}}\n",
    "\\newcommand{\\ECov}{\\boldsymbol{\\Sigma}}\n",
    "\\newcommand{\\EMean}{\\boldsymbol{\\mu}}\n",
    "\\newcommand{\\EAlpha}{\\boldsymbol{\\alpha}}\n",
    "\\newcommand{\\EBeta}{\\boldsymbol{\\beta}}\n",
    "$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Imports and configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "import os\n",
    "import re\n",
    "import datetime as dt\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "%matplotlib inline\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.colors import LinearSegmentedColormap\n",
    "\n",
    "from mosek.fusion import *\n",
    "import mosek.fusion.pythonic   # Requires MOSEK >= 10.2\n",
    "\n",
    "from notebook.services.config import ConfigManager\n",
    "\n",
    "from portfolio_tools import data_download, DataReader, compute_inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.9.7 (default, Sep 16 2021, 13:09:58) \n",
      "[GCC 7.5.0]\n",
      "matplotlib: 3.4.3\n"
     ]
    }
   ],
   "source": [
    "# Version checks\n",
    "print(sys.version)\n",
    "print('matplotlib: {}'.format(matplotlib.__version__))\n",
    "\n",
    "# Jupyter configuration\n",
    "c = ConfigManager()\n",
    "c.update('notebook', {\"CodeCell\": {\"cm_config\": {\"autoCloseBrackets\": False}}})  \n",
    "\n",
    "# Numpy options\n",
    "np.set_printoptions(precision=5, linewidth=120, suppress=True)\n",
    "\n",
    "# Pandas options\n",
    "pd.set_option('display.max_rows', None)\n",
    "\n",
    "# Matplotlib options\n",
    "plt.rcParams['figure.figsize'] = [12, 8]\n",
    "plt.rcParams['figure.dpi'] = 200"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prepare input data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we load the raw data that will be used to compute the optimization input variables, the vector $\\EMean$ of expected returns and the covariance matrix $\\ECov$. The data consists of daily stock prices of $8$ stocks from the US market. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data downloading:\n",
    "# If the user has an API key for alphavantage.co, then this code part will download the data. \n",
    "# The code can be modified to download from other sources. To be able to run the examples, \n",
    "# and reproduce results in the cookbook, the files have to have the following format and content:\n",
    "# - File name pattern: \"daily_adjusted_[TICKER].csv\", where TICKER is the symbol of a stock. \n",
    "# - The file contains at least columns \"timestamp\", \"adjusted_close\", and \"volume\".\n",
    "# - The data is daily price/volume, covering at least the period from 2016-03-18 until 2021-03-18, \n",
    "# - Files are for the stocks PM, LMT, MCD, MMM, AAPL, MSFT, TXN, CSCO.\n",
    "list_stocks = [\"PM\", \"LMT\", \"MCD\", \"MMM\", \"AAPL\", \"MSFT\", \"TXN\", \"CSCO\"]\n",
    "list_factors = []\n",
    "alphaToken = None\n",
    " \n",
    "list_tickers = list_stocks + list_factors\n",
    "if alphaToken is not None:\n",
    "    data_download(list_tickers, alphaToken)  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We load the daily stock price data from the downloaded CSV files. The data is adjusted for splits and dividends. Then a selected time period is taken from the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "investment_start = \"2016-03-18\"\n",
    "investment_end = \"2021-03-18\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found data files: \n",
      "stock_data/daily_adjusted_AAPL.csv\n",
      "stock_data/daily_adjusted_PM.csv\n",
      "stock_data/daily_adjusted_CSCO.csv\n",
      "stock_data/daily_adjusted_TXN.csv\n",
      "stock_data/daily_adjusted_MMM.csv\n",
      "stock_data/daily_adjusted_IWM.csv\n",
      "stock_data/daily_adjusted_MCD.csv\n",
      "stock_data/daily_adjusted_SPY.csv\n",
      "stock_data/daily_adjusted_MSFT.csv\n",
      "stock_data/daily_adjusted_LMT.csv\n",
      "\n",
      "Using data files: \n",
      "stock_data/daily_adjusted_PM.csv\n",
      "stock_data/daily_adjusted_LMT.csv\n",
      "stock_data/daily_adjusted_MCD.csv\n",
      "stock_data/daily_adjusted_MMM.csv\n",
      "stock_data/daily_adjusted_AAPL.csv\n",
      "stock_data/daily_adjusted_MSFT.csv\n",
      "stock_data/daily_adjusted_TXN.csv\n",
      "stock_data/daily_adjusted_CSCO.csv\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# The files are in \"stock_data\" folder, named as \"daily_adjusted_[TICKER].csv\"\n",
    "dr = DataReader(folder_path=\"stock_data\", symbol_list=list_tickers)\n",
    "dr.read_data()\n",
    "df_prices, _ = dr.get_period(start_date=investment_start, end_date=investment_end)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run the optimization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define the optimization model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below we implement the optimization model in Fusion API. We create it inside a function so we can call it later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# |x| <= t\n",
    "def absval(M, x, t):\n",
    "    M.constraint(t >= x)\n",
    "    M.constraint(t >= -x)\n",
    "\n",
    "# ||x||_1 <= t\n",
    "def norm1(M, x, t):\n",
    "    u = M.variable(x.getShape(), Domain.unbounded())\n",
    "    absval(M, x, u)\n",
    "    M.constraint(Expr.sum(u) == t)\n",
    "\n",
    "def EfficientFrontier(N, m, G, deltas):\n",
    "\n",
    "    with Model(\"Case study\") as M:\n",
    "        # Settings\n",
    "        #M.setLogHandler(sys.stdout)\n",
    "        \n",
    "        # Variables \n",
    "        # The variable x is the fraction of holdings relative to the initial capital. \n",
    "        # It is a free variable, allowing long and short positions.\n",
    "        x = M.variable(\"x\", N, Domain.unbounded())\n",
    "        \n",
    "        # The variable s models the portfolio variance term in the objective.\n",
    "        s = M.variable(\"s\", 1, Domain.unbounded())\n",
    "        \n",
    "        # Gross exposure constraint (allows 2 times the initial capital)\n",
    "        norm1(M, x, 2.0)\n",
    "        \n",
    "        # Dollar neutrality constraint\n",
    "        M.constraint('neutrality', Expr.sum(x) == 0.0)\n",
    "        \n",
    "        # Objective (quadratic utility version)\n",
    "        delta = M.parameter()\n",
    "        M.objective('obj', ObjectiveSense.Maximize, x.T @ m - delta * s)\n",
    "\n",
    "        # Conic constraint for the portfolio variance \n",
    "        M.constraint('risk', Expr.vstack(s, 0.5, G.T @ x), Domain.inRotatedQCone())\n",
    "        \n",
    "        # Create DataFrame to store the results. Last security name (the SPY) is removed.\n",
    "        columns = [\"delta\", \"obj\", \"return\", \"risk\", \"g. exp.\"] + df_prices.columns.tolist()\n",
    "        df_result = pd.DataFrame(columns=columns)\n",
    "        for d in deltas:\n",
    "            # Update parameter\n",
    "            delta.setValue(d)\n",
    "            \n",
    "            # Solve optimization\n",
    "            M.solve()\n",
    "            \n",
    "            # Check if the solution is an optimal point\n",
    "            solsta = M.getPrimalSolutionStatus()\n",
    "            if (solsta != SolutionStatus.Optimal):\n",
    "                # See https://docs.mosek.com/latest/pythonfusion/accessing-solution.html about handling solution statuses.\n",
    "                raise Exception(\"Unexpected solution status!\") \n",
    "            \n",
    "            # Save results\n",
    "            portfolio_return = m @ x.level()\n",
    "            portfolio_risk = np.sqrt(s.level()[0])\n",
    "            gross_exp = sum(np.absolute(x.level()))\n",
    "            row = pd.Series([d, M.primalObjValue(), portfolio_return, portfolio_risk, gross_exp] + list(x.level()), index=columns)\n",
    "            df_result = pd.concat([df_result, pd.DataFrame([row])], ignore_index=True)\n",
    "\n",
    "        return df_result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute optimization input variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we use the loaded daily price data to compute the corresponding yearly mean return and covariance matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Number of securities\n",
    "N = df_prices.shape[1]\n",
    "\n",
    "# Get optimization parameters\n",
    "m, S = compute_inputs(df_prices)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we compute the matrix $G$ such that $\\ECov=GG^\\mathsf{T}$, this is the input of the conic form of the optimization problem. Here we use Cholesky factorization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "G = np.linalg.cholesky(S)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Call the optimizer function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We run the optimization for a range of risk aversion parameter values: $\\delta = 10^{-1},\\dots,10^{1.5}$. We compute the efficient frontier this way both with and without using shrinkage estimation. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Compute efficient frontier with and without shrinkage\n",
    "deltas = np.logspace(start=-1, stop=1.5, num=20)[::-1]\n",
    "df_result = EfficientFrontier(N, m, G, deltas)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>delta</th>\n",
       "      <th>obj</th>\n",
       "      <th>return</th>\n",
       "      <th>risk</th>\n",
       "      <th>g. exp.</th>\n",
       "      <th>PM</th>\n",
       "      <th>LMT</th>\n",
       "      <th>MCD</th>\n",
       "      <th>MMM</th>\n",
       "      <th>AAPL</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>TXN</th>\n",
       "      <th>CSCO</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>31.622777</td>\n",
       "      <td>0.012181</td>\n",
       "      <td>0.024362</td>\n",
       "      <td>0.019627</td>\n",
       "      <td>0.174698</td>\n",
       "      <td>-0.029866</td>\n",
       "      <td>-1.813651e-03</td>\n",
       "      <td>-3.327063e-03</td>\n",
       "      <td>-3.965543e-02</td>\n",
       "      <td>0.017223</td>\n",
       "      <td>4.664747e-02</td>\n",
       "      <td>2.347876e-02</td>\n",
       "      <td>-1.268697e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23.357215</td>\n",
       "      <td>0.016492</td>\n",
       "      <td>0.032983</td>\n",
       "      <td>0.026572</td>\n",
       "      <td>0.236517</td>\n",
       "      <td>-0.040435</td>\n",
       "      <td>-2.455977e-03</td>\n",
       "      <td>-4.504609e-03</td>\n",
       "      <td>-5.368734e-02</td>\n",
       "      <td>0.023318</td>\n",
       "      <td>6.315380e-02</td>\n",
       "      <td>3.178662e-02</td>\n",
       "      <td>-1.717610e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17.252105</td>\n",
       "      <td>0.022328</td>\n",
       "      <td>0.044655</td>\n",
       "      <td>0.035975</td>\n",
       "      <td>0.320215</td>\n",
       "      <td>-0.054743</td>\n",
       "      <td>-3.324976e-03</td>\n",
       "      <td>-6.098627e-03</td>\n",
       "      <td>-7.268608e-02</td>\n",
       "      <td>0.031570</td>\n",
       "      <td>8.550237e-02</td>\n",
       "      <td>4.303523e-02</td>\n",
       "      <td>-2.325436e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.742750</td>\n",
       "      <td>0.030229</td>\n",
       "      <td>0.060457</td>\n",
       "      <td>0.048705</td>\n",
       "      <td>0.433530</td>\n",
       "      <td>-0.074115</td>\n",
       "      <td>-4.501704e-03</td>\n",
       "      <td>-8.256829e-03</td>\n",
       "      <td>-9.840758e-02</td>\n",
       "      <td>0.042741</td>\n",
       "      <td>1.157593e-01</td>\n",
       "      <td>5.826417e-02</td>\n",
       "      <td>-3.148341e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9.412050</td>\n",
       "      <td>0.040926</td>\n",
       "      <td>0.081850</td>\n",
       "      <td>0.065940</td>\n",
       "      <td>0.586933</td>\n",
       "      <td>-0.100340</td>\n",
       "      <td>-6.094617e-03</td>\n",
       "      <td>-1.117865e-02</td>\n",
       "      <td>-1.332288e-01</td>\n",
       "      <td>0.057866</td>\n",
       "      <td>1.567183e-01</td>\n",
       "      <td>7.888206e-02</td>\n",
       "      <td>-4.262430e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6.951928</td>\n",
       "      <td>0.055409</td>\n",
       "      <td>0.110821</td>\n",
       "      <td>0.089279</td>\n",
       "      <td>0.794681</td>\n",
       "      <td>-0.135856</td>\n",
       "      <td>-8.250688e-03</td>\n",
       "      <td>-1.513487e-02</td>\n",
       "      <td>-1.803870e-01</td>\n",
       "      <td>0.078346</td>\n",
       "      <td>2.121911e-01</td>\n",
       "      <td>1.068038e-01</td>\n",
       "      <td>-5.771226e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5.134833</td>\n",
       "      <td>0.075016</td>\n",
       "      <td>0.150038</td>\n",
       "      <td>0.120873</td>\n",
       "      <td>1.075906</td>\n",
       "      <td>-0.183931</td>\n",
       "      <td>-1.117064e-02</td>\n",
       "      <td>-2.049049e-02</td>\n",
       "      <td>-2.442259e-01</td>\n",
       "      <td>0.106069</td>\n",
       "      <td>2.872825e-01</td>\n",
       "      <td>1.446021e-01</td>\n",
       "      <td>-7.813552e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3.792690</td>\n",
       "      <td>0.101563</td>\n",
       "      <td>0.203125</td>\n",
       "      <td>0.163641</td>\n",
       "      <td>1.456578</td>\n",
       "      <td>-0.249013</td>\n",
       "      <td>-1.512627e-02</td>\n",
       "      <td>-2.774053e-02</td>\n",
       "      <td>-3.306328e-01</td>\n",
       "      <td>0.143605</td>\n",
       "      <td>3.889271e-01</td>\n",
       "      <td>1.957575e-01</td>\n",
       "      <td>-1.057763e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2.801357</td>\n",
       "      <td>0.137504</td>\n",
       "      <td>0.275011</td>\n",
       "      <td>0.221554</td>\n",
       "      <td>1.972071</td>\n",
       "      <td>-0.337138</td>\n",
       "      <td>-2.047841e-02</td>\n",
       "      <td>-3.756367e-02</td>\n",
       "      <td>-4.476385e-01</td>\n",
       "      <td>0.194424</td>\n",
       "      <td>5.265729e-01</td>\n",
       "      <td>2.650385e-01</td>\n",
       "      <td>-1.432172e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2.069138</td>\n",
       "      <td>0.177107</td>\n",
       "      <td>0.298429</td>\n",
       "      <td>0.242145</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-0.415083</td>\n",
       "      <td>-1.588155e-07</td>\n",
       "      <td>-3.462223e-08</td>\n",
       "      <td>-5.158595e-01</td>\n",
       "      <td>0.246408</td>\n",
       "      <td>5.503360e-01</td>\n",
       "      <td>2.032559e-01</td>\n",
       "      <td>-6.905687e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.528307</td>\n",
       "      <td>0.211422</td>\n",
       "      <td>0.315446</td>\n",
       "      <td>0.260893</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-0.476219</td>\n",
       "      <td>-2.838718e-08</td>\n",
       "      <td>-1.277994e-08</td>\n",
       "      <td>-5.237810e-01</td>\n",
       "      <td>0.309753</td>\n",
       "      <td>5.874499e-01</td>\n",
       "      <td>1.027971e-01</td>\n",
       "      <td>-6.044888e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1.128838</td>\n",
       "      <td>0.240334</td>\n",
       "      <td>0.326192</td>\n",
       "      <td>0.275787</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-0.523018</td>\n",
       "      <td>-1.064179e-08</td>\n",
       "      <td>-6.128413e-09</td>\n",
       "      <td>-4.769823e-01</td>\n",
       "      <td>0.381652</td>\n",
       "      <td>6.183482e-01</td>\n",
       "      <td>9.539798e-08</td>\n",
       "      <td>-1.080083e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.833782</td>\n",
       "      <td>0.263130</td>\n",
       "      <td>0.328904</td>\n",
       "      <td>0.280866</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-0.559561</td>\n",
       "      <td>-1.468358e-08</td>\n",
       "      <td>-7.858693e-09</td>\n",
       "      <td>-4.404388e-01</td>\n",
       "      <td>0.438818</td>\n",
       "      <td>5.611816e-01</td>\n",
       "      <td>4.608019e-08</td>\n",
       "      <td>-1.012394e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.615848</td>\n",
       "      <td>0.280802</td>\n",
       "      <td>0.332577</td>\n",
       "      <td>0.289949</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-0.609080</td>\n",
       "      <td>-1.087698e-08</td>\n",
       "      <td>-6.424718e-09</td>\n",
       "      <td>-3.909199e-01</td>\n",
       "      <td>0.516232</td>\n",
       "      <td>4.837682e-01</td>\n",
       "      <td>1.275609e-08</td>\n",
       "      <td>-7.333844e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.454878</td>\n",
       "      <td>0.294985</td>\n",
       "      <td>0.337553</td>\n",
       "      <td>0.305909</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-0.676100</td>\n",
       "      <td>-1.154550e-09</td>\n",
       "      <td>-8.503845e-10</td>\n",
       "      <td>-3.239002e-01</td>\n",
       "      <td>0.621124</td>\n",
       "      <td>3.788759e-01</td>\n",
       "      <td>1.145439e-09</td>\n",
       "      <td>-6.673766e-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.335982</td>\n",
       "      <td>0.306991</td>\n",
       "      <td>0.344282</td>\n",
       "      <td>0.333155</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-0.766835</td>\n",
       "      <td>-2.036140e-10</td>\n",
       "      <td>-1.237167e-10</td>\n",
       "      <td>-2.331652e-01</td>\n",
       "      <td>0.762936</td>\n",
       "      <td>2.370640e-01</td>\n",
       "      <td>1.872415e-10</td>\n",
       "      <td>-1.152393e-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.248163</td>\n",
       "      <td>0.317929</td>\n",
       "      <td>0.353408</td>\n",
       "      <td>0.378110</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-0.889826</td>\n",
       "      <td>-4.466695e-08</td>\n",
       "      <td>-2.863282e-08</td>\n",
       "      <td>-1.101740e-01</td>\n",
       "      <td>0.955296</td>\n",
       "      <td>4.470383e-02</td>\n",
       "      <td>4.271174e-08</td>\n",
       "      <td>-2.692994e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.183298</td>\n",
       "      <td>0.327910</td>\n",
       "      <td>0.356984</td>\n",
       "      <td>0.398270</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-0.999999</td>\n",
       "      <td>-5.917077e-09</td>\n",
       "      <td>-3.883621e-09</td>\n",
       "      <td>-9.958170e-07</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.649493e-08</td>\n",
       "      <td>4.721761e-09</td>\n",
       "      <td>-3.563641e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.135388</td>\n",
       "      <td>0.335509</td>\n",
       "      <td>0.356984</td>\n",
       "      <td>0.398270</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-6.606806e-09</td>\n",
       "      <td>-4.545752e-09</td>\n",
       "      <td>-4.995802e-08</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.714103e-08</td>\n",
       "      <td>4.472662e-09</td>\n",
       "      <td>-4.067312e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.341122</td>\n",
       "      <td>0.356984</td>\n",
       "      <td>0.398270</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.669964e-09</td>\n",
       "      <td>-1.164704e-09</td>\n",
       "      <td>-9.496848e-09</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9.899558e-09</td>\n",
       "      <td>1.368620e-09</td>\n",
       "      <td>-1.014214e-09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        delta       obj    return      risk   g. exp.        PM           LMT  \\\n",
       "0   31.622777  0.012181  0.024362  0.019627  0.174698 -0.029866 -1.813651e-03   \n",
       "1   23.357215  0.016492  0.032983  0.026572  0.236517 -0.040435 -2.455977e-03   \n",
       "2   17.252105  0.022328  0.044655  0.035975  0.320215 -0.054743 -3.324976e-03   \n",
       "3   12.742750  0.030229  0.060457  0.048705  0.433530 -0.074115 -4.501704e-03   \n",
       "4    9.412050  0.040926  0.081850  0.065940  0.586933 -0.100340 -6.094617e-03   \n",
       "5    6.951928  0.055409  0.110821  0.089279  0.794681 -0.135856 -8.250688e-03   \n",
       "6    5.134833  0.075016  0.150038  0.120873  1.075906 -0.183931 -1.117064e-02   \n",
       "7    3.792690  0.101563  0.203125  0.163641  1.456578 -0.249013 -1.512627e-02   \n",
       "8    2.801357  0.137504  0.275011  0.221554  1.972071 -0.337138 -2.047841e-02   \n",
       "9    2.069138  0.177107  0.298429  0.242145  2.000000 -0.415083 -1.588155e-07   \n",
       "10   1.528307  0.211422  0.315446  0.260893  2.000000 -0.476219 -2.838718e-08   \n",
       "11   1.128838  0.240334  0.326192  0.275787  2.000000 -0.523018 -1.064179e-08   \n",
       "12   0.833782  0.263130  0.328904  0.280866  2.000000 -0.559561 -1.468358e-08   \n",
       "13   0.615848  0.280802  0.332577  0.289949  2.000000 -0.609080 -1.087698e-08   \n",
       "14   0.454878  0.294985  0.337553  0.305909  2.000000 -0.676100 -1.154550e-09   \n",
       "15   0.335982  0.306991  0.344282  0.333155  2.000000 -0.766835 -2.036140e-10   \n",
       "16   0.248163  0.317929  0.353408  0.378110  2.000000 -0.889826 -4.466695e-08   \n",
       "17   0.183298  0.327910  0.356984  0.398270  2.000000 -0.999999 -5.917077e-09   \n",
       "18   0.135388  0.335509  0.356984  0.398270  2.000000 -1.000000 -6.606806e-09   \n",
       "19   0.100000  0.341122  0.356984  0.398270  2.000000 -1.000000 -1.669964e-09   \n",
       "\n",
       "             MCD           MMM      AAPL          MSFT           TXN  \\\n",
       "0  -3.327063e-03 -3.965543e-02  0.017223  4.664747e-02  2.347876e-02   \n",
       "1  -4.504609e-03 -5.368734e-02  0.023318  6.315380e-02  3.178662e-02   \n",
       "2  -6.098627e-03 -7.268608e-02  0.031570  8.550237e-02  4.303523e-02   \n",
       "3  -8.256829e-03 -9.840758e-02  0.042741  1.157593e-01  5.826417e-02   \n",
       "4  -1.117865e-02 -1.332288e-01  0.057866  1.567183e-01  7.888206e-02   \n",
       "5  -1.513487e-02 -1.803870e-01  0.078346  2.121911e-01  1.068038e-01   \n",
       "6  -2.049049e-02 -2.442259e-01  0.106069  2.872825e-01  1.446021e-01   \n",
       "7  -2.774053e-02 -3.306328e-01  0.143605  3.889271e-01  1.957575e-01   \n",
       "8  -3.756367e-02 -4.476385e-01  0.194424  5.265729e-01  2.650385e-01   \n",
       "9  -3.462223e-08 -5.158595e-01  0.246408  5.503360e-01  2.032559e-01   \n",
       "10 -1.277994e-08 -5.237810e-01  0.309753  5.874499e-01  1.027971e-01   \n",
       "11 -6.128413e-09 -4.769823e-01  0.381652  6.183482e-01  9.539798e-08   \n",
       "12 -7.858693e-09 -4.404388e-01  0.438818  5.611816e-01  4.608019e-08   \n",
       "13 -6.424718e-09 -3.909199e-01  0.516232  4.837682e-01  1.275609e-08   \n",
       "14 -8.503845e-10 -3.239002e-01  0.621124  3.788759e-01  1.145439e-09   \n",
       "15 -1.237167e-10 -2.331652e-01  0.762936  2.370640e-01  1.872415e-10   \n",
       "16 -2.863282e-08 -1.101740e-01  0.955296  4.470383e-02  4.271174e-08   \n",
       "17 -3.883621e-09 -9.958170e-07  1.000000  6.649493e-08  4.721761e-09   \n",
       "18 -4.545752e-09 -4.995802e-08  1.000000  2.714103e-08  4.472662e-09   \n",
       "19 -1.164704e-09 -9.496848e-09  1.000000  9.899558e-09  1.368620e-09   \n",
       "\n",
       "            CSCO  \n",
       "0  -1.268697e-02  \n",
       "1  -1.717610e-02  \n",
       "2  -2.325436e-02  \n",
       "3  -3.148341e-02  \n",
       "4  -4.262430e-02  \n",
       "5  -5.771226e-02  \n",
       "6  -7.813552e-02  \n",
       "7  -1.057763e-01  \n",
       "8  -1.432172e-01  \n",
       "9  -6.905687e-02  \n",
       "10 -6.044888e-08  \n",
       "11 -1.080083e-08  \n",
       "12 -1.012394e-08  \n",
       "13 -7.333844e-09  \n",
       "14 -6.673766e-10  \n",
       "15 -1.152393e-10  \n",
       "16 -2.692994e-08  \n",
       "17 -3.563641e-09  \n",
       "18 -4.067312e-09  \n",
       "19 -1.014214e-09  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize the results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the efficient frontier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2400x1600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df_result.plot(x=\"risk\", y=\"return\", style=\"-o\", \n",
    "                    xlabel=\"portfolio risk (std. dev.)\", ylabel=\"portfolio return\", grid=True)   \n",
    "ax.legend([\"return\"]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the portfolio composition."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Round small values to 0 to make plotting work\n",
    "mask = np.absolute(df_result) < 1e-7\n",
    "mask.iloc[:, :-8] = False\n",
    "df_result[mask] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 2400x1600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_cmap = LinearSegmentedColormap.from_list(\"non-extreme gray\", [\"#111111\", \"#eeeeee\"], N=256, gamma=1.0)\n",
    "ax = df_result.set_index('risk').iloc[:, 4:].plot.area(colormap=my_cmap, xlabel='portfolio risk (std. dev.)', ylabel=\"x\") \n",
    "ax.grid(which='both', axis='x', linestyle=':', color='k', linewidth=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}