Linear Regression Test.ipynb

01_linear_regression_intro.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/firmai/f6c5b98e348c38c505ca6fa621c328f5/01_linear_regression_intro.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "locKQ3zwjsZl"
      },
      "source": [
        "## Linear Regression - Introduction\n",
        "\n",
        "Linear regression relates a continuous response (dependent) variable to one or more predictors (features, independent variables), using the assumption that the relationship is linear in nature:\n",
        "- This essentially means that the effects of each variable on the response are additive (but we can include new variables that represent the interaction of two variables).\n",
        "\n",
        "In other words, the model assumes that the response variable can be explained or predicted by a linear combination of the features, except for random deviations from this linear relationship.\n",
        "\n",
        "**Note that I would provide the best student solution for every question as the final solution.**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7ywtWYaWjsZp"
      },
      "source": [
        "## Imports & Settings"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Have a look out for the <font color='orange'>orange text </font> it indicates questions that has to be answered or code that has to be writte. The number of points for each question will appear next to it, like <font color='orange'>Question 1 (4 points) </font>. In total we have <font color='orange'>**16 points** </font>."
      ],
      "metadata": {
        "id": "9T9laXBxrI6U"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:55.794199Z",
          "start_time": "2021-04-15T19:54:55.790730Z"
        },
        "id": "oTjx_IiYjsZr"
      },
      "outputs": [],
      "source": [
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:56.695927Z",
          "start_time": "2021-04-15T19:54:55.801810Z"
        },
        "id": "gfqosp_ojsZt"
      },
      "outputs": [],
      "source": [
        "%matplotlib inline\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "import statsmodels.api as sm\n",
        "from sklearn.linear_model import SGDRegressor\n",
        "from sklearn.preprocessing import StandardScaler"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:56.700217Z",
          "start_time": "2021-04-15T19:54:56.697453Z"
        },
        "id": "gyWtmvL3jsZu"
      },
      "outputs": [],
      "source": [
        "sns.set_style('whitegrid')\n",
        "pd.options.display.float_format = '{:,.2f}'.format"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FkLyOuu1jsZu"
      },
      "source": [
        "### Simple Regression"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7B3IKLxFjsZw"
      },
      "source": [
        "#### Generate random data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:56.926876Z",
          "start_time": "2021-04-15T19:54:56.702002Z"
        },
        "id": "GkBhq_qKjsZx",
        "outputId": "9e4cb390-9003-40dd-c9b4-3583897906bd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 626
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1400x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "x = np.linspace(-5, 50, 100)\n",
        "y = 50 + 2 * x + np.random.normal(0, 20, size=len(x))\n",
        "data = pd.DataFrame({'X': x, 'Y': y})\n",
        "ax = data.plot.scatter(x='X', y='Y', figsize=(14, 6))\n",
        "sns.despine()\n",
        "plt.tight_layout()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "62mtRWVUvupd"
      },
      "source": [
        "Our linear model with a single independent variable on the left-hand side assumes the following form:\n",
        "\n",
        "$$y = \\beta_0 + \\beta_1 X_1 + \\epsilon$$\n",
        "\n",
        "$\\epsilon$ accounts for the deviations or errors that we will encounter when our data do not actually fit a straight line. When $\\epsilon$ materializes, that is when we run the model of this type on actual data, the errors are called **residuals**."
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<font color='orange'>Question 1: Get stock price data (4 points) </font>\n",
        "\n",
        "Have a look at the format of the random dataframe above called *data* above, you can see what it looks like by running `data.head()`  \n",
        "\n",
        "*   We want to create a new Pandas dataframe and have the S&P index **returns** in the X column, and Tesla **returns** in the y column; you can give the columns appropriate names.\n",
        "*   The data should start on the 7th of January 2020 and stop on the 21st of January 2022.\n",
        "*   The returns should be calculated on the adjusted closing price of the security.\n",
        "*   The date should be set as the index so that it doesn't appear as a feature, you can use any daily date format.\n",
        "\n",
        "\n",
        "### Some advice\n",
        "You could use multiple open source python packages like googlefinance or yfinance. There are many places where you can learn how to use the package, I can recomend Stefan Jansen's [resource](https://github.com/stefan-jansen/machine-learning-for-trading/blob/main/02_market_and_fundamental_data/03_data_providers/02_yfinance_demo.ipynb). Notice that this data might not be as accurate as those from paid providers.\n",
        "\n",
        "*Note the technique I showed below might not be the easiest solution, and you need to do some additional work to get the returns out of the package.*\n",
        "\n",
        "\n",
        "```python\n",
        "import yfinance as yf\n",
        "symbol = 'FB'\n",
        "ticker = yf.Ticker(symbol)\n",
        "```\n",
        "\n",
        "You have to learn how to download Python packages, a popular method is to use `!pip install yfinance` for example\n",
        "\n",
        "Perhaps you can even do it without a package if you know how to query and API, you can query the yahoo data directly:\n",
        "\n",
        "\n",
        "\n",
        "```python\n",
        "# yahoo url template (5 years of daily data: 2015-09-21 to 2020-09-18)\n",
        "yahoo_url = 'https://query1.finance.yahoo.com/v7/finance/download/{}?period1=1442707200&period2=1600560000&interval=1d&events=history'\n",
        "# get data for 3 tickers and concatenate together\n",
        "tickers = ['AAPL', 'MSFT', '^GSPC']\n",
        "\n",
        "df = pd.DataFrame()\n",
        "for ticker in tickers:\n",
        "    url = yahoo_url.format(ticker)\n",
        "    df_tmp = pd.read_csv(url)\n",
        "    df_tmp['Ticker'] = ticker\n",
        "    df = pd.concat([df, df_tmp])\n",
        "df\n",
        "```\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "uvLc5OQ2sah-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#### Your solution for 4 points goes into this code block (there are thousands of ways to get the data you can use any method to get to the final solution):\n",
        "\n"
      ],
      "metadata": {
        "id": "y6adk7z6yJoo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ApsAlJiKjsZ0"
      },
      "source": [
        "#### Estimate a simple regression with statsmodels"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "avmSgvPZjsZ1"
      },
      "source": [
        "The upper part of the summary displays the dataset characteristics, namely the estimation method, the number of observations and parameters, and indicates that standard error estimates do not account for heteroskedasticity.\n",
        "\n",
        "The middle panel shows the coefficient values that closely reflect the artificial data generating process. We can confirm that the estimates displayed in the middle of the summary result can be obtained using the OLS formula derived previously:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:56.970047Z",
          "start_time": "2021-04-15T19:54:56.928301Z"
        },
        "id": "ME-AUaZ4jsZ2",
        "outputId": "743b46d7-ae75-4ec0-bc40-0f6c13e10dd7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                            OLS Regression Results                            \n",
            "==============================================================================\n",
            "Dep. Variable:                      Y   R-squared:                       0.686\n",
            "Model:                            OLS   Adj. R-squared:                  0.683\n",
            "Method:                 Least Squares   F-statistic:                     214.0\n",
            "Date:                Tue, 06 Aug 2024   Prob (F-statistic):           2.20e-26\n",
            "Time:                        18:18:32   Log-Likelihood:                -438.99\n",
            "No. Observations:                 100   AIC:                             882.0\n",
            "Df Residuals:                      98   BIC:                             887.2\n",
            "Df Model:                           1                                         \n",
            "Covariance Type:            nonrobust                                         \n",
            "==============================================================================\n",
            "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
            "------------------------------------------------------------------------------\n",
            "const         53.2807      3.396     15.691      0.000      46.542      60.019\n",
            "X              1.7979      0.123     14.629      0.000       1.554       2.042\n",
            "==============================================================================\n",
            "Omnibus:                        0.390   Durbin-Watson:                   1.892\n",
            "Prob(Omnibus):                  0.823   Jarque-Bera (JB):                0.404\n",
            "Skew:                          -0.144   Prob(JB):                        0.817\n",
            "Kurtosis:                       2.881   Cond. No.                         47.6\n",
            "==============================================================================\n",
            "\n",
            "Notes:\n",
            "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
          ]
        }
      ],
      "source": [
        "## Here you can choose to assess the random dataframe, or the new return dataframe that you just created\n",
        "X = sm.add_constant(data['X'])\n",
        "model = sm.OLS(data['Y'], X).fit()\n",
        "print(model.summary())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2018-09-03T18:56:37.274147Z",
          "start_time": "2018-09-03T18:56:37.270065Z"
        },
        "id": "rsZ2EyDUjsZ3"
      },
      "source": [
        "#### Verify calculation"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:56.977705Z",
          "start_time": "2021-04-15T19:54:56.971237Z"
        },
        "id": "plX0AkUWjsZ3",
        "outputId": "c507321c-b329-4e46-8a1f-143c6448e602",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "const   53.28\n",
              "X        1.80\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "beta = np.linalg.inv(X.T.dot(X)).dot(X.T.dot(y))\n",
        "pd.Series(beta, index=X.columns)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J-6daeN8jsZ4"
      },
      "source": [
        "#### Display model & residuals"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:57.296302Z",
          "start_time": "2021-04-15T19:54:56.979198Z"
        },
        "id": "pu0x9cpPjsZ4",
        "outputId": "f87f5fda-f1f1-4097-9b93-0d8f2a313fb4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 626
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1400x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "data['y-hat'] = model.predict()\n",
        "data['residuals'] = model.resid\n",
        "ax = data.plot.scatter(x='X', y='Y', c='darkgrey', figsize=(14,6))\n",
        "data.plot.line(x='X', y='y-hat', ax=ax);\n",
        "for _, row in data.iterrows():\n",
        "    plt.plot((row.X, row.X), (row.Y, row['y-hat']), 'k-')\n",
        "sns.despine()\n",
        "plt.tight_layout();"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<font color='orange'>Question 2: There is a common metric in statistics called mean squared error (MSE), define it and calculate it for the predictions above (4 points) </font>\n",
        "\n",
        "\n",
        "\n",
        "*   You can either use the prediction using returns data or the predictions of the random data, i.e., you decide what predictions to use.\n",
        "*   I only care about your definition and the methodology you use.\n",
        "\n"
      ],
      "metadata": {
        "id": "mDt2I63szA3y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Write (code) your answers here to obtain all 4 points\n"
      ],
      "metadata": {
        "id": "CGs0kRTZz53H"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1hKSq55mjsZ5"
      },
      "source": [
        "### Multiple Regression\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n6Ghn-rsjsZ5"
      },
      "source": [
        "For two independent variables, the model simply changes as follows:\n",
        "\n",
        "$$y = \\beta_0 + \\beta_1 X_1 + \\beta_2 X_2 + \\epsilon$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sw7QvQnFjsZ6"
      },
      "source": [
        "#### Generate new random data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:57.427534Z",
          "start_time": "2021-04-15T19:54:57.297651Z"
        },
        "id": "thYSk6gtjsZ6",
        "outputId": "cc1fa016-06c0-4343-9a81-ffe3771e1fa9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 695
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Create data\n",
        "size = 25\n",
        "X_1, X_2 = np.meshgrid(np.linspace(-50, 50, size), np.linspace(-50, 50, size), indexing='ij')\n",
        "data = pd.DataFrame({'X_1': X_1.ravel(), 'X_2': X_2.ravel()})\n",
        "data['Y'] = 50 + data.X_1 + 3 * data.X_2 + np.random.normal(0, 50, size=size**2)\n",
        "\n",
        "# Create 3D plot\n",
        "fig = plt.figure(figsize=(12, 8))\n",
        "ax = fig.add_subplot(111, projection='3d')\n",
        "\n",
        "# Create scatter plot\n",
        "scatter = ax.scatter(data.X_1, data.X_2, data.Y, c=data.Y, cmap='viridis')\n",
        "\n",
        "# Set labels\n",
        "ax.set_xlabel('X_1')\n",
        "ax.set_ylabel('X_2')\n",
        "ax.set_zlabel('Y')\n",
        "\n",
        "# Add a color bar\n",
        "plt.colorbar(scatter)\n",
        "\n",
        "# Set title\n",
        "plt.title('3D Scatter Plot')\n",
        "\n",
        "# Show the plot\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:57.432065Z",
          "start_time": "2021-04-15T19:54:57.428738Z"
        },
        "id": "0Bj5O3yrjsZ6"
      },
      "outputs": [],
      "source": [
        "X = data[['X_1', 'X_2']]\n",
        "y = data['Y']"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "K4ihuYaMjsZ7"
      },
      "source": [
        "#### Estimate multiple regression model with statsmodels"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qAvKzgBUjsZ8"
      },
      "source": [
        "The upper right part of the panel displays the goodness-of-fit measures just discussed, alongside the F-test that rejects the hypothesis that all coefficients are zero and irrelevant. Similarly, the t-statistics indicate that intercept and both slope coefficients are, unsurprisingly, highly significant.\n",
        "\n",
        "The bottom part of the summary contains the residual diagnostics. The left panel displays skew and kurtosis that are used to test the normality hypothesis. Both the Omnibus and the Jarque—Bera test fails to reject the null hypothesis that the residuals are normally distributed. The Durbin—Watson statistic tests for serial correlation in the residuals and has a value near 2 which, given 2 parameters and 625 observations, fails to reject the hypothesis of no serial correlation.\n",
        "\n",
        "Lastly, the condition number provides evidence about multicollinearity: it is the ratio of the square roots of the largest and the smallest eigenvalue of the design matrix that contains the input data. A value above 30 suggests that the regression may have significant multicollinearity."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:57.459228Z",
          "start_time": "2021-04-15T19:54:57.434370Z"
        },
        "id": "MgwmmKnmjsZ8",
        "outputId": "7a7521df-cd7a-4a8e-aee5-c0cddb6f78f4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                            OLS Regression Results                            \n",
            "==============================================================================\n",
            "Dep. Variable:                      Y   R-squared:                       0.770\n",
            "Model:                            OLS   Adj. R-squared:                  0.769\n",
            "Method:                 Least Squares   F-statistic:                     1039.\n",
            "Date:                Tue, 06 Aug 2024   Prob (F-statistic):          5.17e-199\n",
            "Time:                        18:20:10   Log-Likelihood:                -3335.4\n",
            "No. Observations:                 625   AIC:                             6677.\n",
            "Df Residuals:                     622   BIC:                             6690.\n",
            "Df Model:                           2                                         \n",
            "Covariance Type:            nonrobust                                         \n",
            "==============================================================================\n",
            "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
            "------------------------------------------------------------------------------\n",
            "const         49.0996      2.016     24.353      0.000      45.140      53.059\n",
            "X_1            1.0680      0.067     15.916      0.000       0.936       1.200\n",
            "X_2            2.8664      0.067     42.717      0.000       2.735       2.998\n",
            "==============================================================================\n",
            "Omnibus:                        0.187   Durbin-Watson:                   1.973\n",
            "Prob(Omnibus):                  0.911   Jarque-Bera (JB):                0.135\n",
            "Skew:                           0.035   Prob(JB):                        0.935\n",
            "Kurtosis:                       3.020   Cond. No.                         30.0\n",
            "==============================================================================\n",
            "\n",
            "Notes:\n",
            "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
          ]
        }
      ],
      "source": [
        "X_ols = sm.add_constant(X)\n",
        "model = sm.OLS(y, X_ols).fit()\n",
        "print(model.summary())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bBKQVeGwjsZ9"
      },
      "source": [
        "#### Verify computation"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:57.466883Z",
          "start_time": "2021-04-15T19:54:57.460886Z"
        },
        "id": "NTxJnnUIjsZ9",
        "outputId": "4cf84a1a-2297-44ed-a414-73eb3ebbabcb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "const   48.57\n",
              "X_1      1.11\n",
              "X_2      2.96\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "beta = np.linalg.inv(X_ols.T.dot(X_ols)).dot(X_ols.T.dot(y))\n",
        "pd.Series(beta, index=X_ols.columns)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CyfrjfC0jsZ9"
      },
      "source": [
        "#### Save output as image"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:57.634435Z",
          "start_time": "2021-04-15T19:54:57.468510Z"
        },
        "id": "-uJGbIjIjsZ-",
        "outputId": "1a8bf610-cae0-4792-a475-c213d7f737df",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 648
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.rc('figure', figsize=(12, 7))\n",
        "plt.text(0.01, 0.05, str(model.summary()), {'fontsize': 14}, fontproperties = 'monospace')\n",
        "plt.axis('off')\n",
        "plt.tight_layout()\n",
        "plt.subplots_adjust(left=0.2, right=0.8, top=0.8, bottom=0.1)\n",
        "# plt.savefig('multiple_regression_summary.png', bbox_inches='tight', dpi=300);"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nAoVIWcbjsZ-"
      },
      "source": [
        "#### Display model & residuals"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vckwbs24jsZ-"
      },
      "source": [
        "The following diagram illustrates the hyperplane fitted by the model to the randomly generated data points"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:58.914449Z",
          "start_time": "2021-04-15T19:54:57.635292Z"
        },
        "id": "-4lruZFhjsZ_",
        "outputId": "c81fd008-90d4-4fcc-fbb2-58d712ab5daa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 369
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "three_dee = plt.figure(figsize=(15, 5)).gca(projection='3d')\n",
        "three_dee.scatter(data.X_1, data.X_2, data.Y, c='g')\n",
        "data['y-hat'] = model.predict()\n",
        "to_plot = data.set_index(['X_1', 'X_2']).unstack().loc[:, 'y-hat']\n",
        "three_dee.plot_surface(X_1, X_2, to_plot.values, color='black', alpha=0.2, linewidth=1, antialiased=True)\n",
        "for _, row in data.iterrows():\n",
        "    plt.plot((row.X_1, row.X_1), (row.X_2, row.X_2), (row.Y, row['y-hat']), 'k-');\n",
        "three_dee.set_xlabel('$X_1$');three_dee.set_ylabel('$X_2$');three_dee.set_zlabel('$Y, \\hat{Y}$')\n",
        "sns.despine()\n",
        "plt.tight_layout();"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4kZTVg04jsZ_"
      },
      "source": [
        "Additional [diagnostic tests](https://www.statsmodels.org/dev/diagnostic.html)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xiwM3nexjsZ_"
      },
      "source": [
        "## Stochastic Gradient Descent Regression"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UjWj8WJFjsaA"
      },
      "source": [
        "The sklearn library includes an SGDRegressor model in its linear_models module. To learn the parameters for the same model using this method, we need to first standardize the data because the gradient is sensitive to the scale."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g8mzdQuPjsaB"
      },
      "source": [
        "### Prepare data\n",
        "\n",
        "The gradient is sensitive to scale and so is SGDRegressor. Use the `StandardScaler` or `scale` to adjust the features."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a3ZCsLCzjsaB"
      },
      "source": [
        "We use StandardScaler() for this purpose that computes the mean and the standard deviation for each input variable during the fit step, and then subtracts the mean and divides by the standard deviation during the transform step that we can conveniently conduct in a single fit_transform() command:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:58.920869Z",
          "start_time": "2021-04-15T19:54:58.915601Z"
        },
        "id": "_dIHt453jsaB"
      },
      "outputs": [],
      "source": [
        "scaler = StandardScaler()\n",
        "X_ = scaler.fit_transform(X)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TEvd0Lq-jsaC"
      },
      "source": [
        "### Configure SGDRegressor"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B7buJ7DtjsaC"
      },
      "source": [
        "Then we instantiate the SGDRegressor using the default values except for a random_state setting to facilitate replication:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:58.939674Z",
          "start_time": "2021-04-15T19:54:58.921999Z"
        },
        "id": "4tyBoEISjsaD"
      },
      "outputs": [],
      "source": [
        "sgd = SGDRegressor(loss='squared_error',\n",
        "                   fit_intercept=True,\n",
        "                   shuffle=True,\n",
        "                   random_state=42,\n",
        "                   learning_rate='invscaling',\n",
        "                   eta0=0.01,\n",
        "                   power_t=0.25)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "K1fe0KBhjsaE"
      },
      "source": [
        "### Fit Model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pcvWbiWdjsaE"
      },
      "source": [
        "Now we can fit the sgd model, create the in-sample predictions for both the OLS and the sgd models, and compute the root mean squared error for each:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:58.951053Z",
          "start_time": "2021-04-15T19:54:58.940995Z"
        },
        "id": "b3MDnK9qjsaE",
        "outputId": "233c4c16-0373-4589-c09b-e57e0fe40118",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 94
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SGDRegressor(random_state=42)"
            ],
            "text/html": [
              "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>SGDRegressor(random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SGDRegressor</label><div class=\"sk-toggleable__content\"><pre>SGDRegressor(random_state=42)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ],
      "source": [
        "# sgd.n_iter = np.ceil(10**6 / len(y))\n",
        "sgd.fit(X=X_, y=y)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0_m3f5sKjsaF"
      },
      "source": [
        "As expected, both models yield the same result. We will now take on a more ambitious project using linear regression to estimate a multi-factor asset pricing model."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:58.960700Z",
          "start_time": "2021-04-15T19:54:58.952206Z"
        },
        "id": "tnYMG9wujsaF",
        "outputId": "4d4d054a-30f3-4d5b-c552-712b0f0090bc",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "X_1     969.56\n",
              "X_2   2,594.83\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ],
      "source": [
        "coeffs = (sgd.coef_ * scaler.scale_) + scaler.mean_\n",
        "pd.Series(coeffs, index=X.columns)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:58.973085Z",
          "start_time": "2021-04-15T19:54:58.962760Z"
        },
        "id": "7XeBcE0njsaF"
      },
      "outputs": [],
      "source": [
        "resids = pd.DataFrame({'sgd': y - sgd.predict(X_),\n",
        "                      'ols': y - model.predict(sm.add_constant(X))})"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:58.983549Z",
          "start_time": "2021-04-15T19:54:58.974199Z"
        },
        "id": "oqRrfQz7jsaG",
        "outputId": "a1acef4d-a527-4ee2-8f61-0bd5961e1cac",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "sgd   50.28\n",
              "ols   50.28\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ],
      "source": [
        "resids.pow(2).sum().div(len(y)).pow(.5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:54:59.147588Z",
          "start_time": "2021-04-15T19:54:58.984711Z"
        },
        "id": "k_l9HUxijsaG",
        "outputId": "b11bd37c-a670-4d8b-e721-98b10ac1628d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 727
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x700 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "resids.plot.scatter(x='sgd', y='ols')\n",
        "sns.despine()\n",
        "plt.tight_layout();"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## How to build a linear factor model"
      ],
      "metadata": {
        "id": "33csJl65lVru"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Algorithmic trading strategies use linear factor models to quantify the relationship between the return of an asset and the sources of risk that represent the main drivers of these returns. Each factor risk carries a premium, and the total asset return can be expected to correspond to a weighted average of these risk premia."
      ],
      "metadata": {
        "id": "282UMofFlcj7"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fh8oWGLclSfq"
      },
      "source": [
        "There are several practical applications of factor models across the portfolio management process from construction and asset selection to risk management and performance evaluation. The importance of factor models continues to grow as common risk factors are now *tradeable*:\n",
        "\n",
        "- A summary of the returns of many assets by a much smaller number of factors reduces the amount of data required to estimate the covariance matrix when optimizing a portfolio\n",
        "- An estimate of the exposure of an asset or a portfolio to these factors allows for the management of the resultant risk, for instance by entering suitable hedges when risk factors are themselves traded\n",
        "- A factor model also permits the assessment of the incremental signal content of new alpha factors\n",
        "- A factor model can also help assess whether a manager's performance relative to a benchmark is indeed due to skill in selecting assets and timing the market, or if instead, the performance can be explained by portfolio tilts towards known return drivers that can today be replicated as low-cost, passively managed funds without incurring active management fees"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mmbu5zPLlSfu"
      },
      "source": [
        "## Imports & Settings"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:55:07.984117Z",
          "start_time": "2021-04-15T19:55:07.982285Z"
        },
        "id": "7f70A9iSlSfv"
      },
      "outputs": [],
      "source": [
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture\n",
        "!pip install linearmodels"
      ],
      "metadata": {
        "id": "BRlDPop2UHP_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Linear (regression) models for Python. Extends statsmodels with Panel regression, instrumental variable estimators, system estimators and models for estimating asset prices:"
      ],
      "metadata": {
        "id": "5HqWzK35UL52"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:55:09.073976Z",
          "start_time": "2021-04-15T19:55:08.102748Z"
        },
        "id": "7U4cU1urlSfx"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "\n",
        "from statsmodels.api import OLS, add_constant\n",
        "import pandas_datareader.data as web\n",
        "\n",
        "from linearmodels.asset_pricing import LinearFactorModel\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:55:09.077317Z",
          "start_time": "2021-04-15T19:55:09.075045Z"
        },
        "id": "7T2Z-e4dlSfz"
      },
      "outputs": [],
      "source": [
        "sns.set_style('whitegrid')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BF2QT6GxlSf0"
      },
      "source": [
        "## Get Data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Omwizr9slSf1"
      },
      "source": [
        "Fama and French make updated risk factor and research portfolio data available through their [website](http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html), and you can use the `pandas_datareader` package to obtain the data."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zLZy9TbWlSf3"
      },
      "source": [
        "### Risk Factors"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e4wFjbXPlSf3"
      },
      "source": [
        "In particular, we will be using the five Fama—French factors that result from sorting stocks first into three size groups and then into two for each of the remaining three firm-specific factors.\n",
        "\n",
        "Hence, the factors involve three sets of value-weighted portfolios formed as 3 x 2 sorts on size and book-to-market, size and operating profitability, and size and investment. The risk factor values computed as the average returns of the portfolios (PF) as outlined in the following table:"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0JPdPPqplSf4"
      },
      "source": [
        "| Label | Name                          | Description                                                                                                                                                                               |\n",
        "|-------|-------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n",
        "| SMB   | Small Minus Big               | Average return on the nine small stock portfolios minus the average return on the nine big stock portfolios                                                                               |\n",
        "| HML   | High Minus Low                | Average return on the two value portfolios minus the average return on the two growth portfolios                                                                                          |\n",
        "| RMW   | Robust minus Weak             | Average return on the two robust operating profitability portfolios minus the average return on the two weak operating profitability portfolios                                           |\n",
        "| CMA   | Conservative Minus Aggressive | Average return on the two conservative investment portfolios minus the average return on the two aggressive investment portfolios                                                         |\n",
        "| Rm-Rf | Excess return on the market   | Value-weight return of all firms incorporated in the US and listed on the NYSE, AMEX, or NASDAQ at the beginning of month t with 'good' data for t minus the one-month Treasury bill rate |"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qB-fIwiYlSf5"
      },
      "source": [
        "The Fama-French 5 factors are based on the 6 value-weight portfolios formed on size and book-to-market, the 6 value-weight portfolios formed on size and operating profitability, and the 6 value-weight portfolios formed on size and investment. We will look more into these factors in future lectures, so don't worry too much if you don't understand it yet."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8KjtsHFblSf6"
      },
      "source": [
        "We will use returns at a monthly frequency that we obtain for the period 2010 – 2017 as follows:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:55:13.367412Z",
          "start_time": "2021-04-15T19:55:13.065455Z"
        },
        "id": "6mDC6A-VlSf6",
        "outputId": "a2d23b1f-a155-432f-f8c5-ae394f7f3dfe",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "PeriodIndex: 96 entries, 2010-01 to 2017-12\n",
            "Freq: M\n",
            "Data columns (total 6 columns):\n",
            " #   Column  Non-Null Count  Dtype  \n",
            "---  ------  --------------  -----  \n",
            " 0   Mkt-RF  96 non-null     float64\n",
            " 1   SMB     96 non-null     float64\n",
            " 2   HML     96 non-null     float64\n",
            " 3   RMW     96 non-null     float64\n",
            " 4   CMA     96 non-null     float64\n",
            " 5   RF      96 non-null     float64\n",
            "dtypes: float64(6)\n",
            "memory usage: 5.2 KB\n"
          ]
        }
      ],
      "source": [
        "ff_factor = 'F-F_Research_Data_5_Factors_2x3'\n",
        "ff_factor_data = web.DataReader(ff_factor, 'famafrench', start='2010-1-1', end='2017-12-31')[0]\n",
        "ff_factor_data.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:55:13.386698Z",
          "start_time": "2021-04-15T19:55:13.368623Z"
        },
        "id": "mIR2fuM3lSf7",
        "outputId": "a97c54a5-3e43-45d9-b403-320b836f8945",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Mkt-RF   SMB   HML   RMW   CMA    RF\n",
              "count   96.00 96.00 96.00 96.00 96.00 96.00\n",
              "mean     1.16  0.06 -0.05  0.13  0.05  0.01\n",
              "std      3.58  2.30  2.20  1.58  1.41  0.02\n",
              "min     -7.89 -4.55 -4.70 -3.88 -3.27  0.00\n",
              "25%     -0.92 -1.70 -1.66 -1.09 -0.95  0.00\n",
              "50%      1.23  0.21 -0.31  0.20 -0.01  0.00\n",
              "75%      3.20  1.59  1.21  1.20  0.92  0.01\n",
              "max     11.35  7.07  8.21  3.48  3.70  0.09"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d1f3c478-0cb7-4036-9191-0ed5119ee489\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Mkt-RF</th>\n",
              "      <th>SMB</th>\n",
              "      <th>HML</th>\n",
              "      <th>RMW</th>\n",
              "      <th>CMA</th>\n",
              "      <th>RF</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1.16</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>0.13</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>3.58</td>\n",
              "      <td>2.30</td>\n",
              "      <td>2.20</td>\n",
              "      <td>1.58</td>\n",
              "      <td>1.41</td>\n",
              "      <td>0.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-7.89</td>\n",
              "      <td>-4.55</td>\n",
              "      <td>-4.70</td>\n",
              "      <td>-3.88</td>\n",
              "      <td>-3.27</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>-0.92</td>\n",
              "      <td>-1.70</td>\n",
              "      <td>-1.66</td>\n",
              "      <td>-1.09</td>\n",
              "      <td>-0.95</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1.23</td>\n",
              "      <td>0.21</td>\n",
              "      <td>-0.31</td>\n",
              "      <td>0.20</td>\n",
              "      <td>-0.01</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>3.20</td>\n",
              "      <td>1.59</td>\n",
              "      <td>1.21</td>\n",
              "      <td>1.20</td>\n",
              "      <td>0.92</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>11.35</td>\n",
              "      <td>7.07</td>\n",
              "      <td>8.21</td>\n",
              "      <td>3.48</td>\n",
              "      <td>3.70</td>\n",
              "      <td>0.09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d1f3c478-0cb7-4036-9191-0ed5119ee489')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-d1f3c478-0cb7-4036-9191-0ed5119ee489 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-d1f3c478-0cb7-4036-9191-0ed5119ee489');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-11c1b3fc-4177-4fb7-9df6-2a1bd374cdac\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-11c1b3fc-4177-4fb7-9df6-2a1bd374cdac')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-11c1b3fc-4177-4fb7-9df6-2a1bd374cdac button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"ff_factor_data\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"Mkt-RF\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.77139060507983,\n        \"min\": -7.89,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.1585416666666666,\n          1.2349999999999999,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"SMB\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.85467745835841,\n        \"min\": -4.55,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.06020833333333334,\n          0.20500000000000002,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"HML\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.89516710271428,\n        \"min\": -4.7,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          -0.04999999999999997,\n          -0.31,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"RMW\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.927026972887056,\n        \"min\": -3.88,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.12833333333333333,\n          0.195,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CMA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.905713668680534,\n        \"min\": -3.27,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.047916666666666656,\n          -0.005,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"RF\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.934310689764864,\n        \"min\": 0.0,\n        \"max\": 96.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          96.0,\n          0.012604166666666666,\n          0.09\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 37
        }
      ],
      "source": [
        "ff_factor_data.describe()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CR8HcESklSf8"
      },
      "source": [
        "### Portfolios"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BjcVuZaMlSf8"
      },
      "source": [
        "Fama and French also make available numerous portfolios that we can illustrate the estimation of the factor exposures, as well as the value of the risk premia available in the market for a given time period. We will use a panel of the 17 industry portfolios at a monthly frequency.\n",
        "\n",
        "We will subtract the risk-free rate from the returns because the factor model works with excess returns:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:55:14.483710Z",
          "start_time": "2021-04-15T19:55:13.388307Z"
        },
        "id": "f9nNmnRzlSf8",
        "outputId": "e47b38b5-3b42-4273-e858-8fd05055a5e2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "PeriodIndex: 96 entries, 2010-01 to 2017-12\n",
            "Freq: M\n",
            "Data columns (total 17 columns):\n",
            " #   Column  Non-Null Count  Dtype  \n",
            "---  ------  --------------  -----  \n",
            " 0   Food    96 non-null     float64\n",
            " 1   Mines   96 non-null     float64\n",
            " 2   Oil     96 non-null     float64\n",
            " 3   Clths   96 non-null     float64\n",
            " 4   Durbl   96 non-null     float64\n",
            " 5   Chems   96 non-null     float64\n",
            " 6   Cnsum   96 non-null     float64\n",
            " 7   Cnstr   96 non-null     float64\n",
            " 8   Steel   96 non-null     float64\n",
            " 9   FabPr   96 non-null     float64\n",
            " 10  Machn   96 non-null     float64\n",
            " 11  Cars    96 non-null     float64\n",
            " 12  Trans   96 non-null     float64\n",
            " 13  Utils   96 non-null     float64\n",
            " 14  Rtail   96 non-null     float64\n",
            " 15  Finan   96 non-null     float64\n",
            " 16  Other   96 non-null     float64\n",
            "dtypes: float64(17)\n",
            "memory usage: 13.5 KB\n"
          ]
        }
      ],
      "source": [
        "ff_portfolio = '17_Industry_Portfolios'\n",
        "ff_portfolio_data = web.DataReader(ff_portfolio, 'famafrench', start='2010-1-1', end='2017-12-31')[0]\n",
        "ff_portfolio_data = ff_portfolio_data.sub(ff_factor_data.RF, axis=0)\n",
        "ff_portfolio_data.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:55:14.519355Z",
          "start_time": "2021-04-15T19:55:14.484749Z"
        },
        "id": "h0ykhAMUlSf8",
        "outputId": "8b54a0ea-9a5e-4195-8cd6-85986681f279",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Food   Mines  Oil    Clths  Durbl  Chems  Cnsum  Cnstr  Steel  FabPr  \\\n",
              "count  96.00  96.00  96.00  96.00  96.00  96.00  96.00  96.00  96.00  96.00   \n",
              "mean    1.04   0.21   0.59   1.38   1.14   1.33   1.19   1.73   0.54   1.35   \n",
              "std     2.81   7.94   5.50   5.01   5.21   5.59   3.14   5.25   7.42   4.71   \n",
              "min    -5.16 -24.51 -11.76  -9.77 -13.17 -16.77  -7.18 -14.14 -20.57 -12.18   \n",
              "25%    -0.80  -5.81  -3.17  -1.57  -2.27  -1.34  -0.90  -2.44  -4.38  -1.45   \n",
              "50%     0.94  -0.48   0.99   1.15   1.23   1.44   1.47   2.16   0.66   1.50   \n",
              "75%     3.21   5.90   4.20   3.77   4.63   4.44   3.29   5.55   4.27   3.85   \n",
              "max     6.68  22.03  16.03  17.32  16.58  18.36   8.28  15.58  21.62  17.87   \n",
              "\n",
              "       Machn  Cars   Trans  Utils  Rtail  Finan  Other  \n",
              "count  96.00  96.00  96.00  96.00  96.00  96.00  96.00  \n",
              "mean    1.22   1.28   1.47   0.89   1.24   1.25   1.29  \n",
              "std     4.80   5.76   4.17   3.23   3.52   4.87   3.67  \n",
              "min    -9.11 -11.77  -8.66  -7.11  -9.20 -11.29  -8.04  \n",
              "25%    -2.01  -1.25  -0.86  -0.73  -0.95  -1.53  -1.15  \n",
              "50%     1.49   0.62   1.52   1.27   0.89   1.79   1.57  \n",
              "75%     4.58   4.81   4.34   2.93   3.37   4.15   3.42  \n",
              "max    14.74  21.04  13.03   7.84  12.46  13.50  10.43  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-aa2f820c-5a16-47c4-806c-c2de2a298a52\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Food</th>\n",
              "      <th>Mines</th>\n",
              "      <th>Oil</th>\n",
              "      <th>Clths</th>\n",
              "      <th>Durbl</th>\n",
              "      <th>Chems</th>\n",
              "      <th>Cnsum</th>\n",
              "      <th>Cnstr</th>\n",
              "      <th>Steel</th>\n",
              "      <th>FabPr</th>\n",
              "      <th>Machn</th>\n",
              "      <th>Cars</th>\n",
              "      <th>Trans</th>\n",
              "      <th>Utils</th>\n",
              "      <th>Rtail</th>\n",
              "      <th>Finan</th>\n",
              "      <th>Other</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "      <td>96.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1.04</td>\n",
              "      <td>0.21</td>\n",
              "      <td>0.59</td>\n",
              "      <td>1.38</td>\n",
              "      <td>1.14</td>\n",
              "      <td>1.33</td>\n",
              "      <td>1.19</td>\n",
              "      <td>1.73</td>\n",
              "      <td>0.54</td>\n",
              "      <td>1.35</td>\n",
              "      <td>1.22</td>\n",
              "      <td>1.28</td>\n",
              "      <td>1.47</td>\n",
              "      <td>0.89</td>\n",
              "      <td>1.24</td>\n",
              "      <td>1.25</td>\n",
              "      <td>1.29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>2.81</td>\n",
              "      <td>7.94</td>\n",
              "      <td>5.50</td>\n",
              "      <td>5.01</td>\n",
              "      <td>5.21</td>\n",
              "      <td>5.59</td>\n",
              "      <td>3.14</td>\n",
              "      <td>5.25</td>\n",
              "      <td>7.42</td>\n",
              "      <td>4.71</td>\n",
              "      <td>4.80</td>\n",
              "      <td>5.76</td>\n",
              "      <td>4.17</td>\n",
              "      <td>3.23</td>\n",
              "      <td>3.52</td>\n",
              "      <td>4.87</td>\n",
              "      <td>3.67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-5.16</td>\n",
              "      <td>-24.51</td>\n",
              "      <td>-11.76</td>\n",
              "      <td>-9.77</td>\n",
              "      <td>-13.17</td>\n",
              "      <td>-16.77</td>\n",
              "      <td>-7.18</td>\n",
              "      <td>-14.14</td>\n",
              "      <td>-20.57</td>\n",
              "      <td>-12.18</td>\n",
              "      <td>-9.11</td>\n",
              "      <td>-11.77</td>\n",
              "      <td>-8.66</td>\n",
              "      <td>-7.11</td>\n",
              "      <td>-9.20</td>\n",
              "      <td>-11.29</td>\n",
              "      <td>-8.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>-0.80</td>\n",
              "      <td>-5.81</td>\n",
              "      <td>-3.17</td>\n",
              "      <td>-1.57</td>\n",
              "      <td>-2.27</td>\n",
              "      <td>-1.34</td>\n",
              "      <td>-0.90</td>\n",
              "      <td>-2.44</td>\n",
              "      <td>-4.38</td>\n",
              "      <td>-1.45</td>\n",
              "      <td>-2.01</td>\n",
              "      <td>-1.25</td>\n",
              "      <td>-0.86</td>\n",
              "      <td>-0.73</td>\n",
              "      <td>-0.95</td>\n",
              "      <td>-1.53</td>\n",
              "      <td>-1.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.94</td>\n",
              "      <td>-0.48</td>\n",
              "      <td>0.99</td>\n",
              "      <td>1.15</td>\n",
              "      <td>1.23</td>\n",
              "      <td>1.44</td>\n",
              "      <td>1.47</td>\n",
              "      <td>2.16</td>\n",
              "      <td>0.66</td>\n",
              "      <td>1.50</td>\n",
              "      <td>1.49</td>\n",
              "      <td>0.62</td>\n",
              "      <td>1.52</td>\n",
              "      <td>1.27</td>\n",
              "      <td>0.89</td>\n",
              "      <td>1.79</td>\n",
              "      <td>1.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>3.21</td>\n",
              "      <td>5.90</td>\n",
              "      <td>4.20</td>\n",
              "      <td>3.77</td>\n",
              "      <td>4.63</td>\n",
              "      <td>4.44</td>\n",
              "      <td>3.29</td>\n",
              "      <td>5.55</td>\n",
              "      <td>4.27</td>\n",
              "      <td>3.85</td>\n",
              "      <td>4.58</td>\n",
              "      <td>4.81</td>\n",
              "      <td>4.34</td>\n",
              "      <td>2.93</td>\n",
              "      <td>3.37</td>\n",
              "      <td>4.15</td>\n",
              "      <td>3.42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>6.68</td>\n",
              "      <td>22.03</td>\n",
              "      <td>16.03</td>\n",
              "      <td>17.32</td>\n",
              "      <td>16.58</td>\n",
              "      <td>18.36</td>\n",
              "      <td>8.28</td>\n",
              "      <td>15.58</td>\n",
              "      <td>21.62</td>\n",
              "      <td>17.87</td>\n",
              "      <td>14.74</td>\n",
              "      <td>21.04</td>\n",
              "      <td>13.03</td>\n",
              "      <td>7.84</td>\n",
              "      <td>12.46</td>\n",
              "      <td>13.50</td>\n",
              "      <td>10.43</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-aa2f820c-5a16-47c4-806c-c2de2a298a52')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-aa2f820c-5a16-47c4-806c-c2de2a298a52 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-aa2f820c-5a16-47c4-806c-c2de2a298a52');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-a8560566-63a8-4496-bce1-c0560f58505e\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-a8560566-63a8-4496-bce1-c0560f58505e')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-a8560566-63a8-4496-bce1-c0560f58505e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"ff_portfolio_data\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"Food \",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.67363427006049,\n        \"min\": -5.16,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.0354166666666667,\n          0.94,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Mines\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 36.15768218246214,\n        \"min\": -24.51,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.2100000000000001,\n          -0.48,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Oil  \",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 34.23044035894398,\n        \"min\": -11.76,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.5948958333333333,\n          0.99,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Clths\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.91587099433812,\n        \"min\": -9.77,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.3836458333333335,\n          1.1549999999999998,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Durbl\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 34.28130945092025,\n        \"min\": -13.17,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.1417708333333334,\n          1.225,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Chems\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 34.65010373966953,\n        \"min\": -16.77,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.327604166666667,\n          1.4449999999999998,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Cnsum\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.75396155499807,\n        \"min\": -7.18,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.1890625000000001,\n          1.465,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Cnstr\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 34.28103030010487,\n        \"min\": -14.14,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.7341666666666669,\n          2.16,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Steel\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 35.470803650099235,\n        \"min\": -20.57,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.5355208333333336,\n          0.655,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"FabPr\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 34.160711214013375,\n        \"min\": -12.18,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.3502083333333335,\n          1.5,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Machn\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.82297576470163,\n        \"min\": -9.11,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.2192708333333335,\n          1.4949999999999999,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Cars \",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 34.1444768007195,\n        \"min\": -11.77,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.2822916666666668,\n          0.62,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Trans\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.72538163985798,\n        \"min\": -8.66,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.4697916666666666,\n          1.52,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Utils\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.78399640440801,\n        \"min\": -7.11,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.8942708333333336,\n          1.275,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rtail\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.89724019841643,\n        \"min\": -9.2,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.2404166666666667,\n          0.885,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Finan\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 34.00809684746285,\n        \"min\": -11.29,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.2472916666666667,\n          1.79,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Other\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33.77163842829509,\n        \"min\": -8.04,\n        \"max\": 96.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.2862500000000001,\n          1.5699999999999998,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 39
        }
      ],
      "source": [
        "ff_portfolio_data.describe()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1uWxnMHslSf8"
      },
      "source": [
        "### Equity Data"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<font color='orange'>Question 3: You are going to work with large files in financial machine learning applications, as such you should show that you can extract compressed files (4 points) </font>\n",
        "\n",
        "link: `https://storage.googleapis.com/public-quant/course//content/quandl-wiki-prices-us-equites.zip` (**changed**)\n",
        "\n",
        "*   Once more you can use any method and library that you please, i will simply provide you with the compressed link.\n",
        "*   The final csv file that you extract has to be renamed as ``wiki_prices.csv`` then you can succesfully run the code below.\n",
        "*   Note we don't know all the solutions, so stackoverflow and google are your friends, use them!\n",
        "*   Hint, you might want to learn how to `!wget` to download the file directly to the notebook, and how to use `!mv` to rename the file.\n",
        "*   We use the `!` command when we want to speak directly to the terminal.\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "i3q1GJcPZf2G"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Provide your solution here (first perform the wget command)\n"
      ],
      "metadata": {
        "id": "nVhTxPq_a3Ko"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "## Provide your solution here (then unzip the file)\n"
      ],
      "metadata": {
        "id": "V2Zqv_Mk30qa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!mv WIKI_PRICES_212b326a081eacca455e13140d7bb9db.csv wiki_prices.csv"
      ],
      "metadata": {
        "id": "dVqkbKAG3s3y"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "quandl_archive = (pd.read_csv('wiki_prices.csv',\n",
        "                 parse_dates=['date'],\n",
        "                 index_col=['date', 'ticker'],\n",
        "                 infer_datetime_format=True).sort_index())\n",
        "prices = quandl_archive.adj_close.unstack().loc['2010':'2017']"
      ],
      "metadata": {
        "id": "ZAcSr-NMWjr_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "equities = pd.read_csv('https://raw.githubusercontent.com/stefan-jansen/machine-learning-for-trading/f881ea01ef8ae5a308ab75de833ba24bee27435e/data/us_equities_meta_data.csv')\n",
        "equities = equities.set_index('ticker').drop_duplicates()"
      ],
      "metadata": {
        "id": "OUKeAfu2bW5R"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:55:20.245270Z",
          "start_time": "2021-04-15T19:55:20.201602Z"
        },
        "id": "sjoAJQZklSf9"
      },
      "outputs": [],
      "source": [
        "sectors = equities.filter(prices.columns, axis=0).sector.to_dict()\n",
        "prices = prices.filter(sectors.keys()).dropna(how='all', axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:55:20.330305Z",
          "start_time": "2021-04-15T19:55:20.246605Z"
        },
        "id": "XThhcGbrlSf-"
      },
      "outputs": [],
      "source": [
        "returns = prices.resample('M').last().pct_change().mul(100).to_period('M')\n",
        "returns = returns.dropna(how='all').dropna(axis=1)\n",
        "returns.info()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q9axHYT9lSf-"
      },
      "source": [
        "### Question 4"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2021-04-15T19:55:20.336370Z",
          "start_time": "2021-04-15T19:55:20.332866Z"
        },
        "id": "faUtyS0ylSf_"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "np.random.seed(42)\n",
        "\n",
        "# Generate 500 days of returns\n",
        "n_days = 500\n",
        "\n",
        "# S&P 500 returns (normally distributed with mean 0.0005 and std 0.01)\n",
        "sp500_returns = np.random.normal(0.0005, 0.01, n_days)\n",
        "\n",
        "# Generate correlated stock returns\n",
        "beta = 1.2\n",
        "alpha = 0.0001\n",
        "epsilon = np.random.normal(0, 0.02, n_days)\n",
        "stock_returns = alpha + beta * sp500_returns + epsilon\n",
        "\n",
        "# Create a DataFrame\n",
        "df = pd.DataFrame({\n",
        "    'Date': pd.date_range(start='2022-01-01', periods=n_days),\n",
        "    'SP500_Return': sp500_returns,\n",
        "    'Stock_Return': stock_returns\n",
        "})"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<font color='orange'>Question 4: Calculate the rolling correlation between the stock returns and the S&P 500 returns with a 14 day lookback period and plot the stock price. Also calculate the rolling volatility of the stock. Plot both on the same plot\n",
        "(4 points)</font>"
      ],
      "metadata": {
        "id": "KaojJUCo8lgB"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "imfuUGYt8lUo"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "celltoolbar": "Slideshow",
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.8"
    },
    "latex_envs": {
      "bibliofile": "biblio.bib",
      "cite_by": "apalike",
      "current_citInitial": 1,
      "eqLabelWithNumbers": true,
      "eqNumInitial": 0
    },
    "toc": {
      "base_numbering": 1,
      "nav_menu": {},
      "number_sections": true,
      "sideBar": true,
      "skip_h1_title": false,
      "title_cell": "Table of Contents",
      "title_sidebar": "Contents",
      "toc_cell": false,
      "toc_position": {},
      "toc_section_display": true,
      "toc_window_display": true
    },
    "colab": {
      "name": "Linear Regression Test.ipynb",
      "provenance": [],
      "include_colab_link": true
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}