{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Linear Regression: Model Estimation\n", "\n", "**Functions**\n", "\n", "`sm.OLS`\n", "\n", "### Exercise 32\n", "Use the OLS function to estimate the coefficients of the Fama-French portfolios (monthly data) on the\n", "market, size and value factors. Include a constant in the regressions. Use only the four\n", "extremum portfolios – that is the 1-1, 1-5, 5-1 and 5-5 portfolios. Estimate the model with\n", "homoskedastic errors and with White's covariance estimator." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "execution": { "iopub.execute_input": "2021-09-22T10:07:16.072021Z", "iopub.status.busy": "2021-09-22T10:07:16.072021Z", "iopub.status.idle": "2021-09-22T10:07:16.758021Z", "shell.execute_reply": "2021-09-22T10:07:16.757024Z" } }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Exercise 33\n", "Are the parameter standard errors similar using the two covariance estimators?\n", "If not, what does this mean? " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "execution": { "iopub.execute_input": "2021-09-22T10:07:17.729020Z", "iopub.status.busy": "2021-09-22T10:07:17.728021Z", "iopub.status.idle": "2021-09-22T10:07:17.757021Z", "shell.execute_reply": "2021-09-22T10:07:17.757021Z" } }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Exercise 34\n", "How much of the variation is explained by these three regressors?" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "execution": { "iopub.execute_input": "2021-09-22T10:07:17.793020Z", "iopub.status.busy": "2021-09-22T10:07:17.792020Z", "iopub.status.idle": "2021-09-22T10:07:17.804021Z", "shell.execute_reply": "2021-09-22T10:07:17.804021Z" } }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.6" }, "pycharm": { "stem_cell": { "cell_type": "raw", "metadata": { "collapsed": false }, "source": [] } } }, "nbformat": 4, "nbformat_minor": 4 }