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  3. Introduction to Portfolio Risk Management in Python
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Exercise

Calculating beta with CAPM

There are many ways to model stock returns, but the Capital Asset Pricing Model, or CAPM, is one the most well known:

$$ E(R_{P}) - RF = \beta_{{P}}(E(R_{M})-RF)\ $$

  • \(E(R_{P}) - RF\): The excess expected return of a stock or portfolio P
  • \(E(R_{M}) - RF\): The excess expected return of the broad market portfolio B
  • \(RF\): The regional risk free-rate
  • \(\beta_{{P}}\): Portfolio beta, or exposure, to the broad market portfolio B

You can call the .fit() method from statsmodels.formula.api on an .ols(formula, data) model object to perform the analysis, and the .summary() method on the analysis object to anaylze the results.

The FamaFrenchData DataFrame is available in your workspace and contains the proper data for this exercise.

Instrukcje

100 XP
  • First, you will need to import statsmodels.formula.api as smf.
  • Define a regression model that explains Portfolio_Excess as a function of Market_Excess.
  • Extract and print the adjusted r-squared of the fitted regression model.
  • Extract the market beta of your portfolio.