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  3. Introduction to Portfolio Risk Management in Python

Exercise

The Fama French 3-factor model

The Fama-French model famously adds two additional factors to the CAPM model to describe asset returns:

$$ R_{P} = RF + \beta_{M}(R_{M}-RF)+b_{SMB} \cdot SMB + b_{HML} \cdot HML + \alpha $$

  • SMB: The small minus big factor
  • \(b_{SMB}\): Exposure to the SMB factor
  • HML: The high minus low factor
  • \(b_{HML}\): Exposure to the HML factor
  • \(\alpha \): Performance which is unexplained by any other factors
  • \(\beta_{M}\): Beta to the broad market portfolio B

The FamaFrenchData DataFrame is available in your workspace and contains the HML and SMB factors as columns for this exercise.

Instructions

100 XP
  • Define a regression model that explains Portfolio_Excess as a function of Market_Excess, SMB, and HML.
  • Extract the adjusted r-squared value from FamaFrench_fit.