The efficient market and alpha
The alpha (\(\alpha\)) left over by the regression is unexplained performance due to unknown factors. In a regression model, this is simply the coefficient of the intercept.
There are two general schools of thought as to why:
- The model simply needs to be expanded. When you have found all of the missing economic factors, you can explain all stock and portfolio returns. This is known as the Efficient Market Hypothesis.
- There is a degree of unexplainable performance that no model will ever capture reliably. Perhaps it is due to skill, timing, intuition or luck, but investors should seek to maximize their alpha.
Your fitted regression analysis from the previous exercise has been stored in FamaFrench_fit.
This exercise is part of the course
Introduction to Portfolio Risk Management in Python
Exercise instructions
- Extract the coefficient of your intercept and assign it to
portfolio_alpha. - Annualize your
portfolio_alphareturn by assuming 252 trading days in a year.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Calculate your portfolio alpha
portfolio_alpha = FamaFrench_fit.____
print(portfolio_alpha)
# Annualize your portfolio alpha
portfolio_alpha_annualized = ____
print(portfolio_alpha_annualized)