The Capital Asset Pricing Model (CAPM) is today\'s most important financial model for estimating cost of capital and asset allocation. It\'s centerpiece are variables, commonly called betas and alphas, estimated using ordinary least squares (OLS) regression. Since financial returns typically have an asymmetric and heavy-tailed distribution, OLS estimates can be severely biased. In this talk we will introduce robust regression estimates with zero bias in beta and low bias in alpha (even under asymmetric distributions) but 99% asymptotic efficiency at the Gaussian model. We will show that the removal of less than 1% of outlying data produces significantly different CAPM estimates, which also proof to be much better predictors of future risk and return.
Heiko Manfred Bailer