Bias, Stability and Predictive Ability in the Measurement of Systematic Risk

Abstract

Estimates of systematic risk or beta are an important determinant of the cost of capital. The standard technique used to compile beta estimates is an ordinary least squares regression of stock returns on market returns using 4 - 5 years of monthly data. This convention assumes that a longer time series of data will not adequately capture risks associated with existing assets. We show that the ability of beta estimates to predict future stock returns systematically increases with the length of the estimation window, the implication being that all available returns data should be used in beta estimation. In addition, for all estimation periods, there is an increase in returns predictability when the Vasicek adjustment is applied, an easily-implementable technique which reduces the weight placed on imprecise beta estimates.

Keywords: Beta, systematic risk, Capital Asset Pricing Model

JEL Classification: G11, G12