How Much Return Predictability Do We Expect from an Asset Pricing Model?

Abstract:     
Stock market predictability is of considerable interest in both academic research and investment practice. Ross (2005) provides a simple and elegant upper bound on the predictive regression R-squared that R^2 <= (1 R_f)^2 Var(m) for a given asset pricing model with kernel m, where R_f is the risk-free rate of return. In this paper, we tighten this bound by a squared factor of the correlation between the default pricing kernel and the state variables of the economy. Since the correlation can be substantially smaller than one, our bound can be much tighter than Ross's. An empirical application illustrates that while Ross's bound is not binding, our bound does.

Keywords: Predictability, predictive regression, R-squared, stochastic discount factor

JEL Classifications: C22, G11, G12

Working Paper Series