Upper Bounds on Return Predictability

Abstract

Can the degree of predictability found in data be explained by existing asset pricing models? We provide two theoretical upper bounds on the R 2 of predictive regressions. Using data on the market portfolio and component portfolios, we find that the empirical R 2 s are significantly greater than the theoretical upper bounds. Our results suggest that the most promising direction for future research should aim to identify new state variables that are highly correlated with stock returns instead of seeking more elaborate stochastic discount factors.