This paper investigates whether return predictability can be explained by existing asset pricing models. Using different assumptions, I develop two theoretical upper bounds on the R-square of the regression of stock returns on predictive variables. Empirically, I find that the predictive R-square is significantly larger than the upper bounds, implying that extant asset pricing models are incapable of explaining the degree of return predictability. The reason for this inconsistency is the low correlation between the excess returns and the state variables used in the discount factor. The finding of this paper suggests the development of new asset pricing models with new state variables that are highly correlated with stock returns.
Return predictability, predictive regression, stochastic discount factor
Business Administration, Management, and Operations
What Is the Maximum Predictability Permitted by Asset Pricing Models?. (2013). Research Collection Lee Kong Chian School Of Business.
Available at: http://ink.library.smu.edu.sg/lkcsb_research/3776