Publication Type
Working Paper
Version
publishedVersion
Publication Date
11-2013
Abstract
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.
Keywords
Return predictability, predictive regression, stochastic discount factor
Discipline
Business Administration, Management, and Operations
Research Areas
Finance
Citation
Huang, Dashan.
What Is the Maximum Predictability Permitted by Asset Pricing Models?. (2013).
Available at: https://ink.library.smu.edu.sg/lkcsb_research/3776
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.