Upper bounds on return predictability

• Main Authors: HUANG, Dashan, ZHOU, Guofu
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Return predictability; asset pricing; stochastic discount factor; habit formation; long-run risks; rare disaster; Business; Finance and Financial Management
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/4569; https://ink.library.smu.edu.sg/context/lkcsb_research/article/5568/viewcontent/UpperBounds.pdf
• Institution: Singapore Management University

Can the degree of predictability found in data be explained by existing asset pricing models? We provide two theoretical upper bounds on the R2 of predictive regressions. Using data on the market portfolio and component portfolios, we find that the empirical R2 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.