Upper Bounds on Return Predictability

46 Pages Posted: 18 Apr 2014 Last revised: 24 Apr 2017

See all articles by Dashan Huang

Dashan Huang

Singapore Management University - Lee Kong Chian School of Business

Guofu Zhou

Washington University in St. Louis - John M. Olin Business School; China Academy of Financial Research (CAFR)

Date Written: August 1, 2015

Abstract

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

Keywords: Return predictability, asset pricing, stochastic discount factor, habit formation, long-run risks, rare disaster

JEL Classification: C22, C53, C58, G10, G12, G14, G17

Suggested Citation

Huang, Dashan and Zhou, Guofu, Upper Bounds on Return Predictability (August 1, 2015). Journal of Financial and Quantitative Analysis (JFQA), Vol. 52, No. 2, 2017. Available at SSRN: https://ssrn.com/abstract=2426447 or http://dx.doi.org/10.2139/ssrn.2426447

Dashan Huang

Singapore Management University - Lee Kong Chian School of Business ( email )

50 Stamford Road
Singapore, 178899
Singapore

HOME PAGE: http://dashanhuang.weebly.com/

Guofu Zhou (Contact Author)

Washington University in St. Louis - John M. Olin Business School ( email )

Washington University
Campus Box 1133
St. Louis, MO 63130-4899
United States
314-935-6384 (Phone)
314-658-6359 (Fax)

HOME PAGE: http://apps.olin.wustl.edu/faculty/zhou/

China Academy of Financial Research (CAFR)

Shanghai Advanced Institute of Finance
Shanghai P.R.China, 200030
China

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