Publication Type
Working Paper
Version
acceptedVersion
Publication Date
7-2017
Abstract
This paper proposes a two-state predictive regression model and shows that stock market 12-month return (TMR), the time-series momentum predictor of Moskowitz, Ooi, and Pedersen (2012), forecasts the aggregate stock market negatively in good times and positively in bad times. The out-of-sample R-squares are 0.96% and 1.72% in good and bad times, or 1.28% and 1.41% in NBER economic expansions and recessions, respectively. The TMR predictability pattern holds in the cross-section of U.S. stocks and the international markets. Our study shows that the absence of return predictability in good times, an important finding of recent studies, is largely driven by the use of the popular one-state predictive regression model.
Keywords
Return predictability, Mean reversion, Momentum, Market risk premium, Leading economic indicator, 200-day moving average, Business cycle
Discipline
Finance | Finance and Financial Management
Research Areas
Finance
First Page
1
Last Page
41
Identifier
10.2139/ssrn.2188989
Citation
HUANG, Dashan; JIANG, Fuwei; Jun TU; and ZHOU, Guofu.
Forecasting stock returns in good and bad times: The role of market states. (2017). 1-41.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/5156
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.2139/ssrn.2188989