Forecasting stock returns in good and bad times: The role of market states

• Main Authors: HUANG, Dashan, JIANG, Fuwei, Jun TU, ZHOU, Guofu
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Return predictability; Mean reversion; Momentum; Market risk premium; Leading economic indicator; 200-day moving average; Business cycle; Finance; Finance and Financial Management
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/5156; https://ink.library.smu.edu.sg/context/lkcsb_research/article/6155/viewcontent/SSRN_id2188989.pdf
• Institution: Singapore Management University

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.