What is it about?
This paper asks whether a range of stock market factors contain information that is useful to investors by generating a trading rule based on one-step-ahead forecasts from rolling and recursive regressions using a range of factors. Results from panel regressions and individual firm regressions show that an extended Fama-French five-factor model includes momentum, reversal, and quality factors that outperform other models. Moreover, the rolling based regressions outperform recursive ones in returns forecasting. This result suggests that more observations that are distant do not add to the predictive power of the factor and perhaps suggest notably time-variation on parameter values. The results presented here will be of interest to both academics in understanding the dynamics of expected stock returns and investors who seek to improve portfolio performance through understanding which factors determine stock return movement.