A Conditional Multifactor Analysis of Return Momentum

Abstract

Although the Fama-French three-factor model captures most CAPM anomalies, it still fails to explain return momentum. This paper shows that the incorporation of conditioning information into an asset-pricing model is one way to capture return momentum. Results from the conditional regression with linear exposures in the instruments show clear evidence that both SMB and HML risks are time varying and that momentum and reversal return patterns have different time-varying risk characteristics. The conditional Fama-French regression model seems, however, to remain misspecified. Conversely, when the linearity assumption is relaxed and cross-sectional restrictions are imposed, the conditional pricing model appears to capture both short-term momentum and long-term reversal. Key words: Conditional Asset Pricing, Conditioning Information, Multifactor Model, Return Momentum, Return Reversal