Winners from Winners: A Tale of Risk Factors
29 Pages Posted: 17 Nov 2019
Date Written: October 30, 2019
Taking the union of the risk factors recently proposed by Fama and French (1993, 2015, 2018), Hou, Xue, and Zhang (2015), Stambaugh and Yuan (2017), and Daniel, Hirshleifer, and Sun (2019), a pool we refer to as the “winners”, we ask what collection of winners from winners emerge when each factor is allowed to play the role of a risk factor, or a non-risk factor. Our comparison of 4,095 models shows that a six factor model consisting of Mkt, SMB, MOM, ROE, MGMT, and PEAD as risk factors has the largest Bayesian posterior probability. Moreover, this collection displays superior out-of-sample predictive performance, higher Sharpe ratios, and greater ability in pricing anomalies, than the preceding models. These results suggest that both fundamental and behavioral factors play an important role in explaining the cross-section of expected equity returns.
Keywords: Model comparison, Risk factors, Marginal Likelihoods
JEL Classification: G10, G12
Suggested Citation: Suggested Citation