Winners from Winners: A Tale of Risk Factors

Starting from twelve distinct factors from the recent literature, plus twelve principal components (PCs) of anomalies unexplained by the initial factors, a Bayesian comparison of approximately seventeen million models in terms of marginal likelihoods and posterior model probabilities shows that {Mkt, MOM, IA, ROE, MGMT, PERF, PEAD, FIN}, plus the nonconsecutive principal components, {${\text{PC}}_1,\hspace{0.17em}{\text{PC}}_5,\hspace{0.17em}{\text{PC}}_7$} are the best supported risk factors. Pricing tests and annualized out-of-sample Sharpe ratios for tangency portfolios suggest that this asset pricing model should be used for computing expected returns, assessing investment strategies and building portfolios.

This paper was accepted by Lukas Schmid, finance.

Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4668.