Bayesian selection of asset pricing factors using individual stocks
A previous version of this paper circulated under the title "Searching the Factor Zoo". A revised version has been published on the Journal of Financial Econometrics (https://doi.org/10.1093/jjfinec/nbaa045)
48 Pages Posted: 12 Mar 2018 Last revised: 21 Oct 2021
Date Written: October 14, 2020
We apply Bayesian variable selection to investigate linear factor asset pricing models for a large set of candidate factors identified in the literature. We extract model and factor posterior probabilities from thousands of individual stocks via Markov Chain Monte Carlo estimation together with the exact distribution of pricing statistics. Our results show that only a small number of factors are relevant and, except for the market and size factors, these are not the factors in widely used linear factor models such as Fama & French (2015) or Hou et al. (2015). Moreover, many different linear factor models achieve similar empirical performance, suggesting that the search for a single linear factor model is unlikely to yield a definitive answer.
Keywords: Multi-factor model, Factor zoo, Factor selection, Bayesian variable selection, SeeminglyUnrelated Regressions
JEL Classification: G12, C52
Suggested Citation: Suggested Citation