Fishing with a Licence: An Empirical Search for Asset Pricing Factors

Abstract

We study the question of which asset pricing factors should be included in linear factor asset pricing model. We develop a simple multivariate extension of a Bayesian variable selection procedure from the statistics literature to estimate posterior probabilities of asset pricing factors using many assets at once. Using a dataset of thousands of individual stocks in the US market, we calculate posterior probabilities of 12 factors which have been suggested in the literature. Our results indicate strong and robust evidence that a linear factor model should include the excess market return, the size and the liquidity factors, and only weak evidence that the idiosyncratic volatility and downside risk factors matter. We find that the famous Fama and French (1993, 1996) HML factor has high posterior probability only if portfolios formed on book-to-market ratio are used.

Keywords: linear factor model, asset pricing, Bayesian, variable selection

JEL Classification: G12