Time-variation, multiple testing, and the factor zoo

Abstract

Bayesians circumvent the need for significance threshold correction when multiple testing and we recommend controlling the Type-S (sign), rather than the Type-1, error rate because it yields more reliable frequency properties for inferences. Our unified Bayesian framework, with theory-informed priors, identifies two breaks (2001 and 2008) in our 1980–2018 sample period. After each break the set of characteristics changes, and only market beta is selected in all regimes. In a portfolio application, the method generates significantly larger Sharpe ratios after transaction costs than a range of benchmark methods, including the same model that uses a Type-1 (not Type-S) error framework.