A Bayesian Re-Interpretation of ”Significant” Empirical Financial Research

Abstract Currently, the use of t statistics and p-values is under scrutiny in various scientific fields for several reasons: p-hacking, data dredging, misinterpretation or selective reporting, among others. To the best of our knowledge, this discussion has hardly reached the empirical finance community. The aim of this paper is to show how typical testing frameworks of empirical findings in finance can be fruitfully enriched by supplemental use of further statistical tools. We revisit popular studies regarding the validity of the CAPM and determine Bayesian measures for hypothesis testing, e.g., we find popular asset pricing studies might have been evaluated differently.