Bayesian tests of global factor models

I use the Bayesian approach of Barillas and Shanken(2018) to examine the mean-variance efficiency of nine global factor models in global stock returns and to conduct multiple model comparison tests. The mean-variance efficiency of each factor model is strongly rejected. In the multiple model comparison tests, the three-factor model of Asness, Moskowitz and Pedersen(2013) has the best performance at higher prior maximum Sharpe(1966) ratio multiples and significantly outperforms all the other factor models. However, in out-of-sample tests, the AMP model significantly underperforms the best performing models that can be formed among the set of all factors used by the global factor models.