Investigating linear multi-factor models in asset pricing: considerable supplemental evidence

The literature has offered an interesting debate about whether the performance of Fama-French's three-factor benchmark model is inadequate because it fails to pass some model specification tests and its R2 is not convincingly high in cross-sectional estimations. Previous studies have been quite limited, since they only focused on the time-series procedure with many models. We extend their work by providing a more robust investigation of the performance of several well-regarded pricing models in pooled portfolios and other portfolios sorted by new and important anomalies, using cross-sectional GMM tests for robustness. Finally, we find that, in addition to Fama and French's five-factor model proposed in 1993, Fama-French's three-factor model augmented by other factors usually outperforms Fama-French's three-factor model across a significant proportion of different portfolios. In particular, Frazzini, Kabiller, and Pedersen's model shows the best overall performance and consistency across different portfolios.