N°25-32: Generalized Portfolio Sorts for Factor Validation

Portfolio sorts are widely used in empirical asset pricing to identify firm characteristics that predict stock returns. However, such tests can conflate genuine characteristic-based predictability with persistent, firm-level heterogeneity. To address this limitation, we propose a Generalized Portfolio Sorts (GPS) model, which can exactly replicate results from all variants of conventional portfolio sorts, but can also be specified so that it separates a firm characteristic’s genuine predictive power from stable firm-level factors. We also derive a statistical test to detect whether return predictability arises from the sorting characteristic itself or from persistent, firm-level traits. Applied to a large set of proposed asset pricing predictors, we find that nearly half lose significance once persistent, firm-level heterogeneity is accounted for. The GPS-model thus strengthens factor validation, advances our understanding of the factor zoo, and provides a more robust foundation for empirical asset pricing tests.