Deep Learning in Characteristics-Sorted Factor Models

Guanhao Feng (), Jingyu He, Nicholas G. Polson and Jianeng Xu

Journal of Financial and Quantitative Analysis, 2024, vol. 59, issue 7, 3001-3036

Abstract: This article presents an augmented deep factor model that generates latent factors for cross-sectional asset pricing. The conventional security sorting on firm characteristics for constructing long–short factor portfolio weights is nonlinear modeling, while factors are treated as inputs in linear models. We provide a structural deep-learning framework to generalize the complete mechanism for fitting cross-sectional returns by firm characteristics through generating risk factors (hidden layers). Our model has an economic-guided objective function that minimizes aggregated realized pricing errors. Empirical results on high-dimensional characteristics demonstrate robust asset pricing performance and strong investment improvements by identifying important raw characteristic sources.

Date: 2024
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