Deep Learning in Characteristics-Sorted Factor Models

Journal of Financial and Quantitative Analysis, Forthcoming

50 Pages Posted: 23 Sep 2018 Last revised: 26 Jun 2023

See all articles by Guanhao Feng

Guanhao Feng

City University of Hong Kong (CityU)

Jingyu He

City University of Hong Kong (CityU)

Nick Polson

University of Chicago - Booth School of Business

Jianeng Xu

University of Chicago, Students

Date Written: June 26, 2023

Abstract

This paper 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.

Keywords: Cross-sectional Returns, Deep Learning, Latent Factors, Nonlinearity, Security Sorting.

JEL Classification: C45, G11, G12.

Suggested Citation

Feng, Guanhao and He, Jingyu and Polson, Nick and Xu, Jianeng, Deep Learning in Characteristics-Sorted Factor Models (June 26, 2023). Journal of Financial and Quantitative Analysis, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3243683 or http://dx.doi.org/10.2139/ssrn.3243683

Guanhao Feng (Contact Author)

City University of Hong Kong (CityU) ( email )

83 Tat Chee Avenue
Hong Kong

Jingyu He

City University of Hong Kong (CityU) ( email )

83 Tat Chee Avenue
Hong Kong
Hong Kong

Nick Polson

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States
773-702-7513 (Phone)
773-702-0458 (Fax)

Jianeng Xu

University of Chicago, Students ( email )

Chicago, IL
United States

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