FactorVQVAE: Discrete latent factor model via Vector Quantized Variational Autoencoder

This study introduces FactorVQVAE, the first integration of the Vector Quantized Variational Autoencoder (VQVAE) into factor modeling, providing a novel framework for predicting cross-sectional stock returns and constructing systematic investment portfolios. The model employs a two-stage architectur...

Full description

Bibliographic Details

Published in:	Knowledge-based systems Vol. 318; p. 113460
Main Authors:	Kim, Namhyoung, Ock, Seung Eun, Song, Jae Wook
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 07.06.2025
Subjects:	Autoencoder Dynamic latent factor model Portfolio investment Transformer Vector quantization Portfolio investment Transformer Vector quantization Dynamic latent factor model Autoencoder
ISSN:	0950-7051
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!