Factor-GAN: Enhancing stock price prediction and factor investment with Generative Adversarial Networks.

ABSTRACT: Deep learning, a pivotal branch of artificial intelligence, has increasingly influenced the financial domain with its advanced data processing capabilities. This paper introduces Factor-GAN, an innovative framework that utilizes Generative Adversarial Networks (GAN) technology for factor investing. Leveraging a comprehensive factor database comprising 70 firm characteristics, Factor-GAN integrates deep learning techniques with the multi-factor pricing model, thereby elevating the precision and stability of investment strategies. To explain the economic mechanisms underlying deep learning, we conduct a subsample analysis of the Chinese stock market. The findings reveal that the deep learning-based pricing model significantly enhances return prediction accuracy and factor investment performa

SUBMITTER: Wang J 

PROVIDER: S-EPMC11198854 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature