Can Long-short Term Memory Neural Network With Symbolic Genetic Algorithm Predict Stock Price Change Basing on Fundamental Indicators
Qi Li,
Norshaliza Kamaruddin,
Hamdan Ali Al-Jaifi
Abstract:This paper presents an enhanced framework that combines Symbolic Genetic Algorithm (SGA) with Long-Short Term Memory Neural Network (LSTM) for predicting cross-sectional price returns using fundamental indicators of 4,500 listed stocks in China. The study addresses the challenges posed by fundamental indicators resembling smart beta factors in efficient markets and the low frequency of fundamental indicator updates for deep learning models (DNN). The proposed DNN framework incorporates data augmentation and fe… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.