Research on Stock Index Prediction Based on the Spatiotemporal Attention BiLSTM Model

Research on Stock Index Prediction Based on the Spatiotemporal Attention BiLSTM Model

Stock index fluctuations are characterized by high noise and their accurate prediction is extremely challenging. To address this challenge, this study proposes a spatial–temporal–bidirectional long short-term memory (STBL) model, incorporating spatiotemporal attention mechanisms. The model enhances...

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Bibliographic Details
Main Authors: Shengdong Mu, Boyu Liu, Jijian Gu, Chaolung Lien, Nedjah Nadia
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:Mathematics
Subjects:
spatiotemporal attention
bidirectional long short-term memory network (BiLSTM)
stock index prediction
graph attention network
Online Access:https://www.mdpi.com/2227-7390/12/18/2812

Internet

https://www.mdpi.com/2227-7390/12/18/2812

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