A multi-feature stock price prediction model based on multi-feature calculation, LASSO feature selection, and Ca-LSTM network

A multi-feature stock price prediction model based on multi-feature calculation, LASSO feature selection, and Ca-LSTM network

This paper addresses the crucial realm of stock price prediction, highly coveted by individual investors and institutions for its substantial economic implications. The inherent non-stationary and intricate nature of stock market fluctuations, coupled with real-time transactions, poses a formidable...

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Bibliographic Details
Main Authors: Xiao Chen, Lei Cao, Zhi Cao, HongWei Zhang
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Connection Science
Subjects:
Stock
long short-term memory
feature selection
predict
sliding window
Online Access:https://www.tandfonline.com/doi/10.1080/09540091.2023.2286188
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https://www.tandfonline.com/doi/10.1080/09540091.2023.2286188

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