Multi-step-ahead stock price index forecasting using long short-term memory model with multivariate empirical mode decomposition

•MEMD- LSTM model for multi-step ahead stock price forecasting was built.•Multi-step ahead forecasting was based on the multiple-input multiple-output strategy.•MEMD was employed to decompose the original time series without information loss.•The proposed model demonstrated its superiority than othe...

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Vydáno v:	Information sciences Ročník 607; s. 297 - 321
Hlavní autoři:	Deng, Changrui, Huang, Yanmei, Hasan, Najmul, Bao, Yukun
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Inc 01.08.2022
Témata:	Long short-term memory Multi-step-ahead forecasting Multivariate empirical mode decomposition Orthogonal array tuning method Stock price index Long short-term memory Stock price index Multi-step-ahead forecasting Orthogonal array tuning method Multivariate empirical mode decomposition
ISSN:	0020-0255, 1872-6291
On-line přístup:	Získat plný text
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