Advancing stock price prediction through the development of hybrid ensembles: a comprehensive comparative analysis of machine learning approaches

Abstract This study introduces an innovative ensemble learning approach for stock direction classification and prediction. The methodology enhances accuracy through strategic base learner selection, hyperparameter optimisation using GridSearchCV, and hybrid ensemble techniques. Leveraging a diverse...

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Váldodahkkit:	Akila Dabara Kayit, Mohd Tahir Ismail
Materiálatiipa:	Artigo
Giella:	Inglês
Almmustuhtton:	SpringerOpen 2025-10-01
Ráidu:	Journal of Big Data
Fáttát:	Stock direction prediction Machine-learning Classification Hybrid-ensemble Soft-voting Statistical test
Liŋkkat:	https://doi.org/10.1186/s40537-025-01185-8
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