A new multivariate decomposition-ensemble approach with denoised neighborhood rough set for stock price forecasting over time-series information system

The uncertainty of the stock market is the foundation for investors to obtain returns. Driven by interests, stock price forecasting has become a research hotspot. However, as the high latitude, highly volatile, and noisy, forecasting the stock prices has become a highly challenging task. The existin...

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Veröffentlicht in:	Applied intelligence (Dordrecht, Netherlands) Netherlands), 2025-02, Vol.55 (4), p.284, Article 284
Hauptverfasser:	Bai, Juncheng, Sun, Bingzhen, Guo, Yuqi, Chu, Xiaoli
Format:	Artikel
Sprache:	eng
Schlagworte:	Forecasting Information systems Machine learning Multivariate analysis Noise reduction Securities markets Stock prices Time series
Online-Zugang:	Volltext
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