Comparing model-specific and model-agnostic features importance methods using machine learning with technical indicators: A NASDAQ sector-based study

Predicting stock prices is crucial for making informed investment decisions as stock markets significantly influence the global economy. Although previous studies have explored feature importance methods for stock price prediction, comprehensive comparisons of those methods have been limited. This s...

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Autors principals:	Jeonghoe Lee, Lin Cai
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2026-03-01
Col·lecció:	Machine Learning with Applications
Matèries:	Feature importance Technical indicators Stock price prediction Machine learning Explainable artificial intelligence (XAI)
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S2666827025001823
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