Risk prediction of investment funds in member countries of the Federation of European and Asian Stock Exchanges - Machine Learning Approaches

The main objective of this study is to compare the predictive accuracy of machine learning models, particularly Random Forest and Artificial Neural Networks, with classical statistical methods (such as Logistic Regression and Linear Discriminant Analysis) in forecasting the risk of Exchange-Traded F...

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Autores principales:	Nashmil Esmaily, Parviz Piri, Ali Ashtab, Mehdi Heydari, Akbar Zavari Rezaei
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Iran Finance Association 2025-12-01
Colección:	Iranian Journal of Finance
Materias:	machine learning random forest neural networks risk prediction exchange-traded funds
Acceso en línea:	https://www.ijfifsa.ir/article_230952_a4f71938e696705830a482e9d2283c53.pdf
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