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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Bibliografiske detaljer

Principais autores:	Nashmil Esmaily, Parviz Piri, Ali Ashtab, Mehdi Heydari, Akbar Zavari Rezaei
Format:	Artigo
Sprog:	Inglês
Udgivet:	Iran Finance Association 2025-12-01
Serier:	Iranian Journal of Finance
Fag:	machine learning random forest neural networks risk prediction exchange-traded funds
Online adgang:	https://www.ijfifsa.ir/article_230952_a4f71938e696705830a482e9d2283c53.pdf
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