Predicting financial crises: an evaluation of machine learning algorithms and model explainability for early warning systems

This paper addresses the critical challenge of detecting financial crises in their early stages given their profound economic and societal consequences. It investigates the efficacy of machine learning models by comparing the standard econometric model of Logistic Regression with k-nearest Neighbour...

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Vydané v:	Review of evolutionary political economy (Online) Ročník 5; číslo 1; s. 51 - 83
Hlavný autor:	Reimann, Chris
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cham Springer International Publishing 01.06.2024
Predmet:	Economics Economics and Finance Institutional/Evolutionary Economics International Political Economy Original Paper Political Economy/Economic Systems C53 C63 C45 Machine learning Model explainability Financial stability G01 G17 Early warning systems
ISSN:	2662-6136, 2662-6144
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