Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering

The emergence of big data, information technology, and social media provides an enormous amount of information about firms’ current financial health. When facing this abundance of data, decision makers must identify the crucial information to build upon an effective and operative prediction model wi...

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Bibliographic Details
Published in:	Computational economics Vol. 61; no. 2; pp. 715 - 741
Main Authors:	Ben Jabeur, Sami, Stef, Nicolae, Carmona, Pedro
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.02.2023 Springer Springer Nature B.V Springer Verlag
Subjects:	Algorithms Bankruptcy Behavioral/Experimental Economics Big Data Classification Computer Appl. in Social and Behavioral Sciences Data mining Decision makers Discriminant analysis Economic Theory/Quantitative Economics/Mathematical Methods Economics Economics and Finance Feature selection Humanities and Social Sciences Information technology Machine learning Math Applications in Computer Science Medical decision making Operations Research/Decision Theory Prediction models Predictions Social media Specification Corporate failure XGBoost Bankruptcy Machine learning Apprentissage automatique Défaillance d'entreprise Faillite
ISSN:	0927-7099, 1572-9974
Online Access:	Get full text
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