Machine Learning Approaches on the Bankruptcy Modeling: Altman z-score, Neural Net, and CatBoost Classifier models - Couverture souple

Yazici, Murat

 
9789999319331: Machine Learning Approaches on the Bankruptcy Modeling: Altman z-score, Neural Net, and CatBoost Classifier models
Couverture souple
ISBN 10 : 9999319335 ISBN 13 : 9789999319331
Editeur : Eliva Press, 2024

Synopsis

This study includes Machine Learning (ML) approaches on the bankruptcy modeling. The Altman z-score model was selected as the subject of the study due to its widespread usage and extensive scientific validation, as well as its reputation as one of the most reliable tools for predicting bankruptcy. Typically, z-score models are evaluated in concert with other models or metrics. The Altman z-score remains a popular tool amongst investors, accountants, and stakeholders due to its versatility in application. The z-score model is especially useful due to its ease of use, compared to other predictive models. The models chosen for this study provided clear results for predicting a company’s financial stability in two regions as bankrupt and non-bankrupt, making it easy to compare between companies.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Éditeur
Eliva Press
Date d'édition
2024
Langue
anglais
ISBN 10 
9999319335
ISBN 13 
9789999319331
Reliure
Broché
Nombre de pages
41
Coordonnées du fabricant
non disponible
Personne responsable
GPSR Kontakt
gpsr@libri.de

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