The ability of Altman's Z"-score model to detect the economic distress of Kazakh banks.

Salina, Aigul P.; Zhang, Xin; Jiao, Tong; Hassan, Omaima A.G.

Abstract

This study contributes to the literature by evaluating the ability of Altman's Z"-score model to predict the economic distress of twelve Kazakh banks over the period of 2008 to 2014. The original Z"-score model, with a cut-off point implied by Altman (2005), produces a prediction accuracy ratio of 44.05% and correctly classifies 76.19% of the observations originally assigned to the economically distressed group. The study then re-estimates the model using three approaches, namely: the "leave-one-out", Direct and Wilk's methods, and identifies new, optimal cut-off points for the re-estimated models. The re-estimated models, together with the new, optimal cut-off points, improve the prediction accuracy ratio to 70% and correctly classifies over 90% of the observations originally assigned to the economically distressed group. The results imply that the Kazakh banking regulators and other market participants could use the Altman's Z"-score model to detect economically distressed banks.

Citation

SALINA, A.P., ZHANG, X., JIAO, T. and HASSAN, O.A.G. 2023. The ability of Altman's Z"-score model to detect the economic distress of Kazakh banks. In Boubaker, S. and Elnahass, M. (eds.) Banking resilience and global financial stability. London: World Scientific [online], chapter 13 . Available from: https://doi.org/10.1142/q0422

• Online Publication Date: Feb 9, 2023
• Publication Date: Dec 31, 2023
• Deposit Date: Apr 12, 2023
• Publicly Available Date: Feb 10, 2024
• Publisher: World Scientific Publishing
• Pages: 347-373
• Series Title: Transformations in banking, finance and regulation
• Series ISSN: 2752-5821; 2752-583X
• Book Title: Banking resilience and global financial stability
• Chapter Number: Chapter 13
• ISBN: 9781800614314
• DOI: https://doi.org/10.1142/9781800614321_0013
• Keywords: Altman's Z"-score model; Banks; Bank collapses; Bank failures; Financial distress; Economic distress; Emerging markets; Kazakhstan
• Public URL: https://rgu-repository.worktribe.com/output/1937963
• Contract Date: Mar 10, 2023