Modeling company failure: a longitudinal study of Turkish banks

Date

2014-01-01

Author

İlk Dağ, Özlem
ÇİNKO, MURAT

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Determining the factors related to the financial failure of a company is important. In this paper, we extend literature on bank failure prediction by modelling bank failures in Turkey from 1998 to 2000 using three statistical models combined with a principal component analysis on financial ratios. The three statistical models employed are a logistic regression, a logistic regression that takes serial correlation into account via generalized estimating equations and a marginalized transition model (MTM). Time and financial ratios that are related with capital adequacy and profitability, risk, non-interest income and Fx assets to Fx liabilities are found to be significant in classifying failed banks. Each of our methods achieves a correct classification rate of 93.3%. Among the three models, MTM, which is the soundest model in terms of statistical assumptions, shows slightly better model fit properties.

Subject Keywords

Uncertainty modelling, Regression, Financial ratios, Hierarchical models, Panel data

URI

https://hdl.handle.net/11511/43962

Journal

OPTIMIZATION

DOI

https://doi.org/10.1080/02331934.2013.855762

Collections

Department of Statistics, Article

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Citation Formats

Ö. İlk Dağ and M. ÇİNKO, “Modeling company failure: a longitudinal study of Turkish banks,” OPTIMIZATION, pp. 1837–1849, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/43962.