PROBABILISTIC PREDICTION OF BANK FAILURES WITH FINANCIAL RATIOS: AN EMPIRICAL STUDY ON TURKISH BANKS

Gamze Özel, Nihal Ata Tutkun

Abstract


Banking risk management has become more important during the last 20 years in response to a worldwide increase in the number of bank failures. Turkey has experienced a series of economic and financial crisis since the declaration of Republic and banking system has the most affected sector from the results of these crises. This paper examines some bank failure prediction models using financial ratios. Survival, ordinary and conditional logistic regression models are employed in order to develop these prediction models. The empirical results indicate that the bank is more likely to go bankrupt if it is unprofitable, small, highly leveraged, and has liquidity problems and less financial flexibility to invest itself. 


Keywords


Bank Failure, Conditional Logistic Regression, Cox Regression, Financial Ratio, Hazard, Ordinary Logistic Regression.

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DOI: http://dx.doi.org/10.18187/pjsor.v9i4.492

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Title

PROBABILISTIC PREDICTION OF BANK FAILURES WITH FINANCIAL RATIOS: AN EMPIRICAL STUDY ON TURKISH BANKS

Keywords

Bank Failure, Conditional Logistic Regression, Cox Regression, Financial Ratio, Hazard, Ordinary Logistic Regression.

Description

Banking risk management has become more important during the last 20 years in response to a worldwide increase in the number of bank failures. Turkey has experienced a series of economic and financial crisis since the declaration of Republic and banking system has the most affected sector from the results of these crises. This paper examines some bank failure prediction models using financial ratios. Survival, ordinary and conditional logistic regression models are employed in order to develop these prediction models. The empirical results indicate that the bank is more likely to go bankrupt if it is unprofitable, small, highly leveraged, and has liquidity problems and less financial flexibility to invest itself. 


Date

2014-02-06

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol. 9 No. 4, 2013



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810