Modeling company failure: a longitudinal study of Turkish banks

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. T...

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Bibliographic Details
Published in:Optimization 2014-12, Vol.63 (12), p.1837-1849
Main Authors: Ilk, Ozlem, Pekkurnaz, Didem, Cinko, Murat
Format: Article
Language:English
Subjects:
6207
Bank assets
Bank failures
Bank liabilities
Banks
Classification
Failure
Failure analysis
Financial ratios
hierarchical models
Logistics
Mathematical models
panel data
Principal components analysis
Regression
Statistical analysis
Studies
uncertainty modelling
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Summary: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.
ISSN:0233-1934
1029-4945
DOI:10.1080/02331934.2013.855762