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Modeling company failure: a longitudinal study of Turkish banks
Date
2014-01-01
Author
İlk Dağ, Özlem
Pekkurnaz, Didem
ÇİNKO, MURAT
Metadata
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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