Modeling company failure: a longitudinal study of Turkish banks


İLK DAĞ Ö., Pekkurnaz D., ÇİNKO M.

OPTIMIZATION, vol.63, no.12, pp.1837-1849, 2014 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 63 Issue: 12
  • Publication Date: 2014
  • Doi Number: 10.1080/02331934.2013.855762
  • Journal Name: OPTIMIZATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1837-1849
  • Middle East Technical University Affiliated: Yes

Abstract

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.