THE ACCURACY OF FINANCIAL DISTRESS PREDICTION MODELS IN TURKEY: A COMPARATIVE INVESTIGATION WITH SIMPLE MODEL PROPOSALS

Erol Muzir and Nazan Caglar ()
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Nazan Caglar: Yildiz Teknik University

Anadolu University Journal of Social Sciences, 2009, vol. 9, issue 2, 15-48

Abstract: This study aims to test eight well-known and widely used financial distress prediction models and to compare their performance in Turkey for the first year prior to failure. The comparison is enriched with the details of four new and simple model proposals, namely Failure Score (F-Score) Models, developed using four statistical techniques. The results show that none of the existing models could achieve satisfactorily high correct- classification rates over 90 %. Ohlson’s O-Score Model seems to be superior to other existing models and has the highest rate of correct classification, 81,6 %. However, our new model proposal based on logistic regression outperforms the O-Score model in terms of the overall accuracy t-value and may be viewed as an equally worthy model for predicting bankruptcy.

Keywords: Corporate failure; financial distress prediction; failure risk assessment; discriminant analysis; binary logistic regression; probit analysis; one-zero linear regression. (search for similar items in EconPapers)
JEL-codes: G32 G33 (search for similar items in EconPapers)
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:and:journl:v:9:y:2009:i:2:p:15-48

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