Prediction of corporate financial distress in an emerging market: The case of Turkey

Basit Öğe Kaydı
dc.authorscopusid35777085800
dc.authorscopusid57191048889
dc.contributor.authorUğurlu, M.
dc.contributor.authorAksoy, H.
dc.date.accessioned2024-07-18T20:17:02Z
dc.date.available2024-07-18T20:17:02Z
dc.date.issued2006
dc.description.abstractPurpose – To identify predictors of corporate financial distress, using the discriminant and logit models, in an emerging market over a period of economic turbulence and to reveal the comparative predictive and classification accuracies of the models in this different environmental setting. Design/methodology/approach – The research relies on a sample of 27 failed and 27 non-failed manufacturing firms listed in the Istanbul Stock Exchange over the 1996-2003 period, which includes a period of high economic growth (1996-1999) followed by an economic crisis period (2000-2002). The two well-known methods, discriminant analysis and logit, are compared on the basis of a better overall fit and a higher percentage of correct classification under changing economic conditions. Furthermore, this research attempts to reveal the changes, if any, in the bankruptcy predictors, from those found in the earlier studies that rested on the data from the developed markets. Findings – The logistic regression model is found to have higher classification power and predictive accuracy, over the four years prior to bankruptcy, than the discriminant model. In this research, the discriminant and logit models identify the same number of significant predictors out of the total variables analyzed, and six of these are common in both. EBITDA/total assets is the most important predictor of financial distress in both models. The logit model identifies operating profit margin and the proportion of trade credit within total claims ratios as the second and third most important predictors, respectively. Originality/value – This paper reveals the accuracy with which the discriminant and logit models work in an emerging market over a period when firms face high uncertainty and turbulence. This study may be extended to other emerging markets to eliminate the limitation of the small sample size in this study and to further validate the use of these models in the developing countries. This can serve to make the methods important decision tools for managers and investors in these volatile markets. © 2006, Emerald Group Publishing Limiteden_US
dc.identifier.doi10.1108/13527600610713396
dc.identifier.endpage295en_US
dc.identifier.issn1352-7606
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-84986091968en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage277en_US
dc.identifier.urihttps://doi.org/10.1108/13527600610713396
dc.identifier.urihttps://hdl.handle.net/11411/6379
dc.identifier.volume13en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofCross Cultural Management: An International Journalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFinancial Performanceen_US
dc.subjectModellingen_US
dc.subjectPredictive Processen_US
dc.subjectTurkeyen_US
dc.titlePrediction of corporate financial distress in an emerging market: The case of Turkey
dc.typeArticle

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