Comparison of financial distress prediction models: Evidence from Turkey

dc.authorscopusid 55346693000
dc.authorscopusid 55346515200
dc.authorscopusid 55345766200
dc.contributor.author Terzi,S.
dc.contributor.author Sen,I.K.
dc.contributor.author Ucoglu,D.
dc.date.accessioned 2024-10-15T20:22:25Z
dc.date.available 2024-10-15T20:22:25Z
dc.date.issued 2012
dc.department Okan University en_US
dc.department-temp Terzi S., Cankiri Karatekin University, Cankiri, Turkey; Sen I.K., Okan University, Istanbul, Turkey; Ucoglu D., Istanbul Bilgi University, Istanbul, Turkey en_US
dc.description.abstract The purpose of this paper is to explore the differences and similarities between financial distress prediction (FDP) models and to determine which explanatory variables and methodologies are the most effective in prediction of financial distress. For this purpose, 167 manufacturing companies (full sample) listed in Istanbul Stock Exchange (ISE) were used. In total, 27 financial ratios were identified from previous literature studies as potentially significant and they were calculated for the years 2009 and 2010. In the study, logistic regression, artificial neural networks and decision tree methods, which are frequently used in the literature, have been employed. As a result, many of the financial ratios are found to be effective in predicting financial distress. Moreover, logistic regression and artificial neural network methods have indicated better prediction accuracy results of financial distress for classification of companies. © EuroJournals Publishing, Inc. 2012. en_US
dc.identifier.citationcount 0
dc.identifier.endpage 618 en_US
dc.identifier.issn 1450-2267
dc.identifier.issue 4 en_US
dc.identifier.scopus 2-s2.0-84865446985
dc.identifier.startpage 607 en_US
dc.identifier.uri https://hdl.handle.net/20.500.14517/6748
dc.identifier.volume 32 en_US
dc.language.iso en
dc.relation.ispartof European Journal of Social Sciences en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 0
dc.subject Artificial neural networks en_US
dc.subject Decision trees en_US
dc.subject Financial distress en_US
dc.subject Financial ratios en_US
dc.subject Logistic regression en_US
dc.title Comparison of financial distress prediction models: Evidence from Turkey en_US
dc.type Article en_US

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