PREDICTING FINANCIAL FAILURE: EMPIRICAL EVIDENCE FROM PUBLICLY-QUOTED FIRMS IN DEVELOPED AND DEVELOPING COUNTRIES

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dc.contributor.authorGul, Yavuz
dc.contributor.authorAltinirmak, Serpil
dc.date.accessioned2026-01-31T15:09:03Z
dc.date.available2026-01-31T15:09:03Z
dc.date.issued2025
dc.departmentİstanbul Beykent Üniversitesi
dc.description.abstractThis paper analyzes the data of 570 firms from developed and developing countries between 2010 and 2019 in an attempt to create high-accuracy financial failure prediction models. In this sense, we utilize three different methods, namely logistic regression (LR), artificial neural networks (ANN), and decision trees (DT), Aand compare the classification accuracy performances of these techniques. Using 16 financial ratios as independent variables, ANN is able to generate the most accurate prediction and outperforms the other methods in predicting failure. Otherwise said, ANN yields a correct classification accuracy of 98.1% one year prior to failure while LR and DT achieve accuracy rates of 94.7% and 96.1%, respectively. Furthermore, the empirical results demonstrate that the classification accuracy rate reaches 92.5% by ANN, 91.1% by DT, and 84.4% by logistic regression two years in advance. The findings of current research provide valuable insights into financial failure prediction and may entice practical implications for stakeholders, especially investors and regulatory bodies, by indicating that the use of the ANN approach mayAbe more effective.
dc.identifier.doi10.30784/epfad.1595915
dc.identifier.endpage126
dc.identifier.issn2587-151X
dc.identifier.issue1
dc.identifier.startpage107
dc.identifier.trdizinid1306795
dc.identifier.urihttps://doi.org./10.30784/epfad.1595915
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1306795
dc.identifier.urihttps://hdl.handle.net/20.500.12662/10800
dc.identifier.volume10
dc.identifier.wosWOS:001476105900006
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.publisherEconomic And Financial Research Assoc - Efad
dc.relation.ispartofEkonomi Politika & Finans Arastirmalari Dergisi
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20260128
dc.subjectFinancial Failure
dc.subjectLogistic Regression
dc.subjectArtificial Neural Networks
dc.subjectDecision Trees
dc.subjectTrees
dc.titlePREDICTING FINANCIAL FAILURE: EMPIRICAL EVIDENCE FROM PUBLICLY-QUOTED FIRMS IN DEVELOPED AND DEVELOPING COUNTRIES
dc.typeArticle

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