Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7302
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dc.contributor.authorÖgüt, Hulisi-
dc.contributor.authorDoğanay, M. Mete-
dc.contributor.authorCeylan, Nildağ Başak-
dc.contributor.authorAktaş, Ramazan-
dc.date.accessioned2021-09-11T15:56:20Z-
dc.date.available2021-09-11T15:56:20Z-
dc.date.issued2012en_US
dc.identifier.issn0264-9993-
dc.identifier.urihttps://doi.org/10.1016/j.econmod.2012.01.010-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/7302-
dc.description.abstractBank financial strength ratings have gained widespread popularity especially after the recent financial turmoil. Rating agencies were criticized because of their ratings and failure to predict the bankruptcy of the banks. Based on this observation, we investigate whether the forecast of the rating of bank's financial strength using publicly available data is consistent with those of the credit rating agency. We use the data of Turkish banks for this investigation. We take a country-specific approach because previous studies found that proxies used for environmental factors (political, economic, and financial risk of the country) did not have any explanatory power and it is hard to find international data for other important factors such as franchise value, concentration, and efficiency. We use two popular multivariate statistical techniques (multiple discriminant analysis and ordered logistic regression) to estimate a suitable model and we compare their performances with those of two mostly used data mining techniques (Support Vector Machine and Artificial Neural Network). Our results suggest that our predictions are consistent with those of Moody's financial strength rating in general.. The important factors in rating are found to be profitability (measured by return on equity), efficient use of resources, and funding the businesses and the households instead of the government that shows efficient placement of the funds. (C) 2012 Elsevier B.V. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherElsevier Science Bven_US
dc.relation.ispartofEconomic Modellingen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectRating agenciesen_US
dc.subjectBank financial strength ratingen_US
dc.subjectFinancial and operational ratiosen_US
dc.subjectRating predictionen_US
dc.subjectMultivariate statistical modelen_US
dc.subjectData mining techniqueen_US
dc.titlePrediction of Bank Financial Strength Ratings: the Case of Turkeyen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Economics and Administrative Sciences, Department of Managementen_US
dc.departmentFakülteler, İktisadi ve İdari Bilimler Fakültesi, İşletme Bölümütr_TR
dc.identifier.volume29en_US
dc.identifier.issue3en_US
dc.identifier.startpage632en_US
dc.identifier.endpage640en_US
dc.identifier.wosWOS:000303073700011en_US
dc.identifier.scopus2-s2.0-84858744806en_US
dc.institutionauthorAktaş, Ramazan-
dc.identifier.doi10.1016/j.econmod.2012.01.010-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept04.03. Department of Management-
Appears in Collections:İşletme Bölümü / Department of Management
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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