<efrbr:recordSet xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:efrbr="http://vfrbr.info/efrbr/1.1" xmlns:efrbr-work="http://vfrbr.info/efrbr/1.1/work" xmlns:efrbr-expression="http://vfrbr.info/efrbr/1.1/expression" xmlns:efrbr-manifestation="http://vfrbr.info/efrbr/1.1/manifestation" xmlns:efrbr-person="http://vfrbr.info/efrbr/1.1/person" xmlns:efrbr-corporateBody="http://vfrbr.info/efrbr/1.1/corporateBody" xmlns:efrbr-concept="http://vfrbr.info/efrbr/1.1/concept" xmlns:efrbr-structure="http://vfrbr.info/efrbr/1.1/structure" xmlns:efrbr-responsible="http://vfrbr.info/efrbr/1.1/responsible" xmlns:efrbr-subject="http://vfrbr.info/efrbr/1.1/subject" xmlns:efrbr-other="http://vfrbr.info/efrbr/1.1/other" xsi:schemaLocation="http://vfrbr.info/efrbr/1.1 http://vfrbr.info/schemas/1.1/efrbr.xsd"><efrbr:entities><efrbr-work:work identifier="http://purl.tuc.gr/dl/dias/2925D9C1-2E1F-44C5-A48B-1D7B1FAD12D2"><efrbr-work:titleOfTheWork>Bankruptcy prediction using auditor size and auditor opinion</efrbr-work:titleOfTheWork></efrbr-work:work><efrbr-expression:expression identifier="http://purl.tuc.gr/dl/dias/2925D9C1-2E1F-44C5-A48B-1D7B1FAD12D2"><efrbr-expression:titleOfTheExpression>Bankruptcy prediction using auditor size and auditor opinion</efrbr-expression:titleOfTheExpression><efrbr-expression:formOfExpression vocabulary="DIAS:TYPES">
            Peer-Reviewed Journal Publication
            Δημοσίευση σε Περιοδικό με Κριτές
         </efrbr-expression:formOfExpression><efrbr-expression:dateOfExpression type="issued">2015-11-05</efrbr-expression:dateOfExpression><efrbr-expression:dateOfExpression type="published">2010</efrbr-expression:dateOfExpression><efrbr-expression:languageOfExpression vocabulary="iso639-1">en</efrbr-expression:languageOfExpression><efrbr-expression:summarizationOfContent>In the present study, we investigate the explanatory power of information such as auditors' opinion and auditors' size in predicting impending bankruptcy for companies operating in the Greek market. Using nine financial ratios and two dummy variables, covering all dimensions of firms' financial performance, we initially develop two classification technique based models, Artificial Neural Networks (ANN) and Discriminant Analysis (DA). Our main purpose is to find out if the integration of the variables of audit opinion and auditor size in the initial models increases their ability in predicting impending bankruptcy. A comparison of the prediction accuracy of these two models before and after the integration of the additional informational variables is also included. The results indicate that both models achieve more satisfactory classification accuracy in discriminating bankrupted and non-bankrupted firms when the variables of audit opinion, auditors' are incorporated in the analysis compared to the use of financial ratios, only.</efrbr-expression:summarizationOfContent><efrbr-expression:useRestrictionsOnTheExpression type="creative-commons">http://creativecommons.org/licenses/by/4.0/</efrbr-expression:useRestrictionsOnTheExpression><efrbr-expression:note type="journal name">International Journal of Financial Services Management</efrbr-expression:note><efrbr-expression:note type="journal volume">4</efrbr-expression:note><efrbr-expression:note type="journal number">3</efrbr-expression:note><efrbr-expression:note type="page range">220-238</efrbr-expression:note></efrbr-expression:expression><efrbr-person:person identifier="http://viaf.org/viaf/314898779"><efrbr-person:nameOfPerson vocabulary="VIAF">
            Gaganis, Chrysovalantis
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            Pavlos Sochos
         </efrbr-person:nameOfPerson></efrbr-person:person><efrbr-person:person identifier="http://users.isc.tuc.gr/~kzopounidis"><efrbr-person:nameOfPerson vocabulary="TUC:LDAP">
            Zopounidis Konstantinos
            Ζοπουνιδης Κωνσταντινος
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            Inderscience
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            bankruptcy prediction
         </efrbr-concept:termForTheConcept></efrbr-concept:concept><efrbr-concept:concept identifier="AA0B7A98-4A07-4044-BFE5-471935AB96DE"><efrbr-concept:termForTheConcept>
             artificial neural networks
         </efrbr-concept:termForTheConcept></efrbr-concept:concept><efrbr-concept:concept identifier="B282F4F1-2526-47BE-BFAA-8BEAF3CD9D12"><efrbr-concept:termForTheConcept>
            discriminant analysis
         </efrbr-concept:termForTheConcept></efrbr-concept:concept><efrbr-concept:concept identifier="00177567-0AF3-4D1E-922F-4EB90C611902"><efrbr-concept:termForTheConcept>
            auditor opinion
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