A Theoretical Approach To Financial Distress Prediction Modeling

dc.contributor.author Oz, Ibrahim Onur
dc.contributor.author Yelkenci, Tezer
dc.date.accessioned 2023-06-16T14:25:18Z
dc.date.available 2023-06-16T14:25:18Z
dc.date.issued 2017
dc.description.abstract Purpose - The purpose of this paper is to examine a theoretical base for the financial distress prediction modeling over eight countries for a sample of 2,500 publicly listed non-financial firms for the period from 2000 to 2014. Design/methodology/approach - The prediction model derived through the theory has the potential to produce prediction results that are generalizable over distinct industry and country samples. For this reason, the prediction model is on the earnings components, and it uses two different estimation methods and four sub-samples to examine the validity of the results. Findings - The findings suggest that the theoretical model provides high-level prediction accuracy through its earnings components. The use of a large sample from different industries in distinct countries increases the validity of the prediction results, and contributes to the generalizability of the predictionmodel in distinct sectors. Originality/value - The results of the study fulfill the gap and extend the literature through a distress model, which has the theoretical origin enabling the generalization of the prediction results over different samples and estimation methods. en_US
dc.identifier.doi 10.1108/MF-03-2016-0084
dc.identifier.issn 0307-4358
dc.identifier.issn 1758-7743
dc.identifier.scopus 2-s2.0-85011695836
dc.identifier.uri https://doi.org/10.1108/MF-03-2016-0084
dc.identifier.uri https://hdl.handle.net/20.500.14365/1916
dc.language.iso en en_US
dc.publisher Emerald Group Publishing Ltd en_US
dc.relation.ispartof Managerıal Fınance en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Accounting theory en_US
dc.subject Modelling en_US
dc.subject Financial distress en_US
dc.subject Generalizability en_US
dc.subject Bankruptcy Prediction en_US
dc.subject Discriminant-Analysis en_US
dc.subject Neural-Networks en_US
dc.subject Credit Risk en_US
dc.subject Cash Flows en_US
dc.subject Failure en_US
dc.subject Ratios en_US
dc.subject Information en_US
dc.subject Accruals en_US
dc.subject Firms en_US
dc.title A Theoretical Approach To Financial Distress Prediction Modeling en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Oz, Ibrahim Onur/0000-0001-8699-1770
gdc.author.scopusid 56455145900
gdc.author.scopusid 56455368000
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gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department İzmir Ekonomi Üniversitesi en_US
gdc.description.departmenttemp [Oz, Ibrahim Onur] Univ Hartford, Accounting & Taxat Dept, Hartford, CT 06117 USA; [Yelkenci, Tezer] Izmir Econ Univ, Izmir, Turkey en_US
gdc.description.endpage 230 en_US
gdc.description.issue 2 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q2
gdc.description.startpage 212 en_US
gdc.description.volume 43 en_US
gdc.description.wosquality Q2
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gdc.oaire.sciencefields 0502 economics and business
gdc.oaire.sciencefields 05 social sciences
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gdc.opencitations.count 11
gdc.plumx.crossrefcites 11
gdc.plumx.mendeley 206
gdc.plumx.scopuscites 18
gdc.scopus.citedcount 18
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