Industry Specific Financial Distress Modeling

dc.contributor.author Sayari, Naz
dc.contributor.author Simga-Mugan, Can
dc.date.accessioned 2023-06-16T12:58:58Z
dc.date.available 2023-06-16T12:58:58Z
dc.date.issued 2017
dc.description.abstract This study investigates uncertainty levels of various industries and tries to determine financial ratios having the greatest information content in determining the set of industry characteristics. It then uses these ratios to develop industry specific financial distress models. First, we employ factor analysis to determine the set of ratios that are most informative in specified industries. Second, we use a method based on the concept of entropy to measure the level of uncertainty in industries and also to single out the ratios that best reflect the uncertainty levels in specific industries. Finally, we conduct a logistic regression analysis and derive industry specific financial distress models which can be used to judge the predictive ability of selected financial ratios for each industry. The results show that financial ratios do indeed echo industry characteristics and that information content of specific ratios varies among different industries. Our findings show diverging impact of industry characteristics on companies; and thus the necessity of constructing industry specific financial distress models. (C) 2016 ACEDE. Published by Elsevier Espana, S.L.U. en_US
dc.description.sponsorship Scientific and Technological Research Council of Turkey (TUBITAK) [B.14.2.TBT.0.06.01-219115543] en_US
dc.description.sponsorship The authors would like to thank Umit Akinc (Professor at WFU) and Carol Cain (Professor at WFU) for providing language help and writing assistance. This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under grant no: B.14.2.TBT.0.06.01-219115543. en_US
dc.identifier.doi 10.1016/j.brq.2016.03.003
dc.identifier.issn 2340-9436
dc.identifier.issn 2340-9444
dc.identifier.scopus 2-s2.0-84975498806
dc.identifier.uri https://doi.org/10.1016/j.brq.2016.03.003
dc.identifier.uri https://hdl.handle.net/20.500.14365/1088
dc.language.iso en en_US
dc.publisher Sage Publications Inc en_US
dc.relation.ispartof Brq-Busıness Research Quarterly en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Uncertainty en_US
dc.subject Information theory en_US
dc.subject Financial ratios en_US
dc.subject Financial distress modeling en_US
dc.subject Prediction en_US
dc.subject Ratios en_US
dc.subject Regression en_US
dc.subject Stability en_US
dc.subject Entropy en_US
dc.title Industry Specific Financial Distress Modeling en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Mugan, Can F N Simga/0000-0001-9745-7899
gdc.author.id Simga Mugan, Can/0000-0002-0358-8992
gdc.author.scopusid 57189874019
gdc.author.scopusid 7801371051
gdc.author.wosid Simga-Mugan, Can/GXA-3133-2022
gdc.author.wosid Mugan, Can F N Simga/B-6043-2011
gdc.author.wosid Simga Mugan, Can/F-9321-2013
gdc.bip.impulseclass C4
gdc.bip.influenceclass C4
gdc.bip.popularityclass C4
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department İzmir Ekonomi Üniversitesi en_US
gdc.description.departmenttemp [Sayari, Naz] Wake Forest Univ, Sch Business, 1836 Wake Forest Rd, Winston Salem, NC 27106 USA; [Simga-Mugan, Can] Izmir Univ Econ, Fac Business, Sakarya Caddesi 156, TR-35330 Izmir, Turkey en_US
gdc.description.endpage 62 en_US
gdc.description.issue 1 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.startpage 45 en_US
gdc.description.volume 20 en_US
gdc.description.wosquality Q2
gdc.identifier.openalex W2395589879
gdc.identifier.wos WOS:000394560400005
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gdc.oaire.downloads 0
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gdc.oaire.keywords Financial ratios
gdc.oaire.keywords Information theory
gdc.oaire.keywords ddc:650
gdc.oaire.keywords Uncertainty
gdc.oaire.keywords Financial distress modeling
gdc.oaire.popularity 1.743025E-8
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gdc.oaire.sciencefields 0502 economics and business
gdc.oaire.sciencefields 05 social sciences
gdc.oaire.views 6
gdc.openalex.collaboration International
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gdc.openalex.toppercent TOP 1%
gdc.opencitations.count 34
gdc.plumx.crossrefcites 1
gdc.plumx.mendeley 471
gdc.plumx.scopuscites 49
gdc.scopus.citedcount 49
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