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dc.contributor.authorKaras, Michal
dc.contributor.authorRežňáková, Mária
dc.date.accessioned2017-08-30T11:41:27Z
dc.date.available2017-08-30T11:41:27Z
dc.date.issued2017
dc.identifier.citationE+M. Ekonomie a Management = Economics and Management. 2017, č. 2, s. 116-133.cs
dc.identifier.issn2336-5604 (Online)
dc.identifier.issn1212-3609 (Print)
dc.identifier.urihttp://hdl.handle.net/11025/26266
dc.format18 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherTechnická univerzita v Libercics
dc.relation.ispartofseriesE+M. Ekonomie a Management = Economics and Managementcs
dc.rights© Technická univerzita v Libercics
dc.rightsCC BY-NC 4.0cs
dc.subjectfinanční poměrycs
dc.subjectmodely předvídání bankrotucs
dc.subjectčasově specifické prediktorycs
dc.subjectoborově specifické prediktorycs
dc.subjectvýrobacs
dc.subjectkonstrukcecs
dc.subjectboosted treescs
dc.titleThe stability of bankruptcy predictors in the construction and manufacturing industries at various times before bankruptcyen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedThis article focuses on the design of bankruptcy models, specifi cally the selection of suitable predictors. Previous research has drawn mainly on data concerning manufacturing companies one year before bankruptcy. Our research examines fi nancial ratios that are suitable bankruptcy indicators in two different industries (the construction and manufacturing industries) over a period of fi ve years prior to bankruptcy. Our main objective is to verify whether bankruptcy predictors are industry-specifi c. Another objective was to determine which indicators can detect signs of bankruptcy earlier than one period before bankruptcy. We presume that the application of industryspecifi c indicators can help increase the predictive accuracy of bankruptcy models when applied to a particular industry. Per analogiam, we assume that the inclusion of indicators capable of detecting signs of bankruptcy more than a year before its occurrence will increase their predictive capacity. Signifi cant predictors were fi rst identifi ed on a linear basis using the parametric t-test or F-test; for the sake of comparison, a non-linear non-parametric Boosted Trees method was also applied. Data for a total of 34,229 active companies and 304 companies that went bankrupt during the relevant period was analyzed. The research confi rmed our presumption that bankruptcy predictors are both industry and time specifi c. Four years before bankruptcy, the indicators return on assets, inventory turnover and asset structure are important predictors in both the manufacturing and construction industries. The net working capital to total assets ratio is a specifi c predictor for manufacturing companies in the third year before bankruptcy, as is the short-term indebtedness indicator. In the construction industry, specifi c predictors are the net working capital to sales ratio in the third and fi rst years before bankruptcy, and the interest coverage indicator in all four years preceding bankruptcy. Were these indicators to be included in a model for an alternative industry, they would be likely to reduce its accuracy.en
dc.subject.translatedfinancial ratiosen
dc.subject.translatedbankruptcy prediction modelsen
dc.subject.translatedtime-specifi c predictorsen
dc.subject.translatedbranch-specific predictorsen
dc.subject.translatedmanufacturingen
dc.subject.translatedconstructionen
dc.subject.translatedboosted treesen
dc.identifier.doi10.15240/tul/001/2017-2-009
dc.type.statusPeer-revieweden
Appears in Collections:Číslo 2 (2017)
Číslo 2 (2017)

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