A New Bankruptcy Forecast Modelling For Energy Companies
dc.authorid | 302688 | en_US |
dc.contributor.author | Özparlak, Gerçek | |
dc.date.accessioned | 2023-02-02T08:30:57Z | |
dc.date.available | 2023-02-02T08:30:57Z | |
dc.date.issued | 2022 | |
dc.department | İstanbul Beykent Üniversitesi | en_US |
dc.description.abstract | Due to the Covid-19 epidemic, there was a significant increase in company bankruptcies in 2020. In this period, especially the energy sector has been one area where bankruptcies are the most seen. In this context, this study aims to build a model that can predict financially unsuccessful companies that have declared bankruptcy and successful companies operating in the energy sector in the U.S.A. For the study sample, 30 financial ratios of 23 energy companies that declared bankruptcy in the U.S.A. in 2020 and 30 financial ratios of 23 energy companies that were financially successful in the same period were selected. The multiple discriminant analysis (M.D.A.) was chosen to differentiate between the groups. According to the research results, the accuracy rate of the created function was found to be 87.0%. According to the sensitivity and specificity (R.O.C.) results, the performance of the model was found to be strong for distinguish differ between bankrupted and non-bankrupted companies. | en_US |
dc.identifier.doi | 10.11611/yead.1100824 | |
dc.identifier.issn | 2619-9718 | |
dc.identifier.trdizinid | 1133012 | en_US |
dc.identifier.uri | https://search.trdizin.gov.tr/yayin/detay/1133012 | |
dc.identifier.uri | https://doi.org/10.11611/yead.1100824 | |
dc.indekslendigikaynak | TR-Dizin | en_US |
dc.language.iso | en | en_US |
dc.publisher | Bandırma Onyedi Eylül Üniversitesi | en_US |
dc.relation.publicationcategory | Makale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.subject | Financial Failure | en_US |
dc.subject | Bankruptcies | en_US |
dc.subject | Financial Modelling | en_US |
dc.subject | Multiple Discriminant Analysis | en_US |
dc.title | A New Bankruptcy Forecast Modelling For Energy Companies | en_US |
dc.type | Article | en_US |
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