Financial distress prediction using support vector machines and logistic regression

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dc.authorid0000-0001-7835-7905en_US
dc.contributor.authorDoğan, Seyyide
dc.contributor.authorKoçak, Deniz
dc.contributor.authorAtan, Murat
dc.date.accessioned2022-02-15T06:46:35Z
dc.date.available2022-02-15T06:46:35Z
dc.date.issued2022en_US
dc.departmentKMÜ, İktisadi ve İdari Bilimler Fakültesi, Uluslararası Ticaret ve İşletmecilik Bölümüen_US
dc.description.abstractFinancial distress and bankruptcies are highly costly and devastating processes for all parts of the economy. Prediction of distress is notable both for the functioning of the general economy and for the firm’s partners, investors, and lenders at the micro-level. This study aims to develop an effective prediction model with Support Vector Machine and Logistic Regression Analysis. As the field of the study, 172 firms that are traded in Borsa İstanbul, have been chosen. Besides, two basic prediction methods, LRA was also used as a feature selection method and the results of this model were compared. The empirical results show us, both methods achieve a good prediction model. However, the SVM model in which the feature selection phase is applied shows the best performance.en_US
dc.identifier.citationDoğan, S., Koçak, D., & Atan, M. (2022). Financial distress prediction using support vector machines and logistic regression. Contributions to Economics. 429-452.doi:10.1007/978-3-030-85254-2_26en_US
dc.identifier.doi10.1007/978-3-030-85254-2_26
dc.identifier.issn1431-1933
dc.identifier.issue429en_US
dc.identifier.scopus2-s2.0-85123407160
dc.identifier.scopusqualityQ4
dc.identifier.startpage452en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-030-85254-2_26
dc.identifier.urihttps://hdl.handle.net/11492/5965
dc.indekslendigikaynakScopus
dc.institutionauthorDoğan, Seyyide
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.journalContributions to Economicsen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFinancial Distressen_US
dc.subjectLogistic Regression Analysisen_US
dc.subjectSupport Vector Machineen_US
dc.titleFinancial distress prediction using support vector machines and logistic regressionen_US
dc.typeBook Part

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