Comparison of Machine Learning Methods in Prediction of Financial Failure of Businesses in The Manufacturing Industry: Evidence from Borsa İstanbul

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dc.contributor.authorAksoy, Barış
dc.contributor.authorBoztosun, Derviş
dc.date.accessioned2025-05-04T16:18:59Z
dc.date.available2025-05-04T16:18:59Z
dc.date.issued2020
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description.abstractIn this study, Artificial Neural Networks (NN), C5.0 Classification Algorithm, Classification and Regression Trees (CART) analyses were used to predict the financial success/failure of 126 businesses that are operating in the BIST (Borsa İstanbul) Manufacturing Industry Sector. The data contains the years 2006 to 2009. In the study, 25 quantitative variable and 4 qualitative variable were used. The overall classification accuracy from the highest to the lowest of 3 years prior to successful-failure year (for 2006) is 84.21% for CART, 81.58% for ANN and 76.32% for C5.0, respectively. The overall classification accuracy from the highest to the lowest of 2 years prior to successful-failure year (for 2007) is 86.84% for CART, 84.21% for ANN, 78.95% for C5.0, respectively. The overall classification accuracy from the highest to the lowest of 1 year prior to successful-failure year (for 2008) is 92.11% for CART, 92.11 for ANN and 86.84% for C5.0, respectively. ANN and CART models are notable in terms of their ability to predict upcoming financial failure of unsuccessful businesses with 100% classification accuracy from a year ago. The prediction of the financial success/failure by the three models obtained in the study more than one, two and three years ago shows that the models used in this study can be included in the model used by those concerned.
dc.description.abstract[No abstract available]
dc.identifier.doi10.18037/ausbd.845792
dc.identifier.doihttps://doi.org/10.18037/ausbd.845792
dc.identifier.endpage268
dc.identifier.issn2667-8683
dc.identifier.issue4
dc.identifier.startpage237
dc.identifier.urihttps://hdl.handle.net/20.500.12418/31223
dc.identifier.volume20
dc.language.isotr
dc.publisherAnadolu Üniversitesi
dc.relation.ispartofAnadolu Üniversitesi Sosyal Bilimler Dergisi
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_20250504
dc.subjectFinancial Failure Prediction
dc.subjectBorsa İstanbul
dc.subjectArtificial Neural Networks
dc.subjectC5.0 Decision Rule Algorithm
dc.subjectCART Classification and Regression Trees
dc.titleComparison of Machine Learning Methods in Prediction of Financial Failure of Businesses in The Manufacturing Industry: Evidence from Borsa İstanbul
dc.typeResearch Article

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