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dc.creatorBlanco Oliver, Antonio Jesúses
dc.creatorIrimia Diéguez, Ana Isabeles
dc.creatorOliver Alfonso, María Doloreses
dc.creatorVázquez Cueto, María Josées
dc.date.accessioned2018-12-07T11:45:06Z
dc.date.available2018-12-07T11:45:06Z
dc.date.issued2016
dc.identifier.citationBlanco Oliver, A.J., Irimia Diéguez, A.I., Oliver Alfonso, M.D. y Vázquez Cueto, M.J. (2016). Hybrid model using logit and nonparametric methods for predicting micro-entity failure. Investment Management and Financial Innovations, 13 (3), 35-46.
dc.identifier.issn1810-4967es
dc.identifier.issn1812-9358es
dc.identifier.urihttps://hdl.handle.net/11441/80840
dc.description.abstractFollowing the calls from literature on bankruptcy, a parsimonious hybrid bankruptcy model is developed in this paper by combining parametric and non-parametric approaches.To this end, the variables with the highest predictive power to detect bankruptcy are selected using logistic regression (LR). Subsequently, alternative non-parametric methods (Multilayer Perceptron, Rough Set, and Classification-Regression Trees) are applied, in turn, to firms classified as either “bankrupt” or “not bankrupt”. Our findings show that hybrid models, particularly those combining LR and Multilayer Perceptron, offer better accuracy performance and interpretability and converge faster than each method implemented in isolation. Moreover, the authors demonstrate that the introduction of non-financial and macroeconomic variables complement financial ratios for bankruptcy prediction.es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherLLC “Consulting Publishing Company “Business Perspectives”es
dc.relation.ispartofInvestment Management and Financial Innovations, 13 (3), 35-46.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBankruptcy modelses
dc.subjectCombining forecastses
dc.subjectDecision makinges
dc.subjectHybrid modelses
dc.subjectData mininges
dc.subjectSmall firmses
dc.titleHybrid model using logit and nonparametric methods for predicting micro-entity failurees
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Economía Financiera y Dirección de Operacioneses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Economía Aplicada IIIes
dc.relation.publisherversionhttps://businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/7616/imfi_en_2016_03_Blanco-Oliver.pdfes
idus.format.extent12es
dc.journaltitleInvestment Management and Financial Innovationses
dc.publication.volumen13es
dc.publication.issue3es
dc.publication.initialPage35es
dc.publication.endPage46es

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