dc.creator | Blanco Oliver, Antonio Jesús | es |
dc.creator | Irimia Diéguez, Ana Isabel | es |
dc.creator | Oliver Alfonso, María Dolores | es |
dc.creator | Vázquez Cueto, María José | es |
dc.date.accessioned | 2018-12-07T11:45:06Z | |
dc.date.available | 2018-12-07T11:45:06Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Blanco 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.issn | 1810-4967 | es |
dc.identifier.issn | 1812-9358 | es |
dc.identifier.uri | https://hdl.handle.net/11441/80840 | |
dc.description.abstract | Following 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.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | LLC “Consulting Publishing Company “Business Perspectives” | es |
dc.relation.ispartof | Investment Management and Financial Innovations, 13 (3), 35-46. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Bankruptcy models | es |
dc.subject | Combining forecasts | es |
dc.subject | Decision making | es |
dc.subject | Hybrid models | es |
dc.subject | Data mining | es |
dc.subject | Small firms | es |
dc.title | Hybrid model using logit and nonparametric methods for predicting micro-entity failure | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Economía Financiera y Dirección de Operaciones | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Economía Aplicada III | es |
dc.relation.publisherversion | https://businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/7616/imfi_en_2016_03_Blanco-Oliver.pdf | es |
idus.format.extent | 12 | es |
dc.journaltitle | Investment Management and Financial Innovations | es |
dc.publication.volumen | 13 | es |
dc.publication.issue | 3 | es |
dc.publication.initialPage | 35 | es |
dc.publication.endPage | 46 | es |