Analysis of Economic Environment Incidence in Genetic Programming-Evolved Multiperiod Bankruptcy Prediction Models
| UDC.coleccion | Investigación | |
| UDC.departamento | Ciencias da Computación e Tecnoloxías da Información | |
| UDC.grupoInv | Information Retrieval Lab (IRlab) | |
| UDC.institutoCentro | CITIC - Centro de Investigación de Tecnoloxías da Información e da Comunicación | |
| UDC.issue | 1 | |
| UDC.journalTitle | Intelligent Systems in Accounting, Finance and Management | |
| UDC.startPage | e70034 | |
| UDC.volume | 33 | |
| dc.contributor.author | Beade, Angel | |
| dc.contributor.author | Santos Reyes, José | |
| dc.contributor.author | Rodríguez López, Manuel | |
| dc.date.accessioned | 2026-07-06T11:34:10Z | |
| dc.date.available | 2026-07-06T11:34:10Z | |
| dc.date.issued | 2026-03 | |
| dc.description.abstract | [Abstract]: Genetic programming (GP) is used to obtain multiperiod bankruptcy prediction models, as well as to perform a prior featureselection process for these models. Given the controversy in the field of bankruptcy prediction about the need to include (or not)variables from the economic environment as input information for the prediction models, an analysis is carried out to checkwhether the impact that the economic environment undoubtedly has on the firms can be captured using only the financialvariables of the firm as explanatory variables. To this end, the analysis includes a study of the correlation between the estimatesof the prediction models and certain economic indicators. The results confirm the possibility of capturing the evolution of theeconomic environment using only financial information as input, as strong correlations are shown between the predictions of themodels and important economic indicators over a very long postlearning period (2008–2020) and varied in terms of the economicenvironment (crisis, recovery, COVID, etc.). | |
| dc.description.sponsorship | This study was funded by the Xunta de Galicia and the European Union (European Regional Development Fund—Galicia 2021–2027 FEDER Program), with grants CITIC (ED431G 2023/01) and GRC ED431C 2025/49, as well as by the Spanish Ministry of Science, Innovation, and Universities (project PID2023-148531NB-I00). | |
| dc.description.sponsorship | Xunta de Galicia; ED431G 2023/01 | |
| dc.description.sponsorship | Xunta de Galicia; GRC ED431C 2025/49 | |
| dc.identifier.citation | Beade, Á., J. Santos, and M. Rodríguez. 2026. “ Analysis of Economic Environment Incidence in Genetic Programming-Evolved Multiperiod Bankruptcy Prediction Models.” Intelligent Systems in Accounting, Finance and Management 33, no. 1: e70034. https://doi.org/10.1002/isaf.70034. | |
| dc.identifier.doi | 10.1002/isaf.70034 | |
| dc.identifier.issn | 2160-0074 | |
| dc.identifier.uri | https://hdl.handle.net/2183/48780 | |
| dc.language.iso | eng | |
| dc.publisher | Wiley | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023/PID2023-148531NB-I00/ES/GENERACION DE EXPLICACIONES EN SISTEMAS INTELIGENTES HIBRIDOS PARA ASEGURAR LA FIABILIDAD | |
| dc.relation.uri | https://doi.org/10.1002/isaf.70034 | |
| dc.rights | Attribution 4.0 International | en |
| dc.rights.accessRights | open access | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Bankruptcy prediction models | |
| dc.subject | Evolutionary computation | |
| dc.subject | Genetic programming | |
| dc.title | Analysis of Economic Environment Incidence in Genetic Programming-Evolved Multiperiod Bankruptcy Prediction Models | |
| dc.type | journal article | |
| dc.type.hasVersion | VoR | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | f5e23200-9174-4def-9fde-e3ce6c3c26d5 | |
| relation.isAuthorOfPublication | c85b6a48-b6d1-41c9-af79-3f6a2ee2e82d | |
| relation.isAuthorOfPublication.latestForDiscovery | f5e23200-9174-4def-9fde-e3ce6c3c26d5 |
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