Analysis of Economic Environment Incidence in Genetic Programming-Evolved Multiperiod Bankruptcy Prediction Models

UDC.coleccionInvestigación
UDC.departamentoCiencias da Computación e Tecnoloxías da Información
UDC.grupoInvInformation Retrieval Lab (IRlab)
UDC.institutoCentroCITIC - Centro de Investigación de Tecnoloxías da Información e da Comunicación
UDC.issue1
UDC.journalTitleIntelligent Systems in Accounting, Finance and Management
UDC.startPagee70034
UDC.volume33
dc.contributor.authorBeade, Angel
dc.contributor.authorSantos Reyes, José
dc.contributor.authorRodríguez López, Manuel
dc.date.accessioned2026-07-06T11:34:10Z
dc.date.available2026-07-06T11:34:10Z
dc.date.issued2026-03
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.sponsorshipThis 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.sponsorshipXunta de Galicia; ED431G 2023/01
dc.description.sponsorshipXunta de Galicia; GRC ED431C 2025/49
dc.identifier.citationBeade, 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.doi10.1002/isaf.70034
dc.identifier.issn2160-0074
dc.identifier.urihttps://hdl.handle.net/2183/48780
dc.language.isoeng
dc.publisherWiley
dc.relation.projectIDinfo: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.urihttps://doi.org/10.1002/isaf.70034
dc.rightsAttribution 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectBankruptcy prediction models
dc.subjectEvolutionary computation
dc.subjectGenetic programming
dc.titleAnalysis of Economic Environment Incidence in Genetic Programming-Evolved Multiperiod Bankruptcy Prediction Models
dc.typejournal article
dc.type.hasVersionVoR
dspace.entity.typePublication
relation.isAuthorOfPublicationf5e23200-9174-4def-9fde-e3ce6c3c26d5
relation.isAuthorOfPublicationc85b6a48-b6d1-41c9-af79-3f6a2ee2e82d
relation.isAuthorOfPublication.latestForDiscoveryf5e23200-9174-4def-9fde-e3ce6c3c26d5

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