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

ABSTRACT Genetic programming (GP) is used to obtain multiperiod bankruptcy prediction models, as well as to perform a prior feature selection 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 check whether the impact that the economic environment undoubtedly has on the firms can be captured using only the financial variables of the firm as explanatory variables. To this end, the analysis includes a study of the correlation between the estimates of the prediction models and certain economic indicators. The results confirm the possibility of capturing the evolution of the economic environment using only financial information as input, as strong correlations are shown between the predictions of the models and important economic indicators over a very long postlearning period (2008–2020) and varied in terms of the economic environment (crisis, recovery, COVID, etc.).

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Journal
Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & management
Published
2026-02-09
DOI
https://doi.org/10.1002/isaf.70034
Primary Topic
Financial Distress and Bankruptcy Prediction
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article
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article

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

Carmen Rodríguez-Rodríguez, José Manuel Sánchez Santos, Ángel Beade
Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & management
Financial Distress and Bankruptcy Prediction
article

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

Carmen Rodríguez-Rodríguez, José Manuel Sánchez Santos, Ángel Beade
article en

Abstract

ABSTRACT Genetic programming (GP) is used to obtain multiperiod bankruptcy prediction models, as well as to perform a prior feature selection 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 check whether the impact that the economic environment undoubtedly has on the firms can be captured using only the financial variables of the firm as explanatory variables. To this end, the analysis includes a study of the correlation between the estimates of the prediction models and certain economic indicators. The results confirm the possibility of capturing the evolution of the economic environment using only financial information as input, as strong correlations are shown between the predictions of the models and important economic indicators over a very long postlearning period (2008–2020) and varied in terms of the economic environment (crisis, recovery, COVID, etc.).

Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & managementVol. 33(1)
Universidade da Coruña (ES)
Openalex Percentile: Top 60%
Financial Distress and Bankruptcy Prediction
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Analysis of Economic Environment Incidence in Genetic Programming‐Evolved Multiperiod Bankruptcy Prediction Models — Carmen Rodríguez-Rodríguez, José Manuel Sánchez Santos, et al. · Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & management (2026) | TGRS Research Map | TGRS