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February 12, 2026Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & management0 citationsOpen Access

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

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ÁBÁngel BeadeJSJosé Manuel Sánchez SantosCRCarmen Rodríguez-Rodríguez

Key Points

  • The aim is to determine if financial variables alone can predict bankruptcy and reflect the economic environment.
  • Utilized genetic programming to develop multiperiod bankruptcy prediction models.
  • Conducted feature selection to identify relevant financial variables.
  • Analyzed correlations between model predictions and various economic indicators.
  • Confirmed strong correlations between model predictions and economic indicators over 2008–2020.
  • Demonstrated that financial information can effectively capture economic trends despite varying conditions.

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.).

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Cite This Study

Beade et al. (2026) studied this question.

synapsesocial.com/papers/698d6ebb5be6419ac0d54757https://doi.org/10.1002/isaf.70034
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