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

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Authors: Ángel Beade, José Carlos Almeida Santos, Carmen Rodríguez-Rodríguez
Cited by: 0
References: 33

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.).

Fields of Study & Subjects

Financial Distress and Bankruptcy Prediction Corporate Insolvency and Governance Stock Market Forecasting Methods

Publication details

Journal / source
Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & management
Volume
33
Issue
1
Publication date
9 February 2026
Language
EN