A new approach to deal with variable selection in neural networks: an application to bankruptcy prediction

DOI10.1007/S10479-021-04236-4zbMath1494.91173OpenAlexW3201640276MaRDI QIDQ2151634

Khaled Guesmi, Farid Mkaouar, Rim Ayadi, Ilyes Abid

Publication date: 5 July 2022

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-021-04236-4

zbMATH Keywords

classificationneural networksvariable selectionbankruptcy prediction

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Corporate finance (dividends, real options, etc.) (91G50)

Related Items (1)

Designing topological data to forecast bankruptcy using convolutional neural networks

Cites Work

• Predicting bankruptcies with the self-organizing map
• Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis
• Prediction of commercial bank failure via multivariate statistical analysis of financial structures: the Turkish case
• A hybrid genetic model for the prediction of corporate failure
• Model combination for credit risk assessment: a stacked generalization approach
• Predicting the survival or failure of click-and-mortar corporations: a knowledge discovery approach
• Input Variable Selection in Neural Network Models
• Comparative analysis of artificial neural network models: Application in bankruptcy prediction

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