A comparison of corporate distress prediction models in Brazil: hybrid neural networks, logit models and discriminant analysis

Yim, J and Mitchell, H 2005, 'A comparison of corporate distress prediction models in Brazil: hybrid neural networks, logit models and discriminant analysis', Nova Economia, vol. 15, no. 1, pp. 73-93.


Document type: Journal Article
Collection: Journal Articles

Title A comparison of corporate distress prediction models in Brazil: hybrid neural networks, logit models and discriminant analysis
Author(s) Yim, J
Mitchell, H
Year 2005
Journal name Nova Economia
Volume number 15
Issue number 1
Start page 73
End page 93
Total pages 21
Publisher Universidade Federal de Minas Gerais, Faculdade de Ciencias Economicas
Abstract This paper looks at the ability of a relatively new technique, hybrid ANN's, to predict corporate distress in Brazil. These models are compared with traditional statistical techniques and conventional ANN models. The results suggest that hybrid neural networks outperform all other models in predicting firms in financial distress one year prior to the event. This suggests that for researchers, policymakers and others interested in early warning systems, hybrid networks may be a useful tool for predicting firm failure.
Subject Applied Economics not elsewhere classified
Keyword(s) Hybrid Neural Networks
Corporate Failures
ISSN 0103-6351
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