A comparison of Japanese failure models: hybrid neural networks, logit models, and discriminant analysis

Yim, J and Mitchell, H 2005, 'A comparison of Japanese failure models: hybrid neural networks, logit models, and discriminant analysis', International Journal of Asian Management, vol. 3, no. 1, pp. 103-120.


Document type: Journal Article
Collection: Journal Articles

Title A comparison of Japanese failure models: hybrid neural networks, logit models, and discriminant analysis
Author(s) Yim, J
Mitchell, H
Year 2005
Journal name International Journal of Asian Management
Volume number 3
Issue number 1
Start page 103
End page 120
Total pages 17
Publisher Springer-Verlag, Tokyo
Abstract This article looks at the ability of a relatively new technique, hybrid artificial neural networks (ANNs), to predict Japanese banking and firm failures. 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 failure for one year prior to the event. This suggests that for researchers, policymakers, and others interested in early warning systems, the hybrid network may be a useful tool for predicting banking and firm failures.
Subject Expert Systems
Keyword(s) hybrid neural networks
statistical models
firm failures
bank failures
early warning systems
hybrid neural networks
DOI - identifier 10.1007/s10276-004-0022-0
Copyright notice © Springer-Verlag 2004
ISSN 1618-7504
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