Abstract
The paper presents a comparison between two different approaches to the problem of bankruptcy prediction: the traditional discriminant analysis method and possible solutions based on neural networks. The performance of a simple mathematical model applied to economic and financial ratios obtained from a small sample of manufacturing companies balance-sheets is compared with the performance of some BPN family neural networks trained with the same set of information. The results obtained from the neural networks suggest some interesting improvements and practical applications which are the object of the second and third section of the experiment programme in progress.
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© 1996 Physica-Verlag Heidelberg
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Carrara, D., Cavalli, E. (1996). Bankruptcy Prediction: Discriminant Analysis versus Neural Networks. In: Bertocchi, M., Cavalli, E., Komlósi, S. (eds) Modelling Techniques for Financial Markets and Bank Management. Contributions to Management Science. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-51730-3_11
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DOI: https://doi.org/10.1007/978-3-642-51730-3_11
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-0928-2
Online ISBN: 978-3-642-51730-3
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