On the utility of input selection and pruning for financial distress prediction models

Becerra, V. M., Galvão, R. K. H. and Abou-Seada, M. (2002) On the utility of input selection and pruning for financial distress prediction models. In: International Joint Conference on Neural Networks: IJCNN 2002, 12-17 May 2002, Honolulu, HI, USA, pp. 1328-1333. doi: 10.1109/IJCNN.2002.1007687

Abstract/Summary

Analyzes the use of linear and neural network models for financial distress classification, with emphasis on the issues of input variable selection and model pruning. A data-driven method for selecting input variables (financial ratios, in this case) is proposed. A case study involving 60 British firms in the period 1997-2000 is used for illustration. It is shown that the use of the Optimal Brain Damage pruning technique can considerably improve the generalization ability of a neural model. Moreover, the set of financial ratios obtained with the proposed selection procedure is shown to be an appropriate alternative to the ratios usually employed by practitioners.

Item Type	Conference or Workshop Item (Paper)
URI	https://reading-clone.eprints-hosting.org/id/eprint/19199
Item Type	Conference or Workshop Item
Refereed	Yes
Divisions	Science
Uncontrolled Keywords	British firms, Optimal Brain Damage, data-driven method, financial distress classification, financial distress prediction models, financial ratios, generalization ability, input selection, linear models, model pruning, neural network models
Publisher Statement	2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290)
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