Diagnosing corporate stability using grammatical evolution

Brabazon, Anthony ; O'Neill, Michael

International Journal of Applied Mathematics and Computer Science, Tome 14 (2004), p. 363-374 / Harvested from The Polish Digital Mathematics Library

Résumé

Grammatical Evolution (GE) is a novel data-driven, model-induction tool, inspired by the biological gene-to-protein mapping process. This study provides an introduction to GE, and demonstrates the methodology by applying it to construct a series of models for the prediction of bankruptcy, employing information drawn from financial statements. Unlike prior studies in this domain, the raw financial information is not preprocessed into pre-determined financial ratios. Instead, the ratios to be incorporated into the classification rule are evolved from the raw financial data. This allows the creation and subsequent evolution of alternative ratio-based representations of the financial data. A sample of 178 publicly quoted, US firms, drawn from the period 1991 to 2000 are used to train and test the model. The best evolved model correctly classified 86 (77)% of the firms in the in-sample training set (out-of-sample validation set), one year prior to failure.

Détail

Publié le : 2004-01-01

Zbl 1180.91240

EUDML-ID : urn:eudml:doc:207703

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