Variable selection for financial distress classification using a genetic algorithm

Authors:
R. K. H. Galveo;V. M. Becerra;M. Abou-Seada
Affiliations:
Div. Eng. Eletronica, ITA, Sao Paulo, Brazil;Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore;Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
Venue:
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Year:
2002

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Abstract

This paper is concerned with the use of a genetic algorithm to select financial ratios for corporate distress classification models. For this purpose, the fitness value associated to a set of ratios is made to reflect the requirements of maximizing the amount of information available for the model and minimizing the collinearity between the model inputs. A case study involving 60 failed and continuing British firms in the period 1997-2000 is used for illustration. The classification model based on ratios selected by the genetic algorithm compares favorably with a model employing ratios usually found in the financial distress literature.