Variable selection for financial distress classification using a genetic algorithm
Gãlvao, R. K. H., Becerra, V. M. and Abou-Seada, M. (2002) Variable selection for financial distress classification using a genetic algorithm. In: Congress on evolutionary computation: CEC '02, 12 May 2002, Honolulu, HI, USA, pp. 2000-2005.
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To link to this article DOI: 10.1109/CEC.2002.1004550
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.