Accessibility navigation

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,

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item 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.

Item Type:Conference or Workshop Item (Paper)
ID Code:19200
Uncontrolled Keywords:corporate distress classification, discriminant analysis, financial distress, financial ratios, genetic algorithm, prediction models, ratio selection, variable selection

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation