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.

To link to this article DOI: 10.1109/CEC.2002.1004550

Abstract/Summary

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)
Refereed:Yes
Divisions:Faculty of Science > School of Systems Engineering
ID Code:19200
Uncontrolled Keywords:corporate distress classification, discriminant analysis, financial distress, financial ratios, genetic algorithm, prediction models, ratio selection, variable selection

Centaur Editors: Update this record

Page navigation