Variable selection for financial distress classification using a genetic algorithm

Author

Galveo, R.K.H. ; Becerra, V.M. ; Abou-Seada, M.

Author_Institution

Div. Eng. Eletronica, ITA, Sao Paulo, Brazil

Volume

2

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

2000

Lastpage

2005

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

Keywords

economic cybernetics; genetic algorithms; pattern classification; corporate distress classification; discriminant analysis; financial distress; financial ratios; genetic algorithm; prediction models; ratio selection; variable selection; Companies; Context modeling; Cybernetics; Failure analysis; Finance; Genetic algorithms; Government; Input variables; Predictive models; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-7282-4

Type

conf

DOI

10.1109/CEC.2002.1004550

Filename

1004550