Variable selection for financial distress classification using a genetic algorithm

被引：0

作者：

Galvao, RKH ^{[1
]}

Becerra, VM ^{[1
]}

Abou-Seada, M ^{[1
]}

机构：

[1] ITA, Div Engn Eletron, Sao Jose Dos Campos, SP, Brazil

来源：

CEC'02: PROCEEDINGS OF THE 2002 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2 | 2002年

关键词：

Galva;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：2000 / 2005

页数：6

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