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
收藏
页码：2000 / 2005
页数：6
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