Variable selection for financial distress classification using a genetic algorithm

R. K. H. Gãlvao; Victor Manuel Becerra; M. Abou-Seada

doi:10.1109/CEC.2002.1004550

Variable selection for financial distress classification using a genetic algorithm

R. K. H. Gãlvao, Victor Manuel Becerra, M. Abou-Seada

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Congress on evolutionary computation: CEC '02
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2000-2005
Number of pages	6
DOIs	https://doi.org/10.1109/CEC.2002.1004550
Publication status	Published - 2002

Keywords

corporate distress classification, discriminant analysis, financial distress, financial ratios, genetic algorithm, prediction models, ratio selection, variable selection

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10.1109/CEC.2002.1004550

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title = "Variable selection for financial distress classification using a genetic algorithm",

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.",

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AB - 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.

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DO - 10.1109/CEC.2002.1004550

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BT - Congress on evolutionary computation: CEC '02

PB - Institute of Electrical and Electronics Engineers Inc.

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Variable selection for financial distress classification using a genetic algorithm

Abstract

Keywords

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