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 proceedingConference 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 languageEnglish
    Title of host publicationCongress on evolutionary computation: CEC '02
    PublisherIEEE
    Pages2000-2005
    Number of pages6
    DOIs
    Publication statusPublished - 2002

    Keywords

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

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