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Predicting financial distress of companies: Comparison between multivariate discriminant analysis and multilayer perceptron for Tunisian case

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  • Fayçal Mraihi

    (Higher School of Economics and Business Sciences of Tunis)

  • Inane Kanzari

    (Higher School of Economics and Business Sciences of Tunis)

Abstract

In this study, we try to develop a model for predicting corporate default based on a multivariate discriminant analysis (ADM) and a multilayer perceptron (MLP). The two models are applied to the Tunisian cases. Our sample consists of 212 companies in the various industries (106 ‘healthy’ companies and 106 “distressed” companies) over the period 2005-2010. The results of the use of a battery of 87 ratios showed that 16 ratios can build the model and that liquidity and solvency have more weight than profitability and management in predicting the distress. Despite the slight superiority of the results provided by the MLP model, on the control sample, the results provided by the two models are good either in terms of correct percentage of classification or in terms of stability of discriminating power over time and space.

Suggested Citation

  • Fayçal Mraihi & Inane Kanzari, 2019. "Predicting financial distress of companies: Comparison between multivariate discriminant analysis and multilayer perceptron for Tunisian case," Working Papers 1328, Economic Research Forum, revised 21 Aug 2019.
    • Handle: RePEc:erg:wpaper:1328
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    References listed on IDEAS

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