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Analysis of the Predictors of Default for Portuguese Firms

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  • Russ A. Moro

Abstract

The paper presents an insolvency risk analysis of Portuguese companies with three techniques: logistic regression, discriminant analysis and support vector machines (SVM). It identifies the most critical predictors of default based on the accounting, employee and debt concentration data. A comparison of the three methods reveals a superiority of SVM. Non-financial information such as employee data and the debt concentration index appear to be strong predictors of default.

Suggested Citation

  • Russ A. Moro, 2008. "Analysis of the Predictors of Default for Portuguese Firms," Working Papers w200822, Banco de Portugal, Economics and Research Department.
    • Handle: RePEc:ptu:wpaper:w200822
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    File URL: https://www.bportugal.pt/sites/default/files/anexos/papers/wp200822.pdf
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    Cited by:

    1. Nehrebecka Natalia, 2018. "Predicting the Default Risk of Companies. Comparison of Credit Scoring Models: Logit Vs Support Vector Machines," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 22(2), pages 54-73, June.

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