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Credit risk assessment: a comparison of the performances of the linear discriminant analysis and the logistic regression
[Évaluation du risque de crédit des PME: Une approche comparative des performances de l'analyse discriminante linéaire et de la régression logistique]

Author

Listed:
  • Aldo Lévy

    (LIRSA - Laboratoire interdisciplinaire de recherche en sciences de l'action - CNAM - Conservatoire National des Arts et Métiers [CNAM])

  • Riad Baha

    (LIRSA - Laboratoire interdisciplinaire de recherche en sciences de l'action - CNAM - Conservatoire National des Arts et Métiers [CNAM])

Abstract

The prediction of credit risk and borrowers solvency has been widely discussed in the financial and accounting literature whatever the international financial accounting standards (Levy et al., 2016). Various methods are used to build prediction models and can be adapted according to the country, the sector of activity and the nature of the data used. These methods have shown their effectiveness compared to traditional financial analysis for companies classification. This paper aims to compare the classification performances of the logistic regression (LR) model with those of the linear discriminant analysis (LDA) one on a SMEs sample belonging to the Algerian private sector.

Suggested Citation

  • Aldo Lévy & Riad Baha, 2021. "Credit risk assessment: a comparison of the performances of the linear discriminant analysis and the logistic regression [Évaluation du risque de crédit des PME: Une approche comparative des perfor," Post-Print hal-04553429, HAL.
    • Handle: RePEc:hal:journl:hal-04553429
    DOI: 10.1504/IJESB.2021.112265
    as

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