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Development of a Shadow Rating Model

Author

Listed:
  • Remy Estran

    (ESCP Europe - Ecole Supérieure de Commerce de Paris)

  • Victor-Manuel De Fabritus

    (EthiFinance - EthiFinance Analytics)

  • Antoine Souchaud

    (NEOMA - Neoma Business School, i3-CRG - Centre de recherche en gestion i3 - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - Université Paris-Saclay - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

Abstract

In this article, we cover the essential development steps of a Shadow Rating Model (SRM) for large companies. After a univariate analysis of the predictive power of 20 financial variables (18 ratios, sizes, and sectors) on a sample of 1101 credit ratings we selected one ratio per risk family to estimate the multifactor model. With replication rates within one notch on the learning sample of 89.5%, and on the test sample of 87.3%, this model seems to be capable of explaining and predicting the rating of large companies based on their financial statements and sectors. The solutions we propose complements the literature by proposing an SRM complying with the current requirements of the CRR and those of the finalised Basel III (BCBS, 2017) which will be applicable from 1 January 2023. Our paper is also a call for and a first step towards more transparent dialogues and scientifically rooted debates about credit risks assessment models.

Suggested Citation

  • Remy Estran & Victor-Manuel De Fabritus & Antoine Souchaud, 2023. "Development of a Shadow Rating Model," Post-Print hal-03831225, HAL.
    • Handle: RePEc:hal:journl:hal-03831225
    as

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