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Development of a Shadow Rating Model

Author

Listed:
  • Rémy Estran
  • Victor-Manuel de Fabritus
  • Antoine Souchaud

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. JEL Classification G320, G330, E580

Suggested Citation

  • Rémy Estran & Victor-Manuel de Fabritus & Antoine Souchaud, 2023. "Development of a Shadow Rating Model," Finance, Presses universitaires de Grenoble, vol. 44(2), pages 112-148.
    • Handle: RePEc:cai:finpug:fina_pr_017
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    More about this item

    Keywords

    Shadow rating model; default risk; credit rating; CRR; Basel III;
    All these keywords.

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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