Development of a Shadow Rating Model

Rémy Estran, Victor-Manuel de Fabritus and Antoine Souchaud

Finance, 2023, vol. 44, issue 2, 112-148

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

Keywords: Shadow rating model; default risk; credit rating; CRR; Basel III (search for similar items in EconPapers)
JEL-codes: E58 G32 G33 (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.cairn.info/load_pdf.php?ID_ARTICLE=FINA_PR_017 (application/pdf)
http://www.cairn.info/revue-finance-2023-2-page-112.htm (text/html)
restricted

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cai:finpug:fina_pr_017

Access Statistics for this article

More articles in Finance from Presses universitaires de Grenoble
Bibliographic data for series maintained by Jean-Baptiste de Vathaire ().