Reconciling credit correlations

Andrew Chernih and Luc Henrard and Steven Vanduffel

Journal of Risk Model Validation

Abstract: ABSTRACT The credit crisis has resulted in a new impetus for regulators in analyzing the framework for determining regulatory capital requirements; in particular, the assessment of credit risk will be challenged. Confronted with a lack of default statistics, it is common for industry practitioners to apply a financial approach known as Merton's model of the firm, which also underpins modern solvency standards such as Basel II and Solvency II. However, while Merton's theory is an academic beauty, its implementation does not make full use of available default statistics but, instead, relies on the concept of so-called asset correlations. We study the different estimates used for asset correlations that have appeared in the literature and analyze to what extent these estimates are in line with each other, with available default statistics and with our own findings. Our results are the same as most of those found in the literature but deviate from the results reported by some major software providers as well as from the Basel II and Solvency II figures. We offer several explanations to reconcile these differences and point to several other features that should not be overlooked when building credit portfolio models.

References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.risk.net/journal-risk-model-validation ... -credit-correlations (text/html)

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:rsk:journ5:2161257

Access Statistics for this article

More articles in Journal of Risk Model Validation from Journal of Risk Model Validation
Bibliographic data for series maintained by Thomas Paine (maintainer@infopro-digital.com).