Misspecified Copulas in Credit Risk Models: How Good is Gaussian?

Journal of Risk 8 (1), 2005, pp. 41-58

29 Pages Posted: 31 Oct 2013

See all articles by Alfred Hamerle

Alfred Hamerle

University of Regensburg - Faculty of Business, Economics & Information Systems

Daniel Roesch

University of Regensburg

Multiple version iconThere are 2 versions of this paper

Date Written: April 31, 2005

Abstract

In addition to “classical” approaches, such as the Gaussian CreditMetrics or Basel II model, recently the use of other copulas has been proposed in the area of credit risk for modeling loss distributions, particularly T copulas which lead to fatter tails ceteris paribus. As an amendment to recent research this paper shows some estimation results when the copula in a default-mode framework using a latent variable distribution is misspecified. It turns out that parameter estimates may be biased, but that the resulting forecast for the loss distribution may still be adequate. We also compare the performance of the true and misspecified models with respect to estimation risk. Finally, we demonstrate the ideas using rating agencies data and show a simple way how to deal with estimation risk in practice. Overall, our findings on the robustness of the Gaussian copula considerably reduce model risk in practical applications.

Keywords: Credit Risk Models, Correlations, Copulas, Basel II

JEL Classification: C16, C50, G21, G24

Suggested Citation

Hamerle, Alfred and Roesch, Daniel, Misspecified Copulas in Credit Risk Models: How Good is Gaussian? (April 31, 2005). Journal of Risk 8 (1), 2005, pp. 41-58, Available at SSRN: https://ssrn.com/abstract=2347939 or http://dx.doi.org/10.2139/ssrn.2347939

Alfred Hamerle

University of Regensburg - Faculty of Business, Economics & Information Systems ( email )

Universitstrasse 31
Regensberg D-93053
Germany

Daniel Roesch (Contact Author)

University of Regensburg ( email )

Chair of Statistics and Risk Management
Faculty of Business, Economics and BIS
Regensburg, 93040
Germany

HOME PAGE: http://www-risk.ur.de/

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
254
Abstract Views
947
rank
131,735
PlumX Metrics