Calibration of Internal Rating Systems: The Case of Dependent Default Events

Kredit und Kapital, Vol. 40, pp. 527-552, 2007

24 Pages Posted: 26 Nov 2005 Last revised: 17 Sep 2009

See all articles by Andre Guettler

Andre Guettler

Ulm University - Department of Mathematics and Economics; Halle Institute for Economic Research

Helge G. Liedtke

BearingPoint

Date Written: 2007

Abstract

We compare four different test approaches for the calibration quality of internal rating systems in the case of dependent default events. Two of them are approximation approaches and two are simulation approaches of one- and multi-factor models. We find that multi-factor models generate more precise results through lower upper bound default rates and narrower confidence intervals. For confidence levels of 95%, the approximation approaches overestimate the upper bound default rates. For low asset correlation, especially for less than 0.5%, the granularity adjustment approach does not deliver reasonable results. For low numbers of debtors, the approximation approaches sharply overestimate the upper bound default rates. Using empirical inter-factor correlations we find that confidence intervals of two-factor models are much tighter compared with the one-factor model.

Keywords: Validation, Calibration, Basel II, Rating systems

JEL Classification: C6, G21

Suggested Citation

Guettler, Andre and Liedtke, Helge G., Calibration of Internal Rating Systems: The Case of Dependent Default Events (2007). Kredit und Kapital, Vol. 40, pp. 527-552, 2007, Available at SSRN: https://ssrn.com/abstract=855084

Andre Guettler (Contact Author)

Ulm University - Department of Mathematics and Economics ( email )

Helmholzstrasse
Ulm, D-89081
Germany

Halle Institute for Economic Research ( email )

P.O. Box 11 03 61
Kleine Maerkerstrasse 8
D-06017 Halle, 06108
Germany

Helge G. Liedtke

BearingPoint ( email )

1676 International Drive
McLean, VA 22102
United States
+49 1726506792 (Phone)
+49 69 13022 1402 (Fax)

HOME PAGE: http://www.bearingpoint.com

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