Exposure at Default Modeling - A Theoretical and Empirical Assessment of Estimation Approaches and Parameter Choice

Journal of Banking & Finance, Vol. 91, 2018, pp. 176–188

42 Pages Posted: 25 Sep 2015 Last revised: 24 Aug 2018

See all articles by Marc Gürtler

Marc Gürtler

University of Braunschweig - Institute of Technology, Department of Finance

Martin Thomas Hibbeln

University of Duisburg-Essen - Mercator School of Management

Piet Usselmann

University of Braunschweig - Institute of Technology, Department of Finance

Abstract

Estimating the credit risk parameter exposure at default is important for banks from an internal risk management and a regulatory perspective. Several approaches are common in the literature and in practice. We theoretically and empirically analyze how the exposure at default should be modeled to obtain accurate estimates of the expected loss. Our empirical analysis is based on a large and unique dataset from a retail portfolio of a European bank. We demonstrate that some approaches can lead to substantially biased estimates of the expected loss and show that the generalized cohort approach is advantageous. Moreover, using in- and out-of-sample analyses, we empirically demonstrate that using the credit conversion factor is preferable to the loan equivalent factor, exposure at default factor, and direct exposure at default estimation to achieve high estimation accuracy.

Keywords: Credit risk, checking accounts, exposure at default, credit conversion factor, probability of default

JEL Classification: G21, G28

Suggested Citation

Gürtler, Marc and Hibbeln, Martin Thomas and Usselmann, Piet, Exposure at Default Modeling - A Theoretical and Empirical Assessment of Estimation Approaches and Parameter Choice. Journal of Banking & Finance, Vol. 91, 2018, pp. 176–188, Available at SSRN: https://ssrn.com/abstract=2665693

Marc Gürtler

University of Braunschweig - Institute of Technology, Department of Finance ( email )

Abt-Jerusalem-Str. 7
Braunschweig, 38106
Germany

Martin Thomas Hibbeln

University of Duisburg-Essen - Mercator School of Management ( email )

Lotharstraße 65
Duisburg, Nordrhein-Westfalen 47057
Germany
+49 203 379-2830 (Phone)

Piet Usselmann (Contact Author)

University of Braunschweig - Institute of Technology, Department of Finance ( email )

Abt-Jerusalem-Str. 7
Braunschweig, 38106
Germany

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