Operational-Risk Dependencies and the Determination of Risk Capital

Center for Quantitative Risk Analysis (CEQURA) Working Paper No. 3

35 Pages Posted: 6 Aug 2011  

Stefan Mittnik

University of Kiel - Institute of Statistics & Econometrics; Ludwig Maximilian University of Munich - Faculty of Economics; CESifo (Center for Economic Studies and Ifo Institute)

Sandra Paterlini

Università degli Studi di Trento - Department of Economics and Management

Tina Yener

Ludwig Maximilians University of Munich

Date Written: June 30, 2011

Abstract

With the advent of Basel II, risk-capital provisions need to also account for operational risk. The specification of dependence structures and the assessment of their effects on aggregate risk-capital are still open issues in modeling operational risk. In this paper, we investigate the potential consequences of adopting the restrictive Basel's Loss Distribution Approach (LDA), as compared to strategies that take dependencies explicitly into account. Drawing on a real-world database, we fit alternative dependence structures, using parametric copulas and nonparametric tail-dependence coefficients, and discuss the implications on the estimation of aggregate risk capital.

We find that risk-capital estimates may increase relative to that derived for the LDA when accounting explicitly for the presence of dependencies. This phenomenon is not only be due to the (fitted) characteristics of the data, but also arise from the specific Monte Carlo setup in simulation-based risk-capital analysis.

Keywords: Copula, Nonparametric Tail Dependence, Basel II, Loss Distribution Approach

JEL Classification: C14, C15, G10, G21

Suggested Citation

Mittnik, Stefan and Paterlini, Sandra and Yener, Tina, Operational-Risk Dependencies and the Determination of Risk Capital (June 30, 2011). Center for Quantitative Risk Analysis (CEQURA) Working Paper No. 3. Available at SSRN: https://ssrn.com/abstract=1905600 or http://dx.doi.org/10.2139/ssrn.1905600

Stefan Mittnik

University of Kiel - Institute of Statistics & Econometrics ( email )

Olshausenstr. 40
Kiel, Schleswig-Holstein 24118
Germany

Ludwig Maximilian University of Munich - Faculty of Economics ( email )

Akademiestr.1/III
Munich, D-80539
Germany

CESifo (Center for Economic Studies and Ifo Institute)

Poschinger Str. 5
Munich, DE-81679
Germany

Sandra Paterlini (Contact Author)

Università degli Studi di Trento - Department of Economics and Management ( email )

Via Inama 5
Trento, I-38100
Italy

Tina Yener

Ludwig Maximilians University of Munich ( email )

Ludwigstr. 33
Munchen, D-80539
Germany

HOME PAGE: http://www.stat.uni-muenchen.de/

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