Dynamic Operational Risk: Modeling Dependence and Combining Different Sources of Information

The Journal of Operational Risk 4(2), pp. 69-104, 2009

47 Pages Posted: 23 Nov 2014

See all articles by Gareth Peters

Gareth Peters

University of California Santa Barbara; University of California, Santa Barbara

Pavel V. Shevchenko

Macquarie University - Department of Actuarial Studies and Business Analytics

Mario V. Wuthrich

RiskLab, ETH Zurich

Date Written: April 11, 2009

Abstract

In this paper, we model dependence between operational risks by allowing risk profiles to evolve stochastically in time and to be dependent. This allows for a flexible correlation structure where the dependence between frequencies of different risk categories and between severities of different risk categories as well as within risk categories can be modeled. The model is estimated using Bayesian inference methodology, allowing for combination of internal data, external data and expert opinion in the estimation procedure. We use a specialized Markov chain Monte Carlo simulation methodology known as Slice sampling to obtain samples from the resulting posterior distribution and estimate the model parameters.

Keywords: dependence modelling, copula, compound process, operational risk, Bayesian inference, Markov chain Monte Carlo, Slice sampling.

JEL Classification: C00, G00

Suggested Citation

Peters, Gareth and Shevchenko, Pavel V. and Wuthrich, Mario V., Dynamic Operational Risk: Modeling Dependence and Combining Different Sources of Information (April 11, 2009). The Journal of Operational Risk 4(2), pp. 69-104, 2009, Available at SSRN: https://ssrn.com/abstract=2529590

Gareth Peters

University of California Santa Barbara ( email )

Santa Barbara, CA 93106
United States

University of California, Santa Barbara ( email )

Pavel V. Shevchenko (Contact Author)

Macquarie University - Department of Actuarial Studies and Business Analytics ( email )

Australia

HOME PAGE: http://www.mq.edu.au/research/centre-for-risk-analytics/pavel-shevchenko

Mario V. Wuthrich

RiskLab, ETH Zurich ( email )

Department of Mathematics
Ramistrasse 101
Zurich, 8092
Switzerland

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