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Dynamic Operational Risk: Modeling Dependence and Combining Different Sources of Information
Year Of Publication: 2009
Month Of Publication: April
Pages: 47
Download Count: 18
View Count: 2145
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 7-17-2010
Publisher: Administrator
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.
This document was published in the Journal of Operational Risk (volume 4, number 2), 2009, pp. 69-104.
Peters, Gareth Sign in to follow this author
Shevchenko, Pavel Sign in to follow this author
Wuethrich, Mario V. Sign in to follow this author
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