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| Importance Sampling for Integrated Market and Credit Portfolio Models by Peter Grundke of the University of Cologne September 2006 Abstract: The predominant approach in risk management is to determine the economic capital for each risk type separately. Thus, the problem arises how to combine these different amounts of capital to a single number. Beside just adding the economic capital values or assuming multivariate normality of the different risk types, the usage of Copulas has been proposed recently for linking the marginal distributions of losses. In this paper, a different approach is pursued by modeling market and credit risk simultaneously, whereby stochastic dependencies between these two risk types can be taken into account directly. However, integrating market risk factors into standard credit portfolio models increases the computational burden of calculating risk measures. That is why the application of various importance sampling techniques to an integrated market and credit portfolio model is presented. The computational difficulties which result from the additional integration of market risk are discussed. The effectiveness of these approaches is tested by numerical experiments for linear and non-linear portfolios. JEL Classification: C63, G21, G33. Keywords: risk management, credit risk, importance sampling, interest rate risk, Value-at-Risk. Books Referenced in this Paper: (what is this?)
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