Bee, Marco (2001) Mixture models for VaR and stress testing. UNSPECIFIED. (Unpublished)
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Abstract
In this paper we deal with the use of multivariate normal mixture distributions to model asset returns, In particular, by modelling daily asset returns as a mixture of a low-volatility and a high-volatility distribution, we obtain three main results: (i) we can use posterior probabilities to identify hectic observations; (ii) we are able to compute a non-parametric fat-tails Value at Risk by sampling repeatedly from the mixture and computing the quantile of the empirical distribution; (iii) we can use the estimated parameters of the hectic distribution for stress testing purposes. We show how these three items can be addressed using either real data and simulation methods.
| Item Type: | Departmental Technical Report |
|---|---|
| Department or Research center: | Computer and management sciences |
| Subjects: | H Social Sciences > HB Economic Theory > HB615 Risk and uncertainty H Social Sciences > HG Finance |
| Uncontrolled Keywords: | Financial market - ARCH-type models - Extreme value theory - Stochastic volatility models |
| Report Number: | ALEA ; 12 |
| Repository staff approval on: | 12 Dec 2002 |
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