Mixture models for VaR and stress testing

Marco Bee

No 12, Alea Tech Reports from Department of Computer and Management Sciences, University of Trento, Italy

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.

Pages: 18 pages
Date: 2001-06, Revised 2008-06-14
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Citations: View citations in EconPapers (3)

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