Computing portfolio risk using Gaussian mixtures and independentcomponent analysis
Chin, E.; Weigend, A.S.; Zimmermann, H.
Computational Intelligence for Financial Engineering, 1999. (CIFEr) Proceedings of the IEEE/IAFE 1999 Conference on
Volume , Issue , 1999 Page(s):74 - 117
Digital Object Identifier   10.1109/CIFER.1999.771108
Summary:Addressing the problem of non-normal portfolio returns, we introduce a novel approach for estimating the distribution of portfolio returns considering higher order mutual information. It allows us to extend the standard variance-covariance framework and efficiently re-compute measures of market risk such as the standard Value-at-Risk or any other probability density based measure. The approach combines two clean and transparent methodologies-independent component analysis and finite Gaussian mixture distributions-and is formulated algorithmically in three steps

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