Title: Tail Conditional Variance for Elliptically Contoured Distributions
Abstract: The tail conditional expectation, TCE for short, provides a measure of the riskiness of the tail of a distribution and is an index that has gained popularity over the years. On the other hand, the tail conditional variance, TCV for short, is lesser known but provides a measure of the variability of the risk along the tail of its distribution. Landsman and Valdez (2003) derive explicit formulas for computing tail conditional expectations for elliptical distributions, a family of symmetric distributions which includes the more familiar Normal and Studentt distributions. In this paper, we are able to similarly exploit the properties of the elliptical distributions to derive similar explicit forms in computing the tail conditional variance. In particular, the tail generator defi ned in the paper plays an important role in the process of developing these explicit forms. We further investigate these results in the multivariate case especially when the addition of several risks is concerned.
Publication Year: 2004
Publication Date: 2004-01-01
Language: en
Type: article
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Cited By Count: 37
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