Bernardi, Mauro (2012): Risk measures for Skew Normal mixtures.
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Finite mixtures of Skew distributions have become increasingly popular in the last few years as a flexible tool for handling data displaying several different characteristics such as multimodality, asymmetry and fat-tails. Examples of such data can be found in financial and actuarial applications as well as biological and epidemiological analysis. In this paper we will show that a convex linear combination of multivariate Skew Normal mixtures can be represented as finite mixtures of univariate Skew Normal distributions. This result can be useful in modeling portfolio returns where the evaluation of extremal events is of great interest. We provide analytical formula for different risk measures like the Value-at-Risk and the Expected Shortfall probability.
|Item Type:||MPRA Paper|
|Original Title:||Risk measures for Skew Normal mixtures|
|Keywords:||Finite mixtures, Skew Normal distributions, Value-at-Risk, Expected Shortfall probability|
|Subjects:||C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C16 - Specific Distributions|
|Depositing User:||Mauro Bernardi|
|Date Deposited:||04. Jul 2012 12:31|
|Last Modified:||21. Feb 2013 07:30|
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