Risk measures for Skew Normal mixtures

Mauro Bernardi

MPRA Paper from University Library of Munich, Germany

Abstract: 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.

Keywords: Finite mixtures; Skew Normal distributions; Value-at-Risk; Expected Shortfall probability (search for similar items in EconPapers)
JEL-codes: C16 (search for similar items in EconPapers)
Date: 2012
New Economics Papers: this item is included in nep-ban, nep-ecm and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Risk measures for skew normal mixtures (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:39828

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