Risk measures for skew normal mixtures
In this paper we show that linear combinations of multivariate skew normal mixtures can be represented as finite mixtures of univariate skew normals. Based on this result we provide an analytical formula for some well known risk measures.
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Volume (Year): 83 (2013)
Issue (Month): 8 ()
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References listed on IDEAS
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- Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2012.
"Skew mixture models for loss distributions: A Bayesian approach,"
Insurance: Mathematics and Economics,
Elsevier, vol. 51(3), pages 617-623.
- Bernardi, Mauro & Maruotti, Antonello & Lea, Petrella, 2012. "Skew mixture models for loss distributions: a Bayesian approach," MPRA Paper 39826, University Library of Munich, Germany.
- Acerbi, Carlo & Tasche, Dirk, 2002.
"On the coherence of expected shortfall,"
Journal of Banking & Finance,
Elsevier, vol. 26(7), pages 1487-1503, July.
- Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
- A. Azzalini & A. Capitanio, 1999. "Statistical applications of the multivariate skew normal distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 579-602.
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