Approximation of some multivariate risk measures for Gaussian risks

JOURNAL OF MULTIVARIATE ANALYSIS

卷:169

Article

Hashorva, Enkelejd¹ 

[1] Univ Lausanne, Dept Sci Actuarielles, CH-1015 Lausanne, Switzerland

关键词: Conditional limit theorem;    Gaussian random vectors;    Marginal expected shortfall;    Marginal mean excess;    Multivariate conditional tail expectation;   

DOI  :  10.1016/j.jmva.2018.10.006

来源: Elsevier

【 摘 要 】

Gaussian random vectors exhibit the loss of dimension phenomenon, which relates to their joint survival tail behavior. Besides, the fact that the components of such vectors are light tailed complicates the approximations of various multivariate risk measures significantly. In this contribution we derive precise approximations of marginal mean excess, marginal expected shortfall and multivariate conditional tail expectation of Gaussian random vectors and highlight links with conditional limit theorems. Our study indicates that similar results hold for elliptical and Gaussian like multivariate risks. (C) 2018 Elsevier Inc. All rights reserved.

【 授权许可】

Free