CoVaR of families of copulas

被引：34

作者：

Bernardi, M. ^{[1
]}

Durante, F. ^{[2
]}

Jaworski, P. ^{[3
]}

机构：

[1] Univ Padua, Dept Stat Sci, I-35100 Padua, Italy

[2] Free Univ Bozen Bolzano, Fac Econ & Management, Bolzano, Italy

[3] Univ Warsaw, Inst Math, Warsaw, Poland

来源：

STATISTICS & PROBABILITY LETTERS | 2017年 / 120卷

关键词：

Copula; CoVaR; Risk measure; Singular measure; Systemic risk; Value-at-Risk;

D O I：

10.1016/j.spl.2016.09.005

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

070103 [概率论与数理统计]; 140311 [社会设计与社会创新];

摘要：

We revisit the notion of Conditional Value-at-Risk (shortly, CoVaR) by weakening the usual assumptions on the joint distribution function of the involved random variables. The new approach exploits the copula methodology and uses the concept of Dini derivatives. A directory of CoVaR values for different families of copulas is provided. (C) 2016 Elsevier B.V. All rights reserved.

引用

收藏

页码：8 / 17

页数：10

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