On Conditional Value at Risk (CoVaR) for tail-dependent copulas

Piotr Jaworski

Dependence Modeling (2017)

  • Volume: 5, Issue: 1, page 1-19
  • ISSN: 2300-2298

Abstract

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The paper deals with Conditional Value at Risk (CoVaR) for copulas with nontrivial tail dependence. We show that both in the standard and the modified settings, the tail dependence function determines the limiting properties of CoVaR as the conditioning event becomes more extreme. The results are illustrated with examples using the extreme value, conic and truncation invariant families of bivariate tail-dependent copulas.

How to cite

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Piotr Jaworski. "On Conditional Value at Risk (CoVaR) for tail-dependent copulas." Dependence Modeling 5.1 (2017): 1-19. <http://eudml.org/doc/287975>.

@article{PiotrJaworski2017,
abstract = {The paper deals with Conditional Value at Risk (CoVaR) for copulas with nontrivial tail dependence. We show that both in the standard and the modified settings, the tail dependence function determines the limiting properties of CoVaR as the conditioning event becomes more extreme. The results are illustrated with examples using the extreme value, conic and truncation invariant families of bivariate tail-dependent copulas.},
author = {Piotr Jaworski},
journal = {Dependence Modeling},
keywords = {Copulas; Tail dependence; Value-at-Risk (VaR); Conditional Value-at-Risk (CoVaR); Conditional quantiles; copulas; tail dependence; value-at-risk (VaR); conditional value-at-risk (CoVaR); conditional quantiles},
language = {eng},
number = {1},
pages = {1-19},
title = {On Conditional Value at Risk (CoVaR) for tail-dependent copulas},
url = {http://eudml.org/doc/287975},
volume = {5},
year = {2017},
}

TY - JOUR
AU - Piotr Jaworski
TI - On Conditional Value at Risk (CoVaR) for tail-dependent copulas
JO - Dependence Modeling
PY - 2017
VL - 5
IS - 1
SP - 1
EP - 19
AB - The paper deals with Conditional Value at Risk (CoVaR) for copulas with nontrivial tail dependence. We show that both in the standard and the modified settings, the tail dependence function determines the limiting properties of CoVaR as the conditioning event becomes more extreme. The results are illustrated with examples using the extreme value, conic and truncation invariant families of bivariate tail-dependent copulas.
LA - eng
KW - Copulas; Tail dependence; Value-at-Risk (VaR); Conditional Value-at-Risk (CoVaR); Conditional quantiles; copulas; tail dependence; value-at-risk (VaR); conditional value-at-risk (CoVaR); conditional quantiles
UR - http://eudml.org/doc/287975
ER -

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