Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5129938 | Statistics & Probability Letters | 2017 | 10 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
M. Bernardi, F. Durante, P. Jaworski,