3 papers
math.ST2021
Non-parametric estimator of a multivariate madogram for missing-data and extreme value framework
Alexis Boulin, Elena Di Bernardino, Thomas Laloë +1
The modeling of dependence between maxima is an important subject in several applications in risk analysis. To this aim, the extreme value copula function, characterised via the ma…
stat.AP2016
On the estimation of extreme directional multivariate quantiles
Raúl Torres, Elena Di Bernardino, Henry Laniado +1
In multivariate extreme value theory (MEVT), the focus is on analysis outside of the observable sampling zone, which implies that the region of interest is associated to high risk…
q-fin.RM2011
On Multivariate Extensions of Value-at-Risk
Areski Cousin, Elena Di Bernadino
In this paper, we introduce two alternative extensions of the classical univariate Value-at-Risk (VaR) in a multivariate setting. The two proposed multivariate VaR are vector-value…