One of the central objectives of modern risk management is to find a set of risks where the probability of multiple simultaneous catastrophic events is negligible. That is, risks are taken only when their joint behavior seems sufficiently independent. This paper aims to identify asymptotically independent risks by providing tools for describing dependence structures of multiple risks when the individual risks can obtain very large values. The study is performed in the setting of multivariate regular variation. We show how asymptotic independence is connected to properties of the support of the angular measure and present an asymptotically consistent estimator of the support. The estimator generalizes to any dimension N >= 2 and requires no ...
This paper deals with semiparametric estimation of the asymptotic portfolio risk factor γ ξ introduc...
We find the asymptotic distribution of the multi-dimensional multi-scale and kernel estimators for h...
The traditional approach to multivariate extreme values has been through the multivariate extreme va...
One of the central objectives of modern risk management is to find a set of risks where the probabil...
Modeling and forecasting extreme co-movements in financial market is important for conducting stress...
Multivariate extremes behave very differently under asymptotic dependence as compared to asymptotic ...
Modern risk modelling approaches deal with vectors of multiple components. The components could be, ...
Many multivariate analyses require the account of extreme events. Correlation is an insufficient me...
It is well-known that a Gaussian dependence structure implies asymptotic indepen-dence in the sense ...
In the classical setting of bivariate extreme value theory, the procedures for estimating the probab...
In multivariate extreme value analysis, the nature of the extremal dependence between variables shou...
In this thesis, we aim at a quantitative understanding of extreme risks and extremal depen- dence in...
A bivariate random vector can exhibit either asymptotic independence or dependence between the large...
Probabilistic and statistical aspects of extremes of univariate processes have been extensively stud...
In insurance and reinsurance, heavy-tail analysis is used to model insurance claim sizes and frequen...
This paper deals with semiparametric estimation of the asymptotic portfolio risk factor γ ξ introduc...
We find the asymptotic distribution of the multi-dimensional multi-scale and kernel estimators for h...
The traditional approach to multivariate extreme values has been through the multivariate extreme va...
One of the central objectives of modern risk management is to find a set of risks where the probabil...
Modeling and forecasting extreme co-movements in financial market is important for conducting stress...
Multivariate extremes behave very differently under asymptotic dependence as compared to asymptotic ...
Modern risk modelling approaches deal with vectors of multiple components. The components could be, ...
Many multivariate analyses require the account of extreme events. Correlation is an insufficient me...
It is well-known that a Gaussian dependence structure implies asymptotic indepen-dence in the sense ...
In the classical setting of bivariate extreme value theory, the procedures for estimating the probab...
In multivariate extreme value analysis, the nature of the extremal dependence between variables shou...
In this thesis, we aim at a quantitative understanding of extreme risks and extremal depen- dence in...
A bivariate random vector can exhibit either asymptotic independence or dependence between the large...
Probabilistic and statistical aspects of extremes of univariate processes have been extensively stud...
In insurance and reinsurance, heavy-tail analysis is used to model insurance claim sizes and frequen...
This paper deals with semiparametric estimation of the asymptotic portfolio risk factor γ ξ introduc...
We find the asymptotic distribution of the multi-dimensional multi-scale and kernel estimators for h...
The traditional approach to multivariate extreme values has been through the multivariate extreme va...