Tail risk refers to the risk associated with extreme values and is often affected by extremal dependence among multivariate extremes. Multivariate tail risk, as measured by a coherent risk measure of tail conditional expectation, is analyzed for multivariate regularly varying distribu-tions. Asymptotic expressions for tail risk are established in terms of the intensity measure that characterizes multivariate regular variation. Tractable bounds for tail risk are derived in terms of the tail dependence function that describes extremal dependence. Various examples involving Archimedean copulas are presented to illustrate the results and quality of the bounds
In this PhD thesis we consider different aspects of dependence modeling with applications in multiva...
This paper focuses on measuring risk due to extreme events going beyond the multivariate normal dist...
International audienceThis paper presents the impact of a class of transformations of copulas in the...
Tail risk refers to the risk associated with extreme values and is often affected by extremal depend...
Stochastic dependence arises in many fields including electrical grid reliability, network/internet ...
Thesis (Ph.D.), Washington State UniversityA central topic in modern financial and insurance mathema...
Existing theory for multivariate extreme values focuses upon characterizations of the distributional...
AbstractThe orthant tail dependence describes the relative deviation of upper- (or lower-) orthant t...
The tail dependence of multivariate distributions is frequently studied via the tool of copulas. Thi...
Abstract Various multivariate Pareto distributions are known to exhibit the heavy tail behaviors. Th...
International audienceMultivariate expectiles, a new family of vector-valued risk measures, were rec...
Regular variation of the tail of a multivariate probability distribution is implied by regular varia...
This dissertation has 4 chapters, in which we attempt to explore and analyze the structure of extrem...
The extremal dependence behavior of t copulas is examined and their extreme value limiting copulas, ...
Abstract: The conditional tail expectation in risk analysis describes the expected amount of risk th...
In this PhD thesis we consider different aspects of dependence modeling with applications in multiva...
This paper focuses on measuring risk due to extreme events going beyond the multivariate normal dist...
International audienceThis paper presents the impact of a class of transformations of copulas in the...
Tail risk refers to the risk associated with extreme values and is often affected by extremal depend...
Stochastic dependence arises in many fields including electrical grid reliability, network/internet ...
Thesis (Ph.D.), Washington State UniversityA central topic in modern financial and insurance mathema...
Existing theory for multivariate extreme values focuses upon characterizations of the distributional...
AbstractThe orthant tail dependence describes the relative deviation of upper- (or lower-) orthant t...
The tail dependence of multivariate distributions is frequently studied via the tool of copulas. Thi...
Abstract Various multivariate Pareto distributions are known to exhibit the heavy tail behaviors. Th...
International audienceMultivariate expectiles, a new family of vector-valued risk measures, were rec...
Regular variation of the tail of a multivariate probability distribution is implied by regular varia...
This dissertation has 4 chapters, in which we attempt to explore and analyze the structure of extrem...
The extremal dependence behavior of t copulas is examined and their extreme value limiting copulas, ...
Abstract: The conditional tail expectation in risk analysis describes the expected amount of risk th...
In this PhD thesis we consider different aspects of dependence modeling with applications in multiva...
This paper focuses on measuring risk due to extreme events going beyond the multivariate normal dist...
International audienceThis paper presents the impact of a class of transformations of copulas in the...