Add to ORKGIn [16], a new family of vector-valued risk measures called multivariate expectiles is introduced. In this paper, we focus on the asymptotic behavior of these measures in a multivariate regular variations context. For models with equivalent tails, we propose an estimator of these multivariate asymptotic expectiles, in the Fréchet attraction domain case, with asymptotic independence, or in the comonotonic case
Expectiles and quantiles can both be defined as the solution of minimization problems. Contrary to q...
This paper deals with semiparametric estimation of the asymptotic portfolio risk factor γ ξ introduc...
Hidden regular variation is a sub-model of multivariate regular variation and facilitates accurate e...
International audienceMultivariate expectiles, a new family of vector-valued risk measures, were rec...
International audienceThis paper is devoted to the introduction and study of a new family of multiva...
Tail risk refers to the risk associated with extreme values and is often affected by extremal depend...
Existing theory for multivariate extreme values focuses upon characterizations of the distributional...
We use tail expectiles to estimate alternative measures to the Value at Risk (VaR) and Marginal Expe...
We define the appropriate analogue of Student's t-statistic for multivariate data, and prove that it...
In this paper, we introduce two alternative extensions of the classical univariate Conditional-Tail-...
In this paper, we introduce two alternative extensions of the classical univariate Value-at-Risk (Va...
International audienceWe use tail expectiles to estimate alternative measures to the Value at Risk (...
Consider a portfolio of n obligors subject to possible default. We propose a new structural model fo...
Thesis (Ph.D.), Washington State UniversityA central topic in modern financial and insurance mathema...
<div><p>This article develops a nonparametric varying-coefficient approach for modeling the expectil...
Expectiles and quantiles can both be defined as the solution of minimization problems. Contrary to q...
This paper deals with semiparametric estimation of the asymptotic portfolio risk factor γ ξ introduc...
Hidden regular variation is a sub-model of multivariate regular variation and facilitates accurate e...
International audienceMultivariate expectiles, a new family of vector-valued risk measures, were rec...
International audienceThis paper is devoted to the introduction and study of a new family of multiva...
Tail risk refers to the risk associated with extreme values and is often affected by extremal depend...
Existing theory for multivariate extreme values focuses upon characterizations of the distributional...
We use tail expectiles to estimate alternative measures to the Value at Risk (VaR) and Marginal Expe...
We define the appropriate analogue of Student's t-statistic for multivariate data, and prove that it...
In this paper, we introduce two alternative extensions of the classical univariate Conditional-Tail-...
In this paper, we introduce two alternative extensions of the classical univariate Value-at-Risk (Va...
International audienceWe use tail expectiles to estimate alternative measures to the Value at Risk (...
Consider a portfolio of n obligors subject to possible default. We propose a new structural model fo...
Thesis (Ph.D.), Washington State UniversityA central topic in modern financial and insurance mathema...
<div><p>This article develops a nonparametric varying-coefficient approach for modeling the expectil...
Expectiles and quantiles can both be defined as the solution of minimization problems. Contrary to q...
This paper deals with semiparametric estimation of the asymptotic portfolio risk factor γ ξ introduc...
Hidden regular variation is a sub-model of multivariate regular variation and facilitates accurate e...