We study bivariate stochastic recurrence equations with triangular matrix coefficients and we characterize the tail behavior of their stationary solutions ${\bf W} =(W_1,W_2)$. Recently it has been observed that $W_1,W_2$ may exhibit regularly varying tails with different indices, which is in contrast to well-known Kesten-type results. However, only partial results have been derived. Under typical "Kesten-Goldie" and "Grey" conditions, we completely characterize tail behavior of $W_1,W_2$. The tail asymptotics we obtain has not been observed in previous settings of stochastic recurrence equations.Comment: 42 page
We establish the equivalence between the multivariate regular variation of a random vector and the u...
We investigate a family of discrete-time stationary processes defined by multiple stable integrals a...
Abstract. We establish the equivalence between the multivariate regular variation of a random vector...
Multivariate process satisfying affine stochastic recurrence equation with generic diagonal matrices...
In this monograph the authors give a systematic approach to the probabilistic properties of the fixe...
We examine the auto-dependence structure of strictly stationary solutions of linear stochastic recur...
The tail behavior of aggregates of heavy-tailed random vectors is known to be determined by the so-c...
AbstractExtreme values of a stationary, multivariate time series may exhibit dependence across coord...
AbstractFor the solution Y of a multivariate random recurrence model Yn=AnYn−1+ζn in Rq we investiga...
We consider autoregressive sequences Xn=aXn−1+ξn and Mn=max{aMn−1,ξn} with a constant a∈(0,1) and wi...
International audienceWe consider a threshold autoregressive stochastic volatility model where the d...
Extreme values of a stationary, multivariate time series may exhibit dependence across coordinates a...
In this paper, we study the asymptotic distribution of the maxima of suprema of dependent Gaussian p...
AbstractIn this paper, we deal with the real stochastic difference equation Yn+1=anYn+bn,n∈Z, where ...
AbstractWe consider a simple bilinear process Xt=aXt−1+bXt−1Zt−1+Zt, where (Zt) is a sequence of iid...
We establish the equivalence between the multivariate regular variation of a random vector and the u...
We investigate a family of discrete-time stationary processes defined by multiple stable integrals a...
Abstract. We establish the equivalence between the multivariate regular variation of a random vector...
Multivariate process satisfying affine stochastic recurrence equation with generic diagonal matrices...
In this monograph the authors give a systematic approach to the probabilistic properties of the fixe...
We examine the auto-dependence structure of strictly stationary solutions of linear stochastic recur...
The tail behavior of aggregates of heavy-tailed random vectors is known to be determined by the so-c...
AbstractExtreme values of a stationary, multivariate time series may exhibit dependence across coord...
AbstractFor the solution Y of a multivariate random recurrence model Yn=AnYn−1+ζn in Rq we investiga...
We consider autoregressive sequences Xn=aXn−1+ξn and Mn=max{aMn−1,ξn} with a constant a∈(0,1) and wi...
International audienceWe consider a threshold autoregressive stochastic volatility model where the d...
Extreme values of a stationary, multivariate time series may exhibit dependence across coordinates a...
In this paper, we study the asymptotic distribution of the maxima of suprema of dependent Gaussian p...
AbstractIn this paper, we deal with the real stochastic difference equation Yn+1=anYn+bn,n∈Z, where ...
AbstractWe consider a simple bilinear process Xt=aXt−1+bXt−1Zt−1+Zt, where (Zt) is a sequence of iid...
We establish the equivalence between the multivariate regular variation of a random vector and the u...
We investigate a family of discrete-time stationary processes defined by multiple stable integrals a...
Abstract. We establish the equivalence between the multivariate regular variation of a random vector...