Joint tail of randomly weighted sums under generalized quasi asymptotic independence

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Konstantinides, Dimitrios G., Passalidis, Charalampos D.
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866908379437334528
author Konstantinides, Dimitrios G.
Passalidis, Charalampos D.
author_facet Konstantinides, Dimitrios G.
Passalidis, Charalampos D.
contents In this paper we revisited the classical problem of max-sum equivalence of randomly weighted sums in two dimensions. In opposite to the most papers in literature, we consider that there exists some interdependence between the primary random variables, which is achieved by a combination of a new dependence structure with some two-dimensional heavy-tailed classes of distributions. Further, we introduce a new approach in two-dimensional regular varying distributions, that in contrast to well-established multivariate regularly varying distributions, is consistent with the multivariate non-linear single big jump principle. We study some closure properties of this, and of other two-dimensional classes. Our results contain the finite-time ruin probability in a two-dimensional discrete time risk model
format Preprint
id arxiv_https___arxiv_org_abs_2408_01010
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Joint tail of randomly weighted sums under generalized quasi asymptotic independence
Konstantinides, Dimitrios G.
Passalidis, Charalampos D.
Probability
In this paper we revisited the classical problem of max-sum equivalence of randomly weighted sums in two dimensions. In opposite to the most papers in literature, we consider that there exists some interdependence between the primary random variables, which is achieved by a combination of a new dependence structure with some two-dimensional heavy-tailed classes of distributions. Further, we introduce a new approach in two-dimensional regular varying distributions, that in contrast to well-established multivariate regularly varying distributions, is consistent with the multivariate non-linear single big jump principle. We study some closure properties of this, and of other two-dimensional classes. Our results contain the finite-time ruin probability in a two-dimensional discrete time risk model
title Joint tail of randomly weighted sums under generalized quasi asymptotic independence
topic Probability
url https://arxiv.org/abs/2408.01010