arbiter
JournalsAccount

A new approach in two-dimensional heavy-tailed distributions

Dimitrios G. Konstantinides & Charalampos D. Passalidis

Annals of Actuarial Science2025https://doi.org/10.1017/s1748499525000041article
AJG 1ABDC A
Weight
0.41

Abstract

We consider a new approach in the definition of two-dimensional heavy-tailed distributions. Specifically, we introduce the classes of two-dimensional long-tailed, of two-dimensional dominatedly varying, and of two-dimensional consistently varying distributions. Next, we define the closure property with respect to two-dimensional convolution and to joint max-sum equivalence in order to study whether they are satisfied by these classes. Further, we examine the joint-tail behavior of two random sums, under generalized tail asymptotic independence. Afterward, we study the closure property under scalar product and two-dimensional product convolution, and by these results, we extended our main result in the case of jointly randomly weighted sums. Our results contained some applications where we establish the asymptotic expression of the ruin probability in a two-dimensional discrete-time risk model.

2 citations

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1017/s1748499525000041

Or copy a formatted citation

@article{dimitrios2025,
  title        = {{A new approach in two-dimensional heavy-tailed distributions}},
  author       = {Dimitrios G. Konstantinides & Charalampos D. Passalidis},
  journal      = {Annals of Actuarial Science},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1017/s1748499525000041},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

A new approach in two-dimensional heavy-tailed distributions

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.