Asymptotics for aggregated interdependent multivariate subexponential claims with general investment returns

[2507.23713] Asymptotics for aggregated interdependent multivariate subexponential claims with general investment returns Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Mathematics > Probability arXiv:2507.23713 (math) [Submitted on 31 Jul 2025 ( v1 ), last revised 5 Jul 2026 (this version, v3)] Title: Asymptotics for aggregated interdependent multivariate subexponential claims with general investment returns Authors: Zhangting Chen , Dimitrios G. Konstantinides , Charalampos D. Passalidis View a PDF of the paper titled Asymptotics for aggregated interdependent multivariate subexponential claims with general investment returns, by Zhangting Chen and 2 other authors View PDF HTML (experimental) Abstract: This paper investigates asymptotic estimates for the entrance probability of the discounted aggregate claim vector from a multivariate renewal risk model into some rare set. We provide asymptotic results for the entrance probability on both finite and infinite time horizons under various assumptions regarding the stochastic price process of the investment portfolio, the distribution class of claim vectors, and the dependence structure among the claim vectors. We note that the main results extend beyond the class of multivariate regular variation. Furthermore, we introduce two dependence structures to model the dependence among the claim vectors. In particular, our results are new even in the one-dimensional subcase. Subjects: Probability (math.PR) Cite as: arXiv:2507.23713 [math.PR] (or arXiv:2507.23713v3 [math.PR] for this version) https://doi.org/10.48550/arXiv.2507.23713 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Charalampos D. Passalidis [ view email ] [v1] Thu, 31 Jul 2025 16:42:32 UTC (31 KB) [v2] Sat, 11 Apr 2026 14:08:49 UTC (30 KB) [v3] Sun, 5 Jul 2026 15:54:05 UTC (30 KB) Full-text links: Access Paper: View a PDF of the paper titled Asymptotics for aggregated interdependent multivariate subexponential claims with general investment returns, by Zhangting Chen and 2 other authors View PDF HTML (experimental) TeX Source view license Current browse context: math.PR < prev | next > new | recent | 2025-07 Change to browse by: math References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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