English

Asymptotic results for tail probabilities of sums of dependent heavy-tailed random variables

Probability 2013-02-28 v1

Abstract

Let {X1,X2,...}\{X_1, X_2, ... \} be a sequence of dependent heavy-tailed random variables with distributions F1,F2,...F_1, F_2,... on (,)(-\infty,\infty), and let τ\tau be a nonnegative integer-valued random variable independent of the sequence {Xk,k1}\{X_k, k \ge 1\}. In this framework, we study the asymptotic behavior of the tail probabilities of the quantities X(n)=max1knXkX_{(n)} = \max_{1\le k \le n} X_k, Sn=k=1nXkS_n =\sum_{k=1}^n X_k and S(n)=max1knSkS_{(n)}=\max_{1\le k\le n} S_k for n>1n>1, and for those of their randomized versions X(τ)X_{(\tau)}, SτS_{\tau} and S(τ)S_{(\tau)}. We also consider applications of the results obtained to some commonly-used risk processes.

Keywords

Cite

@article{arxiv.1101.4056,
  title  = {Asymptotic results for tail probabilities of sums of dependent heavy-tailed random variables},
  author = {Kam Chuen Yuen and Chuancun Yin},
  journal= {arXiv preprint arXiv:1101.4056},
  year   = {2013}
}