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

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