On almost sure limit theorems for heavy-tailed products of long-range dependent linear processes

TL;DR

This paper establishes almost sure limit theorems for products of long-range dependent linear processes with heavy tails, extending classical results to complex dependent and heavy-tailed data.

Contribution

It develops Marcinkiewicz strong laws for heavy-tailed products of long-range dependent linear processes, including multivariate cases, highlighting the decoupling of dependence and tail effects.

Findings

Convergence rate is determined by the dominant effect of either long-range dependence or heavy tails.

The Marcinkiewicz strong law is extended to multivariate linear processes.

Heavy tails and long-range dependence can coexist without affecting each other's impact on convergence.

Abstract

Marcinkiewicz strong law of large numbers, ${n^{-\frac1p}}\sum_{k=1}^{n} (d_{k}- d)\rightarrow 0\ $ almost surely with $p\in(1,2)$, are developed for products $d_k=\prod_{r=1}^s x_k^{(r)}$, where the $x_k^{(r)} = \sum_{l=-\infty}^{\infty}c_{k-l}^{(r)}\xi_l^{(r)}$ are two-sided linear processes with coefficients $\{c_l^{(r)}\}_{l\in \mathbb{Z}}$ and i.i.d. zero-mean innovations $\{\xi_l^{(r)}\}_{l\in \mathbb{Z}}$. The decay of the coefficients $c_l^{(r)}$ as $|l|\to\infty$, can be slow enough for $\{x_k^{(r)}\}$ to have long memory while $\{d_k\}$ can have heavy tails. The long-range dependence and heavy tails for $\{d_k\}$ are handled simultaneously and a decoupling property shows the convergence rate is dictated by the worst of long-range dependence and heavy tails, but not their combination. The Marcinkiewicz strong law of large numbers is also extended to the multivariate linear process case.