Abstract

We study the recurrence/transience phase transition for Markov chains on $\mathbb{R}_+$, $\mathbb{R}$, and $\mathbb{R}^2$ whose increments have heavy tails with exponent in $(1,2)$ and asymptotically zero mean. This is the infinite-variance analogue of the classical Lamperti problem. On $\mathbb{R}_+$, for example, we show that if the tail of the positive increments is about $c y^{-\alpha}$ for an exponent $\alpha \in (1,2)$ and if the drift at $x$ is about $b x^{-\gamma}$, then the critical regime has $\gamma = \alpha -1$ and recurrence/transience is determined by the sign of $b + c\pi \textrm{cosec} (\pi \alpha)$. On $\mathbb{R}$ we classify whether transience is directional or oscillatory, and extend an example of Rogozin \& Foss to a class of transient martingales which oscillate between $\pm \infty$. In addition to our recurrence/transience results, we also give sharp results on the existence/non-existence of moments of passage times.

Highlights

  • Lamperti’s problem describes how the asymptotic behaviour of a non-homogeneous random walk (Markov chain) ξn on R+ whose increments have at least 2 moments is determined by the interplay between the increment moment functions μ(x) := E[ξn+1 − ξn | ξn = x], and s2(x) := E[(ξn+1 − ξn)2 | ξn = x]

  • We show that in the heavy-tailed case it is the interplay between the drift and the tails of the increments that determines the asymptotic behaviour

  • Ξ is recurrent by Theorem 2.1(i), and Theorem 2.3(i) shows that the critical exponent for τa is 1/α ∈ (1/2, 1); in the case of a spatially homogeneous random walk, this fact is essentially contained in a result of Doney [3]

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Summary

Introduction

We show (Theorem 2.7 below) that the transience in this case is oscillatory and give general conditions for behaviour of this kind, and show how an asymptotically zero drift perturbs the picture. These include criteria for directional and oscillatory transience. Technical results on integral computations needed for our Lyapunov-function estimates are collected in the Appendix

Notation
Walks on the half line
Walks on the whole line: heavier outward tails
Walks on the whole line: heavier inward tails
Walks in higher dimensions: an example
Walks in higher dimensions: an open problem
Semimartingale criteria for real-valued processes
Preliminaries
Lyapunov function on the half line
Lyapunov functions on the whole line
Proofs of main results
The whole line
A An integration by parts formula
B Some useful integrals
Full Text
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