Almost sure subexponential decay rates of scalar Ito-Volterra equations.

The paper studies the subexponential convergence of solutions of scalar Itˆo-Volterra equations. First, we consider linear equations with an instantaneous multiplicative noise term with intensity . If the kernel obeys lim t!1 k0(t)/k(t) = 0, and another nonexponential decay criterion, and the solution X tends to zero as t ! 1, then limsup t!1 log |X(t)| log(tk(t)) = 1 − (||), a.s. where the random variable (||) ! 0 as ! 1 a.s. We also prove a decay result for equations with a superlinear diffusion coefficient at zero. If the deterministic equation has solution which is uniformly asymptotically stable, and the kernel is subexponential, the decay rate of the stochastic problem is exactly the same as that of the underlying deterministic problem

A sufficient condition for the subexponential asymptotics of GI/G/1-type Markov chains with queueing applications

The main contribution of this paper is to present a new sufficient condition for the subexponential asymptotics of the stationary distribution of a GI/GI/1-type Markov chain without jumps from level "infinity" to level zero. For simplicity, we call such Markov chains {\it GI/GI/1-type Markov chains without disasters} because they are often used to analyze semi-Markovian queues without "disasters", which are negative customers who remove all the customers in the system (including themselves) on their arrivals. In this paper, we demonstrate the application of our main result to the stationary queue length distribution in the standard BMAP/GI/1 queue. Thus we obtain new asymptotic formulas and prove the existing formulas under weaker conditions than those in the literature. In addition, applying our main result to a single-server queue with Markovian arrivals and the $(a,b)$-bulk-service rule (i.e., MAP/${\rm GI}^{(a,b)}$/1 queue), we obatin a subexponential asymptotic formula for the stationary queue length distribution.Comment: Submitted for revie

Subexponential instability implies infinite invariant measure

We study subexponential instability to characterize a dynamical instability of weak chaos. We show that a dynamical system with subexponential instability has an infinite invariant measure, and then we present the generalized Lyapunov exponent to characterize subexponential instability.Comment: 7 pages, 5 figure

Asymptotic tail behavior of phase-type scale mixture distributions

We consider phase-type scale mixture distributions which correspond to distributions of a product of two independent random variables: a phase-type random variable $Y$ and a nonnegative but otherwise arbitrary random variable $S$ called the scaling random variable. We investigate conditions for such a class of distributions to be either light- or heavy-tailed, we explore subexponentiality and determine their maximum domains of attraction. Particular focus is given to phase-type scale mixture distributions where the scaling random variable $S$ has discrete support --- such a class of distributions has been recently used in risk applications to approximate heavy-tailed distributions. Our results are complemented with several examples.Comment: 18 pages, 0 figur

Two-dimensional ruin probability for subexponential claim size

We analyse the asymptotics of ruin probabilities of two insurance companies (or two branches of the same company) that divide between them both claims and premia in some specified proportions when the initial reserves of both companies tend to infinity and generic claim size is subexponential