Rare-Event Simulation for Stochastic Recurrence Equations with Heavy-Tailed Innovations

In this article, rare-event simulation for stochastic recurrence equations of the form Xn+1 = A(n+1)X(n) + Bn+1, X-0 = 0 is studied, where {A(n);n >= 1} and {B-n;n >= 1} are independent sequences consisting of independent and identically distributed real-valued random variables. It is assumed that the tail of the distribution of B-1 is regularly varying, whereas the distribution of A(1) has a suitably light tail. The problem of efficient estimation, via simulation, of quantities such as P{X-n > b} and P{sup(k <= n) X-k > b} for large b and n is studied. Importance sampling strategies are investigated that provide unbiased estimators with bounded relative error as b and n tend to infinity.