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Convergence to stable laws for multidimensional stochastic recursions: the case of regular matrices

Abstract

Given a sequence (Mn,Qn)n1(M_{n},Q_{n})_{n\ge 1} of i.i.d.\ random variables with generic copy (M,Q)GL(d,R)×Rd(M,Q) \in GL(d, \R) \times \R^d, we consider the random difference equation (RDE) Rn=MnRn1+Qn, R_{n}=M_{n}R_{n-1}+Q_{n}, n1n\ge 1, and assume the existence of κ>0\kappa >0 such that \lim_{n \to \infty}(\E{\norm{M_1 ... M_n}^\kappa})^{\frac{1}{n}} = 1 . We prove, under suitable assumptions, that the sequence Sn=R1+...+RnS_n = R_1 + ... + R_n, appropriately normalized, converges in law to a multidimensional stable distribution with index κ\kappa. As a by-product, we show that the unique stationary solution RR of the RDE is regularly varying with index κ\kappa, and give a precise description of its tail measure. This extends the prior work http://arxiv.org/abs/1009.1728v3 .Comment: 15 page

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