Low-frequency estimation of continuous-time moving average Lévy processes

Abstract

In this paper we study the problem of statistical inference for a continuoustime moving average Lévy process of the form Zt=∫ℝκ(t-s)dLs, t∈ℝ with a deterministic kernel κ and a Lévy process L. Especially the estimation of the Lévy measure v of L from low-frequency observations of the process Z is considered. We construct a consistent estimator, derive its convergence rates and illustrate its performance by a numerical example. On the technical level, the main challenge is to establish a kind of exponential mixing for continuous-time moving average Lévy processes.