Statistical inference for time-changed Lévy processes via Mellin transform approach

Denis Belomestny and John Schoenmakers

Stochastic Processes and their Applications, 2016, vol. 126, issue 7, 2092-2122

Abstract: Given a Lévy process (Lt)t≥0 and an independent nondecreasing process (time change) (T(t))t≥0, we consider the problem of statistical inference on T based on low-frequency observations of the time-changed Lévy process LT(t). Our approach is based on the genuine use of Mellin and Laplace transforms. We propose a consistent estimator for the density of the increments of T in a stationary regime, derive its convergence rates and prove the optimality of the rates. It turns out that the convergence rates heavily depend on the decay of the Mellin transform of T. Finally, the performance of the estimator is analysed via a Monte Carlo simulation study.

Keywords: Time-changed Lévy processes; Low-frequency observations; Mellin transform; Laplace transform (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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DOI: 10.1016/j.spa.2016.01.005

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