Nonparametric estimation for Lévy processes from low-frequency observations

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dc.creatorNeumann, Michael H.
dc.creatorReiss, Markus
dc.date2007-09-13
dc.date2008-05-29
dc.date.accessioned2026-07-07T09:41:11Z
dc.date.available2026-07-07T09:41:11Z
dc.descriptionWe suppose that a Lévy process is observed at discrete time points. A rather general construction of minimum-distance estimators is shown to give consistent estimators of the Lévy-Khinchine characteristics as the number of observations tends to infinity, keeping the observation distance fixed. For a specific $C^2$-criterion this estimator is rate-optimal. The connection with deconvolution and inverse problems is explained. A key step in the proof is a uniform control on the deviations of the empirical characteristic function on the whole real line.
dc.description24 pages, 2 figures
dc.identifierhttps://arxiv.org/abs/0709.2007
dc.identifierhttp://arxiv.org/abs/0709.2007
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/161738
dc.subjectStatistics Theory
dc.subjectProbability
dc.subjectMethodology
dc.subject62G15; 62M15
dc.titleNonparametric estimation for Lévy processes from low-frequency observations
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