Nonparametric adaptive estimation of linear functionals for low frequency observed Lévy processes

Johanna Kappus

No 2012-016, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

Abstract: For a Lévy process X having finite variation on compact sets and finite first moments, u (dx) = xv (dx) is a finite signed measure which completely describes the jump dynamics. We construct kernel estimators for linear functionals of u and provide rates of convergence under regularity assumptions. Moreover, we consider adaptive estimation via model selection and propose a new strategy for the data driven choice of the smoothing parameter.

Keywords: statistics of stochastic processes; low frequency observed Lévy processes; nonparametric statistics; adaptive estimation; model selection with unknown variance (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Date: 2012
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