Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/56711 
Authors: 
Year of Publication: 
2012
Series/Report no.: 
SFB 649 Discussion Paper No. 2012-016
Publisher: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
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.
Subjects: 
statistics of stochastic processes
low frequency observed Lévy processes
nonparametric statistics
adaptive estimation
model selection with unknown variance
JEL: 
C14
Document Type: 
Working Paper

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