Nonparametric estimation for a class of Lévy processes
Song Chen,
Aurore Delaigle and
Peter Hall
Journal of Econometrics, 2010, vol. 157, issue 2, 257-271
Abstract:
We consider estimation for a class of Lévy processes, modelled as a sum of a drift, a symmetric stable process and a compound Poisson process. We propose a nonparametric approach to estimating unknown parameters of our model, including the drift, the scale and index parameters in the stable law, the mean of the Poisson process and the underlying jump size distribution. We show that regression and nonparametric deconvolution methods, based on the empirical characteristic function, can be used for inference. Interesting connections are shown to exist between properties of our estimators and of those found in conventional deconvolution.
Keywords: Deconvolution; Empirical; characteristic; function; Errors; in; variables; Financial; data; Inverse; problem; Jump; process; Levy; process; Rates; of; convergence; Regression; Stable; law (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304-4076(10)00002-3
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:157:y:2010:i:2:p:257-271
Access Statistics for this article
Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson
More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().