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Estimating The Skewness In Discretely Observed Lévy Processes

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  • Woerner, Jeannette H.C.

Abstract

We consider models for financial data by Lévy processes, including hyperbolic, normal inverse Gaussian, and Carr, Geman, Madan, and Yor (CGMY) processes. They are given by their Lévy triplet (μ(θ),σ2,eθxg(x)ν(dx)), where μ denotes the drift, σ2 the diffusion, and eθxg(x)ν(dx) the Lévy measure, and the unknown parameter θ models the skewness of the process. We provide local asymptotic normality results and construct efficient estimators for the skewness parameter θ taking into account different discrete sampling schemes.I thank Prof. Dr. L. Rüschendorf for his steady encouragement, the referees for helpful comments, and the German National Scholarship Foundation for financial support.

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  • Woerner, Jeannette H.C., 2004. "Estimating The Skewness In Discretely Observed Lévy Processes," Econometric Theory, Cambridge University Press, vol. 20(5), pages 927-942, October.
    • Handle: RePEc:cup:etheor:v:20:y:2004:i:05:p:927-942_20
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    Cited by:

    1. Emanuele Taufer, 2008. "Characteristic function estimation of non-Gaussian Ornstein-Uhlenbeck processes," DISA Working Papers 0805, Department of Computer and Management Sciences, University of Trento, Italy, revised 07 Jul 2008.
    2. Chen, Song X. & Delaigle, Aurore & Hall, Peter, 2010. "Nonparametric estimation for a class of Lévy processes," Journal of Econometrics, Elsevier, vol. 157(2), pages 257-271, August.

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