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Title:

Parametric estimation of a bivariate stable Lévy process

Document type:
Zeitschriftenaufsatz
Author(s):
Esmaeili, H., Klüppelberg, C.
Abstract:
We propose a parametric model for a bivariate stable Lévy process based on a Lévy copula as a dependence model.We estimate the parameters of the full bivariate model by maximum likelihood estimation. As an observation scheme we assume that we observe all jumps larger than some ε> 0 and base our statistical analysis on the resulting compound Poisson process. We derive the Fisher information matrix and prove asymptotic normality of all estimates, when the truncation point ε tends to 0. A sim...     »
Keywords:
Lévy copula, maximum likelihood estimation, dependence structure, Fisher information matrix, multivariate stable process, parameter estimation.
Journal title:
Journal of Multivariate Analysis
Year:
2011
Journal volume:
102
Journal issue:
5
Pages contribution:
918–930
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.1016/j.jmva.2011.01.008
Semester:
SS 11
Format:
Text
 BibTeX