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Document type:
Zeitschriftenaufsatz 
Author(s):
Esmaeili, H., Klüppelberg, C. 
Title:
Parametric estimation of a bivariate stable Lévy process 
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....    »
 
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:
Pages contribution:
918–930 
Reviewed:
ja 
Language:
en 
Semester:
SS 11 
Format:
Text