Titlebook: Copulae in Mathematical and Quantitative Finance; Proceedings of the W Piotr Jaworski,Fabrizio Durante,Wolfgang Karl H?rd Conference procee

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Strategic Planning of Spectrum and Services,ied intervals of homogenous dependence. This paper summarizes the important aspects of (V)MEM, its estimation, and a sequential test for changes in the dependence structure. The techniques are applied in an empirical example.

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Modeling Time-Varying Dependencies Between Positive-Valued High-Frequency Time Series,ied intervals of homogenous dependence. This paper summarizes the important aspects of (V)MEM, its estimation, and a sequential test for changes in the dependence structure. The techniques are applied in an empirical example.

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Vector Generalized Linear Models: A Gaussian Copula Approach,ation studies, we compare the VGLM to the popular generalized estimating equations (GEEs) approach. The simulation results indicate that the VGLMs provide more efficient inference for the regression coefficients than the GEEs. The VGLM is also illustrated via real-data examples.

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An Overview of the Goodness-of-Fit Test Problem for Copulas,egral transformations (PITs), on Kendall’s dependence function, etc., and some corresponding reductions of dimension techniques. The problems of finding asymptotic distribution-free test statistics and the calculation of reliable .-values are discussed. Some particular cases, like convenient tests f

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Modeling Time-Varying Dependencies Between Positive-Valued High-Frequency Time Series,ng volumes. The parametric estimation of the corresponding multivariate model, the so-called vector MEM (VMEM), requires a specification of the joint error term distribution, which is due to the lack of multivariate distribution functions on . defined via a copula. Maximum likelihood estimation is b

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