Dynamic copula models for multivariate high-frequency data in finance
نویسندگان
چکیده
The stylized facts of univariate high-frequency data in finance are well known; see Dacorogna et al. (2001). In Breymann et al. (2003) we analyzed bivariate high frequency forex data as a function of the sampling frequency, however treating the data as iid. In the present paper, using the data from Breymann et al. (2003), we model the dynamics as GARCH type processes and investigate the stylized facts of the bivariate residuals. As a function of the sampling frequency, we test for tail-dependence and ellipticity. We also investigate clustering of extremes and change-points.
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