The extremogram and the cross-extremogram for a bivariate GARCH(1,1) process
Abstract
In this paper, we derive some asymptotic theory for the extremogram and cross-extremogram of a bivariate GARCH(1,1) process. We show that the tails of the components of a bivariate GARCH(1,1) process may exhibit power law behavior but, depending on the choice of the parameters, the tail indices of the components may differ. We apply the theory to 5-minute return data of stock prices and foreign exchange rates. We judge the fit of a bivariate GARCH(1,1) model by considering the sample extremogram and cross-extremogram of the residuals. The results are in agreement with the iid hypothesis of the two-dimensional innovations sequence. The cross-extremograms at lag zero have a value significantly distinct from zero. This fact points at some strong extremal dependence of the components of the innovations.
Cite
@article{arxiv.1505.05385,
title = {The extremogram and the cross-extremogram for a bivariate GARCH(1,1) process},
author = {Muneya Matsui and Thomas Mikosch},
journal= {arXiv preprint arXiv:1505.05385},
year = {2015}
}
Comments
21 pages, 31 figures,