Davis and Mikosch [7] introduced the extremogram as a flexible quantitative
tool for measuring various types of extremal dependence in a stationary time
series. There we showed some standard statistical properties of the sample
extremogram. A major difficulty was the construction of credible confidence
bands for the extremogram. In this paper, we employ the stationary bootstrap to
overcome this problem. Moreover, we introduce the cross extremogram as a
measure of extremal serial dependence between two or more time series. We also
study the extremogram for return times between extremal events. The use of the
stationary bootstrap for the extremogram and the resulting interpretations are
illustrated in several univariate and multivariate financial time series
examples.