  Cluster indices describe extremal behaviour of stationary time series. We
consider their sliding blocks estimators. Using a modern theory of
multivariate, regularly varying time series, we obtain central limit theorems
under conditions that can be easily verified for a large class of models. In
particular, we show that in the Peak over Threshold framework, sliding and
disjoint blocks estimators have the same limiting variance.
