# Estimation of cluster functionals for regularly varying time series: sliding blocks estimators

@article{Cissokho2020EstimationOC, title={Estimation of cluster functionals for regularly varying time series: sliding blocks estimators}, author={Youssouph Cissokho and Rafal Kulik}, journal={arXiv: Statistics Theory}, year={2020} }

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.

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