Cluster based inference for extremes of time series

We introduce a new type of estimator for the spectral tail process regularly varying time series. The approach is based on characterizing invariance property process, which incorporated into via projection technique. show uniform asymptotic normality this estimator, both in case known and unknown index regular variation. In simulation study procedure shows more stable performance than previously proposed estimators.