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