Cluster based inference for extremes of time series

Holger Drees, Anja Janßen and Sebastian Neblung

Stochastic Processes and their Applications, 2021, vol. 142, issue C, 1-33

Abstract: 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.

Keywords: Cluster of extremes; Extreme value analysis; Projection estimator; Spectral tail process; Time series; Uniform central limit theorems (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.spa.2021.07.012

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