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arXiv · 1912.08584

Method of moments estimators for the extremal index of a stationary time series

Axel Bücher·Tobias Jennessen
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Abstract

The extremal index $\theta$, a number in the interval $[0,1]$, is known to be a measure of primal importance for analyzing the extremes of a stationary time series. New rank-based estimators for $\theta$ are proposed which rely on the construction of approximate samples from the exponential distribution with parameter $\theta$ that is then to be fitted via the method of moments. The new estimators are analyzed both theoretically as well as empirically through a large-scale simulation study. In specific scenarios, in particular for time series models with $\theta \approx 1$, they are found to be superior to recent competitors from the literature.

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Axel Bücher, Tobias Jennessen. 2019-12-18. Method of moments estimators for the extremal index of a stationary time series. https://arxiv.org/abs/1912.08584

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