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arXiv · 1104.0763

A moving window approach for nonparametric estimation of the conditional tail index

L. Gardes·S. Girard
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Abstract

We present a nonparametric family of estimators for the tail index of a Pareto-type distribution when covariate information is available. Our estimators are based on a weighted sum of the log-spacings between some selected observations. This selection is achieved through a moving window approach on the covariate domain and a random threshold on the variable of interest. Asymptotic normality is proved under mild regularity conditions and illustrated for some weight functions. Finite sample performances are presented on a real data study.

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L. Gardes, S. Girard. 2011-04-05. A moving window approach for nonparametric estimation of the conditional tail index. https://arxiv.org/abs/1104.0763

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