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

Laurent Gardes and Stéphane Girard

Journal of Multivariate Analysis, 2008, vol. 99, issue 10, 2368-2388

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.

Keywords: 62G32; 62G05; 62E20; Conditional; tail; index; Extreme; values; Nonparametric; estimation; Moving; window (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (12)

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