A bootstrap-based method to achieve optimality on estimating the extreme-value index

Estimators of the extreme-value index are based on a set of upper order statistics. We present an adaptive method to choose the number of order statistics involved in an optimal way, balancing variance and bias components. Recently this has been achieved for the similar but somewhat less involved case of regularly varying tails (Drees and Kaufmann(1997); Danielsson et al.(1996)). The present paper follows the line of proof of the last mentioned paper.

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Year of publication:	2000-05-25
Authors:	Draisma, G. ; Haan, L.F.M. de ; Peng, L. ; Pereira, T.T.
Institutions:	Erasmus University Rotterdam, Econometric Institute
Subject:	moment estimator \| Pickands estimator \| bootstrap \| mean squared error

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Extent:	application/pdf
Series:	Econometric Institute Report. - ISSN 1566-7294.
Type of publication:	Book / Working Paper
Notes:	The text is part of a series RePEc:dgr:eureir Number EI 2000-18/A
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008484088