Bootstrap approximation of tail dependence function
For estimating a rare event via the multivariate extreme value theory, the so-called tail dependence function has to be investigated (see [L. de Haan, J. de Ronde, Sea and wind: Multivariate extremes at work, Extremes 1 (1998) 7-45]). A simple, but effective estimator for the tail dependence function is the tail empirical distribution function, see [X. Huang, Statistics of Bivariate Extreme Values, Ph.D. Thesis, Tinbergen Institute Research Series, 1992] or [R. Schmidt, U. Stadtmüller, Nonparametric estimation of tail dependence, Scand. J. Stat. 33 (2006) 307-335]. In this paper, we first derive a bootstrap approximation for a tail dependence function with an approximation rate via the construction approach developed by [K. Chen, S.H. Lo, On a mapping approach to investigating the bootstrap accuracy, Probab. Theory Relat. Fields 107 (1997) 197-217], and then apply it to construct a confidence band for the tail dependence function. A simulation study is conducted to assess the accuracy of the bootstrap approach.
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Volume (Year): 99 (2008)
Issue (Month): 8 (September)
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References listed on IDEAS
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Other publications TiSEM
94429b0f-0175-452f-b41b-f, Tilburg University, School of Economics and Management.
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- Danielsson, J. & de Haan, L.F.M. & Peng, L. & de Vries, C.G., 2000. "Using a bootstrap method to choose the sample fraction in tail index estimation," Econometric Institute Research Papers EI 2000-19/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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