An M-Estimator for Tail Dependence in Arbitrary Dimensions
AbstractConsider a random sample in the max-domain of attraction of a multivariate extreme value distribution such that the dependence structure of the attractor belongs to a parametric model. A new estimator for the unknown parameter is defined as the value that minimises the distance between a vector of weighted integrals of the tail dependence function and their empirical counterparts. The minimisation problem has, with probability tending to one, a unique, global solution. The estimator is consistent and asymptotically normal. The spectral measures of the tail dependence models to which the method applies can be discrete or continuous. Examples demonstrate the applicability and the performance of the method.
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Bibliographic InfoPaper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2011-013.
Date of creation: 2011
Date of revision:
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Web page: http://center.uvt.nl
asymptotic statistics; factor model; M-estimation; multivariate extremes; tail dependence;
Other versions of this item:
- Einmahl, J.H.J. & Krajina, A. & Segers, J., 2012. "An M-estimator for tail dependence in arbitrary dimensions," Open Access publications from Tilburg University urn:nbn:nl:ui:12-5539332, Tilburg University.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-04-09 (All new papers)
- NEP-ECM-2011-04-09 (Econometrics)
- NEP-RMG-2011-04-09 (Risk Management)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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