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Bias-corrected and robust estimation of the bivariate stable tail dependence function

Content Provider	Springer Nature Link
Author	Escobar Bach, Mikael Goegebeur, Yuri Guillou, Armelle You, Alexandre
Copyright Year	2016
Abstract	The stable tail dependence function gives a full characterisation of the extremal dependence between two or more random variables. In this paper, we propose an estimator for this function which is robust against outliers in the sample. The estimator is derived from a bivariate second-order tail model together with a proper transformation of the bivariate observations, and its asymptotic properties are studied under some suitable regularity conditions. Our estimation procedure depends on two parameters: $$\alpha $$ , which controls the trade-off between efficiency and robustness of the estimator, and a second-order parameter $$\tau $$ , which can be replaced by a fixed value or by an estimate. In case where $$\tau $$ has been replaced by the true value or by an external consistent estimator, our robust estimator is asymptotically unbiased, whereas in case where $$\tau $$ is mis-specified, one loses this property, but still our estimator performs quite well with respect to bias. The finite sample performance of our robust and bias-corrected estimator of the stable tail dependence function is examined on a simulation study involving uncontaminated and contaminated samples. In particular, its behavior is illustrated for different values of the pair $$(\alpha , \tau )$$ and is compared with alternative estimators from the extreme value literature.
Starting Page	284
Ending Page	307
Page Count	24
File Format	PDF
ISSN	11330686
Journal	Test
Volume Number	26
Issue Number	2
e-ISSN	18638260
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-11-19
Publisher Institution	Spanish Society of Statistics and Operations Research
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Multivariate extreme value statistics Stable tail dependence function Robustness Bias-correction Estimation Asymptotic properties Statistics of extreme values; tail inference Statistics Statistical Theory and Methods Statistics for Business/Economics/Mathematical Finance/Insurance
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Statistics, Probability and Uncertainty

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