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A Note on Nonparametric Estimation of Bivariate Tail Dependence
Year Of Publication: 2012
Month Of Publication: July
Pages: 8
Download Count: 3
View Count: 846
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 5-31-2014
Publisher: Administrator
Summary
Nonparametric estimation of tail dependence can be based on a standardization of the marginals if their cumulative distribution functions are known. In this paper it is shown to be asymptotically more efficient if the additional knowledge of the marginals is ignored and estimators are based on ranks. The discrepancy between the two estimators is shown to be substantial for the popular Clayton model. A brief simulation study indicates that the asymptotic conclusions transfer to finite samples.
A later version of this document is published in Statistics & Risk Modeling (volume 31, number 2) June 2014,
http://dx.doi.org/10.1515/strm-2013-1143
Author(s)
Bucher, Axel Sign in to follow this author
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