Multivariate Hill Estimators
| Autor: | David Veredas, Yves Dominicy, Pauliina Ilmonen |
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| Rok vydání: | 2015 |
| Předmět: |
Statistics and Probability
Multivariate statistics Multivariate random variable 05 social sciences Estimator 01 natural sciences 010104 statistics & probability 0502 economics and business Generalized extreme value distribution Exponent Order (group theory) Applied mathematics 0101 mathematics Statistics Probability and Uncertainty Elliptical distribution 050205 econometrics Quantile Mathematics |
| Zdroj: | International Statistical Review. 85:108-142 |
| ISSN: | 0306-7734 |
| Popis: | Summary We propose two classes of semi-parametric estimators for the tail index of a regular varying elliptical random vector. The first one is based on the distance between a tail probability contour and the observations outside this contour. We denote it as the class of separating estimators. The second one is based on the norm of an arbitrary order. We denote it as the class of angular estimators. We show the asymptotic properties and the finite sample performances of both classes. We also illustrate the separating estimators with an empirical application to 21 worldwide financial market indexes. |
| Databáze: | OpenAIRE |
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