### Abstract

Original language | English |
---|---|

Place of Publication | Tilburg |

Publisher | Econometrics |

Volume | 2011-013 |

Publication status | Published - 2011 |

### Publication series

Name | CentER Discussion Paper |
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Volume | 2011-013 |

### Fingerprint

### Keywords

- asymptotic statistics
- factor model
- M-estimation
- multivariate extremes
- tail dependence

### Cite this

*An M-Estimator for Tail Dependence in Arbitrary Dimensions*. (CentER Discussion Paper; Vol. 2011-013). Tilburg: Econometrics.

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**An M-Estimator for Tail Dependence in Arbitrary Dimensions.** / Einmahl, J.H.J.; Krajina, A.; Segers, J.

Research output: Working paper › Discussion paper › Other research output

TY - UNPB

T1 - An M-Estimator for Tail Dependence in Arbitrary Dimensions

AU - Einmahl, J.H.J.

AU - Krajina, A.

AU - Segers, J.

N1 - Subsequently published in Annals of Statistics (2012)

PY - 2011

Y1 - 2011

N2 - Consider 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.

AB - Consider 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.

KW - asymptotic statistics

KW - factor model

KW - M-estimation

KW - multivariate extremes

KW - tail dependence

M3 - Discussion paper

VL - 2011-013

T3 - CentER Discussion Paper

BT - An M-Estimator for Tail Dependence in Arbitrary Dimensions

PB - Econometrics

CY - Tilburg

ER -