Bivariate extension of the Pickands–Balkema–de Haan theorem

نویسنده

  • Mario V. Wüthrich
چکیده

We prove a two-dimensional version of the famous Pickands–Balkema–de Haan theorem of extreme value theory. The bivariate random variables are generated using the copula language. This representation of dependence structures allows to derive asymptotic results for bivariate excess distributions.  2003 Elsevier SAS. All rights reserved. Résumé Une version en dimension 2 du célèbre théorème de Pickands–Balkema–de Haan sur la théorie des valeurs extrêmes est démontrée. Les variables aléatoires bivariées sont générées en utilisant le langage des copules. Cette représentation des structures de dépendance permet de dériver des résultats asymptotiques pour les distributions d’excès bivariées.  2003 Elsevier SAS. All rights reserved. MSC: 62E20; 62H20; 62P05

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Estimating Bivariate Tail: a copula based approach

This paper deals with the problem of estimating the tail of a bivariate distribution function. To this end we develop a general extension of the POT (PeaksOver-Threshold) method, mainly based on a two-dimensional version of the Pickands-Balkema-de Haan Theorem. We introduce a new parameter that describes the nature of the tail dependence, and we provide a way to estimate it. We construct a two-...

متن کامل

Limiting Dependence Structures for Tail Events, with Applications to Credit Derivatives

Dependence structures for bivariate extremal events are analyzed using particular types of copula. Weak convergence results for copulas along the lines of the Pickands–Balkema– de Haan theorem provide limiting dependence structures for bivariate tail events. A characterization of these limiting copulas is also provided by means of invariance properties. The results obtained are applied to the c...

متن کامل

Estimating a bivariate tail: A copula based approach

This paper deals with the problem of estimating the tail of a bivariate distribution function. To this end we develop a general extension of the POT (peaks-over-threshold) method, mainly based on a two-dimensional version of the Pickands–Balkema–de Haan Theorem. We introduce a new parameter that describes the nature of the tail dependence, and we provide a way to estimate it. We construct a two...

متن کامل

Estimating Bivariate Tails

In this paper we consider the general problem of estimating the tail of a bivariate distribution. An extension of the threshold method for extreme values is developed, using a two-dimensional version of the Pickands-Balkema-de Hann Theorem. We construct a two-dimensional tail estimator and we provide its asymptotic properties. The dependence structure between the marginals is described by a cop...

متن کامل

An entropic view of Pickands' theorem

It is shown that distributions arising in Rényi-Tsallis maximum entropy setting are related to the Generalized Pareto Distributions (GPD) that are widely used for modeling the tails of distributions. The relevance of such modelization, as well as the ubiquity of GPD in practical situations follows from Balkema-De Haan-Pickands theorem on the distribution of excesses (over a high threshold). We ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2002