|
High-level dependence in time series models
Fasen, Vicky
;
Klüppelberg, Claudia
;
Schlather, Martin
|
DOI:
|
https://doi.org/10.1007/s10687-009-0084-8
|
|
URL:
|
https://link.springer.com/article/10.1007/s10687-0...
|
|
Additional URL:
|
https://www.semanticscholar.org/paper/High-level-d...
|
|
Document Type:
|
Article
|
|
Year of publication:
|
2010
|
|
The title of a journal, publication series:
|
Extremes : Statistical Theory and Applications in Science, Engineering and Economics
|
|
Volume:
|
13
|
|
Issue number:
|
1
|
|
Page range:
|
1-33
|
|
Place of publication:
|
Dordrecht [u.a.]
|
|
Publishing house:
|
Springer Science + Business Media
|
|
ISSN:
|
1386-1999 , 1572-915X
|
|
Publication language:
|
English
|
|
Institution:
|
School of Business Informatics and Mathematics > Applied Stochastics (Schlather 2012-)
|
|
Subject:
|
510 Mathematics
|
|
Keywords (English):
|
ARCH, COGARCH, Extreme cluster, Extreme dependence measure, Extremal index, Extreme value theory, GARCH, Linear model, Multivariate regular variation, Nonlinear model, Lévy-driven Ornstein–Uhlenbeck process, Random recurrence equation
|
|
Abstract:
|
We present several notions of high-level dependence for stochastic processes, which have appeared in the literature. We calculate such measures for discrete and continuous-time models, where we concentrate on time series with heavy-tailed marginals, where extremes are likely to occur in clusters.
Such models include linear models and solutions to random recurrence equations; in particular, discrete and continuous-time moving average and
(G)ARCH processes. To illustrate our results we present a small simulation study.
|
 | Dieser Datensatz wurde nicht während einer Tätigkeit an der Universität Mannheim veröffentlicht, dies ist eine Externe Publikation. |
 Search Authors in
You have found an error? Please let us know about your desired correction here: E-Mail
Actions (login required)
 |
Show item |
|
|
