Arbeitspapier
Multivariate tail copula: modeling and estimation
In general, risk of an extreme outcome in financial markets can be expressed as a function of the tail copula of a high-dimensional vector after standardizing marginals. Hence it is of importance to model and estimate tail copulas. Even for moderate dimension, nonparametrically estimating a tail copula is very inefficient and fitting a parametric model to tail copulas is not robust. In this paper we propose a semi-parametric model for tail copulas via an elliptical copula. Based on this model assumption, we propose a novel estimator for the tail copula, which proves favourable compared to the empirical tail copula, both theoretically and empirically
- Sprache
-
Englisch
- Erschienen in
-
Series: Discussion Paper ; No. 468
- Thema
-
Asymptotic normality
Dependence modeling
Elliptical copula
Elliptical distribution
Multivariate modeling
Regular variation
Tail copula
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Klüppelberg, Claudia
Kuhn, Gabriel
Peng, Liang
- Ereignis
-
Veröffentlichung
- (wer)
-
Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen
- (wo)
-
München
- (wann)
-
2006
- DOI
-
doi:10.5282/ubm/epub.1836
- Handle
- URN
-
urn:nbn:de:bvb:19-epub-1836-8
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Klüppelberg, Claudia
- Kuhn, Gabriel
- Peng, Liang
- Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen
Entstanden
- 2006
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