Nicklas, Stephan (2013). Pair Constructions for High-Dimensional Dependence Models in Discrete and Continuous Time. PhD thesis, Universität zu Köln.

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Abstract

Modeling high-dimensional dependence structures with parametric dependence models is a challenging and important part in statistics. The dependence models that we discuss here are based on bivariate building blocks and we illustrate how to assemble these building blocks to multivariate dependence structures. In the first part of the dissertation, we recall the pair-copula construction for random variables, present different extensions and apply the concept in an empirical study. In the second part, we introduce the new pair-Lévy copula construction to model the jump dependence of high-dimensional Lévy processes. Moreover, we present simulation and estimation algorithms, conduct a simulation study and discuss various applications of this concept.

Item Type: Thesis (PhD thesis)
Creators:
CreatorsEmailORCID
Nicklas, Stephannicklas@wiso.uni-koeln.deUNSPECIFIED
URN: urn:nbn:de:hbz:38-51324
Subjects: General statistics
Uncontrolled Keywords:
KeywordsLanguage
Pair-copula construction, Vine copula, Lévy copula, Pair-Lévy copula construction, Multivariate Lévy processesEnglish
Faculty: Faculty of Management, Economy and Social Sciences
Divisions: Faculty of Management, Economics and Social Sciences > Economics > Econometrics and Statistics > Professorship for Economic and Social Statistics
Language: English
Date: 15 May 2013
Date of oral exam: 10 May 2013
Referee:
NameAcademic Title
Schmid, FriedrichUniv.-Prof. Dr.
Refereed: Yes
URI: http://kups.ub.uni-koeln.de/id/eprint/5132

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