Please use this identifier to cite or link to this item:
Title: Vine copulas as a way to describe and analyze multi-variate dependence in econometrics: Computational motivation and comparison with Bayesian networks and fuzzy approaches
Authors: Songsak Sriboonchitta
Jianxu Liu
Vladik Kreinovich
Hung T. Nguyen
Keywords: Computer Science
Issue Date: 1-Jan-2014
Abstract: In the last decade, vine copulas emerged as a new efficient techniques for describing and analyzing multi-variate dependence in econometrics; see, e.g., [1, 2, 3, 7, 9, 10, 11, 13, 14, 21]. Our experience has shown, however, that while these techniques have been successfully applied to many practical problems of econometrics, there is still a lot of confusion and misunderstanding related to vine copulas. In this paper, we provide a motivation for this new technique from the computational viewpoint. We show that other techniques used to described dependence - Bayesian networks and fuzzy techniques - can be viewed as a particular case of vine copulas. © Springer International Publishing Switzerland 2014.
ISSN: 21945357
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.

Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.