 Archimedean copula estimation and model selection via l1-norm symmetric distributionXiaomei Qu, Jie Zhou and Xiaojing Shen Insurance: Mathematics and Economics, 2010, vol. 46, issue 2, 406-414 Abstract: Based on the relationship between Archimedean copulas and l1-norm symmetric distributions, we propose a method to not only estimate the copula parameter but also select the copula model through the observation data in this paper. The strong consistency of the estimator is proved, and a Radial Information Criteria (RIC) is provided to select the appropriate Archimedean copula model fitting the data best. It can be extended to the multivariate cases conveniently because the selection is achieved by using the one-dimensional radial distribution to capture the dependence structure for multivariate data. The Monte Carlo simulation experiments illustrate that the proposed approach works well in parameter estimation and model selection for both bivariate and multivariate cases. An application in modelling the dependence structure of real stock indices is carried out with good performance as well. Keywords: Archimedean; copula; Archimedean; generator; l1-norm; symmetric; distribution; Radial; distribution (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:46:y:2010:i:2:p:406-414 Access Statistics for this article Insurance: Mathematics and Economics is currently edited by R. Kaas, Hansjoerg Albrecher, M. J. Goovaerts and E. S. W. Shiu More articles in Insurance: Mathematics and Economics from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.