 CD-vine model for capturing complex dependenceO. Ozan Evkaya, Ceylan Yozgatlıgil and A. Sevtap Selcuk-Kestel Journal of Applied Statistics, 2021, vol. 48, issue 13-15, 2406-2420 Abstract: Copula based finite mixture models allow us to capture the dependence between random variables more flexibly. Although bivariate case of finite mixture models has been commonly studied, limited efforts have been spent on finite mixture of vines. Instead of using classical mixture models, it is possible to incorporate C-vines into the D-vine model (CD-vine) to understand both the dependence among the variables over different time points. The aim of this study is to create a CD-vine mixture model expressing the dependencies between variables in temporal order. To achieve this, cumulative distribution function values generated within the time components are tied together with D-vine probabilistically. With this approach, dependence structure between variables at each time point is explained by C-vine and the dependence among the time points is captured by the D-vine model. The performance of the proposed CD-vine model is validated using simulated data and applied on four stock market indices. Date: 2021 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:48:y:2021:i:13-15:p:2406-2420 Ordering information: This journal article can be ordered from DOI: 10.1080/02664763.2020.1834519 Access Statistics for this article Journal of Applied Statistics is currently edited by Robert Aykroyd More articles in Journal of Applied Statistics from Taylor & Francis Journals |
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