CD-vine model for capturing complex dependence

Ozan Evkaya O., Yozgatlıgil C., Kestel S. A.

JOURNAL OF APPLIED STATISTICS, vol.48, no.13-15, pp.2406-2420, 2021 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 48 Issue: 13-15
  • Publication Date: 2021
  • Doi Number: 10.1080/02664763.2020.1834519
  • Journal Name: JOURNAL OF APPLIED STATISTICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, ABI/INFORM, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Veterinary Science Database, zbMATH
  • Page Numbers: pp.2406-2420
  • Keywords: Mixture model, C-vine, D-vine, CD-vine mixture, stock market indices, DECOMPOSITION
  • Middle East Technical University Affiliated: Yes

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.