Copula-Based Factor Models for Multivariate Asset Returns
AbstractRecently, several copula-based approaches have been proposed for modeling stationary multivariate time series. All of them are based on vine copulas, and they differ in the choice of the regular vine structure. In this article, we consider a copula autoregressive (COPAR) approach to model the dependence of unobserved multivariate factors resulting from two dynamic factor models. However, the proposed methodology is general and applicable to several factor models as well as to other copula models for stationary multivariate time series. An empirical study illustrates the forecasting superiority of our approach for constructing an optimal portfolio of U.S. industrial stocks in the mean-variance framework. View Full-Text
Share & Cite This Article
Ivanov, E.; Min, A.; Ramsauer, F. Copula-Based Factor Models for Multivariate Asset Returns. Econometrics 2017, 5, 20.
Ivanov E, Min A, Ramsauer F. Copula-Based Factor Models for Multivariate Asset Returns. Econometrics. 2017; 5(2):20.Chicago/Turabian Style
Ivanov, Eugen; Min, Aleksey; Ramsauer, Franz. 2017. "Copula-Based Factor Models for Multivariate Asset Returns." Econometrics 5, no. 2: 20.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.