Multivariate Dynamic Copula Models: Parameter Estimation and Forecast Evaluation

Matthias D. Aepli (), Karl Frauendorfer (), Roland Fuess () and Florentina Paraschiv
Authors registered in the RePEc Author Service: Roland Füss ()

No 1513, Working Papers on Finance from University of St. Gallen, School of Finance

Abstract: This paper introduces multivariate dynamic copula models to account for the time-varying dependence structure in asset portfolios. We firstly enhance the flexibility of this structure by modeling regimes with multivariate mixture copulas. In our second approach, we derive dynamic elliptical copulas by applying the dynamic conditional correlation model (DCC) to multivariate elliptical copulas. The best-ranked copulas according to both in-sample fit and out-of-sample forecast performance indicate the importance of accounting for time-variation. The superiority of multivariate dynamic Clayton and Student-t models further highlight that positive tail dependence as well as the capability of capturing asymmetries in the dependence structure are crucial features of a well-fitting model for an equity portfolio.

Keywords: Multivariate dynamic copulas; regime-switching copulas; dynamic conditional correlation (DCC) model; forecast performance; tail dependence. (search for similar items in EconPapers)
JEL-codes: C32 C51 C53 (search for similar items in EconPapers)
Pages: 47 pages
Date: 2015-07
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-ger
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:usg:sfwpfi:2015:13

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