Dynamic Asset Correlations Based on Vines

Benjamin Poignard and Jean-David Fermanian ()
Additional contact information
Benjamin Poignard: ENSAE, CREST and University Paris-Dauphine
Jean-David Fermanian: ENSAE and CREST

No 2014-46, Working Papers from Center for Research in Economics and Statistics

Abstract: We develop a new method for generating dynamics of conditional correlation matrices between asset returns. These correlation matrices will be parameterized by a subset of their partial correlations, whose structure will be described by an undirected graph called \vine". Since such partial correlation processes can be speci ed separately, our approach provides very exible and potentially parsimonious multivariate processes. We introduce the so-called\vine-GARCH" class of processes and describe a quasi-maximum likelihood (QML) estimation procedure. Compared to other usual techniques, particularly for the Dynamic Conditional Correlation family, inference is simpler and can be led equation per equation. We compare our models with some DCC-type speci cations through some simulated experiments and we evaluate their empirical performances by exploiting a database of daily stock returns.

Keywords: Dynamic Conditional Correlations; Multivariate GARCH; Partial Correlations; Quasi Maximum Likelihood Estimator; Regular vine. (search for similar items in EconPapers)
Pages: 60
Date: 2014-02
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://crest.science/RePEc/wpstorage/2014-46.pdf Crest working paper version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:crs:wpaper:2014-46

Access Statistics for this paper

More papers in Working Papers from Center for Research in Economics and Statistics Contact information at EDIRC.
Bibliographic data for series maintained by Secretariat General () and Murielle Jules Maintainer-Email : murielle.jules@ensae.Fr.