Dynamic Asset Correlations Based on Vines

57 Pages Posted: 7 Feb 2015 Last revised: 10 Nov 2016

See all articles by Benjamin Poignard

Benjamin Poignard

ENSAE-CREST; Université Paris Dauphine

Jean-David Fermanian


Date Written: May 2016


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 specified separately, our approach provides very flexible 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 specifications 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

JEL Classification: C32, C58

Suggested Citation

Poignard, Benjamin and Fermanian, Jean-David, Dynamic Asset Correlations Based on Vines (May 2016). Available at SSRN: https://ssrn.com/abstract=2561029 or http://dx.doi.org/10.2139/ssrn.2561029

Benjamin Poignard

ENSAE-CREST ( email )

15 Boulevard Gabriel Peri
Malakoff Cedex, 1 92245

Université Paris Dauphine ( email )

Place du Maréchal de Tassigny
Paris, Cedex 16 75775

Jean-David Fermanian (Contact Author)

Ensae-Crest ( email )

92245 Malakoff Cedex
+33141176538 (Phone)
141176538 (Fax)

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