DYNAMIC ASSET CORRELATIONS BASED ON VINES

Benjamin Poignard and Jean-David Fermanian

Econometric Theory, 2019, vol. 35, issue 1, 167-197

Abstract: We develop a new method for generating dynamics of conditional correlation matrices of asset returns. These correlation matrices are parameterized by a subset of their partial correlations, whose structure is described by a set of connected trees called “vine”. Partial correlation processes can be specified separately and arbitrarily, providing a new family of very flexible multivariate GARCH processes, called “vine-GARCH” processes. We estimate such models by quasi-maximum likelihood. We compare our models with DCC and GAS-type specifications through simulated experiments and we evaluate their empirical performances.

Date: 2019
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