Published online by Cambridge University Press: 17 April 2018
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.
The authors are grateful for very helpful discussions with Christian Francq and Jean-Michel Zakoïan. They thank numerous seminar participants, particularly at the 11th World Congress of the Econometric Society, Computational and Financial Econometrics 2015, the Bachelier seminar, the Oberwolfach copulae conference 2015, etc. Numerous remarks of the AE and of two anonymous referees have allowed significant improvements of the article. The authors have been supported by the labex Ecodec.