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Dynamic Asset Correlations Based On Vines

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  • Poignard, Benjamin
  • Fermanian, Jean-David

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.

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  • Poignard, Benjamin & Fermanian, Jean-David, 2019. "Dynamic Asset Correlations Based On Vines," Econometric Theory, Cambridge University Press, vol. 35(1), pages 167-197, February.
    • Handle: RePEc:cup:etheor:v:35:y:2019:i:01:p:167-197_00
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    Cited by:

    1. Shanshan Jiang & Jie Wang & Ruiting Dong & Yutong Li & Min Xia, 2023. "Systemic Risk with Multi-Channel Risk Contagion in the Interbank Market," Sustainability, MDPI, vol. 15(3), pages 1-24, February.
    2. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.

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