Average conditional correlation and tree structures for multivariate GARCH models

Giovanni Barone-Adesi and Francesco Audrino ()
Additional contact information
Giovanni Barone-Adesi: Institute of Finance, University of Lugano, Switzerland, Postal: Institute of Finance, University of Lugano, Switzerland

Journal of Forecasting, 2006, vol. 25, issue 8, pages 579-600

Abstract: We propose a simple class of multivariate GARCH models, allowing for time-varying conditional correlations. Estimates for time-varying conditional correlations are constructed by means of a convex combination of averaged correlations (across all series) and dynamic realized (historical) correlations. Our model is very parsimonious. Estimation is computationally feasible in very large dimensions without resorting to any variance reduction technique. We back-test the models on a six-dimensional exchange-rate time series using different goodness-of-fit criteria and statistical tests. We collect empirical evidence of their strong predictive power, also in comparison to alternative benchmark procedures.  Copyright © 2006 John Wiley & Sons, Ltd.

Downloads: (external link)
http://hdl.handle.net/10.1002/for.1014 Link to full text; subscription required (text/html)

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

Access Statistics for this article

Journal of Forecasting is edited by Derek W. Bunn

More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Series data maintained by Christopher F. Baum ().