Average conditional correlation and tree structures for multivariate GARCH models
Giovanni Barone-Adesi and
Francesco Audrino ()
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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
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.
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Persistent link: /RePEc:jof:jforec:v:25:y:2006:i:8:p:579-600
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