Average conditional correlation and tree structures for multivariate GARCH models

Average conditional correlation and tree structures for multivariate GARCH models

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Article ID: iaor20081535
Country: United Kingdom
Volume: 25
Issue: 8
Start Page Number: 579
End Page Number: 600
Publication Date: Dec 2006
Journal: International Journal of Forecasting
Authors: ,
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.

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