Average Conditional Correlation and Tree Structures for Multivariate GARCH Models
Journal
Journal of Forecasting
ISSN
0277-6693
ISSN-Digital
1099-131X
Type
journal article
Date Issued
2006-12-01
Author(s)
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.
Language
English
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Wiley
Publisher place
Chichester
Volume
25
Number
8
Start page
579
End page
600
Pages
22
Subject(s)
Eprints ID
36416