A General Multivariate Threshold GARCH Model with Dynamic Conditional Correlations

University of St.Gallen, Department of Economics, Discussion Paper No. 2007-25

34 Pages Posted: 14 Apr 2005

See all articles by Fabio Trojani

Fabio Trojani

Swiss Finance Institute; University of Geneva

Francesco Audrino

University of St. Gallen

Date Written: April 2007

Abstract

Revised version of paper no. 2005-04.

We propose a new multivariate GARCH model with Dynamic Conditional Correlations that extends previous models by admitting multivariate thresholds in conditional volatilities and correlations. The model estimation is feasible in large dimensions and the positive deniteness of the conditional covariance matrix is easily ensured by the structure of the model. Thresholds in conditional volatilities and correlations are estimated from the data, together with all other model parameters. We study the performance of our model in three distinct applications to US stock and bond market data. Even if the conditional volatility functions of stock returns exhibit pronounced GARCH and threshold features, their conditional correlation dynamics depends on a very simple threshold structure with no local GARCH features. We obtain a similar result for the conditional correlations between government and corporate bond returns. On the contrary, we ¯nd both threshold and GARCH structures in the conditional correlations between stock and government bond returns. In all applications, our model improves signi¯cantly the in-sample and out-of-sample forecasting power for future conditional correlations with respect to other relevant multivariate GARCH models.

Keywords: Multivariate GARCH models, Dynamic conditional correlations, Tree-structured GARCH models

JEL Classification: C12, C13, C51, C53, C61

Suggested Citation

Trojani, Fabio and Audrino, Francesco, A General Multivariate Threshold GARCH Model with Dynamic Conditional Correlations (April 2007). University of St.Gallen, Department of Economics, Discussion Paper No. 2007-25, Available at SSRN: https://ssrn.com/abstract=691204 or http://dx.doi.org/10.2139/ssrn.691204

Fabio Trojani (Contact Author)

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

University of Geneva ( email )

Geneva, Geneva
Switzerland

Francesco Audrino

University of St. Gallen ( email )

Bodanstrasse 6
St. Gallen, CH-9000
Switzerland

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