On a Threshold Multivariate GARCH Model

This paper proposes a threshold multivariate GARCH model (Threshold MGARCH) which integrates threshold nonlinearity, mean and volatility asymmetries and time-varying correlation in financial markets. The main feature of this model is that the mean, volatility and time-varying correlation can be governed by different threshold variables with different number of regimes. Estimation is performed using Markov Chain Monte Carlo methods. Forecasts of volatility and value at risk can be generated from the predictive distributions. The proposed methodology is illustrated using both simulated and actual international market with high dimensional data.