Multivariate Threshold Models: TVARs and TVECMs

Testing and Modeling Multivariate Threshold Models

Threshold autoregressive models in which the process is piecewise linear in the threshold space have received much attention in recent years. In this paper, we use predictive residuals to construct a test statistic to detect threshold nonlinearity in a vector time series and propose a procedure for building a multivariate threshold model. The thresholds and the model are selected jointly based ...

15 Threshold Effects in Multivariate Error Correction Models

We propose a testing procedure for assessing the presence of threshold effects in nonstationary vector autoregressive models with or without cointegration. Our approach involves first testing whether the long-run impact matrix characterizing the VECM type representation of the VAR switches according to the magnitude of some threshold variable and is valid regardless of whether the system is pur...

Multivariate Threshold Methods

Risk Management in Oil Market: A Comparison between Multivariate GARCH Models and Copula-based Models

H igh price volatility and the risk are the main features of commodity markets. One way to reduce this risk is to apply the hedging policy by future contracts. In this regard, in this paper, we will calculate the optimal hedging ratios for OPEC oil. In this study, besides the multivariate GARCH models, for the first time we use conditional copula models for modelling dependence struc...

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 u...