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...

This paper studies transmission of international energy price shocks to various sectors in the Australian stock market. We take the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) approach to modeling volatility and gather evidence that energy price shocks transmit to the price indices of various sectors classified by the global industry classification standard (...

Since the launch of Bitcoin, there has been a lot controversy surrounding what asset class it is. Several authors recognize potential cryptocurrencies but also certain deviations with respect to functions conventional currency. Instead, Bitcoin’s diversifying factor and its high return have generated attention portfolio managers. In this context, understanding how volatility is explained critic...

It is well-known that the estimated GARCH dynamics exhibit common patterns. Starting from this fact we extend the Dynamic Conditional Correlation (DCC) model by allowing for a clustering structure of the univariate GARCH parameters. The model can be estimated in two steps, the first devoted to the clustering structure, and the second focusing on correlation parameters. Differently from the trad...