Modelling Dynamic Conditional Correlations in the Volatility of Spot and Forward Oil Price Returns

This paper estimates the dynamic conditional correlations in the returns on Tapis oil spot and onemonth forward prices for the period 2 June 1992 to 16 January 2004, using recently developed multivariate conditional volatility models, namely the Constant Conditional Correlation Multivariate GARCH (CCCMGARCH) model of Bollerslev [1990], Vector Autoregressive Moving Average – GARCH (VARMAGARCH) model of Ling and McAleer [2003], VARMA – Asymmetric GARCH (VARMA-AGARCH) model of Chan et al. [2002], and the Dynamic Conditional Correlation (DCC) model of Engle [2002]. The multivariate estimates show that the ARCH and GARCH effects for spot (forward) returns are significant in the conditional volatility model for spot (forward) returns. Moreover, there are significant interdependences in the conditional volatilities between the spot and forward markets. The multivariate asymmetric effects are significant for both spot and forward returns. The calculated constant conditional correlations between the conditional volatilities of spot and forward returns using CCC-GARCH(1,1), VAR(1)-GARCH(1,1) and VAR(1)-AGARCH(1,1) are virtually identical. Finally, the estimates of the two DCC parameters are statistically significant, which makes it clear that the assumption of constant conditional correlation is not supported empirically.