This paper estimates univariate and multivariate conditional volatility and conditional
correlation models of spot, forward and futures returns from three major benchmarks of
international crude oil markets, namely Brent, WTI and Dubai, to aid in risk diversification.
Conditional correlations are estimated using the CCC model of Bollerslev (1990), VARMAGARCH
model of Ling and McAleer (2003), VARMA-AGARCH model of McAleer et al.
(2009), and DCC model of Engle (2002). The paper also presents the ARCH and GARCH
effects for returns and shows the presence of significant interdependences in the conditional
volatilities across returns for each market. The estimates of volatility spillovers and
asymmetric effects for negative and positive shocks on conditional variance suggest that
VARMA-GARCH is superior to the VARMA-AGARCH model. In addition, the DCC model
gives statistically significant estimates for the returns in each market, which shows that
constant conditional correlations do not hold in practice. |