Journal of Energy Markets

Volume 2 Number 4, Winter 2009/10

Modeling conditional correlations for risk diversification in crude oil markets

Chia-Lin Chang
Department of Applied Economics, National Chung Hsing University, 250 Kuo Kuang Road, Taichung 402, Taiwan; email: changchialin@nchu.edu.tw

Michael McAleer
Econometric Institute, Erasmus University Rotterdam, PO Box 1738, 3000 DR, Rotterdam, The Netherlands; email: michael.mcaleer@gmail.com and Tinbergen Institute, Burgemeester Oudlaan 50, 3062 PA, Rotterdam, The Netherlands and Center for International Research on the Japanese Economy (CIRJE), Faculty of Economics, University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo 113-0033, Japan

Roengchai Tansuchat
Faculty of Economics, Maejo University, Phrao Road, Sansai, Chiang Mai 50290, Thailand; email: roengchaitan@gmail.com

This paper estimates univariate and multivariate conditional volatility and conditional correlation models of spot, forward and futures returns from three major benchmarks of the international crude oil markets, namely Brent,West Texas Intermediate and Dubai, to aid with the process of risk diversification. Conditional correlations are estimated using Bollerslev's constant conditional correlation model, Ling and McAleer's vector autoregressive moving average-generalized autoregressive conditional heteroscedasticity (VARMA-GARCH) model, the vector autoregressive moving average-asymmetric generalized autoregressive conditional heteroscedasticity (VARMA-AGARCH) model of McAleer et al and a dynamic conditional correlation model by Engle. The paper also presents the autoregressive conditional heteroscedasticity and generalized autoregressive conditional heteroscedasticity effects for returns and shows the presence of significant interdependencies in the conditional volatilities across returns for each market.

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