Analyzing and forecasting volatility spillovers, asymmetries and hedging in major oil markets

• Published in: Energy economics Vol. 32; no. 6; pp. 1445 - 1455
• Main Authors: Chang, Chia-Lin, McAleer, Michael, Tansuchat, Roengchai
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.11.2010; Elsevier; Elsevier Science Ltd
• Series: Energy Economics
• Subjects: Applied sciences; Asymmetries; Asymmetry; Conditional correlation; Correlation; Correlation analysis; Crude oil; Crude oil prices; Economic data; Energy; Energy economics; Exact sciences and technology; Forecasts; Fossil fuels and derived products; General, economic and professional studies; Hedging; International markets; Market analysis; Markets; Mathematical analysis; Mathematical models; Methodology. Modelling; Multivariate GARCH; Oil; Oil market; Price instability; Spillovers; Stochastic models; Studies; Vectors (mathematics); Volatility; Volatility spillovers; Volatility spillovers Multivariate GARCH Conditional correlation Asymmetries Hedging; ANE, North Sea; Middle East; ASW, USA, Texas; ISW, Oman; ISW, United Arab Emirates, Dubai; C22; C32; G32; Hedging; Conditional correlation; Asymmetries; G17; Multivariate GARCH; Volatility spillovers
• ISSN: 0140-9883; 1873-6181
• DOI: 10.1016/j.eneco.2010.04.014

Crude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over a decade, and is crucial for forecasting volatility and Value-at-Risk (VaR). There are four major benchmarks in the international oil market, namely West Texas Intermediate (USA), Brent (North Sea), Dubai/Oman (Middle East), and Tapis (Asia-Pacific), which are likely to be highly correlated. This paper analyses the volatility spillover and asymmetric effects across and within the four markets, using three multivariate GARCH models, namely the constant conditional correlation (CCC), vector ARMA–GARCH (VARMA–GARCH) and vector ARMA–asymmetric GARCH (VARMA–AGARCH) models. A rolling window approach is used to forecast the 1-day ahead conditional correlations. The paper presents evidence of volatility spillovers and asymmetric effects on the conditional variances for most pairs of series. In addition, the forecast conditional correlations between pairs of crude oil returns have both positive and negative trends. Moreover, the optimal hedge ratios and optimal portfolio weights of crude oil across different assets and market portfolios are evaluated in order to provide important policy implications for risk management in crude oil markets.