Risk Management in Oil Market: A Comparison between Multivariate GARCH Models and Copula-based Models

Authors

Faculty of Economics, University of Tehran, Tehran, Iran.

Abstract

High price volatility and risk are the main features of commodity markets. One way to reduce this risk is to apply the hedging policy in future contracts. In this regard, in this paper, we will calculate the optimal hedging ratios for OPEC oil. In this study, besides the multivariate GARCH models, for the first time, we use conditional copula models for modeling the dependence structure between OPEC oil and WTI future contract with different maturities and estimating hedging ratios for OPEC oil by using WTI future contracts. The results of this study show that the dependence structure between OPEC oil and WTI future contract in three maturities is asymmetric. In addition, results indicate that during the studied period (2003-2017), Copula-based models have more efficient in applying the hedging policy than multivariate GARCH models. The average optimal hedge ratio increases with a rise in the maturity of contracts. On the other hand, the highest performance of hedging strategies was achieved by using WTI futures contracts with six months’ maturity.

Keywords

References

Ang, A., & Chen, J. (2002). Asymmetric Correlations of Equity Portfolios. Journal of Financial Economics, 63, 443-494
Ansari Ardali, Z., & Mousavi, M., & Kurdbacheh, H. (2017). Estimating Optimal Hedge Ratio and Comparing Their Effectiveness in the Natural Gas Market. Quarterly Journal of Energy Economics, 13(53), 35-60.
Chang, K. (2012). The Time-varying and Asymmetric Dependence between Crude Oil Spot and Futures Markets: Evidence from the Mixture Copula-based ARJI–GARCH Model. Economic Modelling, 29, 2298–2309.
Chang, C., McAleer, M., & Tansuchat, R. (2011). Crude Oil Hedging Strategies Using Dynamic Multivariate GARCH. Energy Economics, 33(5), 912–923.
Doifli, I., & Ghorbel, A. (2015). Optimal Hedging Strategy with Futures Oil Markets via FI-EGARCH Copula Model. American Journal of Finance and Accounting, 4(1), 1-28.
Ghorbel, A., & Trabelsi, A. (2012). Optimal Dynamic Hedging Strategy with Futures Oil Markets via FIEGARCH-EVT Copula Models. International Journal of Managerial and Financial Accounting, 4, 1-28.
Haigh, M. S., & Holt, M. (2002). Crack Spread Hedging: Accounting for Time-varying Spillovers in the Energy Futures Markets. Journal of Applied Econometrics, 17, 269–289.
Hsu, C. C., Tseng, C. P., & Wang, Y. H. (2008). Dynamic Hedging with Futures: A Copula Based GARCH Model. Journal of Futures Markets, 28(11), 1095–1116
Khodadadian, B. (2010). Hedging of Oil Price Risk Using Future Contracts: Case Study of Iran (Unpublished Master's Thesis). University of Tarbiat Modarres, Tehran.
Kotkatvuori-Örnberg, J. (2016). Dynamic Conditional Copula Correlation and Optimal Hedge Ratios with Currency Futures. International Review of Financial Analysis, 47(C), 60-69.
Lai, Y., Chen, W. S., & Gerlach, R. (2009). Optimal Dynamic Hedging via Copula-Threshold GARCH Models. Mathematics and Computers in Simulation, 79, 2609–2624.
Lai, Y. S. (2018). Dynamic Hedging with Futures: A Copula-based GARCH Model with High-frequency Data. Review of Derivatives Research, 21, 307–329.
Lee, H. T. (2009). A Copula-based Regime Switching GARCH for Optimal Futures Hedging. Journal of Future Market, 29, 946–972.
Liu, P., Vedenov, D., & Power, G. J. (2017). Is Hedging the Crack Spread No Longer All it is Cracked up to be? Energy Economics, 63, 31-40.
Mehrara, M., & Naebi, F. (2017). Assessing the Effectiveness of Fixed and Dynamic Hedge Ratio for Gold Coin Future Contracts of Iranian Commodity Exchangers. Economic Research, 52(3), 711-734.
Nasserian, M., & Esmaeeli, A. (2014). Hedging of Iran's crude oil price risk by futures contracts in the NYMEX using the mv-GARCH method (unpublished master's thesis). Islamic Azad University, Central Tehran Branch.
Nikoloulopoulos, A. K., Joe, H., & Li, H. (2012). Vine Copulas with Asymmetric Tail Dependence and Applications to Financial Return Data. Computational Statistics & Data Analysis, 56(11), 3659-3673.
Ornberg, J. (2016). Dynamic Conditional Copula Correlation and Optimal Hedge Ratios with Currency Futures. International Review of Financial Analysis, 47, 60-69.
Patton, A. J. (2006). Modeling Asymmetric Exchange Rate Dependence. International Economic Review, 47, 527-556.
Sukcharoen, K., & Leatham, D. J. (2017). Hedging Downside Risk of Oil Refineries: A Vine Copula Approach. Energy Economics, 66, 493-507.
Iranian Economic Review
Volume 24, Issue 2
May 2020
Pages 489-513

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