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Managing Energy Price Risk using Futures Contracts: A Comparative Analysis

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  • Jim Hanly

Abstract

This paper carries out a comparative analysis of managing energy risk through futures hedging, for energy market participants across a broad dataset that encompasses the largest and most actively traded energy products. Uniquely, we carry out a hedge comparison using a variety of risk measures including Variance, Value at risk (VaR), and Expected Shortfall as well as a utility based performance metric for two different investor horizons; weekly and monthly. We find that hedging is effective across the spectrum of risk measures we employ. We also find significant differences in both the hedging strategies and the hedging effectiveness of different energy assets. Better performance is found for West Texas Intermediate Oil and Heating Oil while the poorest performer in hedging terms is Natural Gas.

Suggested Citation

  • Jim Hanly, 2017. "Managing Energy Price Risk using Futures Contracts: A Comparative Analysis," The Energy Journal, , vol. 38(3), pages 93-112, May.
    • Handle: RePEc:sae:enejou:v:38:y:2017:i:3:p:93-112
    DOI: 10.5547/01956574.38.3.jhan
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    References listed on IDEAS

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    1. Lien, Donald & Yang, Li, 2008. "Asymmetric effect of basis on dynamic futures hedging: Empirical evidence from commodity markets," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 187-198, February.
    2. Ted Juhl & Ira G. Kawaller & Paul D. Koch, 2012. "The Effect of the Hedge Horizon on Optimal Hedge Size and Effectiveness When Prices are Cointegrated," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(9), pages 837-876, September.
    3. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(4), pages 535-551, December.
    4. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
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