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Performance of utility based hedges

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  • Cotter, John
  • Hanly, Jim

Abstract

Hedgers as investors are concerned with both risk and return. However when measuring hedging performance, the role of returns and investor risk aversion has generally been neglected in the literature, by its focus on minimum variance hedging. In this paper we address this by using utility based performance metrics to evaluate the hedging effectiveness of utility based hedges for hedgers with both moderate and high risk aversion together with the more traditional minimum variance approach. To examine this for an energy hedger, we apply our approach to WTI Crude Oil, for three different hedging horizons, daily, weekly and monthly. We find significant differences between the minimum variance and utility based hedging strategies in-sample for all frequencies. However performance differentials between the different strategies are small and not economically significant. Out-of-sample results support these findings across all frequencies.

Suggested Citation

  • Cotter, John & Hanly, Jim, 2015. "Performance of utility based hedges," Energy Economics, Elsevier, vol. 49(C), pages 718-726.
  • Handle: RePEc:eee:eneeco:v:49:y:2015:i:c:p:718-726
    DOI: 10.1016/j.eneco.2015.04.004
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    1. John Cotter & Jim Hanly, 2006. "Reevaluating hedging performance," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(7), pages 677-702, July.
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    Citations

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    Cited by:

    1. Martínez, Beatriz & Torró, Hipòlit, 2018. "Hedging spark spread risk with futures," Energy Policy, Elsevier, vol. 113(C), pages 731-746.
    2. Martínez, Beatriz & Torró, Hipòlit, 2015. "European natural gas seasonal effects on futures hedging," Energy Economics, Elsevier, vol. 50(C), pages 154-168.
    3. Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
    4. Shrestha, Keshab & Subramaniam, Ravichandran & Peranginangin, Yessy & Philip, Sheena Sara Suresh, 2018. "Quantile hedge ratio for energy markets," Energy Economics, Elsevier, vol. 71(C), pages 253-272.
    5. Vedenov, Dmitry & Power, Gabriel J., 2022. "We don't need no fancy hedges! Or do we?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    6. Demiralay, Sercan & Gencer, Hatice Gaye & Bayraci, Selcuk, 2022. "Carbon credit futures as an emerging asset: Hedging, diversification and downside risks," Energy Economics, Elsevier, vol. 113(C).
    7. Shrestha, Keshab & Subramaniam, Ravichandran & Rassiah, Puspavathy, 2017. "Pure martingale and joint normality tests for energy futures contracts," Energy Economics, Elsevier, vol. 63(C), pages 174-184.
    8. Barbi, Massimiliano & Romagnoli, Silvia, 2018. "Skewness, basis risk, and optimal futures demand," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 14-29.
    9. Cui, Yan & Feng, Yun, 2020. "Composite hedge and utility maximization for optimal futures hedging," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 15-32.
    10. Kuang, Wei, 2022. "The economic value of high-frequency data in equity-oil hedge," Energy, Elsevier, vol. 239(PA).
    11. Xianling Ren & Xinping Yu, 2024. "Hedging performance analysis of energy markets: Evidence from copula quantile regression," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(3), pages 432-450, March.
    12. Martínez, Beatriz & Torró, Hipòlit, 2018. "Analysis of risk premium in UK natural gas futures," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 621-636.
    13. Wang, Yudong & Geng, Qianjie & Meng, Fanyi, 2019. "Futures hedging in crude oil markets: A comparison between minimum-variance and minimum-risk frameworks," Energy, Elsevier, vol. 181(C), pages 815-826.
    14. George E. Halkos & Apostolos S. Tsirivis, 2019. "Energy Commodities: A Review of Optimal Hedging Strategies," Energies, MDPI, vol. 12(20), pages 1-19, October.
    15. Yan Hu & Jian Ni, 2024. "A deep learning‐based financial hedging approach for the effective management of commodity risks," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(6), pages 879-900, June.

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    More about this item

    Keywords

    Hedging performance; Utility; Energy; Risk aversion;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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