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Performance of Utility Based Hedges

Author

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  • John Cotter

    (UCD School of Business, University College Dublin)

  • Jim Hanly

    (UCD School of Business, University College Dublin)

Abstract

Hedgers as investors are concerned with both risk and return; however the literature has generally neglected the role of both returns and investor risk aversion 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. We apply our approach to two asset classes, equity and energy, for three different hedging horizons, daily,weekly and monthly. We find significant differences between the minimum variance and utility based hedges and their attendant performance in-sample for all frequencies. However out of sample performance differences persist for the monthly frequency only.

Suggested Citation

  • John Cotter & Jim Hanly, 2014. "Performance of Utility Based Hedges," Working Papers 201404, Geary Institute, University College Dublin.
  • Handle: RePEc:ucd:wpaper:201404
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    References listed on IDEAS

    as
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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. 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.
    6. Barbi, Massimiliano & Romagnoli, Silvia, 2018. "Skewness, basis risk, and optimal futures demand," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 14-29.
    7. 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.
    8. 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.
    9. 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.
    10. George E. Halkos & Apostolos S. Tsirivis, 2019. "Energy Commodities: A Review of Optimal Hedging Strategies," Energies, MDPI, Open Access Journal, vol. 12(20), pages 1-19, October.

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    More about this item

    Keywords

    Energy; Hedging Performance; Utility; 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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