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Time Varying Risk Aversion: An Application to Energy Hedging

Author

Listed:
  • John Cotter

    (School of Business, University College Dublin)

  • Jim Hanly

    (School of Accounting and Finance, Dublin Institute of Technology)

Abstract

Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of energy hedgers. We find that the risk aversion based hedges differ significantly from simpler OLS hedges. When implemented in-sample, risk aversion hedges for short hedgers outperform the OLS hedge ratio in a utility based comparison.

Suggested Citation

  • John Cotter & Jim Hanly, 2010. "Time Varying Risk Aversion: An Application to Energy Hedging," Working Papers 201007, Geary Institute, University College Dublin.
    • Handle: RePEc:ucd:wpaper:201007
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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. Conlon, Thomas & Cotter, John, 2013. "Downside risk and the energy hedger's horizon," Energy Economics, Elsevier, vol. 36(C), pages 371-379.
    3. Antonio Díaz & Carlos Esparcia, 2021. "Dynamic optimal portfolio choice under time-varying risk aversion," International Economics, CEPII research center, issue 166, pages 1-22.
    4. Ayoub, Mahmoud & Qadan, Mahmoud, 2024. "Ambiguity and risk in the oil market," Economic Modelling, Elsevier, vol. 132(C).
    5. Martínez, Beatriz & Torró, Hipòlit, 2015. "European natural gas seasonal effects on futures hedging," Energy Economics, Elsevier, vol. 50(C), pages 154-168.
    6. Othieno, Ferdinand & Biekpe, Nicholas, 2019. "Estimating the conditional equity risk premium in African frontier markets," Research in International Business and Finance, Elsevier, vol. 47(C), pages 538-551.
    7. Furió, Dolores & Torró, Hipòlit, 2020. "Optimal hedging under biased energy futures markets," Energy Economics, Elsevier, vol. 88(C).
    8. Lihui Tian & Haifeng Wu & Qichang Xie, 2025. "The impact of FOMC announcements on cryptocurrency risk spillover across different market conditions," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 161(3), pages 1035-1069, August.
    9. Cotter, John & Hanly, Jim, 2015. "Performance of utility based hedges," Energy Economics, Elsevier, vol. 49(C), pages 718-726.
    10. George E. Halkos & Apostolos S. Tsirivis, 2019. "Energy Commodities: A Review of Optimal Hedging Strategies," Energies, MDPI, vol. 12(20), pages 1-19, October.
    11. Cotter, John & Hanly, Jim, 2012. "A utility based approach to energy hedging," Energy Economics, Elsevier, vol. 34(3), pages 817-827.
    12. Gong, Xu & Wen, Fenghua & Xia, X.H. & Huang, Jianbai & Pan, Bin, 2017. "Investigating the risk-return trade-off for crude oil futures using high-frequency data," Applied Energy, Elsevier, vol. 196(C), pages 152-161.
    13. 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).
    14. Sato, Ayano & Nakata, Hayato & Percy, Jay, 2024. "Time-variant safe haven currencies," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 316-328.
    15. Díaz, Antonio & Escribano, Ana & Esparcia, Carlos, 2024. "Sustainable risk preferences on asset allocation: a higher order optimal portfolio study," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).

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    Keywords

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    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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