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Time-varying risk aversion: An application to energy hedging

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  • Cotter, John
  • Hanly, Jim

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

  • Cotter, John & Hanly, Jim, 2010. "Time-varying risk aversion: An application to energy hedging," Energy Economics, Elsevier, vol. 32(2), pages 432-441, March.
    • Handle: RePEc:eee:eneeco:v:32:y:2010:i:2:p:432-441
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    Cited by:

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    3. Díaz, Antonio & Esparcia, Carlos, 2021. "Dynamic optimal portfolio choice under time-varying risk aversion," International Economics, Elsevier, vol. 166(C), pages 1-22.
    4. Furió, Dolores & Torró, Hipòlit, 2020. "Optimal hedging under biased energy futures markets," Energy Economics, Elsevier, vol. 88(C).
    5. 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.
    6. Conlon, Thomas & Cotter, John, 2013. "Downside risk and the energy hedger's horizon," Energy Economics, Elsevier, vol. 36(C), pages 371-379.
    7. Ayoub, Mahmoud & Qadan, Mahmoud, 2024. "Ambiguity and risk in the oil market," Economic Modelling, Elsevier, vol. 132(C).
    8. Cotter, John & Hanly, Jim, 2015. "Performance of utility based hedges," Energy Economics, Elsevier, vol. 49(C), pages 718-726.
    9. Cotter, John & Hanly, Jim, 2012. "A utility based approach to energy hedging," Energy Economics, Elsevier, vol. 34(3), pages 817-827.
    10. 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).
    11. 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.
    12. George E. Halkos & Apostolos S. Tsirivis, 2019. "Energy Commodities: A Review of Optimal Hedging Strategies," Energies, MDPI, vol. 12(20), pages 1-19, October.
    13. 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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    More about this item

    Keywords

    Energy Hedging Risk management Risk aversion Forecasting;

    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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