IDEAS home Printed from https://ideas.repec.org/p/ucd/wpaper/201106.html
   My bibliography  Save this paper

A Utility Based Approach to Energy Hedging

Author

Listed:
  • John Cotter

    (University College Dublin)

  • Jim Hanly

    (Dublin Institute of Technology)

Abstract

A key issue in the estimation of energy hedges is the hedgers’ attitude towards risk which is encapsulated in the form of the hedgers’ utility function. However, the literature typically uses only one form of utility function such as the quadratic when estimating hedges. This paper addresses this issue by estimating and applying energy market based risk aversion to commonly applied utility functions including log, exponential and quadratic, and we incorporate these in our hedging frameworks. We find significant differences in the optimal hedge strategies based on the utility function chosen.

Suggested Citation

  • John Cotter & Jim Hanly, 2011. "A Utility Based Approach to Energy Hedging," Working Papers 201106, Geary Institute, University College Dublin.
  • Handle: RePEc:ucd:wpaper:201106
    as

    Download full text from publisher

    File URL: http://www.ucd.ie/geary/static/publications/workingpapers/gearywp201106.pdf
    File Function: First version, 2011
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cecchetti, Stephen G & Cumby, Robert E & Figlewski, Stephen, 1988. "Estimation of the Optimal Futures Hedge," The Review of Economics and Statistics, MIT Press, vol. 70(4), pages 623-630, November.
    2. K. C. Chen & R. Stephen Sears & Dah‐Nein Tzang, 1987. "Oil prices and energy futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 7(5), pages 501-518, October.
    3. Townsend, Robert M, 1994. "Risk and Insurance in Village India," Econometrica, Econometric Society, vol. 62(3), pages 539-591, May.
    4. John Cotter & Jim Hanly, 2006. "Reevaluating hedging performance," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(7), pages 677-702, July.
    5. Regnier, Eva, 2007. "Oil and energy price volatility," Energy Economics, Elsevier, vol. 29(3), pages 405-427, May.
    6. Ederington, Louis H, 1979. "The Hedging Performance of the New Futures Markets," Journal of Finance, American Finance Association, vol. 34(1), pages 157-170, March.
    7. Cotter, John & Hanly, Jim, 2010. "Time-varying risk aversion: An application to energy hedging," Energy Economics, Elsevier, vol. 32(2), pages 432-441, March.
    8. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
    9. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    10. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    11. Alberto Giovannini & Philippe Jorion, 1988. "The Time-Variation of Risk and Return in the Foreign Exchange and Stock Markets," NBER Working Papers 2573, National Bureau of Economic Research, Inc.
    12. 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.
    13. Giovannini, Alberto & Jorion, Philippe, 1989. " The Time Variation of Risk and Return in the Foreign Exchange and Stock Markets," Journal of Finance, American Finance Association, vol. 44(2), pages 307-325, June.
    14. David Cabedo, J. & Moya, Ismael, 2003. "Estimating oil price 'Value at Risk' using the historical simulation approach," Energy Economics, Elsevier, vol. 25(3), pages 239-253, May.
    15. Brandt, Michael W. & Wang, Kevin Q., 2003. "Time-varying risk aversion and unexpected inflation," Journal of Monetary Economics, Elsevier, vol. 50(7), pages 1457-1498, October.
    16. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Furió, Dolores & Torró, Hipòlit, 2020. "Optimal hedging under biased energy futures markets," Energy Economics, Elsevier, vol. 88(C).
    2. Jim Hanly, 2017. "Managing Energy Price Risk using Futures Contracts: A Comparative Analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    3. Conlon, Thomas & Cotter, John, 2013. "Downside risk and the energy hedger's horizon," Energy Economics, Elsevier, vol. 36(C), pages 371-379.
    4. Cotter, John & Hanly, Jim, 2015. "Performance of utility based hedges," Energy Economics, Elsevier, vol. 49(C), pages 718-726.
    5. Dinica, Mihai Cristian & Armeanu, Daniel, 2014. "The Optimal Hedging Ratio for Non-Ferrous Metals," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 105-122, March.
    6. 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.
    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. Arunanondchai, Panit & Sukcharoen, Kunlapath & Leatham, David J., 2020. "Dealing with tail risk in energy commodity markets: Futures contracts versus exchange-traded funds," Journal of Commodity Markets, Elsevier, vol. 20(C).
    11. Charalampous, Georgios & Madlener, Reinhard, 2013. "Risk Management and Portfolio Optimization for Gas- and Coal-fired Power Plants in Germany: A Multivariate GARCH Approach," FCN Working Papers 23/2013, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    12. Panos K. Pouliasis & Ilias D. Visvikis & Nikos C. Papapostolou & Alexander A. Kryukov, 2020. "A novel risk management framework for natural gas markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(3), pages 430-459, March.
    13. Chiou-Wei, Song-Zan & Chen, Sheng-Hung & Zhu, Zhen, 2020. "Natural gas price, market fundamentals and hedging effectiveness," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 321-337.
    14. Devine, Mel & Farrell, Niall & Lee, William, 2014. "Managing investor and consumer exposure to electricity market price risks through Feed-in Tariff design," MPRA Paper 59208, University Library of Munich, Germany.
    15. Chai, Shanglei & Zhou, P., 2018. "The Minimum-CVaR strategy with semi-parametric estimation in carbon market hedging problems," Energy Economics, Elsevier, vol. 76(C), pages 64-75.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cotter, John & Hanly, Jim, 2010. "Time-varying risk aversion: An application to energy hedging," Energy Economics, Elsevier, vol. 32(2), pages 432-441, March.
    2. Díaz, Antonio & Esparcia, Carlos, 2021. "Dynamic optimal portfolio choice under time-varying risk aversion," International Economics, Elsevier, vol. 166(C), pages 1-22.
    3. Martínez, Beatriz & Torró, Hipòlit, 2015. "European natural gas seasonal effects on futures hedging," Energy Economics, Elsevier, vol. 50(C), pages 154-168.
    4. John Cotter & Jim Hanly, 2012. "Hedging effectiveness under conditions of asymmetry," The European Journal of Finance, Taylor & Francis Journals, vol. 18(2), pages 135-147, February.
    5. Cotter, John & Hanly, Jim, 2015. "Performance of utility based hedges," Energy Economics, Elsevier, vol. 49(C), pages 718-726.
    6. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    7. Gagnon, Louis & Lypny, Gregory J. & McCurdy, Thomas H., 1998. "Hedging foreign currency portfolios," Journal of Empirical Finance, Elsevier, vol. 5(3), pages 197-220, September.
    8. Su, EnDer, 2013. "Stock index hedge using trend and volatility regime switch model considering hedging cost," MPRA Paper 49190, University Library of Munich, Germany.
    9. Bessler, Wolfgang & Leonhardt, Alexander & Wolff, Dominik, 2016. "Analyzing hedging strategies for fixed income portfolios: A Bayesian approach for model selection," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 239-256.
    10. Haigh, Michael S. & Bryant, Henry L., 2000. "Price And Price Risk Dynamics In Barge And Ocean Freight Markets And The Effects On Commodity Trading," 2000 Conference, April 17-18 2000, Chicago, Illinois 18934, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    11. Michael S. Haigh & Henry L. Bryant, 2000. "The effect of barge and ocean freight price volatility in international grain markets," Agricultural Economics, International Association of Agricultural Economists, vol. 25(1), pages 41-58, June.
    12. Martínez, Beatriz & Torró, Hipòlit, 2018. "Hedging spark spread risk with futures," Energy Policy, Elsevier, vol. 113(C), pages 731-746.
    13. repec:adr:anecst:y:1991:i:24:p:01 is not listed on IDEAS
    14. Michael S. Haigh & Matthew T. Holt, 2002. "Crack spread hedging: accounting for time-varying volatility spillovers in the energy futures markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(3), pages 269-289.
    15. Su, EnDer, 2017. "Stock index hedging using a trend and volatility regime-switching model involving hedging cost," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 233-254.
    16. Kim Liow & Zhiwei Chen & Jingran Liu, 2011. "Multiple Regimes and Volatility Transmission in Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 42(3), pages 295-328, April.
    17. Pablo Urtubia & Alfonso Novales & Andrés Mora-Valencia, 2021. "Cross-Hedging Portfolios in Emerging Stock Markets: Evidence for the LATIBEX Index," Mathematics, MDPI, vol. 9(21), pages 1-19, October.
    18. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    19. Haigh, Michael S. & Bryant, Henry L., 2001. "The effect of barge and ocean freight price volatility in international grain markets," Agricultural Economics, Blackwell, vol. 25(1), pages 41-58, June.
    20. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2011. "Crude oil hedging strategies using dynamic multivariate GARCH," Energy Economics, Elsevier, vol. 33(5), pages 912-923, September.
    21. Atreya Chakraborty & John Barkoulas, 1999. "Dynamic futures hedging in currency markets," The European Journal of Finance, Taylor & Francis Journals, vol. 5(4), pages 299-314.

    More about this item

    Keywords

    Energy; Hedging; Risk Management; Risk Aversion; Forecasting;
    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ucd:wpaper:201106. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/geucdie.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Geary Tech (email available below). General contact details of provider: https://edirc.repec.org/data/geucdie.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.