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Energy price risk management

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  • Weron, Rafal

Abstract

The price of electricity is far more volatile than that of other commodities normally noted for extreme volatility. Demand and supply are balanced on a knife-edge because electric power cannot be economically stored, end user demand is largely weather dependent, and the reliability of the grid is paramount. The possibility of extreme price movements increases the risk of trading in electricity markets. However, a number of standard financial tools cannot be readily applied to pricing and hedging electricity derivatives. In this paper we present arguments why this is the case.

Suggested Citation

  • Weron, Rafal, 2000. "Energy price risk management," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(1), pages 127-134.
  • Handle: RePEc:eee:phsmap:v:285:y:2000:i:1:p:127-134
    DOI: 10.1016/S0378-4371(00)00276-4
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    References listed on IDEAS

    as
    1. Weron, Rafal & Przybyłowicz, Beata, 2000. "Hurst analysis of electricity price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 283(3), pages 462-468.
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    Citations

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    Cited by:

    1. Erzgräber, Hartmut & Strozzi, Fernanda & Zaldívar, José-Manuel & Touchette, Hugo & Gutiérrez, Eugénio & Arrowsmith, David K., 2008. "Time series analysis and long range correlations of Nordic spot electricity market data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6567-6574.
    2. Marossy, Zita, 2011. "A villamos energia áralakulásának egy új modellje
      [A new model for price movement in electric power]
      ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 253-274.
    3. Mehmet Sait Söylemez, 2012. "Effect of the Energy Price Rate on Insulation Applications," International Journal of Energy Economics and Policy, Econjournals, vol. 2(3), pages 103-107.
    4. Al Janabi, Mazin A.M., 2012. "Optimal commodity asset allocation with a coherent market risk modeling," Review of Financial Economics, Elsevier, vol. 21(3), pages 131-140.
    5. Rafal Weron, 2001. "Measuring long-range dependence in electricity prices," Papers cond-mat/0103621, arXiv.org.
    6. Rypdal, Martin & Løvsletten, Ola, 2013. "Modeling electricity spot prices using mean-reverting multifractal processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(1), pages 194-207.
    7. Evans, Lewis & Meade, Richard, 2001. "Economic Analysis of Financial Transmission Rights (FTRs) with Specific Reference to the Transpower Proposal for New Zealand," Working Paper Series 3902, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.
    8. Rangga Handika & Chi Truong & Stefan Trueck & Rafal Weron, 2014. "Modelling price spikes in electricity markets - the impact of load, weather and capacity," HSC Research Reports HSC/14/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    9. Naito, Yuta & Takashima, Ryuta & Kimura, Hiroshi & Madarame, Haruki, 2010. "Evaluating replacement project of nuclear power plants under uncertainty," Energy Policy, Elsevier, vol. 38(3), pages 1321-1329, March.
    10. Sandro Sapio & Agnieszka Wylomanska, 2008. "The impact of forward trading on the spot power price volatility with Cournot competition," HSC Research Reports HSC/08/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    11. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    12. Martin Rypdal & Ola L{o}vsletten, 2012. "Modeling electricity spot prices using mean-reverting multifractal processes," Papers 1201.6137, arXiv.org.
    13. Miśkiewicz, J. & Ausloos, M., 2004. "A logistic map approach to economic cycles. (I). The best adapted companies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 206-214.
    14. Park, S.C. & Jin, Y.G. & Song, H.Y. & Yoon, Y.T., 2015. "Designing a critical peak pricing scheme for the profit maximization objective considering price responsiveness of customers," Energy, Elsevier, vol. 83(C), pages 521-531.
    15. Kamimura, A. & Guerra, S.M.G., 2001. "Economic fluctuations and possible non-linear relations between macroeconomic variables for Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 291(1), pages 542-552.
    16. Berrada, Asmae & Loudiyi, Khalid & Zorkani, Izeddine, 2017. "Profitability, risk, and financial modeling of energy storage in residential and large scale applications," Energy, Elsevier, vol. 119(C), pages 94-109.
    17. Kracík, Jiří & Lavička, Hynek, 2016. "Fluctuation analysis of high frequency electric power load in the Czech Republic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 951-961.
    18. Adams, R. & Jamasb, J., 2016. "Optimal Power Generation Portfolios with Renewables: An Application to the UK," Cambridge Working Papers in Economics 1646, Faculty of Economics, University of Cambridge.
    19. Prokopczuk, Marcel & Rachev, Svetlozar T. & Schindlmayr, Gero & Truck, Stefan, 2007. "Quantifying risk in the electricity business: A RAROC-based approach," Energy Economics, Elsevier, vol. 29(5), pages 1033-1049, September.
    20. Joanna Nowicka-Zagrajek & Rafal Weron, 2002. "Modeling electricity loads in California: ARMA models with hyperbolic noise," HSC Research Reports HSC/02/02, Hugo Steinhaus Center, Wroclaw University of Technology.

    More about this item

    Keywords

    Econophysics; Electricity price; Risk management; Mean-reversion;

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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