IDEAS home Printed from https://ideas.repec.org/p/ris/fcnwpa/2012_002.html
   My bibliography  Save this paper

Evaluation of Different Hedging Strategies for Commodity Price Risks of Industrial Cogeneration Plants

Author

Listed:

Abstract

In this paper, we design and evaluate eight different strategies for hedging commodity price risks of industrial cogeneration plants. Price developments are parameterized based on EEX data from 2008-2011. The probability distributions derived are used to determine the value-at-risk (VaR) of the individual strategies, which are in a final step combined in a mean-variance portfolio analysis for determining the most efficient hedging strategy. We find that the strate-gy adopted can have a marked influence on the remaining price risk. Quarter futures are found to be particularly well suited for reducing market price risk. In contrast, spot trading of CO2 certificates is found to be preferable compared to forward market trading. Finally, portfolio optimization shows that a mix of various hedging strategies can further improve the profita-bility of a heat-based cogeneration plant.

Suggested Citation

  • Palzer, Andreas & Westner, Günther & Madlener, Reinhard, 2012. "Evaluation of Different Hedging Strategies for Commodity Price Risks of Industrial Cogeneration Plants," FCN Working Papers 2/2012, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Mar 2013.
    • Handle: RePEc:ris:fcnwpa:2012_002
    as

    Download full text from publisher

    File URL: http://www.fcn.eonerc.rwth-aachen.de/global/show_document.asp?id=aaaaaaaaaagvvtk
    File Function: Full text
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Huisman, Ronald & Huurman, Christian & Mahieu, Ronald, 2007. "Hourly electricity prices in day-ahead markets," Energy Economics, Elsevier, vol. 29(2), pages 240-248, March.
    2. Westner, Günther & Madlener, Reinhard, 2012. "Investment in new power generation under uncertainty: Benefits of CHP vs. condensing plants in a copula-based analysis," Energy Economics, Elsevier, vol. 34(1), pages 31-44.
    3. Guthrie, Graeme & Videbeck, Steen, 2007. "Electricity spot price dynamics: Beyond financial models," Energy Policy, Elsevier, vol. 35(11), pages 5614-5621, November.
    4. repec:dau:papers:123456789/4222 is not listed on IDEAS
    5. Markus Burger & Bernhard Klar & Alfred Muller & Gero Schindlmayr, 2004. "A spot market model for pricing derivatives in electricity markets," Quantitative Finance, Taylor & Francis Journals, vol. 4(1), pages 109-122.
    6. Chevallier, Julien, 2011. "Detecting instability in the volatility of carbon prices," Energy Economics, Elsevier, vol. 33(1), pages 99-110, January.
    7. Geman, Hélyette & Ohana, Steve, 2009. "Forward curves, scarcity and price volatility in oil and natural gas markets," Energy Economics, Elsevier, vol. 31(4), pages 576-585, July.
    8. Westner, Günther & Madlener, Reinhard, 2010. "The benefit of regional diversification of cogeneration investments in Europe: A mean-variance portfolio analysis," Energy Policy, Elsevier, vol. 38(12), pages 7911-7920, December.
    9. Benz, Eva & Trück, Stefan, 2009. "Modeling the price dynamics of CO2 emission allowances," Energy Economics, Elsevier, vol. 31(1), pages 4-15, January.
    10. Arouri, Mohamed El Hédi & Jawadi, Fredj & Nguyen, Duc Khuong, 2012. "Nonlinearities in carbon spot-futures price relationships during Phase II of the EU ETS," Economic Modelling, Elsevier, vol. 29(3), pages 884-892.
    11. repec:dau:papers:123456789/120 is not listed on IDEAS
    12. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2013. "Multivariate Volatility Modeling Of Electricity Futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 743-761, August.
    13. Vehvilainen, Iivo & Keppo, Jussi, 2003. "Managing electricity market price risk," European Journal of Operational Research, Elsevier, vol. 145(1), pages 136-147, February.
    14. Rafal Weron, 2005. "Heavy tails and electricity prices," HSC Research Reports HSC/05/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    15. Heydari, Somayeh & Siddiqui, Afzal, 2010. "Valuing a gas-fired power plant: A comparison of ordinary linear models, regime-switching approaches, and models with stochastic volatility," Energy Economics, Elsevier, vol. 32(3), pages 709-725, May.
    16. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    17. Rong, Aiying & Lahdelma, Risto, 2007. "CO2 emissions trading planning in combined heat and power production via multi-period stochastic optimization," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1874-1895, February.
    18. Huisman, R. & Huurman, C., 2003. "Fat Tails in Power Prices," ERIM Report Series Research in Management ERS-2003-059-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    19. Alberola, Emilie & Chevallier, Julien & Cheze, Benoi^t, 2008. "Price drivers and structural breaks in European carbon prices 2005-2007," Energy Policy, Elsevier, vol. 36(2), pages 787-797, February.
    20. Nakamura, Masao & Nakashima, Tomoaki & Niimura, Takahide, 2006. "Electricity markets volatility: estimates, regularities and risk management applications," Energy Policy, Elsevier, vol. 34(14), pages 1736-1749, September.
    21. Jin-Chuan Duan, 1995. "The Garch Option Pricing Model," Mathematical Finance, Wiley Blackwell, vol. 5(1), pages 13-32.
    22. Felder, Frank A, 1996. "Integrating financial theory and methods in electricity resource planning," Energy Policy, Elsevier, vol. 24(2), pages 149-154, February.
    23. repec:dau:papers:123456789/5110 is not listed on IDEAS
    24. Alvaro Escribano & J. Ignacio Peña & Pablo Villaplana, 2011. "Modelling Electricity Prices: International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 622-650, October.
    25. Weron, R. & Kozłowska, B. & Nowicka-Zagrajek, J., 2001. "Modeling electricity loads in California: a continuous-time approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 344-350.
    26. Westner, Günther & Madlener, Reinhard, 2011. "Development of cogeneration in Germany: A mean-variance portfolio analysis of individual technology’s prospects in view of the new regulatory framework," Energy, Elsevier, vol. 36(8), pages 5301-5313.
    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. Dergiades, Theologos & Madlener, Reinhard & Christofidou, Georgia, 2012. "The Nexus between Natural Gas Spot and Futures Prices at NYMEX: Do Weather Shocks and Non-Linear Causality in Low Frequencies Matter?," FCN Working Papers 17/2012, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Sep 2013.
    2. Rohlfs, Wilko & Madlener, Reinhard, 2011. "Multi-Commodity Real Options Analysis of Power Plant Investments: Discounting Endogenous Risk Structures," FCN Working Papers 22/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    3. repec:eee:energy:v:148:y:2018:i:c:p:283-295 is not listed on IDEAS
    4. repec:eee:eneeco:v:70:y:2018:i:c:p:516-524 is not listed on IDEAS
    5. Kavvadias, K.C., 2016. "Energy price spread as a driving force for combined generation investments: A view on Europe," Energy, Elsevier, vol. 115(P3), pages 1632-1639.

    More about this item

    Keywords

    Commodity price risk; Cogeneration; Hedging; mean-variance portfolio optimization;

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

    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:ris:fcnwpa:2012_002. 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: (Hendrik Schmitz). General contact details of provider: http://edirc.repec.org/data/fceonde.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 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.

    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.