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The impact of forward trading on the spot power price volatility with Cournot competition

Author

Listed:
  • Sandro Sapio
  • Agnieszka Wylomanska

Abstract

In this paper, we analyze the influence of forward trading on the volatility of spot power prices, in models where forward contracts are strategic tools used by energy producers to obtain profit security. We define volatility as the variance of the percentage change in spot power prices over a given time interval. As shown in Sapio (2008), volatility is related to stochastic fluctuations in preference and technology fundamentals, and is tuned by the price-elasticity of demand and supply, evaluated at equilibrium. We study two cases. First, we analyze the volatility implications of a model wherein the amount of forward trading is fixed, and producers compete a la Cournot. Fixed forward trading increases spot volatility, because forwards lower the spot price level, corresponding to a less elastic region of a linear demand function. However, if the amount of forward trading is endogenous, as in the two-stage model of Allaz (1992), producers can anticipate the spot market impact of stochastic shocks on fundamentals and 'sterilize' them. As a result, spot price volatility is closer to the value implied by an efficient market. Our theoretical results are illustrated by means of a simple simulation study.

Suggested Citation

  • 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 Science and Technology.
  • Handle: RePEc:wuu:wpaper:hsc0802
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    File URL: http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_08_02.pdf
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    References listed on IDEAS

    as
    1. Weron, Rafal, 2000. "Energy price risk management," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(1), pages 127-134.
    2. repec:dau:papers:123456789/607 is not listed on IDEAS
    3. Sandro Sapio, 2008. "Volatility-price relationships in power exchanges: A demand-supply analysis," LEM Papers Series 2008/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    4. Helyette Geman, 2005. "Commodities and Commodity Derivatives. Modeling and Pricing for Agriculturals, Metals and Energy," Post-Print halshs-00144182, HAL.
    5. Green, R., 1996. "The Electricity Contract Market," Cambridge Working Papers in Economics 9616, Faculty of Economics, University of Cambridge.
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    Cited by:

    1. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    2. Chuntian Cheng & Bin Luo & Shumin Miao & Xinyu Wu, 2016. "Mid-Term Electricity Market Clearing Price Forecasting with Sparse Data: A Case in Newly-Reformed Yunnan Electricity Market," Energies, MDPI, vol. 9(10), pages 1-22, October.

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    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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