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Volatility transmission and volatility impulse response functions in European electricity forward markets

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  • Yannick LE PEN
  • Benoît SEVI

Abstract

Using daily data from March 2001 to June 2005, we estimate a VAR-BEKK model and find evidence of return and volatility spillovers between the German, the Dutch and the British forward electricity markets. We apply Hafner and Herwartz [2006, Journal of International Money and Finance 25, 719-740] Volatility Impulse Response Function(VIRF) to quantify the impact of shock on expected conditional volatility. We observe that a shock has a high positive impact only if its size is large compared to the current level of volatility. The impact of shocks are usually not persistent, which may be an indication of market efficiency. Finally, we estimate the density of the VIRF at different forecast horizon. These fitted distributions are asymmetric and show that extreme events are possible even if their probability is low. These results have interesting implications for market participants whose risk management policy is based on option prices which themselves depend on the volatility level.

Suggested Citation

  • Yannick LE PEN & Benoît SEVI, 2008. "Volatility transmission and volatility impulse response functions in European electricity forward markets," Cahiers du CREDEN (CREDEN Working Papers) 08.09.77, CREDEN (Centre de Recherche en Economie et Droit de l'Energie), Faculty of Economics, University of Montpellier 1.
  • Handle: RePEc:mop:credwp:08.09.77
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    3. Jin, Xiaoye, 2015. "Volatility transmission and volatility impulse response functions among the Greater China stock markets," Journal of Asian Economics, Elsevier, vol. 39(C), pages 43-58.
    4. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2016. "Cross-Commodity News Transmission and Volatility Spillovers in the German Energy Markets," Working Papers 2016:2, Lund University, Department of Economics, revised 11 Oct 2017.
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    7. Daglish, Toby & de Braganca, Gabriel & Owen, Sally & Romano, Teresa, 2015. "Electricity Market Operation: Transitioning from a Free Market to a Single Buyer structure: An econometric analysis of the Brazilian case using a Two-State Markov Switching Model," Working Paper Series 4181, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.
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    13. de Menezes, Lilian M. & Houllier, Melanie A., 2015. "Germany's nuclear power plant closures and the integration of electricity markets in Europe," Energy Policy, Elsevier, vol. 85(C), pages 357-368.
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    15. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
    16. Lindström, Erik & Regland, Fredrik, 2012. "Modeling extreme dependence between European electricity markets," Energy Economics, Elsevier, vol. 34(4), pages 899-904.
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    18. Haugom, Erik & Westgaard, Sjur & Solibakke, Per Bjarte & Lien, Gudbrand, 2011. "Realized volatility and the influence of market measures on predictability: Analysis of Nord Pool forward electricity data," Energy Economics, Elsevier, vol. 33(6), pages 1206-1215.

    More about this item

    Keywords

    volatility impulse response function; GARCH; non Gaussian distributions; electricity market; forward markets;

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • G1 - Financial Economics - - General Financial Markets
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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