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The Nature of Power Spikes: A Regime-Switch Approach


  • De Jong Cyriel

    () (Erasmus University Rotterdam)


Due to its non-storable nature, electricity is a commodity with probably the most volatile spot prices, exemplified by occasional spikes. Appropriate pricing, portfolio, and risk management models have to incorporate these characteristics, and the spikes in particular. We investigate the nature of power spikes in a number of different markets. We test what time-series model is best able to capture the dynamics of these disruptive spot prices. We use regime-switching models to infer whether the price spikes should be treated as abnormal and independent deviations from the normal price dynamics or whether they form an integral part of the price process. We test the time-series models on day-ahead markets in Europe and the US. We find that regime-switch models are better able to capture the market dynamics than a GARCH(1,1) or Poisson jump model. We also find clear differences between the markets and attribute part of the differences to the share of hydro-power in the total supply stack: hydro-power serves as an indirect means to store electricity, which has a dampening effect on spikes.

Suggested Citation

  • De Jong Cyriel, 2006. "The Nature of Power Spikes: A Regime-Switch Approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-28, September.
  • Handle: RePEc:bpj:sndecm:v:10:y:2006:i:3:n:3

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    References listed on IDEAS

    1. Alvaro Cartea & Marcelo Figueroa, 2005. "Pricing in Electricity Markets: A Mean Reverting Jump Diffusion Model with Seasonality," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(4), pages 313-335.
    2. Schwartz, Eduardo S, 1997. " The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    3. Fred Espen Benth & Lars Ekeland & Ragnar Hauge & BjøRn Fredrik Nielsen, 2003. "A note on arbitrage-free pricing of forward contracts in energy markets," Applied Mathematical Finance, Taylor & Francis Journals, vol. 10(4), pages 325-336.
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