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Structure and stylized facts of a deregulated power market

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  • Simonsen, Ingve
  • Weron, Rafal
  • Mo, Birger

Abstract

Dramatic changes to the structure of the power sector have taken place over the past few decades. The major structural change being the introduction of competitive markets and power exchanges. In this paper, we conduct a detailed empirical study of the statistical properties of the Nordic power (Nord Pool) spot market. The aim of this study is to identify so-called stylized facts of the market. We address the structure of the market, and in particular, describe in detail the spot price forming process (equilibrium point trading). A collection of stylized facts is identified and discussed for the hourly system spot price, based on the entire 12 year history of available Nord Pool data. In particular we analyze: seasonallity, weather effects, the human factor, return distributions, volatility, spikes, and mean-reversion (anticorrelation). The empirical study presented in this paper shed new light on the mechanisms, features and structures of these new commodity markets. The market features that distinguish them from more classic financial and commodity markets are pointed out.

Suggested Citation

  • Simonsen, Ingve & Weron, Rafal & Mo, Birger, 2004. "Structure and stylized facts of a deregulated power market," MPRA Paper 1443, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:1443
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    File URL: https://mpra.ub.uni-muenchen.de/1443/1/MPRA_paper_1443.pdf
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    References listed on IDEAS

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    1. Marina Resta & Davide Sciutti, 2003. "Spot price dynamics in deregulated power markets," Econometrics 0312002, University Library of Munich, Germany.
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    Cited by:

    1. Joachim Geske & Richard Green, 2020. "Optimal Storage, Investment and Management under Uncertainty: It is Costly to Avoid Outages!," The Energy Journal, , vol. 41(2), pages 1-28, March.
    2. Kyritsis, Evangelos & Andersson, Jonas & Serletis, Apostolos, 2017. "Electricity prices, large-scale renewable integration, and policy implications," Energy Policy, Elsevier, vol. 101(C), pages 550-560.
    3. Ladislav KRISTOUFEK & Petra LUNACKOVA, 2013. "Long-term Memory in Electricity Prices: Czech Market Evidence," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 407-424, November.
    4. Avci-Surucu, Ezgi & Aydogan, A. Kursat & Akgul, Doganbey, 2016. "Bidding structure, market efficiency and persistence in a multi-time tariff setting," Energy Economics, Elsevier, vol. 54(C), pages 77-87.
    5. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601, December.
    6. George P Papaioannou & Christos Dikaiakos & Anargyros Dramountanis & Dionysios S Georgiadis & Panagiotis G Papaioannou, 2017. "Using nonlinear stochastic and deterministic (chaotic tools) to test the EMH of two Electricity Markets the case of Italy and Greece," Papers 1711.10552, arXiv.org.
    7. Paraschiv, Florentina, 2013. "Price Dynamics in Electricity Markets," Working Papers on Finance 1314, University of St. Gallen, School of Finance.
    8. N. K. Nomikos & O. Soldatos, 2008. "Using Affine Jump Diffusion Models for Modelling and Pricing Electricity Derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 15(1), pages 41-71.
    9. 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.
    10. Wang, Peng & Zareipour, Hamidreza & Rosehart, William D., 2011. "Characteristics of the prices of operating reserves and regulation services in competitive electricity markets," Energy Policy, Elsevier, vol. 39(6), pages 3210-3221, June.

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      More about this item

      Keywords

      Electricity markets; Spot price; Stylized facts; Deregulation; Econophysics;
      All these keywords.

      JEL classification:

      • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
      • 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
      • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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