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Volatility of power markets

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  • Simonsen, Ingve

Abstract

Volatility features of the Nordic day ahead power spot market for a 12-year period up till May 2004 are studied. The daily logarithmic volatility was measured for this period to be about 16%. This level is well above what is observed for most other well-studied financial markets. Volatility clustering, log-normal distribution, and long-range correlations are found to be striking features of the volatility of power markets. In addition, a cyclic behavior of the time-dependent volatility can be observed for the Nordic power market. Furthermore, the volatility shows a dependence on the price level, and this is pronounced mostly when the spot price is low. The correlation in volatility is consistent with an inverse power-law decay, τ-ν, superposed on an oscillating term. The numerical value of the exponent ν is similar to what has been reported previously for stock markets.

Suggested Citation

  • Simonsen, Ingve, 2005. "Volatility of power markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 10-20.
    • Handle: RePEc:eee:phsmap:v:355:y:2005:i:1:p:10-20
    DOI: 10.1016/j.physa.2005.02.062
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    Citations

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    Cited by:

    1. Erzgräber, Hartmut & Strozzi, Fernanda & Zaldívar, José-Manuel & Touchette, Hugo & Gutiérrez, Eugénio & Arrowsmith, David K., 2008. "Time series analysis and long range correlations of Nordic spot electricity market data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6567-6574.
    2. Zareipour, Hamidreza & Bhattacharya, Kankar & Canizares, Claudio A., 2007. "Electricity market price volatility: The case of Ontario," Energy Policy, Elsevier, vol. 35(9), pages 4739-4748, September.
    3. Weron, Rafal, 2008. "Market price of risk implied by Asian-style electricity options and futures," Energy Economics, Elsevier, vol. 30(3), pages 1098-1115, May.
    4. Rafał Weron, 2009. "Heavy-tails and regime-switching in electricity prices," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 457-473, July.
    5. Sandro Sapio, 2012. "Modeling the distribution of day-ahead electricity returns: a comparison," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1935-1949, December.
    6. Shaker, Hamid & Zareipour, Hamidreza & Wood, David, 2016. "Impacts of large-scale wind and solar power integration on California׳s net electrical load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 761-774.
    7. Sandro Sapio, 2006. "An Empirically Based Model of the Supply Schedule in Day-Ahead Electricity Markets," LEM Papers Series 2006/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    8. Zorana Božić & Dušan Dobromirov & Jovana Arsić & Mladen Radišić & Beata Ślusarczyk, 2020. "Power Exchange Prices: Comparison of Volatility in European Markets," Energies, MDPI, vol. 13(21), pages 1-15, October.
    9. Janczura, Joanna & Trück, Stefan & Weron, Rafał & Wolff, Rodney C., 2013. "Identifying spikes and seasonal components in electricity spot price data: A guide to robust modeling," Energy Economics, Elsevier, vol. 38(C), pages 96-110.
    10. Khoshrou, Abdolrahman & Dorsman, André B. & Pauwels, Eric J., 2019. "The evolution of electricity price on the German day-ahead market before and after the energy switch," Renewable Energy, Elsevier, vol. 134(C), pages 1-13.
    11. Petrella, Andrea & Sapio, Alessandro, 2012. "Assessing the impact of forward trading, retail liberalization, and white certificates on the Italian wholesale electricity prices," Energy Policy, Elsevier, vol. 40(C), pages 307-317.
    12. Swasti R. Khuntia & Jose L. Rueda & Mart A.M.M. Van der Meijden, 2018. "Long-Term Electricity Load Forecasting Considering Volatility Using Multiplicative Error Model," Energies, MDPI, vol. 11(12), pages 1-19, November.
    13. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number hsbook0601, December.
    14. Werner, Dan, 2014. "Electricity Market Price Volatility: The Importance of Ramping Costs," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169619, Agricultural and Applied Economics Association.
    15. Wang, Yudong & Wei, Yu & Wu, Chongfeng, 2010. "Auto-correlated behavior of WTI crude oil volatilities: A multiscale perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5759-5768.
    16. 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.
    17. Janczura, Joanna & Weron, Rafal, 2009. "Regime-switching models for electricity spot prices: Introducing heteroskedastic base regime dynamics and shifted spike distributions," MPRA Paper 18784, University Library of Munich, Germany.
    18. Zorana Zoran Stanković & Milena Nebojsa Rajic & Zorana Božić & Peđa Milosavljević & Ancuța Păcurar & Cristina Borzan & Răzvan Păcurar & Emilia Sabău, 2024. "The Volatility Dynamics of Prices in the European Power Markets during the COVID-19 Pandemic Period," Sustainability, MDPI, vol. 16(6), pages 1-16, March.
    19. 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.
    20. Rypdal, Martin & Løvsletten, Ola, 2013. "Modeling electricity spot prices using mean-reverting multifractal processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(1), pages 194-207.
    21. Martin Rypdal & Ola L{o}vsletten, 2012. "Modeling electricity spot prices using mean-reverting multifractal processes," Papers 1201.6137, arXiv.org.
    22. Ciarreta, Aitor & Martinez, Blanca & Nasirov, Shahriyar, 2023. "Forecasting electricity prices using bid data," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1253-1271.

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