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Realized volatility and price spikes in electricity markets: The importance of observation frequency

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  • Ullrich, Carl J.

Abstract

This paper uses high frequency spot price data from eight wholesale electricity markets in Australia, Canada, and the United States to estimate realized volatility and the frequency of price spikes. I find similar levels of realized volatility in Australia and North America, with estimates ranging from 1500% to 2700%, much greater than estimates reported previously in the literature. In hourly data, the frequency of price spikes ranges from approximately 35% to 40% in seven of eight markets. I present evidence that increasing the lag length in the calculation of bipower variation improves jump detection in electricity prices.

Suggested Citation

  • Ullrich, Carl J., 2012. "Realized volatility and price spikes in electricity markets: The importance of observation frequency," Energy Economics, Elsevier, vol. 34(6), pages 1809-1818.
    • Handle: RePEc:eee:eneeco:v:34:y:2012:i:6:p:1809-1818
    DOI: 10.1016/j.eneco.2012.07.003
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    References listed on IDEAS

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    1. Chan, Kam Fong & Gray, Philip & van Campen, Bart, 2008. "A new approach to characterizing and forecasting electricity price volatility," International Journal of Forecasting, Elsevier, vol. 24(4), pages 728-743.
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    Citations

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    Cited by:

    1. Ciarreta, Aitor & Zarraga, Ainhoa, 2016. "Modeling realized volatility on the Spanish intra-day electricity market," Energy Economics, Elsevier, vol. 58(C), pages 152-163.
    2. 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.
    3. 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.
    4. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
    5. Sirin, Selahattin Murat & Camadan, Ercument & Erten, Ibrahim Etem & Zhang, Alex Hongliang, 2023. "Market failure or politics? Understanding the motives behind regulatory actions to address surging electricity prices," Energy Policy, Elsevier, vol. 180(C).
    6. Jeremy Lin & Alessio Saretto & Anastasia Shcherbakova, 2024. "What Fuels the Volatility of Electricity Prices?," Working Papers 2408, Federal Reserve Bank of Dallas.
    7. Frömmel, Michael & Han, Xing & Kratochvil, Stepan, 2014. "Modeling the daily electricity price volatility with realized measures," Energy Economics, Elsevier, vol. 44(C), pages 492-502.
    8. Qu, Hui & Chen, Wei & Niu, Mengyi & Li, Xindan, 2016. "Forecasting realized volatility in electricity markets using logistic smooth transition heterogeneous autoregressive models," Energy Economics, Elsevier, vol. 54(C), pages 68-76.
    9. Aitor Ciarreta & Peru Muniain & Ainhoa Zarraga, 2020. "Realized volatility and jump testing in the Japanese electricity spot market," Empirical Economics, Springer, vol. 58(3), pages 1143-1166, March.
    10. Mayer, Klaus & Trück, Stefan, 2018. "Electricity markets around the world," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 77-100.
    11. Mario Domingues de Paula Simões & Marcelo Cabus Klotzle & Antonio Carlos Figueiredo Pinto & Leonardo Lima Gomes, 2016. "Electricity prices forecast analysis using the extreme value theory," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 5(1), pages 1-22.
    12. Aitor Ciarreta & Peru Muniainy & Ainhoa Zarraga, 2017. "Modelling Realized Volatility in Electricity Spot Prices: New insights and Application to the Japanese Electricity Market," ISER Discussion Paper 0991, Institute of Social and Economic Research, Osaka University.
    13. 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.
    14. Qu, Hui & Duan, Qingling & Niu, Mengyi, 2018. "Modeling the volatility of realized volatility to improve volatility forecasts in electricity markets," Energy Economics, Elsevier, vol. 74(C), pages 767-776.
    15. Yang, Lu, 2022. "Idiosyncratic information spillover and connectedness network between the electricity and carbon markets in Europe," Journal of Commodity Markets, Elsevier, vol. 25(C).
    16. Haugom, Erik & Ullrich, Carl J., 2012. "Forecasting spot price volatility using the short-term forward curve," Energy Economics, Elsevier, vol. 34(6), pages 1826-1833.
    17. Fleten, Stein-Erik & Haugom, Erik & Pichler, Alois & Ullrich, Carl J., 2020. "Structural estimation of switching costs for peaking power plants," European Journal of Operational Research, Elsevier, vol. 285(1), pages 23-33.
    18. 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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    More about this item

    Keywords

    Realized volatility; Bipower variation; Observation frequency; Electricity markets; Price spikes;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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