IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i18p6515-d1236647.html
   My bibliography  Save this article

Electricity Market Dynamics and Regional Interdependence in the Face of Pandemic Restrictions and the Russian–Ukrainian Conflict

Author

Listed:
  • András Szeberényi

    (Institute of Marketing and Communication, Budapest Metropolitan University, 1148 Budapest, Hungary)

  • Ferenc Bakó

    (Department of International and Applied Economics, Széchenyi István University, 9026 Győr, Hungary)

Abstract

Electricity constitutes a significant part of the consumption basket of European households and companies. Since energy products are essential components of almost all products and services, any change in energy prices directly impacts the general price level of those products and services. Therefore, this study aims to conduct a comprehensive analysis of power exchange data between 2019 and 2022. For the analysis, we examined the data of 15 countries. In the research, we compared electricity prices in European power exchanges using the Jaccard similarity index and the overlap coefficient, using the DAM hourly prices between 1 January 2019 and 31 December 2022. We transformed the time series into networks using the visibility graph procedure and compared the networks of the studied countries using the two comparison methods with the degree distribution functions. Our aim is to examine how the market anomalies caused by the COVID-19 pandemic and the Russian–Ukrainian conflict affect European electricity markets and how quickly the repercussions spread across the studied countries’ exchanges, and whether they show persistent or anti-persistent characteristics. The results support that similar market effects significantly influence the pattern of price changes among the countries. The methods forming the basis of the research can provide significant assistance in analyzing market trends and contribute to a better understanding of market processes.

Suggested Citation

  • András Szeberényi & Ferenc Bakó, 2023. "Electricity Market Dynamics and Regional Interdependence in the Face of Pandemic Restrictions and the Russian–Ukrainian Conflict," Energies, MDPI, vol. 16(18), pages 1-22, September.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:18:p:6515-:d:1236647
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/18/6515/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/18/6515/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Anna Cretì & Fulvio Fontini, 2019. "Economics of Electricity. Markets, Competition and Rules," Post-Print hal-02304345, HAL.
    2. Ocker, Fabian & Jaenisch, Vincent, 2020. "The way towards European electricity intraday auctions – Status quo and future developments," Energy Policy, Elsevier, vol. 145(C).
    3. Han, Mengjiao & Fan, Qingju & Ling, Guang, 2022. "Multiscale online-horizontal-visibility-graph correlation analysis of financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    4. Hesamzadeh, M.R. & Biggar, D.R. & Bunn, D.W. & Moiseeva, E., 2020. "The impact of generator market power on the electricity hedge market," Energy Economics, Elsevier, vol. 86(C).
    5. Thomas, Samuel & Rosenow, Jan, 2020. "Drivers of increasing energy consumption in Europe and policy implications," Energy Policy, Elsevier, vol. 137(C).
    6. Lu, Xiaoxing & Li, Kangping & Xu, Hanchen & Wang, Fei & Zhou, Zhenyu & Zhang, Yagang, 2020. "Fundamentals and business model for resource aggregator of demand response in electricity markets," Energy, Elsevier, vol. 204(C).
    7. Szőke, Tamás & Hortay, Olivér & Balogh, Eszter, 2019. "Asymmetric price transmission in the Hungarian retail electricity market," Energy Policy, Elsevier, vol. 133(C).
    8. Tomasz Rokicki & Radosław Jadczak & Adam Kucharski & Piotr Bórawski & Aneta Bełdycka-Bórawska & András Szeberényi & Aleksandra Perkowska, 2022. "Changes in Energy Consumption and Energy Intensity in EU Countries as a Result of the COVID-19 Pandemic by Sector and Area Economy," Energies, MDPI, vol. 15(17), pages 1-26, August.
    9. Grau-Carles, Pilar, 2001. "Long-range power-law correlations in stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(3), pages 521-527.
    10. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    11. Hortay, Olivér & Víg, Attila A., 2020. "Potential effects of market power in Hungarian solar boom," Energy, Elsevier, vol. 213(C).
    12. Fan, Xinghua & Li, Xuxia & Yin, Jiuli & Tian, Lixin & Liang, Jiaochen, 2019. "Similarity and heterogeneity of price dynamics across China’s regional carbon markets: A visibility graph network approach," Applied Energy, Elsevier, vol. 235(C), pages 739-746.
    13. András Szeberényi & Tomasz Rokicki & Árpád Papp-Váry, 2022. "Examining the Relationship between Renewable Energy and Environmental Awareness," Energies, MDPI, vol. 15(19), pages 1-25, September.
    14. Brugger, Heike & Eichhammer, Wolfgang & Mikova, Nadezhda & Dönitz, Ewa, 2021. "Energy Efficiency Vision 2050: How will new societal trends influence future energy demand in the European countries?," Energy Policy, Elsevier, vol. 152(C).
    15. Roxana Săvescu & Ștefania Kifor & Raluca Dănuț & Raluca Rusu, 2022. "Transition from Office to Home Office: Lessons from Romania during COVID-19 Pandemic," Sustainability, MDPI, vol. 14(10), pages 1-14, May.
    16. Norbert Bozsik & András Szeberényi & Nándor Bozsik, 2023. "Examination of the Hungarian Electricity Industry Structure with Special Regard to Renewables," Energies, MDPI, vol. 16(9), pages 1-23, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marina Bertolini & Gregorio Morosinotto, 2023. "Business Models for Energy Community in the Aggregator Perspective: State of the Art and Research Gaps," Energies, MDPI, vol. 16(11), pages 1-26, June.
    2. Gu, Rongbao & Xiong, Wei & Li, Xinjie, 2015. "Does the singular value decomposition entropy have predictive power for stock market? — Evidence from the Shenzhen stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 103-113.
    3. Zhang, Bo & Wang, Jun & Fang, Wen, 2015. "Volatility behavior of visibility graph EMD financial time series from Ising interacting system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 301-314.
    4. González-Pla, Francisco & Lovreta, Lidija, 2019. "Persistence in firm’s asset and equity volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    5. Alvarez-Ramirez, Jose & Rodriguez, Eduardo, 2021. "A singular value decomposition entropy approach for testing stock market efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    6. Andrea Benedek & Tomasz Rokicki & András Szeberényi, 2023. "Bibliometric Evaluation of Energy Efficiency in Agriculture," Energies, MDPI, vol. 16(16), pages 1-27, August.
    7. Piotr Olczak & Dominika Matuszewska, 2023. "Energy Storage Potential Needed at the National Grid Scale (Poland) in Order to Stabilize Daily Electricity Production from Fossil Fuels and Nuclear Power," Energies, MDPI, vol. 16(16), pages 1-11, August.
    8. Norbert Bozsik & András Szeberényi & Nándor Bozsik, 2023. "Examination of the Hungarian Electricity Industry Structure with Special Regard to Renewables," Energies, MDPI, vol. 16(9), pages 1-23, April.
    9. Zhang, Bo & Wang, Guochao & Wang, Yiduan & Zhang, Wei & Wang, Jun, 2019. "Multiscale statistical behaviors for Ising financial dynamics with continuum percolation jump," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1012-1025.
    10. İşcanoğlu-Çekiç, Ayşegül & Gülteki̇n, Havva, 2019. "Are cross-correlations between Turkish Stock Exchange and three major country indices multifractal or monofractal?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 978-990.
    11. Haoran Zhang & Rongxia Zhang & Guomin Li & Wei Li & Yongrok Choi, 2020. "Has China’s Emission Trading System Achieved the Development of a Low-Carbon Economy in High-Emission Industrial Subsectors?," Sustainability, MDPI, vol. 12(13), pages 1-20, July.
    12. Demiralay, Sercan & Ulusoy, Veysel, 2014. "Value-at-risk Predictions of Precious Metals with Long Memory Volatility Models," MPRA Paper 53229, University Library of Munich, Germany.
    13. Koop, Gary & Ley, Eduardo & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian analysis of long memory and persistence using ARFIMA models," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 149-169.
    14. Ngene, Geoffrey & Tah, Kenneth A. & Darrat, Ali F., 2017. "Long memory or structural breaks: Some evidence for African stock markets," Review of Financial Economics, Elsevier, vol. 34(C), pages 61-73.
    15. Anders Johansson, 2009. "An analysis of dynamic risk in the Greater China equity markets," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 7(3), pages 299-320.
    16. Zhang, Wei-Guo & Li, Zhe & Liu, Yong-Jun, 2018. "Analytical pricing of geometric Asian power options on an underlying driven by a mixed fractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 402-418.
    17. Cornelis A. Los, 2004. "Nonparametric Efficiency Testing of Asian Stock Markets Using Weekly Data," Finance 0409033, University Library of Munich, Germany.
    18. Wang, Mingtao & Zhang, Juan & Liu, Huanwei, 2022. "Thermodynamic analysis and optimization of two low-grade energy driven transcritical CO2 combined cooling, heating and power systems," Energy, Elsevier, vol. 249(C).
    19. Zeinali, Narges & Pourdarvish, Ahmad, 2022. "An entropy-based estimator of the Hurst exponent in fractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    20. Bollerslev, Tim & Gibson, Michael & Zhou, Hao, 2011. "Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities," Journal of Econometrics, Elsevier, vol. 160(1), pages 235-245, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:18:p:6515-:d:1236647. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.