IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v111y2022ics0140988322002407.html
   My bibliography  Save this article

A volatility spillover analysis with realized semi(co)variances in Australian electricity markets

Author

Listed:
  • Chanatásig-Niza, Evelyn
  • Ciarreta, Aitor
  • Zarraga, Ainhoa

Abstract

Volatility spillovers are a characteristic of interconnected electricity markets. We use high-frequency prices to analyze the transmission of volatility across five Australian regional electricity markets. We propose several models: The first includes only realized variances; the second adds realized covariances; the last two include positive and negative realized semi(co)variances, separately, obtained from the decomposition of the realized covariance matrix into components based on the sign of the underlying returns. We carry out the analysis for both static and dynamic frameworks and relate the behavior of spillovers to major events and policies affecting the markets. Results show that ignoring covariances results in spillovers being underestimated and highlight the importance of the role of semi(co)variances in detecting asymmetric spillovers. Finally, we discuss implications for short-run market participants and long-term planning by regulators.

Suggested Citation

  • Chanatásig-Niza, Evelyn & Ciarreta, Aitor & Zarraga, Ainhoa, 2022. "A volatility spillover analysis with realized semi(co)variances in Australian electricity markets," Energy Economics, Elsevier, vol. 111(C).
    • Handle: RePEc:eee:eneeco:v:111:y:2022:i:c:s0140988322002407
    DOI: 10.1016/j.eneco.2022.106076
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988322002407
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2022.106076?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    2. Fengler, Matthias R. & Gisler, Katja I.M., 2015. "A variance spillover analysis without covariances: What do we miss?," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 174-195.
    3. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    4. Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September.
    5. Ciarreta, Aitor & Zarraga, Ainhoa, 2016. "Modeling realized volatility on the Spanish intra-day electricity market," Energy Economics, Elsevier, vol. 58(C), pages 152-163.
    6. Francesco Audrino & Simon D. Knaus, 2016. "Lassoing the HAR Model: A Model Selection Perspective on Realized Volatility Dynamics," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1485-1521, December.
    7. Peter Cramton, 2017. "Electricity market design," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 589-612.
    8. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    9. Do, Hung Xuan & Nepal, Rabindra & Jamasb, Tooraj, 2020. "Electricity market integration, decarbonisation and security of supply: Dynamic volatility connectedness in the Irish and Great Britain markets," Energy Economics, Elsevier, vol. 92(C).
    10. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    11. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    12. A Ciarreta and A Zarraga, 2015. "Analysis of mean and volatility price transmissions in the MIBEL and EPEX electricity spot markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    13. Robert Wilson, 2002. "Architecture of Power Markets," Econometrica, Econometric Society, vol. 70(4), pages 1299-1340, July.
    14. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    15. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
    16. Higgs, Helen, 2009. "Modelling price and volatility inter-relationships in the Australian wholesale spot electricity markets," Energy Economics, Elsevier, vol. 31(5), pages 748-756, September.
    17. Lindström, Erik & Regland, Fredrik, 2012. "Modeling extreme dependence between European electricity markets," Energy Economics, Elsevier, vol. 34(4), pages 899-904.
    18. Tim Bollerslev & Jia Li & Andrew J. Patton & Rogier Quaedvlieg, 2020. "Realized Semicovariances," Econometrica, Econometric Society, vol. 88(4), pages 1515-1551, July.
    19. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
    20. Worthington, Andrew & Kay-Spratley, Adam & Higgs, Helen, 2005. "Transmission of prices and price volatility in Australian electricity spot markets: a multivariate GARCH analysis," Energy Economics, Elsevier, vol. 27(2), pages 337-350, March.
    21. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    22. Bartosz Uniejewski & Rafal Weron & Florian Ziel, 2017. "Variance stabilizing transformations for electricity spot price forecasting," HSC Research Reports HSC/17/01, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    23. Park, Haesun & Mjelde, James W. & Bessler, David A., 2006. "Price dynamics among U.S. electricity spot markets," Energy Economics, Elsevier, vol. 28(1), pages 81-101, January.
    24. Helen Higgs, 2009. "Modelling price and volatility inter-relationships in the Australian wholesale spot electricity markets," Discussion Papers in Economics economics:200904, Griffith University, Department of Accounting, Finance and Economics.
    25. Yan, Guan & Trück, Stefan, 2020. "A dynamic network analysis of spot electricity prices in the Australian national electricity market," Energy Economics, Elsevier, vol. 92(C).
    26. Apergis, Nicholas & Gozgor, Giray & Lau, Chi Keung Marco & Wang, Shixuan, 2019. "Decoding the Australian electricity market: New evidence from three-regime hidden semi-Markov model," Energy Economics, Elsevier, vol. 78(C), pages 129-142.
    27. Bunn, Derek W. & Gianfreda, Angelica, 2010. "Integration and shock transmissions across European electricity forward markets," Energy Economics, Elsevier, vol. 32(2), pages 278-291, March.
    28. Apergis, Nicholas & Baruník, Jozef & Lau, Marco Chi Keung, 2017. "Good volatility, bad volatility: What drives the asymmetric connectedness of Australian electricity markets?," Energy Economics, Elsevier, vol. 66(C), pages 108-115.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rangarajan, Arvind & Foley, Sean & Trück, Stefan, 2023. "Assessing the impact of battery storage on Australian electricity markets," Energy Economics, Elsevier, vol. 120(C).
    2. Guan, Bo & Mazouz, Khelifa & Xu, Yongdeng, 2024. "Asymmetric volatility spillover between crude oil and other asset markets," Energy Economics, Elsevier, vol. 130(C).
    3. Lyu, Chenyan & Do, Hung Xuan & Nepal, Rabindra & Jamasb, Tooraj, 2024. "Volatility spillovers and carbon price in the Nordic wholesale electricity markets," Energy Economics, Elsevier, vol. 134(C).
    4. Abdullah, Mohammad & Abakah, Emmanuel Joel Aikins & Wali Ullah, G M & Tiwari, Aviral Kumar & Khan, Isma, 2023. "Tail risk contagion across electricity markets in crisis periods," Energy Economics, Elsevier, vol. 127(PB).
    5. Maki, Daiki, 2024. "Evaluation of volatility spillovers for asymmetric realized covariance," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    6. Say, Kelvin & Csereklyei, Zsuzsanna & Brown, Felix Gabriel & Wang, Changlong, 2024. "The economics of public transport electrification: The charging dilemma," Energy Economics, Elsevier, vol. 135(C).

    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. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
    2. Lyu, Chenyan & Do, Hung Xuan & Nepal, Rabindra & Jamasb, Tooraj, 2024. "Volatility spillovers and carbon price in the Nordic wholesale electricity markets," Energy Economics, Elsevier, vol. 134(C).
    3. Shi Chen & Wolfgang Karl Hardle & Brenda L'opez Cabrera, 2020. "Regularization Approach for Network Modeling of German Power Derivative Market," Papers 2009.09739, arXiv.org.
    4. Abdullah, Mohammad & Abakah, Emmanuel Joel Aikins & Wali Ullah, G M & Tiwari, Aviral Kumar & Khan, Isma, 2023. "Tail risk contagion across electricity markets in crisis periods," Energy Economics, Elsevier, vol. 127(PB).
    5. Ma, Rufei & Liu, Zhenhua & Zhai, Pengxiang, 2022. "Does economic policy uncertainty drive volatility spillovers in electricity markets: Time and frequency evidence," Energy Economics, Elsevier, vol. 107(C).
    6. Naeem, Muhammad Abubakr & Karim, Sitara & Rabbani, Mustafa Raza & Nepal, Rabindra & Uddin, Gazi Salah, 2022. "Market integration in the Australian National Electricity Market: Fresh evidence from asymmetric time-frequency connectedness," Energy Economics, Elsevier, vol. 112(C).
    7. Do, Hung Xuan & Nepal, Rabindra & Jamasb, Tooraj, 2020. "Electricity market integration, decarbonisation and security of supply: Dynamic volatility connectedness in the Irish and Great Britain markets," Energy Economics, Elsevier, vol. 92(C).
    8. Sikorska-Pastuszka, Magdalena & Papież, Monika, 2023. "Dynamic volatility connectedness in the European electricity market," Energy Economics, Elsevier, vol. 127(PA).
    9. Hasan, Mudassar & Arif, Muhammad & Naeem, Muhammad Abubakr & Ngo, Quang-Thanh & Taghizadeh–Hesary, Farhad, 2021. "Time-frequency connectedness between Asian electricity sectors," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 208-224.
    10. Hung Do & Rabindra Nepal & Russell Smyth, 2020. "Interconnectedness in the Australian National Electricity Market: A Higher‐Moment Analysis," The Economic Record, The Economic Society of Australia, vol. 96(315), pages 450-469, December.
    11. Maki, Daiki, 2024. "Evaluation of volatility spillovers for asymmetric realized covariance," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    12. Apergis, Nicholas & Baruník, Jozef & Lau, Marco Chi Keung, 2017. "Good volatility, bad volatility: What drives the asymmetric connectedness of Australian electricity markets?," Energy Economics, Elsevier, vol. 66(C), pages 108-115.
    13. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    14. Apergis, Nicholas & Pan, Wei-Fong & Reade, James & Wang, Shixuan, 2023. "Modelling Australian electricity prices using indicator saturation," Energy Economics, Elsevier, vol. 120(C).
    15. Guo, Li-Yang & Feng, Chao, 2021. "Are there spillovers among China's pilots for carbon emission allowances trading?," Energy Economics, Elsevier, vol. 103(C).
    16. Gong, Jue & Wang, Gang-Jin & Zhou, Yang & Zhu, You & Xie, Chi & Foglia, Matteo, 2023. "Spreading of cross-market volatility information: Evidence from multiplex network analysis of volatility spillovers," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    17. Mwampashi, Muthe Mathias & Nikitopoulos, Christina Sklibosios & Konstandatos, Otto & Rai, Alan, 2021. "Wind generation and the dynamics of electricity prices in Australia," Energy Economics, Elsevier, vol. 103(C).
    18. Cipollini, Andrea & Lo Cascio, Iolanda & Muzzioli, Silvia, 2018. "Risk aversion connectedness in five European countries," Economic Modelling, Elsevier, vol. 71(C), pages 68-79.
    19. Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Commodity Connectedness," Central Banking, Analysis, and Economic Policies Book Series, in: Enrique G. Mendoza & Ernesto Pastén & Diego Saravia (ed.),Monetary Policy and Global Spillovers: Mechanisms, Effects and Policy Measures, edition 1, volume 25, chapter 4, pages 097-136, Central Bank of Chile.
    20. Okorie, David Iheke & Lin, Boqiang, 2022. "Givers never lack: Nigerian oil & gas asymmetric network analyses," Energy Economics, Elsevier, vol. 108(C).

    More about this item

    Keywords

    Electricity prices; Volatility spillovers; Semivariance; Semicovariance; Asymmetric effects;
    All these keywords.

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    Statistics

    Access and download statistics

    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:eee:eneeco:v:111:y:2022:i:c:s0140988322002407. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.