IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v67y2020icp163-175.html
   My bibliography  Save this article

Exploring the risk spillover effects between carbon market and electricity market: A bidimensional empirical mode decomposition based conditional value at risk approach

Author

Listed:
  • Zhu, Bangzhu
  • Huang, Liqing
  • Yuan, Lili
  • Ye, Shunxin
  • Wang, Ping

Abstract

This study proposes a bidimensional empirical mode decomposition based conditional value at risk approach to explore the risk spillover effects between carbon market and electricity market. Firstly, bidimensional empirical mode decomposition is applied to decompose the pair of carbon and electricity prices into a series of simple modes with different frequencies. Secondly, conditional value at risk is used to capture the risk spillover effects between carbon market and electricity market at each frequency. The empirical results show that the risks of high frequency modes are higher than those of intermediate and low frequency modes. Carbon market has a positive risk spillover on electricity market, and electricity market has a negative risk spillover on carbon market. For high and low frequency modes, the risk spillover effects from carbon market to electricity market are positive, however those from electricity market to carbon market are negative. For intermediate frequency modes, there are bidirectional negative risk spillover effects between carbon market and electricity market.

Suggested Citation

  • Zhu, Bangzhu & Huang, Liqing & Yuan, Lili & Ye, Shunxin & Wang, Ping, 2020. "Exploring the risk spillover effects between carbon market and electricity market: A bidimensional empirical mode decomposition based conditional value at risk approach," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 163-175.
    • Handle: RePEc:eee:reveco:v:67:y:2020:i:c:p:163-175
    DOI: 10.1016/j.iref.2020.01.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056020300307
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.iref.2020.01.003?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. Hintermann, Beat, 2010. "Allowance price drivers in the first phase of the EU ETS," Journal of Environmental Economics and Management, Elsevier, vol. 59(1), pages 43-56, January.
    2. So, Mike K.P. & Yu, Philip L.H., 2006. "Empirical analysis of GARCH models in value at risk estimation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(2), pages 180-197, April.
    3. Keppler, Jan Horst & Mansanet-Bataller, Maria, 2010. "Causalities between CO2, electricity, and other energy variables during phase I and phase II of the EU ETS," Energy Policy, Elsevier, vol. 38(7), pages 3329-3341, July.
    4. Ma, Yan-Ran & Zhang, Dayong & Ji, Qiang & Pan, Jiaofeng, 2019. "Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter?," Energy Economics, Elsevier, vol. 81(C), pages 536-544.
    5. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    6. Fan, Xinghua & Li, Shasha & Tian, Lixin, 2016. "Complexity of carbon market from multi-scale entropy analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 79-85.
    7. Feng, Zhen-Hua & Wei, Yi-Ming & Wang, Kai, 2012. "Estimating risk for the carbon market via extreme value theory: An empirical analysis of the EU ETS," Applied Energy, Elsevier, vol. 99(C), pages 97-108.
    8. Ji, Qiang & Li, Jianping & Sun, Xiaolei, 2019. "Measuring the interdependence between investor sentiment and crude oil returns: New evidence from the CFTC's disaggregated reports," Finance Research Letters, Elsevier, vol. 30(C), pages 420-425.
    9. Chevallier, Julien & Ielpo, Florian & Mercier, Ludovic, 2009. "Risk aversion and institutional information disclosure on the European carbon market: A case-study of the 2006 compliance event," Energy Policy, Elsevier, vol. 37(1), pages 15-28, January.
    10. Zhu, Bangzhu & Han, Dong & Chevallier, Julien & Wei, Yi-Ming, 2017. "Dynamic multiscale interactions between European carbon and electricity markets during 2005–2016," Energy Policy, Elsevier, vol. 107(C), pages 309-322.
    11. López-Espinosa, Germán & Moreno, Antonio & Rubia, Antonio & Valderrama, Laura, 2012. "Short-term wholesale funding and systemic risk: A global CoVaR approach," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3150-3162.
    12. Michael Phelan, 1997. "Probability and Statistics Applied to the Practice of Financial Risk Management: The Case of J.P. Morgan's RiskMetrics™," Journal of Financial Services Research, Springer;Western Finance Association, vol. 12(2), pages 175-200, October.
    13. Girardi, Giulio & Tolga Ergün, A., 2013. "Systemic risk measurement: Multivariate GARCH estimation of CoVaR," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3169-3180.
    14. Gary Koop & Lise Tole, 2013. "Forecasting the European carbon market," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(3), pages 723-741, June.
    15. repec:dau:papers:123456789/4221 is not listed on IDEAS
    16. Bangzhu Zhu & Shujiao Ma & Rui Xie & Julien Chevallier & Yi-Ming Wei, 2018. "Hilbert Spectra and Empirical Mode Decomposition: A Multiscale Event Analysis Method to Detect the Impact of Economic Crises on the European Carbon Market," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 105-121, June.
    17. Bangzhu Zhu & Shujiao Ma & Rui Xie & Julien Chevallier & Yi-Ming Wei, 2018. "Erratum to: Hilbert Spectra and Empirical Mode Decomposition: A Multiscale Event Analysis Method to Detect the Impact of Economic Crises on the European Carbon Market," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 123-123, June.
    18. Reboredo, Juan C. & Ugolini, Andrea, 2015. "Systemic risk in European sovereign debt markets: A CoVaR-copula approach," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 214-244.
    19. Maria Mansanet-Bataller & Angel Pardo & Enric Valor, 2007. "CO2 Prices, Energy and Weather," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 73-92.
    20. repec:dau:papers:123456789/5269 is not listed on IDEAS
    21. Tang, Ling & Yu, Lean & Wang, Shuai & Li, Jianping & Wang, Shouyang, 2012. "A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting," Applied Energy, Elsevier, vol. 93(C), pages 432-443.
    22. Zhu, Bangzhu & Yuan, Lili & Ye, Shunxin, 2019. "Examining the multi-timescales of European carbon market with grey relational analysis and empirical mode decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 392-399.
    23. Boersen, Arieke & Scholtens, Bert, 2014. "The relationship between European electricity markets and emission allowance futures prices in phase II of the EU (European Union) emission trading scheme," Energy, Elsevier, vol. 74(C), pages 585-594.
    24. Ji, Qiang & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2019. "Information interdependence among energy, cryptocurrency and major commodity markets," Energy Economics, Elsevier, vol. 81(C), pages 1042-1055.
    25. Cui, Lian-Biao & Fan, Ying & Zhu, Lei & Bi, Qing-Hua, 2014. "How will the emissions trading scheme save cost for achieving China’s 2020 carbon intensity reduction target?," Applied Energy, Elsevier, vol. 136(C), pages 1043-1052.
    26. Zhu, Bangzhu & Ye, Shunxin & Wang, Ping & He, Kaijian & Zhang, Tao & Wei, Yi-Ming, 2018. "A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting," Energy Economics, Elsevier, vol. 70(C), pages 143-157.
    27. Drakos, Anastassios A. & Kouretas, Georgios P., 2015. "Bank ownership, financial segments and the measurement of systemic risk: An application of CoVaR," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 127-140.
    28. Li Wang, 2019. "The Risk Spillover Effects of Securities Companies in China’s Capital Market with the CoVaR Method," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(3), pages 1-7.
    29. International Monetary Fund, 2012. "Short-Term Wholesale Funding and Systemic Risk: A Global Covar Approach," IMF Working Papers 2012/046, International Monetary Fund.
    30. Ji, Qiang & Liu, Bing-Yue & Nehler, Henrik & Uddin, Gazi Salah, 2018. "Uncertainties and extreme risk spillover in the energy markets: A time-varying copula-based CoVaR approach," Energy Economics, Elsevier, vol. 76(C), pages 115-126.
    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. Xu, Yingying, 2021. "Risk spillover from energy market uncertainties to the Chinese carbon market," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    2. Zhu, Bangzhu & Ye, Shunxin & Han, Dong & Wang, Ping & He, Kaijian & Wei, Yi-Ming & Xie, Rui, 2019. "A multiscale analysis for carbon price drivers," Energy Economics, Elsevier, vol. 78(C), pages 202-216.
    3. Shimizu, Katsutoshi & Ly, Kim Cuong, 2017. "Were regulatory interventions effective in lowering systemic risk during the financial crisis in Japan?," Journal of Multinational Financial Management, Elsevier, vol. 41(C), pages 80-91.
    4. Morelli, David & Vioto, Davide, 2020. "Assessing the contribution of China’s financial sectors to systemic risk," Journal of Financial Stability, Elsevier, vol. 50(C).
    5. Usman, Muhammad & Umar, Zaghum & Choi, Sun-Yong & Teplova, Tamara, 2024. "Quantifying endogenous and exogenous shocks to financial sector systemic risk: A comparison of GFC and COVID-19," The Quarterly Review of Economics and Finance, Elsevier, vol. 94(C), pages 281-293.
    6. Xu, Qiuhua & Yan, Haoyang & Zhao, Tianyu, 2022. "Contagion effect of systemic risk among industry sectors in China’s stock market," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    7. Fang, Libing & Sun, Boyang & Li, Huijing & Yu, Honghai, 2018. "Systemic risk network of Chinese financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 190-206.
    8. Fenghua Wen & Kaiyan Weng & Wei-Xing Zhou, 2020. "Measuring the contribution of Chinese financial institutions to systemic risk: an extended asymmetric CoVaR approach," Risk Management, Palgrave Macmillan, vol. 22(4), pages 310-337, December.
    9. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    10. Xia, Tongshui & Yao, Chen-Xi & Geng, Jiang-Bo, 2020. "Dynamic and frequency-domain spillover among economic policy uncertainty, stock and housing markets in China," International Review of Financial Analysis, Elsevier, vol. 67(C).
    11. Zhu, Bangzhu & Yuan, Lili & Ye, Shunxin, 2019. "Examining the multi-timescales of European carbon market with grey relational analysis and empirical mode decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 392-399.
    12. Varotto, Simone & Zhao, Lei, 2018. "Systemic risk and bank size," Journal of International Money and Finance, Elsevier, vol. 82(C), pages 45-70.
    13. Curcio, Domenico & Gianfrancesco, Igor & Vioto, Davide, 2023. "Climate change and financial systemic risk: Evidence from US banks and insurers," Journal of Financial Stability, Elsevier, vol. 66(C).
    14. Abendschein, Michael & Grundke, Peter, 2018. "On the ranking consistency of global systemic risk measures: empirical evidence," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181623, Verein für Socialpolitik / German Economic Association.
    15. Bernal, Oscar & Gnabo, Jean-Yves & Guilmin, Grégory, 2014. "Assessing the contribution of banks, insurance and other financial services to systemic risk," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 270-287.
    16. Yanbin Li & Dan Nie & Bingkang Li & Xiyu Li, 2020. "The Spillover Effect between Carbon Emission Trading (CET) Price and Power Company Stock Price in China," Sustainability, MDPI, vol. 12(16), pages 1-17, August.
    17. Gu, Fu & Wang, Jiqiang & Guo, Jianfeng & Fan, Ying, 2020. "Dynamic linkages between international oil price, plastic stock index and recycle plastic markets in China," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 167-179.
    18. Liu, Xiaochun, 2017. "Measuring systemic risk with regime switching in tails," Economic Modelling, Elsevier, vol. 67(C), pages 55-72.
    19. Markus Brunnermeier & Simon Rother & Isabel Schnabel & Itay Goldstein, 2020. "Asset Price Bubbles and Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 33(9), pages 4272-4317.
    20. Bing‐Yue Liu & Qiang Ji & Duc Khuong Nguyen & Ying Fan, 2021. "Dynamic dependence and extreme risk comovement: The case of oil prices and exchange rates," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2612-2636, April.

    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:reveco:v:67:y:2020:i:c:p:163-175. 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/inca/620165 .

    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.