IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0298811.html

Source tracing and contagion measurement of carbon emission trading price fluctuation in China from the perspective of major emergencies

Author

Listed:
  • Binhong Wu
  • Hongyu Wang
  • Bangsheng Xie
  • Zhizhong Xie

Abstract

Based on monthly economic data spanning from January 2015 to December 2022, we have established an analytical framework to examine the "Russia-Ukraine conflict—financial market pressure and energy market—China carbon emission trading prices." To achieve this objective, we developed indices for financial system pressure, the energy market, and investor sentiment, applying a mediation effects model to validate their transmission mechanisms. Subsequently, the TVP-SV-VAR model was employed to scrutinize the nonlinear impact of the Russia-Ukraine conflict on the valuation of China’s carbon emission trading rights. This model integrates time-varying parameters (TVP) and stochastic volatility (SV), utilizing Markov Chain Monte Carlo (MCMC) technology for parameter estimation. Finally, various wavelet analysis techniques, including continuous wavelet transform, cross-wavelet transform, and wavelet coherence spectrum, were applied to decompose time series data into distinct time-frequency scales, facilitating an analysis of the lead-lag relationships within each time series. The research outcomes provide crucial insights for safeguarding the interests of trading organizations, refining the structure of the carbon market, and mitigating systemic risks on a global scale.

Suggested Citation

  • Binhong Wu & Hongyu Wang & Bangsheng Xie & Zhizhong Xie, 2024. "Source tracing and contagion measurement of carbon emission trading price fluctuation in China from the perspective of major emergencies," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-19, March.
    • Handle: RePEc:plo:pone00:0298811
    DOI: 10.1371/journal.pone.0298811
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0298811
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0298811&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0298811?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
    ---><---

    References listed on IDEAS

    as
    1. Ramsey James B. & Lampart Camille, 1998. "The Decomposition of Economic Relationships by Time Scale Using Wavelets: Expenditure and Income," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(1), pages 1-22, April.
    2. repec:dau:papers:123456789/6969 is not listed on IDEAS
    3. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2020. "How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics," Energy Economics, Elsevier, vol. 90(C).
    4. Dai, Peng-Fei & Xiong, Xiong & Duc Huynh, Toan Luu & Wang, Jiqiang, 2022. "The impact of economic policy uncertainties on the volatility of European carbon market," Journal of Commodity Markets, Elsevier, vol. 26(C).
    5. Bel, Germà & Joseph, Stephan, 2015. "Emission abatement: Untangling the impacts of the EU ETS and the economic crisis," Energy Economics, Elsevier, vol. 49(C), pages 531-539.
    6. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    7. Chevallier, Julien, 2011. "A model of carbon price interactions with macroeconomic and energy dynamics," Energy Economics, Elsevier, vol. 33(6), pages 1295-1312.
    8. Raza, Syed Ali & Shahbaz, Muhammad & Amir-ud-Din, Rafi & Sbia, Rashid & Shah, Nida, 2018. "Testing for wavelet based time-frequency relationship between oil prices and US economic activity," Energy, Elsevier, vol. 154(C), pages 571-580.
    9. Nerlinger, Martin & Utz, Sebastian, 2022. "The impact of the Russia-Ukraine conflict on energy firms: A capital market perspective," Finance Research Letters, Elsevier, vol. 50(C).
    10. Umar, Zaghum & Bossman, Ahmed & Choi, Sun-Yong & Vo, Xuan Vinh, 2023. "Are short stocks susceptible to geopolitical shocks? Time-Frequency evidence from the Russian-Ukrainian conflict," Finance Research Letters, Elsevier, vol. 52(C).
    11. Aloui, Chaker & Hkiri, Besma, 2014. "Co-movements of GCC emerging stock markets: New evidence from wavelet coherence analysis," Economic Modelling, Elsevier, vol. 36(C), pages 421-431.
    12. Jin, Jiayu & Han, Liyan & Wu, Lei & Zeng, Hongchao, 2020. "The hedging effect of green bonds on carbon market risk," International Review of Financial Analysis, Elsevier, vol. 71(C).
    13. Islamaj, Ergys & Kose, M. Ayhan, 2022. "What types of capital flows help improve international risk sharing?," Journal of International Money and Finance, Elsevier, vol. 122(C).
    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. Li, Houjian & Li, Qingman & Huang, Xinya & Guo, Lili, 2023. "Do green bonds and economic policy uncertainty matter for carbon price? New insights from a TVP-VAR framework," International Review of Financial Analysis, Elsevier, vol. 86(C).
    2. Qi, Shaozhou & Pang, Lidong & Li, Xinqiang & Huang, Lin, 2025. "The dynamic connectedness in the “carbon-energy-green finance” system: The role of climate policy uncertainty and artificial intelligence," Energy Economics, Elsevier, vol. 143(C).
    3. Wu, Hao & Huang, Yuan, 2025. "Identifying risk transmission in carbon, energy and metal markets: Evidence from a novel quantile frequency connectedness approach," The North American Journal of Economics and Finance, Elsevier, vol. 76(C).
    4. Wang, Jiqian & Guo, Xiaozhu & Tan, Xueping & Chevallier, Julien & Ma, Feng, 2023. "Which exogenous driver is informative in forecasting European carbon volatility: Bond, commodity, stock or uncertainty?," Energy Economics, Elsevier, vol. 117(C).
    5. Maneejuk, Paravee & Huang, Wucaihong & Yamaka, Woraphon, 2025. "Asymmetric volatility spillover effects from energy, agriculture, green bond, and financial market uncertainty on carbon market during major market crisis," Energy Economics, Elsevier, vol. 145(C).
    6. Mohammed Ahmar Uddin & Bisharat Hussain Chang & Salem Hamad Aldawsari & Ruoyu Li, 2025. "The Interplay Between Green Finance, Policy Uncertainty and Carbon Market Volatility: A Time Frequency Approach," Sustainability, MDPI, vol. 17(3), pages 1-28, February.
    7. Sousa, Rita & Aguiar-Conraria, Luís & Soares, Maria Joana, 2014. "Carbon financial markets: A time–frequency analysis of CO2 prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 118-127.
    8. Oguzhan Ozcelebi & Kaya Tokmakcioglu, 2022. "Assessment of the asymmetric impacts of the geopolitical risk on oil market dynamics," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 275-289, January.
    9. Zhong, Meirui & Zhang, Rui & Ren, Xiaohang, 2023. "The time-varying effects of liquidity and market efficiency of the European Union carbon market: Evidence from the TVP-SVAR-SV approach," Energy Economics, Elsevier, vol. 123(C).
    10. Ali Matar, 2020. "Does electricity consumption impacting financial development? Wavelet analysis," Future Business Journal, Springer, vol. 6(1), pages 1-9, December.
    11. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Noman, Ambreen, 2021. "The volatility connectedness of the EU carbon market with commodity and financial markets in time- and frequency-domain: The role of the U.S. economic policy uncertainty," Resources Policy, Elsevier, vol. 74(C).
    12. Chun, Dohyun & Cho, Hoon & Kim, Jihun, 2022. "The relationship between carbon-intensive fuel and renewable energy stock prices under the emissions trading system," Energy Economics, Elsevier, vol. 114(C).
    13. Jian Liu & Ziting Zhang & Lizhao Yan & Fenghua Wen, 2021. "Forecasting the volatility of EUA futures with economic policy uncertainty using the GARCH-MIDAS model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
    14. Muhammad Azmat Hayat & Huma Ghulam & Maryam Batool & Muhammad Zahid Naeem & Abdullah Ejaz & Cristi Spulbar & Ramona Birau, 2021. "Investigating the Causal Linkages among Inflation, Interest Rate, and Economic Growth in Pakistan under the Influence of COVID-19 Pandemic: A Wavelet Transformation Approach," JRFM, MDPI, vol. 14(6), pages 1-22, June.
    15. Zheng, Yan & Yin, Hua & Zhou, Min & Liu, Wenhua & Wen, Fenghua, 2021. "Impacts of oil shocks on the EU carbon emissions allowances under different market conditions," Energy Economics, Elsevier, vol. 104(C).
    16. Ren, Xiaohang & Li, Yiying & yan, Cheng & Wen, Fenghua & Lu, Zudi, 2022. "The interrelationship between the carbon market and the green bonds market: Evidence from wavelet quantile-on-quantile method," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    17. Wang, Lu & Ruan, Hang & Lai, Xiaodong & Li, Dongxin, 2024. "Economic extremes steering renewable energy trajectories: A time-frequency dissection of global shocks," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    18. Naeem, Muhammad Abubakr & Husain, Afzol & Bossman, Ahmed & Karim, Sitara, 2024. "Assessing the linkage of energy cryptocurrency with clean and dirty energy markets," Energy Economics, Elsevier, vol. 130(C).
    19. Xu, Yingying & Dai, Yifan & Guo, Lingling & Chen, Jingjing, 2024. "Leveraging machine learning to forecast carbon returns: Factors from energy markets," Applied Energy, Elsevier, vol. 357(C).
    20. Yanping Liu & Bo Yan, 2024. "Spillover effects of carbon, energy, and stock markets considering economic policy uncertainty," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 48(3), pages 563-591, September.

    More about this item

    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:plo:pone00:0298811. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.