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Factors of carbon price volatility in a comparative analysis of the EUA and sCER

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  • Bao-jun Tang

    (Beijing Institute of Technology
    Beijing Institute of Technology)

  • Pi-qin Gong

    (Beijing Institute of Technology
    Beijing Institute of Technology)

  • Cheng Shen

    (China Shipbuilding Industry Research Center)

Abstract

The paper proposes three hypotheses for the factors of carbon price volatility on the basis of the existing literature, and then uses ensemble empirical model decomposition and variance ratio to analyze the carbon price volatility of the European Union emission trading system (EU ETS) and clean development mechanisms (CDM). The results show that carbon price volatility is mainly affected by the market mechanism and external environment. The frequency of the market mechanism is high, with the duration being $$

Suggested Citation

  • Bao-jun Tang & Pi-qin Gong & Cheng Shen, 2017. "Factors of carbon price volatility in a comparative analysis of the EUA and sCER," Annals of Operations Research, Springer, vol. 255(1), pages 157-168, August.
    • Handle: RePEc:spr:annopr:v:255:y:2017:i:1:d:10.1007_s10479-015-1864-y
    DOI: 10.1007/s10479-015-1864-y
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    References listed on IDEAS

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    Cited by:

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    2. Zhang, Lixia & Luo, Qin & Guo, Xiaozhu & Umar, Muhammad, 2022. "Medium-term and long-term volatility forecasts for EUA futures with country-specific economic policy uncertainty indices," Resources Policy, Elsevier, vol. 77(C).
    3. Zhang, Xi & Li, Jian, 2018. "Credit and market risks measurement in carbon financing for Chinese banks," Energy Economics, Elsevier, vol. 76(C), pages 549-557.
    4. 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).
    5. 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.
    6. Lin, Boqiang & Jia, Zhijie, 2019. "What will China's carbon emission trading market affect with only electricity sector involvement? A CGE based study," Energy Economics, Elsevier, vol. 78(C), pages 301-311.
    7. Bangzhu Zhu & Shunxin Ye & Kaijian He & Julien Chevallier & Rui Xie, 2019. "Measuring the risk of European carbon market: an empirical mode decomposition-based value at risk approach," Annals of Operations Research, Springer, vol. 281(1), pages 373-395, October.
    8. Peng Chen & Andrew Vivian & Cheng Ye, 2022. "Forecasting carbon futures price: a hybrid method incorporating fuzzy entropy and extreme learning machine," Annals of Operations Research, Springer, vol. 313(1), pages 559-601, June.
    9. Julien Chevallier & Stéphane Goutte, 2017. "Estimation of Lévy-driven Ornstein–Uhlenbeck processes: application to modeling of $$\hbox {CO}_2$$ CO 2 and fuel-switching," Annals of Operations Research, Springer, vol. 255(1), pages 169-197, August.
    10. Bangzhu Zhu & Ping Wang & Julien Chevallier & Yi‐Ming Wei, 2023. "Enriching the value‐at‐risk framework to ensemble empirical mode decomposition with an application to the European carbon market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2975-2988, July.
    11. Vellachami, Sanggetha & Hasanov, Akram Shavkatovich & Brooks, Robert, 2023. "Risk transmission from the energy markets to the carbon market: Evidence from the recursive window approach," International Review of Financial Analysis, Elsevier, vol. 89(C).
    12. Chang-Jing Ji & Xiao-Yi Li & Yu-Jie Hu & Xiang-Yu Wang & Bao-Jun Tang, 2019. "Research on carbon price in emissions trading scheme: a bibliometric analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(3), pages 1381-1396, December.

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