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Modeling the Risk of Extreme Value Dependence in Chinese Regional Carbon Emission Markets

Author

Listed:
  • Hong Qiu

    (School of Management, Xihua University, Chengdu 610039, China)

  • Genhua Hu

    (Anhui Institute for Innovation-Driven Development, School of Business, Anhui University of Technology, Maanshan 243032, China)

  • Yuhong Yang

    (School of Business Administration, Shanghai Lixin University of Accounting and Finance, Shanghai 201620, China)

  • Jeffrey Zhang

    (Centerville High School, Centerville, OH 45459, USA)

  • Ting Zhang

    (Department of Economics and Finance, School of Business Administration, University of Dayton, Dayton, OH 45469, USA)

Abstract

In this study, we analyze the risk of extreme value dependence in Chinese regional carbon emission markets. After filtering the daily return data of six carbon markets in China using a generalized autoregressive conditional heteroscedasticity (GARCH) model, we obtain the standardized residual series. Next, the dependence structures in the markets are captured by the Copula function and the Extreme Value theory (EVT). We report high peaks, heavy tails and fluctuation aggregation in the logarithm return series of the markets, as well as significant dependent structures. There are significant extreme value risks in Chinese regional carbon markets, but the risks can be mitigated through appropriate portfolio diversification.

Suggested Citation

  • Hong Qiu & Genhua Hu & Yuhong Yang & Jeffrey Zhang & Ting Zhang, 2020. "Modeling the Risk of Extreme Value Dependence in Chinese Regional Carbon Emission Markets," Sustainability, MDPI, vol. 12(19), pages 1-15, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:7911-:d:418785
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    2. Hongpeng Guo & Boqun Fan & Chulin Pan, 2021. "Study on Mechanisms Underlying Changes in Agricultural Carbon Emissions: A Case in Jilin Province, China, 1998–2018," IJERPH, MDPI, vol. 18(3), pages 1-17, January.

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