IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v27y2022i1p1280-1290.html
   My bibliography  Save this article

A new risk measurement method for China's carbon market

Author

Listed:
  • Xianzi Yang
  • Chen Zhang
  • Yu Yang
  • Wenjun Wang
  • Zulfiqar Ali Wagan

Abstract

Carbon markets were set up with the aim to achieve carbon reduction target and sustainable development. However, market risk has become one of the key factors influencing continuous development of carbon markets. Different from traditional financial asset price, carbon price has a heterogeneous characteristic in its tail distribution. The current value at risk (VaR) model with student t or generalized error distribution (GED) cannot describe the asymmetric tail distribution of carbon price. Therefore, this article propose to develop a combined model for China's carbon market risk measurement. First, extend generalized autoregressive conditional heteroscedasticity (GARCH) with standardized standard asymmetric exponential power distribution (SSAEPD) to reflect volatility clustering phenomenon and heterogeneous distribution character of China's carbon price. Then, genetic algorithm (GA) was innovatively used to solve GARCH‐SSAEPD linear programming instead of interior‐point algorithm. Finally, use VaR to measure the carbon market risk. The new model (GARCH‐SSAEPD‐GA‐VaR) is implied to China's carbon market and compared with the traditional GARCH‐VaR model, the empirical results show: (a) Compared with current VaR framework, the GARCH‐SSAEPD‐GA‐VaR model we constructed can help describe the heterogeneous tail distribution of carbon price and help increase the precision of carbon market risk measurement. (b) SSAEPD can capture fat‐tail, asymmetric effects of China's carbon price more entirely, which puts forward a new method to study the evolvement laws of carbon market risk. (c) GA is effective to achieve global optimum to some extent in parameter estimation. This study contribute to developing theory and methodology of describing particularity features of carbon price, increasing the accuracy of carbon market risk measurement and provide a new perspective for investigating the evolvement regularity of China's carbon market risks.

Suggested Citation

  • Xianzi Yang & Chen Zhang & Yu Yang & Wenjun Wang & Zulfiqar Ali Wagan, 2022. "A new risk measurement method for China's carbon market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1280-1290, January.
    • Handle: RePEc:wly:ijfiec:v:27:y:2022:i:1:p:1280-1290
    DOI: 10.1002/ijfe.2214
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.2214
    Download Restriction: no
    File URL: https://libkey.io/10.1002/ijfe.2214?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. Yu Liu & Hongwei Xiao & Precious Zikhali & Yingkang Lv, 2014. "Carbon Emissions in China: A Spatial Econometric Analysis at the Regional Level," Sustainability, MDPI, vol. 6(9), pages 1-19, September.
    2. Zhu, Bangzhu & Ma, Shujiao & Chevallier, Julien & Wei, Yiming, 2014. "Modelling the dynamics of European carbon futures price: A Zipf analysis," Economic Modelling, Elsevier, vol. 38(C), pages 372-380.
    3. Chevallier, Julien, 2011. "Detecting instability in the volatility of carbon prices," Energy Economics, Elsevier, vol. 33(1), pages 99-110, January.
    4. Mazza, Paolo & Petitjean, Mikael, 2015. "How integrated is the European carbon derivatives market?," Finance Research Letters, Elsevier, vol. 15(C), pages 18-30.
    5. Balcılar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2016. "Risk spillovers across the energy and carbon markets and hedging strategies for carbon risk," Energy Economics, Elsevier, vol. 54(C), pages 159-172.
    6. Zhu, Dongming & Zinde-Walsh, Victoria, 2009. "Properties and estimation of asymmetric exponential power distribution," Journal of Econometrics, Elsevier, vol. 148(1), pages 86-99, January.
    7. Changjian Wang & Fei Wang & Hongou Zhang & Yuyao Ye & Qitao Wu & Yongxian Su, 2014. "Carbon Emissions Decomposition and Environmental Mitigation Policy Recommendations for Sustainable Development in Shandong Province," Sustainability, MDPI, vol. 6(11), pages 1-16, November.
    8. Zhang, Yue-Jun & Wei, Yi-Ming, 2010. "An overview of current research on EU ETS: Evidence from its operating mechanism and economic effect," Applied Energy, Elsevier, vol. 87(6), pages 1804-1814, June.
    9. Bangzhu Zhu & Ping Wang & Julien Chevallier & Yi‐Ming Wei & Rui Xie, 2018. "Enriching the VaR framework to EEMD with an application to the European carbon market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 23(3), pages 315-328, July.
    10. Hung, Jui-Cheng & Lee, Ming-Chih & Liu, Hung-Chun, 2008. "Estimation of value-at-risk for energy commodities via fat-tailed GARCH models," Energy Economics, Elsevier, vol. 30(3), pages 1173-1191, May.
    11. Engle, Robert F. & Manganelli, Simone, 2001. "Value at risk models in finance," Working Paper Series 75, European Central Bank.
    12. Montagnoli, Alberto & de Vries, Frans P., 2010. "Carbon trading thickness and market efficiency," Energy Economics, Elsevier, vol. 32(6), pages 1331-1336, November.
    13. repec:dau:papers:123456789/5110 is not listed on IDEAS
    14. Alexander Afonin & Don Bredin & Keith Cuthbertson & Cal Muckley & Dirk Nitzsche, 2018. "Carbon portfolio management," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 23(4), pages 349-361, October.
    15. Jiao, Lei & Liao, Yin & Zhou, Qing, 2018. "Predicting carbon market risk using information from macroeconomic fundamentals," Energy Economics, Elsevier, vol. 73(C), pages 212-227.
    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. Hao, Xinyu & Sun, Wen & Zhang, Xiaoling, 2023. "How does a scarcer allowance remake the carbon market? An evolutionary game analysis from the perspective of stakeholders," Energy, Elsevier, vol. 280(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. Xianzi Yang & Chen Zhang & Yu Yang & Yaqi Wu & Po Yun & Zulfiqar Ali Wagan, 2020. "China’s Carbon Pricing Based on Heterogeneous Tail Distribution," Sustainability, MDPI, vol. 12(7), pages 1-16, April.
    2. Chang, Kai & Chen, Rongda & Chevallier, Julien, 2018. "Market fragmentation, liquidity measures and improvement perspectives from China's emissions trading scheme pilots," Energy Economics, Elsevier, vol. 75(C), pages 249-260.
    3. Demiralay, Sercan & Gencer, Hatice Gaye & Bayraci, Selcuk, 2022. "Carbon credit futures as an emerging asset: Hedging, diversification and downside risks," Energy Economics, Elsevier, vol. 113(C).
    4. Chang, Kai & Pei, Ping & Zhang, Chao & Wu, Xin, 2017. "Exploring the price dynamics of CO2 emissions allowances in China's emissions trading scheme pilots," Energy Economics, Elsevier, vol. 67(C), pages 213-223.
    5. 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.
    6. Getachew Nigatu, 2016. "Assessing the effects of climate change policy on the volatility of carbon prices in reference to the Great Recession," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 5(2), pages 200-215, July.
    7. Cretí, Anna & Joëts, Marc, 2017. "Multiple bubbles in the European Union Emission Trading Scheme," Energy Policy, Elsevier, vol. 107(C), pages 119-130.
    8. Chen, Huayi & Shi, Huai-Long & Zhou, Wei-Xing, 2024. "Carbon volatility connectedness and the role of external uncertainties: Evidence from China," Journal of Commodity Markets, Elsevier, vol. 33(C).
    9. 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.
    10. Friedrich, Marina & Mauer, Eva-Maria & Pahle, Michael & Tietjen, Oliver, 2020. "From fundamentals to financial assets: the evolution of understanding price formation in the EU ETS," EconStor Preprints 196150, ZBW - Leibniz Information Centre for Economics, revised 2020.
    11. Fang, Sheng & Lu, Xinsheng & Li, Jianfeng & Qu, Ling, 2018. "Multifractal detrended cross-correlation analysis of carbon emission allowance and stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 551-566.
    12. 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).
    13. Zhao, Xin-gang & Wu, Lei & Li, Ang, 2017. "Research on the efficiency of carbon trading market in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1-8.
    14. Fang Zhang & Zhengjun Zhang, 2020. "The tail dependence of the carbon markets: The implication of portfolio management," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-17, August.
    15. Wen, Xiaoqian & Bouri, Elie & Roubaud, David, 2017. "Can energy commodity futures add to the value of carbon assets?," Economic Modelling, Elsevier, vol. 62(C), pages 194-206.
    16. Remes, Piia, 2013. "Putting a Price on Carbon – Econometric Essays on the European Union Emissions Trading Scheme and its Impacts," Research Reports 62, VATT Institute for Economic Research.
    17. Chen, Weidong & Xiong, Shi & Chen, Quanyu, 2022. "Characterizing the dynamic evolutionary behavior of multivariate price movement fluctuation in the carbon-fuel energy markets system from complex network perspective," Energy, Elsevier, vol. 239(PA).
    18. 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.
    19. Hintermann, Beat & Peterson, Sonja & Rickels, Wilfried, 2014. "Price and market behavior in Phase II of the EU ETS," Kiel Working Papers 1962, Kiel Institute for the World Economy (IfW Kiel).
    20. 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.

    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:wly:ijfiec:v:27:y:2022:i:1:p:1280-1290. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1076-9307/ .

    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.