IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i19p7911-d418785.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/19/7911/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/19/7911/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. P. Hartmann & S. Straetmans & C. G. de Vries, 2004. "Asset Market Linkages in Crisis Periods," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 313-326, February.
    3. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    4. Sobreira, Nuno & Louro, Rui, 2020. "Evaluation of volatility models for forecasting Value-at-Risk and Expected Shortfall in the Portuguese stock market," Finance Research Letters, Elsevier, vol. 32(C).
    5. Wenjun Chu & Shanglei Chai & Xi Chen & Mo Du, 2020. "Does the Impact of Carbon Price Determinants Change with the Different Quantiles of Carbon Prices? Evidence from China ETS Pilots," Sustainability, MDPI, vol. 12(14), pages 1-19, July.
    6. Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sousa, Ricardo M., 2014. "What explain the short-term dynamics of the prices of CO2 emissions?," Energy Economics, Elsevier, vol. 46(C), pages 122-135.
    7. L. Gazola & C. Fernandes & A. Pizzinga & R. Riera, 2008. "The log-periodic-AR(1)-GARCH(1,1) model for financial crashes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 61(3), pages 355-362, February.
    8. Boyce, James K., 2018. "Carbon Pricing: Effectiveness and Equity," Ecological Economics, Elsevier, vol. 150(C), pages 52-61.
    9. Koliai, Lyes, 2016. "Extreme risk modeling: An EVT–pair-copulas approach for financial stress tests," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 1-22.
    10. Liu, Guangqiang & Wei, Yu & Chen, Yongfei & Yu, Jiang & Hu, Yang, 2018. "Forecasting the value-at-risk of Chinese stock market using the HARQ model and extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 288-297.
    11. Fuquan Zhao & Feiqi Liu & Han Hao & Zongwei Liu, 2020. "Carbon Emission Reduction Strategy for Energy Users in China," Sustainability, MDPI, vol. 12(16), pages 1-19, August.
    12. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    13. 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.
    14. Herrera, Rodrigo & González, Sergio & Clements, Adam, 2018. "Mutual excitation between OECD stock and oil markets: A conditional intensity extreme value approach," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 70-88.
    15. repec:ipg:wpaper:2014-081 is not listed on IDEAS
    16. Michael Grubb & Karsten Neuhoff, 2006. "Allocation and competitiveness in the EU emissions trading scheme: policy overview," Climate Policy, Taylor & Francis Journals, vol. 6(1), pages 7-30, January.
    17. Wang, Zong-Run & Chen, Xiao-Hong & Jin, Yan-Bo & Zhou, Yan-Ju, 2010. "Estimating risk of foreign exchange portfolio: Using VaR and CVaR based on GARCH–EVT-Copula model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4918-4928.
    18. Rosenberg, Joshua V. & Schuermann, Til, 2006. "A general approach to integrated risk management with skewed, fat-tailed risks," Journal of Financial Economics, Elsevier, vol. 79(3), pages 569-614, March.
    19. Mo, Jian-Lei & Zhu, Lei & Fan, Ying, 2012. "The impact of the EU ETS on the corporate value of European electricity corporations," Energy, Elsevier, vol. 45(1), pages 3-11.
    20. Yingkai Yin & Zhihui Jiang & Yazhou Liu & Zheng Yu, 2019. "Factors Affecting Carbon Emission Trading Price: Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(15), pages 3433-3451, December.
    21. L. Gazola & C. Fernandes & A. Pizzinga & R. Riera, 2008. "The log-periodic-AR(1)-GARCH(1,1) model for financial crashes," Papers 0801.4341, arXiv.org.
    22. Yue Dai & Nan Li & Rongrong Gu & Xiaodong Zhu, 2018. "Can China’s Carbon Emissions Trading Rights Mechanism Transform its Manufacturing Industry? Based on the Perspective of Enterprise Behavior," Sustainability, MDPI, vol. 10(7), pages 1-16, July.
    23. Brian H. Boyer & Michael S. Gibson & Mico Loretan, 1997. "Pitfalls in tests for changes in correlations," International Finance Discussion Papers 597, Board of Governors of the Federal Reserve System (U.S.).
    24. Angelidis, Timotheos & Benos, Alexandros & Degiannakis, Stavros, 2004. "The Use of GARCH Models in VaR Estimation," MPRA Paper 96332, University Library of Munich, Germany.
    25. repec:cii:cepiei:2013-q1-133-6 is not listed on IDEAS
    26. Abadie, Luis M. & Chamorro, José M., 2008. "European CO2 prices and carbon capture investments," Energy Economics, Elsevier, vol. 30(6), pages 2992-3015, November.
    27. Philip, Dennis & Shi, Yukun, 2016. "Optimal hedging in carbon emission markets using Markov regime switching models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 1-15.
    28. Theo Berger, 2013. "Forecasting value-at-risk using time varying copulas and EVT return distributions," International Economics, CEPII research center, issue 133, pages 93-106.
    29. Shawkat Hammoudeh & Duc Khuong Nguyen & Ricardo M. Sousa, 2014. "What explains the short," Working Papers 2014-81, Department of Research, Ipag Business School.
    30. Biage, Milton, 2019. "Analysis of shares frequency components on daily value-at-risk in emerging and developed markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 532(C).
    31. 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.
    32. Longin, François & Pagliardi, Giovanni, 2016. "Tail relation between return and volume in the US stock market: An analysis based on extreme value theory," Economics Letters, Elsevier, vol. 145(C), pages 252-254.
    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. 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.

    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. Garcia, René & Tsafack, Georges, 2011. "Dependence structure and extreme comovements in international equity and bond markets," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1954-1970, August.
    2. Phong Nguyen & Wei-han Liu, 2017. "Time-Varying Linkage of Possible Safe Haven Assets: A Cross-Market and Cross-asset Analysis," International Review of Finance, International Review of Finance Ltd., vol. 17(1), pages 43-76, March.
    3. Gagnon, Louis & Karolyi, G. Andrew, 2006. "Price and Volatility Transmission across Borders," Working Paper Series 2006-5, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    4. Xiaojian Su & Chao Deng, 2019. "The heterogeneous effects of exchange rate and stock market on CO2 emission allowance price in China: A panel quantile regression approach," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-11, August.
    5. Mo, Jian-Lei & Agnolucci, Paolo & Jiang, Mao-Rong & Fan, Ying, 2016. "The impact of Chinese carbon emission trading scheme (ETS) on low carbon energy (LCE) investment," Energy Policy, Elsevier, vol. 89(C), pages 271-283.
    6. Aloui, Chaker & Jammazi, Rania, 2015. "Dependence and risk assessment for oil prices and exchange rate portfolios: A wavelet based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 62-86.
    7. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    8. Berger, Theo & Gençay, Ramazan, 2018. "Improving daily Value-at-Risk forecasts: The relevance of short-run volatility for regulatory quality assessment," Journal of Economic Dynamics and Control, Elsevier, vol. 92(C), pages 30-46.
    9. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    10. Annastiina Silvennoinen & Timo Teräsvirta, 2009. "Modeling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 373-411, Fall.
    11. Lee, Chia-Hao & Chou, Pei-I, 2020. "Structural breaks in the correlations between Asian and US stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    12. Hemei Li & Zhenya Liu & Shixuan Wang, 2022. "Vines climbing higher: Risk management for commodity futures markets using a regular vine copula approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2438-2457, April.
    13. Jian-Lei Mo & Lei Zhu, 2014. "Using Floor Price Mechanisms to Promote Carbon Capture and Storage (Ccs) Investment and Co2 Abatement," Energy & Environment, , vol. 25(3-4), pages 687-707, April.
    14. Polanski, Arnold & Stoja, Evarist, 2014. "Co-dependence of extreme events in high frequency FX returns," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 164-178.
    15. Chollete, Loran & Ismailescu, Iuliana & Lu, Ching-Chih, 2014. "Dependence between Extreme Events in the Real and Financial Sectors," UiS Working Papers in Economics and Finance 2014/12, University of Stavanger.
    16. Sahamkhadam, Maziar & Stephan, Andreas & Östermark, Ralf, 2018. "Portfolio optimization based on GARCH-EVT-Copula forecasting models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 497-506.
    17. Maria Kasch & Massimiliano Caporin, 2013. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," Journal of Financial Econometrics, Oxford University Press, vol. 11(4), pages 706-742, September.
    18. Geert Bekaert & Campbell R. Harvey & Angela Ng, 2005. "Market Integration and Contagion," The Journal of Business, University of Chicago Press, vol. 78(1), pages 39-70, January.
    19. Dima Rahman, 2014. "Are banking systems increasingly fragile? Investigating financial institutions' CDS returns extreme co-movements," Quantitative Finance, Taylor & Francis Journals, vol. 14(5), pages 805-830, May.
    20. Mateusz Buczyński & Marcin Chlebus, 2021. "GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks," Working Papers 2021-08, Faculty of Economic Sciences, University of Warsaw.

    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:gam:jsusta:v:12:y:2020:i:19:p:7911-:d:418785. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.