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The Linkages of Carbon Spot-Futures: Evidence from EU-ETS in the Third Phase

Author

Listed:
  • Hao Chen

    (School of Economics and Management, Beihang University, Beijing 100191, China)

  • Zhixin Liu

    (School of Economics and Management, Beihang University, Beijing 100191, China)

  • Yinpeng Zhang

    (College of Economics, Shenzhen University, Shenzhen 518061, China)

  • You Wu

    (School of Economics, Beijing Technology and Business University, Beijing 100048, China)

Abstract
Based on the prices selected from European Energy Exchange (EEX) from 2013 to 2018, we investigate the inter-correlation of carbon spot and futures markets. Specifically, we adopt the widely used DCC-GARCH model and VAR-BEKK-GARCH model to conduct a comprehensive analysis on the carbon market, i.e., the dynamic correlation and volatility spillover between carbon spot and carbon futures. Moreover, we develop a hedge strategy based on the VAR-BEKK-GARCH model and calculate the hedging effectiveness (HE) value to evaluate the strategy performance. The empirical results show that (i) during our sample period, carbon spot and futures markets are highly correlated, (ii) carbon spot overflows to the futures market and vice versa, and (iii) the HE value is equal to 0.9370, indicating a good performance for the hedging strategy. Then, we provide further discussion on the relationship between carbon spot and futures markets by replacing our dataset with the data of phase II. The results do not change our conclusions on the dynamic correlation and volatility spillover. However, the HE value of phase III is higher than that of phase II, which indicates that the carbon futures market of phase III is not only an available market to hedge risk from the contemporaneous carbon spot market but also has a better hedge effectiveness than phase II.

Suggested Citation

  • Hao Chen & Zhixin Liu & Yinpeng Zhang & You Wu, 2020. "The Linkages of Carbon Spot-Futures: Evidence from EU-ETS in the Third Phase," Sustainability, MDPI, vol. 12(6), pages 1-18, March.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2517-:d:336069
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    References listed on IDEAS

    as
    1. Julien Chevallier, 2010. "A Note on Cointegrating and Vector Autoregressive Relationships between CO2 allowances spot and futures prices," Economics Bulletin, AccessEcon, vol. 30(2), pages 1564-1584.
    2. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," The Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    3. Stavins, Robert N., 2003. "Experience with market-based environmental policy instruments," Handbook of Environmental Economics, in: K. G. Mäler & J. R. Vincent (ed.), Handbook of Environmental Economics, edition 1, volume 1, chapter 9, pages 355-435, Elsevier.
    4. Miao, Hong & Ramchander, Sanjay & Wang, Tianyang & Yang, Dongxiao, 2017. "Role of index futures on China's stock markets: Evidence from price discovery and volatility spillover," Pacific-Basin Finance Journal, Elsevier, vol. 44(C), pages 13-26.
    5. Arouri, Mohamed El Hédi & Jawadi, Fredj & Nguyen, Duc Khuong, 2012. "Nonlinearities in carbon spot-futures price relationships during Phase II of the EU ETS," Economic Modelling, Elsevier, vol. 29(3), pages 884-892.
    6. Param Silvapulle & Imad A. Moosa, 1999. "The relationship between spot and futures prices: Evidence from the crude oil market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(2), pages 175-193, April.
    7. Corsetti, Giancarlo & Pericoli, Marcello & Sbracia, Massimo, 2005. "'Some contagion, some interdependence': More pitfalls in tests of financial contagion," Journal of International Money and Finance, Elsevier, vol. 24(8), pages 1177-1199, December.
    8. Zhang, Yue-Jun & Lin, Jia-Juan, 2019. "Can the VAR model outperform MRS model for asset allocation in commodity market under different risk preferences of investors?," International Review of Financial Analysis, Elsevier, vol. 66(C).
    9. Guidolin, Massimo & Hyde, Stuart, 2012. "Can VAR models capture regime shifts in asset returns? A long-horizon strategic asset allocation perspective," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 695-716.
    10. Akkoc, Ugur & Civcir, Irfan, 2019. "Dynamic linkages between strategic commodities and stock market in Turkey: Evidence from SVAR-DCC-GARCH model," Resources Policy, Elsevier, vol. 62(C), pages 231-239.
    11. Benz, Eva & Trück, Stefan, 2009. "Modeling the price dynamics of CO2 emission allowances," Energy Economics, Elsevier, vol. 31(1), pages 4-15, January.
    12. Kocaarslan, Baris & Soytas, Ugur, 2019. "Dynamic correlations between oil prices and the stock prices of clean energy and technology firms: The role of reserve currency (US dollar)," Energy Economics, Elsevier, vol. 84(C).
    13. Yuan-Hung Hsu Ku & Ho-Chyuan Chen & Kuang-Hua Chen, 2007. "On the application of the dynamic conditional correlation model in estimating optimal time-varying hedge ratios," Applied Economics Letters, Taylor & Francis Journals, vol. 14(7), pages 503-509.
    14. 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.
    15. Jong-Min Kim & Hojin Jung & Li Qin, 2016. "Linear time-varying regression with a DCC-GARCH model for volatility," Applied Economics, Taylor & Francis Journals, vol. 48(17), pages 1573-1582, April.
    16. Ping, Li & Ziyi, Zhang & Tianna, Yang & Qingchao, Zeng, 2018. "The relationship among China’s fuel oil spot, futures and stock markets," Finance Research Letters, Elsevier, vol. 24(C), pages 151-162.
    17. Kang, Sang Hoon & Lee, Jang Woo, 2019. "The network connectedness of volatility spillovers across global futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    18. Feng, Zhen-Hua & Zou, Le-Le & Wei, Yi-Ming, 2011. "Carbon price volatility: Evidence from EU ETS," Applied Energy, Elsevier, vol. 88(3), pages 590-598, March.
    19. Yinpeng Zhang & Zhixin Liu & Yingying Xu, 2018. "Carbon price volatility: The case of China," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-15, October.
    20. Chiang, Thomas C. & Jeon, Bang Nam & Li, Huimin, 2007. "Dynamic correlation analysis of financial contagion: Evidence from Asian markets," Journal of International Money and Finance, Elsevier, vol. 26(7), pages 1206-1228, November.
    21. repec:dau:papers:123456789/4237 is not listed on IDEAS
    22. de Oliveira, Felipe A. & Maia, Sinézio F. & de Jesus, Diego P. & Besarria, Cássio da N., 2018. "Which information matters to market risk spreading in Brazil? Volatility transmission modelling using MGARCH-BEKK, DCC, t-Copulas," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 83-100.
    23. Fassas, Athanasios P. & Siriopoulos, Costas, 2019. "Intraday price discovery and volatility spillovers in an emerging market," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 333-346.
    24. Shiferaw, Yegnanew A., 2019. "Time-varying correlation between agricultural commodity and energy price dynamics with Bayesian multivariate DCC-GARCH models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    25. Kim, Jungmu & Park, Yuen Jung & Ryu, Doojin, 2017. "Stochastic volatility of the futures prices of emission allowances: A Bayesian approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 714-724.
    26. Efimova, Olga & Serletis, Apostolos, 2014. "Energy markets volatility modelling using GARCH," Energy Economics, Elsevier, vol. 43(C), pages 264-273.
    27. Apostolos Serletis, 2012. "Oil Price Uncertainty," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8407, February.
    28. Yinpeng Zhang & Zhixin Liu & Xueying Yu, 2017. "The Diversification Benefits of Including Carbon Assets in Financial Portfolios," Sustainability, MDPI, vol. 9(3), pages 1-13, March.
    29. Ronald D. Ripple & Imad A. Moosa, 2007. "Hedging effectiveness and futures contract maturity: the case of NYMEX crude oil futures," Applied Financial Economics, Taylor & Francis Journals, vol. 17(9), pages 683-689.
    30. Syllignakis, Manolis N. & Kouretas, Georgios P., 2011. "Dynamic correlation analysis of financial contagion: Evidence from the Central and Eastern European markets," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 717-732, October.
    31. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis," Finance Research Letters, Elsevier, vol. 29(C), pages 68-74.
    32. Rahman, Sajjadur & Serletis, Apostolos, 2012. "Oil price uncertainty and the Canadian economy: Evidence from a VARMA, GARCH-in-Mean, asymmetric BEKK model," Energy Economics, Elsevier, vol. 34(2), pages 603-610.
    33. Lin, Sharon Xiaowen & Tamvakis, Michael N., 2001. "Spillover effects in energy futures markets," Energy Economics, Elsevier, vol. 23(1), pages 43-56, January.
    34. Roselyne Joyeux & George Milunovich, 2010. "Testing market efficiency in the EU carbon futures market," Applied Financial Economics, Taylor & Francis Journals, vol. 20(10), pages 803-809.
    35. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    36. Rittler, Daniel, 2012. "Price discovery and volatility spillovers in the European Union emissions trading scheme: A high-frequency analysis," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 774-785.
    37. Baillie, Richard T & Myers, Robert J, 1991. "Bivariate GARCH Estimation of the Optimal Commodity Futures Hedge," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(2), pages 109-124, April-Jun.
    38. Lin, Arthur J. & Chang, Hai Yen & Hsiao, Jung Lieh, 2019. "Does the Baltic Dry Index drive volatility spillovers in the commodities, currency, or stock markets?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 265-283.
    39. Kim, Jong-Min & Jung, Hojin, 2016. "Linear time-varying regression with Copula–DCC–GARCH models for volatility," Economics Letters, Elsevier, vol. 145(C), pages 262-265.
    40. Leland L. Johnson, 1976. "The Theory of Hedging and Speculation in Commodity Futures," Palgrave Macmillan Books, in: The Economics of Futures Trading, chapter 3, pages 83-99, Palgrave Macmillan.
    41. Morana, Claudio, 2001. "A semiparametric approach to short-term oil price forecasting," Energy Economics, Elsevier, vol. 23(3), pages 325-338, May.
    42. Hou, Yang & Li, Steven & Wen, Fenghua, 2019. "Time-varying volatility spillover between Chinese fuel oil and stock index futures markets based on a DCC-GARCH model with a semi-nonparametric approach," Energy Economics, Elsevier, vol. 83(C), pages 119-143.
    43. Marcel Gorenflo, 2013. "Futures price dynamics of CO 2 emission allowances," Empirical Economics, Springer, vol. 45(3), pages 1025-1047, December.
    44. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
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