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Futures trading with information asymmetry and OTC predominance: Another look at the volume/volatility relations in the European carbon markets

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  • Rannou, Yves
  • Barneto, Pascal

Abstract

This paper constitutes the first exercise of analysing the European carbon market efficiency from a double perspective combining both nature of execution venues (screen vs. OTC trading) and their volatility/liquidity relations. Using a bivariate asymmetric GJR-GARCH model, we first document that OTC (exchange traded) trading volume shows consistent bi-(uni) directional Granger causality to our volatility estimates, consistent with greater responsiveness of the OTC (exchange traded) market to changes in market-wide (idiosyncratic) risks. Second, we report significant contemporaneous and lagged positive causality of OTC derivatives volume on spot/futures volatility confirming that the Sequential Information Arrival Hypothesis (SIAH) applies. Third, we find that the one-way causality from OTC to futures volumes is mainly driven by heterogeneous investor beliefs: trading volume provides an indication on how (private) information is dispersed and held at different levels rather than proxying information signal itself. After rejecting execution venues' substitutability, we advocate for systematic clearing and netting of OTC positions through a unique clearing house and reporting rules to identify speculation in line with Mifid (Art. 59) proposals.

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  • Rannou, Yves & Barneto, Pascal, 2016. "Futures trading with information asymmetry and OTC predominance: Another look at the volume/volatility relations in the European carbon markets," Energy Economics, Elsevier, vol. 53(C), pages 159-174.
    • Handle: RePEc:eee:eneeco:v:53:y:2016:i:c:p:159-174
    DOI: 10.1016/j.eneco.2014.10.010
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    2. Federico Galán-Valdivieso & Elena Villar-Rubio & María-Dolores Huete-Morales, 2018. "The erratic behaviour of the EU ETS on the path towards consolidation and price stability," International Environmental Agreements: Politics, Law and Economics, Springer, vol. 18(5), pages 689-706, October.
    3. Wang, Ge & Zhang, Qi & Su, Bin & Shen, Bo & Li, Yan & Li, Zhengjun, 2021. "Coordination of tradable carbon emission permits market and renewable electricity certificates market in China," Energy Economics, Elsevier, vol. 93(C).
    4. Fang, Guochang & Tian, Lixin & Liu, Menghe & Fu, Min & Sun, Mei, 2018. "How to optimize the development of carbon trading in China—Enlightenment from evolution rules of the EU carbon price," Applied Energy, Elsevier, vol. 211(C), pages 1039-1049.
    5. Xingang Zhao & Yuzhuo Zhang & Ji Liang & Yanbin Li & Rongda Jia & Ling Wang, 2018. "The Sustainable Development of the Economic-Energy-Environment (3E) System under the Carbon Trading (CT) Mechanism: A Chinese Case," Sustainability, MDPI, vol. 10(1), pages 1-21, January.
    6. Al Aali-Bujari & Francisco Venegas-Mart nez & Roberto J. Santill n-Salgado, 2018. "On the Stock Market-Electricity Sector Nexus in Latin America: A Dynamic Panel Data Model," International Journal of Energy Economics and Policy, Econjournals, vol. 8(6), pages 148-154.
    7. Zhou, Liyun & Zhang, Rixin & Huang, Jialiang, 2019. "Investor trading behavior on agricultural future prices," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 365-379.
    8. Yves Rannou & Pascal Barneto & Mohamed Amine Boutabba, 2020. "Green Bond market vs. Carbon market in Europe : Two different trajectories but some complementarities," Working Papers hal-02981422, HAL.
    9. Yang, Lu & Hamori, Shigeyuki, 2021. "The role of the carbon market in relation to the cryptocurrency market: Only diversification or more?," International Review of Financial Analysis, Elsevier, vol. 77(C).
    10. Rannou, Yves & Boutabba, Mohamed Amine & Barneto, Pascal, 2021. "Are Green Bond and Carbon Markets in Europe complements or substitutes? Insights from the activity of power firms," Energy Economics, Elsevier, vol. 104(C).
    11. Huawei Niu & Tianyu Liu, 2024. "Forecasting the volatility of European Union allowance futures with macroeconomic variables using the GJR-GARCH-MIDAS model," Empirical Economics, Springer, vol. 67(1), pages 75-96, July.
    12. Fan, John Hua & Todorova, Neda, 2017. "Dynamics of China’s carbon prices in the pilot trading phase," Applied Energy, Elsevier, vol. 208(C), pages 1452-1467.
    13. 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.
    14. Alizadeh, Amir H. & Tamvakis, Michael, 2016. "Market conditions, trader types and price–volume relation in energy futures markets," Energy Economics, Elsevier, vol. 56(C), pages 134-149.
    15. Phan, Hoàng-Long & Zurbruegg, Ralf & Brockman, Paul & Yu, Chia-Feng (Jeffrey), 2022. "Time-to-maturity and commodity futures return volatility: The role of time-varying asymmetric information," Journal of Commodity Markets, Elsevier, vol. 26(C).
    16. Tan, Xue-Ping & Wang, Xin-Yu, 2017. "Dependence changes between the carbon price and its fundamentals: A quantile regression approach," Applied Energy, Elsevier, vol. 190(C), pages 306-325.

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    More about this item

    Keywords

    Carbon markets; Asymmetric volatility; Trading volume; Market architecture;
    All these keywords.

    JEL classification:

    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G19 - Financial Economics - - General Financial Markets - - - Other

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