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What makes carbon traders cluster their orders?

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  • Palao, Fernando
  • Pardo, Ángel

Abstract

The ability to trade large amounts of assets at low costs could be hindered when the size of the orders is concentrated at specific trade sizes. This paper documents evidence of size clustering behavior in the European Carbon Futures Market and analyzes the circumstances under which it happens. Our findings show that carbon trades are concentrated in sizes of one to five contracts and in multiples of five. We have also demonstrated that more clustered prices have more clustered sizes, suggesting that price and size resolution in the European Carbon Market are complementary and that carbon traders round both the price and the size of their orders. Finally, the analysis of the key determinants of the size clustering reveals that traders use a reduced number of different trade sizes when uncertainty is high, market liquidity is poor, and the desire to open new positions and cancel old ones is very strong.

Suggested Citation

  • Palao, Fernando & Pardo, Ángel, 2014. "What makes carbon traders cluster their orders?," Energy Economics, Elsevier, vol. 43(C), pages 158-165.
    • Handle: RePEc:eee:eneeco:v:43:y:2014:i:c:p:158-165
    DOI: 10.1016/j.eneco.2014.03.003
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    References listed on IDEAS

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    1. Owain ap Gwilym & Lei Meng, 2010. "Size clustering in the FTSE100 index futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(5), pages 432-443, May.
    2. Julio Lucia & Angel Pardo, 2010. "On measuring speculative and hedging activities in futures markets from volume and open interest data," Applied Economics, Taylor & Francis Journals, vol. 42(12), pages 1549-1557.
    3. Garvey, Ryan & Wu, Fei, 2014. "Clustering of intraday order-sizes by uninformed versus informed traders," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 222-235.
    4. Verousis, Thanos & ap Gwilym, Owain, 2013. "Trade size clustering and the cost of trading at the London Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 27(C), pages 91-102.
    5. 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.
    6. Conrad, Christian & Rittler, Daniel & Rotfuß, Waldemar, 2012. "Modeling and explaining the dynamics of European Union Allowance prices at high-frequency," Energy Economics, Elsevier, vol. 34(1), pages 316-326.
    7. Palao, Fernando & Pardo, Angel, 2012. "Assessing price clustering in European Carbon Markets," Applied Energy, Elsevier, vol. 92(C), pages 51-56.
    8. Clifford A. Ball & Walter N. Torous & Adrian E. Tschoegl, 1985. "The degree of price resolution: The case of the gold market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 5(1), pages 29-43, March.
    9. Medina, Vicente & Pardo, Ángel & Pascual, Roberto, 2014. "The timeline of trading frictions in the European carbon market," Energy Economics, Elsevier, vol. 42(C), pages 378-394.
    10. Harris, Lawrence, 1991. "Stock Price Clustering and Discreteness," The Review of Financial Studies, Society for Financial Studies, vol. 4(3), pages 389-415.
    11. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    12. Laurie Simon Hodrick & Pamela C. Moulton, 2009. "Liquidity: Considerations of a Portfolio Manager," Financial Management, Financial Management Association International, vol. 38(1), pages 59-74, March.
    13. Meng, Lei & Verousis, Thanos & ap Gwilym, Owain, 2013. "A substitution effect between price clustering and size clustering in credit default swaps," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 139-152.
    14. Benjamin M. Blau & Bonnie F. Van Ness & Robert A. Van Ness, 2012. "Trade Size And Price Clustering: The Case Of Short Sales And The Suspension Of Price Tests," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 35(2), pages 159-182, June.
    15. Mizrach, Bruce & Otsubo, Yoichi, 2014. "The market microstructure of the European climate exchange," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 107-116.
    16. Riccardo Curcio & Charles Goodhart, 1991. "The Clustering of Bid/Ask Prices and the Spread in the Foreign Exchange Market," FMG Discussion Papers dp110, Financial Markets Group.
    17. Robert Brooks & Edwyna Harris & Yovina Joymungul, 2013. "Price clustering in Australian water markets," Applied Economics, Taylor & Francis Journals, vol. 45(6), pages 677-685, February.
    18. Alexander, Gordon J. & Peterson, Mark A., 2007. "An analysis of trade-size clustering and its relation to stealth trading," Journal of Financial Economics, Elsevier, vol. 84(2), pages 435-471, May.
    19. repec:dau:papers:123456789/10174 is not listed on IDEAS
    20. Moulton, Pamela C., 2005. "You can't always get what you want: Trade-size clustering and quantity choice in liquidity," Journal of Financial Economics, Elsevier, vol. 78(1), pages 89-119, October.
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    Cited by:

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    2. Zhou, Xinxing & Gao, Yan & Wang, Ping & Zhu, Bangzhu & Wu, Zhanchi, 2022. "Does herding behavior exist in China's carbon markets?," Applied Energy, Elsevier, vol. 308(C).
    3. Rannou, Yves, 2019. "Limit order books, uninformed traders and commodity derivatives: Insights from the European carbon futures," Economic Modelling, Elsevier, vol. 81(C), pages 387-410.
    4. Telli, Şahin & Zhao, Xufeng, 2023. "Clustering in Bitcoin balance," Finance Research Letters, Elsevier, vol. 55(PA).
    5. Martin T. Bohl, Pierre Siklos, Claudia Wellenreuther, 2018. "Speculative Activity and Returns to Volatility of Chinese Major Agricultural Commodity Futures," LCERPA Working Papers 0111, Laurier Centre for Economic Research and Policy Analysis, revised 30 Jan 2018.
    6. Bohl, Martin T. & Siklos, Pierre L. & Wellenreuther, Claudia, 2018. "Speculative activity and returns volatility of Chinese agricultural commodity futures," Journal of Asian Economics, Elsevier, vol. 54(C), pages 69-91.
    7. Rannou, Yves, 2017. "Liquidity, information, strategic trading in an electronic order book: New insights from the European carbon markets," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 779-808.
    8. Song, Yazhi & Liu, Tiansen & Li, Yin & Zhu, Yue & Ye, Bin, 2022. "Paths and policy adjustments for improving carbon-market liquidity in China," Energy Economics, Elsevier, vol. 115(C).
    9. Ibrahim, Boulis Maher & Kalaitzoglou, Iordanis Angelos, 2016. "Why do carbon prices and price volatility change?," Journal of Banking & Finance, Elsevier, vol. 63(C), pages 76-94.
    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. Jiqiang Wang & Fu Gu & Yingpeng Liu & Ying Fan & Jianfeng Guo, 2020. "An Endowment Effect Study in the European Union Emission Trading Market based on Trading Price and Price Fluctuation," IJERPH, MDPI, vol. 17(9), pages 1-13, May.

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    More about this item

    Keywords

    Clustering; Size; EUA; ECX; EU ETS;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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