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Does order flow in the European Carbon Futures Market reveal information?

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  • Kalaitzoglou, Iordanis
  • Ibrahim, Boulis M.

Abstract

This paper identifies the classes of agents at play in the European Carbon Futures Market and analyzes their trading behaviour during the market's early development period. A number of hypotheses related to microstructure are tested using enhanced ACD models. Evidence is presented that the market is characterized by three different groups of traders: informed, fundamental, and uninformed. OTC trades are distinct to regular trades and are used strategically by the informed. Fundamental traders react faster in Phase II and the informed counteract by increasing their trade size and speed. The results indicate enhanced market transparency and increased market maturity.

Suggested Citation

  • Kalaitzoglou, Iordanis & Ibrahim, Boulis M., 2013. "Does order flow in the European Carbon Futures Market reveal information?," Journal of Financial Markets, Elsevier, vol. 16(3), pages 604-635.
  • Handle: RePEc:eee:finmar:v:16:y:2013:i:3:p:604-635
    DOI: 10.1016/j.finmar.2012.11.002
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    Citations

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    Cited by:

    1. Chen, Jiayuan & Muckley, Cal B. & Bredin, Don, 2017. "Is information assimilated at announcements in the European carbon market?," Energy Economics, Elsevier, vol. 63(C), pages 234-247.
    2. Mengyu Zhang & Thanos Verousis & Iordanis Kalaitzoglou, 2022. "Information and the arrival rate of option trading volume," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(4), pages 605-644, April.
    3. Kalaitzoglou, Iordanis Angelos & Ibrahim, Boulis Maher, 2015. "Liquidity and resolution of uncertainty in the European carbon futures market," International Review of Financial Analysis, Elsevier, vol. 37(C), pages 89-102.
    4. Lucia, Julio J. & Mansanet-Bataller, Maria & Pardo, Ángel, 2015. "Speculative and hedging activities in the European carbon market," Energy Policy, Elsevier, vol. 82(C), pages 342-351.
    5. 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.
    6. 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.
    7. Ibikunle, Gbenga & Gregoriou, Andros & Hoepner, Andreas G.F. & Rhodes, Mark, 2016. "Liquidity and market efficiency in the world's largest carbon market," The British Accounting Review, Elsevier, vol. 48(4), pages 431-447.
    8. Iordanis Angelos Kalaitzoglou & Boulis Maher Ibrahim, 2015. "Liquidity and resolution of uncertainty in the European carbon futures market," Post-Print hal-01107956, HAL.
    9. Don Bredin and John Parsons, 2016. "Why is Spot Carbon so Cheap and Future Carbon so Dear? The Term Structure of Carbon Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    10. 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.
    11. 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.
    12. Bredin, Don & Hyde, Stuart & Muckley, Cal, 2014. "A microstructure analysis of the carbon finance market," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 222-234.
    13. 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.
    14. Balietti, Anca Claudia, 2016. "Trader types and volatility of emission allowance prices. Evidence from EU ETS Phase I," Energy Policy, Elsevier, vol. 98(C), pages 607-620.

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    More about this item

    Keywords

    Carbon market; Microstructure; Duration model; Ultra-high-frequency data;
    All these keywords.

    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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