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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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    1. Roberto Pascual & Alvaro Escribano & Mikel Tapia, 2004. "On the bi-dimensionality of liquidity," The European Journal of Finance, Taylor & Francis Journals, vol. 10(6), pages 542-566.
    2. Hasbrouck, Joel, 1991. "Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    3. Alfonso Dufour & Robert F. Engle, 2000. "Time and the Price Impact of a Trade," Journal of Finance, American Finance Association, vol. 55(6), pages 2467-2498, December.
    4. Benz, Eva & Trück, Stefan, 2009. "Modeling the price dynamics of CO2 emission allowances," Energy Economics, Elsevier, vol. 31(1), pages 4-15, January.
    5. De Luca, Giovanni & Zuccolotto, Paola, 2006. "Regime-switching Pareto distributions for ACD models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2179-2191, December.
    6. Hujer, Reinhard & Vuletic, Sandra, 2007. "Econometric analysis of financial trade processes by discrete mixture duration models," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 635-667, February.
    7. Xavier Vives, 1993. "How Fast do Rational Agents Learn?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(2), pages 329-347.
    8. 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.
    9. 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.
    10. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    11. Robert F. Engle, 2000. "The Econometrics of Ultra-High Frequency Data," Econometrica, Econometric Society, vol. 68(1), pages 1-22, January.
    12. Frank Gerhard & Nikolaus Hautsch, 2000. "Determinants of Inter-Trade Durations Using Proportional Hazard ARMA Models," Econometric Society World Congress 2000 Contributed Papers 1082, Econometric Society.
    13. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    14. Madhavan, Ananth, 2000. "Market microstructure: A survey," Journal of Financial Markets, Elsevier, vol. 3(3), pages 205-258, August.
    15. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    16. Gerhard, Frank & Hautsch, Nikolaus, 2000. "Determinants of Inter-Trade Durations and Hazard Rates Using Proportional Hazard ARMA Model," CoFE Discussion Papers 00/20, University of Konstanz, Center of Finance and Econometrics (CoFE).
    17. Mizrach, Bruce & Otsubo, Yoichi, 2014. "The market microstructure of the European climate exchange," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 107-116.
    18. Easley, David & O'Hara, Maureen, 1987. "Price, trade size, and information in securities markets," Journal of Financial Economics, Elsevier, vol. 19(1), pages 69-90, September.
    19. Zhang, Michael Yuanjie & Russell, Jeffrey R. & Tsay, Ruey S., 2001. "A nonlinear autoregressive conditional duration model with applications to financial transaction data," Journal of Econometrics, Elsevier, vol. 104(1), pages 179-207, August.
    20. Paolella, Marc S. & Taschini, Luca, 2008. "An econometric analysis of emission allowance prices," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2022-2032, October.
    21. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    22. Diamond, Douglas W. & Verrecchia, Robert E., 1987. "Constraints on short-selling and asset price adjustment to private information," Journal of Financial Economics, Elsevier, vol. 18(2), pages 277-311, June.
    23. Kerry Back & Shmuel Baruch, 2004. "Information in Securities Markets: Kyle Meets Glosten and Milgrom," Econometrica, Econometric Society, vol. 72(2), pages 433-465, March.
    24. Easley, David & O'Hara, Maureen, 1992. "Time and the Process of Security Price Adjustment," Journal of Finance, American Finance Association, vol. 47(2), pages 576-605, June.
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    Cited by:

    1. Zhong, Meirui & Zhang, Rui & Ren, Xiaohang, 2023. "The time-varying effects of liquidity and market efficiency of the European Union carbon market: Evidence from the TVP-SVAR-SV approach," Energy Economics, Elsevier, vol. 123(C).
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Kalaitzoglou, Iordanis Angelos & Ibrahim, Boulis Maher, 2023. "Market conditions and order-type preference," International Review of Financial Analysis, Elsevier, vol. 87(C).
    8. 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.
    9. 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.
    10. Iordanis Angelos Kalaitzoglou & Boulis Maher Ibrahim, 2015. "Liquidity and resolution of uncertainty in the European carbon futures market," Post-Print hal-01107956, HAL.
    11. 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).
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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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