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Intraday Transaction Price Dynamics

Author

Listed:
  • Gaëlle Le Fol

    (DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

  • Serge Darolles

    (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique)

  • Christian Gourieroux

    (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique, Department of Economics - University of Toronto)

Abstract

High frequency transaction prices exhibit two major characteristics: they are discrete in level and only exist at random transaction dates. In this paper we seek to model transaction price dynamics, taking into account these two features. We specify the transaction price process as a Markov Chain with random transaction dates, and discuss various tools for dynamic analysis like the canonical decomposition, the scale and speed measures. The approach is applied to high frequency data on the stock Elf-Aquitaine traded on the Paris Bourse.

Suggested Citation

  • Gaëlle Le Fol & Serge Darolles & Christian Gourieroux, 1999. "Intraday Transaction Price Dynamics," Post-Print halshs-00536272, HAL.
    • Handle: RePEc:hal:journl:halshs-00536272
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    Cited by:

    1. Antonio A. F. Santos, 2021. "Bayesian Estimation for High-Frequency Volatility Models in a Time Deformed Framework," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 455-479, February.
    2. Edson Kambeu & Olipha Mpofu & Drayton Muchochoma, 2017. "Price Discovery and Volatility:A theoretical Approach," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 6(2), pages 37-43, April.
    3. Tina Hviid Rydberg & Neil Shephard, 2003. "Dynamics of Trade-by-Trade Price Movements: Decomposition and Models," Journal of Financial Econometrics, Oxford University Press, vol. 1(1), pages 2-25.
    4. Hautsch, Nikolaus & Pohlmeier, Winfried, 2001. "Econometric Analysis of Financial Transaction Data: Pitfalls and Opportunities," CoFE Discussion Papers 01/05, University of Konstanz, Center of Finance and Econometrics (CoFE).
    5. Joann Jasiak, 1996. "Persistence in Intertrade Durations," Working Papers 1999_8, York University, Department of Economics, revised Mar 1999.
    6. Simonsen, Ola, 2005. "An Empirical Model for Durations in Stocks," Umeå Economic Studies 657, Umeå University, Department of Economics.
    7. Nikolaus Hautsch, 1999. "Analyzing the Time between Trades with a Gamma Compounded Hazard Model. An Application to LIFFE Bund Future Transactions," Finance 9904002, University Library of Munich, Germany.
    8. Ola Simonsen, 2007. "An empirical model for durations in stocks," Annals of Finance, Springer, vol. 3(2), pages 241-255, March.
    9. GIOT, Pierre, 1999. "Time transformations, intraday data and volatility models," LIDAM Discussion Papers CORE 1999044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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