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LOB modeling using Hawkes processes with a state-dependent factor

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  • Emmanouil Sfendourakis
  • Ioane Muni Toke

Abstract

A point process model for order flows in limit order books is proposed, in which the conditional intensity is the product of a Hawkes component and a state-dependent factor. In the LOB context, state observations may include the observed imbalance or the observed spread. Full technical details for the computationally-efficient estimation of such a process are provided, using either direct likelihood maximization or EM-type estimation. Applications include models for bid and ask market orders, or for upwards and downwards price movements. Empirical results on multiple stocks traded in Euronext Paris underline the benefits of state-dependent formulations for LOB modeling, e.g. in terms of goodness-of-fit to financial data.

Suggested Citation

  • Emmanouil Sfendourakis & Ioane Muni Toke, 2021. "LOB modeling using Hawkes processes with a state-dependent factor," Papers 2107.12872, arXiv.org, revised Dec 2021.
    • Handle: RePEc:arx:papers:2107.12872
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    File URL: http://arxiv.org/pdf/2107.12872
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    References listed on IDEAS

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    1. Alexander Lipton & Umberto Pesavento & Michael G Sotiropoulos, 2013. "Trade arrival dynamics and quote imbalance in a limit order book," Papers 1312.0514, arXiv.org.
    2. Maxime Morariu-Patrichi & Mikko Pakkanen, 2018. "State-dependent Hawkes processes and their application to limit order book modelling," CREATES Research Papers 2018-26, Department of Economics and Business Economics, Aarhus University.
    3. Xiaofei Lu & Frédéric Abergel, 2018. "High-dimensional Hawkes processes for limit order books: modelling, empirical analysis and numerical calibration," Quantitative Finance, Taylor & Francis Journals, vol. 18(2), pages 249-264, February.
    4. Mehdi Lallouache & Damien Challet, 2016. "The limits of statistical significance of Hawkes processes fitted to financial data," Quantitative Finance, Taylor & Francis Journals, vol. 16(1), pages 1-11, January.
    5. Rama Cont & Sasha Stoikov & Rishi Talreja, 2010. "A Stochastic Model for Order Book Dynamics," Operations Research, INFORMS, vol. 58(3), pages 549-563, June.
    6. Stephen Hardiman & Nicolas Bercot & Jean-Philippe Bouchaud, 2013. "Critical reflexivity in financial markets: a Hawkes process analysis," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(10), pages 1-9, October.
    7. Xiaofei Lu & Frédéric Abergel, 2018. "High dimensional Hawkes processes for limit order books Modelling, empirical analysis and numerical calibration," Post-Print hal-01686122, HAL.
    8. Ioane Muni Toke & Nakahiro Yoshida, 2020. "Analyzing order flows in limit order books with ratios of Cox-type intensities," Quantitative Finance, Taylor & Francis Journals, vol. 20(1), pages 81-98, January.
    9. Abergel,Frédéric & Anane,Marouane & Chakraborti,Anirban & Jedidi,Aymen & Muni Toke,Ioane, 2016. "Limit Order Books," Cambridge Books, Cambridge University Press, number 9781107163980, November.
    10. Frédéric Abergel & Anirban Chakraborti & Aymen Jedidi & Ioane Muni Toke & Marouane Anane, 2016. "Limit Order Books," Post-Print hal-02177394, HAL.
    11. Ioane Muni Toke & Nakahiro Yoshida, 2020. "Analyzing order flows in limit order books with ratios of Cox-type intensities," Post-Print hal-01799398, HAL.
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    Cited by:

    1. Luca Lalor & Anatoliy Swishchuk, 2024. "Algorithmic and High-Frequency Trading Problems for Semi-Markov and Hawkes Jump-Diffusion Models," Papers 2409.12776, arXiv.org.

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