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Hawkes model for price and trades high-frequency dynamics

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  • E. Bacry
  • J. F Muzy

Abstract

We introduce a multivariate Hawkes process that accounts for the dynamics of market prices through the impact of market order arrivals at microstructural level. Our model is a point process mainly characterized by 4 kernels associated with respectively the trade arrival self-excitation, the price changes mean reversion the impact of trade arrivals on price variations and the feedback of price changes on trading activity. It allows one to account for both stylized facts of market prices microstructure (including random time arrival of price moves, discrete price grid, high frequency mean reversion, correlation functions behavior at various time scales) and the stylized facts of market impact (mainly the concave-square-root-like/relaxation characteristic shape of the market impact of a meta-order). Moreover, it allows one to estimate the entire market impact profile from anonymous market data. We show that these kernels can be estimated from the empirical conditional mean intensities. We provide numerical examples, application to real data and comparisons to former approaches.

Suggested Citation

  • E. Bacry & J. F Muzy, 2013. "Hawkes model for price and trades high-frequency dynamics," Papers 1301.1135, arXiv.org.
  • Handle: RePEc:arx:papers:1301.1135
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    References listed on IDEAS

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    1. Eric Smith & J Doyne Farmer & Laszlo Gillemot & Supriya Krishnamurthy, 2003. "Statistical theory of the continuous double auction," Quantitative Finance, Taylor & Francis Journals, vol. 3(6), pages 481-514.
    2. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    3. J. Doyne Farmer & Paolo Patelli & Ilija I. Zovko, 2003. "The Predictive Power of Zero Intelligence in Financial Markets," Papers cond-mat/0309233, arXiv.org, revised Feb 2004.
    4. Esteban Moro & Javier Vicente & Luis G. Moyano & Austin Gerig & J. Doyne Farmer & Gabriella Vaglica & Fabrizio Lillo & Rosario N. Mantegna, 2009. "Market impact and trading profile of large trading orders in stock markets," Papers 0908.0202, arXiv.org.
    5. Frédéric Abergel & Anirban Chakraborti & B.K. Chakrabarti & M. Mitra, 2011. "Econophysics of order-driven markets," Post-Print hal-00872396, HAL.
    6. Jim Gatheral, 2010. "No-dynamic-arbitrage and market impact," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 749-759.
    7. E. Bacry & S. Delattre & M. Hoffmann & J. F. Muzy, 2013. "Modelling microstructure noise with mutually exciting point processes," Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 65-77, January.
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    Cited by:

    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. Weibing Huang & Charles-Albert Lehalle & Mathieu Rosenbaum, 2015. "Simulating and Analyzing Order Book Data: The Queue-Reactive Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 107-122, March.
    3. Emmanuel Bacry & Adrian Iuga & Matthieu Lasnier & Charles-Albert Lehalle, 2014. "Market impacts and the life cycle of investors orders," Papers 1412.0217, arXiv.org, revised Dec 2014.
    4. Markus Bibinger & Moritz Jirak & Markus Reiss, 2014. "Improved Volatility Estimation Based On Limit Order Books," SFB 649 Discussion Papers SFB649DP2014-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Aymen Jedidi & Frédéric Abergel, 2013. "Stability and price scaling limit of a Hawkes-process based order book model," Working Papers hal-00821607, HAL.
    6. Aurélien Alfonsi & Pierre Blanc, 2016. "Dynamic optimal execution in a mixed-market-impact Hawkes price model," Post-Print hal-00971369, HAL.

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