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Branching ratio approximation for the self-exciting Hawkes process

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  • Stephen J. Hardiman
  • Jean-Philippe Bouchaud

Abstract

We introduce a model-independent approximation for the branching ratio of Hawkes self-exciting point processes. Our estimator requires knowing only the mean and variance of the event count in a sufficiently large time window, statistics that are readily obtained from empirical data. The method we propose greatly simplifies the estimation of the Hawkes branching ratio, recently proposed as a proxy for market endogeneity and formerly estimated using numerical likelihood maximisation. We employ our new method to support recent theoretical and experimental results indicating that the best fitting Hawkes model to describe S&P futures price changes is in fact critical (now and in the recent past) in light of the long memory of financial market activity.

Suggested Citation

  • Stephen J. Hardiman & Jean-Philippe Bouchaud, 2014. "Branching ratio approximation for the self-exciting Hawkes process," Papers 1403.5227, arXiv.org, revised Oct 2014.
    • Handle: RePEc:arx:papers:1403.5227
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    Cited by:

    1. Roger Martins & Dieter Hendricks, 2016. "The statistical significance of multivariate Hawkes processes fitted to limit order book data," Papers 1604.01824, arXiv.org, revised Apr 2016.
    2. Pierre Blanc & Jonathan Donier & Jean-Philippe Bouchaud, 2015. "Quadratic Hawkes processes for financial prices," Papers 1509.07710, arXiv.org.
    3. Emmanuel Bacry & Iacopo Mastromatteo & Jean-Franc{c}ois Muzy, 2015. "Hawkes processes in finance," Papers 1502.04592, arXiv.org, revised May 2015.
    4. Carlo Campajola & Domenico Di Gangi & Fabrizio Lillo & Daniele Tantari, 2020. "Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model," Papers 2007.15545, arXiv.org, revised Aug 2021.
    5. Hainaut, Donatien & Goutte, Stephane, 2018. "A switching microstructure model for stock prices," LIDAM Discussion Papers ISBA 2018014, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Aur'elien Alfonsi & Pierre Blanc, 2015. "Extension and calibration of a Hawkes-based optimal execution model," Papers 1506.08740, arXiv.org.
    7. Massil Achab & Emmanuel Bacry & Jean-Franc{c}ois Muzy & Marcello Rambaldi, 2017. "Analysis of order book flows using a nonparametric estimation of the branching ratio matrix," Papers 1706.03411, arXiv.org.

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