Testing for Self-excitation in Financial Events: A Bayesian Approach

  • Ali Caner TürkmenEmail author
  • Ali Taylan Cemgil
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11054)


Self-exciting temporal point processes are used to model a variety of financial event data including order flows, trades, and news. In this work, we take a Bayesian approach to inference and model comparison in self-exciting processes. We discuss strategies to compute marginal likelihood estimates for the univariate Hawkes process, and describe a Bayesian model comparison scheme. We demonstrate on currency, cryptocurrency and equity limit order book data that the test captures excitatory dynamics.



We gratefully acknowledge the support of Scientific and Technological Research Council of Turkey (TUBITAK), under research grant 116E580.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer EngineeringBoğaziçi UniversityIstanbulTurkey

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