Testing the causality of Hawkes processes with time reversal

Abstract : We show that univariate and symmetric multivariate Hawkes processes are only weakly causal: the true log-likelihoods of real and reversed event time vectors are almost equal, thus parameter estimation via maximum likelihood only weakly depends on the direction of the arrow of time. In ideal (synthetic) conditions, tests of goodness of parametric fit unambiguously reject backward event times, which implies that inferring kernels from time-symmetric quantities, such as the autocovariance of the event rate, only rarely produce statistically significant fits. Finally, we find that fitting financial data with many-parameter kernels may yield significant fits for both arrows of time for the same event time vector, sometimes favouring the backward time direction. This goes to show that a significant fit of Hawkes processes to real data with flexible kernels does not imply a definite arrow of time unless one tests it.
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Contributor : Marcus Cordi <>
Submitted on : Tuesday, September 26, 2017 - 11:47:53 AM
Last modification on : Wednesday, April 17, 2019 - 2:56:14 PM

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  • HAL Id : hal-01593448, version 1
  • ARXIV : 1709.08516


Marcus Cordi, Damien Challet, Ioane Muni Toke. Testing the causality of Hawkes processes with time reversal. Journal of Statistical Mechanics: Theory and Experiment, IOP Publishing, 2018. ⟨hal-01593448⟩



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