The Queue-Hawkes Process: Ephemeral Self-Excitement

In this paper we consider a self-exciting model that couples a Hawkes process and a queueing system which we call the Queue-Hawkes process. In this process the intensity responds to the queue: increasing at arrivals, dropping upon departures, and decaying between. Hence the influence of each arrival is ephemeral, as the excitement only lasts for the duration of the entity's time in system. We study this process both individually and by comparison to other processes, primarily the Hawkes process and the Affine Queue-Hawkes process, which we define as the zero-decay case of the Queue-Hawkes. Our results include showing that a batch-scaling of the Affine Queue-Hawkes process will converge to the Hawkes process. We also prove a strong law of large numbers for the non-identical and dependent inter-arrival times of the Queue-Hawkes, Hawkes, and Affine Queue-Hawkes processes. Additionally, we provide all moments of the Hawkes process and the Affine Queue-Hawkes process via a novel matrix structure. Finally, we prove fluid and diffusion limits for the Queue-Hawkes process using moment generating function techniques.

[1]  Esko Valkeila,et al.  An Introduction to the Theory of Point Processes, Volume II: General Theory and Structure, 2nd Edition by Daryl J. Daley, David Vere‐Jones , 2008 .

[2]  Richard H. Rand,et al.  An analysis of queues with delayed information and time-varying arrival rates , 2018 .

[3]  A. Dassios,et al.  A dynamic contagion process , 2011, Advances in Applied Probability.

[4]  Guodong Pang,et al.  Two-parameter heavy-traffic limits for infinite-server queues with dependent service times , 2013, Queueing Syst. Theory Appl..

[5]  Lingjiong Zhu,et al.  Dynamics of Order Positions and Related Queues in a Limit Order Book , 2015, 1505.04810.

[6]  Eric P. Xing,et al.  Dynamic Non-Parametric Mixture Models and the Recurrent Chinese Restaurant Process: with Applications to Evolutionary Clustering , 2008, SDM.

[7]  Hongyuan Zha,et al.  Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence Towards Effective Prioritizing Water Pipe Replacement and Rehabilitation ∗ , 2022 .

[8]  Erik A. van Doorn,et al.  On the α-classification of birth-death and quasi-birth-death processes , 2006 .

[9]  Hongyuan Zha,et al.  Discrete Interventions in Hawkes Processes with Applications in Invasive Species Management , 2018, IJCAI.

[10]  Ward Whitt,et al.  The Physics of the Mt/G/∞ Queue , 1993, Oper. Res..

[11]  Onno Boxma,et al.  Networks of ·/G/∞ queues with shot-noise-driven arrival intensities , 2016 .

[12]  Xiang Zhou,et al.  Transform analysis for Hawkes processes with applications in dark pool trading , 2017, 1710.01452.

[13]  Ronald W. Wolff,et al.  Poisson Arrivals See Time Averages , 1982, Oper. Res..

[14]  A. Hawkes Point Spectra of Some Mutually Exciting Point Processes , 1971 .

[15]  Le Song,et al.  Fake News Mitigation via Point Process Based Intervention , 2017, ICML.

[16]  K. Giesecke,et al.  Exploring the Sources of Default Clustering , 2017, Journal of Financial Economics.

[17]  Maurizio Porfiri,et al.  Modeling Memory Effects in Activity-Driven Networks , 2018, SIAM J. Appl. Dyn. Syst..

[18]  David Blackwell,et al.  A renewal theorem , 1948 .

[19]  C. Myers,et al.  Outbreak statistics and scaling laws for externally driven epidemics. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[20]  Xuefeng Gao,et al.  Functional central limit theorems for stationary Hawkes processes and application to infinite-server queues , 2016, Queueing Systems.

[21]  Kay Giesecke,et al.  Affine Point Processes and Portfolio Credit Risk , 2010, SIAM J. Financial Math..

[22]  D. Karlis,et al.  Mixed Poisson Distributions , 2005 .

[23]  Hongyuan Zha,et al.  Energy Usage Behavior Modeling in Energy Disaggregation via Hawkes Processes , 2018, ACM Trans. Intell. Syst. Technol..

[24]  A. Dassios,et al.  Exact Simulation of Hawkes Process with Exponentially Decaying Intensity , 2013 .

[25]  J. Lloyd-Smith Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious Diseases , 2007, PloS one.

[26]  Jamol Pender,et al.  On the distributions of infinite server queues with batch arrivals , 2019, Queueing Syst. Theory Appl..

[27]  D. Blackwell,et al.  Ferguson Distributions Via Polya Urn Schemes , 1973 .

[28]  Richard J. Boucherie,et al.  Shot-noise fluid queues and infinite-server systems with batch arrivals , 2017, Perform. Evaluation.

[29]  J. Bouchaud,et al.  Quadratic Hawkes processes for financial prices , 2015, 1509.07710.

[30]  Hongyuan Zha,et al.  Trailer Generation via a Point Process-Based Visual Attractiveness Model , 2015, IJCAI.

[31]  Emmanuel Bacry,et al.  Queue-reactive Hawkes models for the order flow , 2019, 1901.08938.

[32]  Samuel Karlin,et al.  The classification of birth and death processes , 1957 .

[33]  Riadh Zaatour,et al.  Hawkes Process: Fast Calibration, Application to Trade Clustering and Diffusive Limit , 2013, Journal of Futures Markets.

[34]  Lingjiong Zhu,et al.  Large deviations and applications for Markovian Hawkes processes with a large initial intensity , 2016, Bernoulli.

[35]  Jamol Pender,et al.  Exact simulation of the queue-hawkes process , 2018, WSC 2018.

[36]  C. Rudin,et al.  Reactive point processes: A new approach to predicting power failures in underground electrical systems , 2015, 1505.07661.

[37]  Stephen Suen,et al.  A note on moment generating functions , 2006 .

[38]  A. Hawkes Spectra of some self-exciting and mutually exciting point processes , 1971 .

[39]  Remco van der Hofstad,et al.  An Elementary Proof of the Hitting Time Theorem , 2008, Am. Math. Mon..

[40]  W. Rudin Principles of mathematical analysis , 1964 .

[41]  A. Hawkes,et al.  A cluster process representation of a self-exciting process , 1974, Journal of Applied Probability.

[42]  E. Bacry,et al.  Estimation of slowly decreasing Hawkes kernels: application to high-frequency order book dynamics , 2016 .

[43]  Yosihiko Ogata,et al.  Statistical Models for Earthquake Occurrences and Residual Analysis for Point Processes , 1988 .

[44]  Peter W. Glynn,et al.  Rare event simulation for a generalized Hawkes process , 2009, Proceedings of the 2009 Winter Simulation Conference (WSC).

[45]  R. Otter The Multiplicative Process , 1949 .

[46]  D. Aldous Exchangeability and related topics , 1985 .

[47]  Hongyuan Zha,et al.  Learning Hawkes Processes from Short Doubly-Censored Event Sequences , 2017, ICML.

[48]  Peter W. Glynn,et al.  Affine Point Processes: Approximation and Efficient Simulation , 2015, Math. Oper. Res..

[49]  Onno Boxma,et al.  Infinite-server systems with Coxian arrivals , 2019, Queueing Syst. Theory Appl..

[50]  R. Rand,et al.  Strong Approximations for Queues with Customer Choice and Constant Delays , 2017 .

[51]  Michel Mandjes,et al.  Infinite-server queues with Hawkes input , 2017, J. Appl. Probab..

[52]  Mark H. A. Davis Piecewise‐Deterministic Markov Processes: A General Class of Non‐Diffusion Stochastic Models , 1984 .

[53]  Pierre L'Ecuyer,et al.  Rate-Based Daily Arrival Process Models with Application to Call Centers , 2016, Oper. Res..

[54]  Le Song,et al.  Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams , 2015, KDD.

[55]  Swapnil Mishra,et al.  SIR-Hawkes: Linking Epidemic Models and Hawkes Processes to Model Diffusions in Finite Populations , 2017, WWW.

[56]  Feller William,et al.  An Introduction To Probability Theory And Its Applications , 1950 .

[57]  Scott Sanner,et al.  Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity , 2016, WWW.

[58]  P. Brémaud,et al.  STABILITY OF NONLINEAR HAWKES PROCESSES , 1996 .

[59]  Marian-Andrei Rizoiu,et al.  Hawkes processes for events in social media , 2017, Frontiers of Multimedia Research.

[60]  Amy R. Ward,et al.  On Transitory Queueing , 2014, ArXiv.

[61]  Jason Eisner,et al.  The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process , 2016, NIPS.

[62]  Frank Ball,et al.  The threshold behaviour of epidemic models , 1983, Journal of Applied Probability.

[63]  Richard H. Rand,et al.  Queues with Choice via Delay Differential Equations , 2017, Int. J. Bifurc. Chaos.

[64]  Angelos Dassios,et al.  Efficient Simulation of Clustering Jumps with CIR Intensity , 2017, Oper. Res..

[65]  Guodong Pang,et al.  Two-parameter heavy-traffic limits for infinite-server queues , 2008, Queueing Syst. Theory Appl..

[66]  Peter I. Frazier,et al.  Distance dependent Chinese restaurant processes , 2009, ICML.

[67]  G. Willmot,et al.  Mixed Compound Poisson Distributions , 1986, ASTIN Bulletin.

[68]  Pierre L'Ecuyer,et al.  Modeling and forecasting call center arrivals: A literature survey and a case study , 2015 .

[69]  Jamol Pender,et al.  Gaussian skewness approximation for dynamic rate multi-server queues with abandonment , 2013, Queueing Syst. Theory Appl..

[70]  Emmanuel Bacry,et al.  Hawkes model for price and trades high-frequency dynamics , 2013, 1301.1135.

[71]  Anthony Unwin,et al.  Reversibility and Stochastic Networks , 1980 .

[72]  Jianhong Wu,et al.  Introduction to Functional Differential Equations , 2013 .

[73]  Leif Olsson,et al.  MODELING BURSTS IN THE ARRIVAL PROCESS TO AN EMERGENCY CALL CENTER , 2018, 2018 Winter Simulation Conference (WSC).

[74]  E. Bacry,et al.  Some limit theorems for Hawkes processes and application to financial statistics , 2013 .

[75]  Jamol Pender,et al.  Queues Driven by Hawkes Processes , 2017, Stochastic Systems.

[76]  Fabrizio Lillo,et al.  The role of volume in order book dynamics: a multivariate Hawkes process analysis , 2016, 1602.07663.

[77]  A Probabilistic Proof of Blackwell's Renewal Theorem , 1977 .