Exact asymptotic solutions to nonlinear Hawkes processes: a systematic classification of the steady-state solutions
arXiv:2110.01523 · doi:10.1103/PhysRevResearch.5.013067
Abstract
Hawkes point processes are first-order non-Markovian stochastic models of intermittent bursty dynamics with applications to physical, seismic, epidemic, biological, financial, and social systems. While accounting for positive feedback loops that may lead to critical phenomena in complex systems, the standard linear Hawkes process only describes excitative phenomena. To describe the co-existence of excitatory and inhibitory effects (or negative feedbacks), extensions involving nonlinear dependences of the intensity as a function of past activity are needed. However, such nonlinear Hawkes processes have been found hitherto to be analytically intractable due to the interplay between their non-Markovian and nonlinear characteristics, with no analytical solutions available. Here, we present various exact and robust asymptotic solutions to nonlinear Hawkes processes using the field master equation approach. We report explicit power law formulas for the steady state intensity distributions , where the tail exponent is expressed analytically as a function of parameters of the nonlinear Hawkes models. We present three robust interesting characteristics of the nonlinear Hawkes process: (i) for one-sided positive marks (i.e., in the absence of inhibitory effects), the nonlinear Hawkes process can exhibit any power law relation either as intermediate asymptotics () or as true asymptotics () by appropriate model selection; (ii) for distribution of marks with zero mean (i.e., for balanced excitatory and inhibitory effects), the Zipf law () is universally observed for a wide class of nonlinear Hawkes processes with fast-accelerating intensity map; (iii) for marks with a negative mean, the asymptotic power law tail becomes lighter with an exponent increasing above 1 () as the mean mark becomes more negative.
arXiv comment63 pages, 12 figures, 1 table
References in corpus (23)
- Robust dynamic classes revealed by measuring the response function of a social system
- A multifractal random walk
- Multifractal analysis of financial markets
- Sub-critical and Super-critical Regimes in Epidemic Models of Earthquake Aftershocks
- Quantifying reflexivity in financial markets: towards a prediction of flash crashes
- The dynamical foundation of fractal stream chemistry: The origin of extremely long retention times
- Endogenous Versus Exogenous Shocks in Complex Networks: an Empirical Test Using Book Sale Ranking
- Predictability in the ETAS Model of Interacting Triggered Seismicity
- The effect of disorder on the fracture nucleation process
- Multifractal Scaling of Thermally-Activated Rupture Processes
- Magnitude-Dependent Omori Law: Empirical Study and Theory
- Minimal Model of Stochastic Athermal Systems: Origin of Non-Gaussian Noise
- Functional central limit theorems for stationary Hawkes processes and application to infinite-server queues
- Linear stochastic dynamics with nonlinear fractal properties
- Andrade, Omori and Time-to-failure Laws from Thermal Noise in Material Rupture
- Generic Multifractality in Exponentials of Long Memory Processes
- Asymptotic derivation of Langevin-like equation with non-Gaussian noise and its analytical solution
- Systematic Assessment of the Static Stress-Triggering Hypothesis using Inter-earthquake Time Statistics
- Self-Excited Multifractal Dynamics
- Non-universal power law distribution of intensities of the self-excited Hawkes process: a field-theoretical approach
- Field master equation theory of the self-excited Hawkes process
- Ubiquitous power law scaling in nonlinear self-excited Hawkes processes
- Long-range Static Directional Stress Transfer in a Cracked, Nonlinear Elastic Crust
Cited by in corpus (3)
- Revisiting Seismicity Criticality: A New Framework for Bias Correction of Statistical Seismology Model Calibrations
- A standard form of master equations for general non-Markovian jump processes: the Laplace-space embedding framework and asymptotic solution
- Assessing fluctuations of long-memory environmental variables based on the robustified dynamic Orlicz risk