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Related papers: Multivariate Quadratic Hawkes Processes -- Part I:…

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Hawkes processes are point process models that have been used to capture self-excitatory behavior in social interactions, neural activity, earthquakes and viral epidemics. They can model the occurrence of the times and locations of events.…

Machine Learning · Statistics 2022-10-24 Xenia Miscouridou , Samir Bhatt , George Mohler , Seth Flaxman , Swapnil Mishra

This paper proposes a simple and parsimonious discrete-time simulation model to describe the endogenous formation and periodic collapse of financial bubbles. While existing literature has extensively explored the statistical properties of…

Trading and Market Microstructure · Quantitative Finance 2026-05-05 Naohiro Yoshida

The Hawkes model is a past-dependent point process, widely used in various fields for modeling temporal clustering of events. Extending this framework, the multidimensional marked Hawkes process incorporates multiple interacting event types…

Methodology · Statistics 2025-05-20 Anna Bonnet , Charlotte Dion-Blanc , Maya Sadeler-Perrin

Wavelets provide the flexibility to analyse stochastic processes at different scales. Here, we apply them to multivariate point processes as a means of detecting and analysing unknown non-stationarity, both within and across data streams.…

Methodology · Statistics 2020-11-04 Edward A. K. Cohen , Alexander J. Gibberd

Multiplicative random cascade model naturally reproduces the intermittency or multifractality, which is frequently shown among hierarchical complex systems such as turbulence and financial markets. As described herein, we investigate the…

Statistical Finance · Quantitative Finance 2018-09-05 Jun-ichi Maskawa , Koji Kuroda , Joshin Murai

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…

Statistical Finance · Quantitative Finance 2014-12-17 Stephen J. Hardiman , Jean-Philippe Bouchaud

Hawkes process provides an effective statistical framework for analyzing the time-dependent interaction of neuronal spiking activities. Although utilized in many real applications, the classic Hawkes process is incapable of modelling…

Machine Learning · Statistics 2021-02-23 Feng Zhou , Yixuan Zhang , Jun Zhu

Over the last decade, nonparametric methods have gained increasing attention for modeling complex data structures due to their flexibility and minimal structural assumptions. In this paper, we study a general multivariate nonparametric…

Methodology · Statistics 2026-03-18 Kunal Rai , Archi Roy , Itai Dattner , Soudeep Deb

Multilayer network is a potent platform which paves a way to study the interactions among entities in various networks with multiple types of relationships. In this study, the dynamics of discrete-time quantum walk on a multilayer network…

Quantum Physics · Physics 2023-10-05 M. N. Jayakody , Priodyuti Pradhan , Dana Ben Porath , E. Cohen

We define a new model using a Hawkes process as a subordinator in a standard Brownian motion. We demonstrate that this Hawkes subordinated Brownian motion or more succinctly, variance-Hawkes process can be fit to 2018 and 2019 natural gas…

Mathematical Finance · Quantitative Finance 2024-10-14 Joshua McGillivray , Anatoliy Swishchuk

A self-exciting point process with a continuous-time autoregressive moving average intensity process, named CARMA(p,q)-Hawkes model, has recently been introduced. The model generalizes the Hawkes process by substituting the…

Mathematical Finance · Quantitative Finance 2024-12-20 Lorenzo Mercuri , Andrea Perchiazzo , Edit Rroji

We present a stability study of the class of multivariate self-excited Hawkes point processes, that can model natural and social systems, including earthquakes, epileptic seizures and the dynamics of neuron assemblies, bursts of exchanges…

Statistical Mechanics · Physics 2015-05-27 A. Saichev , D. Sornette

We investigate the asymptotic behavior as time goes to infinity of Hawkes processes whose regression kernel has $L^1$ norm close to one and power law tail of the form $x^{-(1+\alpha)}$, with $\alpha\in(0,1)$. We in particular prove that…

Probability · Mathematics 2015-04-14 Thibault Jaisson , Mathieu Rosenbaum

Quantum theory is used to model secondary financial markets. Contrary to stochastic descriptions, the formalism emphasizes the importance of trading in determining the value of a security. All possible realizations of investors holding…

Physics and Society · Physics 2009-11-07 Martin Schaden

Learning the latent network structure from large scale multivariate point process data is an important task in a wide range of scientific and business applications. For instance, we might wish to estimate the neuronal functional…

Methodology · Statistics 2021-01-21 Biao Cai , Jingfei Zhang , Yongtao Guan

Online learning of Hawkes processes has received increasing attention in the last couple of years especially for modeling a network of actors. However, these works typically either model the rich interaction between the events or the latent…

Many events occur in the world. Some event types are stochastically excited or inhibited---in the sense of having their probabilities elevated or decreased---by patterns in the sequence of previous events. Discovering such patterns can help…

Machine Learning · Computer Science 2017-11-22 Hongyuan Mei , Jason Eisner

Quantum random walks (QRWs) are random processes in which the resulting probability density of the "walker" state, whose movement is governed by a "coin" state, is described in a non-classical manner. Previously, Q-plates have been used to…

We develop a quasi-likelihood analysis procedure for a general class of multivariate marked point processes. As a by-product of the general method, we establish under stability and ergodicity conditions the local asymptotic normality of the…

Statistics Theory · Mathematics 2021-08-06 Simon Clinet

The Tick library allows researchers in market microstructure to simulate and learn Hawkes process in high-frequency data, with optimized parametric and non-parametric learners. But one challenge is to take into account the correct causality…

Machine Learning · Statistics 2021-01-19 Marcos Costa Santos Carreira