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Multivariate Hawkes Processes (MHPs) are an important class of temporal point processes that have enabled key advances in understanding and predicting social information systems. However, due to their complex modeling of temporal…

Machine Learning · Computer Science 2020-03-02 Maximilian Nickel , Matthew Le

The Hawkes process is a widely used model in many areas, such as finance, seismology, neuroscience, epidemiology, and social sciences. Estimation of the Hawkes process from continuous observations of a sample path is relatively…

Methodology · Statistics 2024-01-23 Feng Chen , Jeffrey Kwan , Tom Stindl

Hawkes process is a class of simple point processes that is self-exciting and has clustering effect. The intensity of this point process depends on its entire past history. It has wide applications in finance, insurance, neuroscience,…

Probability · Mathematics 2018-03-28 Xuefeng Gao , Lingjiong Zhu

Hawkes Processes capture self-excitation and mutual-excitation between events when the arrival of an event makes future events more likely to happen. Identification of such temporal covariance can reveal the underlying structure to better…

Machine Learning · Computer Science 2020-06-03 Rafael Lima , Jaesik Choi

Multi-dimensional Hawkes process (MHP) is a class of self and mutually exciting point processes that find wide range of applications -- from prediction of earthquakes to modelling of order books in high frequency trading. This paper makes…

Machine Learning · Statistics 2020-06-05 Sobin Joseph , Lekhapriya Dheeraj Kashyap , Shashi Jain

We study the continuous time limit of a self-exciting negative binomial process and discuss the critical properties of its intensity distribution. In this limit, the process transforms into a marked Hawkes process. The probability mass…

Probability · Mathematics 2023-05-24 Kotaro Sakuraba , Wataru Kurebayashi , Masato Hisakado , Shintaro Mori

Hawkes process is a class of simple point processes with self-exciting and clustering properties. Hawkes process has been widely applied in finance, neuroscience, social networks, criminology, seismology, and many other fields. In this…

Probability · Mathematics 2018-11-05 Fuqing Gao , Lingjiong Zhu

Price changes are induced by aggressive market orders in stock market. We introduce a bivariate marked Hawkes process to model aggressive market order arrivals at the microstructural level. The order arrival intensity is marked by an…

Trading and Market Microstructure · Quantitative Finance 2022-08-23 Hai-Chuan Xu , Wei-Xing Zhou

We aim to explicitly model the delayed Granger causal effects based on multivariate Hawkes processes. The idea is inspired by the fact that a causal event usually takes some time to exert an effect. Studying this time lag itself is of…

Machine Learning · Computer Science 2023-08-14 Chao Yang , Hengyuan Miao , Shuang Li

We present a Hawkes model approach to foreign exchange market in which the high frequency price dynamics is affected by a self exciting mechanism and an exogenous component, generated by the pre-announced arrival of macroeconomic news. By…

Trading and Market Microstructure · Quantitative Finance 2015-06-19 Marcello Rambaldi , Paris Pennesi , Fabrizio Lillo

Single-cell lineage tracking strategies enabled by recent experimental technologies have produced significant insights into cell fate decisions, but lack the quantitative framework necessary for rigorous statistical analysis of mechanistic…

As an extension of self-exciting Hawkes process, the multivariate Hawkes process models counting processes of different types of random events with mutual excitement. In this paper, we present a perfect sampling algorithm that can generate…

Applications · Statistics 2020-11-12 Xinyun Chen , Xiuwen Wang

We propose and investigate two model classes for forward power price dynamics, based on continuous branching processes with immigration, and on Hawkes processes with exponential kernel, respectively. The models proposed exhibit jumps…

Statistical Finance · Quantitative Finance 2019-10-30 Giorgia Callegaro , Andrea Mazzoran , Carlo Sgarra

The marked Hawkes risk process is a compound point process for which the occurrence and amplitude of past events impact the future. Thanks to its autoregressive properties, it found applications in various fields such as neuosciences,…

Probability · Mathematics 2024-09-11 Laure Coutin , Mahmoud Khabou

Given a collection of entities (or nodes) in a network and our intermittent observations of activities from each entity, an important problem is to learn the hidden edges depicting directional relationships among these entities. Here, we…

Machine Learning · Statistics 2017-08-01 Triet M Le

We consider a 2-dimensional marked Hawkes process with increasing baseline intensity in order to model prices on electricity intraday markets. This model allows to represent different empirical facts such as increasing market activity,…

Trading and Market Microstructure · Quantitative Finance 2021-03-17 Thomas Deschatre , Pierre Gruet

We model the arrival of mid-price changes in the E-Mini S&P futures contract as a self-exciting Hawkes process. Using several estimation methods, we find that the Hawkes kernel is power-law with a decay exponent close to -1.15 at short…

Statistical Finance · Quantitative Finance 2015-06-12 Stephen J. Hardiman , Nicolas Bercot , Jean-Philippe Bouchaud

This paper extends the existing fractional Hawkes process to better model mainshock-aftershock sequences of earthquakes. The fractional Hawkes process is a self-exciting point process model with temporal decay kernel being a Mittag-Leffler…

Applications · Statistics 2026-04-13 Louis Davis , Boris Baeumer , Ting Wang

We propose a novel probabilistic framework to model continuous-time interaction events data. Our goal is to infer the \emph{implicit} community structure underlying the temporal interactions among entities, and also to exploit how the…

Social and Information Networks · Computer Science 2020-06-24 Sikun Yang , Heinz Koeppl

We determine the large size limit of a network of interacting Hawkes Processes on an adaptive network. The flipping of the node variables is taken to have an intensity given by the mean-field of the afferent edges and nodes. The flipping of…

Probability · Mathematics 2024-11-15 James MacLaurin
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