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This study considers a new multi-term urn process that has a correlation in the same term and temporal correlation. The objective is to clarify the relationship between the urn model and the Hawkes process. Correlation in the same term is…

Statistical Mechanics · Physics 2022-09-14 Masato Hisakado , Kodai Hattori , Shintaro Mori

The Hawkes self-excited point process provides an efficient representation of the bursty intermittent dynamics of many physical, biological, geological and economic systems. By expressing the probability for the next event per unit time…

Statistical Mechanics · Physics 2020-09-23 Kiyoshi Kanazawa , Didier Sornette

We introduce and show the existence of a Hawkes self-exciting point process with exponentially-decreasing kernel and where parameters are time-varying. The quantity of interest is defined as the integrated parameter…

Statistical Finance · Quantitative Finance 2017-06-28 Simon Clinet , Yoann Potiron

The origin(s) of the ubiquity of probability distribution functions (PDF) with power law tails is still a matter of fascination and investigation in many scientific fields from linguistic, social, economic, computer sciences to essentially…

Statistical Mechanics · Physics 2021-11-01 Kiyoshi Kanazawa , Didier Sornette

The Hawks process is a point process with a self-exciting property. It has been used to model earthquakes, social media events, infections, etc., and is getting a lot of attention. However, as a real problem, there are often situations…

Statistics Theory · Mathematics 2021-07-30 Masatoshi Goda

We prove a central limit type theorem for critical marked Hawkes processes. We study the case where the marks are i.i.d. with nonnegative values and their common distribution is either heavy tailed or has finite variance. The kernel…

Probability · Mathematics 2026-05-05 Anna Talarczyk

Hawkes process is a simple point process 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, neuroscience, social networks,…

Probability · Mathematics 2018-10-02 Xuefeng Gao , Lingjiong Zhu

The Hawkes process is a self-exciting sample point process. It has wide applications in finance, social networks, criminology, seismology, and many other fields. With the development of storage technology, data-driven models are attracting…

Probability · Mathematics 2021-06-23 Haixu Wang

We present a careful analysis of possible issues on the application of the self-excited Hawkes process to high-frequency financial data. We carefully analyze a set of effects leading to significant biases in the estimation of the…

Statistical Finance · Quantitative Finance 2014-07-04 Vladimir Filimonov , Didier Sornette

In this work, several convergence results are established for nearly critical self-excited systems in which event arrivals are described by multivariate marked Hawkes point processes. Under some mild high-frequency assumptions, the rescaled…

Probability · Mathematics 2024-01-31 Wei Xu

In this paper we consider some non linear Hawkes processes with signed reproduction function (or memory kernel) thus exhibiting both self-excitation and inhibition. We provide a Law of Large Numbers, a Central Limit Theorem and large…

Probability · Mathematics 2022-07-06 Patrick Cattiaux , Laetitia Colombani , Manon Costa

We prove regenerative properties for the linear Hawkes process under minimal assumptions on the transfer function, which may have unbounded support. These results are applicable to sliding window statistical estimators. We exploit…

Probability · Mathematics 2019-06-07 Carl Graham

We study large time behavior of critical marked Hawkes processes and related branching particle systems. In case of marked Hawkes processes we assume that the kernel function has multiplicative form and the marks corresponding to the events…

Probability · Mathematics 2026-05-05 Anna Talarczyk

A field theoretical framework is developed for the Hawkes self-excited point process with arbitrary memory kernels by embedding the original non-Markovian one-dimensional dynamics onto a Markovian infinite-dimensional one. The corresponding…

Statistical Mechanics · Physics 2020-09-23 Kiyoshi Kanazawa , Didier Sornette

The asymptotic distribution of the score test of the null hypothesis that marks do not impact the intensity of a Hawkes marked self-exciting point process is shown to be chi-squared. For local asymptotic power, the distribution against…

Statistics Theory · Mathematics 2019-05-01 Simon Clinet , William T. M. Dunsmuir , Gareth W. Peters , Kylie-Anne Richards

Across a wide variety of applications, the self-exciting Hawkes process has been used to model phenomena in which the history of events influences future occurrences. However, there may be many situations in which the past events only…

Probability · Mathematics 2021-01-12 Andrew Daw , Jamol Pender

Hawkes processes are a class of simple point processes that are self-exciting and have clustering effect, with wide applications in finance, social networks and many other fields. This paper considers a self-exciting Hawkes process where…

Trading and Market Microstructure · Quantitative Finance 2018-01-10 Xuefeng Gao , Xiang Zhou , Lingjiong Zhu

The Hawkes process is a simple point process that has long memory, clustering effect, self-exciting property and is in general non-Markovian. The future evolution of a self-exciting point process is influenced by the timing of the past…

Probability · Mathematics 2013-06-25 Lingjiong Zhu

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

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
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