An Algorithm for the Computation of Joint Hawkes Moments with Exponential Kernel-Reference-Cited by-同舟云学术

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An Algorithm for the Computation of Joint Hawkes Moments with Exponential Kernel

Published:2022-03-31 Issue:0 Volume:2022 Page:72-79
ISSN:2188-4730
Container-title:Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
language:en
Short-container-title:Stochastic Systems Theory and its Applications (SSS)

Author:

Privault Nicolas¹

Affiliation:

1. School of Physical and Mathematical Sciences, Nanyang Technological University

Publisher

The Institute of Systems, Control and Information Engineers

Subject

General Medicine

Link

https://www.jstage.jst.go.jp/article/sss/2022/0/2022_72/_pdf

Reference29 articles.

1. [ABG⁺17] M. Achab, E. Bacry, S. Gaïffas, I. Mastro matteo, and J.-F. Muzy. Uncovering causality from multivariate Hawkes integrated cumulants. Journal of Machine Learning Research, 18(1):6998-7025, 2017.

2. [ABMR18] M. Achab, E. Bacry, J. F. Muzy, and M. Rambaldi. Analysis of order book ows using a nonparametric estimation of the branching ratio matrix. Quant. Finance, 18(2):199-212, 2018.

3. [BDM12] E. Bacry, K. Dayri, and J.F. Muzy. Nonparametric kernel estimation for symmetric Hawkes processes. Application to high frequency nancial data. Eur. Phys. J. B, 85:157-168, 2012.

4. [BSS18] G. Bernis, K. Salhi, and S. Scotti. Sensitivity analysis for marked Hawkes processes: application to CLO pricing. Math. Financ. Econ., 12(4):541-559, 2018.

5. [CF06] P.C. Consul and F. Famoye. Lagrangian probability distributions. Birkhäuser Boston, Inc., Boston, MA, 2006.

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