Efficient simulation of clustering jumps with CIR intensity

Dassios, Angelos ORCID: 0000-0002-3968-2366 and Zhao, Hongbiao (2017) Efficient simulation of clustering jumps with CIR intensity. Operations Research, 65 (6). pp. 1494-1515. ISSN 0030-364X

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Abstract

We introduce a broad family of generalised self-exciting point processes with CIR-type intensities, and develop associated algorithms for their exact simulation. The underlying models are extensions of the classical Hawkes process, which already has numerous applications in modelling the arrival of events with clustering or contagion effect in finance, economics and many other fields. Interestingly, we find that the CIR-type intensity together with its point process can be sequentially decomposed into simple random variables, which immediately leads to a very efficient simulation scheme. Our algorithms are also pretty accurate and flexible. They can be easily extended to further incorporate externally-excited jumps, or, to a multidimensional framework. Some typical numerical examples and comparisons with other well known schemes are reported in detail. In addition, a simple application for modelling a portfolio loss process is presented.

Item Type:	Article
Official URL:	http://pubsonline.informs.org/journal/opre
Additional Information:	© 2017 INFORMS
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics
JEL classification:	C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C15 - Statistical Simulation Methods; Monte Carlo Methods; Bootstrap Methods C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Other Model Applications C - Mathematical and Quantitative Methods > C6 - Mathematical Methods and Programming > C63 - Computational Techniques
Date Deposited:	21 Apr 2017 15:58
Last Modified:	03 Oct 2024 19:33
Projects:	71401147
Funders:	National Natural Science Foundation of China
URI:	http://eprints.lse.ac.uk/id/eprint/74205

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