From the multiterm urn model to the self-exciting negative binomial distribution and Hawkes processes

التفاصيل البيبلوغرافية
العنوان: From the multiterm urn model to the self-exciting negative binomial distribution and Hawkes processes
المؤلفون: Masato Hisakado, Kodai Hattori, Shintaro Mori
المصدر: Physical Review E. 106
بيانات النشر: American Physical Society (APS), 2022.
سنة النشر: 2022
مصطلحات موضوعية: Methodology (stat.ME), FOS: Computer and information sciences, Statistical Mechanics (cond-mat.stat-mech), FOS: Physical sciences, Condensed Matter - Statistical Mechanics, Statistics - Methodology
الوصف: 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 represented by the P\'{o}lya urn model and the temporal correlation is incorporated by introducing the conditional initial condition. In the double-scaling limit of this urn process, the self-exciting negative binomial distribution (SE-NBD) process, which is a marked Hawkes process, is obtained. In the standard continuous limit, this process becomes the Hawkes process, which has no correlation in the same term. The difference is the variance of the intensity function in that the phase transition from the steady to the non-steady state can be observed. The critical point, at which the power law distribution is obtained, is the same for the Hawkes and the urn processes. These two processes are used to analyze empirical data of financial default to estimate the parameters of the model. For the default portfolio, the results produced by the urn process are superior to those obtained with the Hawkes process and confirm self-excitation.
Comment: 22 pages, 3 figures, 3 tables
تدمد: 2470-0053
2470-0045
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::436c5fe8bb71e7e7b2757600320e385a
https://doi.org/10.1103/physreve.106.034106
حقوق: OPEN
رقم الأكسشن: edsair.doi.dedup.....436c5fe8bb71e7e7b2757600320e385a
قاعدة البيانات: OpenAIRE