Correlated multivariate Poisson processes and extreme measures

Issue title: Statistical Models in Finance and Insurance

Guest editors: Arkady Shemyakin and Vladimir Ladyzhets

Article type: Research Article

Authors: Chiu, Michael^a | Jackson, K.R.^a | Kreinin, Alexander^{b; *}

Affiliations: [a] Department of Computer Science, University of Toronto, Toronto, ON, Canada | [b] Quantitative Research, Risk Analytics, IBM Canada, Toronto, ON, Canada

Correspondence: [*] Corresponding author: Alexander Kreinin, Quantitative Research, Risk Analytics, IBM Canada, Toronto, Canada. E-mail: [email protected].

Abstract: Multivariate Poisson processes have many important applications in Insurance, Finance, and many other areas of Applied Probability. In this paper we study the backward simulation approach to modelling multivariate Poisson processes and analyze the connection to the extreme measures describing the joint distribution of the processes at the terminal simulation time. Multivariate Poisson processes have many important applications in Insurance, Finance, and many other areas of Applied Probability. In this paper we study the backward simulation approach to modelling multivariate Poisson processes and analyze the connection to the extreme measures describing the joint distribution of the processes at the terminal simulation time.

Keywords: Correlated multivariate Poisson process, negative correlation, extreme measures, simulation

DOI: 10.3233/MAS-170405

Journal: Model Assisted Statistics and Applications, vol. 12, no. 4, pp. 369-385, 2017