Thematic month on statistics - Week 4: Extremes, copulas and actuarial science / Mois thématique sur les statistiques - Semaine 4 : Extrêmes, copules et actuariat

Collection Thematic month on statistics - Week 4: Extremes, copulas and actuarial science / Mois thématique sur les statistiques - Semaine 4 : Extrêmes, copules et actuariat

Organizer(s) Boutahar, Mohamed ; Pommeret, Denys ; Royer-Carenzi, Manuela

Date(s) 22/02/2016 - 26/02/2016

linked URL http://conferences.cirm-math.fr/1618.html

00:00:00 / 00:00:00

1 5

Fractional Poisson process: long-range dependence and applications in ruin theory

By Romain Biard

We study a renewal risk model in which the surplus process of the insurance company is modeled by a compound fractional Poisson process. We establish the long-range dependence property of this non-stationary process. Some results for the ruin probabilities are presented in various assumptions on the distribution of the claim sizes.

Information about the video

Date of recording 23/02/2016
Date of publication 08/03/2016
Institution CIRM
Licence CC BY NC ND
Language English
Audience Researchers
Director(s) Guillaume Hennenfent
Format MP4

Citation data

DOI 10.24350/CIRM.V.18933903
Cite this video Biard, Romain (23/02/2016). Fractional Poisson process: long-range dependence and applications in ruin theory. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.18933903
URL https://dx.doi.org/10.24350/CIRM.V.18933903

Domain(s)

Probability

Bibliography

Biard, R., & Saussereau, B. (2014). Fractional Poisson process: long-range dependence and applications in ruin theory. Journal of Applied Probability, 51(3), 727-740 - http://dx.doi.org/10.1239/jap/1409932670

MSC codes

Last related questions on MathOverflow

You have to connect your Carmin.tv account with mathoverflow to add question

Ask a question on MathOverflow

All the collection videos

24:37

published on March 8, 2016

Fractional Poisson process: long-range dependence and applications in ruin theory

By Romain Biard

26:55

published on March 8, 2016

A measure of dependence for stable distributions

By John P. Nolan

33:01

published on March 10, 2016

Copulas based inference for discrete or mixed data

By Bruno Rémillard

29:53

published on March 8, 2016

Discrete Schur-constant models in inssurance

By Claude Lefèvre

29:38

published on March 8, 2016

On tail dependence coefficients of transformed multivariate Archimedean copulas

By Elena Di Bernardino

Copyright Carmin.tv 2024

Give feedback