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

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Authors : Biard, Romain (Author of the conference)
CIRM (Publisher )

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Abstract : 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.

Keywords : fractional Poisson process; renewal process; long-range dependence; ruin probability

MSC Codes :
60G55 - Point processes
60K05 - Renewal theory
91B30 - Risk theory, insurance
33E12 - Mittag-Leffler functions and generalizations
60G22 - Fractional processes, including fractional Brownian motion

    Information on the Video

    Film maker : Hennenfent, Guillaume
    Language : English
    Available date : 08/03/16
    Conference Date : 23/02/16
    Subseries : Research talks
    arXiv category : Probability
    Mathematical Area(s) : Probability & Statistics
    Format : MP4 (.mp4) - HD
    Video Time : 00:24:38
    Targeted Audience : Researchers
    Download : https://videos.cirm-math.fr/2016-02-23_Biard.mp4

Information on the Event

Event Title : Thematic month on statistics - Week 4: Extremes, copulas and actuarial science / Mois thématique sur les statistiques - Semaine 4 : Extrêmes, copules et actuariat
Event Organizers : Boutahar, Mohamed ; Pommeret, Denys ; Royer-Carenzi, Manuela
Dates : 22/02/16 - 26/02/16
Event Year : 2016
Event URL : http://conferences.cirm-math.fr/1618.html

Citation Data

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

See Also

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



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