En poursuivant votre navigation sur ce site, vous acceptez l'utilisation d'un simple cookie d'identification. Aucune autre exploitation n'est faite de ce cookie. OK
1

PDMPs and Integrals PDMPs in risk theory and QMC integration II

Sélection Signaler une erreur
Virtualconference
Auteurs : Thonhauser, Stefan (Auteur de la conférence)
CIRM (Editeur )

Loading the player...

Résumé : This talk will give an overview on the usage of piecewise deterministic Markov processes for risk theoretic modeling and the application of QMC integration in this framework. This class of processes includes several common risk models and their generalizations. In this field, many objects of interest such as ruin probabilities, penalty functions or expected dividend payments are typically studied by means of associated integro-differential equations. Unfortunately, only particular parameter constellations allow for closed form solutions such that in general one needs to rely on numerical methods. Instead of studying these associated integro-differential equations, we adapt the problem in a way that allows us to apply deterministic numerical integration algorithms such as QMC rules.

Mots-Clés : risk theory; Markov process; quasi Monte-Carlo integration

Codes MSC :
60J25 - Continuous-time Markov processes on general state spaces
65R20 - Integral equations
91B30 - Risk theory, insurance
91G60 - Numerical methods in mathematical finance

Ressources complémentaires :
https://www.cirm-math.com/uploads/2/6/6/0/26605521/thonhauser_cirm_i.pdf

    Informations sur la Vidéo

    Réalisateur : Hennenfent, Guillaume
    Langue : Anglais
    Date de Publication : 02/11/2020
    Date de Captation : 02/11/2020
    Sous Collection : Research School
    Catégorie arXiv : Probability
    Domaine(s) : Probabilités & Statistiques
    Format : MP4 (.mp4) - HD
    Durée : 00:59:27
    Audience : Chercheurs
    Download : https://videos.cirm-math.fr/2020-10-28_Thonhauser_2.mp4

Informations sur la Rencontre

Nom de la Rencontre : Jean-Morlet Chair 2020 - Research School: Quasi-Monte Carlo Methods and Applications / Chaire Jean-Morlet 2020 - Ecole: Méthode de quasi-Monte-Carlo et applications
Organisateurs de la Rencontre : Rivat, Joël ; Thonhauser, Stefan ; Tichy, Robert
Dates : 02/11/2020 - 07/11/2020
Année de la rencontre : 2020
URL de la Rencontre : https://www.chairejeanmorlet.com/2255.html

Données de citation

DOI : 10.24350/CIRM.V.19680003
Citer cette vidéo: Thonhauser, Stefan (2020). PDMPs and Integrals PDMPs in risk theory and QMC integration II. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.19680003
URI : http://dx.doi.org/10.24350/CIRM.V.19680003

Voir Aussi

Bibliographie

  • KRITZER, Peter, LEOBACHER, Gunther, SZÖLGYENYI, Michaela, et al. Approximation methods for piecewise deterministic Markov processes and their costs. Scandinavian actuarial journal, 2019, vol. 2019, no 4, p. 308-335. - https://doi.org/10.1080/03461238.2018.1560357

  • PREISCHL, Michael, THONHAUSER, Stefan, et TICHY, Robert F. Integral equations, quasi-monte carlo methods and risk modeling. In : Contemporary Computational Mathematics-A Celebration of the 80th Birthday of Ian Sloan. Springer, Cham, 2018. p. 1051-1074. - http://dx.doi.org/10.1007/978-3-319-72456-0_47

  • PAUSINGER, Florian et SVANE, Anne Marie. A Koksma–Hlawka inequality for general discrepancy systems. Journal of Complexity, 2015, vol. 31, no 6, p. 773-797. - https://doi.org/10.1016/j.jco.2015.06.002



Sélection Signaler une erreur