Numerical computation of risk functionals in PDMP risk models

Lea Maria Enzi; Stefan Thonhauser

doi:10.1007/978-3-031-59762-6_10

Numerical computation of risk functionals in PDMP risk models

Lea Maria Enzi
, Stefan Thonhauser

Institut für Statistik (5060)

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Abstract

We analyze the ruin event in a Markovian insurance risk model. For actual computations of risk functionals, we sketch different numerical approaches and focus on assessing the performance of a quantization algorithm. Since by nature ruin should be a rare event, it is necessary to deploy a variance reduction technique based on a proper change of measure.

Originalsprache	englisch
Titel	Monte Carlo and Quasi-Monte Carlo Methods - MCQMC 2022
Untertitel	MCQMC 2022, Linz, Austria
Redakteure/-innen	Aicke Hinrichs, Friedrich Pillichshammer, Peter Kritzer
Erscheinungsort	Cham
Herausgeber (Verlag)	Springer Nature Switzerland AG
Seiten	223-240
Seitenumfang	18
ISBN (Print)	978-3-031-59761-9
DOIs	https://doi.org/10.1007/978-3-031-59762-6_10
Publikationsstatus	Veröffentlicht - 2024

Publikationsreihe

Name	Springer Proceedings in Mathematics and Statistics
Band	460

ASJC Scopus subject areas

Angewandte Mathematik
Allgemeine Mathematik

Fields of Expertise

Information, Communication & Computing

Treatment code (Nähere Zuordnung)

Basic - Fundamental (Grundlagenforschung)

Zugriff auf Dokument

10.1007/978-3-031-59762-6_10

Andere Dateien und Links

Verknüpfung zur Publikation in Scopus

FWF - Risk Modelling - Analysis, Simulation und Optimierung
Thonhauser, S. M. (Projektleiter an der OE) & Pojer, S. (Teilnehmer / Mitarbeiter)
1/07/20 → 30/06/25
Projekt: Forschungsprojekt

Dieses zitieren

Enzi, L. M., & Thonhauser, S. (2024). Numerical computation of risk functionals in PDMP risk models. in A. Hinrichs, F. Pillichshammer, & P. Kritzer (Hrsg.), Monte Carlo and Quasi-Monte Carlo Methods - MCQMC 2022: MCQMC 2022, Linz, Austria (S. 223-240). (Springer Proceedings in Mathematics and Statistics; Band 460). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-031-59762-6_10

Numerical computation of risk functionals in PDMP risk models. / Enzi, Lea Maria; Thonhauser, Stefan.
Monte Carlo and Quasi-Monte Carlo Methods - MCQMC 2022: MCQMC 2022, Linz, Austria. Hrsg. / Aicke Hinrichs; Friedrich Pillichshammer; Peter Kritzer. Cham: Springer Nature Switzerland AG, 2024. S. 223-240 (Springer Proceedings in Mathematics and Statistics; Band 460).

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Enzi, LM & Thonhauser, S 2024, Numerical computation of risk functionals in PDMP risk models. in A Hinrichs, F Pillichshammer & P Kritzer (Hrsg.), Monte Carlo and Quasi-Monte Carlo Methods - MCQMC 2022: MCQMC 2022, Linz, Austria. Springer Proceedings in Mathematics and Statistics, Bd. 460, Springer Nature Switzerland AG, Cham, S. 223-240. https://doi.org/10.1007/978-3-031-59762-6_10

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Numerical computation of risk functionals in PDMP risk models

Abstract

Publikationsreihe

ASJC Scopus subject areas

Fields of Expertise

Treatment code (Nähere Zuordnung)

Zugriff auf Dokument

Andere Dateien und Links

Projekte

FWF - Risk Modelling - Analysis, Simulation und Optimierung

Dieses zitieren