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Ruin Probability: The Classical Model extended to heavy tailed distribution functions and to a simulation approach with bivariate dependent claims using Copulas - Softcover
Ruin probability is a central component of actuarial science. The first part of this thesis describes the classical model including some premium principles and derives some main results, such as the Upper Lundberg bound and the Cramér-Lundberg approximation formula. One assumption for these results is the existence of the adjustment coefficient. Heavy tailed distribution functions are treated in the second part, where it is shown that this coefficient does not exist. Then some results from the classical model are extended to a class of heavy tailed distribution functions, i.e. subexponential functions. A central limit theorem for stable distribution functions is shown. Regularly and slowly varying functions as well as mean excess functions are explained. The third part describes some dependency structures, with a focus on copula functions, and explains the simulation procedure. First, the classical model is simulated using three different distribution functions: a light tailed, a medium tailed and a heavy tailed function. Following this, bivariate dependent claims are assumed, which are modeled with different copula functions: with and without tail dependency.
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About the Author:
Stefan Simons was born in Heidelberg in 1978. After a banking apprenticeship, he studied Mathematical Finance at the University of Constance. During his studies, he gained practical experience in the reinsurance industry. Following this, he started his professional career as an insurance mathematician with Munich RE.
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- PublisherVDM Verlag Dr. Müller
- Publication date2011
- ISBN 10 3639319869
- ISBN 13 9783639319866
- BindingPaperback
- Number of pages128
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Ruin Probability: The Classical Model extended to heavy tailed distribution functions and to a simulation approach with bivariate dependent claims using Copulas
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Ruin Probability The Classical Model extended to heavy tailed distribution functions and to a simulation approach with bivariate dependent claims using Copulas
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Book Description Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Ruin probability is a central component of actuarial science. The first part of this thesis describes the classical model including some premium principles and derives some main results, such as the Upper Lundberg bound and the Cramér-Lundberg approximation formula. One assumption for these results is the existence of the adjustment coefficient. Heavy tailed distribution functions are treated in the second part, where it is shown that this coefficient does not exist. Then some results from the classical model are extended to a class of heavy tailed distribution functions, i.e. subexponential functions. A central limit theorem for stable distribution functions is shown. Regularly and slowly varying functions as well as mean excess functions are explained. The third part describes some dependency structures, with a focus on copula functions, and explains the simulation procedure. First, the classical model is simulated using three different distribution functions: a light tailed, a medium tailed and a heavy tailed function. Following this, bivariate dependent claims are assumed, which are modeled with different copula functions: with and without tail dependency. 128 pp. Englisch. Seller Inventory # 9783639319866
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Ruin Probability : The Classical Model extended to heavy tailed distribution functions and to a simulation approach with bivariate dependent claims using Copulas
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Book Description Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Ruin probability is a central component of actuarial science. The first part of this thesis describes the classical model including some premium principles and derives some main results, such as the Upper Lundberg bound and the Cramér-Lundberg approximation formula. One assumption for these results is the existence of the adjustment coefficient. Heavy tailed distribution functions are treated in the second part, where it is shown that this coefficient does not exist. Then some results from the classical model are extended to a class of heavy tailed distribution functions, i.e. subexponential functions. A central limit theorem for stable distribution functions is shown. Regularly and slowly varying functions as well as mean excess functions are explained. The third part describes some dependency structures, with a focus on copula functions, and explains the simulation procedure. First, the classical model is simulated using three different distribution functions: a light tailed, a medium tailed and a heavy tailed function. Following this, bivariate dependent claims are assumed, which are modeled with different copula functions: with and without tail dependency. Seller Inventory # 9783639319866
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Book Description Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Simons StefanStefan Simons was born in Heidelberg in 1978. After a banking apprenticeship, he studied Mathematical Finance at the University of Constance. During his studies, he gained practical experience in the reinsurance industry. Seller Inventory # 4977272
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