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Reinsurance : Actuarial and Statistical Aspects.
Reinsurance: Actuarial and Statistical Aspects provides a survey of both the academic literature in the field as well as challenges appearing in reinsurance practice and puts the two in perspective. The book is written for researchers with an interest in reinsurance problems, for graduate students w...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken :
John Wiley & Sons, Incorporated,
2008.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Title Page ; Copyright page; Contents; Preface; Chapter 1 Introduction ; 1.1 What is Reinsurance?; 1.2 Why Reinsurance?; 1.3 Reinsurance Data; 1.3.1 Case Study I: Motor Liability Data; 1.3.2 Case Study II: Dutch Fire Insurance Data; 1.3.3 Case Study III: Austrian Storm Claim Data; 1.3.4 Case Study IV: European Flood Risk Data; 1.3.5 Case Study V: Groningen Earthquakes; 1.3.6 Case Study VI: Danish Fire Insurance Data; 1.4 Notes and Bibliography; Chapter 2 Reinsurance Forms and their Properties ; 2.1 Quota-share Reinsurance; 2.1.1 Some Practical Considerations; 2.2 Surplus Reinsurance.
- 2.3 Excess-of-loss Reinsurance2.3.1 Moment Calculations; 2.3.2 Reinstatements; 2.3.3 Further Practical Considerations; 2.4 Stop-loss Reinsurance; 2.5 Large Claim Reinsurance; 2.6 Combinations of Reinsurance Forms and Global Protections; 2.7 Facultative Contracts; 2.8 Notes and Bibliography; Chapter 3 Models for Claim Sizes ; 3.1 Tails of Distributions; 3.2 Large Claims; 3.3 Common Claim Size Distributions; 3.3.1 Light-tailed Models; 3.3.2 Heavy-tailed Models; 3.4 Mean Excess Analysis; 3.5 Full Models: Splicing; 3.6 Multivariate Modelling of Large Claims; Chapter 4 Statistics for Claim Sizes.
- 4.1 Heavy or Light Tails: QQ- and Derivative Plots4.2 Large Claims Modelling through Extreme Value Analysis; 4.2.1 EVA for Pareto-type Tails; 4.2.2 General Tail Modelling using EVA; 4.2.3 EVA under Upper-truncation; 4.3 Global Fits: Splicing, Upper-truncation and Interval Censoring; 4.3.1 Tail-mixed Erlang Splicing; 4.3.2 Tail-mixed Erlang Splicing under Censoring and Upper-truncation; 4.4 Incorporating Covariate Information; 4.4.1 Pareto-type Modelling; 4.4.2 Generalized Pareto Modelling; 4.4.3 Regression Extremes with Censored Data; 4.5 Multivariate Analysis of Claim Distributions.
- 4.5.1 The Multivariate POT Approach4.5.2 Multivariate Mixtures of Erlangs; 4.6 Estimation of Other Tail Characteristics; 4.7 Further Case Studies; 4.8 Notes and Bibliography; Chapter 5 Models for Claim Counts ; 5.1 General Treatment; 5.1.1 Main Properties of the Claim Number Process; 5.2 The Poisson Process and its Extensions; 5.2.1 The Homogeneous Poisson Process; 5.2.2 Inhomogeneous Poisson Processes; 5.2.3 Mixed Poisson Processes; 5.2.4 Doubly Stochastic Poisson Processes; 5.3 Other Claim Number Processes; 5.3.1 The Nearly Mixed Poisson Model; 5.3.2 Infinitely Divisible Processes.
- 5.3.3 The Renewal Model5.3.4 Markov Models; 5.4 Discrete Claim Counts; 5.5 Statistics of Claim Counts; 5.5.1 Modelling Yearly Claim Counts; 5.5.2 Modelling the Claim Arrival Process; 5.6 Claim Numbers under Reinsurance; 5.6.1 Number of Claims under Excess-loss Reinsurance; 5.7 Notes and Bibliography; Chapter 6 Total Claim Amount ; 6.1 General Formulas for Aggregating Independent Risks; 6.2 Classical Approximations for the Total Claim Size; 6.2.1 Approximations based on the First Few Moments; 6.2.2 Asymptotic Approximations for Light-tailed Claims.