Nonlife actuarial models : theory, methods and evaluation / Yiu-Kuen Tse.
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EWU Library E-book | Non-fiction | 368.01 TSN 2009 (Browse shelf(Opens below)) | Not for loan | ||||
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368.01 GRR 2012 Risk modelling in general insurance : | 368.01 MOD 2005 Modern actuarial theory and practice / | 368.01 PEF 2015 Fundamentals of actuarial mathematics / | 368.01 TSN 2009 Nonlife actuarial models : | 368.012 KLL 2012 Loss models : | 368.38601 HAA 1999 Actuarial models for disability insurance / | 368 REP 2017 Principles of risk management and insurance / |
Includes bibliographical references and index.
TOC Preface --
Notation and convention --
Part I. Loss Models. 1. Claim-frequency distribution --
2. Claim-severity distribution --
3. Aggregate-loss models --
Part II. Risk and Ruin. 4. Risk measures --
5. Ruin theory --
Part III. Credibility. 6. Classical credibility --
7. Bühlmann credibility --
8. Bayesian approach --
9. Empirical implementation of credibility --
Part IV. Model Construction and Evaluation. 10. Model estimation and types of data --
11. Nonparametric model estimation --
12. Parametric model estimation --
13. Model evaluation and selection --
14. Basic Monte Carlo methods --
15. Applications of Monte Carlo methods --
Appendix. Review of statistics --
Answers to exercises --
References --
Index.
"Actuaries must pass exams, but more than that: they must put knowledge into practice. This coherent book gives complete syllabus coverage for Exam C of the Society of Actuaries (SOA) while emphasizing the concepts and practical application of nonlife actuarial models. Ideal for those approaching their professional exams, it is also a class-tested textbook for undergraduate university courses in actuarial science. All the topics that students need to prepare for Exam C are here, including modeling of losses, risk and ruin theory, credibility theory and applications, and empirical implementation of loss models. The book also covers more recent topics, such as risk measures and bootstrapping. Readers are assumed to have studied statistical inference and probability at the introductory undergraduate level. Numerous examples and exercises are provided, with many exercises adapted from past Exam C questions. Computational notes on the use of Excel are included"--Book cover.
AS
Sagar Shahanawaz
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