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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. Teaching slides are available for download.Read more
- Contains numerous illustrative examples to enhance understanding and facilitate self-study
- Features over 300 exercises, including some adapted from past exam questions, which allow the reader to apply their understanding
- Provides notes on the use of Excel to facilitate computation
- Teaching slides for instructors are available from the website
Reviews & endorsements
'a very good balance of rigor and readability makes this book an impressive encyclopedia of results and methods for nonlife actuarial modeling.' Zentralblatt MATH
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- Date Published: September 2009
- format: Hardback
- isbn: 9780521764650
- length: 542 pages
- dimensions: 231 x 152 x 30 mm
- weight: 0.98kg
- contains: 1 b/w illus. 55 tables 350 exercises
- availability: Available
Table of Contents
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
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- Actuarial Models
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