Nonlife Actuarial Models
Nonlife Actuarial Models
£74.99
GBPActuaries 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.
- 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
Product details
September 2009Hardback
9780521764650
542 pages
235 × 157 × 30 mm
0.98kg
1 b/w illus. 55 tables 350 exercises
Temporarily unavailable - available from TBC
Table of Contents
- 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.
