Nonlife Actuarial Models: Theory, Methods and Evaluation / Edition 1

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Overview

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.
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Editorial Reviews

From the Publisher
'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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Product Details

  • ISBN-13: 9780521764650
  • Publisher: Cambridge University Press
  • Publication date: 10/31/2009
  • Series: International Series on Actuarial Science
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 540
  • Sales rank: 911,392
  • Product dimensions: 6.10 (w) x 9.00 (h) x 1.20 (d)

Meet the Author

Yiu-Kuen Tse is currently a Professor with the School of Economics at Singapore Management University. He has been a Fellow of the Society of Actuaries (FSA) since 1993.
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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.
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