Statistical and Probabilistic Methods in Actuarial Science

Philip J. Boland

March 5, 2007 by Chapman and Hall/CRC
Textbook - 368 Pages - 25 B/W Illustrations
ISBN 9781584886952 - CAT# C6951
Series: Chapman & Hall/CRC Interdisciplinary Statistics

USD$109.95

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Features

  • Features practical applications to general insurance, including loss distributions and collective risk models, reserving and experience rating, credibility estimation, and security measures of risk
  • Presents useful introductions to generalized linear models, credibility theory, and game theory
  • Includes material on computing, such as simulation techniques
  • Contains numerous worked numerical examples and problems with selected answers in an appendix
  • Provides appendices on Bayesian statistics and basic tools in probability and statistics
  • Offers a solutions manual for qualifying instructors
  • Summary

    Statistical and Probabilistic Methods in Actuarial Science covers many of the diverse methods in applied probability and statistics for students aspiring to careers in insurance, actuarial science, and finance. The book builds on students’ existing knowledge of probability and statistics by establishing a solid and thorough understanding of these methods. It also emphasizes the wide variety of practical situations in insurance and actuarial science where these techniques may be used.

     

    Although some chapters are linked, several can be studied independently from the others. The first chapter introduces claims reserving via the deterministic chain ladder technique. The next few chapters survey loss distributions, risk models in a fixed period of time, and surplus processes, followed by an examination of credibility theory in which collateral and sample information are brought together to provide reasonable methods of estimation. In the subsequent chapter, experience rating via no claim discount schemes for motor insurance provides an interesting application of Markov chain methods. The final chapters discuss generalized linear models and decision and game theory.

    Developed by an author with many years of teaching experience, this text presents an accessible, sound foundation in both the theory and applications of actuarial science. It encourages students to use the statistical software package R to check examples and solve problems.

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