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Focusing on what actuaries need in practice, this introductory account provides readers with essential tools for handling complex problems and explains how simulation models can be created, used and re-used (with modifications) in related situations. The book begins by outlining the basic tools of modelling and simulation, including a discussion of the Monte Carlo method and its use. Part II deals with general insurance and Part III with life insurance and financial risk. Algorithms that can be implemented on any programming platform are spread throughout and a program library written in R is included. Numerous figures and experiments with R-code illustrate the text. The author's non-technical approach is ideal for graduate students, the only prerequisites being introductory courses in calculus and linear algebra, probability and statistics. The book will also be of value to actuaries and other analysts in the industry looking to update their skills.Read more
- Covers the main stochastic models in insurance and finance
- Explains Monte Carlo techniques and how simulation models are built
- Includes a program library in R
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- Date Published: May 2014
- format: Hardback
- isbn: 9780521830485
- length: 712 pages
- dimensions: 251 x 178 x 34 mm
- weight: 1.53kg
- contains: 80 b/w illus. 45 tables 550 exercises
- availability: Available
Table of Contents
Part I. Tools for Risk Analysis:
2. Getting started the Monte Carlo way
3. Evaluating risk: a primer
4. Monte Carlo II: improving technique
5. Modelling I: linear dependence
6. Modelling II: conditional and non-linear
7. Historical estimation and error
Part II. General Insurance:
8. Modelling claim frequency
9. Modelling claim size
10. Solvency and pricing
11. Liabilities over long terms
Part III. Life Insurance and Financial Risk:
12. Life and state-dependent insurance
13. Stochastic asset models
14. Financial derivatives
15. Integrating risk of different origin
Appendix A. Random variables: principal tools
Appendix B. Linear algebra and stochastic vectors
Appendix C. Numerical algorithms: a third tool
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