Computation and Modelling in Insurance and Finance
Computation and Modelling in Insurance and Finance
AUD$199.05
exc GSTFocusing 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.
- 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
Product details
No date availableAdobe eBook Reader
9781107776722
0 pages
0kg
80 b/w illus. 45 tables 550 exercises
This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
- 1. Introduction
- 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
- References
- Index.
