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
Not yet reviewed
Be the first to review
Review was not posted due to profanity×
- Date Published: April 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
Find resources associated with this titleYour search for '' returned .
Type Name Unlocked * Format Size
This title is supported by one or more locked resources. Access to locked resources is granted exclusively by Cambridge University Press to lecturers whose faculty status has been verified. To gain access to locked resources, lecturers should sign in to or register for a Cambridge user account.
Please use locked resources responsibly and exercise your professional discretion when choosing how you share these materials with your students. Other lecturers may wish to use locked resources for assessment purposes and their usefulness is undermined when the source files (for example, solution manuals or test banks) are shared online or via social networks.
Supplementary resources are subject to copyright. Lecturers are permitted to view, print or download these resources for use in their teaching, but may not change them or use them for commercial gain.
If you are having problems accessing these resources please contact firstname.lastname@example.org.
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email email@example.comRegister Sign in
You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.Continue ×
Are you sure you want to delete your account?
This cannot be undone.
Thank you for your feedback which will help us improve our service.
If you requested a response, we will make sure to get back to you shortly.×