Actuarial statistics with R theory and case studies - Gan, Guojun (New Hartford, CT ACTEX Learning, a division of SRBooks Inc., 2018)
"This book covers several topics on data analysis and statistical learning prescribed by the International Actuarial Association (IAA). In particular, it has been designed to cover the learning objectives for the SOA's statistics for Risk Modeling (SRMI) Exam. Many materials from this book also cover parts of the syllabus for the CAS Modern Actuarial Statistics (MAS-I and MAS-II) Exam. It is broadly intended for students and practitioners to learn R programming and its applications in actuarial science, finance, and quantitative risk management."--Page 4 de la couverture.
I. Supervised learning -- 1. Simple linear regression -- 2. Case study: implementing the CAPM -- 3. Multiple linear regression models -- 4. Case study: predicting intraday movements -- 5. Case study: estimating fair market values -- 6. Generalized linear models -- 7. Case study: predicting demand -- 8. Case study: modeling the number of auto claims -- 9. Case study: modeling the loss severity -- 10. Decision trees -- 11. Case study: decision trees -- II. Unsupervised learning -- 12. Data clustering -- 13. Case study: clustering variable annuity policies -- 14. Principal component analysis -- 15. Case study: PCA on interest rate swaps -- III. Time series models -- 16. Time series models -- 17. Case study: forecasting exchange rates -- IV. Simulation -- 18. Case study: profitability analysis -- 19. Case study: simulating the future lifetime -- Appendix: Introduction to R.
Keywords: Insurance -- Mathematics; Actuarial science -- Textbooks