Regression Modeling with Actuarial and Financial Applications
Statistical techniques can be used to address new situations. This is important in a rapidly evolving risk management and financial world. Analysts with a strong statistical background understand that a large data set can represent a treasure trove of information to be mined and can yield a strong competitive advantage. This book provides budding actuaries and financial analysts with a foundation in multiple regression and time series. Readers will learn about these statistical techniques...
Search in google:
Teaches multiple regression and time series and how to use these to analyze real data in risk management and finance.
1. Regression and the normal distribution; Part I. Linear Regression: 2. Basic linear regression; 3. Multiple linear regression - I; 4. Multiple linear regression - II; 5. Variable selection; 6. Interpreting regression results; Part II. Topics in Time Series: 7. Modeling trends; 8. Autocorrelations and autoregressive models; 9. Forecasting and time series models; 10. Longitudinal and panel data models; Part III. Topics in Nonlinear Regression: 11. Categorical dependent variables; 12. Count dependent variables; 13. Generalized linear models; 14. Survival models; 15. Miscellaneous regression topics; Part IV. Actuarial Applications: 16. Frequency-severity models; 17. Fat-tailed regression models; 18. Credibility and bonus-malus; 19. Claims triangles; 20. Report writing: communicating data analysis results; 21. Designing effective graphs; Appendix 1: basic statistical inference; Appendix 2: matrix algebra; Appendix 3: probability tables.
