Loss Models: From Data to Decisions, 2/e

Description:

Revised, updated, and even more useful to students, teachers, and practicing professionals
The First Edition of Loss Models was deemed "worthy of classical status" by the Journal of the International Statistical Institute. While retaining its predecessor's thorough treatment of the concepts and methods of analyzing contingent events, this powerful Second Edition is updated and expanded to offer even more complete and flexible coverage of risk theory, loss distributions, and survival models.
Beginning with a framework for model building and a description of frequency and severity loss data typically available, it shows readers how to combine frequency, severity, and loss models to build aggregate loss models and credibility-based pricing models, and how to analyze loss over multiple time periods. Important features of this new edition include:
* Thorough preparation for relevant parts of preliminary examinations of the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS)
* Exercises based on past SOA and CAS exams
* Examples using actual insurance data
* Practical treatment of modern credibility theory
* Data files and more from an ftp site
Loss Models, Second Edition is an important resource, providing a comprehensive, practically motivated toolkit and an excellent reference, for actuaries preparing for SOA and CAS preliminary examinations, students in actuarial science who need to understand loss and risk models, and practicing professionals involved in loss modeling.

 

Table of Contents:

Preface.

Acknowledgments.

PART I: INTRODUCTION.

1. Modeling.

PART II: ACTUARIAL MODELS.

2. Random Variables.

3. Basic Distributional Quantities.

4. Classifying and Creating Distributions.

5. Frequency and Severity with Coverage Modifications.

6. Aggregate Loss Models.

7. Discrete Time Ruin Models.

8. Continuous Time Ruin Models.

PART III: CONSTRUCTION OF EMPIRICAL MODELS.

9. Review of Mathematical Statistics.

10. Estimation for Complete Data.

11. Estimation for Modified Data.

PART IV: PARAMETRIC STATISTICAL METHODS.

12. Parameter Estimation.

13. Model Selection.

14. Five Examples.

PART V: ADJUSTED ESTIMATES AND SIMULATION.

15. Interpolation and Smoothing.

16. Credibility.

17. Simulation.

Appendix A: An Inventory of Continuous Distributions.

Appendix B: An Inventory of Discrete Distributions.

Appendix C: Frequency and Severity Relationships.

Appendix D: The Recursive Formula.

Appendix E: Discretization of the Serverity Distribution.

Appendix F: Numerical Optimization and Solution of Systems.

References.

Index.