Description
Book SynopsisDiscover how to optimize business strategies from both qualitative and quantitative points of view Operational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk.
Trade Review"…offers the tool needed to design, develop, and implement industry-level operational risk models…would serve as an excellent text…" (
Journal of the American Statistical Association, December 2007)
"...interesting and timely. It creatively and skillfully elucidates key issues in the analysis of operational risks." (Mathematical Reviews, 2007f)
Table of ContentsPreface.
Acknowledgments.
PART I: INTRODUCTIN TO OPERATIONAL RISK MODELING.
1. Operational Risk.
2. Basic Probability concepts.
3. Measures of Risk.
PART II: PROBABILISTIC TOOLS FOR OPERATIONAL RISK MODELING.
4. Models for the size of losses: Continuous distributions.
5. Models for the number of losses: Counting distributions.
6. Aggregate loss models.
7. Extreme value theory: The study of jumbo losses.
8. Multivariate models.
PART III: STATISTICAL METHODS FOR CALIBRATING MODELS OF OPERATIONAL RISK.
9. Review of mathematical statistics.
10. Parameter Estimation.
11. Estimation for discrete distributions.
12. Model selection.
13. Fitting extreme value models.
14. Fitting copula models.
Appendix A: Gamma and related functions.
Appendix B: Discretization of the severity distribution.
Appendix C: Nelder-Mead simplex Method.
References.
Index.
