Quantitative operational risk models / Catalina BolanceĢ [and others].
Using real-life examples from the banking and insurance industries, Quantitative Operational Risk Models details how internal data can be improved based on external information of various kinds. Using a simple and intuitive methodology based on classical transformation methods, the book includes rea...
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Full Text (via O'Reilly/Safari) |
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| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton :
Taylor & Francis,
2012.
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| Series: | Chapman & Hall/CRC finance series.
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| Subjects: |
Table of Contents:
- Understanding Operational Risk; Introduction; Our Approach to Operational Risk Quantification; Regulatory Framework; The Fundamentals of Calculating Operational Risk Capital; Notation and Definitions; The Calculation of Operational Risk Capital in Practice; Organization of the Book; ; Operational Risk Data and Parametric Models; Introduction; Internal Data and External Data; Basic Parametric Severity Distributions; The Generalized Champernowne Distribution; Quantile Estimation; Further Reading and Bibliographic Notes; ; Semiparametric Model for Operational Risk Severities; Introduction; Classical Kernel Density Estimation; Transformation Method; Bandwidth Selection; Boundary Correction; Transformation with the Generalized Champernowne Distributions; Results for the Operational Risk Data; Further Reading and Bibliographic Notes; ; Combining Operational Risk.
- Data Sources; Why Mixing?; Combining Data Sources with the Transformation Method; The Mixing Transformation Technique; ; Data Study; Further Reading and Bibliographic Notes; ; Underreporting; Introduction; The Underreporting Function; Publicly Reported Loss Data; Semiparametric Approach to Correction tor Underreporting; An Application to Evaluate Operational Risk with Correction; An Application to Evaluate Internal Operational Risk; Further Reading and Bibliographic Notes; ; Combining Underreported Internal and External Data; Introduction; Data Availability; Underreporting Losses; A Mixing Model in a Truncation Framework; Operational Risk Application; Further Reading and Bibliographic Notes; ; A Guided Practical Example; Introduction; Descriptive Statistics and Basic Procedures; Transformation Kernel Estimation; Combining Internal.
- And External Data; Underreporting Implementation; Programming in R.