The area of quantitative operational risk has undergone explosive developmentfor the last five years and is of critical importance for the banking industry. It is driven mainly by recent Basel II regulatory requirements that introduced definitions and capital charges for operational risk. The area of quantitative operational risk is very new and the different approaches to it are heatedly debated. This book is devoted to quantitative issues in the loss distribution approach for operational risk being adopted in many banks. In particular, the use of the Bayesian inference method is the main focus of this book. Though it is very new in this area, the Bayesian approach is well suited for modelling operational risk, as it provides a consistent and convenient statistical framework to quantify the uncertainties involved. It also allows the combination of expert opinions with historical internal and external data in estimation procedures. These are critical, especially for operational risks with small datasets. Presents Bayesian framework for operational risk that can be used by banks to resolve quantitative challenges with implementation of Basel II advanced measurement approach Numerous examples will help risk practitioners to quantify operational risks Examples and exercises will help graduate students to learn quantitative risk concepts and models INDICE: Operational Risk and Basel II.- Loss Distribution Approach.- Calculation of Compound Distribution.- Bayesian approach for LDA.- Addressing the Data Truncation Problem.- Modelling Large Losses.- Modelling Dependence.- List of Distributions.- Selected Simulation Algorithms.- Solutions for Selected Problems.- References.- Index.
- ISBN: 978-3-642-15922-0
- Editorial: Springer
- Encuadernacion: Cartoné
- Páginas: 310
- Fecha Publicación: 01/11/2010
- Nº Volúmenes: 1
- Idioma: Inglés