The Basel II Risk Parameters [electronic resource] : Estimation, Validation, and Stress Testing /
Engelmann, Bernd.editor.
Rauhmeier, Robert.editor.
In the last decade the banking industry has experienced a significant development in the understanding of credit risk. Refined methods were proposed concerning the estimation of key risk parameters like default probabilities. Further, a large v- ume of literature on the pricing and measurement of credit risk in a portfolio c- text has evolved. This development was partly reflected by supervisors when they agreed on the new revised capital adequacy framework, Basel II. Under Basel II, the level of regulatory capital depends on the risk characteristics of each credit while a portfolio context is still neglected. The focus of this book is on the estimation and validation of the three key Basel II risk parameters, probability of default (PD), loss given default (LGD), and ex- sure at default (EAD). Since the new regulatory framework will become operative in January 2007 (at least in Europe), many banks are in the final stages of imp- mentation. Many questions have arisen during the implementation phase and are discussed by practitioners, supervisors, and academics. A 'best practice' approach has to be formed and will be refined in the future even beyond 2007. With this book we aim to contribute to this process. Although the book is inspired by the new capital framework, we hope that it is valuable in a broader context. The three risk parameters are central inputs to credit portfolio models or credit pricing al- rithms and their correct estimation is therefore essential for internal bank contr- ling and management.
Description based upon print version of record.
Includes bibliographical references and index.
Statistical Methods to Develop Rating Models -- Estimation of a Rating Model for Corporate Exposures -- Scoring Models for Retail Exposures -- The Shadow Rating Approach - Experience from Banking Practice -- Estimating Probabilities of Default for Low Default Portfolios -- A Multi-Factor Approach for Systematic Default and Recovery Risk -- Modelling Loss Given Default: A "Point in Time"-Approach -- Estimating Loss Given Default - Experiences from Banking Practice -- Overview of EAD Estimation Concepts -- EAD Estimates for Facilities with Explicit Limits -- Validation of Banks' Internal Rating Systems - A Supervisory Perspective -- Measures of a Rating's Discriminative Power - Applications and Limitations -- Statistical Approaches to PD Validation -- PD-Validation - Experience from Banking Practice -- Development of Stress Tests for Credit Portfolios.
In the last decade the banking industry has experienced a significant development in the understanding of credit risk. Refined methods were proposed concerning the estimation of key risk parameters like default probabilities. Further, a large v- ume of literature on the pricing and measurement of credit risk in a portfolio c- text has evolved. This development was partly reflected by supervisors when they agreed on the new revised capital adequacy framework, Basel II. Under Basel II, the level of regulatory capital depends on the risk characteristics of each credit while a portfolio context is still neglected. The focus of this book is on the estimation and validation of the three key Basel II risk parameters, probability of default (PD), loss given default (LGD), and ex- sure at default (EAD). Since the new regulatory framework will become operative in January 2007 (at least in Europe), many banks are in the final stages of imp- mentation. Many questions have arisen during the implementation phase and are discussed by practitioners, supervisors, and academics. A 'best practice' approach has to be formed and will be refined in the future even beyond 2007. With this book we aim to contribute to this process. Although the book is inspired by the new capital framework, we hope that it is valuable in a broader context. The three risk parameters are central inputs to credit portfolio models or credit pricing al- rithms and their correct estimation is therefore essential for internal bank contr- ling and management.
Finance.
Management.
Economics, Mathematical .
Econometrics.
Finance, general.
Management.
Quantitative Finance.
Econometrics.