Key Features
*Risk model validation is a requirement of Basel I and II
*The first collection of papers in this new and developing area of research
*International authors cover model validation in credit, market, and operational risk
Description
Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk.
Readership
Primary audience: Investment Professionals and academics
The Analytics of Risk Model Validation, 1st Edition
ContentsChapter 1 Determinants of small business default,
Sumit Agarwal, Souphala Chomsisengphet and Chunlin LiuChapter 2 Validation of stress testing models,
Jospeh L. BreedenChapter 3 The validity of credit risk model validation methods,
George Christodoulakis and Stephen SatchellChapter 4 A moment-based procedure for evaluating risk forecasting models,
Kevin Dowd Chpater 5 Measuring concentration risk in credit portfolios,
Klaus DuellmannChapter 6 A simple method for regulators to cross-check operational risk loss models for banks,
Wayne Holland and ManMohan S. SodhiChapter 7 Of the credibility of mapping and bencmarking credit risk estimates for internal rating systems,
Vichett OungChapter 8 Analytic models of the ROC curve: Applications to credit rating model validation,
Stephen Satchell and Wei XiaChapter 9 The validation of the equity portfolio risk models,
Stephen SatchellChapter 10 Dynamic risk analysis and risk model evaluation,
Gunter Schwarz and Christoph KesslerChapter 11 Validation of internal rating systems and PD esitmates,
Dirk TascheIndex
