Book description
Senior management are expected to make crucial business decisions using complex risk models that, without specialized quantitative financial knowledge, can lead to ill judged choices. The recent controversial discussions concerning the use of risk models during the financial crisis, and the new regulatory framework, have highlighted the need for a consistent approach to answer the question “What are risk models made for?” and maybe even more importantly “What are risk models NOT made for?”.
The report aims to explain:
- What risk model validation is;
- What risk models exist;
- How a risk model can fail;
- Which aspects of reality are included, and which aspects are excluded from a risk model; and
- How business decisions can be based on a risk models’ output.
In addressing these issues, this report provides practical advice to the management of financial institutions and a toolbox to raise the key questions when it comes to integrating the results of quantitative models into business decisions.
Book details
- ISBN
- Book 9781906348519 / EBook 9781908823274
- Publish date
- 30 Mar 2011
- Format
- Paperback
- Size
- A4
Author biography
Christian Meyer and Peter Quell
Christian Meyer is working as Quantitative Analyst in the Portfolio Modeling Team for Market and Credit Risk in the Risk Controlling Unit of DZ BANK AG in Frankfurt where he is responsible for the development of portfolio models for credit risk in the banking book and incremental risk in the trading book. Prior to joining DZ BANK AG he was working for KPMG where he dealt with various aspects (audit and consulting) of market risk, credit risk, and economic capital models in the banking industry. He holds a diploma and PhD in Mathematics.
Peter Quell is Head of the Portfolio Analytics Team for Market and Credit Risk in the Risk Controlling Unit of DZ BANK AG in Frankfurt. Prior to joining DZ BANK AG he was Manager at d-fine GmbH where he dealt with various aspects of risk management systems in the banking industry. He holds a MSc. in Mathematical Finance from Oxford University and a PhD in Mathematics.
Table of contents
Introduction
1 Basics of Quantitative Risk Models
Thinking About Risk
Elements of Quantitative Risk Models
An Historical Example
Usage of Statistics in Quantitative Risk Models
Setup of Quantitative Risk Models
2 How Can a Risk Model Fail?
Design
Implementation
Data
Processes
Use
3 Validation Issues
What is Validation?
When to Introduce Validation
Who Carries Out the Validation?
How to Validate Quantitative Risk Models
4 The Basel Accords and Risk Model Validation
The Pillars of the Basel Framework
Risk Models and their Validation Under Pillar 1
Risk Models and their Validation Under Pillar 2
Stress Testing
Guidance on Validation in Regulatory Documents
Final Comments
5 Tools for Validation of Model Results
Statistical Methods
Benchmarking
Scenario Analysis
6 Other Validation Tools
Software Testing
Sensitivity Analysis
Statistical Methods for Validation Of Data
The Use Test
7 Conclusion – Risk Model Frameworks
The Modelling and Implementation Framework
The Validation Framework
Usage of Risk Models
References
Index
Customer Reviews
