Book contents
- Frontmatter
- Contents
- List of figures
- List of tables
- List of boxes
- List of contributors
- Foreword
- Acknowledgements
- Introduction
- Part I Fundamentals
- 1 A framework for assessing financial stability
- 2 Macroeconomic stress-testing: definitions and main components
- 3 Macroeconomic stress-testing banks: a survey of methodologies
- 4 Scenario design and calibration
- 5 Risk aggregation and economic capital
- 6 Data needs for stress-testing
- 7 Use of macro stress tests in policy-making
- Part II Applications
- Conclusions
- Index
- References
6 - Data needs for stress-testing
from Part I - Fundamentals
Published online by Cambridge University Press: 18 December 2009
- Frontmatter
- Contents
- List of figures
- List of tables
- List of boxes
- List of contributors
- Foreword
- Acknowledgements
- Introduction
- Part I Fundamentals
- 1 A framework for assessing financial stability
- 2 Macroeconomic stress-testing: definitions and main components
- 3 Macroeconomic stress-testing banks: a survey of methodologies
- 4 Scenario design and calibration
- 5 Risk aggregation and economic capital
- 6 Data needs for stress-testing
- 7 Use of macro stress tests in policy-making
- Part II Applications
- Conclusions
- Index
- References
Summary
Introduction
As in the case of any other economic application, stress tests depend heavily on data. The aim of this chapter is to provide an overview of what the main information needs are for stress-testing purposes.
In Chapter 2 of this book, it is pointed out that stress tests can be carried out at the level of individual institutions, groups of institutions or the financial system as a whole. They may be used by central banks and supervisory authorities to assess the stability of the financial system or by individual banks in order to design appropriate capital planning and/or identify weaknesses in their risk management systems. In all cases it is necessary to identify the types of data needed for the exercise.
As discussed in the following sections, information needs can vary significantly and depend on several factors, such as the complexity of the simulation, the technical skills available at the institutions and the type of risk which is to be investigated. First, the distinction between sensitivity analyses, based primarily on an isolated change in an input variable, and scenario analyses, which are based on more complex interactions of risk variables and can potentially capture different types of risk, can matter significantly. Second, data inputs depend on whether the simulation is based on historical experience or hypothetical assumptions. In the latter case, data should be combined with expert judgment.
- Type
- Chapter
- Information
- Stress-testing the Banking SystemMethodologies and Applications, pp. 99 - 116Publisher: Cambridge University PressPrint publication year: 2009
References
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