Stress Testing for Financial Institutions
First published:
ISBN: 9781906348113
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Worst-Case and Stressed Correlations in the Asymptotic Single Risk Factor Model
Steffi Höse and Stefan Huschens
Integrating Stress-Testing Frameworks
Stress Tests, Market Risk Measures and Extremes: Bringing Stress Tests to the Forefront of Market Risk Management
Credit Cycle Stress Testing Using a Point-in-Time Rating System
Stress-Testing Credit Value-at-Risk: a Multiyear Approach
Stress Testing the Impact of Group Dependence on Credit Portfolio Risk
Hedge the Stress: Using Stress Tests to Design Hedges for Foreign Currency Loans
Survey of Retail Loan Portfolio Stress Testing
Stress Tests for Retail Loan Portfolios
Stress-Testing Banks’ Credit Risk Using Mixture Vector Autoregressive Models
Uncertainty, Credit Migration, Stressed Scenarios and Portfolio Losses
Worst-Case and Stressed Correlations in the Asymptotic Single Risk Factor Model
Risk Aggregation, Dependence Structure and Diversification Benefit
Stress-Testing Credit Distributions of Banks’ Portfolios: Risk Structure and Concentration Issues
Time-Varying Correlations for Credit Risk: Modelling, Estimating and Stress Testing
Macro Model-Based Stress Testing of Basel II Capital Requirements
Risk Tolerance Concepts and Scenario Analysis of Bank Capital
Basel II-Type Stress Testing of Credit Portfolios
After the development of advanced credit portfolio models, financial institutions are now challenged to implement meaningful stress tests in order to improve their risk management. In addition to this internal risk control, stress tests are part of the regulatory requirements of the revised capital adequacy framework, known as Basel II.11Cf, Basel Committee on Banking Supervision (2006, pp. 213–217).
From a statistical point of view, in stress testing, unfavourable changes in the parameters of the underlying credit portfolio model are considered. Using the Basel II asymptotic single risk factor (ASRF) model, the model parameters of interest are the asset correlations and the default probabilities of the obligors. The crucial question is how stress scenarios for these model parameters can be identified.
As most of the literature focuses on stressing default probabilities with given asset correlations,22For example Bühn and Richter (2006) and Deutsche Bundesbank (2007, p. 113). the opposite approach is taken in this contribution.33For a simultaneous consideration of the model parameters based on statistical estimation methods cf, Höse (2007, Chapters 4.3, 6) and Rösch and Scheule
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