This paper presents a "second-generation" solvency stress testing framework extending applied stress testing work centered on Cihák (2007). The framework seeks enriching stress tests in terms of risk-sensitivity, while keeping them flexible, transparent, and user-friendly. The main contributions include (a) increasing the risk-sensitivity of stress testing by capturing changes in risk-weighted assets (RWAs) under stress, including for non-internal ratings based (IRB) banks (through a quasi-IRB approach); (b) providing stress testers with a comprehensive platform to use satellite models, and to define various assumptions and scenarios; (c) allowing stress testers to run multi-year scenarios (up to five years) for hundreds of banks, depending on the availability of data. The framework uses balance sheet data and is Excel-based with detailed guidance and documentation.

This paper presents a "second-generation" solvency stress testing framework extending applied stress testing work centered on Cihák (2007). The framework seeks enriching stress tests in terms of risk-sensitivity, while keeping them flexible, transparent, and user-friendly. The main contributions include (a) increasing the risk-sensitivity of stress testing by capturing changes in risk-weighted assets (RWAs) under stress, including for non-internal ratings based (IRB) banks (through a quasi-IRB approach); (b) providing stress testers with a comprehensive platform to use satellite models, and to define various assumptions and scenarios; (c) allowing stress testers to run multi-year scenarios (up to five years) for hundreds of banks, depending on the availability of data. The framework uses balance sheet data and is Excel-based with detailed guidance and documentation.

This paper explains specifics of stress testing at the IMF. After a brief section on the evolution of stress tests at the IMF, the paper presents the key steps of an IMF staff stress test. They are followed by a discussion on how IMF staff uses stress tests results for policy advice. The paper concludes by identifying remaining challenges to make stress tests more useful for the monitoring of financial stability and an overview of IMF staff work program in that direction. Stress tests help assess the resilience of financial systems in IMF member countries and underpin policy advice to preserve or restore financial stability. This assessment and advice are mainly provided through the Financial Sector Assessment Program (FSAP). IMF staff also provide technical assistance in stress testing to many its member countries. An IMF macroprudential stress test is a methodology to assess financial vulnerabilities that can trigger systemic risk and the need of systemwide mitigating measures. The definition of systemic risk as used by the IMF is relevant to understanding the role of its stress tests as tools for financial surveillance and the IMF’s current work program. IMF stress tests primarily apply to depository intermediaries, and, systemically important banks.

Over the last decade, stress testing has become a central aspect of the Fund’s bilateral and multilateral surveillance work. Recently, more emphasis has also been placed on the role of insurance for financial stability analysis. This paper reviews the current state of system-wide solvency stress tests for insurance based on a comparative review of national practices and the experiences from Fund’s FSAP program with the aim of providing practical guidelines for the coherent and consistent implementation of such exercises. The paper also offers recommendations on improving the current insurance stress testing approaches and presentation of results.

Rules of thumb can be useful in undertaking quick, robust, and readily interpretable bank stress tests. Such rules of thumb are proposed for the behavior of banks’ capital ratios and key drivers thereof—primarily credit losses, income, credit growth, and risk weights—in advanced and emerging economies, under more or less severe stress conditions. The proposed rules imply disproportionate responses to large shocks, and can be used to quantify the cyclical behaviour of capital ratios under various regulatory approaches.

Stress Testing and Risk Integration in Banks provides a comprehensive view of the risk management activity by means of the stress testing process. An introduction to multivariate time series modeling paves the way to scenario analysis in order to assess a bank resilience against adverse macroeconomic conditions. Assets and liabilities are jointly studied to highlight the key issues that a risk manager needs to face. A multi-national bank prototype is used all over the book for diving into market, credit, and operational stress testing. Interest rate, liquidity and other major risks are also studied together with the former to outline how to implement a fully integrated risk management toolkit. Examples, business cases, and exercises worked in Matlab and R facilitate readers to develop their own models and methodologies. - Provides a rigorous statistical framework for modeling stress test in line with U.S. Federal Reserve FRB CCAR (Comprehensive Capital Analysis Review), U.K. PRA (Prudential Regulatory Authority), EBA (European Baning Authorithy) and comply with Basel Accord requirements - Follows an integrated bottom-up approach central in the most advanced risk modelling practice - Provides numerous sample codes in Matlab and R

This paper presents a simple heuristic measure of tail risk, which is applied to individual bank stress tests and to public debt. Stress testing can be seen as a first order test of the level of potential negative outcomes in response to tail shocks. However, the results of stress testing can be misleading in the presence of model error and the uncertainty attending parameters and their estimation. The heuristic can be seen as a second order stress test to detect nonlinearities in the tails that can lead to fragility, i.e., provide additional information on the robustness of stress tests. It also shows how the measure can be used to assess the robustness of public debt forecasts, an important issue in many countries. The heuristic measure outlined here can be used in a variety of situations to ascertain an ordinal ranking of fragility to tail risks.