Dieter Gramlich

SAFE: An Early Warning System for Systemic Banking Risk

This paper builds on existing microprudential and macroprudential early warning systems (EWSs) to develop a new, hybrid class of models for systemic risk that incorporates the structural characteristics of the financial system and a feedback amplification mechanism. The models explain financial stress using both public and proprietary supervisory data from systemically important institutions, regressing institutional imbalances using an optimal lag method. The Systemic Assessment of Financial Environment (SAFE) EWS monitors microprudential information from the largest bank holding companies to anticipate the buildup of macroeconomic stresses in the financial markets. To mitigate inherent uncertainty, SAFE develops a set of medium-term forecasting specifications that gives policymakers enough time to take ex-ante policy action and a set of short-term forecasting specifications for verification and adjustment of supervisory actions. This paper highlights the application of these models to stress testing and policy.

The structural fragility of financial systems: Analysis and modeling implications for early warning systems

Purpose - Lessons from the most recent financial crisis show specific vulnerabilities of financial markets due to weaknesses in the structure of the financial system (structural fragility). As the literature points out, the impact of systemic risk can be closely related to issues of concentration (“too big to fail”) and dependency (“too connected to fail”). However, different structural variables are emphasized in various ways, and most authors analyze each variable separately. This raises the questions of how structural fragility, as a cause of systemic distress, can be assessed more comprehensively and consistently, and what the implications are for modeling it within an integrated systemic risk framework. This paper seeks to address these issues. Design/methodology/approach - On the basis of theoretical considerations and in the light of current transformations in financial markets, this paper explores elements of structural fragility and the requirements for modeling them. Findings - The paper suggests an extended approach for conceptualizing structural fragility, evaluates directions for quantifying structural issues in early warning systems (EWSs) for systemic crises, and lays a theoretical groundwork for further empirical studies. Originality/value - The need for supervisory actions to prevent crises is urgent, as is the need for integrating structural aspects into EWSs for systemic financial crises. Since a significant aspect of a financial firms risk comes from outside the firm, individual institutions should understand and monitor the structural aspects of the various risk networks they are in.

Systemic Risk Early Warning System: A Micro-Macro Prudential Synthesis

From the financial supervisor’s point of view, an early warning system involves an ex ante approach to regulation, targeted to predict and prevent crises. An efficient EWS allows timely ex ante policy action and can reduce the need for ex post regulation. This chapter builds on existing microprudential and macroprudential early warning systems (EWSs) to propose a hybrid class of models for systemic risk, incorporating the structural characteristics of the financial system and a feedback amplification mechanism. The models explain financial stress using data from the five largest bank holding companies, regressing institutional imbalances using an optimal lag method. The z-scores of institutional data are justified as explanatory imbalances. The models utilize both public and proprietary supervisory data. The Systemic Assessment of Financial Environment (SAFE) EWS monitors microprudential information from systemically important institutions to anticipate the buildup of macroeconomic stresses in the financial markets at large. To the supervisor, SAFE offers a toolkit of possible institutional actions that can be used to diffuse the buildup of systemic stress in the financial markets. A hazard inherent in all ex ante models is that the model’s uncertainty may lead to wrong policy choices. To mitigate this risk, SAFE develops two modeling perspectives: a set of medium-term (six-quarter) forecasting specifications that gives policymakers enough time to take ex ante policy action, and a set of short-term (two-quarter) forecasting specifications for verification and adjustment of supervisory actions. Individual financial institutions may utilize the public version of SAFE EWS to enhance systemic risk stress testing and scenario analysis. This chapter shows the econometric results and robustness support for the SAFE set of models. The discussion of results addresses the usability and usefulness tests of supervisory data. In addition, the chapter investigates and suggests which action thresholds are appropriate for this EWS.

Policy in Adaptive Financial Markets — The Use of Systemic Risk Early Warning Tools

How can a systemic risk early warning system (EWS) facilitate the financial stability work of policymakers? In the context of evolving financial market dynamics and limitations of microprudential policy, this study examines new directions for financial macroprudential policy. A flexible macroprudential approach is anchored in strategic capacities of systemic risk EWSs. Tactically, macroprudential applications are founded on information about the level, structure, and institutional drivers of systemic financial stress and aim to manage the financial system risk and imbalances in two dimensions: across time and institutions. Time-related EWS policy applications are analyzed in pursuit of prevention and mitigation. EWS applications across institutions are considered via common exposures and interconnectedness. Care must be taken in the calibration of macroprudential applications, given their reliance on quality of the underlying systemic risk-modeling framework.

Sustainability Stress Testing the Financial System: Challenges and Approaches

In addition to risks originating from the economic system, the stability of financial markets and institutions is exposed to adverse conditions in the surrounding social and ecological system. The exposure from unfavorable socio-ecological conditions (sustainability risks) affects the financial markets from multiple perspectives. A way to assess the financial system’s exposure to these risks and also to explore risk mitigation strategies is to incorporate sustainability risks into the framework of stress testing the financial system.

The contributions to systemic stress of financial interactions between the US and Europe

Understanding the connectivity of international financial markets is critical to understanding the origination and propagation of financial crises. This study investigates the contribution of US and European exchange rate interactions to overall stress in the US financial system from 1992 to 2013. The impacts of these interactions are assessed using a financial stress index that aggregates measures of national and international stresses. There are three main findings for the sample period. First, we find that European influences on US financial stress have increased. Second, observing several structural breaks with changing correlation and Granger causality patterns, we find that the euro and the British pound have contributed varying levels of stress. Third, we find that stress in US markets tends to spill over into European markets, while the reverse influences are of lesser importance. These findings have important implications for supervisors in international markets. Understanding the amplifying or attenuating feedback effects from international connectivity provides valuable insight into the development of macroprudential policies.

Information Disclosure, Bank Performance and Bank Stability

The purpose of this research is to identify the effects of information disclosure on commercial bank performance and stability. Specifically, the study examines the relationship between different levels of information disclosure and the subsequent impact on various measures of bank return and risk. The focus is on securitised assets and credit derivative activities, both of which were at the heart of the sub-prime mortgage crisis of 2008. Using a sample of 27 US bank holding companies (BHCs) for the period from June 2001 to December 2008, a significant relationship between the quantity and quality of information disclosure and bank performance and stability is observed. A ‘switching’ behaviour is identified, whereby performance and stability initially decrease and then improve when additional information on a bank’s securitisation and credit derivative activities are disclosed. This switching effect is possibly explained by economies-of-scale and a ‘learning curve’ effect. The results provide guidance for managing both the volume and quality of information disclosed by both bank managers and the regulatory authorities.