SAFE: An Early Warning System for Systemic Banking Risk

Abstract

Advisory: This article is based in whole or in part on the CFSI (Cleveland Financial Stress Indicator), an indicator that was discontinued by the Federal Reserve Bank of Cleveland in 2016 due to the discovery of errors in the indicator's construction. These errors overestimated stress in the real estate and securitization markets. As a result, readers should be cautious and interpret any analysis based on CFSI data with those errors in mind.This paper builds on existing microprudential and macroprudential early warning systems (EWSs) to develop a new, hybrid class of models for systemic risk, incorporating the structural characteristics of the fi nancial system and a feedback amplifi cation mechanism. The models explain fi nancial 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 fi nancial markets. To mitigate inherent uncertainty, SAFE develops a set of medium-term forecasting specifi cations that gives policymakers enough time to take ex-ante policy action and a set of short-term forecasting specifi cations for verifi cation and adjustment of supervisory actions. This paper highlights the application of these models to stress testing, scenario analysis, and policy.

Cryptography and the Economics of Supervisory Information: Balancing Transparency and Confidentiality

“…Because these signals can affect significant financial decisions, there are costs or losses associated with both false positives and false negatives. In some cases, expanding the set of data inputs for the index calculation can improve the accuracy of the index; see Oet et al [166]. Unfortunately, these enhancements can be blocked by legal restrictions due to licensing agreements, privacy laws, and confidentiality of supervisory data.…”

“…For example, Oet et al [167,168] compared an index based on both public and confidential data (Systemic Assessment of Financial Environment, SAFE) with an analogous index based only on publicly available data (Cleveland Financial Stess Index, CFSI). Their analysis indicates that the confidentially augmented SAFE index would have been a significantly more accurate indicator at the height of the recent financial crisis (see Oet et al [166,Figure 4]).…”

Measuring Flight-to-Quality with Granger-Causality Tail Risk Networks

“…Episodes of this type are commonly referred to as "flight-to-quality" and can play a prominent role in the propagation and deepening of financial crises. Thus, the ability of identifying and possibly anticipating (at least partially) such phenomena is of great importance also in the context of early-warning and monitoring of systemic risk (Demirgüç-Kunt and Detragiache, 1998;Kaminsky and Reinhart, 1999;Harrington, 2009;Scheffer et al, 2009; Barrell et al, 2010;Duttagupta and Cashin, 2011;Kritzman et al, 2011;Allen et al, 2012;Arnold et al, 2012;Bisias et al, 2012;Scheffer et al, 2012;Merton et al, 2013;Oet et al, 2013). Moreover the identification of flight-to-quality episodes is of great importance as a measure of the market perception of the quality of the assets.…”

Evaluating the Information Value for Measures of Systemic Conditions

“…These include alternative measures of systemic conditions to identify the cyclical dimension continually, as well as institutional and macroeconomic early warning indicators of exuberance, excessive changes and misalignments. 2 Institutional early warning indicators are grounded in capacities to lead the recognition of institutional imbalances and result in a structural framework for monitoring the buildup of macroeconomic stresses (Oet et al, 2013). Macroeconomic early warning indicators are grounded in capacities to lead the recognition of systemic crises and germinate a common cyclical framework for evaluating policymaker's loss function (Alessi and Detken, 2011;Sarlin, 2013).…”