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Systemic Risk Indicator


The Cleveland Fed provides a systemic risk indicator to gauge the level of systemic risk in the US financial services industry. Specifically, the indicator is designed to capture market perceptions of the risk of widespread insolvency in the banking system. To compute the indicator, we follow the method in Saldías (2013) and use data on US banks and financial intermediaries. The chart and data are updated weekly.

The method of computing the SRI starts with calculating two measures of insolvency risk, one an average of default risk across individual banking institutions (average distance-to-default) and the other a measure of risk for a weighted portfolio of the same institutions (portfolio distance-to-default).  The SRI then compares the difference, or spread, between the two. When the insolvency risk of the banking system as a whole rises and converges to the average insolvency risk of individual banking institutions—the narrowing of the spread—it reflects market perceptions of imminent systematic disruption of the banking system.

How to Interpret the Data

To gauge the level of systemic risk in the banking system, the average distance-to-default, the portfolio distance-to-default, and the spread between the two should be interpreted jointly. The average distance-to-default (ADD) reflects the market’s perception of the average risk of insolvency among a sample of approximately 100 US banks. It is calculated using options on the equity of individual banks in our sample and then averaging the perceived insolvency risk of these individual banks. The portfolio distance-to-default (PDD) is a similar measure that is based on options on a weighted portfolio of the same banks. It is calculated using options on an exchange-traded fund (ETF) that reflects the banking system in the aggregate: State Street Global Advisors’ SPDR S&P Bank ETF, commonly referred to as “KBE,” its ticker symbol.

Falling ADD or falling PDD indicates the market’s perception of rising average insolvency risk in the banking sector. Fragility in the banking system is indicated when falling PDD converges toward ADD (the narrowing of the spread), even when both PDD and ADD are well in positive territory.

The spread is the most useful measure.  Data from 2000 to the present indicate that when the spread is less than 0.1 for more than two days it indicates stress, and if it stays below 0.5 for an extended amount of time, it indicates that the markets are signaling major stress about the banking system.

There are limitations to keep in mind when interpreting the indicator. The most important one is that because it is based primarily on market data, it reflects market participants’ beliefs about risk. Those beliefs may or may not be accurate assessments of true risk. While the indicator can be expected to provide useful information about systemic risk in the banking system, it is one of a number of indicators that attempt to extract market signals from market prices.

Reference Research

Additional Resources

  • Model Documentation. This document provides a technical description of the model and data used to compute the systemic risk indicator.
  • FAQs. This page answers some commonly asked questions.
  • Revision Document and Historical Data. The model that generates the data for the Systemic Risk Indicator was updated in February 2017, and historical data were updated retroactively. This document explains the revision. Non-updated historical data are available in this document.

Related Research

  • Acharya, Viral, Robert F. Engle, and Matt Richardson. 2012. “Capital Shortfall: A New Approach to Ranking and Regulating Systemic Risks,” American Economic Review Papers and Proceedings, 102(3), 59-64.
  • Acharya, Viral, Lasse Pedersen, Thomas Philippon, and Matt Richardson. 2017. “Measuring Systemic Risk,” Review of Financial Studies, 30(1): 2-47.
  • Adrian, Tobias, and Markus K. Brunnermeier. 2016. “CoVaR,” American Economic Review, 106(7), 1705-41.
  • Bisias, Dimitrios, Mark Flood, Andrew Lo, and Stavros Valavanis. 2012. “A Survey of Systemic Risk Analytics,” Office of Financial Research Working Paper, (0001).
  • Brownlees, Christian, and Robert F. Engle. 20176. “SRISK: A Conditional Capital Shortfall Measure of Systemic Risk,” Review of Financial Studies, 30(1): 48-79.
  • Craig, Ben R. 2020. “How Well Does the Cleveland Fed’s Systemic Risk Indicator Predict Stress?” Federal Reserve Bank of Cleveland, Economic Commentary, 2020-28.
  • Saldías, M. 2013. “Systemic Risk Analysis Using Forward-Looking Distance-to-Default Series,” Journal of Financial Stability, 9, 498-517.

The Cleveland Financial Stress Index (CFSI). In May of 2016, we discovered errors in the calculation of the CFSI and began a detailed review of the index and its underlying model. Subsequently, we discontinued the CFSI and developed the systemic risk indicator to gauge the level of systemic risk in the US financial services industry.