From Money Banking and Financial markets:
Economists and policymakers are on a quest. They are looking for the elixir that will protect their economies from financial crises. Their strategy is to find an indicator that provides an early warning of collapse, and then respond with preventative measures.
We think the approach of waiting for warnings is seriously flawed. The necessary information may never be in our grasp. And even if it were, our ability to respond rapidly and effectively is far from clear. Rather than treating the symptoms of illness after they start to develop, we believe the better strategy is early immunization: the more resilient the financial system, the less reliance we will have on faulty or nonexistent warnings.
To back up a bit, there are now an abundance of indices designed to measure financial system stress. In 2012, a study from the Treasury Office of Financial Research cataloged 31 such indicators for the United States alone. More recently, a comprehensive examination of the euro area, the United Kingdom, and the United States by Giglio, Kelley and Pruitt (GKP) considers a total of 39 measures. Following the crisis, central banks quickly got into the act. Four Federal Reserve Banks – Chicago, Cleveland, Kansas City and St. Louis – each publish an indicator of financial system stress. The ECB, as a part of its macroprudential research network, constructed and now publishes a composite index of system stress (CISS).
We view GKP’s work as the current gold standard on this subject. What they do is look for leading indicators of changes in the lower tail of the distribution of output. That is, instead of trying to forecast economic growth per se, they use quantitative techniques capable of forecasting whether the probability of a really bad outcome has increased. (It’s called quantile regression, and is worth knowing about if you are statistically inclined.) After a huge effort to collect data, derive best-practice statistical procedures and write computer code, GKP conclude that the best they can do is forecast changes in the probability of bad outcomes about three months ahead. And, their most useful indicator is the volatility of financial institution stock prices.
These findings are compelling. They tell us that forecasting systemic stress is extremely difficult and that ordinary financial market indicators efficiently summarize what information there is.
Looking at some data, we can see where the problem lies. The chart below plots three measures of financial stress. (All are standardized to have zero mean and unit variance over the period.) The black line is the popular market-based volatility index from the Chicago Board of Trade (CBOT), widely known as the VIX. The red line is the median of the four Federal Reserve Bank stress indicators. And the orange line is the ECB’s CISS.
We see two things in this chart. First, these series move together. There just isn’t much information in either the Fed or the ECB series beyond what is contained in the VIX.
Second, and even more importantly, these are contemporaneous measures of stress. That is, they do not signal where we might be going; they tell us where we are. This is immediately apparent from the fact that in early 2007, mere months before the great financial crisis got started, the measured level of stress is at one of its lowest points! Not only was financial volatility unusually low, but so were interest rate spreads and a variety of other measures of financial system stress.
Comparing Indices of Financial Stress and the VIX
Source: FRED2 and ECB.
We do not mean to strike too harsh a tone. Having accurate measures of where we stand is extremely useful. And, what is true for navigation also holds for crisis management. To see what we mean, look at the NYU Stern Volatility Institute’s state-of-the-art market-based measure of systemic risk called “SRISK.” Computed daily at the level of individual financial institutions, SRISK is the expected capital shortfall conditional on an aggregate equity market decline of 40% over a period of six months. This measure provides high-frequency information about each intermediary that is similar to the results of a stress test. Importantly, by reducing the estimated size of its capital buffer, a fall in the market value of a firm’s equity drives up its estimated contribution to systemic risk.