Cross Asset Class ETF Analysis
StressGrades time series can help us visualize the interrelationship between risk themes. Figure 16 represents major stress themes using ETFs. Observe the sequential cascading of systemic risk starting with the February 27, 2007 equity outlier. In June an outlier drop in 10Y bond yields signaled deflation fear, and in August a jump in GLD signaled escalating inflation fears. Again, note the log scale for PStress.
Especially noteworthy is the increasingly synchronized increase in (Normal Implied) PStress observed across all asset classes after August 1, 2007 as systemic risk increased. Equally noteworthy is the synchronized decline in (Normal Implied) PStress in early 2009, signaling a systemic recovery.
StressQ is a snapshot of where volatility levels are currently compared to the last year. They can give clues about visible risk, and where we might search for hidden risk. Figure 17 shows StressQ for the major asset classes as of July 14, 2012. We can quickly see that volatility for commodities (DBC, USO, UNG) is at elevated levels, while bonds (esp LQD & TIP) are at very low levels. DBC’s StressGrade of 93 means that volatility has only exceeded this level 7 % of the time over the last year. On the other extreme for LQD volatility is lower than 96 % of the time. Most other assets are at average to low volatility levels (58-32), implying broadly moderating volatilities.
A related analysis is to contrast StressQ comparisons with DStress, which considers a longer time horizon anchored to the worst case loss experience by each ETF over the last 10 years. Extremely high DStress for Credit/Interest Rate ETF’s
shows that market perception of these assets is close to risk free levels, a hint of dangerous overconfidence and complacency. Energy commodities, EUR FX and European stocks on the other hand are at quite elevated levels, less than five standard deviation away from the largest historical moves (Fig. 18).
In summary, StressGrades amplify market based risk signals and are a helpful guide for prioritizing attention to both high and low volatility scenarios.
Micro perspective outlier analysis prioritizes attention the relevant emerging risks. And when markets are calm, we can shift back to explore structural vulnerabilities from a macro perspective.