Of VIX, Correlation, And Building A Better Mousetrap

We have discussed the use of correlation (cross-asset-class and intra-asset-class) a number of times in the last few years, most recently here, as a better way to track 'fear' or greed than the traditional (and much misunderstood) VIX. As Nic Colas writes this evening, a review of asset price correlations shows that the convergence typical of 'risk-off' periods in the market is solidly underway. While we prefer to monitor the 'finer' average pairwise realized correlations for the S&P 100 - which have been rising significantly recently, Nic points out that the more coarse S&P 500 industry correlations relative to the index as a whole are up to 88% from a low of 75% back in February. In terms of assessing market health, a decline in correlation is a positive for markets since it shows investors are focused on individual sector and stock fundamentals instead of a macro “Do or die” concerns.  By that measure, we’re moving in the wrong direction, and not just because of recent decline in risk assets.  Moreover, other asset classes such as U.S. High Yield corporate bonds, foreign stocks (both emerging market and develop economies), and even some currencies are increasingly moving in lock step.  Lastly, we would highlight that average sector correlations have done a better job in 2012 of warning investors about upcoming turbulence than the closely-watched CBOE VIX Index.  Those investors looking for reliable “Buy at a bottom” indicators should add this metric to their investment toolbox as a better 'mousetrap' than the now ubiquitous VIX.

Nic Colas, ConvergEx: Building A Better (Volatility) Mousetrap

The most patented machine in American history has nothing to do with the Internet, or automobiles, or space exploration; rather, it is the humble mousetrap.  According to noted historian on the topic (yes, there is a mousetrap historian… See link after the note) Jack Hope, since the U.S. Patent Office opened its doors in 1838 it has awarded over 4,400 patents for distinct approaches to catching mice.  The process for obtaining a “Terminate mouse with extreme prejudice” patent includes categorizing your invention into a distinct subclass – “Impaling,” “Choking or squeezing,” or “Electrocution and explosive,” for example – and then proving that you have a unique approach to the process.   And in case that’s not enough mousetrap trivia for you, consider that the still-popular “Snap trap” was first patented in 1903 and is among the handful of inventions in this realm to ever turn a profit.  According to Hope, 95% of all mousetrap patents have gone to first-time applicants and fewer than two dozen have ever made any money for their inventors.

The desire to build a better method of catching mice is positively ingrained in American lore, exemplified by the old Ralph Waldo Emerson quote, “If a man can write a better book, preach a better sermon, or make a better mousetrap, than his neighbor, though he builds his house in the woods, the world will make a beaten path to his door.”   Innovation is a hallmark of American entrepreneurial spirit, whether it is pointed at a field mouse breakfasting in your pantry or fixated on developing the next tablet computer.  The mousetrap is, for better or worse, the symbol of that drive to create both.  Emerson’s observation may have seemed random at the time, but hoards of patent-seekers have proven him right since then.

In the same spirit of invention, I would like to offer up a “Better mousetrap” for measuring market sentiment.  The existing product – the CBOE VIX Index – has been around for +20 years in its current form and has done yeoman’s work at defining the conversation around how to measure “Fear” in equity markets.  Technically, the VIX is simply the price of short term portfolio insurance on a basket of large-cap U.S. stocks.  That insurance comes through the options market, where every contract is priced against the Black-Scholes five-input model and “Implied Volatility” (IV) is the unknown variable.  The higher the IV, the more investors are willing to pay for options that protect their portfolios against near term price declines.

My mousetrap is the actual price correlations between the S&P 500 sectors and the index as whole, measured on a trailing monthly basis.  Right after the text of this note is a summary table that shows the current levels for each of the 10 major industry sectors as well as some other asset classes such as commodities, international equities, currencies and fixed income investments.  We’ll get to the latter categories in a minute, but let’s focus on sector correlations for a moment.  A few points here:

  • Different industries typically do better at different parts of the economic cycle.  As the U.S. moves from recession and into the early stages of recovery, financials tend to outperform.  Towards the end of an economic upturn, commodity producers take the lead since their products have hit scarcity thresholds that offer them pricing power and cash flow.
  • Historically, active money managers have focused intensely on getting their sector over/underweights correct, and the common wisdom was that these decisions were 50% of outperforming the S&P 500 index benchmark.  The other half was picking the right stocks, but every manager knows the pain of picking the right stock in the wrong sector.   You are often better off picking the worst stock in the right sector.
  • Over the last few years, U.S. industry sector price correlations have yo-yoed between their long term historical averages (50-70%, depending on the group) all the way to +90% in any given month.  For example, the average industry price correlation for the 10 major sectors in the S&P 500 is 88%, measured against the index itself.  This is essentially the average of the past two years (87%), but still higher than “Normal” markets.  Average sector correlations have been as high as +95% and as low as 75% (historical charts attached).
  • While the average sector correlations we’ve outlined here tend to track the VIX pretty well (69% correlation, as shown in the accompanying graph), there has been a strange divergence in the past five months.  Simply put, the VIX is down 21% over the course of 2012, but the average sector correlation is +1.5 points over the same period.
  • Does the current investment environment look and feel like it is 21% less risky than the end of 2011?  Only if you are in cash, gold, shotguns and a cabin in rural Maine, I think.  The VIX has been unexpectedly quiescent in recent weeks, touching 17.5 on June 20th.  Even with Monday’s sell-off it barely held 20, its long run average.
  • Conversely, the correlation data is sending up a very visible warning flare about future market direction.  Back in February/March 2012, this indicator hit its low (good for stocks, since they are moving distinctly and separately) and began to trend higher (bad for stocks). Now, sector price correlations have essentially gotten back to their 2 years averages – 87/88%.  This would be like the CBOE VIX Index reading 28, which is its post-Financial Crisis average.  And frankly, a VIX at 28 would feel about right.
  • The real “Buy signal” from sector correlations is when then hit 95%, some ways from here.  As the accompanying charts show, this occurred in mid 2010 and Fall 2011 – both good times to buy U.S. stocks.

Just to round out the discussion, I would point out that there are asset classes that aren’t clustering around stocks like scared sheep in a thunderstorm.  Precious metals, for all their whippy action this past month, are fulfilling their promise to act independently of financial assets.  Gold’s correlation to the S&P 500 index was (18%) last month, and Silver was just +11%.  I have read some notes recently that were critical of gold’s ability to provide diversification in choppy markets.  This month, however, gold and silver are acting exactly as they should – with no eye to other asset class price movements.  U.S. high yield bonds are at the other end of the spectrum, and now trade more like domestic stocks (87% correlation) than sectors such Utilities (59% correlation to the S&P 500) and Consumer Staples (81%).    International equities – developed and emerging economies alike – trade more like US stocks than most U.S. stocks.  Their correlations are 91% (EAFE stocks) and 89% (Emerging markets), versus that 88% sector average.

My conclusion is that sector correlations are a useful adjunct to the widely-followed CBOE VIX Index when it comes to assessing how much risk is really priced into U.S. stocks.  It isn’t actually a “Better mousetrap,” in that the VIX is widely traded and tracked.  But it is a useful add-on tool, and one that is more accurately reflecting the risks imbedded in U.S. stocks at the moment. 


[ZH: as an addenda, we track implied correlation and cross-asset-class realized correlation almost every day in our various market posts, and furthermore, while Nic's approach at analyzing the sector correlations is extremely valuable in our eyes, we find the greater sensitivity of the average correlation of the entire 100 names of the S&P 100 (and the high-yield and investment grade credit indices) is a more accurate and better indicator for turning points in macro 'fear' and 'insensitivity']

The chart below is the intraday cross-asset-class correlation for today - this measures the minute-by-minute changes in commodities, rates, credit, and FX relative to stocks for a sense of whether stocks are moving systemically or idiosyncratically...

Clearly, stocks began to move on their own after mid-morning as correlations fell and then after-hours this evening, correlations have picked back up as stocks have resynced with systemic risk movements.

Below is the chart of 1-month and 2-month rolling average of all pairwise realized correlations in the S&P 100.  Compare this to the chart in the upper left of the charts above (above measures the high beta correlation between the 10 sectors and the S&P; below measures the much broader and more sensitive correlation across all 100 names in the S&P 100)

Three things should stand out:

1) We are following a very similar cyclical pattern of idiosyncratic to systemic fear rotation once again - i.e. as Fed measures lift and we are left to fend for ourselves so risk rises and systemic fears creep back into the market, slowly at first and then rapidly;

2) We are quite a way from any capitulative 'fear' level across the 100 names of the S&P 100 - i.e. there is considerably more pain to come as correlation is expected to rise; and

3) This realized pairwise correlation is much closer to the implied correlation levels we see by tracking the variation between index volatility and the average of all individual volatilies - i.e. this is a better day-to-day tracker for the premium in implied correlation (the real 'FEAR' index) over a realized correlation.


Finally, the chart above shows the average pairwise correlation for a rolling two-month period across all 125 names in the IG18 credit index. Three things should be apparent:

1) IG credit is considerably more sensitive to swings in systemic risk than stocks - i.e. the variation high-to-low is greater and more rapid;

2) We are at a more extreme level of realized correlation in IG credit currently, perhaps indicative of an increase in dispersion aboout to occur - or post-hoc a major market dislocation; and

3) the rapid rise in pairwise correlation post the JPM-CIO-Whale Debacle as investment grade credit spreads in IG become much more index-driven than idiosyncratic risk driven thanks to the need to unwind their position - i.e. a pronounced turn-down would be indicative of a slowing in the unwind. 


Bottom-Line - Don't worry about VIX, it's simply too contemporaneous with risk to be useful; understand and identify useful relationships in correlation to comprehend real 'fear' in the market. Right now, correlation is indicating a systemic AND risk-off mode in markets.