On Wednesday, we brought you the latest from Bloomberg contributor Cameron Crise who has been batting close to 1.000 lately in terms of “things that HR readers apparently like to click on.”

Crise looked at credit card spending and suggested that unless consumers start tapping revolving credit lines, the promised economic renaissance might not materialize after all.

He also noted that paradoxically, consumers will be sowing the seeds of their own demise should they decide to whip out the plastic again.

Well on Thursday Crise is back, and this time he’s looking to explain why the VIX has been persistently low. Now to be sure, one simple explanation for suppressed volatility goes something like this (from a post earlier this month):

One burning question this year has been why volatility has remained so stubbornly low.

At a base level, this is kind of a silly question if you’re talking about the VIX. That is, January was the fifth calmest month on record as measured by realized vol and if low realized vol begets low implied vol, well then…

But one of the important things to note is the extent to which collapsing stock and sector correlations have contributed. And do you know what’s driven S&P correlation so low? Here’s a hint: the fact that there are clear winners and losers from the Trump agenda. Recall this from Goldman:

• US stock correlations have plummeted, driven by falling correlation between sectors. S&P 500 average 3-month realized stock correlation hit 0.09 earlier this month, the lowest level since the mid-1990s. However, correlations within sectors have declined less than the correlations between sectors, reflecting the relatively “macro” potential consequences of the new administration’s proposed policies and recent economic acceleration as well as the investor use of ETFs to capture those dynamics.

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And from SocGen:

• From a technical perspective, index volatility is a function of not only average single-stock volatility, but also of how stocks within the S&P 500 are moving with respect to one another – a measure of correlation. When the correlation is low, most stocks move in different directions. With all these individual stock moves, there is no clear direction to the overall index, and this, in turn, dampens down volatility. The short term (three month) average pairwise correlation among the S&P 500 sectors touched its lowest level since 2002, while the 3m realised volatility reached its lowest level in the past 27 years and is in the 3rd percentile since 1928 (see charts below). The short-term implied volatility (as measured by the VIX) depends primarily on realised volatility. If realised volatility is low, and expected to remain low, especially because of the dampening effect from the low realised correlation among stocks, the short-term implied volatility is likely to remain subdued, as the cost of carrying long vol positions is too high, making sure implied vol converges towards realised.

  (Click on image to enlarge)

But Crise takes a different approach – which is good because we were sick of repeating the narrative outlined above anyway – looking at the VIX versus the credit cycle for clues. That dovetails nicely with yesterday’s piece on credit card usage (the one linked above).

Below, find Crise’s latest in which he notes that in the simplest possible terms, the VIX is as low as it is “because it should be.”

Via Bloomberg

The credit cycle is the bedrock of macroeconomic trends. When credit is flowing and default rates are low, the economy and financial markets tend to perform well. As the cycle matures and credit quality deteriorates, the conditions fall into place for a recession and a bear market. And while there’s a lot of head-scratching over why the VIX is so low in the face of apparent uncertainty, it’s hard to argue that it’s too far out of whack when compared to credit spreads.

• Of course, spreads themselves are a function of market perception that may or may not reflect current and future economic reality. VIX and spreads are both measures of current market risk appetite, so it is unsurprising that they convey the same message. What if we look at economic measures of credit and the cycle? Will they provide the same conclusion? I decided to find out.
• I modeled the VIX using three simple macro inputs:
• The 6-month moving average of the Chicago Fed National Activity Indicator as a proxy for the economic cycle
• The U.S. credit card delinquency rate
• The 1-year change in the U.S. nonfinancial corporation asset-to-liability ratio from the quarterly flow-of-funds data
• Using such low- frequency data, we shouldn’t expect to derive a signal that captures the high-frequency amplitude of the VIX. Then again, that’s not what we’re interested in. The question we’re asking is “where should trend volatility be given the economic and credit cycle?” The answer appears to be “pretty low.”
• Each of the model inputs has a coefficient pointing in the “correct” direction, and the output has done a pretty good job of capturing trends in the VIX over the past 15 years or so.
• Interestingly, the model suggests that the VIX should be lower than it was in 2006, a year famous for its lack of volatility.
• While the VIX is currently lower than the model reading, the magnitude of the difference is pretty modest in a historical context.
• Until we see a deterioration in credit quality across the broad economy, we can probably put one burning question to bed. Why is the VIX so low? Because it should be.