Why the VIX is so low and why you shouldn’t worry about it yet

Markets have worked themselves to new record highs and almost everybody is talking about the VIX index staying below 10 for so long with no signs of wanting to go up anytime soon. This move to new records has come right on time per our LT wave for July, but more on that in my next weekend post when I will also put out the wave for August.

Long term readers of this blog may know that I consider the VIX an indicator with little or no predictive value, as per this post from 2015: Forget the VIX…. Back then traders were also worried about the VIX being too low, but they would wait another 6 months to get any correction worth talking about and by now we are two years later and 30% higher on the Nasdaq.

So why is the VIX so low again? The answer is the same as in 2015: because volatility has been very low in recent months and weeks. Just how low? Well, I use a very simple measure of volatility: the 50 day (or week) average of the True Range expressed as a percentage of the index (or stock price). I call this “ATR%”. Contrary to the classic ATR the ATR% makes it easy to compare current volatility to earlier periods when the stock or index traded at much lower/higher values.

As of y’day the daily ATR% for the S&P 500 dropped to 0.584, it’s lowest level in more than 23 years and only just above the all time low of 0.566 (Jan 1994). This volatility measure may drop to new record lows if markets stay this calm for a couple more days:

sp_atr_d

The weekly ATR% has also dropped to a very low level of 1.675, which is a 21 year low.

sp_atr_w

With both daily and weekly ATR% at more than 20 year lows we have a VIX at very low levels too. The VIX is simply predicting the recent past.

And there is more. The S&P 500 hasn’t seen a 2% down week since September 9, 2016. That’s 45 weeks without a move that hurts at least a little bit. Such +40 week episodes have been very rare. I have counted only 8 of them since 1950 for the S&P 500, and another 2 of them if we consider the Dow Industrials from 1900-1950. Here is the complete list:

downweeks

As you can see, most of those “painless” episodes have come during the long post-WW2 bull market, which ended in the early 70s. The longest painless period still stands at 90 weeks and ended in September 1959. Since the early 70s we have seen only two such 40+ week periods, in 1994 and 1996. And now we are in the third one. The table also shows you what happens after such a 40+ week period comes to end (obviously when the S&P has a >2% down week again). I have calculated the market returns in the subsequent 4 weeks, 12 weeks, 24 weeks, 52 weeks and you can see the results in the right side columns. Contrary to what most traders might expect, that first >2% down week after a long painless period is usually not the beginning of a bigger crash. Far more often than not the market does very well in the next 4 to 12 weeks. The average gain 4 weeks after that first >2% weekly decline is 2.6% and the average gain after 12 weeks is 3.3%. Both are higher than the average 0.65% and 1.95% gains we have historically seen over 4 and 12 week periods.
Looking at 24 weeks we have an average 3.2% gain (versus 3.95% in all periods), so 6 months after that first >2% weekly drop we see an underperformance for the first time. And after 52 weeks we see an average 10% gain (versus 8.7% normally). This is better than average , but this comes on the back of two large gains in 1954-5 and 1996, when there was an annual gain of 30% and 26% respectively. The other 6 painless periods produced weak or average 1 year performance after they ended. But none of those periods ended with a serious crash in the next 12 months. That doesn’t mean it cannot happen of course. But based on those historic examples, the next >2% down week will not be a reason to panic but rather a short term buying opportunity. And that’s why we shouldn’t worry too much about this low VIX yet.

Going back to the ATR% charts I showed earlier on, we can also look how this indicator did on earlier occasions when it was unusually low. Here is the S&P 500 daily ATR% on its all time low in January 1994:

sp_atr_d2

Even though the market did get a 10% correction soon after the record low ATR% on Jan 21st, it climbed to news first in early February on a higher ATR%. And that brief 10% correction gave way to a massive multi-year advance, so that ultra-low volatility (ATR%) was only a short term selling opportunity here.

In early 2007 the daily ATR% again reached ultra-low levels. This is what happened next:

sp_atr_d3

The ATR% was very low for months, reaching a low of 0.68 in February. There was a brief pullback, but a significant bear market was still months away and there were two strong rallies before the big decline started.

The same thing was observed near the 2015 highs. The daily ATR% bottomed in summer 2014, but markets kept climbing until May 2015 before a real correction started (see first chart of this post)

Looking at the weekly ATR% in 2006-2007 we see something similar:

sp_atr_w2

Low ATR% values were reached in early 2006, but that only led to a minor pullback a few months later. Even lower weekly ATR% was seen in Feb 2007 (low of 1.74), but the market would go on to climb to higher peaks without setting new lows in ATR%. The eventual decline started more than 6 months after the ATR% low.

Bottom line: what we see is that bear markets usually do not start from record low volatility levels. The common pattern in major market advances is that a period of very low volatility gives way to higher volatility while the markets keep setting new highs. Some market participants get more nervous in the final stages and that shows as a higher ATR% in the final weeks/months of a long bull market. The real decline usually starts when a long term trendline gives way, as you can see in some of the charts.

PS: If you want to try the ATR% indicator on others indexes or stocks then you can use my script on TradingView: https://www.tradingview.com/script/GXlziRv4-ATR/. It’s also an easy way to see how the ATR% evolves after the posting of this article.

By Dan

Stock trader since 1986. Method based on proprietary indicators, seasonal patterns and moon cycles.

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