Does The World Really End Eight Times A Year?

by | Jun 21, 2016 | All Articles, Technical Analysis

What Is The Crowd Seeing?

In the last blog, we measured bearish sentiment with the Short Interest Ratio. Another way this can be done is by using volatility indexes.

Today the four main US Equity Volatility Indexes were testing their 21-day highs. Translation: the premiums to insure the S&P 500 ($SPY), the Russell 2000 ($IWM), the NASDAQ 100 ($QQQ) and the Dow ($DIA) have been driven to the highest they’ve been in a month. Below shows the four volatility indexes with their 21-day highs as an orange line.

(Above: Clockwise from top-left, the Volatility Indexes $VIX (S&P500), $VXN (NASDAQ 100), $RVX (Russell 2000), and $VXD (Dow).)

It’s important to note that these indexes are “implied” volatility—measuring the general perception of the level of volatility to come. That’s why it’s nicknamed ‘The Fear Index’. So… is it time to panic with the crowd or to have steely Warren Buffet nerves and look for bargains?

Pattern Of Crazy?

Let’s look at one of these in more detail. In addition to the 1-month high line (orange) there are now blue arrows showing when volatility has crossed above this line for the $VIX.

There seems to be a pattern of volatility rising quickly from a low, peaking sharply, then falling. In fact, from first blush, when the 1-month high water mark is crossed it appears the volatility explosion has likely run its course (two notable exceptions being October 2014 and August 2015).

Let’s see how accurate our hunch is, and what else we can learn. The chart below shows average performance in percentages, 21 days before and 42 days after the 1-month high volatility readings. The $SPY performance is in orange and the $VIX in green.

We Are All Well Protected From What Just Happened

Notice the inverse relationship between the $SPY and the $VIX? The more $SPY prices fall, before time 0, the demand for insurance rises ($VIX). As prices begin rising again after time 0, this demand falls.

Since 1990, these volatility events happened 212 times. Roughly eight times per year. Does the market really crash eight times per year? Hmmm…

The $VIX and $SPY averages are showing that this has led to two things historically: fear is quickly forgotten and the market moves higher. Hmmm again.

Getting Some Perspective

VIX 21 Day High 42 Day Stats

So how much lower does volatility go? Two months later, it’s lower 70% of the time: either 6% (mean) or 13% (median), depending on what type of average you use.

What about market returns? The $SPY is higher 62% of the time.

These imply a near-term bottom is more likely, rather than worsening conditions.

We can also take a look further out at 1 year and see if these trends continue.

Sure enough, with volatility down more than 72% of the time and $SPY price up almost 80%, this tendency of higher prices and lower volatility is consistent.

Measured panic is down more than 10% 1 year later. While the $SPY rallied on average more than 10%, well over the average long-term rise line of 7%.

VIX 21 Day High 252 Day Stats

When Things Go Wrong

The numbers above are compelling and it’s good to make data-informed decisions. However, we can be more informed!

Let’s try to understand what it looks like when the market doesn’t cooperate—the odds don’t play out and the vomit comet isn’t letting anyone off. We need to put context behind the numbers and not just blindly follow them.

The distribution chart below helps us visualize this concept. It takes all of the one-year volatility readings (i.e. the percent change of the $VIX one year after each of the 212 new 21-day highs), and shows where they landed (x-axis) and at what percentage of the time (y-axis).

VIX Distribution 252 Days

What is this telling me? Out of the 212 observations, there were five times where volatility was near or above 100% higher one year later. In other words, a year after each 21-day breakout, volatility had doubled 2.5% of the time since the inception of the $VIX.

Those are extremely high—and quite rare—readings. By contrast, the area shaded dark green is the bulk of what occurred and is more likely to be seen anywhere between down 33.5% and up 12.5% (the 20th and 80th percentiles).

Great! So we know that the majority of the time volatility subsides, but it can climb higher. What do $SPY returns look like following these extreme readings?

High Volatility = Always Bad?

Here’s what it looks like when volatility doesn’t halt. The top 20 culprits with the highest 1-year $VIX increases after the signal are shown with their $SPY returns.

Be aware, this is future information. We didn’t know which ones would turn into whoppers.

Is anything surprising? Half of the time market returns were either up or down single-digits. Markets can go up with high and rising volatility! Fear doesn’t always translate into market declines. This is really counterintuitive.

The other half of the time this scenario turned out to be the precipice. If you look at the years having large negative returns, many were during or right before the major bear markets such as 2000-2002 and 2007-2008. It makes sense that volatility would keep rising as a bear market unfolds. The lesson? One must always manage risk.

In summary, the data suggests the following: markets are going to panic, and often (as we’ve seen, on average eight times per year). At times, it may seem like the end of the world. Rather, it’s likely a knee-jerk reaction that may lead to a correction and possibly opportunity. However, every once in awhile, when confidence cannot regain footing it can become a bear.

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Carson Dahlberg, CMT

Carson Dahlberg, CMT

Author & Co-founder of Northington Dahlberg Research

Carson comes to Optuma bringing nearly 20 years of experience in the financial markets involved in technical and quantitative trading, research and education. Carson has worked for several notable firms: Morgan Stanley, Wachovia Securities, Wells Fargo, and Schaeffer’s Investment Research. In addition, he is the co-founder of Northington Dahlberg Research, a quantitative driven, volatility-based research firm, and was the Director of the CMTinstitute (an online program to assist financial professionals in the passing of the CMT examination process).

Carson is presently a Director at Large on the Board of the Market Technicians Association and serves the Market Technicians Association (MTA) in various capacities. He was the founder and first Chapter Chair of the Charlotte Chapter for the MTA. His involvement with being the Committee Chair for the Ethics Committee has led to an updated and globally relevant ethics offering for the designation. In the past, he has served on the Admissions Committee, was the Board Liaison for the Journal of Technical Analysis Committee, and was the Director of the CMTinstitute.

Carson received a degree in Chemistry from the University of Cincinnati and was awarded the Chartered Market Technician designation in January of 2008.

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