What is the VIX Suggesting about Investor Complacency and Future Volatility?

The CBOE Volatility Index® (VIX® Index®) is a key measure of market expectations of near-term volatility conveyed by S&P 500 stock index option prices. Since its introduction in 1993, theVIX® Index has been considered by many to be the world’s premier barometer of investor sentiment and market volatility.

The VIX® historically trends between a long-term range. An extreme level of the VIX® will likely reverse … eventually. The chart below we show the price level of the VIX® since its inception in 1993. We can visually observe its long-term average is around 20, but (I highlighted in red) its low range is around 12 and it has historically spiked as high as 25 or 60.

VIX Since its introduction in 1993, the VIX Index has been considered by many to be the world's premier barometer of investor sentiment and market volatility

The CBOE Volatility Index®  is an index that cannot be invested in directly, however, there are futures, options, and ETN’s that attempt to track it. Its level is commonly used as a gauge of investor sentiment. An extremely high level of the VIX® means that options traders are paying high premiums for options because they are fearful of future volatility and maybe lower stock prices. Options traders and investors are buying options to hedge their portfolios and their demand drives up the “insurance premium”.

Just the opposite is the driver of an extremely low level of the VIX® like we see today. It means that options traders are paying low premiums for options because they are not so fearful of future volatility and lower stock prices. They are unlikely buying options for hedging and their low demand drives down the “insurance premium”. We could also say “investors are complacent” since they aren’t expecting future volatility to increase or be higher.

These levels of complacency often precede falling stock markets and then rising volatility. When stock prices fall, volatility spikes up as investors suddenly react to their losses in value. Or, in the short term volatility could trend even lower and reach an even more extreme low level for a while. But the VIX® isn’t an index that trends for many years in one direction. Instead, as we see in the above chart, the VIX® oscillates between a low and high range so can expect it to eventually trend the other way.

We shouldn’t be surprised to see at least some short-term trend reversals; maybe stocks trend down and the VIX® trends up…

We’ll see…

There is much more to the VIX® , such as it’s term structure, but the scope of this article is to point out its extreme low level could be an indication of future change.

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The VIX, as I see it…

The CBOE Volatility Index (VIX) reached a low point last week not seen since 2007 as evidenced by the chart below.


To see a closer view of the last period, below I included the last time the VIX was at such a low value. I show this to point out that the VIX oscillated between 9% and 12% for about 4 months before it finally spiked up to 20. Such a trend reversal (or mean reversion if you prefer) can take time. Imagine if the VIX stays this low for the next 4 months before a spike. Or, it could happen very soon. You may notice the VIX reached the level it is now at its lowest level in early 2007. If we believed these trends repeat perfectly, that absolute level would matter. Trends are more like snowflakes: no two are exactly the same. But in relative terms, the fact that today’s level is as low as the lowest point in early 2007 is meaningful if you care about the risk level in stocks and the stage of the market cycle.


The best way to examine a trend is to zoom in. Start with a broader view to see the big picture, then zoom in closer and closer. When people focus too much on the short-term, they miss the forest for the trees. Below is the last time the VIX was below 12. You may notice that is does oscillate up and down in a range.


The level and directional trend of the VIX matters because of the next chart. You may see a trend if you look closely. The black line is the S&P 500 stock index. The black and red line is the VIX CBOE Volatility Index. You may notice the two tend to drift in opposite directions. Not necessarily on a daily basis, but overall they are “negatively correlated”. When the stock index is rising, the volatility is often falling or already at a low level. When the stock index is falling, volatility rises sharply. It isn’t a perfect opposite, but it’s there.

VIX and S&P 500 correlation and trend

If you are interested in stock trends and the trend in volatility, and specifically the current state of those cycles,  you may want to follow along in the coming days. I plan to publish a series on this topic about the VIX, as I see it. Over the last week or so I have written several ideas that I intended to publish as one large piece. Since I haven’t had time to tie it together that way, I thought I would instead publish a series.

When a trend reaches an extreme level like this, it may be useful to spend some time with it.

Stay tuned…

if you haven’t already, you may want to click on “Follow” to the right to get updates by email to follow along. This will likely be several informal notes in the coming days.





Declining (Low) Volatility = Rising (High) Complacency

When we speak of trends, we want to recognize a trend can be rising or declining, high or low. These things are subjective, because there is infinite ways to define the direction of a trend, its magnitude, speed, and absolute level. So, we can apply quantitative analysis to determine what is going on with a trend.

Below we see a quote for the CBOE Market Volatility Index (VIX). The VIX is a measure of the 30 day implied volatility of S&P 500 index options. It is a measure of how much premium options traders are paying on the 500 stocks included in the S&P 500. So, it is a measure of implied or expected volatility based on how options are priced, rather than a measure of actual historical volatility based on a past range of prices. Without going into a more detailed discussion of the many factors of VIX, I’ll add that the VIX is a fine example of an index that is clearly mean reverting. That is, the VIX oscillates between high and low ranges. Once it gets to a high level or low-level, it eventually reverts to its average. Said another way, it’s an excellent example of an index we can apply countertrend systems instead of trend following systems, because the VIX swings up and down rather than trending up or down for years.

The VIX has a long-term average of about 20 since its inception. At this moment, it is 11.82. It’s important to realize the flaw of averages here, because the VIX doesn’t actually stay around 20 – it instead averages 20 as it swings higher and lower.

VIX CBOE Market Volatility below 12


I used the above image from CNNMoney because it shows the rate of change in the VIX over the past 5 years on the bottom of the chart. Notice that over the past 5 years (an arbitrary time frame) market volatility as measured by VIX has declined -63.78%. To get an even better visual of the decline and price action of the VIX, below is a chart of the volatility index going back to 2001.

Do you see a trend? Do you see high and low points?

VIX Long term average high and low

We observe the current level is low by historical measures. In fact, it’s about as low at it has been. The last time the volatility index was this low was 2006 – 2007. That was just before it spiked as high as it has been during the 2007 – 2009 market crash. You can probably see what I mean by “mean reversion” and “countertrend”. When the stock market is rising, volatility gets lower and lower as investors become more complacent. Most investors actually want to get more aggressive and buy more stocks after they have already risen a lot for years, rather than realizing the higher prices go the more risky they become. We love trends, but they don’t last forever. What I think we see above is an indication that investors have become complacent, option premiums are cheap, because options traders aren’t factoring in high volatility exceptions. However, we also see that the VIX is just now down below 12.5, and area the last bull market reached in 2006 and that low volatility stayed low for over a year before it reversed sharply. Therein lies the challenge with counterrend trading: we don’t know exactly when it will reverse and trends can continue longer than we expect. And, there are meaningful shorter term oscillations of 20% or more in the VIX.

I also want to point out how actual historical volatility looks. Recall that the VIX is an index of market volatility based on how options are priced, so it implies the expected volatility over the next 30 days. When we speak of historical volatility, there are different measures to quantify the historical range prices have traded. Volatility speaks of the range of prices, so a price that averaged 100 but trades as high as 110 and low as 105 is less volatile than if it trades from 130 and 70. Below I charted the price chart of the S&P 500 since 2002. The first chart below it is ATR, which is Average True Range. ATR considers the historical high and low prices to determine the true range. A common measure is the standard deviation of historical returns. Standard deviation is charted below as STDDEV below the ATR. Below Standard Deviation is the VIX.

VIX and S&P 500 historical market volatility

Notice that the measures of volatility, both historical and implied, increase when stock prices fall and decrease when stock prices rise. Asymmetric Volatility is the phenomenon that volatility is higher in declining markets than in rising markets. You can see why I say that volatility gets lower and lower as prices move higher and higher for several years. Then, observe what happens next. Right when investors are the most complacent, the trend changes. Prices fall, volatility spikes up. They feel more sure about things after prices have been rising, so there is less indecision reflected in the range of daily trading. When investors feel more uncertain, they become indecisive, so the range of prices spread out.

Based on these empirical observations, we conclude with the title of this article.

The VIX is an unmanaged index, not a security, so it cannot be invested in directly. We can gain exposure to the VIX through derivatives futures or options. This is not a recommendation to buy or sell VIX derivatives. To determine whether or not to take a long or short position in the VIX requires significantly more analysis than just making observations about its current level and direction. For example, we would consider the term structure and implied volatility vs. historical volatility and the risk/reward of any options combinations.




Investors are Complacent

Implied volatility, the amount of “insurance premium” implied by the price of options, continues to suggest that investors are becoming very complacent. When the VIX is high or rising, it says the market expects the S&P to move up or down more. When the VIX is low or declining, it says the market expects the S&P 500 will not move up or down as much in the future. That is, the “insurance premium” priced into options on the S&P 500 stocks is low. That isn’t necessarily directional – it is an indication of the expected range, not necessarily direction. However, what I know about directional price trends is that after a price has been trending directionally for some time, as the S&P 500 stock index has, investors become more and more complacent as they expect that trend to continue. The mind naturally wants to extrapolate the recent past into the future and it keeps doing it until it changes. When we see that in the stock market, it usually occurs as a directional trend is peaking. Investors are caught off guard as they expected a tight range. If the range in prices widens, they probably widen even more because they are – and it wasn’t expected. Interestingly, people actually expect inertia and that is one of the very reasons momentum persists as it does. Yet, momentum may eventually move prices to a point (up or down) that it may move too far and actually reverse the other way.


If we believe the market is right, we would believe the current level accurately reflects the correct expecation for volatility the next 30 days. That is, we would expect today’s implied volatility of about 12 – 13% will match the actual historical volatility 30 days from now. In other words, 30 days from now the historical (backward looking) volatility is match the current implied volatility of 12.6%. If we believe the current volatility implied by option premiums is inaccurate, then we have a position trade opportunity. For example, we may believe that volatility gets to extremes, high or low, and then reverses. That belief may be based on empirical observation and quantitatively studying the historical data to determine that volatility is mean reverting – it may oscillate in a range but also swing from between one extreme to another. If we believe that volatility may reach extremes and then reverse, we may believe the market’s implied volatility is inaccurate at times and aim to exploit it through counter-trend systems. For example, in my world, volatility may oscillate in a range much of the time much like other markets, except it doesn’t necessarily have a bias up or down like stocks. There are times when I want to be short volatility (earning premium from selling insurance) and long volatility (paying premium to buy insurance). I may even do both at the same time, but across different time frames.

The point is, the market’s expectation about the future may be right most of the time and accurately reflect today what will be later. But, what if it’s wrong? If we identify periods when it may be more likely wrong, such as become too complacent, then it sets up a position opportunity to take advantage of an eventual reversal.

Of course, if you believe the market is always priced accurately, then you would never take an option position at all. You would instead believe that options are priced right and if you believe they are, you believe there is no advantage in being long or short them. I believe the market may have it right most of the time, but at points it doesn’t, so convergence trades applying complex trade structures with options to exploit the positive asymmetry between the probability and payoff offers the potential for an edge with positive expectation.