Five Specific Ways To Anticipate Powerful Moves Using Volatility
Part 3 of a three-part series. Click here for
Part 1 and
Part 2.
Understanding concepts is one thing. Putting them into action in the markets is another. Because volatility is often described in highly technical terms, many traders are intimidated by this aspect of trading and fail to translate concept into a practical trading edge.
Here, will attempt to rectify that situation with a number of clear examples that show how you can take advantage of volatility characteristics in the markets. In “Introduction to Volatility” we defined volatility and looked at its characteristics, such as its cyclical nature, its persistency and its tendency to revert to the mean. We used a simple calculation called average true range to illustrate these inherent features of volatility.
In “Historical Volatility“, we looked at historical volatility (HV), a more mathematically complex (but also more useful) way of measuring volatility. We showed how you can use it to find (or avoid) volatile stocks, to determine risk, set practical stops and make market forecasts.
In our final installment of this article series, we will take a deeper look at historical volatility and expand on concepts from the first two installments
(click here for
Part 1 and
Part 2). We’ll show how you can combine various time frames to help find markets that are likely to explode, as well as markets that may have exhausted themselves. Finally, we’ll tie it all together and show specific patterns you can use in the markets.
Short-term HV readings vs. long-term HV readings
As we discussed in Part II, historical volatility (HV) is a useful way to gauge market volatility. A length (look-back period) of 50 to 100 days provides a good longer-term reference for expected volatility.
However, shorter time frames are also useful. For instance, Larry Connors1 has shown that 6 and 10 day periods are useful for determining where a market is in the volatility cycle. Volatility’s inherent reversion to the mean feature can then be used to determine if a market is likely to explode or if a move from a low-volatility situation may have exhausted itself (i.e., if volatility is likely to implode).
Reversion to the mean: market explosions
As we joked in part one, a “mean†person who’s nice for a few days will likely revert back to being mean. By the same token, a market with lower-than-normal volatility will likely revert back to the mean (more normal levels) through an increase in volatility.
Let’s break it down. In part one, we showed that extreme low volatility was usually followed by an increase in volatility, as volatility reverted back to the mean (average), or more normal levels.
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| Figure 1. Amgen (AMGN), daily. Source: Omega Research.
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Figure 1 shows that on 7/02/99, AMGN had a 6-day HV reading of 24% (a), which is less than half of the longer-term 100-day HV reading of 54% (b). Over the next few days, AMGN exploded (c) as volatility reverted back to the mean, that is, to more normal volatility levels (d).
Volatility ratios
To compare short-term and long-term volatility divide the short-term volatility reading by the long-term reading. This serves several purposes: First, it gives you the percentage of where the shorter-term volatility is compared to longer-term. For example, if the 6-day volatility divided by the 100-day volatility (6/100 HV) is 50% or lower, you know the short-term volatility is less than half (representing exceptionally low volatility) of the longer-term and the market has the potential to explode.
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| Figure 2. Amgen (AMGN), daily. Source: Omega Research.
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Second, you only have to look at one indicator, making analysis much simpler. Finally, it provides a clearer picture of the volatility cycle. In Figure 2, notice we plotted a ratio of the same indicators in Figure 1 simply by dividing the short-term (6-day HV) reading by the longer-term (100-day reading). Now, instead of having to read two indicators, you only have to look at one to determine if a low-volatility situation exists.
On 7/02/99, the 6/100 HV ratio was .46 (a). This means the shorter-term volatility is less than half of its longer-term counterpart (referring back to chart 1, the five-day reading was 24% divided by the 100 day reading of 54% = .46). Also, notice the move from a low-volatility situation is more pronounced (b) when using a ratio. This is how we calculate the Volatility Explosion indicators for stocks and futures on the site: dividing the 6-day (and also the 10-day for futures) by the 100-day readings.
Sleeping Tigers
As we explained in the Part II, markets with a high longer-term (50- to 100-day) volatility readings have the potential to make large moves. Therefore, when these markets have an extremely low shorter-term reading, the following move can be quite large.
I have dubbed these markets “Sleeping Tigers†(I thought this had a better ring to it than “Sleeping Mean Guysâ€). This is where the most volatile markets (i.e., those on the “Trading Where The Action Is” list or ranked high on the “Futures Volatility Ranking” list) exhibit lower-than-normal shorter-term readings (i.e., the market is also on the “Volatility Explosion” lists). The theory is that there is potential for a large move (in either direction) as the “tiger†(very volatile long-term) wakes up (from a short-term low volatility or “sleeping†condition).
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| Figure 3. National Discount Brokers (NDB). Source: Omega Research
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For example, in Figure 3, notice that on 6/28/99 NDB has an extremely high 100-day HV reading (b). This suggests that this stock is a “tiger†capable of making a large move. Also notice the short-term volatility (the 6-day HV reading) is only 36%, much less than the longer-term reading of 167%. The market is “sleeping,†if you will. Over the next few days, NDB explodes and nearly doubles in price (c) as volatility reverts back to its mean (d).
Determining the direction of volatility explosions
We’ve shown that markets with very low shorter-term HV readings compared to longer-term HV readings have the potential to explode. Although we have shown examples to the upside, these markets could have just as easily gone down.
So the next question is, what direction will the market go as volatility reverts (explodes) to its mean? It always helps to add in other technical indicators when trying to solve the puzzle. For instance, if a market is in a strong downtrend and has a low short-term vs. long-term HV reading, it is likely the market would explode to the downside.
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| Figure 4. September T-bond futures, daily. Source: Omega Research.
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In Figure 4, on 5/25/99, a low-volatility situation coincides with a pullback from a downtrend (a). The market then drops over 2 points over the next four days. Notice on 6/9/99 (c) the volatility once again drops below half of the longer-term reading while the market continues to be in a downtrend (b). The market then drops over 1 1/2 points over the next two days as volatility reverts back to its mean.
Of course, it doesn’t always set up this perfectly, but it often helps to combine the bigger technical picture when trying to determine the direction of the move out of a low-volatility situation.
Volatility implosion
Volatility tends to decrease until it reaches an extremely low level and then tends to explode and return to more normal levels. By the same token, once it reaches an extreme, it tends to “implode†(decrease rapidly) to more normal levels and prices tend to settle down and go sideways. As a result, it’s often a good point to take profits when volatility reaches an extreme, if you were lucky enough to catch the move from the low-volatility situation.
In Figure 5, let’s look at something that ties it back into Figures 1 and 2. Notice that after Amgen exploded from low levels (a), volatility peaked (b) and the stock then traded sideways (c) as volatility imploded, or decreased, to more normal levels (d).
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| Figure 5. Amgen (AMGN), daily. Source: Omega Research.
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In addition to being a good point to exit trades that were initiated under low-volatility situations2, volatility peaks are useful tools for option traders. For instance, Fernando Diz has shown that once volatility begins to decrease from an extremely high level, it tends to continue moving lower.3 This may provide opportunities for those long options to exit positions and for option sellers to capture a large premium (caused by high volatility) as volatility drops and option premiums drop along with it.
One word of caution: As I discussed in Parts I and II, trading options, especially on the sell side, requires specialized skills. Make sure you fully understand the risk before attempting to apply this or any other theory in real markets.
Summary
Once you cut through the math to understand the principles underlying market volatility, it’s much easier to understand how to apply this aspect of price behavior in your trading. There’s a great deal of common sense involved. We’ve shown how more volatile markets offer more opportunity (especially for the short-term trader) at the cost of higher risk. We used average true range and historical volatility to show that volatility is cyclical, persistent and tends to revert to the mean.
Persistency means that if a market is volatile (or volatility is increasing) it will likely continue to be volatile (or volatility will continue to increase). Reversion to the mean suggests that extremely low short-term volatility readings compared to longer-term (normal) volatility readings will revert back to more normal or long-term readings.
Markets that have extremely low short-term volatility readings compared to their longer-term readings have a high likelihood of exploding (i.e., making a large move) as volatility reverts to the mean (higher levels). Conversely, markets that have a extremely high shorter-term volatility readings are prone to quieter trading as volatility implodes (reverts to more normal readings).
These inherent features can be used to help capture explosive moves in markets, gauge when the move may be over, and to trade options. Although these concepts can be a little overwhelming at first, the bottom line is that if you understand the cyclical nature of volatility and where you are in the volatility cycle, you’ll have a better grasp on a market’s potential.
Footnotes and additional reading:
- Investment Secrets Of a Hedge Fund Manager, Connors and Hayward
- “A Volatility Trade in Gold,” David Landry, Technical Analysis of Stocks and Commodities, July 1998 issue.
- Trading Connors’ VIX Reversals, Larry Connors.
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