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Technical Analysis

Resistance and Support - All About Volatility

Some measurement of market volatility is part of more technical studies and trading systems than most readers might expect. Practically all of Wilder’s techniques (RSI, DMI, CSI, Parabolics, and other studies) incorporate the concept of volatility in some fashion.

Volatility is also part of various trading band or envelope studies available (Bollinger Bands, for example), and volatility is even a key ingredient of point and figure analysis.

Not surprisingly, volatility is also the basis for a series of trading systems that have been sold by various vendors since the early 1970’s for prices ranging up to as much as $10,000. All of these systems were volatility based, and all used essentially the same methods.

Most were derived from similar earlier systems, with minor changes that in many cases seem to have been added only to avoid possible copyright infringement. Many of these volatility based systems have been very profitable.

The Basics - Measuring Volatility

The volatility-based trading systems all use the concept of range to define the extent of recent market movement. The simplest definition of range is the distance from high to low of any given time. This is usually a day, but it could be a week, a month, or even an intraday period measured in minutes.

This simple definition of range works fine most of the time, but it doesn’t take into account days of extreme price movement. Limit days, for example, may have a very narrow range, but the market is obviously very volatile and volatility is increasing.

Similarly, a day when there is a gap opening and the day’s trading takes place outside the prior day’s range is an example of increasing volatility, even if the actual range of the day is less than that of the prior day.

Welles Wilder recognized this problem and defined the True Range (TR) as the greatest of the following: The distance from today’s high to today’s low. - The distance from yesterday’s close to today’s high. - The distance from yesterday’s close to today’s low.

By itself, the True Trading Range is still just an isolated number. To make it meaningful, we must take a number of past days and find the mean, giving us an Average True Range (ATR). This is a direct measurement of market volatility. If the ATR is increasing, the market is becoming more volatile. If the ATR is decreasing, the market is becoming less volatile.

How many days to use to produce the “best” ATR is a matter of conjecture. Welles Wilder’s original volatility formula (explained later) uses 14-days, but most of the modern system sellers have optimized this variable and found that anywhere from 2 to 9-days was better. The most profitable (as measured by Futures Truth) of these systems, the Volatility Breakout System, normally uses only 2-days.

How the Volatility Systems Work

All of the popular volatility-based trading systems work on the principle that a breakout or price spike outside of the recent Range or Average True Range is significant and should be used as a point at which to enter the market.

For example, let us say that the ATR for the last 5-days in the NYSE Composite futures is 1.00 points. We’d be interested in a price move that is a percentage, say 150%, of the ATR from the prior day’s close. This means we would be buying or selling if prices moved 150% x 1.00, or 1.50 points. If the prior day’s close was 190.00, we would buy at 191.50 or sell short at 188.50.

The two variables of the system are:

1. The number of days used to find ATR
2. The percent move from the prior day’s close that constitutes a valid breakout.

Most of the system vendors and presently available software rely on optimization to decide which values to be used for each variable.

As you may have deduced, the basic volatility breakout system is a reversal system that is always in the market. Each day after the close, calculate the ATR, and then multiply it by the percent move necessary to trigger a trade.

Add the result to the close, and you will get the point at which a buy will be triggered the next day. Subtract result from the close, and you’ll get the point at which a sell will be triggered. Enter both orders the next day and you are in business.

Comments and Variations

One of the significant strategies of the basic system is that since you are either long or short, there is no neutral area. The risk on any one trade is simply the difference between the entry point and the reversal point. If they are both triggered on the same day or very close in time to one another, a whipsaw is the obvious result. Perhaps more importantly, the risk on a trade depends entirely on recent market volatility, which may or may not agree with a trader’s wallet size or money management techniques.

Another interesting aspect of volatility systems is that the entry point and the reversal point will move away from each other if short-term volatility increases. It is easy to see how this could happen: the market moves, the range increases, and the stops are positioned farther and farther away from each other.

This might tend to reduce whipsaws, but it can also increase the initial risk on a trade after the trade is entered. It can be disconcerting, and potentially disruptive to a strict money management scheme, planning to risk a certain dollar amount on a trade and then have the amount increase once the trade is underway.

It is also possible a reversal point could be delayed almost indefinitely. For instance, let’s assume that T-Bonds are at 100.00, the system is long, and the reversal percentage is 150% of the 2-day ATR. If the ATR remains the same, the move necessary to trigger a short will also remain the same. If T-Bonds move slowly downward every day with a daily range large enough to keep the ATR the same but the short is not triggered, theoretically the reversal point may never be hit. It will just keep moving away. This is obviously a rare occurrence, but it is possible and a sequence of this type could result in large losses (and in fact, at least in test sequences, it has).

What’s Wrong With Volatility-Based Systems? We think the volatility-based trading systems are good over the short run, but limited over the long run. Their trading results often show real promise in spurts, but they also tend to give back their gains over time and in the long run may be no better than a break-even system.

There are several areas of concern for us. First, all of the system vendors have optimized extensively to find the “best” values for the major system variables, Average True Range and the percentage move needed to trigger a trade.

Apparently, they assumed that once the magic (optimized) numbers were found the system would be profitable forever. Any variations among volatility-based systems appear to be minor and concentrate on only these two variables.

For example, the definition of the average true range might be changed slightly, or a simple daily range might be substituted. Or, one vendor might elect calculating percentage move from the following day’s open, rather than the prior day’s close, in order to factor large overnight gaps into the system and reduce whipsaws.

These minor variations haven’t prevented large drawdowns in the system’s trading results. In our opinion, the drawdown problems seem to be the result of two factors: over optimization, and the perhaps invalid assumption that volatility works equally as well as an exit trigger as it does as an entry trigger.

Most of our subscribers are aware of our feelings about optimization and reversal systems. We believe that optimization is purely hindsight curve-fitting, giving only the illusion of potential profitability.

Back-testing and subsequent forward testing, followed by real-time tracking, is perhaps a worthwhile and valuable exercise, but let’s face it, if simple optimization really worked, by now a few die-hard computer addicts would have cornered or busted all the markets.

Suggestions on Making It Work - Filters

Despite the problems we believe to be inherent in a volatility-based approach, we still feel that these systems have the potential to be workable. There is no question that they should always be in the right direction when a market is trending with enough volatility to be worth trading at all. The real difficulty, common to most trend-following approaches, is whipsaws when the markets have no trend and low volatility. Over a long period, markets will be alternately stagnant and dynamic with most of the time spent in the stagnant mode. Similar to moving average systems, a volatility system set up for a trending market will not work well in the sideways periods.

Obviously, a filter is needed. We can suggest several. First, it is possible to cut down the considerable initial risk on each trade by creating a neutral zone between long and short entry points. The simplest way to do this is to set a percentage risk stop that is smaller than the percentage of the ATR that triggers the entry. For instance, in our earlier example we had an ATR of 100-points in the NYSE Composite, and we would buy on a move upward of 150% of this, or 150-points. A tighter stop could be set by subtracting a smaller percentage of the ATR from the entry point. We are afraid that anything less than 100% of the ATR might be classified as too close and subject to almost random whipsaws, but using a number like 125% still gives a tighter stop level than our reversal point. If the risk stop is triggered, the system is now neutral until the sell reversal at 150% is hit, or until a new buy, entry is reached.

Another possible improvement might be to avoid trades when a market is acting poorly, especially when the volatility is unusually low. There may well be “windows” of optimum profitability for the ATR of each commodity where it is within acceptable boundaries, neither too high nor too low. (See sample table below.) It is safe to assume that a stagnant market with a relatively small range will result in losing trades, while a more volatile market will tend to be more profitable. The usual impulse is to reutilize when the markets become stagnant, but it might be more profitable in the long run to sit out completely during the quiet markets and wait until the ATR becomes more in line with what your system normally needs to be successful.

A third possibility is to add an external filter, something that identifies conditions that must be met before a breakout is taken. There are at least two possibilities for this among readily available technical studies: DMI/ADX and CCI. We often mention that an upturn in Wilder’s ADX signals a market is trending. Try trading volatility breakouts only when the 18-day ADX is rising.

Similarly, a 20-period CCI based on either monthly or weekly signals will also tell you to what extent a market is trending over the longer term. Look for rapid acceleration of the CCI from its null or zero line; if this condition exists, the market is probably moving rapidly enough to make volatility based trading highly profitable.

Reprinted w/permission of Technical Traders Bulletin