Elliott and Gann have become household names among the worldwide trading community. These pioneers of technical analysis developed some of the most widely used techniques in the field. But how did Ralph Nelson Elliott and W.D. Gann come up with these techniques, and how did they become so successful? Truth be told, it’s not as difficult as it sounds! This article takes you through the process of building your own custom indicator, which you can use to gain an edge over the competition.

Background

Recall that the theory behind technical analysis states that financial charts take all things into account—that is, all fundamental and environmental factors. The theory goes on to state that these charts display elements of psychology that can be interpreted via technical indicators.

To better understand this, let’s look at an example. Fibonacci retracements are derived from a mathematical sequence: 1, 1, 2, 3, 5, 8, 13 and so on. We can see that the current number is the sum of the previous two numbers. What does this have to do with the markets? Well, it turns out that these retracement levels (33%, 50%, 66%) influence traders’ decisions to such an extent that the levels have become a set of psychological support and resistance levels. The idea is that, by finding these points on charts, one can predict the future directions of price movements.

Components of an Indicator

All indicators are created to predict where a price is headed when a certain condition is present. Traders try to predict two basic things:

• Support and resistance levels: These are important because they are the areas at which prices reverse direction.
• Time: This is important because you need to be able to predict when price movements will occur.

Occasionally, indicators predict these two factors directly—as is the case with Bollinger Bands or Elliott’s waves—but indicators commonly have a set of rules enacted in order to issue a prediction.

For example, when using the breadth thrust indicator (which is represented by a line indicating momentum levels), we need to know which levels are relevant. The indicator itself is simply a line. The breadth thrust indicator looks similar to RSI, in that it is “range-bound,” and it is used to gauge the momentum of price movements. When the line is in the median zone, there is little momentum. When it rises into the upper zone, we know that there is increased momentum and vice versa. One could look to take a long position when the momentum is on the rise from low levels and look to short after the momentum peaks at a high level. It is important to set rules to interpret the meaning of an indicator’s movements in order to make them useful.

With this in mind, let’s look at ways of creating predictions. There are two main types of indicators: unique indicators and hybrid indicators. Unique indicators can be developed only with core elements of chart analysis, while hybrid indicators can use a combination of core elements and existing indicators.

Components of Unique Indicators

Unique indicators are based on inherent aspects of charts and mathematical functions. Here are two of the most common components:

1. Patterns

Patterns are simply repeating price sequences apparent over the course of a given time period. Many indicators use patterns to represent probable future price movements. For example, Elliott Wave theory is based on the premise that all prices move in a certain pattern that is simplified in the following example:

There are many other simple patterns that traders use to identify areas of price movement within cycles. Some of these include triangles, wedges, and rectangles.

These types of patterns can be identified within charts simply by looking at them; however, computers offer a much faster way to accomplish this task. Computer applications and services provide the ability to locate automatically such patterns.

2. Mathematical Functions

Mathematical functions can range from price averaging to more complex functions based on volume and other measures. For example, Bollinger Bands are simply fixed percentages above and below a moving average. This mathematical function gives a clear price channel showing support and resistance levels.

Components of Hybrid Indicators

Hybrid indicators use a combination of existing indicators and can be thought of as simplistic trading systems. There are countless ways in which elements can be combined to form valid indicators. Here’s an example of the MA crossover:

This hybrid indicator utilizes several different indicators including three instances of the moving averages. One must first draw the three-, seven- and 20-day moving averages based on the price history. The rule then looks for a crossover in order to buy the security or a cross-under in order to sell. This system indicates a level at which price movement can be expected and provides a reasonable way to estimate when this will occur (as the lines draw closer together). Here’s what it might look like:

Creating an Indicator

A trader can create an indicator by following several simple steps:

1. Determine the type of indicator you wish to build: unique or hybrid.
2. Determine the components to be included in your indicator.
3. Create a set of rules (if necessary) to govern when and where price movements should be expected to occur.
4. Test your indicator in the real market through backtesting or paper trading.
5. If it produces good returns, put it into use.

An Example

Suppose we want to create an indicator that measures one of the most basic elements of the markets: price swings. The goal of our indicator is to predict future price movements based on this swing pattern.

Step 1:

We look to develop a unique indicator using two core elements, a pattern and math functions.

Step 2:

Looking at weekly charts of company XYZ’s stock, we notice some basic swings between bullishness and bearishness that each last about five days. As our indicator is to measure price swings, we should be interested in patterns to define the swing and a mathematical function, price averages, to define the scope of these swings.

Step 3:

Now we need to define the rules that govern these elements. The patterns are the easiest to define: they are simply bullish and bearish patterns that alternate every five or so days. To create an average, we take a sample of the duration of upward trends and a sample of the duration of downward trends. Our end result should be an expected time period for these moves to occur. To define the scope of the swings, we use a relatively high and a relative low, and we set these at the high and low of the weekly chart. Next, to create a projection of the current incline/decline based on past inclines/declines, we simply average the total inclines/declines and predict the same measured moves (+/-) occur in the future. The direction and duration of the move, again, is determined by the pattern.

Step 4:

We take this strategy and test it manually, or use software to plot it and create signals. We find that it can successfully return 5% per swing (every five days).

Step 5:

Finally, we go live with this concept and trade with real money.

Bottom Line

Building your own indicator involves taking a deeper look into technical analysis and then developing these basic components into something unique. Ultimately, the aim is to gain an edge over other traders. Just look at Ralph Nelson Elliott or W. D. Gann. Their successful indicators gave them not only a trading edge but also popularity and notoriety within financial circles worldwide.

Traders and analysts rely on a variety of different indicators to track volatility and to determine optimal exit or entry points for trades. While high volatility is often a deterrent for a risky trade, increased fear during extreme market moves can also create buying opportunities and provide an exceptional trading ground for experienced investors.

On the other hand, periods of low volatility—accompanied by investor complacency—can warn of frothy market conditions and potential market tops. Some of the most commonly used tools to gauge relative levels of volatility are the Cboe Volatility Index (VIX), the average true range (ATR), and Bollinger Bands®.

Cboe Volatility Index

The Cboe Volatility Index is one of the most widely watched gauges of market volatility. Updated throughout the trading day and known by its ticker symbol, VIX, the index is computed using an option-pricing model and reflects the current implied or expected volatility that is priced into a strip of short-term S&P 500 Index options.

Because large institutions account for a large portion of trading in S&P Index options, their volatility perceptions (as measured by VIX) are used by other traders to help get a reading of likely market volatility in the days ahead.

The Cboe Volatility Index stays between 12 and 35 the majority of the time, but it has also dropped into the single digits and has rallied to more than 75. Generally, VIX values higher than 30 indicate increased volatility, while values in the low teens are indicative of low volatility.

Derivatives, such as futures and options, on VIX are actively traded. In addition, leveraged exchange-traded funds based on the volatility index—like the ProShares Ultra VIX Short-Term Futures ETF (UVXY) and its partner ProShares Short VIX Short-Term Futures ETF (SVXY)—exist as well.

Average True Range

While VIX measures S&P 500 volatility, the average true range indicator, developed by J. Welles Wilder Jr., is a technical chart indicator that can be applied to any stock, exchange-traded fund, forex pair, commodity, or futures contract. ATR calculates what Wilder called “true range” and then creates the ATR as a 14-day exponential moving average (EMA) of the true range. The true range is found by using the highest value generated by one of three equations:

True range = Current day’s high minus the current day’s low
True range = Current day’s high minus the previous day’s close
True range = Previous day’s close minus the current day’s low

The ATR is then created as an EMA (computed using the highest value found when the three equations are solved). A larger ATR indicates higher trading ranges and thus increased volatility. Low readings from the ATR are generally consistent with periods of quiet or uneventful trading.

Bollinger Bands®

Bollinger Bands® is another charter indicator and consists of two lines or bands, which are two standard deviations above and below the 20-day moving average, which appears as a line in between the two bands. Widening of the bands shows increased volatility, and narrowing of the bands shows decreased volatility. Like ATR, Bollinger Bands® can be applied to any stock or commodities chart.

The Bottom Line

Market volatility goes through cycles of highs and lows. Analysts watch the direction of market movement when there is a sharp increase in volatility as a possible indication of a future market trend. While VIX is useful in seeing overall levels of volatility of the S&P 500 Index, ATR and Bollinger Bands® can be applied to stocks, commodities, forex, indexes, or futures using any number of charting applications.