Elliott Wave Theory takes its name from R. N. Elliott (1871-1948). The roots of Elliott Wave Theory can be traced to 1926-1927. During that time, Elliott contracted a serious illness, and while he was recovering, he took a serious interest in stock market behavior. It was these observations that formed the basis of the theory.

In 1934, Elliott went to work for Charles Collins, a publisher of one of the major stock market newsletters, where the outline of Wave Theory was first published. In 1940, he published a paper called “The Fibonacci Summation Series of Dynamic Symmetry, which began linking the two concepts, but the two were not fully integrated for another couple of years. Collectively, these became the Elliott Wave Theory we know today.

At the root, EWT is a series of empirical rules used to interpret the action of the major stock market averages. Elliott’s entire body of work focused on the Dow Jones Industrial Average. By studying the average over time, he began discovering patterns, then constructed a series of rules that captured the market’s behavior.

This is a crucial point. EWT is at its best and most successful when used to study and forecast behavior in large, highly liquid markets (i.e., the stock market). There’s a certain psychological underpinning here, which also makes EWT useful for predicting the behavior of any large group

of people. This is because psychological states in groups tend to unfold in distinct, predictable patterns. Stock market pricing is merely a consequence of those various psychological states.

It is somewhat less effective in smaller, relatively illiquid markets.

Given this, EWT practitioners have pushed the theory into two other areas of thought since Elliott’s death. These are: Chaos theory and Fractals.
The Oxford English Reference Dictionary (1995) defines Chaos Theory as:

…the mathematical study of complex systems whose development is highly sensitive to slight changes in conditions, so that small events can give rise to strikingly great consequences…Such behavior is in practice unpredictable beyond a short time scale. Chaos theory, which has applications in physics, biology, ecology, economics and other fields has two main aspects. On one hand, processes that seem random or irregular may actually follow discoverable laws. On the other hand, some processes that used to be thought predictable…have been shown to be chaotic in the long term.

Fractals are define by the Oxford English Reference Dictionary as:

…theoretically useful in describing partly random or chaotic natural phenomena…Non-uniform structures in which similar patterns recur at progressively smaller scales…can be realistically modelled using fractals…The concept was introduced (and the word coined) by the Polish-born mathematician Benoit B. Mandlebrot in 1975.

In a nutshell, Chaos Theory is the study of complex systems that, at first glance, appear to be utterly disorganized, but that, upon closer analysis, are revealed to be governed by a spooky sense of underlying order.

Given EWT’s success at predicting stock market price behavior and given that the stock market is definitely a complex system, it’s easy to connect the dots here.

Fractals are geometric shapes that repeat at every scale. If you look at a fractal image, you can see clearly defined patterns. If you zoom in, you find that the large-scale patterns are repeated on the smaller scale. No matter how far you zoom in (or out), you see exactly the same thing. The patterns recur infinitely, in both directions of scale.

In Elliott Wave Theory, we see this expressed by the fact that wave patterns repeat endlessly at any scale. As Elliott observed, the length of time for cycles at various scales varies, but the underlying structures of the patterns are consistent.

That’s why you can look at pricing data for a year (or even a century), and you’ll see the same wave patterns you find when looking at pricing data for a single day, or even a single hour. Those larger patterns are made up of smaller, identical patterns.


Regarding cycles, Elliott identified a total of nine cyclical degrees, with the largest cycles he could identify based on the body he had available (the entire history of stock market pricing), down to the smallest cycles he could identify (intraday pricing charts). In descending order, he named these cycles as follows and even smaller and larger degrees have been added to make twelve cycles or fractals:

• Grand Sypercycle
• Supercycle
• Cycle
• Primary
• Intermediate
• Minor
• Minute
• Minuette
• SubMinuette
• Micro
• Submicro
• Miniscule

Labelling Convention

With the above in mind, EWT holds that each cycle (of whatever size) unfolds as a series of waves. Up-cycles consisting of five waves, and down trends consisting of a cycle of three waves, for a total of eight waves to complete the cycle.

The waves within each cycle may break into a sequence of smaller waves. When and where this happens, the same pattern will become apparent, with the waves moving in tandem with the cycle breaking into five waves, and the waves moving against the direction of the current trend breaking into three waves.
Given all of this, a consistent labeling scheme is a must in order to properly mark pricing charts so that cogent analysis is possible.

Unfortunately, the early EWT work did not provide a perfectly consistent labeling convention. Over time, this is the convention most analysts have settled around:

Please Note:

The coloring of the labeling below is not part of Elliott Wave and has no real meaning, the coloring of the labeling comes from TradingLounge’s TradingLevels Charting Program which members use to help learn Elliott Wave by simply color coding the labels into groups

Note that in this graphic below, the labeling for the Grand Supercycle is not shown, simply because the scale is too large to have practical analytical value. Here’s what it looks like in practice:

Putting Cycles Under The Microscope

Dow Theory, a predecessor to EWT, postulated that market cycles consisted of three trends: Primary, Secondary, and Minor. The Primary trend in Dow theory lasts a year or longer. Secondary trends move counter to the Primary trend and lasts between three weeks and three months. Minor trends last three weeks or less, and make up sections of the other two trends.

As you can see, this is a much more basic theory than EWT, which provides more in the way of structural detail. Further, Elliott’s observations revealed that cycles are not necessarily repetitive in either duration or amplitude.

As important as those observations are, Elliott’s biggest contribution to the body of analytic thought was to discern that there’s a repetition in the directional form of waves that constitute cycles, which is another way of saying that progress (or regress) must advance through a series of predictable stages. Further, Elliott was able to codify a set of rules and guidelines that could be used by others to identify patterns as they emerged.

Here’s a complete cycle, illustrated in its simplest form:

Of course, one thing we know about price movements is that they never occur in straight lines. Progress is always uneven, so in reality, they look something more like this (and note that all of the above chart is Wave (i) and (ii) in the next chart, this is the fractal nature of Elliott Wave)

Impulse Waves & Corrective Waves

You’ve probably heard the phrase “following the impulse.” While there’s no evidence that this phrase influenced Elliott to name waves that moved with the overall price trend impulsive waves, but the two mesh well together, with the phrase informing the directionality. “Corrective Waves” then, move counter to the prevailing trend.

Look at the chart below. You’ll see that the basic five-wave pattern (labeled 1, 2, 3, 4, and 5) is both an impulse wave of a larger degree, and is, itself made up of two other impulsive waves (A, and C), and one corrective wave (B).

You’ll also note that the basic three-wave corrective pattern (labeled A, B, and C) is both a corrective wave of a larger degree and is made up of two impulsive waves.

Impulse waves (almost) always break (divide) into five wave sets. Corrective waves (almost) always break (divide) into three wave sets. Note the word “almost” in parenthesis. There are a few exceptions, and we’ll cover them later on. For now, here’s the chart:

How Do Fractals And The Fibonacci Sequence Figure In?

Here’s the first part of the famous “Fibonacci Sequence”: 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, etc.

Note that the number of waves in Elliott’s structural definition of patterns are always Fibonacci numbers. Also note that since these patterns repeat at every time scale you investigate, they are, by definition, fractal.

TradingLounge has taken the Fibonacci Sequence and applied it to the actual price, using Fibonacci as a geometry price ratio and called this the TradingLevels. This creates beautiful support and resistance making the use of Elliott wave easier. There is also a course on the TradingLevels.