Elliott Wave Intro Series - Part 1
Elliott Wave Intro Series: Part 1 | Part 2 | Part 3 | Part 4 | Part 5 | Part 6
In 2011, I began writing for Seeking Alpha, and quickly encountered a major challenge. I realized that writing about technical analysis on a fundamental analysis website was not going to be easy.
While those that initially read my articles were quite skeptical (and that is probably being kind), as more and more of my prognostications came to fruition, I started to gain a following. It was not long until I was the number one followed metals analyst on Seeking Alpha, and have basically remained in that position for the great majority of the seven years I have been writing on Seeking Alpha.
Lately, one of the commenters to an article I wrote suggested that we peel back the curtain regarding my analysis methodology:
“You have a large following on SA and in my view are the definitive TA expert on SA, so please consider the following: Offering a weekly SA post on TA Basics (101 if you will) in an effort to introduce more to at least gaining an understanding of TA and how they might benefit from it.”
So, after getting buy-in from the editors at Seeking Alpha, I have begun this new series of articles which will give you a bit more insight into the technical analysis methodologies I use.
In the first several articles in this series, I am simply going to provide you an overview of Elliott Wave analysis and why it can assist you in rising above the herd, which often seem to be chasing their tails. After the introductory articles, I will begin discussing Elliott Wave analysis in more detail, and then explain how we use Fibonacci Pinball – a method we developed – to place a more objective structure around standard Elliott Wave analysis. I will then explain how we use standard technical analysis to assist us in coming up with a higher probability wave count.
So, if you are interested in a methodology which will open your minds and eyes as to how markets really work, then let’s move right into the overview.
Back in the 1930’s, an accountant named Ralph Nelson Elliott identified behavioral patterns within the stock market which represented the larger collective behavioral patterns of society en masse. And, in 1940, Elliott publicly tied the movements of human behavior to the natural law represented through Fibonacci mathematics.
Elliott understood that financial markets provide us with a representation of the overall mood or psychology of the masses. And, he also understood that markets are fractal in nature. That means they are variably self-similar at different degrees of trend.
Most specifically, Elliott theorized that public sentiment and mass psychology move in 5 waves within a primary trend, and 3 waves within a counter-trend. Once a 5 wave move in public sentiment has completed, then it is time for the subconscious sentiment of the public to shift in the opposite direction, which is simply the natural cycle within the human psyche, and not the operative effect of some form of “news.”
This mass form of progression and regression seems to be hard wired deep within the psyche of all living creatures, and that is what we have come to know today as the “herding principle,” which gives this theory its ultimate power.
And, over the last 30 years, many social experiments have been conducted throughout the world which have provided scientific support to Elliott’s theories presented almost a century ago.
In a paper entitled “Large Financial Crashes,” published in 1997 in Physica A., a publication of the European Physical Society, the authors, within their conclusions, present a nice summation for the overall herding phenomena within financial markets:
“Stock markets are fascinating structures with analogies to what is arguably the most complex dynamical system found in natural sciences, i.e., the human mind. Instead of the usual interpretation of the Efficient Market Hypothesis in which traders extract and incorporate consciously (by their action) all information contained in market prices, we propose that the market as a whole can exhibit an “emergent” behavior not shared by any of its constituents. In other words, we have in mind the process of the emergence of intelligent behavior at a macroscopic scale that individuals at the microscopic scales have no idea of. This process has been discussed in biology for instance in the animal populations such as ant colonies or in connection with the emergence of consciousness.”
As Elliott stated:
“The causes of these cyclical changes seem clearly to have their origin in the immutable natural law that governs all things, including the various moods of human behavior. Causes, therefore, tend to become relatively unimportant in the long term progress of the cycle. This fundamental law cannot be subverted or set aside by statutes or restrictions. Current news and political developments are of only incidental importance, soon forgotten; their presumed influence on market trends is not as weighty as is commonly believed.” R.N. Elliott on causes of the waves, October 1, 1940
Next week, I will focus on the last sentence in Elliott’s quote above using real market examples, along with studies performed over the last 20 years. And, once I have presented the theoretical basis for Elliott Wave analysis, I will then present articles breaking down how we perform the analysis.
The studies that were cited herein were compiled in various books written by Robert Prechter, including Socionomics: The Study of History and Social Prediction and The Socionomic Theory of Finance, which are strongly recommended reading material for every single investor.