Elliott Wave Patterns In NFT Trades
NFT economics are a fascinating study, because the lack of abstraction between unseasoned traders and the market means we are working with a direct line into human behavior. The complicating factors that accompany traditional trade/market analysis — anticipatory activity, complex trades, institutional investment vehicles, etc — just aren’t present.
We’re dealing with three buyers:
- Whales. These are the heavily invested, successful NFT traders. They have large pools of ETH to play with, and they will ape into a promising project, bringing follower traders into play.
- NFT ecosystem traders. These are experienced buyers/sellers who understand basic NFT principles, watch the movements of whales and the signals from platforms like OpenSea and Discord, and will attempt to make informed decisions.
- Quick traders. These are folks who are entering — and often exiting — the NFT market at high speeds, normally as a result of media coverage, and often in pursuit of short-term gains and wealth. They are unseasoned, inexperienced, and prone to panic.
These three groups are the foundation of NFT trades, and understanding their motivations is an important part of the analysis process. At Pizza Party, I’ll be using a mix of sentiment from Discord channels, data from Nansen.AI and Icy Tools, and cohort analysis to augment my own opinions, but will try to provide as much original data as possible.
What I want to get into today is the Elliott Wave Principle.
The Elliott Wave Principle holds that collective trader psychology, also known as crowd mentality, travels from optimism to pessimism and back in repeating cycles of intensity and time period. These mood swings produce patterns that can be observed in the price fluctuations of all degrees of trend or time scale.
While Elliott Waves can be too simplistic in tradmarkets, they are still a powerful tool for analysis; and in the NFT market, minimal abstraction layers mean that the way Elliott Waves measure against and track with mood patterns can be fascinating.
Elliott Wave patterns in NFTs reflect the behavior of the above buying groups through their hope, their HODL practices, and their panic sales. The hyperactivity of an NFT trade is what makes it particularly relevant for an Elliot Wave.
The most prominent Elliot Wave structure is the five-wave impulse sequence, followed in order by the three-wave corrective sequence. The impulses are characterized by strong momentum and motive force, while corrections display a counter-balancing sentiment.
A downtrend in price in the financial markets is reflective of an uptrend in psychology and another way to say it is that a bull market advances in waves and crashes in waves.
One measure we can use to gauge these swings in intensity is by determining how wide or narrow the swings are throughout time periods of differing degrees (magnitudes).
All time scales of trend fluctuate between an impulsive, or motive, and a corrective phase in market prices, according to Elliott. The motive and corrective waves or swings of trend are always present in the same amount of degree as the trend to form a motive-corrective combination.
Impetus and diagonal motive waves are two types of wave patterns, while corrective patterns include moving averages that are flat, double zigzags, triangles, flats, zigzags, long flats, or any combination thereof.
Here, you can see a basic Elliott Wave overlaid on a launch chart from an NFT property: Bad Bunnies NFT. Disclosure — I have 3 Bunnies in my own art collection.
This is a useful intro to the concept, because the best place to begin an Elliott Wave is at the nexus of a significant market event — in this case, the mint drop. While the property hasn’t been live for long enough to access a detailed dive, we can already see how the trends are mapping to the motive phase of a 5/3 Elliott pattern.
The impulse is made up of five lower-degree secondary waves that alternate between driving and correcting qualities. The first, third, and fifth waves are impulsive in nature, while the second and fourth waves are smaller retracements of the first and third, respectively.
The correction is made up of three lesser-degree waves. Wave 2 exceeds the end of wave 1 and becomes longer than wave 4 (a blow-off top) during a motive phase. Most of the time, wave 3 floats between the 0% and 100% lines, giving corrections enough power to counteract prior impulsive price movements before it ends.
The third and fourth corrective waves are divided into three smaller-degree waves, including a five-wave counter-trend impulse, a retrace, and another impulse. The pattern is reversed in an advancing market — there are five down and three up. Motive waves follow the current trend at all times.
The first step in establishing a wave count is to decide where you will begin. Your trading goal(s) and the phase of the analysis process you’re in will determine this. Instead of starting counts at the peak of a market rally or fall, it’s usually preferable to begin them at the beginning of a designated market turning point.
I’d suggest an Elliott Wave is more useful in analyzing the performance of an NFT to date, and the moods/activities of the buying group invested in it than it is in predicting movements of the market.
Okay. That’s the basic gist of it. I’d advise reading more into the concept, and examining some of the criticisms of the principle too. And I’m always curious to hear your thoughts/ideas.