Ethereum. P-Modeling Pt 4. Model B: Recovery Mode Initiated

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This is Part 4 of Geometric Linear Regression Modeling for Ethereum . Don't forget to come back for updates! We started at Part 1: Find Model A. Then had Part 2, which explains some of the theory behind Model A and now we are on Part 3: Statistical Outlier #1. Now we are on Model B. We have officially rendered Model B in Pt. #4..

Each Model created in the Modeling Sequence, creates a geometricc pattern of indicators in various forms. These indicators can be read to PREDICT future trend movement many days before traditional indicators appear.
The idea here is to convince you, that what i am doing is not arbitrary but unique and useful. I know the immediate inclination is to doubt what I am doing. That is expected.. and understandable.. But human nature is unpredictable. And you never know when you can learn new things and be completely shocked at someones EXTREMELY insane ideas.. I like going against the norm.. So join me please. :) If you enjoy this.. Hit that like button!

Understand the application of my modeling technique is not traditional by any means. It is theoretical in nature, and 100% experimentally designed and applied by me as we continue this insane experiment day after day.. It was not built for financial analysis, at all. I have literally 0 background in trading, TA's or anything to do with accounting or the stock market. It is being applied, through intuitive and creative means for fun so I could keep up with Bitcoin 2.76% and Ethereum 3.89% personally, and invest for myself.. I promise I will make many mistakes making these non-traditional TA's, or even incorrectly use traditional tools and indicators. That is the fun of it, to learn from scratch and apply another idea to a realm unknown to you. This realm is an unknown to me. A knowledge acquisition process. One i am quite enjoying.. If you confused on how we got to this point.. Please re-read my old charts. You can find links below and in bio. I take you step by step.

Shizz to note:

Model A was a long model.. but the validity of Model A was nonetheless very accurate..
I placed a Gann Fan at the entry into Model A, this laid the trend boundaries really nicely and nicely correlated with my geometric mainframe from my indicators.
As you can closely see.. The trend bounces off our designated boundaries many times and stays within the predicted modeling space.

Double Model Outlier.
Statistical Outlier #1 is very special for Ethereum because it serves a connection to my modeling on, "Bitcoin to C" Pt. 24 with Statistical Outlier #28. Both Ethereum and Bitcoin had a Statistical Outlier that jumped to a second Model. Both coins and their statistical outliers had re-entry into another model at almost the same time as well. Yet.. They are two completely different designed Modeling Sequences, but same technique. This is a huge validity win for this modeling technique.

Model B became True when:

We had entry into Lower boundary which completed the double model statistical outlier #1.
We had a mainframe intersect or connect between Model A and the new Model B. (we had a connect).
We are staying within the designated vector of the model for at least half of the model rendered.
We achieved all of these with Model B.

Model C:
Model C will be rendered when we get enough data points to continue, I suspect that will not be to far from now as Model B was rendered small in size.

As always, thanks for looking!
Glitch420

注释

Statistical Outlier #2 Imminent!

We are hugging the upper boundary!