Vol S&P 500. P-Modeling Pt 2. Trials of Theory UnificationThis is hopefully an Education Post.. to explain a little of what I do.
I am attempting to Unify two theoretical (in development) theories and one old school (unfinished) principle of wave theory by conjoining them into the same methodology protocol.
Theory 1: Geometric Linear Regression Modeling (GLRM)
Theory 2: Elliot Wave Principle (EW)
Theory 3: Geometric Fractal Mapping Protocol (GFMP)
The OP presents TWO theories in development.
Theory 1 & Theory 3 are authored by the OP to advance the pool of knowledge in Bio-Computational Prediction Modeling Protocols (BC-PMP).
-Currently Theory 1, Geometric Linear Regression Modeling is used in experimental EEG brain mapping protocols by the OP in Neuro-Imaging Case Studies.
GLRM decodes the brains functional connectivity using linear regression based geometry to design a 3D graphical rendered case study for further decoding.
Currently Theory 3, Geometric Fractal Mapping Protocol is used in experimental 3D graphical renderings to decode Quantum/Classical Wave Theory in Entropy Dynamical Ecosystems in a variety of domains.
The Old School Theory
Theory 2 is authored by the well known Ralph Nelson Elliot in 1938.
The Elliot Wave Principle is unfinished work. Of course this is my opinion. As a theorist, who aims to architect my own foundation theories. I am convinced Elliot Wave Principle is an unfinished theory because of the lack of understanding of Quantum Physics and advances to Quantum/Classical Wave Theory in the 21st century.
This is where I hope to make a difference.
My theories in development and in-process publication research seeks to close the gap, by presenting a Unifying Prediction Modeling Protocol for a variety of domains including:
-Any 2D analog Quantum Ecosystem based A.I.
-Financial Market Analysis: Cryptocurrency & Stock Market
-Neural Network Mapping : Specifically the Functional Connectivity of the brain.
Quantum Residual Mapping : Specifically the Functional Connectivity of the brain
The point of a Unifying Prediction Modeling Protocol is to create a new way to diagnose mental illness/pathology by creating a neural-data - pool of brains that have been fully mapped and decoded based upon my designed protocols in Wave Function in Mental-Specific Pathological criterion.
Basically, I hook an EEG to your head and decode your brain in real-time and using your brain data, and those from around the world. Compare your brains waves to others who have confirmed diagnosis of pathology. This will render a new era in mental diagnostics by using real brain data, A.I. neural network optimization protocols for comparison, blockchain data pools, and open source software to shift a new paradigm in mental health.
I am here today to explain that this research has come extraordinarily far over the last few years in a plethora of domains. This post is a trial and experimentation of the 3 theories.
I am unsure as to where this experiment will go. But i wanted you to be apart of it as we go.
Technical Analysis has not changed much since the 1980s.
When theory sits idle for this long, someone is bound to find new threads in advancing the theory or even designing new theory for application.
Trial and Error is the hallmark feature of the scientific method.
This is my first trial at combination of applied theory design. You may be in disbelief. But when a paradigm is getting ready to shift.. The mainstream usually takes the presented new evidence as fake news, disbelief and sometimes even anger; that you dare suggest a new way of doing things.
1. Elliot Wave Principle is a application of classical wave theory minus quantum wave theory applied to classical ecosystems.
2. Geometric Linear Regression Modeling is quantum wave theory without classical wave theory applied to linear ecosystems.
3. Geometric Fractal Mapping Protocol is quantum wave theory applied to quantum entropy based ecosystems.
Combining all three, satisfies application of the postulated claim of classical wave theory + quantum wave theory, residing in quantum entropy based ecosystems.
Each theory effectively overlaps the missing literature in each others knowledge pool. This is why the unification is so important. Each theory fills a missing component of the other.
Find the root wave of EWP . - Start.
Notice how each Elliot Wave corresponds to a geometric linear boundary intersects.
Each EW impulse has an increasing number of boundary intersects. Do not ignore this.. Each intersect is a complex confluence of linear boundary lines.
Being that EW decodes waves. We have to abide by classical/quantum wave functionality laws.
A very interesting thing I noticed when people apply EWP is that they have NO supporting geometric vector boundary intersects. When one draws the geometric representation of the data, you notice vectors of space that has linear confluence depicted by linear intersects. These intersects are not random but have geometric statistical application and propositional power that is FOR or AGAINST your potential proposition.
The bottom indicator is the oscillation at a 1 Day time-frame based upon the FFT-Timeshift. Basically we can see that the synchronized movement is visible and decipherable based on classical wave theory alone. One takes a quick look and notices how the wave synchronizes and de-synchronizes based upon a approx 363 day (1 year) wave function.
Notice how in 2015 the wave is synchronized. Notice how we de-synchronize and begin off-beat synchronization. This is a major clue and evidence that can either support or deny a propositional claim. Notice where I have placed a "switch". This switch is the moment we begin to de-couple from the wave function.
The next telling characteristic is the absence of BUY vol over the last 7 years that fails to push the limits of the wave functionality into the red. However, the structure of the off-synchronized wave we are currently in explains that we have a great chance to have incredible vol coming in based on our current position and that of the wave function at the 1 day timeframe.
Ideally, after a fast upward motion depcited by all the red circles, downward movement is almost a must based upon starting a new fractal sequence, which are numbered accordingly. Match the fractals. The choosing of fractal 3 is based upon the geometric linear representation that subjectively fits the narrative.
Volatility should head towards new ATL's. Modeled between the 8.75 and 7.50 range.. This means the S&P should go up. I have a target of 3200.
Then at election time/ end of the summer. We will see a massive spike in volatility as the entire stock market comes crashing down for the 2020 presidential elections.
Let's see how it plays out.. yea? Give a like, and follow along to see where we go! Cheers!
Thanks for pondering the unknown with me,
Glitch420
