Bitcoin to C. Model A-H. Predictive Modeling Pt 13. Model H.
מעודכן
This is a continuation thread of the theoretical geometricc linear regression from 3.22.18. The modeling sequence starts at; Model A, and runs thru Model H. Model H is the newest Model. Each model is strictly built off of the preceding models geometricc regression points. The regression points from each model, creates a geometricc pattern of indicators, that can be read to PREDICT future trend movement, before actual traditional indicators occur.
I am going to try my best to explain, as we go... There will be lots of bubbles with text, explaining each move and why.. and how i make prediction cones, and patterns using geometricc boundary lines and regression modeling. This is A FULLY EXPERIMENTAL MODEL. Take it for what it is worth. I will continue to make these charts regardless of comments or jabs. They are made for a specific purpose and until my purpose is fulfilled, they will keep being made.
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.. being different is what makes you stand out.. So stand out from the rest.
So, watch what I do.. Ask questions, I will try my best to answer them.. if you are confused on how I got to Model A, B, C, D, E, F, G, H. Skim thru my old charts start from 3.22.18. It is about modeling sequencing, and appropriate modeling coherence. I have decided to explain each move I make regarding my theoretical modeling technique. This is part 13.
Red Bubbles = the past.
Blue Bubbles = Now + the predicted future.
Statistical Outliers = Emotions + and/or Market Manipulation. We are now at 22 Statistical Outliers from Model A thru Model G
Green Flags = Geometricc Convergence Indicators (There are almost 20 of them so far).
Converging Geometricc indicators = DROP
Diverging Geometricc indicators = RISE
I want to explain how I created Model H. First understand that Model A through Model G, was created based off of the preceding model. Model H is no different. Once i saw a geometric divergence in the background geometry, and it the widened. I knew it was possible we had reached bottom and were beginning our recovery.. Prediction Model C line boundary extended all the way to Model G. It was responsible for 13 convergence drops. It was a big deal to leave that line and stay above it. By staying above it the geometric indicators were fanning out (diverging) with no indication of converging geometry.. The geometry is based off of the lowest data point in the trend, and the best LINE OF FIT in the regression modeling. The 'line of fit' is simply the best line that fits between a set # of data points.. In this case, the data i am looking at are statistical outliers. So that is where i started my lower boundary Statistical Outlier #22 FOMO, I continue this method of placing lower boundary lines as more data appears.. (x over time). The boundary lines act as a background indicator, and by using the concepts of convergence and divergent vectors.. It seems by this field testing, that these geometric indicators should NOT be ignored.
Model H.. Simple is a divergent vector of paths, that do not converge at any one point along the path of the current data trend. If we get a convergent lower boundary intersect with a older divergent boundary.. it has been consistent that a drop may occur. Likewise, if we have a convergent lower boundary that is intersecting a divergent boundary and the trend moves in such a way that now that convergent boundary makes no sense.. a simple test to see if a divergent boundary will fit better is used.. You must use the BEST LINE OF FIT in order to have high accuracy. Incorrect line regression, will yield incorrect geo-indicators.
As always thanks for looking!
Glitch420
I am going to try my best to explain, as we go... There will be lots of bubbles with text, explaining each move and why.. and how i make prediction cones, and patterns using geometricc boundary lines and regression modeling. This is A FULLY EXPERIMENTAL MODEL. Take it for what it is worth. I will continue to make these charts regardless of comments or jabs. They are made for a specific purpose and until my purpose is fulfilled, they will keep being made.
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.. being different is what makes you stand out.. So stand out from the rest.
So, watch what I do.. Ask questions, I will try my best to answer them.. if you are confused on how I got to Model A, B, C, D, E, F, G, H. Skim thru my old charts start from 3.22.18. It is about modeling sequencing, and appropriate modeling coherence. I have decided to explain each move I make regarding my theoretical modeling technique. This is part 13.
Red Bubbles = the past.
Blue Bubbles = Now + the predicted future.
Statistical Outliers = Emotions + and/or Market Manipulation. We are now at 22 Statistical Outliers from Model A thru Model G
Green Flags = Geometricc Convergence Indicators (There are almost 20 of them so far).
Converging Geometricc indicators = DROP
Diverging Geometricc indicators = RISE
I want to explain how I created Model H. First understand that Model A through Model G, was created based off of the preceding model. Model H is no different. Once i saw a geometric divergence in the background geometry, and it the widened. I knew it was possible we had reached bottom and were beginning our recovery.. Prediction Model C line boundary extended all the way to Model G. It was responsible for 13 convergence drops. It was a big deal to leave that line and stay above it. By staying above it the geometric indicators were fanning out (diverging) with no indication of converging geometry.. The geometry is based off of the lowest data point in the trend, and the best LINE OF FIT in the regression modeling. The 'line of fit' is simply the best line that fits between a set # of data points.. In this case, the data i am looking at are statistical outliers. So that is where i started my lower boundary Statistical Outlier #22 FOMO, I continue this method of placing lower boundary lines as more data appears.. (x over time). The boundary lines act as a background indicator, and by using the concepts of convergence and divergent vectors.. It seems by this field testing, that these geometric indicators should NOT be ignored.
Model H.. Simple is a divergent vector of paths, that do not converge at any one point along the path of the current data trend. If we get a convergent lower boundary intersect with a older divergent boundary.. it has been consistent that a drop may occur. Likewise, if we have a convergent lower boundary that is intersecting a divergent boundary and the trend moves in such a way that now that convergent boundary makes no sense.. a simple test to see if a divergent boundary will fit better is used.. You must use the BEST LINE OF FIT in order to have high accuracy. Incorrect line regression, will yield incorrect geo-indicators.
As always thanks for looking!
Glitch420
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3 min chart closer look.הערה
Goodmorning!As you can see the newly rendered model H prediction cone is doing its job.. keeping the data within its prediction cone. :)
Understand a statistical outlier can knock us out of Model H at any time, at which point the outlier would have to complete itself upon re-entry into the modeled zone. A completed outlier keeps the Model True. I have shit load of research and homework to finish today, so I will try and keep this thread updated..
As always .. thanks for looking..
A word of warning.. Please do not trade based off of my charts.. You are responsible for your money. I have been making these charts for about a week. That is all the exp i have doing this. I love making these charts, but as stated multiple times these charts, constructs and ideas are completely 100% theoretical model that i designed from scratch based off of my neuropsychology research on neural network modeling of the brain.
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New Target 7200.. הערה
MUST CROSS MODEL G INTERSECT LINE. MODEL G can still pull us down until we cross that threshhold.הערה
That line is indicating something.. I say 60% we blast off on that line.. and 40% we drop on that line.. Complete guess. but geometric indicators show an up but Model G was right on the money and we are nearing its peak..הערה
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Model G says, 'get rekt bull trend.. Model G play no games..' 0_oWe must stay in the divergence zone.. or risk a FUD outlier outside Model H.
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I hate when i post a duplicate (angry face).הערה
Ya this zone indicated between red boundary lines, we must get out of.. The peak of Model G indicated a drop.. we are fighting through the peak zone now.. הערה
well look at that shit.. all lower boundary paths have held and we are modeling a nice 100% accuracy with Model H. Still gotta get outta the danger zone though.. :)no idea how i keep doing it.. but it is working whatever i am doing! ;)
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Playing around with some new tools.. הערה
right on the boundary line.. will we see any action?... the world may never know..הערה
I think we are about to witness Statistical Outlier #22 which would consist of a FUD outlier. It shows we are just outside the danger zone, but i have a feeling that danger zone should be expanded since, i am getting geometric indications of a drop..
Drop into Outlier #22 = 60%
Rise back into new channel = 40%..
Just guesses..
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the train just keeps on rolling... right thru Model H prediction cone.. so far it stands at 100% accuracy. (the entire model sequence A-H, not necessarily MY calls). It is hitting the divergent boundaries at all the correct points, so far we are still good.. as we get out further.. i feel things are going to get more dicey..
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The bigger picture now.. הערה
not much to say... as we reach the outer limits of Model H, we can render a new prediction cone based on ANY other model's geometry in the modeling sequence (Model A thru H).. הערה
Still at 100% accuracy.. Kinda blown away. הערה
1 hr Chart. הערה
A new Model Connect line has been formed between Model A-F and Model H. It is depicted by yellow line, which so happens to be the best 'line of fit' to the data points at that specific zone in Model H. There are no coincidences in predictive modeling.. Past data + current data = future data (+/- statistical outliers).Upon the connect line, a new geodivergence was present, this marked a new foundation line for geodivergence that i extended to ZONE C (goal area).
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