In the linked DD, I was able to identify how $GME followed a very set trend to the extent that important dates were almost the same for over a decade. Currently, I've been working on showing how the values also are predetermined.
2/9: One of my many $GME hypotheses is each specific share price range have their own set of "rules" that govern the behaviors. This is called a piecewise function. An example below shows when x > 0, then the x+3 is used to calculate y. For all other values of x, -x is used.
3/9: Looking at GME, an absolute min of ~$3.75 occurred on 2/11/2003. This low was not seen until 7/20/20. Oddly enough, this was also the date I have identified when BTC started to move directly with GME. That DD is here:
4/9: To further stress how 02/11/2003 was an important date, we can look at volume. The majority of the volume is ~xxx,xxx. There are also values that are magnitudes greater and are VERY improbable given the data distribution.
5/9: One of the piecewise ranges identified is ~$3.75 to ~$12. $$3.75 is the local min. ~$12 appears to be used like a touchpoint along with other important characteristics. There are many surrounding values that are also important, but I'm just dropping a quick little teaser.
6/9: Zooming into 2020, the share price immediately went straight up. Each range of data has their own set of governing "rules." I am led to believe on 07/20/20, all those rules addressing constraints like if-then loops and critical values "errored out."
7/9: Touching back to my "trust me, bro" tweets, these graphs highlight how a similar behavior seen in 2019/2020 is also seen recently. This is another example of how different share price ranges adhere to set "rules."
8/9: Similar to how ~$3.75 was an absolute min that also had a big zoom up, we see the same overall behavior occur at ~$77 on 1/25/2021 and 3/14/2022. This is because lots of reason, but the easiest one is because we entered completely new territory.
9/9: This teaser is one of MANY different ways I've been working on trying to show how both the dates and values are ripples of the past.
TLDR: The share price is also controlled and has been set by historical values.
Stay tuned!
Sometimes, I can be awful at explaining stuff. Essentially, I'll half expecting this shit to blow up if it follows the same trend as 2020.
My friend from Ukraine is heading to NY for a week to be with friends he knew back in his hometown of Ternopil. Having support from others who are going through the same pains and heartbreak is so important. I'm wanting to do the charity event when he gets back.
Does anyone have any good ideas on what we should do? I figured we could stream and discuss current events. Neither of us has done anything similar to this so, we could use any suggestions, tips, or advice.
If anyone knows of a solid app or website that could easily show total money collected to aid in transparency, please let me know.
I use engineering methods to analysis stocks such as $GME because the overall behavior is so well controlled that it behaves just like a systemic process.
Manufacturing engineering often uses the below chart to monitor live data. The upper and lower control limit (UCL /LCL) are used for quality controls. These values can be defined by a static value defined by requirement or general distribution of the population.
As a very general statement, $GME's"high-low" values appear to be constant despite how the average values ranged from ~$120-$300. If ~$120-$300 is considered the average, the UCL and LCL are static and not relative ratio to the values suggesting a user defined variable.
@CEOAdam@silverlake_news@egon_durban Silver Lake recently help the acquisition of @VMware. It was only a few days after the department of homeland security told everyone to not use this software due to a cyber security breach from the North Koreans did @Broadcom purchase the company for $61 billion.
Below is an on-going list of DD I have written. Each subject is organized into general topics with more DD tweeted and linked respectively. Any and all of my future analysis and research will be added to this pin.
1/9: So, here is a quick glance of SOME of the $GME shit showing how all this shit is related. Aight. Buckle up. Get your #GME tittehs jacked. This is only the beginning. First we got to separate this shit into 2 distinct sections: the parabolic shit and the linear shit as shown.
2/9: First the parabolic. I did mathz to determine the best dates to most accurately represent that shit. For easier math, I replaced dates to relative days so math is easier. Anyways, focusing on the high volume days, we get this fun graphs from 11/5/2004 to 01/10/2008.
3/9: To figure out the limits, we set those regression equations to 0 to determine essentially what day a limit occurred. From those dates, we can then figure out more important numbers, specifically c_1, along with more important dates.