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.
4/9: Aight. So for the linear. We gonna be doing similar shit but with different equations since it's linear. Using mathz, 08/28/2015 to 01/14/2020 were determined to be the best timeframe to represent this shit.
5/9: Let do that same shit we did earlier and make a table and shit for the linear section:
6/9: Only the close values are shown for formatting reasons. Now, we gotz tah combine important shit to make cool shit. Applying the red boxed numbers to the closing graph, there are now established important values where the share price likes to bounce on oscillate on.
7/9: This is a one of the many different things I've been fucking around with but this data so far only shows like 2002 to 2020. But what 2021 to 2022?
Don't worry, boo. I got u.
Don't worry, boo. I got u.
8/9: We can take those linear regression c_1 values figured out with mathemagics and apply it to the shit we seen today.
9/9: Look at that. Those constants work as a very well-defined minimum. We got one of the many ways I've working on explaining the sideways trading and other shit. Stay tuned for the rest of this shit. #yolo
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