A little dive into the seismic GME graph

CategoriesGamestop_, Issue 2023Q2
With pretty pictures!

From u/ HansAuger :

Hello my highly regarded apes,

this week fellow regard Spinmoon pulled a graph from the vault and presented to the hive, and it was rewelcomed with the usual cheers, shit-flinging and excited chest bumps, the usual healthy hypey stuff that us smooth brains like to do when we get some new fodder to support the MOASS thesis. I am talking of course of this post here. It should be said, that the graph itself comes from another community member,, Antoine_FRITOT. I don’t know where they have got it from, or if they are the originator of the graph.

Seismic activity go brrrrrrr

Now, when I skimmed through the comments, I noticed a lot of comments who had questions about the exact method that was used to derive this graph and how it compares to other stocks. Now, my brain is so smooth that I was part of some mulecular experiment once. Don’t ask me what it was about, I just participated because I was promised two bananas a day and one of the lead scientists was the boyfriend of my wife at the time, so I trusted him. And I am especially not a data scientist. But I do dabble with python every once in a while. So I took some time to look into the data and if I could recreate it. And although I can not say what the original creator of the graph did, I think I came reasonably close to recreate their results.

So here is my representation of the data, how I created it and some other data points, which will hopefully answer some questions and inspire some more questions.

Here is my version of the graph:

First of all, the data I used for this graph comes from NASDAQ, which offers historical stock market data for plenty tickers, GME specifically I have from here. This gives us a stock’s open price, close price and traded volume for each trading day for the last 5 years, which is all that we need.

The first graph just shows the closing price for each day, I’m sure you are familiar with that shape. To come to the second graph, I did the following:

  • Subtract close price from open price for each day

  • Normalize this data by dividing by the average of both prices (0.5 * (open_price + close_price))

  • Divide by the volume of that day

I did the same for some of the basket stocks and some of the other old familiars, keeping the y-axis in the same scale to make comparison easier. As you can see, other basket stocks have had similar seismic activity, although compared to GME, they are rather in decline. Boomer stocks however are basically flatlining.

The code I used to derive these graphs is available here. You can use it for your own purposes or verify my findings if you wish. If you have other suggestions of what to look at, feel free to suggest something in the comments and I might look into it.

BUY HODL DRS and keep that receipt porn up ??????

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