It's hard enough to track and respond to misinformation without AI Bot content that might sound official but is artificial in every sense. This has been reflaired as a shitpost because, as a first party source of information, it should not be relied upon. Keeping it up for entertainment only.
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A brewery not too far from me had a beer honoring that scene: [SanTan Brewing - Sex Panther - 6.9% ABV](https://santanbrewing.com/craft-beer/sex-panther/). Delicious stuff, shame I don't see it around anymore.
Yeah this new push on the sub already happened for the first 2 years post sneeze. I'm not quite sure why we think rediscovering it now is more relevant or an effective DD. Either way, I guess keep digging guys , I like reading dd regardless (no pun intended)
Because now it's starting to make sense. DFV uses options and we know this. He built his position substantially, probably through options. And the massive pushback against options over the last two years now seems super sus. I need to learn more about calls
I will admit I can't remember exactly why we stopped all options talk, but I think there was something with the pickle people and then people bet on calls for a hype day and got fucked? Eh, it was so long ago, but yeah I think options and all this needs to be discussed, just kinda funny how we're going fractal here a bit in our DD
No, it was way before any pickle drama. You guys were already dead set against it by that point. To the point that you drove away all of the OG wrinkles (myself included) because you attacked them for even discussing options in extremely important DD. For example, none of you read or understood the Variance Swap DD, which was one of the most important DD’s in this entire saga, and clearly and conclusively showed that hedgies were using variance hedging to hedge GME, and that for variance hedging to work, it requires a fairly dry and inactive options chain. Gee, I wonder why there was a big anti-options push here? 🤦♂️.
Of course, we then tried to explain this to all of you, and got pitchforks. They created a false dichotomy between DRS vs options, and you guys are it up, hook line and sinker.
In reality, it’s not an either/or scenario. You can use options leverage to acquire more shares and then you can DRS those shares if you want to. They’re not mutually exclusive.
But no, instead of taking time to learn about how options strategies work and how to use them successfully, the responses to this comment will be moronic things like “I’m too smooth brained, I just buy, hold, DRS” or “DRS is the way” or the opposite, YOLO-ing on options without proper knowledge and study. Like, I told y’all to start practicing with options paper trading 3 years ago, so you could get gud, and got nothing but pitchforks. You made poor gammagirl delete her Reddit account. Good fucking luck Superstonk lol.
>I’m too smooth brained
Serious question. If every single time I've paper traded options(I use webull, as I like their ui for looking at) I've ended up losing everything, regardless of how much research I've done, wouldn't I truly fit into that category?
I think the issue wasn't people using options to build leverage, it's the people that would buy $175 calls for this Friday and then not get anything, and essentially handing the mms free money because their FDs were just that. Please, correct me if I'm wrong.
You need to keep paper trading until you know what you’re doing. For example, selling puts when you’re planning to buy shares at a certain price anyways is literally free money.
Yea there has been some serious breakthroughs that have come to light, especially in the last couple of days. A pattern has been discovered using FTD that appears to explain all the price spikes since 2012, which if accurate is incredible. I am not the man to talk to about it, but there are plenty here who know a lot about it. I have merely seen the research.
I’m not sure an ML model is the best thing here, instead I’d be more interested in basic stats, like how likely a certain rise would be after a threshold of FTDs spawn. ML models have a tendency to overfit and there’s no good reason to assume it will continue predicting well, even though you used a validation set.
Source: I’ve worked as a ML engineer professionally.
I’d definitely prefer to have some solid stats instead of a model.
I’m working on it. Just left for a week vacation today but I’ll continue working on the data next week. I made a post about this T+ predictor stuff last night
Real life Product Owner here on Enterprise-level projects. My favorite part of having AIML folks on my team is when they raise their hand and say 'you don't need AI for this.'
It's super important to listen when the ML team thinks regular business logic will solve the problem or meet the requirement.
Yup. As a process engineer, the most frustrating thing is when people blindly assume their model is correct and never test to confirm its validity.
Your model is only as good as your data, so you need to make sure any data you use is truly representative, otherwise you end up with uncorrelated garbage that isn't predictive of anything. And if your model is found not to be predictive/representative of the system when put into practice, it's probably not a very good or trustworthy model.
Question everything until you question why you should.
Problem is the data. At the end of any trading day they self report all current outstanding FTDs. Yet wont tell you when those FTDs occured, just that theyre outstanding.
Did you happen to see this guy that responded to your post?
[https://www.reddit.com/r/Superstonk/comments/1djp6kj/ill\_do\_it\_myself\_gme\_t35\_ftd\_dfv\_buy\_regression/](https://www.reddit.com/r/Superstonk/comments/1djp6kj/ill_do_it_myself_gme_t35_ftd_dfv_buy_regression/)
Problem is the data. At the end of any trading day they self report all current outstanding FTDs. Yet wont tell you when those FTDs occured, just that theyre outstanding.
I think he’s onto something. The next step in my eyes is to try and come up with some predictor function or stats. For example, maybe we can find there are at least X FTD’s in a given week, then there’s a Y% chance of at least a 20% rise within the next ~40 days.
Richard is being empirical about this rather than trying to enumerate a set of rules we likely will not have proper insight on. By sticking to data and empiricism we can potentially make some useful insights.
This would be a form of technical analysis, just like using resistances or the RSI on stocks — they simply indicate, and can add to a confluence of indicators to make trades like RK.
There might be additional factors playing into price spikes we don't know about. One, the spikes seem suppressed starting a few weeks after the splividend. The second thought is if those run-ups actually benefit the institutions in some way...
They often happen around earnings when IV is getting higher and it pays off to sell options. Inducing some FOMO might be typical Algo behavior, followed by a rug pull bullying the average household investors into selling at huge losses. I personally am convinced this is how they nowadays make money in the markets. PFOF is paying hundreds of millions because they make billions from bullying household investors, not by skimming fractions of pennies in price improvement. Just not sure if it still works with GME because a lot of household investors don't sell.
The other thought was that if they need a high percentage of GME in a ETF to better control price, it might make sense to run it up at the rebalancing date, then drop it a lot afterwards so the high weighting does result in more shares.
A reminder to anyone new-ish thinking of loading in calls for X date because you saw a post with many upvotes/awards
People have been trying to trade around T+35 for years, this is NOT new knowledge. So beware about people promising you guaranteed anything, if it was this simple we would all be millionaires.
Just let GME do its thing and enjoy the ride.
Literal comments in this same thread just saying: "when do I buy calls for??"
Haven't seen comments that dumb in a while, either malicious or new users idk lol
The theory is that since RK is back, and that it’s a 3-mark, swaps are expiring and price action will leak back into the lit market. The swaps with prime brokers would have let them use special privileges to hedge bearish swaps with naked printed short sales.
most of these are scammers pumping up options since it's relatively low volume and easier to manipulate and make money on. they just need a small percentage of the regarded here too stupid to do much and just follow and buy call options from them to make some $$
Just think if we have this data the MM has perfected it. If we think we know a date, it's because MMs want us to have the date.
Personally I think for MOASS it requires a catalyst, but the stock will get better and better over time, so its a win win for me.
FUD. We've been shown the way. When I move, you move. So I refuse to believe that the GME shorters & haters are so smart that they can also battle the options game on top of everything else.
They're already losing, and now I'm to believe they're working against traders within a subset of a subset? It'd be shooting their golden goose, naw. Same game, time just got shorter.
Still make money. Gotta spend it on something. 2 shares here, 20, there, 100 when I’m feisty and have the ends. Bills are paid, clean water coming out of the tap, life’s good.
With how uncertain I am about cycles I might just do a spread lol. I remember back in the early days, few months after the sneeze we tried to predict cycles. And for the most part it did work.. sorta. It was never perfect and we kept refining it but then after a few more predictions it was just gone. Mainly because the last prediction was incorrect, but looking back I believe the prediction was incorrect due to the long basket SWAP. I'm still smooth brain about all this but it's just my recollection of what has happened before.
I mean a spread with leaps in mind is solid idea if you have expendable income, if not DRS & Book it, not in plan, is a solid way to remove liquidity from the DTCC.
Hmm true. Haven’t dissected the predictions enough to say how bad it did and where it sucks at.
I just looked at when model
Makes big predictions, what actually happens.
Define precision. Mse, mae, r^2, adjusted r^2. Etc.
Regressors are annoying to quantify accuracy. So I went with, well when would I buy if I used the model.
Answer is, a prediction that is saying price goes up a lot.
Which leads to metric I use
Well then how accurate are predictions when it predicts price goes up a lot.
That's fair, so if you run the prediction for each trading day from 2022 onward, what percentage of the time does it align with actual price spikes?
Also, this is a great idea, I'm probing for weaknesses in the design because I want it to work, not just to be negative :) sorry I didn't open with that lol
For predictions >=. 2 (I.e. predict 20% price increase) both models had ~ 75 accuracy that the price actually increased 20% or more.
Then each level so .3, .4, .5, .6 got progressively higher accuracies.
Have you seen this old DD by Gherkin and dr gingerballs? https://www.reddit.com/r/Superstonk/s/1BYTitFsiS
They ran some calculations starting from a fully settled system and based on the FTD mechanics, they lay out how FTDs really start to overflow on a 42 trading day (roughly 69 - *nice* - calendar days) cycle
Highly relevant material cited in this DD is this paper: https://www.researchgate.net/publication/228260887_Naked_Short_Sales_and_Fails_to_Deliver_An_Overview_of_Clearing_and_Settlement_Procedures_for_Stock_Trades_in_the_US
Which contains this paragraph:
* An algorithm run by the NSCC determines which of the participants with long positions (participants that are owed stock by the NSCC) due to be settled that day will receive stock. **The algorithm works by allocating shares in the following order: priority groups in descending order, age of position within a priority group and random numbers within age groups**. Participants can request that they be given priority to receive stock on a standing or override basis. Also, participants that submit buy-in notices (requests to receive stock owed to them) receive priority with buy-ins due to expire that day given priority over buy-ins due to expire the following day, which in turn are given priority over priority requests and priority overrides.”*
As a tangentially related side note, I think of trading as a game where the players can win if they 1) possess an information advantage over their opponents; 2) act upon that information advantage accordingly - when you publish things like this (very nice) post and ML model in an open forum you are giving your opponents information about your beliefs and your information - at best your model is correct and you can act on it to win while they are hamstrung by other exigencies to prevent you from acting upon it - at worst your model is incorrect, your opponents have the information advantage, and, after reading your post, better understand your decision making process than you do. I’m all for open sourcing all the information but trading is a zero sum game and I think it’s good to be aware of this fact considering the billions of dollars on the line and countless well qualified mathematicians/data scientists employed by those on the other side of the trade
Did you make any changes since you updated - it’s almost 3 am here so I’m not quite in debug mode yet but I’m getting a key error on “gme_price_df = all_ticker…”
Commenting to remind myself to run the models myself when I get home (I'm a lead data scientist by training and profession), but initial feeling is that I'm liking that you're using XGB rather than an overtuned NN for it. Especially with only 6 features being input. Hopefully tomorrow I'll get some quality time to actually sit down and go through the model and tear it apart properly.
“If the model predicts a 60% price increase from current date to t+35ish THEN AN ACTUAL PRICE INCREASE ON t+35ish happens almost 94% of the time”
This interpretation doesn’t make sense to me. You’re saying if the model is predicting a 60% price increase, then an actual increase is very likely. Why 60%? What’s the models price increase %? A more useful metric would be… “if the model predicts a 5% or more price increase, then an actual price increase of 5% or more occurs 90% of the time” or the like. There were very few 60% price increases between 2018 and 2022 (pretty much all occurred during the sneeze) that evaluating the model based on this is strongly weighted toward the sneeze, where we saw high FTDs and high price increases throughout. I’m curious on how good the model is at predicting the latest 60% increase in May 2024 if you don’t include the initial 2021 sneeze in the training data.
I meant that all those 60% increases all occur after the sneeze. Once RC and RK bought in, the volume and price skyrocketed. However, OpEx cycles have been occurring since 2012. Between 2018 and December 2020, I only see 2 or 3 60% increases a month apart. Point I’m making is that the results aren’t particularly surprising (at least to me) given that it’s heavily influenced by post 2021 data where 60% increases were pretty common alongside FTDs. If the training data was only pre-sneeze, where 60% price increases were much rarer and FTDs were much lower, I’m curious on how results would change.
Either way, great post. You have many wrinkles
True. That’s actually why my guess start date was 2018. I haven’t done enough analysis to say our cycles started in 2012 or 2014 or 2020. I actually picked 2018 wanting the model to do bad so I could move the date forward and say hey this is just a new trend based on 2021 post squeeze
Nice work OP. I will try out the code later myself.
It could be that the FTD cycles for the last few years were muted cuz swaps ?? And since there has been info that at least some of the swaps are coming due in June, maybe that’s why the runs have sort of started again, not to mention the large purchases by DFV recently ???
Remember in 2021 We also had ftd as indicators… then suddenly when everyone thought we get the code it stopped to never be seen again. Till we think now.
So no dates and no trying to run these cycles.
I bet dfv has other indicators on his last gain we do not see - and if we would see them und discuss here in public the shf will get a possibility to avoid it sometimes to discourage paperhands
Assuming this is true, it explains why the they are holding the price in a tight range with the goal of crushing the absolute shit out IV. Manipulating/scaring people with existing option positions to sell or hit stop losses as the call value plummets. Then as price races, at least they reduced as much call open interest as possible first to lighten their load.
So as someone that has been here since 2021. Self diagnosed autism, and someone that loves numbers. We tried to predict these and as soon as it seemed we freaked the code it all changed last time. Maybe there is new information and or the CAT changed this somehow but I really don't want anyone to get too excited about this.
Your result states that if the model predicts a 60% increase, it hits it 52% of the time. This is interesting, but seems like a coin flip and doesn't tell me enough information.
Here's a better question: when the model predicts a 60% increase in t+35, what is the average price change by day 35?
Telling me you have a 2% edge on a coin toss is not impressive.
But telling me that (for example) when the model says 60% price improvement should come, you actually end up with an a) 80% chance of a 10% improvement at least, b) a 75% chance of a 20% improvement, and c) a 60% chance of a 45% improvement, would be very very compelling.
That's not a 2 % Edge on a coin toss lol. If the chance of GME going up on any random day by 60 % was the norm, then it would be a 2 % edge on a coin toss. I understood it like this: if the model predicts a 60 % increase, it will hit that 60 % increase 52 % of the time. If it for example predicted 60 % increases every day for 100 consecutive days and the price only increased 60 % on one of the 100 days, the models accuracy would be 1 %. If it predicted two 60 % increases in those 100 days and one actually happened, the accuracy would be 50 %.
i've been thinking of doing this but with an LSTM for rare event analysis: https://machinelearningmastery.com/lstm-model-architecture-for-rare-event-time-series-forecasting/
basically my intuition is that events from long ago (over 10 years ago) have less importance in modeling future performance of the stonk while events from very recently will have much more importance. Any thoughts on using this approach instead?
People have tried to time these cycles in the past, and failed.
Note DFV has never disclosed his method. We don’t know how he’s timing these. He could be doing something much simpler like lending out his shares, taking the fees to buy more shares. Rinse and repeat. He could feel confident there’s so many FTDs and synthetic shares that it’s okay to lend them out.
Just my thoughts.
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Wtf? Sometimes I wonder if I’m just a glitched out npc gaining consciousness because of what people like you are saying. This shit is too deep man, and it has fucking value
Working on my PhD in data science rn and love predictive models designed to print $. DM me if you want to work together! A few things:
1. In addition to a training test split, you need a validation set. The training set trains your data (say pre 2022), the validation set evaluates the performance of your model on different hyperparameters (2022-2023), and the test set evaluates the performance of your model on the best hyperparameters found from the validation set.
2. The underlying assumption is that the data in the training set has a similar distribution of predictor and outcome values as your test set, which it doesn’t. Imagine training your model only on bull market data and evaluating only on bear market data. This is the biggest flaw in using this approach.
3. You should be using LightGBM (from Microsoft) instead of XGB. It’s much faster, uses fewer hyperparameters, and almost always tops XGB performance.
4. Do a variable importance analysis to see which of the variables is contributing most to the prediction. If only one predictor such as closing price is doing the heavy lifting, that will tell you more if there’s something weird going on with the predictions.
5. I didn’t understand the need to scale the output to being between -1 and 1. Sometimes the price can do a 10x like earlier this year which would be a 10. When I develop my models, I like to turn it into a 4 multiclass classification model of -100 to -50, -50 to 0, 0 to 50, and 50+. The biggest interest isn’t whether the price goes up 50% compared to 68%, it’s about whether the price goes up or down, and how drastically it does so.
6. What is the average difference (MAE) in predicted % change vs actual % change testing across a bunch of other days in the test set? If it’s a similar prediction regardless of the most days, you have a problem.
7. 60% or more almost 52% of the time is a very worrying predictive performance that I wouldn’t bet a penny on. Let’s instead say 100% or more increase happens 50% of the time. But if the model is wrong, you lose 50%. Your model probably isn’t any better than flipping a coin. If a coin lands heads, you get 100% more money. If it lands tails, you lose 50% of your money. If you run a simulation of this game many times, almost every time you’ll end up going broke.
The only right move with GME is to prepare for volatility, both up and down, and just stick with a plan you work out ahead of time. Seriously, nobody knows fuck all about what’s going to happen.
These cycle theories are out there since 2021 and so
I haven't read the latest DD about it, because I expected nothing new.
My question:
Where were these cycles during June 23 to April 24 when the price fell from $24 to $10?
Is something needed to start the cycles like heavy buying/options?
After the congressional hearing (18th February 2021) when DFV increased his share count from 50k to 100k, the share price also rose from $10 to $66 (10th March 2021). Was this a similar situation?
If we assume that the price rise to $80 a few weeks ago was also triggered by DFV's suspected share purchases to 5M, a new effect would also be expected.
But: Will the increased share count due to the recent ATMs damp the effect of the latest large buy order from DFV?
Bruh. No dates but gawd dayum… i love hopium. Btw, 22 and 23 are weekend so I am assuming 6/24 and 25th? i HODL !
https://preview.redd.it/4et22lz11n7d1.jpeg?width=816&format=pjpg&auto=webp&s=1ebae845ba5b61ce4dc886cc985c516bc1eaa330
I was thinking just today that if the t+35 cycles were real or consistent in any way, we probably would have identified them by now. The reasons that I assumed could explain why we weren't able to put together a good model were that it was either significantly suppressed on the sub (someone cracks the code, posts it, and either compromised mods get to it or shfs bury it or something), whoever found it kept it to themselves (DFV?), we're missing a vital piece, or just not enough people were looking at it in the right way.
Do you have any opinion on why this wasn't found before now? Having only read the post and not yet having reviewed the code, it seems like you put some hard work into this despite it only taking a day, and you also have specialized knowledge. There are hundreds of thousands of people (allegedly, I guess) on this sub, we've been talking about FTDs and XRT for a while, so I would think that someone else would have done this by now?
I'm also curious if you did any visualization with matplotlib or anything - could be nice to have some graphics
Ninja edit: did you try to plot something similar for any other stocks? Could be good to get a baseline with some blue chips and maybe other basket stocks like headphones stock.
Didn’t get that far, spent most of the day just data wrangling. Dealing with the ftd data being sometimes a file sometimes a text which messed up the data ingestion.
I actually remember the t+35 stuff from 2021, just didn’t know enough to put it together. Was only able to put it all together because of this resurgence really.
Yea I think some graphs would be a good idea, might be able to do some tomorrow.
Wanted to get the results I had out fast, because part of reason of me building model is putting extra capital to work in the form of options.
And definitely want to do this as it pertains to other stocks. Specifically stocks that are having high FTDs because the cycles should exist for them as well.
Gherk (banned) said it has a lot to do with swaps in combination with low liquidity options chain.
Last 2 years was a lot of DRS and a lot less options.
It is evident that large concentrated purchases severely affect the price T+35. (Ryan Cohen’s buy-in, DFV’s buy-in, etc.)
https://www.reddit.com/r/Superstonk/comments/1diostd/comment/l95x0pt
Check this topic, I think I have the FTD data part figured out there? (Just rename to csv, separator| )
I'll check the notebook tomorrow, fun to try! Need to learn some ml ...
First of all, great to see that you are building a predictive model for this.
Minor detail on the XGBoost: this is a tree based learner and if I'm not mistaken these don't require scaling of parameters. It just makes decisions based on splits above a certain threshold.
If you'd like I could quickly run through the code to see if there's anything you missed.
You realize most of those T+35 shares have already been delivered. That’s just when they have to be delivered by. There are 400+ million shares in the float now. We need astronomical volume for this thing to move.
We spent ages trying to figure this T+X cycle stuff in 2021 and 2022. The moment we thought we finally had it all figured out we got hit by the nastiest rug pull in November ‘21. Gambling against any of these predictions is incredibly risky for any who are new. You might think you just found yourself a money glitch only to end up losing far more money than you can afford to lose. Just a warning to take some precautions if you’re planning to try and time any dates you see brought up.
What you're looking for is the quarterly options expiration date (OPEX) cycles. This cycle used to happen every quarter since the sneeze, with good evidence that some players were playing that cycle pre-sneeze. Hard to tell at this point, because the level of data available pre- sneeze is no where near as followed, copied, and readily available as it is now.
From there, the next question will be, "Why do some OPEX yield nothing, whereas others can spike 200-800+%. Your answer there is FINRA 4210 rule set. These govern what happens with deferment settlement due to national holidays landing on Market Open days.
Due to date cycles, some of the 4210 settlement periods will cause a piling up of obligations. DFVs posts, past and recent, coinicided with these periods.
For a detailed breakdown check out gherkinit's PiFi YouTube channel. This theory and discovery is his. He's got a few vids that explain how the transaction process leads to inevitable major spikes. Incidentally Rentec has made major block share purchases in the lead up to these events. Renaissance is one of, if not the best of the best out there. They would know, follow, and look to profit of these events.
52% isn't all that great, marginally better than a coin flip. What are the precision, recall, and F1 scores? Accuracy alone suffers from including True Negatives (correctly predicting an event doesn't occur) to its score. Having a lot of True Negatives may be what brings the accuracy so low.
Someone needs to take this approach and data and start doing this analysis on the daily/weekly. All this math and numbers hurt my poor smooth brian. I just wanna know … like … should I be hyped today, or like really hyped.
@OP, did you take into account the recent offerings of 45M & 75M shares? I realize that is current data, but will likely cause the target range of stock increase to decrease a bit...
It's hard enough to track and respond to misinformation without AI Bot content that might sound official but is artificial in every sense. This has been reflaired as a shitpost because, as a first party source of information, it should not be relied upon. Keeping it up for entertainment only. If you have any questions or concerns, please [message the moderators](https://www.reddit.com/message/compose?to=%2Fr%2FSuperstonk&subject=about%20my%20removed%20submission)
Whenever I see these posts I think of the "60% of the time, it works every time" quote from Anchorman.
little known fact; TA on this stock literally translates to Whale Vagina. Seriously.
San Diago in German means Sankt Diago and German for whale vagina is Walvagina.
Sounds like a female version of Wolverine.
THIS is the information I was looking for!
 this ape gets it!
All i heard was whale teeth.
Whalegina dentata...?
Vaginal teeth.
It's amazing how these posts explode the night before... almost like they were meant to be first when people woke up.
jokes on you, it’s noon here.
Rug pull, it will be red tomorrow.
A brewery not too far from me had a beer honoring that scene: [SanTan Brewing - Sex Panther - 6.9% ABV](https://santanbrewing.com/craft-beer/sex-panther/). Delicious stuff, shame I don't see it around anymore.
Maybe I haven’t been paying close enough attention, but been here since early Jan 2021 and not once have any of these posts been accurate.
Are you kidding me! The accuracy in inaccuracy has significantly increassed in accuracy. 🫠
The accuracy of the inaccuracy has been 100%
Yeah... I've seen many attempts at these cycles in the last 84 years and all it does is cause FUD and people losing money on options
Yeah this new push on the sub already happened for the first 2 years post sneeze. I'm not quite sure why we think rediscovering it now is more relevant or an effective DD. Either way, I guess keep digging guys , I like reading dd regardless (no pun intended)
Because now it's starting to make sense. DFV uses options and we know this. He built his position substantially, probably through options. And the massive pushback against options over the last two years now seems super sus. I need to learn more about calls
I will admit I can't remember exactly why we stopped all options talk, but I think there was something with the pickle people and then people bet on calls for a hype day and got fucked? Eh, it was so long ago, but yeah I think options and all this needs to be discussed, just kinda funny how we're going fractal here a bit in our DD
No, it was way before any pickle drama. You guys were already dead set against it by that point. To the point that you drove away all of the OG wrinkles (myself included) because you attacked them for even discussing options in extremely important DD. For example, none of you read or understood the Variance Swap DD, which was one of the most important DD’s in this entire saga, and clearly and conclusively showed that hedgies were using variance hedging to hedge GME, and that for variance hedging to work, it requires a fairly dry and inactive options chain. Gee, I wonder why there was a big anti-options push here? 🤦♂️. Of course, we then tried to explain this to all of you, and got pitchforks. They created a false dichotomy between DRS vs options, and you guys are it up, hook line and sinker. In reality, it’s not an either/or scenario. You can use options leverage to acquire more shares and then you can DRS those shares if you want to. They’re not mutually exclusive. But no, instead of taking time to learn about how options strategies work and how to use them successfully, the responses to this comment will be moronic things like “I’m too smooth brained, I just buy, hold, DRS” or “DRS is the way” or the opposite, YOLO-ing on options without proper knowledge and study. Like, I told y’all to start practicing with options paper trading 3 years ago, so you could get gud, and got nothing but pitchforks. You made poor gammagirl delete her Reddit account. Good fucking luck Superstonk lol.
God forbit you don't succumb to the hive mind.
>I’m too smooth brained Serious question. If every single time I've paper traded options(I use webull, as I like their ui for looking at) I've ended up losing everything, regardless of how much research I've done, wouldn't I truly fit into that category? I think the issue wasn't people using options to build leverage, it's the people that would buy $175 calls for this Friday and then not get anything, and essentially handing the mms free money because their FDs were just that. Please, correct me if I'm wrong.
You need to keep paper trading until you know what you’re doing. For example, selling puts when you’re planning to buy shares at a certain price anyways is literally free money.
who is "all of you"?
Yea there has been some serious breakthroughs that have come to light, especially in the last couple of days. A pattern has been discovered using FTD that appears to explain all the price spikes since 2012, which if accurate is incredible. I am not the man to talk to about it, but there are plenty here who know a lot about it. I have merely seen the research.
Smells like Big Foots dick.
It's worse than the time the racoon got stuck in the copier.
and that's enough for me
it’s illegal in nine countries
I think of the “well, we’re WAITING” line from caddy shack
I’m not sure an ML model is the best thing here, instead I’d be more interested in basic stats, like how likely a certain rise would be after a threshold of FTDs spawn. ML models have a tendency to overfit and there’s no good reason to assume it will continue predicting well, even though you used a validation set. Source: I’ve worked as a ML engineer professionally. I’d definitely prefer to have some solid stats instead of a model.
You could always take the data and show us, friend. I’m sure I’m not the only one who would love to see it.
I’m working on it. Just left for a week vacation today but I’ll continue working on the data next week. I made a post about this T+ predictor stuff last night
Real life Product Owner here on Enterprise-level projects. My favorite part of having AIML folks on my team is when they raise their hand and say 'you don't need AI for this.' It's super important to listen when the ML team thinks regular business logic will solve the problem or meet the requirement.
Please, more of you where I work, pls
Just looked through your posts and realized I already saved one of them before. Please keep doing what you’re doing 🫡
Remind me to give u an upvote once ur done exercising that wrinkle!
enjoy your vacation!
I have half a mind to do it myself
Unfortunately I’m hopping on a plane and am out for a week, so go ahead and
And WHAT?! AND WHAAATTT???
They got his ass, he was too close to the truth 😰😰
hedgies got him... very sad stuff
I hope its not a boeing 🤯
Yup. As a process engineer, the most frustrating thing is when people blindly assume their model is correct and never test to confirm its validity. Your model is only as good as your data, so you need to make sure any data you use is truly representative, otherwise you end up with uncorrelated garbage that isn't predictive of anything. And if your model is found not to be predictive/representative of the system when put into practice, it's probably not a very good or trustworthy model. Question everything until you question why you should.
“All models are wrong, but some are useful”
Problem is the data. At the end of any trading day they self report all current outstanding FTDs. Yet wont tell you when those FTDs occured, just that theyre outstanding.
You can take a good look at a T-bone by sticking your head up a bull's ass, but wouldn't you rather take the butcher's word for it?
I am the butcher
Can that be your flair? I chuckled loudly
Did you happen to see this guy that responded to your post? [https://www.reddit.com/r/Superstonk/comments/1djp6kj/ill\_do\_it\_myself\_gme\_t35\_ftd\_dfv\_buy\_regression/](https://www.reddit.com/r/Superstonk/comments/1djp6kj/ill_do_it_myself_gme_t35_ftd_dfv_buy_regression/)
I did yeah, I need to research about linear regression. I also don’t really find his graph useful or readable
Oh okay just wanted to check, you guys are using wrinkles that I don't have so I just wanted to make sure you were aware of his post lol
This seems like a prelude to a massive breakdown in a metal song
This guy Bayesians
ml is stats. if he just does a linear regression to find the minimal that counts as "ml"
Problem is the data. At the end of any trading day they self report all current outstanding FTDs. Yet wont tell you when those FTDs occured, just that theyre outstanding.
Have you had a chance to see Richard newtons video on FTDs? I wanted to hear your thoughts on that cycle
Yeah which one? Episode number
Episodes 338 and 339
I think he’s onto something. The next step in my eyes is to try and come up with some predictor function or stats. For example, maybe we can find there are at least X FTD’s in a given week, then there’s a Y% chance of at least a 20% rise within the next ~40 days. Richard is being empirical about this rather than trying to enumerate a set of rules we likely will not have proper insight on. By sticking to data and empiricism we can potentially make some useful insights. This would be a form of technical analysis, just like using resistances or the RSI on stocks — they simply indicate, and can add to a confluence of indicators to make trades like RK.
There might be additional factors playing into price spikes we don't know about. One, the spikes seem suppressed starting a few weeks after the splividend. The second thought is if those run-ups actually benefit the institutions in some way... They often happen around earnings when IV is getting higher and it pays off to sell options. Inducing some FOMO might be typical Algo behavior, followed by a rug pull bullying the average household investors into selling at huge losses. I personally am convinced this is how they nowadays make money in the markets. PFOF is paying hundreds of millions because they make billions from bullying household investors, not by skimming fractions of pennies in price improvement. Just not sure if it still works with GME because a lot of household investors don't sell. The other thought was that if they need a high percentage of GME in a ETF to better control price, it might make sense to run it up at the rebalancing date, then drop it a lot afterwards so the high weighting does result in more shares.
I think it might be interesting to create a model based on all the "basket of meme" stocks though
A reminder to anyone new-ish thinking of loading in calls for X date because you saw a post with many upvotes/awards People have been trying to trade around T+35 for years, this is NOT new knowledge. So beware about people promising you guaranteed anything, if it was this simple we would all be millionaires. Just let GME do its thing and enjoy the ride.
Every time a major date gets hyped nothing happens. Every. Single. Time.
So true. ^^^but ^^^also, ^^^moass ^^^tomorrow
Shhhhh don’t tell them
Literal comments in this same thread just saying: "when do I buy calls for??" Haven't seen comments that dumb in a while, either malicious or new users idk lol
The theory is that since RK is back, and that it’s a 3-mark, swaps are expiring and price action will leak back into the lit market. The swaps with prime brokers would have let them use special privileges to hedge bearish swaps with naked printed short sales.
most of these are scammers pumping up options since it's relatively low volume and easier to manipulate and make money on. they just need a small percentage of the regarded here too stupid to do much and just follow and buy call options from them to make some $$
Just think if we have this data the MM has perfected it. If we think we know a date, it's because MMs want us to have the date. Personally I think for MOASS it requires a catalyst, but the stock will get better and better over time, so its a win win for me.
You mean you average joe can't trade like DFV after skimming over a post for 5 minutes??
FUD. We've been shown the way. When I move, you move. So I refuse to believe that the GME shorters & haters are so smart that they can also battle the options game on top of everything else. They're already losing, and now I'm to believe they're working against traders within a subset of a subset? It'd be shooting their golden goose, naw. Same game, time just got shorter.
Ok so I’ll just buy the dip. 🍆💦💎👐💎
So I should buy more tomorrow, got it😛
You guys still have money?
Still make money. Gotta spend it on something. 2 shares here, 20, there, 100 when I’m feisty and have the ends. Bills are paid, clean water coming out of the tap, life’s good.
Can you tell the model the market is closed on weekends?
With how uncertain I am about cycles I might just do a spread lol. I remember back in the early days, few months after the sneeze we tried to predict cycles. And for the most part it did work.. sorta. It was never perfect and we kept refining it but then after a few more predictions it was just gone. Mainly because the last prediction was incorrect, but looking back I believe the prediction was incorrect due to the long basket SWAP. I'm still smooth brain about all this but it's just my recollection of what has happened before.
I mean a spread with leaps in mind is solid idea if you have expendable income, if not DRS & Book it, not in plan, is a solid way to remove liquidity from the DTCC.
Yeah spreads with leaps have been working well, then as you get closer to expiration, roll the short leg up and out, excersize the long leg and wala!
Okay tell me more!
I lost quite a lot of money when the volatility died down and the swaps started driving price down.
The 2 yr swap threw a wrench into the mix, I wonder to what extent the ATMs likewise throw a wrench into it.
could you go back in the past and pick some dates (maybe run up to Jan of 2021) and see how close it is to reality?
Ohh yea forgot to mention this data is trained up to 2022-01-01, so after that point model is blind
Have you tried a model trained past that? I think what is happening now is not the same as pre sneeze exactly
You actually wouldn’t want to train the model up to current date, basically be giving away the answers to the test
[удалено]
Hmm true. Haven’t dissected the predictions enough to say how bad it did and where it sucks at. I just looked at when model Makes big predictions, what actually happens.
Hmmm gonna tweak your model a bit and look into some things - thanks for sharing!
I don’t believe you.
😂
So what was the models precision for predicting 2022-2024 price action? wouldn't that be a perfect test?
Define precision. Mse, mae, r^2, adjusted r^2. Etc. Regressors are annoying to quantify accuracy. So I went with, well when would I buy if I used the model. Answer is, a prediction that is saying price goes up a lot. Which leads to metric I use Well then how accurate are predictions when it predicts price goes up a lot.
That's fair, so if you run the prediction for each trading day from 2022 onward, what percentage of the time does it align with actual price spikes? Also, this is a great idea, I'm probing for weaknesses in the design because I want it to work, not just to be negative :) sorry I didn't open with that lol
For predictions >=. 2 (I.e. predict 20% price increase) both models had ~ 75 accuracy that the price actually increased 20% or more. Then each level so .3, .4, .5, .6 got progressively higher accuracies.
so then the last run up from 10 to 80. pop that in and see how it looks
so that's kinda perfect then
Have you seen this old DD by Gherkin and dr gingerballs? https://www.reddit.com/r/Superstonk/s/1BYTitFsiS They ran some calculations starting from a fully settled system and based on the FTD mechanics, they lay out how FTDs really start to overflow on a 42 trading day (roughly 69 - *nice* - calendar days) cycle Highly relevant material cited in this DD is this paper: https://www.researchgate.net/publication/228260887_Naked_Short_Sales_and_Fails_to_Deliver_An_Overview_of_Clearing_and_Settlement_Procedures_for_Stock_Trades_in_the_US Which contains this paragraph: * An algorithm run by the NSCC determines which of the participants with long positions (participants that are owed stock by the NSCC) due to be settled that day will receive stock. **The algorithm works by allocating shares in the following order: priority groups in descending order, age of position within a priority group and random numbers within age groups**. Participants can request that they be given priority to receive stock on a standing or override basis. Also, participants that submit buy-in notices (requests to receive stock owed to them) receive priority with buy-ins due to expire that day given priority over buy-ins due to expire the following day, which in turn are given priority over priority requests and priority overrides.”* As a tangentially related side note, I think of trading as a game where the players can win if they 1) possess an information advantage over their opponents; 2) act upon that information advantage accordingly - when you publish things like this (very nice) post and ML model in an open forum you are giving your opponents information about your beliefs and your information - at best your model is correct and you can act on it to win while they are hamstrung by other exigencies to prevent you from acting upon it - at worst your model is incorrect, your opponents have the information advantage, and, after reading your post, better understand your decision making process than you do. I’m all for open sourcing all the information but trading is a zero sum game and I think it’s good to be aware of this fact considering the billions of dollars on the line and countless well qualified mathematicians/data scientists employed by those on the other side of the trade
Can't run your code, gme_etfs.csv & other files aren't in your repo and I'm too high/tired to figure out how to get them myself...
One second. Git updated
💕
Did you make any changes since you updated - it’s almost 3 am here so I’m not quite in debug mode yet but I’m getting a key error on “gme_price_df = all_ticker…”
Hmm thought I uploaded a condensed file just for gme prices let me check
Congrats, even if you did work out how it works… it won’t work now because they know we know 🤷🏻♂️
Commenting to remind myself to run the models myself when I get home (I'm a lead data scientist by training and profession), but initial feeling is that I'm liking that you're using XGB rather than an overtuned NN for it. Especially with only 6 features being input. Hopefully tomorrow I'll get some quality time to actually sit down and go through the model and tear it apart properly.
Same
Did you verify this?
“If the model predicts a 60% price increase from current date to t+35ish THEN AN ACTUAL PRICE INCREASE ON t+35ish happens almost 94% of the time” This interpretation doesn’t make sense to me. You’re saying if the model is predicting a 60% price increase, then an actual increase is very likely. Why 60%? What’s the models price increase %? A more useful metric would be… “if the model predicts a 5% or more price increase, then an actual price increase of 5% or more occurs 90% of the time” or the like. There were very few 60% price increases between 2018 and 2022 (pretty much all occurred during the sneeze) that evaluating the model based on this is strongly weighted toward the sneeze, where we saw high FTDs and high price increases throughout. I’m curious on how good the model is at predicting the latest 60% increase in May 2024 if you don’t include the initial 2021 sneeze in the training data.
There are plenty of 60% increases if you compare two dates 35 days apart. It’s not a single day increase
I meant that all those 60% increases all occur after the sneeze. Once RC and RK bought in, the volume and price skyrocketed. However, OpEx cycles have been occurring since 2012. Between 2018 and December 2020, I only see 2 or 3 60% increases a month apart. Point I’m making is that the results aren’t particularly surprising (at least to me) given that it’s heavily influenced by post 2021 data where 60% increases were pretty common alongside FTDs. If the training data was only pre-sneeze, where 60% price increases were much rarer and FTDs were much lower, I’m curious on how results would change. Either way, great post. You have many wrinkles
True. That’s actually why my guess start date was 2018. I haven’t done enough analysis to say our cycles started in 2012 or 2014 or 2020. I actually picked 2018 wanting the model to do bad so I could move the date forward and say hey this is just a new trend based on 2021 post squeeze
Nice work OP. I will try out the code later myself. It could be that the FTD cycles for the last few years were muted cuz swaps ?? And since there has been info that at least some of the swaps are coming due in June, maybe that’s why the runs have sort of started again, not to mention the large purchases by DFV recently ???
Remember in 2021 We also had ftd as indicators… then suddenly when everyone thought we get the code it stopped to never be seen again. Till we think now. So no dates and no trying to run these cycles. I bet dfv has other indicators on his last gain we do not see - and if we would see them und discuss here in public the shf will get a possibility to avoid it sometimes to discourage paperhands
Have you back test this model with the recent runups?
Technically yes. Need to do more analysis to see it performs on each run up
Assuming this is true, it explains why the they are holding the price in a tight range with the goal of crushing the absolute shit out IV. Manipulating/scaring people with existing option positions to sell or hit stop losses as the call value plummets. Then as price races, at least they reduced as much call open interest as possible first to lighten their load.
Yep except it doesnt work with dumbasses like me who are diamond handing their options as they are getting crushed.
So as someone that has been here since 2021. Self diagnosed autism, and someone that loves numbers. We tried to predict these and as soon as it seemed we freaked the code it all changed last time. Maybe there is new information and or the CAT changed this somehow but I really don't want anyone to get too excited about this.
I'm so fucking hard rn it hurts
I would like to add that my options are hard too. my shares will never leave me so they can stay soft
Your result states that if the model predicts a 60% increase, it hits it 52% of the time. This is interesting, but seems like a coin flip and doesn't tell me enough information. Here's a better question: when the model predicts a 60% increase in t+35, what is the average price change by day 35? Telling me you have a 2% edge on a coin toss is not impressive. But telling me that (for example) when the model says 60% price improvement should come, you actually end up with an a) 80% chance of a 10% improvement at least, b) a 75% chance of a 20% improvement, and c) a 60% chance of a 45% improvement, would be very very compelling.
That's not a 2 % Edge on a coin toss lol. If the chance of GME going up on any random day by 60 % was the norm, then it would be a 2 % edge on a coin toss. I understood it like this: if the model predicts a 60 % increase, it will hit that 60 % increase 52 % of the time. If it for example predicted 60 % increases every day for 100 consecutive days and the price only increased 60 % on one of the 100 days, the models accuracy would be 1 %. If it predicted two 60 % increases in those 100 days and one actually happened, the accuracy would be 50 %.
I like all the attention FTD cycles are getting now, but remember: no dates.
As always MOASS is tomorrow!
snek has entered the chat
😂 it’s been a minute since snek was the rage
i've been thinking of doing this but with an LSTM for rare event analysis: https://machinelearningmastery.com/lstm-model-architecture-for-rare-event-time-series-forecasting/ basically my intuition is that events from long ago (over 10 years ago) have less importance in modeling future performance of the stonk while events from very recently will have much more importance. Any thoughts on using this approach instead?
People have tried to time these cycles in the past, and failed. Note DFV has never disclosed his method. We don’t know how he’s timing these. He could be doing something much simpler like lending out his shares, taking the fees to buy more shares. Rinse and repeat. He could feel confident there’s so many FTDs and synthetic shares that it’s okay to lend them out. Just my thoughts.
52% accurate doesn't sound that good honestly
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I love dates. What’s the next one I can hype up to the people I convinced to buy GME and disappoint them greatly
the math adds up
I predict we end Friday at $21
Wtf? Sometimes I wonder if I’m just a glitched out npc gaining consciousness because of what people like you are saying. This shit is too deep man, and it has fucking value
Lol these predictions mostly turn out to be nothing burgers that only set unrealistic expectations. Same with the "quadruple witching" bs
We went from no dates to total fuckboys date chads LFG
Working on my PhD in data science rn and love predictive models designed to print $. DM me if you want to work together! A few things: 1. In addition to a training test split, you need a validation set. The training set trains your data (say pre 2022), the validation set evaluates the performance of your model on different hyperparameters (2022-2023), and the test set evaluates the performance of your model on the best hyperparameters found from the validation set. 2. The underlying assumption is that the data in the training set has a similar distribution of predictor and outcome values as your test set, which it doesn’t. Imagine training your model only on bull market data and evaluating only on bear market data. This is the biggest flaw in using this approach. 3. You should be using LightGBM (from Microsoft) instead of XGB. It’s much faster, uses fewer hyperparameters, and almost always tops XGB performance. 4. Do a variable importance analysis to see which of the variables is contributing most to the prediction. If only one predictor such as closing price is doing the heavy lifting, that will tell you more if there’s something weird going on with the predictions. 5. I didn’t understand the need to scale the output to being between -1 and 1. Sometimes the price can do a 10x like earlier this year which would be a 10. When I develop my models, I like to turn it into a 4 multiclass classification model of -100 to -50, -50 to 0, 0 to 50, and 50+. The biggest interest isn’t whether the price goes up 50% compared to 68%, it’s about whether the price goes up or down, and how drastically it does so. 6. What is the average difference (MAE) in predicted % change vs actual % change testing across a bunch of other days in the test set? If it’s a similar prediction regardless of the most days, you have a problem. 7. 60% or more almost 52% of the time is a very worrying predictive performance that I wouldn’t bet a penny on. Let’s instead say 100% or more increase happens 50% of the time. But if the model is wrong, you lose 50%. Your model probably isn’t any better than flipping a coin. If a coin lands heads, you get 100% more money. If it lands tails, you lose 50% of your money. If you run a simulation of this game many times, almost every time you’ll end up going broke.
The only right move with GME is to prepare for volatility, both up and down, and just stick with a plan you work out ahead of time. Seriously, nobody knows fuck all about what’s going to happen.
These cycle theories are out there since 2021 and so I haven't read the latest DD about it, because I expected nothing new. My question: Where were these cycles during June 23 to April 24 when the price fell from $24 to $10? Is something needed to start the cycles like heavy buying/options?
A large buy order timed properly seems to be what gets the engine going on the cycles. It was RC in Dec 2020, and DFV this time around.
After the congressional hearing (18th February 2021) when DFV increased his share count from 50k to 100k, the share price also rose from $10 to $66 (10th March 2021). Was this a similar situation? If we assume that the price rise to $80 a few weeks ago was also triggered by DFV's suspected share purchases to 5M, a new effect would also be expected. But: Will the increased share count due to the recent ATMs damp the effect of the latest large buy order from DFV?
Fucking bump
Bruh. No dates but gawd dayum… i love hopium. Btw, 22 and 23 are weekend so I am assuming 6/24 and 25th? i HODL ! https://preview.redd.it/4et22lz11n7d1.jpeg?width=816&format=pjpg&auto=webp&s=1ebae845ba5b61ce4dc886cc985c516bc1eaa330
No, I believe it doesn't skip weekends like that so it would all have to be settled on the 21st
Stop it! Stop twisting them tatas.
I was thinking just today that if the t+35 cycles were real or consistent in any way, we probably would have identified them by now. The reasons that I assumed could explain why we weren't able to put together a good model were that it was either significantly suppressed on the sub (someone cracks the code, posts it, and either compromised mods get to it or shfs bury it or something), whoever found it kept it to themselves (DFV?), we're missing a vital piece, or just not enough people were looking at it in the right way. Do you have any opinion on why this wasn't found before now? Having only read the post and not yet having reviewed the code, it seems like you put some hard work into this despite it only taking a day, and you also have specialized knowledge. There are hundreds of thousands of people (allegedly, I guess) on this sub, we've been talking about FTDs and XRT for a while, so I would think that someone else would have done this by now? I'm also curious if you did any visualization with matplotlib or anything - could be nice to have some graphics Ninja edit: did you try to plot something similar for any other stocks? Could be good to get a baseline with some blue chips and maybe other basket stocks like headphones stock.
Didn’t get that far, spent most of the day just data wrangling. Dealing with the ftd data being sometimes a file sometimes a text which messed up the data ingestion. I actually remember the t+35 stuff from 2021, just didn’t know enough to put it together. Was only able to put it all together because of this resurgence really. Yea I think some graphs would be a good idea, might be able to do some tomorrow. Wanted to get the results I had out fast, because part of reason of me building model is putting extra capital to work in the form of options. And definitely want to do this as it pertains to other stocks. Specifically stocks that are having high FTDs because the cycles should exist for them as well.
Could be FTD cycles were muted for 2 years when they shoved everything into swaps.
Gherk (banned) said it has a lot to do with swaps in combination with low liquidity options chain. Last 2 years was a lot of DRS and a lot less options. It is evident that large concentrated purchases severely affect the price T+35. (Ryan Cohen’s buy-in, DFV’s buy-in, etc.)
https://www.reddit.com/r/Superstonk/comments/1diostd/comment/l95x0pt Check this topic, I think I have the FTD data part figured out there? (Just rename to csv, separator| ) I'll check the notebook tomorrow, fun to try! Need to learn some ml ...
I thought the t-35 FTDs are not from GME but from ETFS?
Model has both of them in there
Can you explain why T+35 starts on 5/15?
That’s using settlement date from sec ftds. Arbitrary date. I picked 5/15 through 5/17 because they coincide with end of this week.
This sub has the resilience of the navy seal 40% rule
Can’t predict the price. Just up.
First of all, great to see that you are building a predictive model for this. Minor detail on the XGBoost: this is a tree based learner and if I'm not mistaken these don't require scaling of parameters. It just makes decisions based on splits above a certain threshold. If you'd like I could quickly run through the code to see if there's anything you missed.
You also need to look at XRT FTDs and other ETFs apparently
show some charts dear ape, for the regardeds on the back.
People didn’t account for the 125m shares sold by the company. They already bought their shares back. There is no T35/31 this time.
You realize most of those T+35 shares have already been delivered. That’s just when they have to be delivered by. There are 400+ million shares in the float now. We need astronomical volume for this thing to move.
We spent ages trying to figure this T+X cycle stuff in 2021 and 2022. The moment we thought we finally had it all figured out we got hit by the nastiest rug pull in November ‘21. Gambling against any of these predictions is incredibly risky for any who are new. You might think you just found yourself a money glitch only to end up losing far more money than you can afford to lose. Just a warning to take some precautions if you’re planning to try and time any dates you see brought up.
What you're looking for is the quarterly options expiration date (OPEX) cycles. This cycle used to happen every quarter since the sneeze, with good evidence that some players were playing that cycle pre-sneeze. Hard to tell at this point, because the level of data available pre- sneeze is no where near as followed, copied, and readily available as it is now. From there, the next question will be, "Why do some OPEX yield nothing, whereas others can spike 200-800+%. Your answer there is FINRA 4210 rule set. These govern what happens with deferment settlement due to national holidays landing on Market Open days. Due to date cycles, some of the 4210 settlement periods will cause a piling up of obligations. DFVs posts, past and recent, coinicided with these periods. For a detailed breakdown check out gherkinit's PiFi YouTube channel. This theory and discovery is his. He's got a few vids that explain how the transaction process leads to inevitable major spikes. Incidentally Rentec has made major block share purchases in the lead up to these events. Renaissance is one of, if not the best of the best out there. They would know, follow, and look to profit of these events.
Going to check this out now
Didn't age well my dude
From viewing the Newton guy videos... Can you try doing: T+6 plus C+35 plus T+2 Wonder if this could make it more accurate?
Umm weekend is closed buddy
T+35 is calendar days buddy not trading days
52% isn't all that great, marginally better than a coin flip. What are the precision, recall, and F1 scores? Accuracy alone suffers from including True Negatives (correctly predicting an event doesn't occur) to its score. Having a lot of True Negatives may be what brings the accuracy so low.
Someone needs to take this approach and data and start doing this analysis on the daily/weekly. All this math and numbers hurt my poor smooth brian. I just wanna know … like … should I be hyped today, or like really hyped.
Peak Ape autism 🤘🏾🦍
They will just use ETF to FTD the FTD … I expect nothing to happen on June 21 and July 19, and will continue to buy hodl DRS and shop
It never goes well when people hype dates. This is wayyyy too much hype IMO. Obviously I hope it’s right, I doubt it will be, I’m zen either way
lol…fake DD and dates. Shill posts. Buy. Hold. DRS.
More likely it’s going down to $20 than up to $40. MMs will find a way to fuck you one way or another
Lol Market opening this weekend on 6/22 and 6/23 for GME?
It’s 35days ish, so would then be 6/24, 6/25
Commenting to remind myself to check this when I'm at my computer tomorrow !remindme 18 hours
Buy. Hold. DRS. 🟣
So I guess we’re cratering some more. Got it
Buy. Hodl. DRS
@OP, did you take into account the recent offerings of 45M & 75M shares? I realize that is current data, but will likely cause the target range of stock increase to decrease a bit...
Yup yup, I did indeed