The Problem With GEX Platforms

If you haven't been living under a rock, you probably noticed that the whole trading space is now talking about gamma exposure. And as I said in a previous video, gamma exposure is a great tool for traders together with option flow to really get the full picture of what institution, retail traders, and market makers are doing in the options market to get really valuable insights, more precise entries. But there is a problem, a problem I didn't know until after spending months researching and trying different GEX platforms. And with this video, I want to save you the money and time I spent and cut through the noise and the bullshit. Because with AI coding, a lot of these new GEX vibe-coded platforms started popping out of nowhere and claiming to display market makers' gamma exposure data. But the problem goes wider than vibe-coded platforms, because also some of the big names and the most popular platforms sometimes carefully avoid talking about these 2 things that you should always ask yourself before considering spending your hard-earned money into a GEX platform. Number one being, what is the source of their data? And number two, how is their GEX actually calculated? So in this video, we'll give you a checklist that you can use to know really what you're buying into and maybe avoid buying something you might not really want to, and how to distinguish proper GAM exposure from the very limited, naive version. And to really understand it, we need to start from how is GEX Typically calculated. The first ever gamma exposure visualization that I came across was this one from squeezemetrics.com. And as you can see, we are somewhat in the daily chart of the S&P 500, and for every day we have a different level of net gamma exposure that is plotted in this sort of yellow line. When the chart gets yellow, it means we are in a negative gamma exposure. When the chart goes purple, it means we are in a positive gamma exposure for that specific day in time. And this is the first raw version of the GEX. So these guys from Squeeze Metrics made did completely for free and posted this research paper where they basically proved that when gamma exposure is positive, the movement of the S&P 500 for that day would typically tend to be more compressed, less volatile. And the higher the positive level of gamma exposure, the more you can see was compressed. So positive gamma exposure equals compression in volatility. Instead, when gamma exposure was negative, you could see you have sessions even at -10% in the stock market or +10% in the stock market. You could see more volatility, confirming the That market maker gamma exposure was potentially predictive for the session volatility. Negative gamma exposure for expansion and positive gamma exposure for compression. And this was awesome. Imagine this paper was from 2017, and it was already pretty revolutionary for option traders. But you should imagine this gamma exposure like one of the first cars that were invented. If you compare it to an 812 super fast Ferrari Competizione, of course nowadays we have better tools. But what is important here is how they calculated GEX. Because they calculated gamma exposure by multiplying gamma times the open interest. And this was the basis for most of the GEX platforms that we see today. And this open interest over here is the data that tells us how many positions in options are still open right now. So to make it simple, if Trader A buys to open a new option trade and Trader B is the other side of that trade and sells that option to open a new option trade, Then the open interest is 1. 1 contract, open interest is 1. If more traders open new trades, open interest rises, and then it can go either one of 2 ways. Either they both close the trade, and at that point the open interest is 0. That option doesn't exist anymore, or the option expires and ceases to exist, and the open interest is also 0. This is how open interest works. It tells us how many open trades are still in the market. And so the question they asked themselves was, who between Trader A And Trader B is the market maker. So how could they figure out what the market maker exposure was just based on open interest? Because this was the only type of data they could have. So as you see in the whitepaper, they started making these 4 assumptions: that all trades are facilitated by market makers, and that market makers are mostly buyers of calls and sellers of puts, which is not always true. And by calculating GEX with these somewhat naive assumptions, still they were able to find a strong correlation Between negative gamma exposure and high volatility, and positive gamma exposure and lower volatility. But this was done in 2017, and after 2017, something happened. In 2017, zero DTE options or daily option options expiring today were less than 6% of the volume. But after 2022, when CBOE released the proper proper zero DTEs, the dailies that you could trade every single day, the volume of zero DTE skyrocketed up to the point where today is approximately. 64% of the total volume. And this brings a problem because this version of the gamma exposure here was using snapshots of open interest at the end of each day. But at the end of each day, most of the option-traded zero DTEs are already expired. So in this version of the GEX, you did not have zero DTEs, which, as we discussed, are more than 50% of the volume. And so what? How do we do it now? What can we use to calculate today's gamma exposure as end-of-day open interest is not enough? And the answer is option flow. Option flow is basically times and sales of options. You could define it as the order flow of options. And when it comes to option flow, there's 3 ways you can go. The first one is just scraping data from other websites or from brokers, which translated means illegally stealing data from brokers and other sources, and even more illegally distributing all of this data without any license and vibe coding your GEX platform by stealing data somewhere else. So the first option is definitely not one you're going to go for. The second option is taking raw order flow from OPRA. OPRA is the Option Price Reporting Authority. They give you the license to redistribute option data. So a lot of platforms started using OPRA data, taking this option flow data And doing a very similar thing to what Squeeze Metrics did, but on a real-time basis, on a daily basis with zero DTE options. And as we will see, this is also very problematic because the time and sales of Oprah looks like something like this. You know how much size was traded, if it was a put or a call, at which strike, which expiration, how much was the premium of that option, and at what time. But nothing here tells us who the market maker is. And market makers are the only one or the biggest ones in the market that need Hedging. So how do we do this? We still have to do some naive assumptions because we have no data. We just know that there was some puts and calls traded at that price, but no idea who the market maker actually is. So a lot of these GEX platforms still have to make assumptions once more. Was the trader closer to the bid or to the ask? Well, maybe if it was there and not at mid-price, then it's market makers. Or maybe not. Maybe yes. Another one is how did the trade impact the volatility surface and other quote-unquote proprietary models that you simply don't know because all these GEX platforms do not tell you, hey, this is how we calculate GEX. It's our proprietary stuff and we will not release it to the public because it's a commercial secret. It's not good for you if you buy a GEX platform that does not tell you how they calculate GEX, which doesn't mean necessarily good or bad or it works better or it doesn't work better. It means that you simply Don't know. So it's up to you to take the bet. And unfortunately, this is still most GEX platforms in the market. So going for Oprah GEX platform is okay, I guess, but there's very big limits. But luckily there is a way, a definitely more expensive way, a different version of option flow that revolutionized how we display gamma exposure. And that source, my friends, is CBOE data. That for a whopping $28,000 a month that we at DeepCharts pay, by the way, don't tell you just how much was traded, but was it a buy or a sell order? Was it to open or to close a trade? So you can know the actual open interest. You actually have that data. And of course, the size, the type, the strike, the expiration, the premium, the time, and most importantly, the trader Type. Oh yes, CBOE actually tell us if the trader behind that buy to open or to close trade was a regular customer, a professional customers trading huge size, a broker dealer, a financial firm, or there we go, a market maker. CBOE, the exchange, the Chicago Board of Options exchange where all SPX options are traded, can tell us if. The trade was facilitated by a market maker. It does not provide market maker open and close flags, unfortunately, but the right software rebuilds the net positioning thanks to these classified flows. It is more expensive, but if we're trying to truly understand market makers' positionings in options, this is the only true way we can calculate the market maker's gamma exposure without having to make assumptions, without having to Guess knowing that it's a market maker comes from an actual CBOE classification, not a guess based on a print or inventing fancy proprietary formulas. So here there's no need to assume who the market maker is. And this unfortunately is done by a few very expensive GEX platforms, or in this case by DeepGamma, 14 days for free. And as you will see on Sunday when we finally release these 14 days for free with the link you find in the description, and you're going to see that is going to be much more affordable because remember, it's $28,000 a month. Most platforms do not have the audience that we have, so they have to charge a higher price. That's understandable. But because we have a wider audience, we can afford to bring prices down for everybody and make actual real CBOE gamma exposure available to everybody. But it doesn't need to be DeepGamma. If you want to try other platforms, it's fine. I'm not here to promote this one specifically. I'm just saying CBOE data is superior because it tells you who the market maker is within all of those huge amounts of trades. And there's no need to infer GEX. But I understand this is very technical now. It's hard to visualize. So I took all of the GEX platforms I could get my hands on and divided them between CBOE ones and OPRA ones. And I've basically divided them so that we can see what's the difference. Here, for example, on the CBOE side, we can see this is DeepGamma, for example. This is another gamma exposure platform that uses CBOE data, and you can see that the levels are exactly the same. This big level here is this big level here. This positive one is also here. This big one is also here. This other positive one is exactly here. This cluster of negative gamma 4 levels is the same here. It's the same, this positive one, and also this one over here. It's exactly the same chart. So that's CBOE data. You can choose either or. I'm not telling you which one to choose, but at least here you know the data Data is the same and you know how the calculation is. These are the CBOE one. And when you start looking at the OPRA one, you're going to start seeing that there's a lot of differences. This is a GEX platform that uses OPRA, and you can see that at 7735, there is a huge negative gamma exposure level that through CBOE data, it's actually the opposite. And where there's supposed to be a big negative gamma level at 7740, at 7740, there's a small positive one. Some level might be similar, but here this cluster is simply absent here and there's just positive gamma ones. And this was a screenshot taken at the exact same time. If you move to other Oprah data sources, they will just give you the total gamma exposure and maybe claim that this is gamma exposure. Well, it's not really market makers' gamma exposure. It's just the gamma calculated based on the entire market on Oprah data, which is a completely different thing. It doesn't mean it works better. It's it is better, or you know it's just a different type of data. It it all depends on what you want to see. These platforms are not problematic. They're not a problem. They're not doing something wrong. They're just showing you something different. So if you want to look at market makers' data and gamma exposure data based on actual market maker positioning, CBOE is the only real way. Also, this other platform at the same time showed a very similar profile. This other platform also call it GEX, but these are not even trying to understand what's the market maker GEX. These are just showing you the overall GEX of the market. So the difference is radical. And CBOE data are typically more expensive, not in the case of DeepGamma, but at least you know what you're seeing. Here, you're not really sure. So here is the checklist to understand if a platform has CBOE data or OPRA. The first thing you can do is check the websites and maybe in the FAQ section, ask if that gamma exposure platform has CBOE data or OPRA data. And there's other signs. CBOE data, for example, only has 1-minute updates. Because it's way more detailed data, so they don't provide a real-time flow. Oprah data instead is real-time, which is also kind of an advantage, if you will, if you're just looking at option flow because it is real-time, but you have no idea who is opening those trades. So there's always a trade-off. On CBOE, it's only SPX, which is, by the way, the biggest traded option. It's $3 trillion in daily notional volume. Oprah has also NDX, QQQ, SPY, and smaller options. So unfortunately, we can only get the cool gamma exposure only with SPX. With NDX, QQQ, SPY, unfortunately, all you can see is inferred gamma exposure. So if you see the update is every minute, if they say it's CBOE, if it has only SPX, then the data source tells you which one are the market makers. And you can also check if they have customers, professional customers, broker-dealers, blah, blah, blah. And there is no need to use naive assumptions. Here with Oprah, you need to infer GEX. You need to do some assumptions. Here, the GEX you see is based on real market maker data. Here, the GEX you see is based on something else, which again doesn't mean good or bad. It means that is something you just don't know. So before you choose to go for either or, always do your research. Always ask questions on how it's calculated so that you know, so that you can make a conscious consumer choice into what you're actually buying. This was the second video of this gamma exposure series that I'm making on this channel. In the next one, we're going to take a look at the other side of the debate, the debate that goes into the actual hedging activity of market makers. How big is the effect potentially in the markets? And we're going to get deep into what gamma truly is, understanding what charm is and vanna and why the last part of the session can be probably one of the most important ones. For assessing hedging flows and a lot of other really cool stuff. So stay tuned by subscribing to the channel. So I'll see you in the next video and I'll see you on Sunday.