Blind Spots Levels

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Good morning, everyone. This is Fabio, CEO and founder of Mentor Q. Welcome again to our product training session. And today we're going to talk about blind spots.

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So very, very excited. We got a lot of questions and the blind spots are one of our most powerful tool to identify hidden risk and opportunities in the market. And today we're going to go over the methodology, why they matter, how can you use them, and we're going to also share some very nice examples. So this is kind of like the agenda for today. So, so first we're going to go over what blind spots are, why we build them, why are they relevant, and how can we use them.

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And then at the end, we're going to do a live Q and A. So please, guys, send us any comments. We're going to reply to that at the end.

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So let's start with the definition of what they are. So blind spots are price zones where the market is likely to react sharply. But these zones aren't always obvious from standard charts. So they're not the typical support and resistance area. They're based on more advanced models.

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And we're going to go into more details in a second. They arise because the markets are interconnected and price movements in one asset can actually influence the other asset in very, very different way. So understanding how different assets interact is very, very important to, to make decisions. And what we've done at Mentor Q is we've developed the concept of blind spots levels to help traders identify overlooked areas of market movement. And those can become hidden signals that can help you either confirm a trade, react to a trade, or even like, manage the trade with your trading plan.

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So what blind spots are not. They're not the typical support and resistance levels. They are derived from our proprietary models that combine option positioning, gamma exposure, volatility structure, and more.

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So why are they relevant? Because they reveal things that traders cannot see. So they often mark liquidity areas or hedging pressure zones coming from correlated assets. And when price eats those areas, market makers might need to adjust positioning, and that could actually trigger sharp volatility moves, sharp liquidity moves, etc. So retail traders typically have no visibility on these levels.

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So spotting them can give you really a true hedge and through advantage when trading and when confirming your trade. So basically what they do is they can help you basically understand when we are facing reversal areas so that you can avoid being trapped in the price action, and you can also use them to position yourself to get a better hedge in the market. Let's talk about asset coverage. Right, so blind spots are available on many different assets. Firstly, we built blind spots for futures indices and ETFs.

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So for those who are trading SPY or QQQ, you have blind spots there. In May we released blind spots on Forex. And basically today we're also going to show you the new blind spots levels on major stocks, in particular our Max 7 coverage. So now blind spots are really covering a large variety of assets. Let's now look at why we develop them.

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Let's try and go over some of the methodology and then of course guys, feel free to share any comments or questions. So blind spots are leveraging three critical data inputs and we're going to share why each one of them is essential. So the first is option positioning, right. Option markets reflect what advanced traders sentiment and expectations are. So if we are able to analyze the net buying and selling pressure coming from the option market, we can actually gain insights where the large players are positioning themselves, where the areas that they are looking to target are, and what are the areas that we should be aware of from a risk management perspective.

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So by looking at this data, we can actually reveal potential areas of support and resistance that might not be visible in the underlying asset price alone. And then of course, option positioning can help us highlight where market participants are actually putting their money. So option data is actually forward looking, while support and resistance coming from traditional technical indicators are actually looking at the past. So the advantage of having option data with your chart is that you're actually looking at the future and looking at areas that the market is targeting. The second input is momentum.

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So momentum can help us measure the strength of and direction of price movement. And basically understanding momentum divergence can really help us get some really good insights on what are the areas that we should be looking for. And incorporating momentum really can help the model identify when the price can be vulnerable for sharp moves, even if we don't see a traditional pattern coming from our technical indicator. So adding momentum can can give us a lot of value there. And then finally, the third aspect is cross asset correlation.

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We're going to show you some examples very very soon. But basically for it's important to understand that markets are interconnected and the move of an asset rarely move, rarely happens in isolation, right? So if you trade stocks like Nvidia or Tesla, you need to be able to analyze what's going on in the overall market and what are the assets that can actually impact the asset or the ticker that you're trading. So by analyzing cross asset correlations, the model can capture how price movement in one Asset can actually influence others. So for example, if we see a shift in a major commodity or currency, that can have a ripple effect through stocks or indices as well.

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And that's very, very important. So what the blind spots can do is really uncover those hidden signals coming from correlated assets that can actually impact the price action of the asset that you trade. So by combining option positioning, momentum and asset correlations, the blind spot models can create a comprehensive, data driven view of where the market reactions are most likely to be. And basically those blind zones can actually help you understand when to take a trade, how to manage your trade, and how to manage your risk as well. So the goal in the end is really giving you access to a tool that can provide you an advantage or an edge.

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So going back to obviously the concept of I asset correlation, again, very, very important to stress it, markets do not move in isolation and many, many assets are highly correlated with each other, meaning that their prices tends to move together because they share common drivers like for example, macro conditions, interest rate, sector flows and so on. So understanding these correlations can help you really improve the timing of your trade, increase the confidence in your trade and reduce the risk. This is a very nice example and we try to simplify this in a chart. So for example, if we look here, we see kind of like a knowledge graph structure where we have our SPX in the left and we can see that SPX is highly correlated with other assets like vix, qqq, spy, even Bitcoin. And then on the other hand, we have our NQ and ENQ is highly correlated with our Max 7 companies.

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And then of course at the bottom we have things like gold that are highly correlated with currency and other factors. So by understanding this correlation and how this moves, and this is of course complex model that we have on our back end, can help you really get a really good information on the asset that you trade. Here we see some typical correlation that probably everyone is aware of, but it's very, very important to understand. And this is like the correlation between stocks and bonds, between gold and US dollar, between stock indices and commodities, of course equities and vix, very, very important oil versus currencies. And then of course the US dollar versus our emerging market, emerging market currencies and so on.

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So let's take another example. If we look at the Max 7 and this, what you see here is the composition of the top holding of the SPX. So if you look at the top 10 holding, which is about 38%, the max 7 account for the majority of that so seven companies within the index are actually driving the price action. So if something happens with Nvidia or Tesla or Apple, that's going to have an impact on the spx. And even if you don't trade those assets, you need to be aware of things that are happening there.

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So this is a very, very good example here. This is Nvidia on the left and NQ on the right. So when one of these correlated assets hits a high, like a strong gamma level, this is where a zone where market makers typically have significant hedging exposure. Right? So this action can actually spill over correlated assets.

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So here what we see is Nvidia hit one of the big gamma levels, our JAX5 drop all the way down. And as a result we don't have the gamma levels on in queue because we want to show you how the correlation between that move can actually impact the other. So here you see a very, very good example. So imagine why is this important? Because again we saw from the previous chart that Nvidia accounts for about 80% of the index.

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And if Nvidia breaks through a level, a very important level, the correlated assets like SPX or NQ or NDX will be impacted. And that's why having blind spots together with gamma levels can give you a very good key advantage. So how can we use blind spots? And we're going to show you some examples. We can use them in really different ways, right?

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So we can use them as target zones. So, so if you are in a trade and you see that there is a blind spots area right above it or below if you're short, then that could be an area where you could take potential partial profits. Or if you are to the opposite side, you could actually use a stop loss target. They can also be used for entries. So you could actually use the blind spots when the price approaches a blind spot.

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And if that's in line with your bias, then it could be a great place to enter a position for a reaction. They can also be used to manage risk. So again, let's say that you are thinking about opening a trade, but you see a very, very strong blind spot against the direction. Maybe that's a signal that you might want to consider and take into action. And then of course for confluence.

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So imagine that you have a strategy, you have an edge, but this strategy can help you use other factors. And together, combining blind spots together with our gamma levels, maybe our Q score data and your own technical zones can actually increase conviction and increase potentially the profitability of your strategy. So let's go over why we created them and then let's give you some examples. When we launched our gamma levels, we did not cover futures at the beginning. So we had a lot of futures traders that wanted to use gamma levels on futures like ES or nq, but they were not able to do that because we didn't have the data just yet.

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So what they wanted to do, what they were doing at that time is convert levels coming from an asset that would move closely together like SPX or or qqq to the futures that they were trading. So they were converting SPX levels to yes or QQQ levels to nq, which is still very possible in the platform. But then we took it a step further and that's when we created blind spots. So let's look at this chart here. Right.

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Let's see if I can show you. Okay. What you see from this chart is 6 different graphs. This represents the net gamma exposure of the index on the left. So we have NDX at the top and SPX at the bottom.

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And then we have the ETF, so QQQ and SPY, and then we have the future NetGam exposure. So as you can see clearly from just looking at the image, the three option chains are completely different. So even though those assets are are moving in the same direction and they represent the same kind of market, same asset, the actual option chain is completely different. So if you are not looking at this type of information, then you could potentially miss out on really interesting opportunities. And that's why it's important to understand how correlated assets are moving.

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And I want to also share now an example right in the platform. So let's go over an example from today. So today we look at SPX, right? So we open up the dashboard August 18, 2025, and we immediately want to look at the Q score. So when we look at the dashboard here, we see that we are in a neutral position on spx.

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So the option activity kind of like is neutral from 0 to 5 is our score. We are at the score of 3. So we are not, we're not bullish, we're not bearish. So we are really in a neutral stance. Our momentum is still very high and we have a slightly negative seasonality.

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But if we are looking at the data, the option chain, we are in a positive gamma condition on spx. And if we look at the matrix overall, we see positive positioning across the full option chain, right? So that means that clearly we're still in a positive gamma environment. Our swing model is still in a bullish Bias and that's very, very interesting. But what about if we move and we look at a correlated asset like spy?

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So in this case the assets represent the same underlying factor, the same market, the US top 500 companies, but we see a completely different picture. So we see a very low option activity. On spy, we are in a negative gamma condition. On spy, we are also in a bearish bias coming from our swing trading model. And if you look at the option chain, we also see a lot of negative positioning across the next few weeks and months.

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So why is this important? Because always you need to look at asset correlation and you need to look at what type of investors are trading both assets. So if we go back into our presentation, let me just go back here.

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So let's look at the different chains and let's look at why this is relevant. So when we look at spx, typically we see a lot of institutional flows. SPX options are cash settled. So typically large institutions might use those for short term hedges and so on. When we look at spy, SPY is mostly used by retail and asset managers and typically they have a longer time horizon.

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So they are not investing for the short term, but they're actually investing for the future for like getting a return on the assets. Think about 401k plans, you know, the Berkshire of the world, those are investing in SPY for a longer period. And then of course you have es, which is really more like futures market makers, institutionals, prop, trading firms, CTA funds and so on. So again we know that there are different customers trading these assets. This is a very good information.

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So what I can see from this analysis that most likely we have a lot of events coming on this week. We have fomc, we have Nvidia earnings coming. So I think when we look at spy, a lot of the investors are actually maybe seeking protection and position themselves for more hedging activity. That's why you see a different value in the option chain. But again, why is this important?

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Because having this at your disposal can actually give you some really interesting clue when trading futures or even the spx.

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Another example on why blind spots are key is for those trading Dow Jones YM futures does not have any option activity. There's no, there's no options on the future. So again, we cannot produce gamma levels. We cannot produce gamma levels there. But we can actually give you some really good insights by using our blind spots level.

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So for those trading ym, we still have a great solution for you guys. You can use our blind spots and basically that can help you understand Those areas that might be overlooked. And without any option activity on ym, you will not be able to use any of the option levels. So the blind spots can really help you understand how the market can react at certain levels. So a lot of questions that we get is the ranking of blind spots.

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So the models really find zones where price levels from multiple correlated assets overlap, creating clusters of potential market reaction point. These zones are ranked from BL1 that you see at the top to BL10 based on the number of overlaps. Right. So the blind spots level is a bit different from our gamma levels. So what we have with BL1, which is BL1 represents the strongest cluster with the highest number of overlapping price levels.

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Right. So again, it's a very, very strong level because we see a lot of reaction zones in the same clusters of areas. With BL10 we have fewer overlaps. But that doesn't mean that is not as relevant as it might. You know, it might not have as many overlapping price as BL1, but it can still be a very, very strong reaction zone.

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So again, the ranking measure the number of overlapping, not the density. So that's why BL10 can just be as critical as BL1 if market condition aligns. So I always don't look at the label, just look at the levels and get them aligned with your price action and your, your strategy. So why are they relevant? Right.

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Again, remember the concept where if you're a trader, you have a lot of information, there's a lot of data out there. You need to be able to simplify complex data to be actually actionable and be able to take more accurate decisions in a timely way. Because again, time is money and money is time. Right. Very, very important.

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You can get a comprehensive market view by looking at asset correlation of different assets. That's very important. You can also use this indicator for risk management. Risk is very key, especially when we have high volatility. So understanding areas where you could face additional risk can be very important.

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And then finally you are actually trading using data. So you are avoiding emotions and you're actually leveraging a data driven system which can actually be very, very powerful. All right, now we're going to go into some use cases and then we're going to go into the charts. We're going to show you also the indicator. But let's start with the use cases.

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We're going to start with Forex. We released our blind spots on Forex about a few months ago and I think the model is actually very unique and can provide a lot of really great advantage. So let's go over why we develop it first and why it can be important for Forex traders. So the Forex market presents a unique challenge for us. The Forex market is fragmented, mostly is operated over the counter, so OTC markets.

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So there's really a lack of a centralized exchange. And again, price discovery data transparency is also an issue because we don't have a repository of data that we can use. So even like the options on Forex are very, very hard to get and there's not a lot of data available there, right? So they're very, very different from the stock market or the futures market. So that's why the blind spot model adapt to these characteristics by leveraging a combination of diverse data sources and advanced analytics.

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We look at for example option positions, option positioning. By looking at the Forex futures data that we have, we look at the option flow coming from that asset and where big players can be positioned there. We also look at momentum indicators to understand how different Forex pairs are moving together. And of course cross asset. Correct correlation is specifically valuable in Forex because currency pairs are really linked through economic relationship and global capital flow.

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So we can actually derive a lot of interesting correlation coming from the Forex world. And we can apply that by integrating these inputs in our blind spot model that can help us identify actionable zones where you know, the price would be likely to react. So for Forex traders, you can actually combine blind spots with your technical indicators, with your support and resistance areas and that can become a very great tool for you guys. If we look at our Forex coverage, we cover right now our major pairs. So we have Australian dollars, Swiss Franc, British pound, gold, Canadian dollar, jpy, Euro and so on.

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So those are all available. Blind spots are both available on the currency pair as well as the future assets. So 6A, 6B and so on. So those are all available within the indicator. Let's, let's look at some examples.

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So here we have an example from a week ago or so on the US Canadian dollar Forex pair. So as you can see, you know, like really the price moved around those blind spot areas. They could have offered a lot interesting entry and trigger points. If you were in a trade, you could have used that as your target or you could have used that to initiate a trade, especially those BL2BL3 areas. Very, very interesting move there.

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So very, very important. Same thing on Euro. So here we have a reversal trade at around BL8, the price moved, stalled around BL9 and went all the way up to BL3 and then reversed back. So you could have taken a trade at BL8, you could have take partial profit at BL9 and you could have take full profit at BL3. Or you could have also taken potentially a reversal trade at BL3 at the top when the price action would align with your strategy.

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Here is another example with jpy. First we have a very strong potential entry Point at BL1 at the bottom here on the center of the chart. Then the price moved to BS7 and BL2 and kind of like went in a range for the old days. So depending on whether you're a scalper or a position trader, you could have used that data to potentially understand entry, exit or even manage your risk right there. Another example on Aussie dollar again here, very nice move from blue 8 at the bottom to be a 6 at the top and then a reversal almost all the way down to be a 9.

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Another example, Canadian dollar from BL3 all the way to BL1. Price kind of like range a little bit on that BL4, BL5 area and then reverse back. Now let's go over why blind spots on futures can actually be very important. And we're going to go go over some examples. So the first what the model does is analyze option flow on correlated assets to detect where large traders are placing significant bets.

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Whether bullish or bearish, this option activity can reveal hidden market expectation beyond what price alone can show. Right. So for example, if you're trading the ES S&P 500 a contract or the NQ, they are highly correlated with assets like the Max 7 companies, gold prices, Vix crude oil and even Bitcoin. So understanding the correlation between these assets can be very important. So we combine option positioning, momentum and cross asset correlation to create the blind spots that can actually provide you a multi dimensional view to help you understand the areas where you could potentially forecast a move or also manage your risk and and get like better information coming from correlated assets.

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This is an example on nq. So we saw a rejection here. This was from last week at BL1 all the way down to BL10. BL10 was a great reversal point for a potential trade to the upside. Same picture on yes, price stalled around BL4 area, move all the way down to BL8 and then reverse back crossing over BL1.

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So again very, very important. CL again we are seeing a rejection of the BL8 level coming all the way down, stopping at BL6 for a potential reversal all the way to BS7 and then all the way down to BL2. So those can be very, very important areas.

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Gold again, this is a good example from last week. Price stalled for a majority of the day at BL1 drop all the way down and then again found [email protected] again for those who are trading Dow Jones futures, very, very important. There's not a lot of data coming from the option market there. So you can use the blind spot as areas for your targets. And you can see here another good example on ym.

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All right now we are very excited because this is new. It's not officially being released but because we are doing this presentation I want to show you guys what we have. So we are now have blind spots also on stocks and we are starting from our Max seven and we will expand this in the future. So this is really brand new for you guys. And what we look at when we talk about stocks is option driven risk mapping.

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So we are trying to reveal what the option floor is telling us and not just looking at price and volume. We're trying to find high liquidity zones where the price could actually flip. And then of course every asset is different so the model actually adapts. We calculate the daily so it can account for e.g. earnings event and so on.

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And of course the goal of this model is to turn complex option positioning into clear zones on your chart. So again we said that we currently cover Max 7. So all the big Max 7 companies that we're going to show you some examples. And then this is for example what you see on Nvidia. This is an example from last week.

[00:30:02.08] - Speaker 1
We have Apple here so you can see how you can combine for example JAX levels together with, with blind spots and yeah, and then we're gonna go into, into some charts as well, so stay tuned.