Lead-Lag Live

Fabio Ruggeri on Modern Market Strategies, Options Trading Evolution, and Democratizing Data Analysis Tools

• Michael A. Gayed, CFA

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Unlock the secrets to modern market strategies that are reshaping the financial landscape. Join us as we sit down with Fabio Ruggeri, former Bloomberg professional and current AI-driven finance innovator, to uncover the shift from traditional fundamental analysis to technical and alternative data in market strategies. Through Fabio's journey, we explore how major events like the credit crisis and the COVID-19 pandemic have catalyzed the adoption of alternative data sources, such as geolocation and credit card information, fundamentally transforming how we predict market movements and create quantitative trading strategies.

Discover how the world of options trading has transformed over the past decade, fueled by retail traders seeking more accessible and simplified strategies. Options have not only become pivotal in market liquidity and volatility but have also seen their volumes sometimes surpass traditional equities. This episode uncovers the critical role of options in shaping market dynamics, with zero DTE options emerging as key players in driving sudden market shifts and enabling institutional strategies like covered calls. Our discussion highlights the innovative ways derivatives are now integral to market analysis.

Immerse yourself in the cutting-edge tools and educational resources provided by MenthorQ, designed to democratize complex options data analysis for retail traders. From advanced features like gamma level analysis to intuitive option data visualizations, learn how MenthorQ's platform is revolutionizing the trading experience. Fabio shares insights on the importance of education in mastering options trading, using real-world examples like NVIDIA's earnings to demonstrate the power of MenthorQ's tools. We also spotlight the platform’s growth journey, the role of community engagement, and Fabio's invaluable contributions to advancing market analysis.

DISCLAIMER – PLEASE READ: This is a sponsored episode for which Lead-Lag Publishing, LLC has been paid a fee. Lead-Lag Publishing, LLC does not guarantee the accuracy or completeness of the information provided in the episode or make any representation as to its quality. All statements and expressions provided in this episode are the sole opinion of MenthorQ and Lead-Lag Publishing, LLC expressly disclaims any responsibility for action taken in connection with the information provided in the discussion. The content in this program is for informational purposes only. You should not construe any information or other material as investment, financial, tax, or other advice. The views expressed by the participants are solely their own. A participant may hav

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Speaker 1:

This is the period between the 90s to 2007, right, where the main strategy that was driving markets was mostly fundamental analysis, where you are looking to discover companies that have good fundamentals that they will appreciate over time. Then the first credit crisis came and obviously with the immersion of liquidity from the Federal Reserve to kind of fix the situation. Fundamental analysis doesn't really work in the past kind of 10 years and that's why, like, retail traders started really embracing something that they understand, that is simple and easy for everyone, which is technical analysis. Right, the problem with those two strategies is that you are using past data to be able to forecast future price movement, and obviously there's lagging in that. And then COVID happened, and then with COVID, we see a big shift in the market for different reasons.

Speaker 2:

This is a sponsored conversation by Fabio's firm. Here I'm going to be talking about his business, as well as the interesting things that he sees from the retail community, as well as the options market and why he came up with his company and with all that said. My name is Michael Guyette, publisher of the Lead Lagarboard. Joining me for roughly 50 minutes is Fabio Ruggieri. Fabio, introduce yourself to the audience maybe to me, a little bit more formally. Who are you? What's your background? What have you done throughout your career? What are you doing now?

Speaker 1:

Yeah, michael, thank you. Thank you for having me. So hi everyone. So my name is Fabio Ruggeri. I'm from Italy.

Speaker 1:

After school, I moved to London and I started really working in finance back in 2007, where I started working at Bloomberg, so obviously a leader in the data space, covering, obviously, global banks and asset managers. I worked part of my career in London and then I moved to New York and I was at Bloomberg for about 11 years where I had the opportunity to kind of like work with the biggest funds in the world, the biggest asset managers, the biggest hedge funds, and that's when I really started developing the interest in the biggest funds in the world, the biggest asset managers, the biggest hedge funds, and that's when I really started developing the interest in what was changing in the finance industry. After Bloomberg in 2018, I went and actually worked for a startup. That was my first startup experience.

Speaker 1:

I was the head of business development for an alternative data company and basically we were selling alternative data to large quantitative funds that were trying to make sense of complex information to basically create trading strategies, and that kind of fascinated me because I saw kind of by the shift from the traditional finance to more like the alternative finance. I was there for about three years covering, obviously, companies, like you know, the CTO of the world and the biggest funds in the world and really trying to understand how they were embracing the large data set, the big data to then create trading strategies. And then I also went and worked for a cybersecurity company in AI, also leveraging big data for both investment and security AI also leveraging big data for both investment and security. And then back in 2020, we really started to see like a shift in the market and that's when we started really implementing our own financial modeling. That then became the backbone of MentorQ and what MentorQ is today.

Speaker 2:

All right, so there's a lot I want to unpack there. The idea of alternative data. Let's talk about what are the sources of that and what actually is alternative data I mean. When I hear alternative data, it sounds like it's almost like political, but what does that actually mean?

Speaker 1:

Alternative data is, it could be everything very broad. So obviously we are most investors are very familiar with fundamental analysis, with technical analysis and the traditional data sets. So Bloomberg is really was really the embrace of traditional strategies. So, from financial statements to news to pricing information Right, what people don't really understand is that there is value in trading coming from sources that might not be as easily consumable as those, and I can give you an example. Let's imagine that you take geolocation data and you are monitoring traffic cameras. Right, as an investor, you want to understand how many people are driving to Macy's in any given location at any given time, and if you see a pattern where there's less traffic over the past three months, that could also be a signal that the sales of Macy's are going to go down. So, like, you have these big companies that are trying to get their hands on all these kinds of data sets that can give them an idea of where the sales of a company that they're monitoring could be, and then they will place their bets.

Speaker 1:

Another interesting data sets that people buy a lot is credit card information. So if you are able to decode this data set that is publicly available information, then you can kind of try and forecast what the potential sale of companies can be, and then obviously you can place your bets ahead of earnings and stuff like that. Other alternative data sets are like executive travels. So let's imagine that you get access to the travel schedule of CEOs like Tim Cook and you understand that Tim Cook is going to Dallas three times in a year. Why is he going there? Maybe there's an M&A activity going on, and then you're trying to look at the companies that are going to be in that location to try and formulate the theory behind something like that. So those types of data set that obviously are not really available for retail investors are the type of data that we were selling and where companies are actually making returns based on those data sets.

Speaker 2:

And it seems like you have to be very clever in terms of figuring out where those data points are, what those data points should be, because it's not like these are things that you will learn about in some finance course.

Speaker 1:

It's basically like uh, you obviously need to have the know-how of building quantitative trading strategies and, obviously, being able to handle big data, so obviously large databases, large uh desksks, obviously technology, so software engineers that can then build the infrastructure to be able to handle that data. But yeah, absolutely, it's not not every day's investors can have that type of setup and that's why, with MentorQ, we are trying to kind of bridge the gap between this type of investment and what the retail can do today.

Speaker 2:

Let's talk about retail because, on the one hand, there's some that argue retail is more sophisticated than ever before in history. Certainly, retail drives markets much more than ever before in history. There's also the argument that retail there has been such an influx of new retail post-COVID that are playing with options and very complex financial instruments that they don't know they're playing with fire and while they're making money now they don't really have an approach that is sustainable long term. I'm curious, given that you've seen this from an institutional perspective, I think largely, what's your impression of sort of the state of retail education when it comes to truly understanding markets?

Speaker 1:

the state of retail education when it comes to truly understanding markets. So I think so there's a couple of trends, and that's why also the option market is now very important. So first of all and I don't know, maybe if we want to bring up my slides, I can go over this also with some visuals Basically, if we go on the first slide, so this is the period between the 90s to 2007, right, where the main strategy that was driving markets was mostly fundamental analysis, where you are looking to discover companies that have good fundamentals that they will appreciate over time. Then the first credit crisis came and obviously, with the immersion of liquidity from the Federal Reserve to kind of fix the situation, fundamental analysis doesn't really work in the past kind of 10 years, and that's why, like, retail traders started really embracing something that they understand, is simple and easy for everyone, which is technical analysis. Right, the problem with those two strategies is that you are using past data to be able to forecast future price movement, and obviously there's lagging in that.

Speaker 1:

And then COVID happened. And then, with COVID, we see a big shift in the market for different reasons. First, the lockdown everybody was at home, everybody lost their jobs, so they had more time to spend to maybe like look at alternative ways of making money. And trading obviously at that time was a very big one, because you had all the GameStop saga, where people that were investing a thousand dollars were hundreds of thousand dollars in profit in a few days, or the crypto situation of 2020, 2021. So a lot of like people that didn't know what trading was started going into the market. Then you also had the Robinhood growth, so like brokers that can now allow you to trade with a few thousand dollars in your bank account, right, so trading became kind of like a gamification.

Speaker 1:

And then, obviously, with that comes like I want to make money fast and what is the way to do that?

Speaker 1:

And that comes the next slide, which shows the growth of option volume in the past like 20 years and, as you can see, from 2020 to 2024, almost we saw like the volumes almost tripled compared to what it was in the past.

Speaker 1:

And the reason is very simple Options have leverage and for someone who wants to get quick profits, they are the perfect instruments for that, but at the same time, they carry on a lot of risk. So if you don't really know how to use them, then you could really lose all your capital very, very fast. But option had a very fast appeal for investors that maybe didn't want to wait 5% return a year to be able to generate enough cash flow for their goals. So they were a very good instrument at that time and that's why we see, obviously, the growth in the market there and obviously, as you can see, the trend is kind of like staying there, so it's really it's not like really gone down again since 2020. And that's why it's important for everyone to be able to understand what option can do and what's the power behind that data set.

Speaker 2:

I think yeah, and as you know, this is October 2023. So I mean, obviously now it's a lot more intense. Do you have a sense of how much of that is zero DTE, very short-term option treaty, how much of that also could be funds that are selling options? I mean, there's also a lot of institutions that are trying to do cover call strategies to generate some income on the option side.

Speaker 1:

So I think in the recent year I don't have the numbers up to hand, I apologize for that, but the zero DTE flows have really become very, very important and those are also the ones that sometimes have an effect on the sudden price movement throughout the day.

Speaker 1:

So sometimes there are days in the market where the market moves 1%, 2% and nobody really can explain. There's no catalyst, there's no news activity, but it's because of the zero DTS flows that can actually have an effect. So, obviously, if you understand how the option market works now we're seeing the growth of volume If you want to understand how it works and the importance of we were talking about market makers and the effect of liquidity, then you can understand why sometimes you see those sudden price movements, especially when you approach like important expiration, like OPEX third Friday of the month, or the weekly expiration on stocks, or the weeks expiration on the Wednesdays. Yeah, options are very, very important drivers of liquidity and that's also why, like a lot of companies are putting a lot of attention in options, understanding how to use them for hedging and for, obviously, speculation and trading.

Speaker 2:

Yeah, and you can argue also to some extent. I hate to use the word manipulation, but there's an extent of that. Right. It'd be. To the extent that everyone knows what dealer positioning might be, they can force a move. We saw that a lot with GameStop and other type of positions like that. Have we gotten to a point, you think, in market analysis, where the derivative matters more than the underlying?

Speaker 1:

So I think so and so, first of all, let's go back to 2021. That was the first time in history where option volume surpassed equity volume. Right, so that was very big time. I remember it when we I think it was the end of 2021. But the problem is that people need to understand that, like option carry, leverage and option have a time to expiration. So sometimes, because of the risk, the option carry, that movement of liquidity, can actually be the main driver of the market. So I think, yes, they are very important and I think you know the trend is here to stay. I don't foresee this going back to what it was, maybe in the 2000s.

Speaker 2:

Okay. So you got all these interesting dynamics playing out. You've got traditional data providers out there that are maybe showing things which are from an old regime and are not factoring in a lot of what's going on. Now Talk to me about MentorQ and talk to me about why that's a different type of a service in terms of what it's providing, analysis-wise. Yeah sure.

Speaker 1:

So we basically are trying to use the same approach. So we started really the history behind. We started trading, uh, for about 10 years now, when we when I was a bloomer, when I was a startup and we started developing some sort of strategies for our own portfolios. Uh, at the beginning it was based on technical analysis and fundamental a little bit for our more like longer term portfolio, but then we started developing a more speculative approach and that we were doing like simple option strategies, like selling options, spreads and so on. And then 2020 kind of came, and then that's when we started really to understand the importance of option flow. So we started partnering with our now it's our head of quant and basically we started developing. So we were coding into Python script our way of trading and our strategy, and then we kind of develop our option models. And then obviously we started applying that during 2020, 2021, and that was very successful.

Speaker 1:

And then we basically said, okay, now that we have all these models option models, simplification of the complex data set that is coming with the option market now can we actually create a business out of it? And at the beginning it was really just our Twitter account that grew from 500 followers to about 56, 57. I think we are right now during 2021, 2022. We started a newsletter in 2023. That was very successful, and then we really started like putting everything into practice and now we actually have a product, we have a platform, we're launching some big things next week, so we're very excited about that and I think the key of the success here was to create simplification out of very complex data set.

Speaker 1:

So the option market is complex and if you are a retail trader, most likely you're going to run away from option Whenever you hear the term option. Oh, that's too dangerous, I don't understand it, it's too complicated. But in reality, like we were able to simplify that and I can share some example on what we did there. And then now people that actually don't even trade option are actually trading with us and are part of our group. We do futures. People that trade futures also leverage the same approach, but the power comes from the backbone of the auction models that we built over time.

Speaker 2:

Let's go through some of the backend. I'm curious to see how the UI UX looks.

Speaker 1:

So, first of all, uh, at the backbone is what we call uh, our products. Our products are mostly option models that are trying to simplify and give you an idea of how to trade and how to use them for trading, and we cover, as you can see on the left, a lot of different asset commodities crypto, etfs, fixed income, forex, futures. We are one of the first companies that are actually using futures options and deriving gamma levels from future options, and we're going to share why that is important. But essentially, we have string models, we have indicators that you can plot on your chart, we have option screeners, but the most important part is really our gamma levels and our option data. So the way it works. Right now we are in Discord, but we are launching a platform next week, for next Thursday, actually launching a platform next week or for next Thursday actually and essentially, you are basically looking at our bot right here. So the first thing that we want to do and I'm going to get like a very nice example Tomorrow we have earnings from NVIDIA and what we want to see is really trying to decode where the market is positioned. So this is one of our main charts and this is trying to understand the sentiment coming from the option market and the positioning based on the option flow. So we're looking at the chart of NVIDIA, we're looking at where the net gamma and positive and negative gamma is and that can help you understand where the market is thinking the price can be. So, as you can see, we have simplified in a way where the green bars are kind of like the cost size, so the kind of like bullish sentiment, the rates are the put size kind of the bearish sentiment. So what the ui is telling us is that there is a lot of activity at the 150 strike price. Our price right now is 140. So there's a lot of like cold gamma right here at the 150 level right. So again, there's not a lot of negative gamma rate here on this strike. So the market overall is potentially betting that the price could go to 150 or above that.

Speaker 1:

Then we also want to understand OK, that's by looking at the full option chain but what happens if we want to look at a single option expiration? So if I take the example of NVIDIA, again, the picture doesn't really change. So here what we see is this friday expiration. We still have our 150 level right there. If we go to next week we also have our 150 right there and then if we go to december, our major level right there is 135, but we still have a big 150 bar right there. So this is translating kind of like the option exposure that we take into our gamma levels and then we are going to be able to actually go and plot those into a chart as well, because we have multiple integrations. We trade in views, one tower book map, ninja trader, sierra chart. We have a lot of integration that are available for users as well.

Speaker 2:

It's not part of the marketplace. I analyze by the stretch of the imagination. You're familiar with a lot of this stuff, but it's interesting to see how clean the visual is. Do you see on the back end from the existing clients, the stocks that most people are looking at for options activity? I wonder if there's anything interesting there, data-wise, in terms of where interest is highest.

Speaker 1:

So I would say we do have some analytics on what users are looking for, and I think the things that people look for are the usual suspects. A lot of our users are trading diffusers, so they're looking at NQ, es, gold and crude oil. Those are the main ones, but then it's always like, yes, the NVIDIA of the world, tesla, the MAX 7, of course, those are the drivers. We're looking at the VIX. Vix is very important because it's a leading indicator of potential sentiment shifts, so looking at VIX option is very key. So you always want to have, like, the data on the VIX and the data on the SPX, and then occasionally, during earnings, there will be a lot of activity, especially this week. We have NVIDIA tomorrow, but we have really important companies reporting. Two weeks ago we had basically like Google, apple and all the stocks that are reported, so that was also very important. And also another thing that option market can do is also can give you probabilities for the future. So we have customers that have day traders, but we also have customers that are stream traders. So we have like stream models that can tell you of where the price of a company can be by looking at the option market. So in this case, if we go back same to a media, here we have our stream model that will tell you the volatility band over the next five days, but also the bias and the potential direction of the price. So when you see a green, a green band, obviously bullish bias. If you were to see a red band is obviously a bearish bias. So here we have some volatility bands for the next five days. We have this 150 level right there and 129 dollars right there, and here we also have our back test over the past 38 days. So the bands actually were successful on 100% of the 38 days, meaning that in five days from now, if we are successful, the price of NVIDIA will be above $129. And if you go at the past, the band basically kind of like we're always kind of right where the price never really went below those bands.

Speaker 1:

And why is this important? For two reasons. One, because with options you can have flexible strategies that can make money in any market condition. So you could have risk neutral, market neutral strategy. You could have very strategy, you could have bullish strategies or they could actually be used as risk management tool. So if you were, for example, an Nvidia investor and you want to understand okay, what I'm making money on this company, what is my exit plan, then this could help you understand okay, what are the levels that you want to pay attention to, which is also very important. A lot of traders don't look at risk management. They only focus on making money, but risk management is actually very, very important.

Speaker 2:

And this work is only be done on individual stocks, not necessarily on indices ETFs. I know you mentioned futures. Maybe touch on that side.

Speaker 1:

Yeah, so we do that on any asset. So we have the same level of information on indices. So here we have the spx. We have the same level of information on etfs, like spy, or we have the same level of information on uh futures, like yes in this case. So the important part is people will think, oh, but they all move in the same direction, right? But the actual option chain of the three assets is different. So SPX is by far the largest by volume in terms of options as one option chain. Spy has a different option chain and ES has also their own option chain.

Speaker 1:

It's important to understand who is the customer of these assets, right? So who buys ES, who buys SPY and who buys SPX? So if you look at SPY, most likely it's going to be pension funds, asset managers, the usual retail investor that is putting their 401k into the market. So they want to track the performance of the index, so their view of the market is more long-term. So, whether if you have SPX or ES, so ES would be, for example, used by the institution that are hedging. They would trade ES futures.

Speaker 1:

So being able to spot any differences in the three different option chain can help you get like a better understanding of potential risk. And the same thing can be done with the with stream water. So, if you want to understand where can be the price offered, the index b in 20 days from now, uh, you have our stream model right there. And then here what you have is our backtesting, our bands upper bands, risk trigger and lower band and here you can see, for example, the data. So, again going back to the option market, if you were to sell credit spreads using those bands, you would have been successful in 100% of the cases. Obviously, the challenge is would there be premium for those strikes? And then, obviously, how do you manage the risk and how much risk do you want to take? So that's a different story there, but you would be able to kind of understand what can be your threshold, how can I manage my risk and how can I then place my bets.

Speaker 2:

How much of the platform would you consider to be AI driven? Whenever I hear predictive, I'm thinking AI or just in general, regression, large data analysis. Are you integrating AI in the LLM way in any way?

Speaker 1:

Basically, this is our first ai model, which uses a lot of factors and we use like a machine learning algorithm. The next step for us is being able to integrate ai to be able to explain what the data means, because I think we've proven that the data kind of works and the approach works, but the challenge is for everyday investor, like, how do you understand this data? So being able to explain that. So we're integrating, we're creating a system that would be able to explain what the data means so that you can actually, in a few minutes a day, actually understand what's going on with the companies that you care about. So, if you are an embedded investor, you'll be able to understand how things have changed over time and being able to explain the data Obviously, it's not a suggestion, it's not investment advice, but it's really can you help me be smarter and understand complex data in a very, very easy way?

Speaker 2:

Let's talk about how you educate people around some of these concepts, because I don't know if that many people understand the options, market gamma levels and data like what you're presenting. So, first of all, do you find that an important part of the business needs to be on the education front, and what kind of things are you doing to educate others?

Speaker 1:

Yes, I think that education is very important. So I think the key part for anyone that approaches this kind of strategies and this kind of world is you really need to want to put time to be able to learn, because options are complicated and everybody obviously wants to. They hear the buzzword gamma levels and they say, oh, I want to use them. But the most important part is you need to learn the basic. You need to know why they are important and what are the mechanics behind it. And then, once you understand that, then that part is done. So you've done the heavy part. Then you can kind of start using it and basically leveraging for your needs. So first, anybody can create a free account and access all of the things that I'm going to show you here. So you can go to mentorqcom, create a free account of the things that I'm going to show you here. So you can go on mentorqcom, create a free account and then, basically, first we have created a section called guides. Guides are really like tutorial documents that can help you understand anything you want to know about our models, about the option market, about strategies, so what type of trade based on what type of trader you are. So if you are. For example, you mentioned zero DTE. Okay, if somebody wants to become a zero DTE trader, what are the steps that you need to take to be able to learn that? If you want to understand, okay, like I, I like your stream trading model. I want to learn more about it Okay, we have a document for that.

Speaker 1:

We have backtesting results, testing results right to show you, uh, how that work. Uh, if you want to understand our gamma levels, right, we have our different gamma levels right there. There's a document for that. And then if you want to learn more about the general option market, then we have a knowledge base too. And if you want to learn about strategies, okay, I want, uh, to learn about income strategies.

Speaker 1:

I hear a lot about the higher income strategy or credit spread, so you can learn about income strategies there and, in any case, show me some success and so on. So that's basically obviously the written content, but then we also have tutorial videos. So, if you go within our academy, we have about I think it's over 400 video lessons right here, 30 plus courses on many different topics. We have, uh, one very good one that we did is we did a live trading event during the us elections, where we were live trading for three days. Uh, we have, um, you know, a roadmap training, technical analysis options, so there's a lot of information there. So, yeah, that's definitely a big part.

Speaker 2:

How long has the?

Speaker 1:

company been around, so we started about three years ago, but I would say the growth of the company started when we launched our first newsletter in 2023. So over a year and a half and the platform was launched about less than a year ago.

Speaker 2:

So yeah, what's what's been the general reception? I mean you're in a, you know you're in a relatively crowded field. Hopefully those that are watching this, you know, learn more about the service and the site, aren't curious to take a look. But you know, talk to me about sort of the, the challenges in terms of marketing and getting awareness. So I think uh, we had.

Speaker 1:

So the challenge is, obviously, we started from scratch and we started back in 2020 and we restarted from. Like it was me and my partner. We had this very small twitter account I think it was at the beginning a personal twitter account that we'd enter into a company twitter account and we started like tweeting about finance that that's our passion, uh and then our content kind of started really picking up and we started generating our first 5 000 followers and then they became 10,000 and then kept growing and growing and then we really started to understand, okay, like, what are the key differentiator that we can bring? And I think the key is really our focus, our ability to simplify complex things and then our dedication. Right, we've been working for the past three years, day and night, nonstop, and then, obviously, we were able to then hire a very good team of people, we built a very solid infrastructure, we built new models, we built. So we keep innovating and I think just this year, we had three major big releases and you know, next week is going to be another big one and basically the challenge is really just keep innovating and building new things and also listen to our customers. So we listen to our customers every day and we try to channel what their needs are into a product.

Speaker 1:

And I think the main growth was the simplification, and I can show you why. Why that is. And, uh, you know if you want to even shove the screen again, um so, so, in order to simplify things, uh, when you start from option, you can have Excel models, you can have financial models, you can have financial models, right, but nobody will really understand unless until you start putting a very simple indication on a chart that people really understand. So this is a good example from today. So we had a massive sell off in the Nasdaq at the beginning of the session and then we had a break right there.

Speaker 1:

So imagine if you are just using kind of technical analysis or any strategy that you might look for where is the end, where is the bottom right, where can the market stop? And basically, then comes the power of the option data and the power of being able to translate those complex charts that we saw, or those signals, into some lines on your chart that have a meaning. So they, they carry a lot of value. So the power of option data now is translated into a chart and suddenly you have a path. You have a clear vision of where the market would go and where you know, once it stops where, where is the next target, where is the next area of interest, and then you can start planning uh, your your day, but uh, at least you know. It can help you give a clear understanding of where the market can reverse, where the market can accelerate and what are the areas that you might want to target.

Speaker 2:

So there's a uh, there's a good saying when it comes to uh, developing an app, which is you are not your user right and as an entrepreneur, you know you try to create a service, create a product to solve, usually, a problem that you're having, but then, as you start to do that, you start realizing that it's not really about you. It it's about the customers. To your point, listening to the customers, I'm curious in terms of sort of the evolution of the service, the evolution of the offering. How many iterations did you go through? How many times did you rejigger or rethink the way you're presenting things? Because it was me resonating with you but not with others. I'm always fascinated by sort of that progression, that journey.

Speaker 1:

So I think the backbone of the technology was built at the beginning and obviously some of the models have not really changed because it was very innovative what we were trying to achieve. So the first thing is obviously gamma levels, reaction zones. The most important part is understanding how the market makers work, how the option market work, and then understand where the price could change, because everybody really needs to understand, okay, what is my risk and what is my potential profit. So those are the two things obviously you have to bear in mind is my risk and what is my potential profit? So those are the two things obviously you have to bear in mind. If I'm in the market, how much can I lose and how much can I make, and what is my risk reward? So am I taking too much risk? And so on. So we try to build kind of like indicators and levels and we call it gamma levels and key levels that can help you understand where the market can go and what could be your potential trading plan. And the goal was, without data, you need to be able to do it in five minutes or less. So if you're like trading nvidia, you need to be able to go into the charts and understand, okay, what is my roadmap for the day in less than five minutes. So we basically built kind of the idea behind it with that, with that mindset. Somebody has to come, they need to be able to understand the charts and already been able to make sense of it, and then obviously we build the education piece, obviously to support that, and then kind of this kind of like evolved. So let me give you an example what we see here is the same level that I showed you before, where the MQ kind of reversed.

Speaker 1:

We did the same for stocks and at the beginning this was tailored more for, like, day traders. So obviously the one day move is really for day traders for the next day. And we had a lot of customers that are like man, I cannot be on my laptop every day. I need to have something that I can use if I'm basically just placing one trade a week or one trade a month. So that's when we developed the same model for StreetTrade. So the evolution of kind of like our technology became like we had some customers that were really active. They were like I love your stuff but I cannot use it because I cannot be in front of a screen every day. So, okay, no problem, let me go back to our team and let's see if we can come up with a model that can help you for the longer term. And then obviously we had a lot of zero DTE traders, right, and they were selling option every day, so this model really worked really well for them. But then we had others that were like okay, I'm losing too much money because I'm taking too much risk for the premium that I'm getting, but it would be great if you could do the same thing with a longer time horizon so I can risk less and potentially generate better risk rewards. So that's why we started building models that can actually solve that problem.

Speaker 1:

Another problem that we had is that a lot of our customers were trading futures, so obviously we didn't have options on futures at the beginning of the year. So we went, we looked at the data and then we created a product that can now be tailored for futures traders. So a lot of our traders do not actually even look at options, but they use our level for trading futures because the option carries a lot of value. So I think, yeah, we have always evolving, always listening to the customers. Integration became a very important part. So everybody was like I love your data, but how can I bring it into my training platform? So then that's when we developed the first training view indicator. Now we are on five or six different platforms because another thing, you want to make the decision and you want to be active. So the way you're active is obviously with your training platform.

Speaker 2:

So that was a very, very key driver as well of our growth yeah, I'm impressed you have as many integrations as you do with trading you, which I happen to use myself. I am curious, how do those even come about? I mean, that's not easy to kind of get in front of these companies and and them on something like this.

Speaker 1:

So I think, with the integration is the first one that we really did was NinjaTrader, and I think we had a lot of customers that were requesting it. So a lot of our user was obviously using TradingView as their main kind of decision making platform for charting, but then all their execution was done outside, because if you are a futures trader, you are most likely using a different tool. So then we started looking at what were the bigger ones and the ones that we could deliver in a very short amount of time. So Ninja Trader was the first one. We were able to get in touch with the team and we're now part of the vendor licensing team with them, and I think the key fact was that they didn't really have a lot of companies that were actually working on options. So they were really impressed by okay, very interesting, because maybe in the future they will have options there. I'm not sure.

Speaker 1:

But basically we are the first really company that has kind of like an indicator that is looking at futures options, not only just pricing data. So it's kind of like a different approach. So we were able to get there. And then the others is really we developed ourselves. We obviously have a team of developers that has been working on those. I have a team of developers that has been working on those and the goal is really to be able to cover almost every integration that we can, basically, with the limitation of the technology that we can build to help everyone facilitate the way they execute and not having to have too many platforms open at the same time, because, again, time is money, money is time. So the more time you spend going from one platform to the other one, maybe you are losing opportunities or maybe you are too late to be able to capitalize on the ideas that you get are you an active trader yourself?

Speaker 2:

I mean, I assume you're using this obviously for yourself.

Speaker 1:

Um, just talk about sort of your, your own integration uh, yeah, absolutely so, obviously, uh, we, we trade ourselves as well, uh, and we really developed these models, obviously for our own use. So it's basically like uh, we had our ideas together, we had our at the time cto, putting this into a code that we could use systematically, and that's when we started doing it ourselves. Now we use it as well not as frequent as before because of the time. Obviously running a business takes away a lot of time, so we are less active as before, but we still use it for our weekly trades and also like our longer-term positioning, so we always monitor what's happening in the option market for our longest term portfolio as well.

Speaker 2:

Come back to the alternative data point. There's alternative data and then there's alternative data that matters Again. You know the options, gamma and that type of visual matters. But I have to assume that when you're trying to create a platform like this, it's very tempting to put alternative data that really doesn't have any predictive power. It's very tempting to put alternative data that really doesn't have any predictive power. So how do you go through sort of a process of identifying what you want to release in the future that's new, that really does add value, because it's not that simple.

Speaker 1:

Yeah, yeah. And again, I was lucky enough to have worked really closely with big funds and kind of understand the approach from alternative data, because whenever they look at alternative data, the challenge is always to be able to find an excessive return. So whatever is called alpha, on top of what they're already doing. And also correlation is also very important. So if you have, for example, a data set that can give you a 2% return additional return and then another data set that can give you a 2.5% return, but they are very highly correlated, that's not interesting. That's not a data set that can actually add value.

Speaker 1:

So when I was at the startup, it was always like not only about alpha, but it was also about correlation. So whenever you can find something that is completely uncorrelated to what everybody else is using, that is when you start adding value, because that's something that is very unique to what what you're doing. So whenever we are building models, we always try to understand things that we can do different, by obviously leveraging the data set that we have access to. So in the future, for example, we are planning on building more macro models or earnings prediction models, things like that, that can re-advance to something that is not there at the moment.

Speaker 2:

Longer term is the hope that you get to be so large that a larger data company acquires you. Are you looking to do funding rounds and be entirely on your own? Sort of talk to me about the business direction.

Speaker 1:

Yeah, sure. So obviously we started very small. Obviously, we started, but now we build a team, so we hire many different resources for 2025. So we're going to start developing our web app, which is going to be a very unique research platform. The first version will come out next week, so we're going to have an initial iteration of what we're going to develop in the future. The goal will always be complex information, simplification, actionable insights, so that's kind of like the way we want to structure our vision.

Speaker 1:

Uh, and then for the future, at the moment we're not, uh, looking to raise funds. Uh, we don't. We don't have the need right now, but in the future, potentially, maybe as we grow uh, we're really like building the team. We're already building the infrastructure. We have kind of started implementing ai and the goal is really to develop an app that can help you, in less than five minutes a day, understand what the market is doing and how you can actually be active. In terms of exit plan. We we're we don't have that yet, but but once we get to that point, I think there could be different options for sure.

Speaker 2:

Fabio, for those who want to get access to the service, maybe just kind of learn more about all this. Talk about where people can get that access and talk about maybe just the Discord, because I think that's where a lot of especially younger traders like to go to.

Speaker 1:

Yeah, absolutely. So. I think if you go to mentorqcom free, uh, you can actually um create a free account right here, uh. So just obviously, uh create an account and then you'll be able to uh get access to our discord, our free discord, within this code. We have, obviously, uh, a lot of different rooms. We have our training rooms right here where you have, like, professional traders talking about futures trading, options trading, macro, iron, condo, like all of that, and then you can also access all our data directly through here.

Speaker 1:

As of next week, you'll be able to actually access the data directly through the website. So all of these models will be actually be moved to the data directly through the website. So all of these models will actually be moved to the website. So we still have it's still be available on Discord, but you're also going to have an app that can help you, especially if you are, like, not used to Discord. For younger traders, discord is obviously the tool that they use, but for more, like, seasonal traders, then obviously you don't really want to learn a new platform. So we're going to have the data all in our website. So the first step is really come here, create an account, sign up for free right here and then, obviously, once you have an account, you'd be able to access your account dashboard whether you're going to be able to get access to the academy, our community, so Discord, our guides. We also have screeners and all of this data will be available right there, so, yeah, Hopefully, everybody found this to be an interesting conversation.

Speaker 2:

Please show some support to Fabio Ruggeri. Check out MentorQ. Sign up for the free because it's free. Why not learn about it? It is true that the option side is very powerful. It will care for liquidity, flow, potential, profit and loss perspective. Any parting words here? Fabio, I think I give you a lot of credit. It's not easy to do what you're doing. I think you're doing something that's different.

Speaker 1:

Yeah, and I think next week also I didn't mention we're actually going to release intraday gamma levels, which is going to be very important, especially for days like today where intraday volatility was really key. So being able to support you also with, like shifting the market throughout the day, that's a massive release for us and I think you know I really would like to thank you first for your time and for our community. That's been really really great to us and I think you know I really would like to thank you for us, for your time and for our community. That's been really really great to us and I hope we can provide value to everybody every day going forward and keep adding value, of course, Appreciate those who watch this live.

Speaker 2:

Again, this was a sponsored conversation. Personally, that was very interesting. Hopefully I'll see you all in the next episode of Lead Lag Live. Thank you, fabio, appreciate it. Thank you, have a good day, guys. Cheers everybody.

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Michael A. Gayed, CFA

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