The importance of trading using Data

[00:00:00.22] - Speaker 1
So first, let's talk about my background first. For those who don't know me, I'm Fabio. I'm the CEO and founder of Mentor Q. I started working in Finance in 2007 and I started working at Bloomberg. So of course everybody knows Bloomberg is the leader in kind of like the data market, data market. And of course that was a very great experience for me because I joined two months before the first credit crisis.

[00:00:26.00] - Speaker 1
So it was a very interesting period. I started working and then obviously Lehman Brothers collapsed and obviously we know what happened after. But basically like my career started in London. I then moved to the US in New York in 2014. And during those 11 years where I was a Bloomberg, I had the opportunity to really work with the largest banks, largest investors in the world.

[00:00:48.09] - Speaker 1
I was covering hedge funds, I was covering large organization. So I got really a very important feel on how the market or the finance market works. After that I decided to actually join a startup and I moved into more the alternative data space. And we're going to talk about alternative data in the presentation where I was selling data to hedge funds. So large organizations, large hedge funds that really started to embrace in data into their investment strategy and that really helped me understand how finance is now evolving.

[00:01:20.25] - Speaker 1
Right. And it was very clear at that time, I was there for about three years, that there was a very big gap between institutional investors and retail traders. Not only for data for the know how and whatever is possible at the institutional level, but obviously our large firms have started to leveraging quantitative models to gain an edge in the market. Right. And that's when we started Mentor Q.

[00:01:48.16] - Speaker 1
The goal of Mentor Q when we started this after Covid is really to bring institutional grade insights to individual traders and being able to simplify them and making sure that they are actionable so that you can actually make smarter decision in less time and be able to be more actionable. Because everybody wants to trade now. We want to be successful, but we struggle because we don't have access to the same tools that maybe institutions have. So today we're going to show you how retail traders can now invest and what's the difference between the way institutions are leveraging data. So let's go first to a very, very short overview on how finance has changed in the past 20 years.

[00:02:33.20] - Speaker 1
Right. So in the early 2000, fundamental analysis really was the way to invest. So you look for a company that has strong fundamentals and you invest with the goal of obviously having a price appreciation. Obviously post 2007, especially after Covid, this strategy does not really did not really work because there was so much liquidity in the market that really company with even bad fundamentals were really skyrocketing to the moon because of all the liquidity that we saw post 2007. We also need to understand our finance have changed.

[00:03:07.24] - Speaker 1
So now we see that about 75% of trading volume is now driven by algorithms. In 2021, for the first time in history, option volume actually surpassed equity volume. Right. So it was the first time in history. This was a very, very big moment.

[00:03:24.15] - Speaker 1
And this is why also we started really investing into the option market. Market makers and hedging strategies are now influencing price like never before. So knowing how market makers are hedging and what are the levels that you should be watching for is very, very important. And then of course, alternative data is becoming more and more important and we're going to show you some example. And of course the change in technology, AI data driven strategies have now proven to be more effective.

[00:03:52.29] - Speaker 1
Right. So we see how kind of like things have changed in the last 20 years since I joined finance in 2007. This has really changed dramatically in maybe 15 years or so. Then we want to show this chart and we show it in a lot of presentation that we do because it's very important to understand that the option volume has really is really increased a lot since the early 2000. And of course Covid brought a lot of importance in option volume.

[00:04:22.12] - Speaker 1
2021 was a very key year for options, but as we can see, like 2024 was actually the highest option volume that we've seen over the past 20 years. So the, the trend is really strong. So today we're going to talk about options, we're going to talk about option models. As a retail trader, if you don't start adapting and using this data, you're going to be left behind because a lot of the trading strategies are going to evolve and obviously options is going to be a key, key part of investing. We're going to show you some example during the course of the presentation.

[00:04:57.11] - Speaker 1
Then we see one of the biggest change is the rise in alternative data. What is alternative data? So when I was working at Bloomberg, I would consider the data that Bloomberg delivered, traditional data, whether it's pricing data, news data, financial statement, and all of that data that is now really a commodity because it's very widely accessible. But what about alternative data? We're going to give you some example.

[00:05:21.07] - Speaker 1
Alternative data is anything that is not really widely accessible to the retail world, but where there's a lot of value from the Data. So institutions are no longer only relying on earnings report or news report or technical indicators, right? But instead they start analyzing really vast data sets. For example, option market, this is like a very big data set that we leverage and we use to create insights. But what about liquidity areas like trading patterns?

[00:05:50.26] - Speaker 1
But here in the slide you actually see a lot of different companies that are delivering a very interesting data set. Geolocation data, credit card information, satellite information, right? So there's a lot of really company that are now being born and they've really been born in the last, last 10 years to deliver insights to institutional investors. And let's make a couple of examples. So let's look at this part of the section here.

[00:06:19.05] - Speaker 1
We have geolocation data, right? So geolocation data, how do you use that data? So you can use that to forecast revenue shifts in companies ahead of earnings, right? So let's say that we look at traffic information for the past years and analyze like companies like Starbucks, right? So we can see that Starbucks has thousands of stores across the U.S. what if you could monitor and track real world traffic to Starbucks location?

[00:06:46.17] - Speaker 1
So people that are actually going to Starbucks to have coffee, right? What if you could overlay this with web traffic data, right? And notice like shift in what's happening. Right? And suppose that we observe a consistent decline in traffic or in visits of people to Starbuck location over the past three months, right?

[00:07:07.11] - Speaker 1
This could become an indicator of weaker sales and potentially negative earnings for Starbucks. Right? So this is kind of like how you can use this data to then invest in a company like Starbucks by analyzing trends and by analyzing pattern coming from alternative data. We have another example. Let's say that we have access to historical app usage data across millions of devices where we can monitor active daily users, the session length of the app and we start looking at trends.

[00:07:41.15] - Speaker 1
Let's say that we are looking at companies like Snapchat and let's say that in the past three months we've seen a decline in active user engagement by 8% month on month. Or let's take an example of Netflix and let's see that we can see that more people are watching less, so we are watching less content on Netflix. So what does this tell us? This could be a signal of a weaker revenue for Snapchat, for example, and could be a signal of higher churn for Netflix subscribers, right? Because we are watching less Netflix.

[00:08:17.11] - Speaker 1
So therefore maybe we will cancel our membership. So that could be a very, very important insight that you could use ahead of earnings to place a bet on A company like Snapshot or Netflix. Of course in the retail world this data is inaccessible, it's very expensive. So it's very, very difficult for a retail investor to be able to access this kind of insight. But this is where finance is going and this is why all these companies have been created.

[00:08:44.17] - Speaker 1
They're very successful and they generate a lot of revenue. So the point of this is that really institutions are leveraging alternative data, AI, quantitative models to generate alpha. Alpha means an excess of return to what the benchmark could do. So if you're looking at the spx, you want to generate more returns, you want to generate a better alpha than the index. So the problem is that as retail traders we're a bit left behind, right?

[00:09:14.18] - Speaker 1
So we have a lack of institutional grade data. We still rely on technical indicators that are kind of like traditional by everybody's using that. So there's not really a lot of key advantage that you can derive from that. And then of course we are missing out on the opportunity coming from alternative data. And today we're going to talk about options, right?

[00:09:36.20] - Speaker 1
We're going to talk about that. So this is why we come in. So this is why we, we created Mentor Queue. This is why we believe we can provide a lot of value. Because with our tools and we're going to show you what we've developed today, we can start identifying important key reaction zones, right where institutions are coming in and moving the market.

[00:09:59.07] - Speaker 1
We can use our gamma levels to predict volatility shifts and then we can start leveraging our quantum model to define our setup. So simplify the way we read the market in a few minutes or a few seconds a day, right? That's the whole goal of what we do. So we are basically trying to solve the problem of providing you with actionable data driven insights that can help you trade like an institution, of course at a fraction of the cost. And basically our philosophy relies on three main principles.

[00:10:36.03] - Speaker 1
First, obviously data, we are leveraging a data driven approach. We ingest a lot of data, we use AI, we use a lot of different tools, machine learning models to be able to take in a lot of really complex information and then simplify this data and finally create actionable signals that you as a retail trader can use to make decisions. Right? The way we do this is in three simple steps. One are quantitative models.

[00:11:04.18] - Speaker 1
Quantitative models are charts, are tables that help us basically generating signals from data. In this case we're talking about options, we're talking about futures data. But basically each model is really designed to provide like market intelligence. By leveraging our proprietary insights. And the goal is really to give you access to actionable data where you can make very, very fast decision and you can actually make better trading and investment decision.

[00:11:35.20] - Speaker 1
The second step is really, okay, we have this data, we have these really amazing quant models. How can we help you simplify and access to this data? Right, so we started with a Discord subscription. Today we are presenting our new Trading Dashboard. The Trading Dashboard will help you leverage our insights and will help you basically create your daily routine.

[00:11:56.29] - Speaker 1
And we're going to show you how we can do that. So we're very excited. The team really worked around the clock. The dashboard was released this morning. Looks amazing.

[00:12:04.09] - Speaker 1
And we're going to give you a demonstration in a very, very few minutes. And then finally is how can you then integrate the data into the platform that you use into the platform that you use for trading? So today we're going to show you some of our integrations. So we are integrating with 10 plus applications. We are releasing today the new integration with MotiveWay.

[00:12:26.16] - Speaker 1
We're going to have a short video on that. And we also released our new TradingView indicator. So TradingView is of course the most used platform in the world, but we also integrate with platforms like Sierra Chart, NinjaTrader, Bookmap, Quantower, ATAS, Tinker Swim, etc. So we're going to show you how this work. During the course of the week we're going to also have a session on integrations.

[00:12:50.22] - Speaker 1
But for today we're going to show you the new ones, Moti Wave and tradingview.

[00:12:56.11] - Speaker 1
All right, so next we want to share a tweet that we posted this this week. This is a tweet coming, a video coming from Cliff Asnes, Chief Investment Officer of AQR Capital Management. AQR is one of the largest hedge fund in the world. And this is really interesting because even though technology is existing based on what Cliff says, the market actually has become less efficient than in the past. So even though we have a lot of technology, we see like less efficiency in the market.

[00:13:32.29] - Speaker 1
So that's why it's very important that you start embracing the data and data driven insights because there's a lot of opportunities that you can capture even though technology is evolving. So this is what for example, aqi Chief Investment Officer has posted recently and we repost this on Twitter this week.