+40% Swing Trade | How to Find AI Stocks & Profitable Trades with Matt Caruso

I think it really helps when you have a good understanding of why you're buying the stock, and it helps you to anticipate what could happen along the way. When you look back at the leading stocks, they all have very similar characteristics, like the way they act. But the interesting thing is that not all stocks act that way. It's really a stock under accumulation that character changes.

You need to bring the right tools to the right job site. So the same tools I use for day trading are not necessarily the same tools I'm using for position trading. You don't need a big loss to figure out that you're wrong. You have to be willing to see open profit scare you and kind of disappear at a point in time. If you're not, then you're running just almost purely a swing trading strategy. So you have to kind of know where you sit. Like, it's easy to just say AI. You have to be able to make money from this AI. At the end, going back to the principles of O'Neal, the earnings got to come. So I want to hear from the companies, what's their plan to actually turn this into a profitable endeavor.

All right, welcome back everybody to the Tra Line Podcast. I'm your host, Richard Moglin. This is brought to you by the Ultimate Trading Guide, which is a free resource that you can access down below. And our guest today is Matt Cruso, veteran investor, professor, former market maker, top trader in the US Investing Championship, as well as the founder of Cruso Insights. Matt, there's a lot to talk about with your background, but thanks so much for being here. It's been a while since we've had you on the podcast, and you're someone who I've learned an immense amount from, and I'm really excited about what we're going to talk about today, which I'll touch on in just a second. But first of all, thanks for being here.

Absolutely. I think I was one of the earlier podcast guests along the way, so it's fun to be back, and it's awesome to see how you guys just keep making it better and better.

Yeah, thanks. And today, because it's something I've always kind of admired with you, we're going to be discussing how you analyze and research a new idea and really dive deep into the story, the fundamentals, things to look out for, things that really make it seem exciting, that you really want to focus on a stock. We'll also discuss a little bit near the end, the larger landscape. Obviously, AI is a huge theme right now. We're going to kind of contrast that with the rollout of the internet, and then finally, we'll touch base on current markets and some top ideas I know you're keeping an eye on. So, Matt, first of all, I know it's been, as we mentioned, a bit since you've last been on. For people who maybe aren't familiar with your background, can you just touch base quickly, kind of where you come from and your investing career?

So, I was obsessed from a young age with markets. And I guess that kind of early trading led me to a market-making job right at university. So, did that for about six years, where then ultimately I left, and I was programming some algos and high-frequency trading models for a small broker-dealer. Then ultimately, I went on my own to trade. Did that for a number of years as I enjoyed the flexibility of just running my own book. Joined the US Investing Championship, was top performer in a great year in 2020. And since then, still trade full-time, but also have Cruso Insights where I, I like to kind of share all my thoughts with the clients and members.

And what's interesting about your background is you were exposed to all these different styles, you know, high frequency, market making. How did you ultimately land on CAN SLIM and kind of your your approach now, which obviously is the evolution of CAN SLIM, you've tweaked it to your own process?

Yeah, kind of bring us into that quickly. So, it's funny. So I used to run both models. So even though I was a market maker, I had a lot of flexibility with what I could do. As long as basically I wasn't breaching risk protocols, I could do whatever I wanted. So I used to always do market-making functions and a lot of day trading. But with all the extra like risk capital I had, I would run kind of a CAN SLIM process, which is breakouts and the rest. And it was funny that, I mean, anyone who's been trading for a while just knows how breakouts in hindsight look good, but in real time, so many fail. So I remember kind of sitting there and going through a really rough like a patch where all these breakouts are failing. And it was funny because I was kind of following a little bit like a robot, as we should, you know, as we learned how it should work in a perfect environment. But I kind of realized where I had this like very nice, easygoing, consistent cash flow from day trading, where usually I'd probably be shorting or selling, where I was buying these breakouts if I was day trading. So I took a step back one day and looked at both processes. I said, whoa, there's something interesting here. So I kind of went down to first principles, like what is it about CAN SLIM that I really felt led to the big moves? And then after there, then there was the timing aspect. So I kind of had a bit of a disagreement with the timing aspects, not that it didn't work, but I felt like there maybe were ways that would work better for me or that jelled with my approach better. So I kind of took a lot of the shorter-term stuff I learned, I put that within the big picture. And then bit by bit, kind of rebuilt it in a way that I thought was maybe a little more robust, less reliant on just breakouts. It allowed me to kind of, I like to trade more concentrated, but I don't like a lot of risk. So I build into positions. And so if you're going to build into a position, you need more than one place to buy the stock, you need multiple. So basically coming from those two angles, and ultimately having worked at HFTs and all that kind of stuff, I just, the writing was on the wall where algorithms and AI was going. Everyone talks AI now, but I mean, AI attacked the trading industry a long time ago. And so I just kind of realized, you know, when you're up against the Terminator, it's a hard fight to win. And day trading really has been dominated by algos. So I felt like I had enough capital, trading is all I want to do. I just felt there would be less direct competition with speed and time and all the rest of day trading if I went to a growth time frame. So I kind of just took this process I'd been working on for 10 plus years and then built that out. And that's how I eventually shifted away from day trading and then fully into growth investing.

And I love how you mentioned there how you build into positions because we're actually going to show that today with both an example from the past, one of the best, you know, the best stocks in the past few years, LVGO, which I'm sure many people remember watching this, and then kind of a current name that you're trading, GEV. So, but before we get there, that's a little teaser for everybody. You know, the first thing I want to talk about today is your process for investigating a company and a stock, and like you said, taking the elements of CAN SLIM that you believe lead to big winners, obviously based on the research from O'Neal, but taking it a step further and personalizing it to you. So when you first hear of a stock or idea that sounds interesting from a very high level, maybe walk us through the steps that you take to dive deeper into the story and see if it's something worth investigating further, and then we'll take it from there.

So, like, I view myself as like a theater trader. Like, I mean, the biggest money I've always made, even when I was day trading, because I was always able to carry stock overnight, like I wasn't restricted just to during the day. Like the biggest moves I always made was, yeah, it was great to make the in-and-out money, but when I really caught on a key trend and I had size and I rode that up, and I would trade around it, that's where like the really big years would come from. So I've always worked from that perspective. Like, yeah, I can trade technically, and I used to trade, you know, since I would early done, I'd trade a stock, I wouldn't even know what the symbol was, I was just trading the technical action. But to take that conviction, to be able to sit and all the rest, you have to have. I think it really helps when you have a good understanding of why you're buying the stock, and it helps you to anticipate what could happen along the way. Because an interesting phenomenon about like CAN SLIM and all the rest is, when you look back at the leading stocks, they all have very similar characteristics, like the way they act. But the interesting thing is that not all stocks act that way. It's really a stock under accumulation that character changes. And so the kind of stock that William O'Neal was trying to identify, which everyone else tries to do the same now today, those stocks have their own way of the way they react to a 10-week moving average and all the rest. Those same tools. So people kind of, I think, make the mistake of saying, like, oh, these tools worked well on this stock, I'll apply it on this other stock or this other approach. You need to bring the right tools to the right job site. So the same tools I use for day trading are not necessarily the same tools I'm using for position trading. And a lot of that comes down to, you want to set everything up for the right tools to ride these monster stocks. So I spend a lot of time even before I get to the technicals, who can be that next big winner, right? And that's really when you answer that correctly, I think, is when you set yourself up to get the size, and then everything else falls in line because you're because the action is according to what you would expect. And so for me, to be honest, I'm always running a lot of scans. We're looking for earnings, we're looking for sales, we're looking for all the typical variables, right? But to me, that's not that, that's always historical information. Same with price data, everything is historical. So, you know, even CAN SLIM, when, you know, Bill didn't articulate it this way, but he would look at earnings, he would look at sales. It's not so much that they already had earnings and sales, it's always what comes next. But the thing is that the company who has those kind of numbers are likely to keep on growing. If you're already doing well, you're likely to keep doing well. And so what I always do is I run all these screens and I look at the stocks. And sometimes it becomes obvious what's going on. So with LVGO, it was an interesting case. Like COVID was a shocking thing, the way it kind of happened very quickly. And sometimes my, you know, your mind will just go to like, oh, okay, this is an obvious winner that will be. LVGO was, um, medical devices, it was analytics, it was at a distance type of monitoring, right? And so sometimes your mind kind of really gets what the next theme will be. Sometimes you don't. So sometimes it comes in a little bit late. So what I always like to do is when I start to kind of get a sense of what's going on, first I look at screens. I try and look for different stocks in the same industry group. If there's a general theme that's going to push, it's likely not going to be one stock. So if I do see several stocks coming out for one group, okay, there's something going on in this group. The best place I like to really go to, just for like a high-level, 10,000-foot view, is go to the investor relations website and try and look at the most recent presentation. Most companies have a presentation, and they're trying to always put their best foot forward. And so they're usually going to come right out, the better presentations, and tell you why you should invest in them, what their total adjustable market is. But sometimes it's funny because sometimes it's such an overnight development that even their presentations are kind of behind and don't really tell the whole full story. So the first step I would go to is to the investor deck. You can't take that at face value because, like I said, management will always make everything look as good as possible. But that's the first step to try and, okay, you're trying to sell me as an investor to invest in your company, at least I get the reason why. Then I have to try and build it within the big picture of how everything else is coming together. So that's kind of my first step process for how I look to kind of find which stocks can be the next theme leaders.

Yeah, and taking it a little bit back to the theme. Obviously, AI has been a theme that has developed pretty sharply over the past two years. But how are you identifying those bigger themes that are in the market and that can drive these bigger moves? And then on an individual stock level, it can be pretty difficult to judge, you know, all right, this theme's going to directly benefit this company. Obviously, semis, AI, it goes together, but sometimes it's a little bit more nebulous, especially with these high-technology stocks, which you have to do a little bit of digging to really kind of understand their story. But yeah, I guess take me to the theme, you know, because you were also early in 2022, I think, with identifying the more oil and gas names as being quite strong, and that's something that growth stock traders typically avoid or it's not their specialty. So, you know, themes can exist in many different ways. But yeah, how, for you, do you decide, all right, these are the larger themes that are impacting most growth stocks and trends?

So usually, I know sometimes there's like the bias of like really small-cap stocks, people think like, oh, this can grow tremendously, and it can. Sometimes, then there's the other side of the equation, like the very, very large-cap stocks. I tend to avoid those. I feel like, oh, you know, law of large numbers, it's hard for a multi-trillion-dollar company to double or triple on the rest. But each theme though has to typically address like a big enough market, like something that's really going to drive stuff. And it's really cool though, because every big market move always does come from a theme. If you think back to every big like leg up in the recent past, like, okay, now it's AI and Nvidia and all the rest, that's been kind of driving this. But during COVID, obviously, game changer overnight. All of COVID. Earlier than that, there was the whole marijuana thing, which was like legalization, that kind of changed the whole recreational, I guess, you know, I don't know if you want to call it drug use or however you want to place it. You know, there was so there's always like the major theme. There was Apple before that, there was Google. Like, it's there's always this major theme that's driving things. And so first of all, there has to be like a big enough total addressable market. Because if the company's already come in with pretty big earnings and sales, they need to keep doing that at scale. So if you've already grown, you already went from a five billion to a 30 billion company, well, now growth-wise, like if you're going to get to the hundred billion dollar or $150 billion status, you better be like, you know, tapping onto a big market. So like, even like, you know, Elon Musk, love him or hate him, he's always focused on these like massive market opportunities. And so you have to kind of almost step back. Like you kind of understand what the stock is doing, what the company's doing specifically, but then you have to kind of take a step back and look as an industry or as that entire group move, is this something that can be really big, much bigger than just what one company can handle? Because again, investors as a whole, if you're even if you're an individual investor, you want a company that can grow. But if you're a big money manager, if you're a BlackRock, a Fidelity, all these kind of massive, if you're going to be putting billions of dollars to work, it has to be a big total addressable market, or it's not even worth their time. So like, step one is like, once you look at the company, you look at themes, step back, how are they really going to change things? That's the growth side of stuff. Then after, you know, you kind of spoke about oil and gas and different things. And as a market maker, most of the stocks I traded were gold-related, so I have a really good kind of monetary background, and that's very cyclical. So then at the same time, you know, there's some stocks that maybe don't have a huge total addressable market, but just the swings of the cycle can be really dramatic. Like if you get a stock, a cyclical stock, coming off of the lows of its cycle, it could be a multibagger on the way up as it gets back to the top of its cycle. So, but again, the tools are different. You're not looking at like long sustained earnings growth in that situation because it's a cyclical play. So again, always knowing like how to pick which tools for the theme that you're building into.

Yeah, perfect. So taking it back to individual stock. You mentioned the first step, which obviously is to check the investor relations page, take a look at their recent presentations, maybe take a look at the products that they offer and judging, you know, how the themes can impact it. What's the next step for you? Say that really piques your interest. What are some other things that you look into? What are some things you look out for, whether it's, you know, I know a lot of people focus on high percentage ownership by management as can be a really good indicator. Do you listen to conference calls? You know, what's kind of the next step for you to build conviction?

I always look at the balance sheet because again, being in the, you know, having traded a lot of mining stocks early on as a market maker, they were really, they always have to raise money, right? They're always expanding the mine, it's very capital intensive, it's very different than growth stocks and all the rest. And so they're always kind of, when the stock goes up, they like to sell stocks. So it was funny, you know, in that business that the company's always talking about how everything's going to be so great, but then every time you have a bit of a stock rise, bang, if you know, they raise money, the stock's going to drop 10, 15% on you or more. So I just got really used to the first step is going to look at the balance sheet. Do they have enough cash? Even if they're cash flow negative, if it's a well-funded growth company, even if it's cash flow negative, they should have like enough cash for an extended period of time. They probably did like a massive raise, have a really big investor backing them. That's different than, again, just to compare a small mining company where usually you want retail investors or a few institutional to kind of put some money in. It's a more dilutive process. So I always go to the balance sheet first. I want to know, are they cash flow positive or not? Because there's always that risk of having to raise money. And then after I look at the rate of cash burn, and if that checks out, I don't have to worry about an impending kind of cash raise. Then after I kind of look at how well-run the company is, what's the return on equity? Are margins being compressed? Like, if you have, if you're like in a leading position, you're probably going to have the best margins in the business. It's only when there's like a real competitive nature that comes in that all of your margins get squeezed through competition. It means you're losing your competitive advantage. So that's kind of like when I'm doing a deep dive. So I like the idea about the company, I like what management has to say, I check the balance sheet, then I look, how are they responding to competitors? Like, even if there are competitors, if it's a growing industry, everyone's doing well, there's not, they're not even directly competing with each other, they're just each trying to get new business. So it's a different type of appearance on the financial statements. And so that's kind of the process I'll go to next to really dive in to make sure there's nothing wrong. You did mention like there's concentration of customers, that's always a risk to me. And that hurt me with Fastly in the 2020 Investing Championship. I was actually in first place when then after they lost TikTok as their biggest company, and like it was a massive position for me that really knocked me down from that. That was frustrating, but that was just a good reminder. Make sure there's no massive competition. There's some stocks where they can have 70, 80, 90% of their revenue from one customer. So make sure there's no customer concentrations. Key too, but that would that's not typical to have so much customer concentration. For me, the biggest risk is usually running out of cash or just not having enough cash to fund operations.

So if you had to list out a few red flags that would kind of turn you off from a company, you just mentioned, you know, the cash flow problems, the concentration of customers. Is there anything else that would really say, okay, you know, I'll just take a step back, look elsewhere?

I like to look at management. Ideally, it's always founder-led. Sometimes it's more an issue, I would say in smaller companies, if the CEO doesn't have a track record of just jumping from like company to company, he's just filling the shoes, he's probably there for the salary, he's just maybe for the stock options, he's not going to really probably drive things very well. So either you want to have really good management, or you want like a founder-led. Founder-led's always going to have their heart in there, they're going to have definitely monetary incentives aligned. I remember starting out, people used to tell me, like, you know, look at management. It was such a, how do you, I mean, I don't know these people, how do I figure out if it's a good manager or not? Why is it important? Because at the end of the day, like Elon Musk, he's not just another regular guy. I mean, he's, that's an extreme type of case. But if you look at all of the really great kind of company moves, most tend to be founder-led, or it's a really good established management team that maybe is just going onto a new project and they see a new opportunity, they're kind of trying to make that blossom. So if it's kind of like a small stock and you see the CEO keeps kind of jumping around, has a poor track record, and there's no one really who's an expert in the industry, that's kind of a big red flag that I'd look at as well. But it's harder because it's more qualitative, it's not easy to kind of put a number on it. It takes a bit of a deep dive, almost like a LinkedIn search, you got to do and take a look at everyone what they've done.

And are there specific market cap sizes that you prefer? You know, some people like over a billion, some people over 10 billion, but you mentioned kind of avoiding the mega caps because they might, the returns might be capped a little bit. But is there a specific range that you look for, or does it not really matter to your process?

So I want to say it doesn't matter to my process because you've seen all kinds of stocks do well. But we all have like our personal biases. I've always had my best success with like the stocks that are, let's say, you know, just about $10 billion to about $50 billion. Like that's the range that I've always felt, you know, because once you get really big, like once you're like a Microsoft or an Apple, you can still grow, but it's a little more of like a slow grind of executing on a longer-term vision and the stock kind of goes up. So because I'm looking more for like, my mind is looking more for like an explosive type of move, it's rare for that. I mean, like Nvidia did it last year because, you know, there's like the ChatGPT was this overnight revolution. Either you got it or you didn't. But typically, like the stocks that are already a four or $500 billion company, they can keep growing, but it's probably going to be about like, you know, doing it, doing growth at scale in a consistent manner, rather than, wow, look at this new, you know, this S-curve of this new adoption of this brand new product. So that's why I always like the $10 to $50 billion range. When I'll sometimes trade a little smaller, but again, as you go smaller, then there's more red flag risk. So I mean, if you get a two billion dollar company, it could be a 10x to 20x if you can catch that. But there's like a higher failure rate, higher turnover, more volatility, lower liquidity, more kind of red flags to be aware of. So there's always the pros and cons to every part of the market cap spectrum. But that's where my favorite portion is.

And flipping, you know, market cap size to time restriction, I guess. Are there any kind of sweet spots in terms of how long a company's been trading? Whether it's a new IPO, very new IPO, or it's been out for a few years versus a more established company? Is there something you prefer? You know, obviously, eBOBOK, they've done excellent work on the lifecycle trade, identifying, you know, a lot of the names that come out of the institutional due diligence period, which is that large base that happens after the IPO. Is that something you take into account as well, or do you kind of look past?

Yeah, yeah, like I'll trade IPO bases for there usually be some really violent moves because there's a very small float to stock, most of the stock is still locked up, and there's usually a good roadshow going on, so there's a lot of enthusiasm. But I have a personal rule, like an IPO sell rule, I call it, where if I get that like 80 to 100% run out of an IPO base, even though the stock looks great, there's great fundamentals, I always sell. Because then there's always the lockup, lockup expiration period, and all the stock comes to market again. Having been through that mining space, I just know how important like dilution can be on performance, and it takes time. When more stock comes to market, it takes time to get digested by the market. So usually I'll trade the IPO phase, the first few months, if there's a setup, it's a little more rare, but it can happen. And then after that, I usually like stocks that are maybe two to five years old. They're still relatively young, but they're fully out of like that lockup expiration, and stock has now changed hands enough where there's probably some strong institutional holders that are holding the stock. So that's usually like my sweet spot I like to look for.

PLTR comes to mind as a good example of that. It had an amazing IPO move and then just went dormant for two years until, you know, coming out of that just recently, a year and a half or so ago, and starting that longer, more mature move. So that's fantastic. A lot of what we talked about so far is the fundamental side, you know, the more qualitative aspect, as you mentioned. How does all of this pair with the technicals, the chart, and signs of accumulation, that type of thing? And if you had to break it down percentage-wise, you know, this matters more than this, or is it kind of a very holistic view where everything comes together?

So again, you know, because obviously your background is a lot of growth stock investing, and so are people who watch your channel, they'll know William O'Neal, obviously, and everything he did for the industry. And it used to frustrate me when he would say, like, I forget the number, he would say, if it was like 80% of everything is fundamentals and charting 10 or 20% of it. I used to get frustrated because he, whenever he would teach, he would always be looking at charts. So it's like, I would spend so much time just studying charts, studying charts, and then after he'd like throw this comment in there saying, like, oh, you know, 90% of it is the fundamentals. So I like, okay, so I kind of got it. But what I get is kind of what we touched upon earlier, is just like, the thing is that if you get the fundamentals right, then the technicals will work properly. So it's almost like you can, you can look at a company that is not undergoing one of those massive moves, so like, or even like like a Tesla, for example, that has those moves and it goes dormant. So, you know, for a while, it won't do anything. Then suddenly, as soon as institutions kind of feel like, okay, we get the growth story, we believe the growth story, let's start allocating funds, it's like a complete switch of character. And now all the traditional technical analysis tools will work just properly. So for people on the outside looking in who don't have experience, if they're just trying to apply some of these tools to any kind of random stock, or even a good stock, but maybe the trend is over, it's tired, or you're too early, they're not going to work. So they kind of feel like this doesn't work. But that's it. It took me a lot of time and study to kind of understand what Bill was saying, where, yeah, the technicals are key, that's how you're going to time everything. I spend so much of my time on the timing of this and deploying the technicals, but they won't work if you don't get the fundamentals right. So it's this weird kind of catch-22. But once they all kind of come together, technicals just play. I mean, I was always a technical analysis first as a market maker, it was all just prices, it didn't even matter what a company did. So I have a lot of kind of different technical tools I use, but it's always, you know, after the rest is kind of fulfilled and understanding what the story will be.

I think that's well said. And you know, we've talked about kind of your high-level process. Now applying it to a recent example, GEV, which you're currently trading. Maybe touch on what you found out when you looked into the company, what piqued your interest, what made you want to learn more, and then ultimately, we'll talk about the technicals. And you've got this great chart analyzing your buys and sells, and I want to talk about how you manage risk and all of that, because that's always fun to talk about. But yeah, taking a step back, how did you first hear about GEV and what did you do to look into it?

So GEV, it was part of looking at like the past year, just top winners, and seeing General Electric, the parent company, being a top performer. So for me, it was kind of like, whoa, how did General Electric become this? I totally missed that. That's just definitely not a stock I would traditionally be looking at. But then I always want to go back and say, okay, there's some kind of trend that I'm unaware of. And so I looked into it and I found out how they were spinning off different divisions. And so I'm always very pro spin-offs. There's a book by Joel Greenblatt called, you can be a stock market genius too, is the name of the book. And he's a former, I think he's a former, I don't know if he's still a hedge fund manager, but definitely former hedge fund manager. And it's a great selling book. And so this book here kind of breaks down all the different kind of unusual market situations that he would use to his advantage to get outsized returns. So one of them was the spin-off. And what's so when I started digging into GE and I saw the spin-off moves, the thing that makes a spin-off great is that most CEOs want a bigger company to manage. It usually means a higher salary, more prestige. So if you're managing, let's just say a $150 billion dollar company, you know, you have, you're running one heck of an enterprise. If you say, oh, you know, we're going to split up into four companies and I'm going to be down to a $30 billion enterprise to run, most CEOs for their own specific egos wouldn't want that because you're probably going to command a smaller salary, you definitely command less prestige. So if a company is spinning off assets, unless there's, you know, even if it's like a junk asset, it could still be a good thing. But sometimes, depending, but if they're spinning off things, it's almost always to unlock shareholder value. They really see an opportunity, there's something that, you know, they feel shareholders are not fully grasping what the value is of this kind of conglomerate to these different units. So that's why usually it can be usually a very bullish thing. So when I was looking at GE, I saw they're spinning off GE Vernova, which is GEV, which we're going to look at. And kind of going through the slide deck, I already kind of noticed a lot of these electric, you know, power generation companies performing so well. And that's a case where sometimes you just totally miss it. Like, I mean, I saw them moving up kind of with Nvidia. I didn't, again, you're not a specialist in every industry, so I didn't realize that there's going to be this massive electricity demand for AI specifically. So kind of understanding that, having missed the first move, but usually it's never one move, there's always multiple moves. So missed the first move, but then saying looking at GEV and saying, oh, okay, so they have this world-class management from General Electric, recent spin-off, so really looking to unlock shareholder value. Of the three units that they spun off, GEV has the biggest future earnings growth, and they're on this key theme, key trend, that was like check mark, check mark, check mark along the. And again, in terms of market cap, it was like, I forget what it was I was looking at now, it's gone up quite a bit, but I don't know if it was 30 billion or something like that. So like, smack dab right where I would like for market cap. So that's kind of like looking at that. So speaking of themes, that's kind of how you step back and, okay, good management, good theme, wanting to push shareholder value, and then after just great fundamentals. And so once I looked at all that, then it's, let's get to the chart and figure out how we can kind of buy this thing. That was kind of my process of how I figured out. And again, most stocks that are going to do well always have that first leg up that you probably miss unless you're an industry insider. I mean, like unless you're specifically in that business, you're probably not going to be anticipating this sudden improvement. So I know people will argue, well, then just be a specialist in an industry. But the problem is, sometimes that industry is dormant for your entire career, and you miss out on all these great stocks. So as a generalist investor, you tend to have to acknowledge you're going to most times miss that first move, but then hopefully cash the second and third. Sometimes you're fortunate, like with LVGO, I was fortunate because there was the COVID drop, and I was able to connect the dots and catch it from the very beginning. But most times, you can miss that first move, but there's always time for more.

I it always reminds me of David Ryan. I think in the Market Wizards book, right there, actually, he says stocks I'm always focused on stocks at double because they like to double again. So even if you miss that first move, doesn't mean you can't have an amazing trade coming out of that. So I think that's so true. Let's go ahead and share the chart. And let's also maybe show that LVGO annotation of your buys and buys and entries there, because I think that's a great way to show your style and how you piece into trades while also managing risk really tightly.

So this came up. The way I kind of build into trades came up just because I became risk-averse. I just didn't want to have to, I want to have concentration, but I didn't want the risk of like an overnight disaster kind of unfolding on me. So if we look, take a look at GEV, this is when it IPO'd. We kind of had that first leg up, and then we went dormant for a number of months. But this, it was very strong during this period of time compared to a lot of its competitors, even versus the market. I mean, this really took its time to kind of consolidate sideways. But again, kind of looking at the way a character will change on the stock. So this was clearly in a basing structure, and you can see how wide and loose it got. But you can see after coming off of earnings and having this bump up, and now everyone's really talking about how electricity demand is going to be such an important factor. Look at how the character during this pause here was so different from every other kind of swing up and down. I mean, there was this clear line in the sand at, let's call it like 180 in this area. And every time we kind of got up to it, it was like immediately knocked down with intensity. This time here, we kind of ran up and we really sat above there for a number of days. And often, even though I prefer candlesticks, sometimes I'll just kind of switch over to a close-only line chart. Let me see here. Right there, line markers, because, you know, sometimes it helps to just show how the tightness will change. So you see like on a closing-only basis, it's very clear, it's up and down, up and down. But then you see here, wow, this suddenly went from being all over the place, where for a number of days, almost a couple of weeks, just no change. So even a lot of the principles, like Bill O'Neal would talk about on a weekly chart, again, if you kind of pull it away and stop looking for a specific pattern, like he would look for a three weeks tightening, rest, and all the rest. But I like to kind of look at what was his thought process, and it's looking for that change of character where the stock is able to hold onto its gains in a very different way. So you'll see that sometimes on the daily chart as well. And so here, what I did basically to start this off, there's a pattern that I've noticed, which this came off of my study from years back as a market maker, where again, I was buying these breakouts only to sell them on the way down, the exact opposite of what I would be doing as a market maker. And then I would see them take off. So I would always look back at some of my trades and say, like, oh, I sold it right on the 21 exponential, I should have been buying it there. Oh, I should have been buying it there. But you can't buy it there if you're buying the breakouts. If you want to manage risk, there's all these catch-22s to trading, right? So often, I've grown to very much dislike buying breakouts unless there's like extreme volume and like a news catalyst, like something where it's really obvious, like, whoa, they just surprised, there's an upgrade, something. Most often, if a stock's just like walking into new territory, I'll let it do its thing. And I call this the failed breakout pullback, because very often you'll break to new highs and then you just like pull back to that 21, and I'll buy it right on the 21 because from experience, I found that's where you tend to find support if it's a normal pullback. So I initiated here. I always love being able to initiate like on a pullback because then after, as it goes up, I can add into strength. There's another pattern I like to always look at, where again, it's abnormal to have a number of stocks trade within the range of one bar. Again, as a market maker, even today with algorithms, the high of a previous day or the low of a previous day is an important point for that intraday trading session. So let's say for example, you're trading on August 15th, if you're playing long, well, a seller came in at the high of that day, and he totally absorbed all of the buying demand. And same thing at the low of that day, sellers were coming in, but buyers totally absorbed that selling demand. So those two points in time, as a market maker, you're always trying to figure out like, is that big seller there? Where, where are the big sellers, the big buyers? And you want to kind of position off of them with low risk intraday. So it's very odd for a stock to not take out the higher low of a wide range bar for a number of days. And even myself, I would always, if I was looking to see, is, you know, if let's say I want to buy X number of shares, and we get near the high of the day, I would personally try and break it out above the prior day's high. See, does the seller come in? If they do, okay, let me get out, I'll back off. If they're gone, okay, maybe we can push this up now with a certain amount of intensity. So I would even always prod the highs and lows to see. So to see a number of stocks in a tight range is very abnormal. So I call that a mini coil, basically a coil is like a triangle, and it's just like a small version. If you go intraday, you'll probably see kind of a triangle building. So after we had that initial pullback here, this here was due to, I think, a

Bloomberg article where some wind turbines fell down. They have wind energy, and I don't know, people algorithms got a hold of the news and they kind of just like pushed it down. But it was, it was sold off and came right back. That's where we bought it. Uh, but then, basically, we got right back into this range again of this one bar session. So, so if this was going to break above this, where this has been this resistance all this time, I'm going to get long there. And what I like is it's not the absolute peak of the move, so it's less obvious. And so that's when I added a second time.

And then we had a run-up. And you can see here again, we had this one wide range bar, and we had one, two, three, four bars which all traded within the range of this one range bar, which again is odd. And so then when it broke out of there, I added again. And, and what's nice too is when you're looking at it from that perspective, you can say, like, look, if we break above the high of this range, either we're going to expand into a new direction, or that seller is going to come back and knock us right back down. So you don't need a big loss to figure out that you're wrong. Again, all this came back to kind of the short-term trading I used to do. So what I like about this pattern, it does, it's not necessarily a very high win percentage pattern. It's not right all the time. But if I'm in the direction of trend, I already like the stock. I'm already accumulating the company. I want to find a way to add to it at a point where this new stock, if I'm wrong, I can get out very quickly. But if I'm right, I have a lot of extra stock at a very low risk. So when this broke above this range here, we add it again.

So kind of looking at the different buys as they came together. Uh, you know, different people use different percentages. I usually like to put about 10% of my account at each buy. So you kind of start with 10%, 20%, and here you have 30% of your account. But you have 30% at $24.25, but your average cost is already down to $19.55 because you did it over time. You took your time to put it on. And to me, that's it's the only way you can do it. By over time, you see if the buying is real. And two, by buying into strength, you have a cushion where if there is some bad news that comes out, you know, like, like we saw here, there's an article here. I forget on the, on the 12th, what happened. I don't remember why there was that gap down. But, but, um, I think maybe it was a downgrade. I'm not sure. But there's going to be these gaps against you. So if you just go put on a 30, 40% position and the stock suddenly gaps down 8, 10%, you're in panic mode. The liquidity is low, you're trying to get out of a big position, and it's, it's not a place you want to be. So by kind of building into it, this, this only works if you're looking to capture a big move and you think there's a big runway. If you, again, if you apply the same kind of tool set to a short-term move, it's a bad idea. Because if you think it's a short-term swing, you want to sell into strength, take your profit, and walk away. This only works if you think you're, you're working into a new sizable uptrend. So again, using the right tools for the right, the right means is what, what matters.

And so if you kind of take a look, I'll bring up my Lavango trade. This is what we, we shared on the very first, uh, podcast we did together. This is one of the big winners I had. I won't go into all the details, but just to kind of show people how the process stays the same. This is now years later. Um, I began buying Lavango on this, this gap up. I call it a kicker, where you're kicking above the, the high of the range of the prior day. It, it broke above the downtrend line and formed this little doji. I call that a doji flag. So I added there. I added on the gap. So I basically built in all this way. And, and where did we get to? I got to, uh, I have to check my notes here now. There's a lot of notes. I remember we spoke through it all. So it's, uh, best to go look at the original video. We'll, yeah, we'll link that down below. And right now, and I highly recommend watching that because it's, we went, we went in depth here, walking through each, each part. Uh, and this is years ago, so I don't, I don't fault you for not remembering everything to the tee. I was able to find the chart, so that was good. But there go, uh, but so at the end here, we ended up with about a 32% position, uh, with a sizable cushion. So once we got up to point, uh, was it point eight here? So again, my process is the same. I, I got to about a 30% position here, and I have a good cushion. Does it work all the time? No. You need the right stock. You need a strong trend. But again, this is my personal goal is to try and find a big leader and get a good size of a percentage of my portfolio in it and, and sit in it for an extended, uh, advance. So a lot's got to go right. But at least because I always think risk first, my, my, my risk is always maybe four or five percent on that initial buy. I mean, if this, if this initial buy had not worked, it would have just kept falling, and I would have sold the stock and, you know, come back to it another time. But because it did work and it had the rest behind it, I was able to build into it over the next few weeks. So just a good example of how you kind of start off with that idea generation of why, why that company, what's the theme, what's the trend, and then after bringing that all together in with, you know, it's a recent spin-off, young stock, has a proper basing structure, and then the actual timing of the entries with risk management. That's, I think it's a good example of how, um, years later after Lavango, we're still running the same kind of playbook. Exactly.

And, you know, this, this group, this theme, I think is the strongest right now in the market. We've got, we've got the rank on a 12-month basis, industry rank is one out of 74. One out. Yeah. So this is, this is the strongest group we've got. Stocks like VST, CG, they're more nuclear, I believe. But, you know, they're acting well as well. Um, yeah, this is, this is moving today. And, and ZEG, I think also is acting great today and is moving out of a flag from that gap. Um, so, yeah, this group is working. If you go back to, um, GEV, I do have some questions here for you, cuz I want to dive into each of these buys and how you manage risk on them. But first, with the concept of the mini coil, I think that's key for, for everybody. I definitely recommend re-watching that part as Matt explained it. And I think Matt, um, at one of the conferences, you went in depth into the different entry tactics you use. Uh, so I'd recommend that as well. We, we'll link that. But I, I'm looking for that same thing. And a lot of that is based on, you know, what I've learned from you, what I've learned from other people, that that relative tightness, uh, after that wide and loose base, as you mentioned. And we've actually got, uh, an indicator that I, I developed that kind of helps find that. If you don't mind going up to the top and adding an indicator, Matt? Yep. And then just type in RMV, or relative measured volatility. What this plots down below is the current volatility compared to a recent lookback period. And when it gets really low, down to zero, which, which happened right before your buy one, that's suggesting that price is very tight relative to recent price action. So right there, that's a low RMV spot. It's identifying that mini coil, the same thing you're looking for, just described in a different way. And it, it identified also right before your buy, uh, buy number three, that that short flag that it built. So I love using this up the right-hand side of a base and then shortly after the base. And that's, that's actually one of my questions I had for you. How far outside of that base breakout are you willing to add? Because you said 10% each time, obviously you don't want to get too top-heavy. What's kind of your process, uh, for that to make sure you're not buying too extended move, moving up your cost too much? Do you have a, do you have a rule kind of built around that?

So there's always, you know, exceptions like Lavango was. I, I probably breached my, my own rules because, like, you know, sometimes when there's extreme demand, you're going to get more aggressive. But in general, um, I, I like to only buy within 10% of the basing structure from. So let's say the high here was 185, so, you know, about $20 within there. That brings me maybe to 205, which pretty much falls in line where, where we are here. So if we're 10% from the, uh, base structure, or 10% from the 10-week moving average, to me, it's, it's open season. Will I ever kind of go beyond that if we're, we're a little more extended, if there's a unique situation, there's a unique catalyst, and there's unique dynamics? Sure. But, but in general, it's a higher risk proposition. I mean, like when you're, when you become very extended, I mean, here GEV has has held these gains very well so far, impressively. Uh, but when you're just far away, it's just the nature of stocks that kind of pull back to key averages or not. So if it's a unique stock, if you're, if you're talking like, let's say SMCI, let me just bring that up from last year. If you take a look at, like, this move up here, I mean, the basic rules don't matter. This is a momentum catalyst-fueled run, and the more you get in, the better. You know, but this is very rare. Again, like not only picking the right tools, but knowing what you're hunting for is very important. Because if you say, like, oh, I'm just looking for these dramatic up moves like this, well, fine, then you have to realize there's maybe only going to be a handful of stocks out of maybe many thousands each year to do it. And you're going to have to catch at the right time in that year. So your, your probability of catching one is just so low. So you have to kind of really factor that in. So that's why I kind of have those rules just to kind of prevent, you know, myself from just that formal impulse of chasing things too far. It's that 10% from the base and 10% from the, the 10-week. Yeah, I think that's a good guideline.

And, and getting into your buy one now, uh, as a great pullback buy. Are you entering as it kind of hammers back up through that, that moving average? Um, um, and then are you managing risk at the low of the day, the moving average, once it's kind of pushed up from that? Talk me through, kind of how you actually entered that and how you manage risk on that, that portion. So, um, I like to buy it right when it comes down to the average. I, I know for some people who are breakout buyers, or even even, you know, like, um, looking for tightness and buying on, on the move up, it's, there's a bit of, there's always that comfort of buying as things are going up because you feel you're going with the trend. Uh, the issue though, I've just noticed, is sometimes, you know, you can kind of bounce around a breakout area for a while. So if you kind of buy it once the strength comes in, then a normal, you know, volatility the next day is enough to knock you out. So if you look here, this didn't fall much, but from the, you know, the close of this day, let's say around almost 184, the next day we did fall back down to, uh, 179. So depending how tight you are. So what I, in my studies, the reason I use a 21 is I don't think there's anything special about the 21 average specifically. It's an average. But what I just noticed is that, you know, most stocks when they break out of a base straight up off the bottom, they're going to have that 10 to 15% pullback, which is usually just enough to shake out everyone who's a weak hand. It's just part of that normal back and forth. And so I just noticed, just the way looking at example after example, that usually coincides more or less with where the 21-day average is. So I always like to make things as simple as possible as possible for myself. So eventually I just said, hey, look, when it gets back to that 21, that's, that's my target. I don't have to kind of, you know, guess each time where I think it's going to go to. So that's why. And I just buy it right on the 21. Similar to sometimes I'll buy right on the 50, 50, right on the 10-week. Because if you're, let's say the stock has already declined 15%, I'm buying it on the 21. It's already declined 15%. That's where it should normally stop. I give it another 5%. And if now it's still falling after it falls another, I mean, now it has fallen 20% from its high, the whole breakout is probably faulty at this point. I mean, you didn't hold the breakout, you pulled back 10 to 15%, you bought it, then it still fell another 5%. Well, maybe we were wrong about the buying demand in the first place. So I basically get, get to be established a position with only 5% risk. That's usually the maximum. And usually it doesn't, if, if you're really right about it, like I, I did a similar buy on Palantir here, uh, where was that? Uh, here. So we had again, this kind of cup with handle here. We had this fast move up, and you see we pulled right back up. This was, I cheated a bit because it was a bit above the base. I prefer it to be in the base. But I bought this at 35, I think it was. And I mean, it barely, barely even got below that. So usually if you nail it just right, you, you pretty, pretty much, um, get the bottom tick if it's a, a normal pullback. Yeah. App is another recent example of a, a nice pullback to the 21. It shook out a little bit below. Look, another perfect look. You just, you went for this fake breakout, just kind of just got above the highs, you came back to the 21, and then you went. So yeah, everyone who bought the first one is, is stopped out, and then they're also too annoyed to try it again. And then the second one goes. So the market has all these like fractals of itself. Like it, it's, it's always, it's always close, but it's always a little bit different, you know? So, uh, that's the, uh, that could be the frustrating part of it all. But another perfect example of how it's applied. Yeah.

And for, for this one with App, uh, is that an example of a mini coil? The two inside days right before, uh, the breakout? Because it's not a super wide range bar, but yeah, just wondering if that kind of meets what you're looking for. Yeah, when, whenever you have kind of just like two bars nested within one, uh, to me, it's another, this is like, kind of a two-in-one. You got the pullback to the, the 21, and then you form the mini coil. So you could even buy and then add, and it took off. Um, but again, this works so well, not just because of the mini coil, but because of the general setup of App. And so sometimes, and I did that a lot in early days, is that I, I thought it was the pattern creating the, uh, the move. It's not. The pattern is just a way to time the move with low risk. So you have to kind of still do the rest of the, uh, the process. But that's a good, a good example of a mini coil there too. Richard. And, and with the low-risk part, is key because if it fails, your stop is very tight. And they're not all going to work like this, which worked. So you want to escape with a paper cut. If, if, if you can, from, you know, from 88.57, which would be the, the break of this mini coil, the low of this bar is 85.23. So I mean, you, you're talking like a 3% risk. You know, like, so if it breaks above the high of this bar, you definitely shouldn't turn over and take out the whole range of the bar before. So I usually put my stop at either the close of the prior session or the low of the prior session to the breakout. Because again, if this is a real move, well, why are you then going negative on the session? So you, you can really find these good setups where there are two or 3% risks. Again, normal volatility of a stock is going to be 2, 3, 4% a day. So there, there could be a high failure rate. But the point of this pattern is not win percentage. The point of this pattern is a low-risk entry in, in a general theme or direction you're already working on. So perfect example. Yeah.

And this entry tactic is the last step of the puzzle. The last step. Everything else has to line up before you're looking for that. So I think that's key to remember. And sorry, can you go back to GEV? I, I went on, I brought us on a, a side, I sidetracked us here. Uh, buy, buy number two, uh, the kicker candle. I know that's one of your favorite entry tactics as well. Talk us through how you bought that, where you managed risk on that part of the position, and if you were moving up your stop at all, and buy one, that'd be interesting to to talk about as well. So sometimes you, you get like a couple of patterns happening at once. So here's a kicker where you had a previous like red candle, and you kicked up above the range. So you're again, if you're closing down, it's rare to gap above the range of the prior session. Here you basically gapped right out of, of this mini coil here. Uh, this wasn't necessarily a kicker, but the way I was looking at this, again, it's, it's understanding the essence of what the pattern is. So if you kind of take a look at, you know, this was the high of that, that bar there, and the low of that bar was here. It's almost a mini base on top of the base, basically. And so like, normally this obviously breaks. If you're going to put this as in a computer to look for a pattern, this, this is not a proper mini coil anymore because this bar ruined it. But it was just for me, it was amazing to see like, well, look how quickly we just got right back into the same range of this bar. Like this bar was an important range. So when we broke out of here, uh, again, the, the, the buy was the high of here was 188, let's say 189, call it. If you'd have gone negative, which would have been 184, what's $5 on a $200 stock? I mean, you're neg, you're less than 3% risk, right? And it allowed me to add another 10% of the portfolio to this, this position. Again, this is why, you know, which stocks do you focus on? I like to take 10% account positions. Do I want to have a very illiquid stock with a wide bid-ask spread? You have to factor that in. Sometimes there's great growth stocks, or they're just thinly traded. So, you know, it's not always just about which stock is going to go, but which stock works well with all of your, your process. So for me, if sometimes it, it could be a, a really nice looking $80 stock, but there's a $1.75 spread. Well, I kind of, for this type of approach, you know, it doesn't work well because you're looking for tight risks. But again, here we had again, this, this other mini coil right here. So the breakout was, uh, above 204.19, so call it 204 and a quarter. The low of the prior session was 199. So again, a $4 risk on a $200 stock. It's, it's a 2% it's negligible. It doesn't always work. Again, this is a really good example. Everything really kind of, this is a, a nice textbook example of how it all came together. But, um, it's just the power of of using low risk. And again, at the end of the day, getting many multiples of your risk is key to survive as a trader. I mean, it's important to cash the big winner, but there's going to be those, those bad years where the market's tough. There's going to be periods of time just where you're off of, like, uh, your focus. I mean, just your mind's on the right direction. I mean, life happens, things happen. We're not robots. So you need to be able to kind of survive those tough periods as well. And you only do that if you're really managing your risk. Like, like making the money is always secondary to being able to manage risk. Because I've seen a lot of even professional investors who were killing it way more than me, even I was trading next, and then ultimately they blew up and they're out of the industry because they didn't have risk management, um, down pat.

Perfect. I, I think that's very well said. And, uh, bringing it back to GEV, this, like you said, this is acting phenomenally well. Uh, it, it's progressed really nicely from your buy points. It's tightening up again and forming a short flag, a little bit more extended from the moving averages now. But, what, what's kind of your mindset now? Your, your average cost is all the way down at 190. How are you managing risk with, with this? What kind of, ultimately, would get you to sell a portion or, or your entire position?

So, uh, with, uh, Caruso Insights, we run two strategies. It's the same strategy, but one that kind of sells a little bit of stock into strength to de-risk it, and the other one where we're purely looking for super winners. It's the same strategy, but we're not selling anything. Because if you think about it, like, you know, philosophically, if you're trying to catch the next major winner, why would you sell any stock at all? So that, but that comes down to character, risk management, all the rest. How do I do it? I, I do it as a mix. Like GEV, where I had such high conviction, I, I didn't really sell any stock into strength. So that's why I sell my full, uh, position on. Looking at this perspective, um, usually we, we'll sell a little bit in the strength to lower the average cost. It's easier to sit through the pullbacks. Because once it gets going this strong, even here, we have another mini coil setting up right now. I mean, as we speak, look, these three bars, despite, you know, today, there was, uh, I didn't see where we are since we started the call, but there was the, uh, Iran launched a strike on Israel. I mean, there, there's plenty of geopolitical risk going on that's causing like pretty wide market swings. Despite all of that, I mean, GEV is up on the session. And it's, it's three days we're sitting within this one range bar. It's incredibly tight and incredibly controlled. So on a mini coil base, a breakout above here, uh, would be another add-on. But we're extended. So this is where you have to kind of figure out how much you want to press the position. Well, will I add above, uh, 258.64? I may, but I'm not going to just add it to my average cost. If I do, again, that would be a breach of my risk, because you're more than 10% from your, your key average. So, you know, this is a situation where it's showing so much relative strength versus the market on a day where the NASDAQ was down almost 2%. This is up already. It was a key leader. Does that call for maybe breaking your rules and taking another low-risk trade? Perhaps. So I, I may do it. But in general, ignoring what comes next, my aim is with this original cost basis down at 190, is to just be able to sit with pullbacks where this comes back down to a 10-week average. I don't know if this is a real true leader that's going to go to maybe 400 or something. I mean, I don't know where ultimately it ends. You're going to touch that 10-week average or that 50-day average. Does that happen back down at 215, or do this keep going up and it happens at 280 after this has gone to 330 and pulls back to 280? That's the, that's the tricky part. We never know ahead of time. So you have to, you know, you have to be willing to sit through those pullbacks. Every leading stock you look at, I mean, almost without any exception, I think there's a couple, but almost with no exception, you're going to touch that 10-week moving average. So if your goal is to sit in a stock for more than two or three weeks, you have to be willing to see open profit scare you and kind of disappear at a point in time. If you're not, then you're running just almost purely a swing trading strategy. So you have to kind of know where you sit. So I'm willing to sit through this pullback. How do you prepare for that is, is important, uh, because it's not my only position. So what you have to do is when things are strong, when the equity curve is going well, you have to anticipate that, okay, we may get this market pullback. Things are very hot. Ideally, you want to sell into strength and you want to sell all of your weakest stocks first. So maybe another stock you're up 12% or 15%, it's not a game-changer. But if you sell that into strength, ultimately when GEV pulls back, I bet you the weaker stock will pull back even harder. That's something I always say is like a, a really odd, like maxim of the markets that people don't realize, but the best stocks are unique in that they go up the most with the market when the market's strong, but they also come down the least when the market is weak. So I used to, early on, have this kind of, um, you know, I think it's a normal way to think of things, where I'd be in stocks that had these big moves up, and I'd be like, oh no, if the market comes down, this is really going to fall. So I would kind of sell a leader because I was scared of it falling too much, and I'd keep a laggard because I said, oh, it hasn't gone up so much yet, it won't fall so much. But then when the market weakness comes, the leader just kind of sits there, doesn't do much, and the laggard kind would just fall apart. So it's this weird thing where you have to reprogram your mind where the stock that's actually the strongest will probably come down the least if it's also under accumulation. So once you build into this position, if you think you have a true leader, something that's really unique, it checks off all the boxes, you need to be willing to see it come down to the 50-day moving average. If you don't think you have that kind of stock, and again, this is where you have to get that in your mind too, so much is psychological. And I had a hard time with this. Not every stock, most stocks, the large majority of stocks won't be special. You want to sell those into strength and just think of it as a way to look, I'm doing this to protect my equity curve so I don't get scared and sell GEV in a panic when it comes down to the 50-day average. And there was one stock in 2010, that was my first year, I had a really like incredible growth stock position move. Even at work, I was a market maker and I was doing that on it. It was, it was a crazy year. But there was one stock, Aruba Networks, it's not, it's not traded anymore. I kept doing it backwards. I build into it, have a big run, and it happened like two or three times on the way up. The stock tripled, I made no money. I'd build in it, run up, it would come down to the 50, I'd be under like panic of the, you know, the P&L coming down, I'd sell it on the 50, then it reset up, I'd buy it, it would go up, then it would come down, I'd be in panic and I'd sell it on the 50. So I said, you know what, if you want to be able to buy on the 50, you need risk capital to to do that. So you have to only, you have to, you have to prepare for that on the way up by selling the weaker names. So that's kind of, it's a long-winded answer, but it's because the individual stock is directly linked with the whole portfolio. Like it's nice to go back and study the stocks on their own, but the way you feel, the way that's why, you know, applying all this in real time, you're balancing so many more variables than you are when you're looking at one stock. You know, when you look back at one stock, you know that was a leader, you know that the market was strong, you know, so you know, you, you don't have the pressure of everything else of your portfolio going right or wrong. You know, so in real time, you have to balance those factors too if you want to get it right.

Yeah, I, I think that was extremely well said. And, uh, bringing it back, a step again, and GEV, obviously related to the, the AI theme, based on through energy and the need for that. Um, I know you want to touch on a little bit, kind of your thoughts on the overall AI theme, you know, and how it compares to, to the internet rollout. Uh, I don't know where you want to start there, but, uh, yeah, I'd love to hear your thoughts on, on, kind of the larger context.

So I think we're, we're lucky because, uh, we can look at the internet, which is pretty recent, uh, and see how that unfolded and use that as a bit of a playbook. And so I, I know like people look back and they kind of like lumped them all as like the dot bubble and everything blew up and was, and all of that. But, uh, that was like a decade or a decade and a half in the making. So if you think about where we end, even to this day, it's still carry-on effects. So every major theme is going to have multiple tailwinds to it. So if you go back even to, I know William O'Neil will talk about like jet engines and airlines in the 60s, where, you know, uh, jet engine was created, so then you had airlines took off like crazy, you had, you know, uh, hotel chains take off to to satisfy the need for new travelers. There's always these knock-on effects. So if you look at the, uh, the internet era and how, I think this is the playbook I'm using for the current AI boom, because the AI, the AI boom has the potential to be a platform for many iterations, just like again, the jet engine allowed for many things to benefit from that invention. So if you look at the internet, the internet really started to, you know, the personal computer only became possible because Microsoft created Windows, like an operating system that people didn't have to code everything to be able to use a personal computer. So Microsoft came out with the operating system, they had tremendous, tremendous runs up in the 80s. Um, once that happened, people, you know, were like, okay, great, we have this computer, but it'd be really helpful if I can communicate with somebody else. So the internet comes alive, but that opens up a whole other set of things that you need. You need the infrastructure to communicate with each other. So Newbridge Networks came out in 1992, it went from $8 to $80, which is a tremendous advance. Um, Cisco Systems came out with switches to make the internet work better in more places. That went from 1990 to two to 2000, that went up 100,000% move, not $100,000, went up 100,000% move. Uh, if you look at EMC, then came out, they created memory, so the computers could do more. Uh, then there was Compaq came out, they created laptops, you want to take your PC on the go. And then the, then the internet created the need for a portal. Yahoo, AOL were created. And that went to, we need faster internet. So then the Ethernet cables came out with Nortel Networks, they had tremendous moves. And then people got so used to email, they said, oh, I'm on the road so much, I wish I had this on my phone. Then in 2003, that brought Blackberry up, I don't know how many hundreds of percent move. So right, it's like each iteration of this technology leads to a new technology, to a new massive stock move. So I know Nvidia kind of captured the imagination because people already knew the company for so long. And even in terms of market cap move, it was astounding. Like, I mean, it actually moved up all the indexes one, because you went from what, 500 billion to like a $3.3 trillion dollar value in terms of market cap move. It was probably very unique. But if you look at any kind of, um, development of a technology, it's, it's layer built upon layer built upon layer, and it creates all these new winners. You know, you know, iPhone came out because they said we could do better than Blackberry. And Google came out because we could do better than Yahoo. And now ChatGPT came out because we have the internet, we have super fast stuff, and now we have better memory and all this kind of stuff. So this is, this is so stage one. We're still where we were in the 80s and early 90s, where it's infrastructure. Like GEV, GEV is not AI, it's just infrastructure to empower AI. Nvidia is not AI, it's just infrastructure to to enable AI. So think about it, if, if Nvidia had a move from 500 billion to 3.3 trillion, and they're not even the output of AI, well, why would you invest in any kind of infrastructure unless the output is not going to be greater than what you invested in? It wouldn't make any sense. I mean, BlackRock and Microsoft just got together, they're launching a fund to invest up to a hundred billion dollars in AI infrastructure to enable the, the rapid, um, you know, growth of AI. We looked at CG before you brought up because, uh, Microsoft got Three Mile Island, which is a big nuclear plant in Pennsylvania, to turn back on so they can power specifically Microsoft data centers. This is all the early stages. Just like Microsoft was not the personal computer, just allowed people to build apps on the computer and to to navigate the computer. This is so early stage. That's the most exciting thing because, um, and the thing is, is each at each step of technology, you always want to see who's the winner of that specific step. So yeah, early on, EMC was a big mover because they had memory, but then ultimately it was somebody else who took that memory and then did something new. And then after, you know, like, then after, um, because we had, you know, internet and all the rest, eventually we needed cell phones, and Blackberry became the king of cell phones. They took over from Nokia, who in the late 90s, they had the first big move up. Then it was Blackberry, then it was iPhone. So you always want to, and so that's kind of the tricky part too, because it's always shifting to someone new. And people, I think most people are are kind of, um, a little bit biased, like following sports teams. You almost like, you make a lot of money with somebody or with a company, and you want to keep rooting for that, that team as if it's like a team where I'm going to stick with them through thick and thin. That's not the case. Because I mean, look at Blackberry, had a tremendous move, like unbelievable. Apple totally dismantled them within a few years. And so it does. So I mean, I don't know what'll happen with Nvidia, but how do I know if someone doesn't create a new GPU that's faster? And again, there's always, I think the, the false belief that the big player is in a strong position that the smaller players can't compete with. But if you look at the history of of innovation, the irony, it's usually really small players that come out. I mean, who's ChatGPT? How come, I mean, yeah, Google has an an AI now, they have their old Gemini and the rest, but why was it some small company no one ever heard of that came out with this revolution that kicks, kickstarted all this? So do you really think that suddenly it won't be some other really smart entrepreneur that's going to kick off maybe a, a GPU better than Nvidia? Or maybe they don't go after Nvidia, maybe they figure out another angle that no one ever thought of with an application of AI. And AI is a broad spectrum. People look at it as like, you know, um, you know, communicating at chatbot type of stuff. That's just really like a smarter way about doing things and allowing computers to be more autonomous. So you unlock, like, I mean, looking at autonomous driving, that's the next big push also by Musk and Y Combinator and so many other kind of different players. If you unlock autonomous driving, that's basically a real-world AI application. You can append the entire like mobility industry, which is huge. I mean, what, what the jet engine that you talked about, it's like the jet engine, exactly right. I mean, and you're doing it again, you're doing with car. Like think, think of like, if you live in a city center, most people have to pay 20, 30, 40, $50,000 for a park space, plus registration for the car, plus gas for your car. If you can get autonomous vehicles, you can go on Uber, and, you know, it's unfortunate that, you know, there'll probably be less human taxi drivers, but the rate of the ride will fall significantly. I mean, look, I was a market maker, I thought they would never get rid of market makers. When I, when I first saw algo, I said, well, this is a tough business, you're a trader, you got to know what you're doing. How are you going to program that? Well, fast forward five years, and they didn't really need market makers that much anymore, you know? So if they can figure out driving, the scale of how that would change the world, it would, it would open. So I mean, and that's just one, one use case, one application. So it's, go back to the internet, take a look at all the great companies, but don't just look at the stock prices, look at how they always built on what came before, and it unlocks something new that people either didn't know it existed or they never thought of even doing it in that way. So that's why I get excited, and that's what I love about growth investing. And I think for growth investors, yeah, people look at Nvidia, say, oh, growth has had a good run. Yeah, Nvidia had a good run, but you know how many tremendous opportunities are about to kind of come our way? To me, for me, it is an incredibly exciting time to be a growth investor.

No, I, I think that's really well said. And are there any other companies that you're watching at this point that, uh, maybe you haven't talked about before, but, but like you said, you know, it'll be the hundred other companies in the next decade that can be the amazing resource that we don't know what they'll be yet. But, uh, yeah, are there any others that you're specifically focused on right now?

So there's like, you know, some, I always, I think the main theme right now is, I like in the 90s, you just want to focus on internets, but like, there's different ways that's going to come out. So one is autonomous driving. So Uber signed a deal to bring like the autonomous YMO cars to Austin and Atlanta. Whether that that blossoms, we'll have to see. That's still like early. It's not a direct thing. You know, Musk is going to have the robo-taxi event on October 10th to see if they're going to have some kind of robo-taxi. That's kind of the autonomous vehicle play. Is one thing I'm watching. There's a small little company called Serve, uh, I forget the the full SV is the name. They build these little like, uh, small robots. Basically, their whole pitch is, why would you take a, a two-pound burrito and transport it in a two-ton car to bring it to somebody? So basically these small, like, small little, like shopping carts, you can put the burrito in it, it'll just drive itself to the person's house. It's that's very, I mean, it's a low price stock, it's like a, it's like a micro-cap. Just something I'm watching. But, um, looking at that general theme of of mobility and how that's going to play out. I think there's interesting things. There's, uh, the rocket companies where they do refinancing mortgages and all the rest. They have enormous data pools. So data is like the currency of AI, right? And it's funny, the whole like refinance industry, mortgages, all the rest, is an incredibly fragmented industry. And their goal as a company is to kind of become the Amazon.com of their industry. And they're really pushing data first to be the biggest lender, the most efficient lender. Um, and by using AI, I mean, you get experiences that you just suddenly come to expect. They look at Netflix, you just expect that to show us what we like in front of us. That's AI doing that. So if they can kind of both take the tailwinds of falling interest rates, which I think is, it's a whole different monetary discussion, but that should help boost refinancing and mortgages, sprinkle that on with really good management who has enormous data that they want to put into AI to kind of capture a bigger share of that market. That's another potential output. It could be in unique places, you know, like, like just like how, uh, like with Hilton Hotels, you didn't think that would be a benefactor of jet engines, but it was. So it'll be interesting. Yeah.

Very cool. There, there's a lot to cover, um, cover there and, um, yeah, no, I'm excited for what's to come. You've got me excited for, for the next few years. We'll see what opportunities come, come about. Um, I know, uh, you know, you put out, put out such great content there and, and teach through Caruso Insights. Do you want to mention where, if somebody is interested in, in what you've said today, where can they go to learn more from you and, uh, yeah, just learn more in general, if they'd like to?

There's, uh, CarusoInsights.com is where I have, uh, my membership where I discuss, you know, videos twice a week with people going over all of my, my process and all the rest. I also have a bunch of free resources. I'm on, uh, YouTube and I'm on Twitter very often at Trader M Caruso, where I, I share a lot of ideas. So there's, uh, plenty of places you can hear me talking around.

Yeah, perfect. And, uh, specifically on AI, were there any podcasts or things you've been kind of, uh, absorbing to learn more about the possibilities? Cuz obviously mentioned a lot of different applications. I was curious if there's any podcasts or, uh, you know, resources that you would recommend for people who want to learn more and, and just learn more about, you know, potential ideas.

You know, I, for me, actually, I've been spending a lot of time reading up on the, the company websites, trying to hear directly from them. Uh, podcasts are are great, but sometimes they're very general nature. So like, I, I want to really, I want to understand the use cases because again, with every new kind of theme, it becomes like, you know, the joke was, every company says I have a website, the stock would go up. Like it's easy to just say AI, but you, you have to be able to make money from this AI. At the end, going back to the principles of O'Neil, the earnings got to come. So I want to hear from the companies, what's their plan to actually turn this into a profitable endeavor? So I spent a lot of time looking at the company sites.

Perfect. Well, Matt, I, I always enjoy talking with you. I always learn something new. So thank you very much for your time. Uh, I'm sure everybody watching as well, really enjoyed it. And if you did, go ahead and leave a like down below. Subscribe if you're new to the channel. Uh, check out Matt's links down below. Uh, Matt, thank you again for coming on and, uh, it's always a pleasure.

Absolutely. Thanks for having me, Rich. Appreciate it.

Yeah, absolutely. And, uh, thanks again for everybody for tuning in and we'll see you guys in future videos. Take care.