The Most Expensive Stocks In the Market: A Tale of Two Strategies

Welcome in, everybody. This is the most expensive stock and the best stocks in the market. A tale of 2 strategies. This is March 27th. Got a nice little presentation for you today. Going to do some deep dives into the most expensive stock in the market. Like we said in the registration email, it's a name you guys know. We'll reveal it here soon. First up, our disclosures and disclaimers. We're publishing research, we're not providing advice. That's the main one. You can read this whole thing in the replay. But we do have a big, exciting announcement before we get into that. David, FinSights is going to be at Google Cloud Next 2026.

Yeah, this is great. They're doing a special presentation, Abhilash and Ashwin there. If you want to throw that link into the chat, Kyle, it'd be great. Yeah, it's going to be awesome. They're going to be talking about the core underlying capability, the technology. These are the guys That we worked with, and these are their top AI Google expert ninjas, I would say, and super smart, great guys. I can't tell you how many testimonials I've done for those guys, but it was great. I think we were really grateful to Google Cloud. I think they probably invested a couple million bucks into FinSites. They wanted to demonstrate the art of the possible of when you take really great data like ours. And put that into great technology like theirs, you get an AI that can actually answer real questions reliably, which I think is pretty rare these days. Got a lot of AI answers out there, not very good.

Yeah.

And ours is good. And Abhilash and Ashwin, just some really super smart, great guys. Just great working with them. I think they got the best AI out there.

Yeah. Excited to see that. With that said, without further ado, we'll get into the topic of today, the most expensive stock in the market. Specifically, we're going to go full into it and break down the future growth expectations baked into the stock price, do a reverse DCF, look at the assumptions, everything going on. David, do we want to reveal that ticker yet, or do you want to talk about it first?

Go ahead, man. Go through some of these slides if you want. We got coming up here.

Cool. I think the slide next will give it away, but we've talked about it. It's not the first time we've talked about this company. Ticker NVDA, Nvidia. That's been expensive for quite some time. We've actually done a few different reverse DCFs on it. Once we call it the secret weapon for calling the top. Going back to September 2023, we also did some reverse DCFs, and even before that on Nvidia. Got links in this we can share in the chat, but they're all on our website and our community. Today we'll take a next deep dive on the expectations in Nvidia now. Obviously, the AI Race, AI wars, AI battles, whatever you want to call them, are constantly changing. It's the one constant supplying the chips and everything for it, but that doesn't mean it's a great stock.

Yeah. So let me, I'll go and share my screen here because I think we got a good question here. Richard pointed out Nvidia versus Arm, who's more expensive? We can run that out, but you're onto something there, Richard. The quick and dirty way we can compare these 2. is you got 4-point price to economic book value, because both of these companies make money. So price to economic book value is a good sort of quick and dirty comparison point. Nvidia is at 4.5 times. Arm is at 22.8. So it's really pretty crazy expensive too. But when you run the reverse DCF on Nvidia, it's really pretty interesting. Because when we go back through here, when I was first building these models, they had 100% consensus growth rates and stuff like that in there. Consensus growth has come quite a bit down for NVIDIA as it's going to in terms of growth rate, just because it's such a huge company. But let's point out here, you know, what happens when we look at some slightly lower growth rates. And here's what's happening in this, what I'm showing you right now. We start with our default scenario. I've already got some different scenarios plugged into this model where we can look at different rates of future growth. I'm gonna make this a little bit bigger so people can see it. But the idea in our reverse DCF model, folks, is that we're going to look at different scenarios of future cash flows. And we're going to run these scenarios out over long periods of time to see when that scenario, how far in the future does it take for that scenario to generate a price equal to the current stock price? And in that process, we can also look at future implied revenue or cash flow compared to the past. And you can see in this neutral scenario, just in particular, going and taking the— what we've already done here, $6.9 trillion. In revenue. $787 million, $992 billion, $6.9 trillion in revenue. And that's what happens here. So look, if the company can grow at 100% for the next 2 years, right? That's good enough to justify the current stock price. But if you think the growth rate's going to be closer to 20%, which is where consensus is, it's going to take them 19 years. And time value of money means you're going to actually have to have better profits. So for example, We can look at revenue past versus future. And by the way, this is not exactly a small number here and huge step-ups, right? They had very little profits. We're talking $215 billion in revenue. We do the same thing for after-tax profit, huge step-up there. Now, if we look at that, what's implied, you can see again, hockey stick. In terms of what's implied. Now, the way we do this, the mechanics behind it are, look, we've got a forecast page, right, where we go in and we program the system to look at different scenarios. When we put in our scenarios, we give our clients the benefit of seeing what the company's done in the past so that we know how likely our scenarios are to come true. Or how, how well they compare to what's gotten done in the past. And so let's jack these margins up close to what the company's got in the past as well. So let's just put all that in there. Tax rate has been, it was really low for a while. It's like 15%. And then in terms of the balance sheet, we should probably knock this up a bit too, because it's definitely become a much more capital-intensive business. So we set up these scenarios so that when we look at different alternatives for the future, because by the way, no one knows the future. And so the idea is to set up a set of conservative or sort of realistic alternatives for what the future might look like and then understand what that means about the valuation of the stock. Is that better than a multiple, P/E multiple? Oh, should it have a 15 multiple or 20 multiple or a 30 multiple or 25 multiple? Why don't we look at actual cash flow And when we're doing that, we're doing that— here's another company model I've got open here. And I can demonstrate to you the mechanism behind all this is a discounted cash flow model. And now the difference between this discounted cash flow model and other discounted cash flow models is that we've got multiple years, expected year into the future is what this EY stands for. And it goes all the way out for a long time.

Okay.

100 years. Why 100 years? Because when I first built these models back in the '90s, I went out 25 years. 25 years is plenty. But as we got into the tech bubble, we needed way more than 25 years. And so I was like, all right, I'm going to build a model that goes out 100 years because no one's going to ever ask me to build a model bigger than that. So we're good. And it's not so much how far the model goes out that matters. It's about casting your net wide enough to capture market expectations. And so we don't really use a lot of the data in this model. All we care about is the year in the future where the model generates a value per share equal to the current stock price or to my target price so that I can use all this discounted cash flow math gobbledygook to understand what my revenue compound on annual growth rate is, what my average economic earnings margin is, what was the performance of the business over the timeframe required to justify the stock price. So I think for this company, the price is around $254 in this scenario. And so we can say, okay, it took them 7 years to get there. What was the performance of the business? Turns out the revenue CAGR and the economic earnings margin are the same. That's unusual, but you get the idea. That's what it takes to generate $250 a share. And so with what we have here with Nvidia, We're going to be able to look at a couple different scenarios. Let's go neutral and optimistic. Let's just, let's stick with neutral. I think neutral seems like our most, I don't know, reasonable, right? Because consensus is at 20% and then 17%, 14%, and trailing down. I just give them 20% all the way out for 20 years. And then the margins, not controversial, staying about the same. Right? It's a competitive business. 64% margin is extremely high. The idea that it stays there forever, I would say that would be very optimistic. We put that in there. You can see tax rates, non-controversial. Working capital needs, fixed asset needs, not controversial. So we're looking at this neutral scenario. We're showing that the company's— the current stock price is showing that the company's got to grow revenue at 20% compounded annually for 12 years with a return on capital versus cost of capital spread of 91%. That's a little bit lower than what it's been in the past, but probably reasonable considering super high returns on capital are not sustainable. They weren't even sustainable for Apple. when they were this high, right? And so that's what it takes to just justify the current stock price. These are the implied values per share. If we go to the DCF review, we go to neutral, we're going to see in year 12, that's when the model generates a price that's closest to but still less than the current stock price. And we can see this 20% revenue CAGR. Average economic earnings margin. You can also look at the CAGR for net operating profit after tax, 20%. And this is all based on the line-by-line modeling out into the future. So you've got the revenue, the revenue CAGR you can see is at 20%. Here's the pretax profit margin and pretax profit. The tax rate gets you to your NOPAT. You take out capital here to get to free cash flow. You find the present value free cash flow. You accumulate that over time. Here's your terminal value. Our terminal value is a no-growth terminal value. So it just assumes that NOPAT stays the same after the forecast period, which again, it comes back to 12 years. Here we make all the adjustments for all the cash they got, the debt, a lot of other things we make adjustments for that we don't need to make for an Nvidia. They're cleaner. But then that's again what it takes to get down to 159, which is still closest to, but still less than the current stock price. Which is a little higher, 171, but we're within range. We're not trying to be super precise here, folks. We're trying to get a real-world sense of what the future cash flows of the company have to be to justify the price. So, Nvidia. And when we say the most expensive stock in the market, You know what, part of what we're coming at here, because it's a fair point, we're looking at price-to-economic book value ratio. Arm is looking even more expensive. But when you look at the implied NOPAT at $361— I'm sorry, at $1 trillion, and then revenue implied at almost $2 trillion, it's pretty crazy. It's a pretty big number. Pretty big number.

Yeah, right between the GDP of Brazil and Spain on that revenue number.

And those guys rank where in the globe?

11, 12.

11 and 12. So when I think when Nvidia was up around 200, over 200, I think they were like where Japan had to be. We can do this.

They were top 5, I believe.

Yeah.

The revenue would've been top 5 GDP in the whole world.

Yeah. Yeah. And we can do the same analysis on Arm. So, let's do that. Let's go in here and you can see, let's start our default scenario. Right now, the default scenario, similar, I think, of the default scenario for Nvidia, takes more than 100 years. So, if you're just going with consensus numbers and assuming margins are maintained in the default, You don't ever get there. And so, what's fun about the reverse DCF models, we can come in here and say, okay, based on consensus, you're not really showing— we're not showing much above $12 a share. So, look, let's just say consensus doesn't get it. And by the way, consensus does not get it, folks. The fact that we have this obsession about quarterly earnings numbers and whether they make it or miss it by a penny or nickel, That's just a diversion from the big picture analysis. That's, this is what I think, this is one of the values that new constructs brings to the table. So let's go with, let's do neutral. So clearly 20% is not good enough, at least for 3 years. So let's just go 20% for 20 years. And then let's also create an optimistic. Oh shoot, it's not letting me do both 2 at the same time. All right, let's go ahead and just make this optimistic and go 20%. for 20 years. Say I've done this for long enough to know that we're going to have to do better than just 20 years. And let's say margins, they don't— obviously they've come down quite a bit from where they were before, but let's say they make it back up to 20. We'll call this optimistic. We'll leave the balance sheet and tax rates the same for now. And then we'll take a look. at what this means for the valuation of Arm. And we'll take a look and see what their implied revenue is and see what that— how that compares. Let's quickly— this is a little bit easier. Let's go in and also create a scenario where we just look at— oh, here it goes. Oh, it did save the neutral. Nice. So this is going to be fun. Neutral is— Right. Higher growth, but not higher margin. They get the 20%. And this is where you see that 20% hitting. Like, this is why this is steep. And then after 20 years, it kind of levels off. Optimistic was the high growth and better margin. So you can see higher growth and higher margin, and we're still only getting to $49 a share. So what do we got to do to get this stock price to equal the current— what do we got to do to generate a future cash flow scenario where the stock price is equal to— we get a stock price that comes close to an implied price that's close to the current Stock price. Let's try jacking margins up to the highest they've ever been. See if that does it. Optimistic. Still don't get there. We're still on sixty bucks a share. So what do we got to do for growth rates? Let's try thirty for twenty years. This is the kind of process that I think this is this is super fun for me. This is like how this is really getting a handle on exactly. how expensive this stock is. Domestic, high growth rate. There we go. 17 years. You can see this is— all right, so let's take a look. Let's say, let's put both of these in here. Go both on optimistic. And then let's look at implied revenue. GAAP forecast 2, $346, $347 billion in implied revenue. So, in comparison to what the company's done in the past, Arm is more expensive than Nvidia. Nvidia is our poster child for a very expensive stock because the implied revenue is so big. And a great question into the chat here, if Nvidia is so overvalued, why is it the 2nd biggest holding in FTCE? The index that we have here for core earnings leaders. It's focused on the advantage of core earnings versus accounting earnings and that entirely. So our index doesn't take into account valuation. It focuses on one thing where core earnings are better than accounting earnings. And we're seeing that core earnings for Nvidia apparently in the Bloomberg 1000 are among the best. Versus accounting earnings. And that's— that was really based on probably the most recent data. When the rebalancing comes, Nvidia is probably going to be sold off because the core earnings are not that strong. But why has it been in there? Why have a lot of expensive stocks been in? Because they've been among the most profitable. So one of the things— there's a difference between our 2 different— we have 3 different index with Bloomberg. And if you go to the site and you see the indices, you're going to see you got the Core Earnings Leaders, you've got the Enhanced S&P 500, which is just the S&P 500 weighted based on core earnings as opposed to market cap, and then you've got the Most Attractive Stocks Index. So if you want to invest just based on our most attractive stocks, that's going to outperform significantly. 10 years, 5 years, it beats the S&P. Year to date, how are we doing? The core earning— the rating system is beating the S&P by a lot. The core earnings beating it by a little. Short term, long term, it's a winner. If you really care about valuation long term, which I think you should, the core— the, the Very Attractive Stocks Index is your best call. If you just care about profits, Core Earnings Leaders. is your best call. See the prior comment for what you could look for there. And so the answer to your question about NVIDIA is a good one. One of the largest holdings in the index is NVIDIA because it had, at the time of the last rebalancing, some of the strongest core earnings compared to accounting earnings. And that strategy on core earnings is such an insight, like core earnings is such an insight compared to what the market has, that on that alone, we can beat the market. Malcolm, does that answer your question? Core Earnings Leaders Index focuses on the core earnings edge, and that alone is good enough to outperform. And that's why I like to talk about the Very Attractive Stocks Index, because it takes into more into account. You can see in our ratings, right, core earnings by themselves, they're not even really a direct part of our rating system. Now, the core earnings distortion score stuff, that is, it's a short-term measure of how companies are going to do compared to their accounting earnings. Or now, Street earnings distortion score compares performance against Street estimates. That's a short-term metric, beat or miss. We like that. And in a market that we've seen the last few years, it's just been focused on earnings and not cared a lot about valuation. It's been a great strategy. Longer term, we think something that's based on a more comprehensive view will be an even better strategy. Yes, there is not yet an ETF for the Very Attractive Stocks Index. We're working on that deal. It's a great concept. And look, I think the fact that you've got an agent from Google that can tell you things like which stocks in the Show the companies most likely to miss earnings. I could say this for any sector. This is our agent, by the way, AI agent from that we were talking about earlier in the presentation. That's going to be a big part of the Google Cloud conference in Vegas. They're going to be demonstrating the power of their underlying AI technology for financial analysis that they built on us. I don't think they're going to talk about our data that much because Google Cloud doesn't play, or Google doesn't play favorites, so they don't want to be inadvertently or implicitly advocating new constructs. But we taught them everything they know about finance, folks, and they paid us handsomely, and they gave us this agent, which is super cool. But you can see here really quickly, right? Oh, there's the tech stocks most likely to miss earnings next quarter. There it is.

There it goes.

These are the basic material stocks most likely to miss All right. Don't want to give too much away here, but a very powerful capability based on the best data in the world on US equities. And I think the reverse DCF capabilities also amazing. And with that, we're coming up close to our time limit here. Kyle, you got some few more slides to close it out here? We can take some more questions.

Yeah, we've got the first— we did mention we were going to give a free report out, so I'm going to send in the chat A link to our Nvidia report so that everyone in this can download that. It'll be our full stock report. So if anyone clicks that link, it'll be a PDF. We've got these reports on every company in our coverage universe. You can see the details on the Nvidia rating, some of the adjustments we're making, stuff like that. And then the rest of the slides, we're really on the best stocks in the market. Do we want to Pull that up. Do you want to do— run through that?

How to find the best stocks in the market?

Yeah, we had some slides about—

I should know this because you showed it to me and I don't remember. My bad. I think we're at time. I think we're good now. Yes, good question about signing up for the agent, folks. You got to go through Google to do that for now. We are working on a better interface. You've probably heard me complaining. I don't like to complain, but I'm going to complain because we had this agent built like in December. Mid-December done, and then we spent all the time in between and tens of thousands of dollars getting it to go from the lab at AI at Google to the marketplace. And I mean, we got some of the smartest people in the world there on our team working on this, and it's still taking that long. And then they get on the marketplace; they're like, yeah, it's on the marketplace now, but you gotta go through ten pages of documentation and register with Gemini Enterprise to access it. I'm like. That's not cool. You got to sign up to new constructs and do all that. Like what? What? We're like, yeah. And if you pay us another $30,000, we'll make it easier. Like, okay.

Good Lord.

Yeah. So Sam, for now, I think if you can click on, let's see here. I think I got a link for that too. FinSites agent. Yeah. I'll put this in there. We can get you hooked up. You gotta go do it the hard way. And we're hoping to create a simpler way pretty soon. We already got quite a few of our, I think some of our pro and institutional people beta testing. But yes, we're gonna make it much easier. We're gonna integrate it into our site and all that kind of stuff. But it's, there's a lot of, I didn't share my screen here. That's what I meant to share the screen real fast. Yeah, here it is on the, the Google Cloud, Cloud Google Marketplace. Here's the marketplace. Contact sales. I put that link into the chat here. It's there. But this isn't like the most user-friendly. Google's really good at, they're really good at big customer deals. So they're not really into user-friendly because they, that's something that their clients, I guess, do.

I don't know.

I don't know what to say. Took us a long time. But it's great. We can't complain because they paid us handsomely. So what are you going to do? Thanks, Google. You spent $2 million building an AI for us. And I do everything else for it. So it's cool. It's cool. But it does take a— it is taking a long time. All right.

I think that's it.

No more questions. We will see you next time. I hope you guys enjoyed this reverse DCF case study and great questions about indices and ETFs and trading and how to understand the truth about the expectations baked into stock prices. Have a great weekend.