Earnings Recap: Decoding Signals from SpaceX, Palantir, Merck, AMD, Caterpillar, McDonald’s, & More

Welcome everybody. Good to see you today. Nice to see so many folks with us and some new names here. We got some interesting companies to talk about this week for sure. And one of my favorites to talk about these days, let's see where it stands on our list market cap-wise. Let's talk about SpaceX. Who here likes SpaceX? I love SpaceX. Yeah, we're on the same page. Love SpaceX. Love the idea. That doesn't mean I love the stock. I think it's lost $1 trillion already in value. So that's money transfer away from the public markets to private equity. And that's not, it's not great. These guys don't even care enough to publish The auditors report on their internal controls. They don't have to because they're an emerging company. They're young or whatever, and the SEC's relaxed rules. But like, why not? Why wouldn't you just say, "Hey, yeah, we've got good internal controls." I'm working with a new nonprofit. The first thing I'm doing is setting up controls. Like, why? How do you not do that? Anyway, it's shady. I don't like it. I'm more of a substance over hype guy. So. That's going to be a thing for me always. But yeah, so look, this is a bad company, bad stock. It's really expensive. The expectations for future cash flows are super high. If you haven't seen our report, I think it does a great job. Thanks for dropping that in there, Kyle. I think it does a great job of just quantifying what the valuation means. Right, this is— there's a lot of good stuff in here, a lot of competition for SpaceX and all the things they do. It's not like they're out there, yeah, they're the best at rockets. That's a losing money, losing business. And the government is their— is one of their biggest clients. So hello, Robin. It's a tough— anyway, look, good company, maybe bad stock. But look at this, profits, they're just negative down to Huge numbers here, bigger than Apple and Nvidia. So that's pretty, pretty crazy. But yeah, look, Apple and Nvidia, super profitable companies. We know about Nvidia, you know about Apple. SpaceX, way more profitable than that. Even if they get close, like halfway, that's a $500 billion. That's, I think, where is SPCX right now in terms of market cap? $1.7 trillion, man. So we're talking about more, less than a third of what it is. And look, surprising, it's up here in, in the last 5 days a good bit, 22%. I would call that a head fake, friends. Call that a head fake. The bigger trend is down and down a lot. And I would suggest to you that is probably a, a better way to think about this. Again, good company, super expensive stock. I think the earnings were disappointing and it dropped on that, but then has bounced on the— I don't know, on the expiry of the lockup. Musk has had ways of keeping the stock up in the past, Tesla in particular, when everything was looking terrible. So I think there are short-term manipulations, especially in the option markets, that people can take advantage of. And when you've got as much money as he has, And you go in and you can 100x your investment by just buying a bunch of calls and forcing the seller of those calls to own the underlying as a hedge to ensure that they can provide the stock if called upon, if the option is exercised. That's a trick. So yeah, I would avoid SpaceX, folks. I would avoid it. Our report, I think, provides a lot of details as to why we did this before the IPO. We remained confident that this is what should— that this is a stock to avoid, not a bad company. What we're seeing right now is a transfer of wealth away from public investors to private investors. That's what we're seeing. That's the SpaceX story. Everything else is a distraction. Wall Street's really good at distractions. They're good at pumping narratives that get you to not think about fundamentals, to believe that the fundamentals don't matter. That somehow in the future magical things will happen and the fundamentals will emerge good enough to justify the price. I wouldn't— I just, I'm not a big fan. Eli Lilly. This is another one. You know, I think this is— this was like we identified this as a long, I don't know, price adjusted or something at $20 or something. I can't even remember. We have it in some of our slide decks. It's now almost $1,200 a share. Look, good company, and it's gotten to be an expensive stock. It's gotten to be a little bit too expensive. So we would suggest you move away from this. Let's see how they do on earnings this week. Good earnings for Eli Lilly. Let's see what they said about Eli Lilly's raised guidance. Yeah, I think these guys are doing the Mounjaro and Zepbound. These are great drugs. And I think this is, this is another place where AI is going to manifest, folks. And I think this is also a misconception about AI itself. I don't believe it's going to make that much money. Too commoditized. Chips, ultimately long-term semiconductors, that's been kind of a commodity business for a long time. I remember back in the Intel days, they were looking at the book-to-bill ratio just to see how things were growing. And it was a cyclical business. It's a commodity. Nvidia's got a better chip. China's making chips too. So, I don't think long-term that these margins are sustainable in any part of the AI stack, because ultimately the value is going to accrue to the people. That's kind of the idea of technology in general. The people selling the technology, selling the magic, don't benefit as much as the people who actually use it to create value, especially when there's so many sellers of the magic or the AI. And you've got lots of people selling chips, you've got lots of people selling compute. Compute. You got lots of people building data centers. You got lots of people selling AI models, the whole stack. And so they're all going to compete their margins down to something very small in the long term. Where does the value actually manifest? It manifests in your hands, in your ability to go take something super cheap, cheaper than hiring somebody, and get it to work for you and allow you to have your own business. It manifests in the hands of Eli Lilly. Where they use it to come up with better drugs, better proteins, better peptides. The peptides, man, this is like— I think these peptides are huge. Guys in the gym talk about peptides all the time. I haven't tried them at all yet. They say they're great. I got a good friend who's a doctor. She says they're great too. Look, peptides is just— it's like a software patch for your body. They figure out how to put together the amino acids in a very particular way to provide directed medicine. And I was just talking to a guy yesterday at a football gathering for my youngest son, and he's in the Army. They're doing research on directed pain relief. And he's like, yeah, man, we found this way that instead of you taking an ibuprofen, he goes, like, he goes, David, less than 5% or something of that pill actually makes it to your pain. So that's why you got to take so much really to have an impact. And he says, there's ways that you can actually direct that right to the spot. But it costs a bunch of money, and look, ibuprofen pills are so cheap we can't justify it. Right? So the technology can be there, but if it doesn't necessarily generate real value for you, it's not going to matter. But with peptides, these things are cheap, are inexpensive, and they can go directly to the source. And that's that's what makes them so effective. And by the way. Ozempic, that was a peptide. That is a peptide that came out long before it got popularized. And they make it illegal. Comes out, people are like, oh, this is great. They use it. And then they go to the FDA and say, hey, will you make this illegal until we can scale it and manufacture it and make a ton of money on it? And FDA says, maybe write us a check. And they say, yeah, of course. Yeah. How much you need? Like, oh, take a couple million bucks. And, um, and Eli Lilly and Pfizer are like, Yeah, sure. You want that now? How about a gift card right now? Deal's done. Yeah, sure. That'd be great. And they're laughing because they're going to make billions. Billions. And I think that's a— and again, I'm getting off on a divergence here or off track here, but AI is going to help companies, lots of companies, medical providers, individuals get better Make better stuff. The AI by itself is useless without someone to manifest it, to use it, in my opinion. And that's where the value is going to be. So I just don't think all these AI companies or chip companies— this, I think we're in a bubble. We're in a bubble for this stuff. And companies like Eli Lilly may continue to generate great stuff, but it's expensive. A lot of that's priced in. AMD, chip company. I pretty much have talked about this. 17.9 price to economic book value, folks. Let's take a look at this over time. Look, accounting earnings way better than economic earnings. Shares going up. Yeah, I'd sell shares too when they're this expensive. Returns on capital pretty low. No pet margins. They were really low back here because they're in a glut. Now all of a sudden, oh yeah, everything's going. Honestly, there's so much money chasing AI that one, one AI, it's like whack-a-mole. Oh, Anthropic AI, Gemini, Meta. Oh, those aren't so good. Well, let me go put my money over here. Let me put my money over here. Whatever AI company I can put my money into. Let's see here. Free cash flow. There's negative free cash flow. Yeah, they're going to make money. It's going to— there's a lot of demand for what they do. But again, what are the margins going to be like? Because if they're charging too much money for access to their chips, it's going to make the compute, the memory, the inference— it's going to make it too expensive. And then the AI model companies are going to be like, I can only charge $0.10, but you're charging me $0.15. It's not going to work. So all these deals you're seeing about these guys, buying each other's and funding each other's chips and promising all this stuff. It's all based on a pricing regime that I think is way too high, way too high, because there's multiple AI competitors and they're going to give it away for cheap. Look, here's a look at the price to economic— price economic book value staying pretty much flat. $27 in 2021, $27 currently. No growth value. And we're talking like 17, 19, 18 times that. Watch out, folks. And let's see what happened to AMD this week. Still good. I think they had a pretty good report. You can ask Caterpillar. It's another example of that's the whack-a-mole. How about these, all these industrial companies helping build the data centers? Yes. Caterpillar, they've got less competition than I think even the semiconductors, the chip companies. There's just not that many big machinery companies out there, frankly. And so I can't remember, Kyle, like if we What we had about Caterpillar, if it was a long idea once a long time ago. Yeah, a while back we had it in there early, and but it's since gone on a big run. So yeah, look, we were in Nvidia 25 cents a share split adjusted. Lilly long time ago. This is what we do, folks. We find the stocks before everybody else. We that's what in super stocks, that's in alpha stocks specials, that was when your most attractive stocks. And we can afford to stand up here and say, don't believe in the prevailing narrative because we can give you good alternatives, dramatically superior alternatives whose numbers and analytics you can trace right back to the source, way lower risk and way more upside without having to wring your hands over like, oh my gosh, do I need to sell now? Because I know this is a bubble. I've seen this movie before, folks. I lived through the tech bubble. And I had all these friends, man, on the trading desk at Credit Suisse who are like, yeah, man, it's crazy. These IPOs are terrible. I'm not going to do that. I'm not going to invest in these things. This is junk. Oh my gosh, I can't believe we're doing this. It's not illegal. What? And then they come to me a few weeks later, say, David, all right, couldn't take the pressure. I'm buying. And it doesn't matter. Fundamentals don't matter, David. It's the greater fool theory. As long as someone else is out there willing to pay more for it, doesn't matter what I pay. I was like, all right, brother, feel free. I'm not your— I'm not your priest. You don't have to confess to me, but I hear where you're coming from. And that's a mentality that prevails. All right, that's Caterpillar. I think Caterpillar had a pretty good report too. Let's see, Eli Lilly beat expectations, or AMD beat expectations. Yeah, they had a good one. CAT. I think CAT beat too. Say about CAT. Exceptional.

Yeah.

Infrastructure demand. These guys, I would imagine, do really well. Fortunately, again, I think it's already priced in, folks. I just think it's already priced in. Tier. All right. So one of my favorite companies. I'm a big fan of Alex Karp. And he and his CTO on a recent earnings call made an analogy that I think is excellent about the AI business. And by the way, you should, if you're not listening to some of Alex Karp stuff, you haven't seen some of my recent emails on Alex Karp, you should take a look. You should take a look at those because he's nailing it. He's flat out saying, companies, if you are token maxing, You're giving Anthropic or OpenAI all this money because you're using it so much. You are absolutely chopping your own head off because they're not delivering a lot of value because they don't really know your business, but you are giving them their business, your business. You're giving them all this proprietary usage information and they don't use it. Yes, they use it. And they frequently publish updates, new skills, new capabilities. Whatever they want to call them, that are based on usage. Same is true of you, my friends. Don't put anything in AI that you would not trust to be on the front page of the Wall Street Journal. Don't do it. They're using it. They're burning billions of dollars giving this product away below cost to do what? To collect information. That old saying, if the product is free, then you're the product. It also applies if the product is super cheap, you're the product. The product is subsidized. So the product doesn't make the seller money. You're the product. Absolutely the product. And Palantir, great company, really expensive stock. But the analogy that they make that I love so much is that the ontology is the body, the AI is the brain. And you guys have been hearing me say that none of this AI stuff is ever going to be working or worthwhile if it doesn't have good data to drive it. AI models are like every other model. This is a universal principle of a model, not a fashion model, but a business model or a financial model. If the inputs are bad, the output is bad. There's no such thing as model alchemy. It can't make the ingredients better than what they are. You can't make steak out of flour. You can't make cake out of steak, right? But the ingredients have got to be right. They've got to— if you want an expert answer, You've got to have expert information. And until that's the case, it's not going to work. And so what Palantir does that I like is that they go to companies and say, listen, we're going to help you harness all of your data into a proprietary AI that only sits in your servers. No one sees it. By the way, we're going to use an open-source model, not Anthropic, because we can't take Anthropic away from Anthropic. It's all run on their systems. They do all that stuff for you. Black magic behind the background. And then it's why? Because they want that data. So Palantir says, no, we're cutting that off. We're cutting off everyone else except for you and your data. These are your systems, and we're going to design taxonomies to help organize all your data into an ontology that gives meaning to all that data. And we're going to put that into AI, and then you're running. And that, that's the model, folks. And that's when he says, The ontology is the body. AI is the brain. What's the taxonomy? Who can guess? For whoever guesses, you get a free Most Attractive Stocks report.

Blood.

Taxonomy is the blood. You got bad blood, you can have bad body, bad brain. Yes, the data goes into a taxonomy, Wally. You're right. But like, in keeping with the body analogy, AI is the brain. Ontology is the body. Data is the blood. All right. So Palantir, but I think people get this, right? Guys, folks, there's smart money out there. Palantir is one of the most expensive stocks in the market. Look at this. 49.1. Also has a 322% return on capital. Chamath Palihapitiya recently published, did a post on Twitter, and maybe I'll look it up, but he did a great post here recently. On the AI stack, and he went through all the different pieces, and he's I'm not in any of these anymore because I think they're commoditized except for one, which you call it harness, which does what Palantir does. Invest in companies that does what Palantir does. Merck, this looks cheap, folks. How did Merck do in their earnings? But yeah, I got strong beat here. Everything looks good about this, folks. Good business. And what I said about these drug companies, what I said about Eli Lilly. Merck too. I think AI is going to be a huge boon to these businesses because they got the distribution and they've got the ability to productize AI. When I said AI has to manifest into something that creates value, they got the ability to do that. Top line revenue beat and a narrower than expected adjusted loss. So good stuff for Merck. Those down this week. That'd be one, folks, I'd be looking at as opposed to all the popular stocks. Toyota. We talked about GM and Ford last week. Let's talk about Toyota. I'm a big Toyota fan in general. I love the cars. I think they last forever. And struggling a little bit here. I think they've been putting a lot of capital into the EVs and other stuff, but I think they're going to get this figured out. It's been one of the best companies in the world for a long time. It is a foreign filer, so we're only getting annual data. From them, but it looks cheap. Looks cheap, but big fan of Toyota. How did they do? What was their earnings report like? Five days. Pretty good. If anybody can handle macroeconomic pressure on margins, it's Toyota. But the business is looking better. Good surge in net income. I'm guessing that we don't get the filings yet, but I'm guessing these numbers are already getting better, and that these numbers would look even better. Because if this is in the process of improving, then these numbers will be even cheaper looking. Pay close attention. Net, good company, expensive stock. This is the same story. We should be getting the Q any minute now. How do they do? Great week for these guys. The AI trade is definitely back on here these days, folks. Definitely back on. First ever $3 billion quarter. Aggressive full-year outlook upgrade. Stock leaped 12%, 13% initial trading. So yeah, good week for these guys. Good week. Good earnings. People are cheering. I think I was just in another interview recently and I said, I think what we're setting up here is basically a big sell-off later. People have seen— look, guys, it's all over the news. These Chinese models is a real thing. It's competition. The first time we heard of DeepSeek, NVIDIA dropped, I don't know, 20%, 30%, some huge amount. I don't remember the exact number, but NVIDIA got crushed the first time DeepSeek came on the scene. And now we got DeepSeek, we got Moonshot, we got other stuff out there, models out there, and there's going to be global competition. We need open source models. Cybersecurity is not possible without an open source model. You can't say, oh, my AI agent that's gonna be helping me with cybersecurity is OpenAI or Anthropic because I don't know how those guys work. Shoot, they could be the attacker. We've already seen them attack stuff. So I have to have an open source model that I control that's private to me. I control the weights, I control the dials, I control the input, I control the calculations. It's like having a security guard that works, that potentially works for the bad guys, right? It's like hiring security.

Yeah.

How to— from criminals. It's like hiring a gang to be your security. I know I want my own people cover my stuff. Yeah, decentralized, Sam. It's gotta be decentralized. It's— and that, that's the open source code has been amazing for society. Jensen Huang, and I'd sent an email out about this, Jensen Huang dropped the hammer, like when he came out and wrote that letter in favor of open source modeling. And what he said was so prima facie true. So abundantly and overwhelmingly true that everybody in the industry jumped right on board, except for for your most attractive stocks report, except for Tropic, even OpenAI. I don't think they mean it. Don't mean it.

Don't care.

They say whatever they need to say to get business done. Amgen, good company, not as good a stock. Falls in a similar category as Merck. How they do this week?

Pretty good.

Good week for Amgen. I think we've liked this company, I think, for a while. I believe at some point it was— yeah, we used to have a positive rating on these guys, but then it got expensive. Yeah, that was back— it was a while back. Yeah, a while back. We're early. We are early on stocks, folks. That's where you want to be. That's where you want to be. We're going to— are we going to see risk early as well? Yes. But guess what? Our systems outperform. Maybe that's a strategy you like. You buy stuff you can trust and you sell it when it gets expensive. Could it possibly get crazy expensive? Yeah. McDonald's, one of my favorite companies of all time. Executive compensation is linked to ROIC. It's looking attractive again. That's great. We love that. One of the things I love about this business is just return on invested capital, just unstoppable, super high for a restaurant. 6 sticks there and all the competitors run all these crazy promotions trying to steal market share and they lose money running the promotion and McDonald's just, they just bounce off. McDonald's is like, yeah, good try. Didn't work. And I'm going to get to a couple of questions here. Can I determine the dollar amount of what a company's free cash flow and dividends paid of the past few years have been for a company using New Constructs data? Oh, for a company using our data, not for a company that's a client. We track— Kyle, do we have the— I know we got the free cash flow. Free cash flow is right here. And then dividends paid, though, I know we show that. There's your free cash flow. I know that we show in all of our featured stocks for dividend model portfolios, we always show a comparison of dividends to free cash flow. So we've done that work. I'm not so sure if we've got an easy way to get that on our site.

We collect it in the model, but that would require institutional-level access there to get the specific dividend data on the cash flow statement in the model.

Okay, so if you open a model— what he means by model here is if you open a model and you look at financials, and where would it be in the model?

The cash flow statement. We've got the cash paid for dividends, which for SpaceX will be zero.

Yeah, here we go. Report accumulated value for dividends paid. Yeah, so we would Yeah, we track that in the models. It's there. That's where Kyle gets it to find reports like the one I showed a second ago, which I clicked away from. So, yes. All right, folks, we're at time. Great question, Forrest. Appreciate it. And everybody, thanks for being with us. We'll see you next week.