The Earnings Report That Could Move the Market

In this episode of Motley Fool Hidden Gems Investing, Motley Fool contributors Jon Quast, Matt Frankel, and Rachel Warren discuss:

• What to watch for during Nvidia's report on Wednesday.
• How Nvidia's report could ripple through the stock market.
• Overbuilding with data centers?
• What is Jevon's Paradox?
• What to watch after acquisition announcements.

To catch full episodes of all The Motley Fool's free podcasts, check out our podcast center. When you're ready to invest, check out this top 10 list of stocks to buy.

A full transcript is below.

This podcast was recorded on Aug. 24, 2026.

Jon Quast: There's one earnings report that could move the market. Motley Fool Hidden Gems Investing starts now. Welcome to Motley Fool Hidden Gems Investing. My name is Jon Quast. I'm your host today, and I'm joined by our guests Matt Frankel and Rachel Warren. Today we're going to dive into our Mailbag a couple of times to talk about data centers, also talk about mergers and acquisitions. But first, we wanted to get to our news of the week. This week, Nvidia is going to report quarterly earnings results. Just to share an anecdote from over the weekend, it's amazing that there are some people who still don't know what Nvidia is, and I had to explain it to somebody. I want to do that here in the podcast, not take for granted that everybody knows what Nvidia is. This is a $5 trillion company. Mass very, very important. Really got it start in gaming, but those GPUs that it makes are what is powering the AI revolution. These are what are being bought up like crazy to fill the data centers that you might have heard about that are going in around the country. Very, very important company and it is reporting its earnings later this week, Wednesday to be precise. As we get started here, Matt, tell us about Nvidia and what we should look forward to in this report.

Matt Frankel: Just to put what you said in a little more perspective, Nvidia actually invented the GPU, and they have roughly a 95% market share in the Data Center GPU space. They're a dominant player. That's why all these data centers that everyone's pushing back being built in their towns, it's their chips that are filling them. They're expected to report about $92 billion in revenue this quarter, billion would it be. Their management guided for $91 billion, but honestly, investors just simply assume that they're going to beat expectations at this point. It's a pretty fair assumption given the past few quarters. That would be roughly 100% year-over-year growth, as well as a sequential acceleration, meaning that the growth rate from quarter to quarter is expected to pick up. That's off an already pretty enormous revenue base. I mean, of course, Data Center is the big piece to watch. They do other things, but quite frankly, everything else Nvidia does, their gaming chips that you mentioned, pro visualization, which is like graphic design chips and things like that. The Auto division, they make chips for automotive use. They're essentially rounding errors at this point, compared to the Data Center business.

Jon Quast: They would be enormous standalone companies if they were standalone. But I just want to circle back to what you just said here. We're talking about the world's most valuable company growing revenue at 100% year over year, doubling year over year. This is just absolutely astonishing. But one of the other astonishing things, if that wasn't astonishing enough, is Nvidia's margin over the last decade, ten years ago, a 58% gross margin more or less, and that's good. But right now, sitting at 74% gross margin, basically for every $100 a product that they sell, it only costs them $36 to make it in direct costs. Obviously, there's operational costs as well, but $74 gross profit per hundred that they sell, is this something that investors should watch in the upcoming report?

Matt Frankel: For sure, and it's something I'll definitely be keeping an eye on. The margins, it's not just because Nvidia got a lot bigger over the past ten years. That's definitely part of it. Companies get more efficient as they scale. A lot of it is because of the new big data center build-out. Nvidia has a lot of pricing power. They can charge whatever they want. They're essentially sold out of chips for data centers for the next couple of years. Right now they can charge whatever they want. I'm going to be really watching that because it's a great indicator of pricing power. I'm especially interested because AMD just rolled out its first full-scale rack system for data centers. Competition is heating up. That 95% market share AMD is trying to take some of it. The margins are going to be a good indicator of whether or not they're successful.

Jon Quast: Rachel, let's bring you in here because obviously, higher gross margin good, and that could start to come down feasibly. Let's say that there's just not as much demand or if competition starts coming in, what would be a level of gross margin that it comes down to that you would start to be concerned about the competitive nature of the market?

Rachel Warren: Well, first I want to talk a little bit more about what's driving these gross margins. I mean, Matt hit on it briefly, but to understand how is Nvidia commanding these roughly 75% gross margins, you really have to look more at that supply-demand imbalance and high-end computing that we’re seeing right now. Right now, the hyperscalers, Microsoft, Amazon, Alphabet, they are ordering these next generation ships faster than Nvidia's manufacturing partner, TSMC, can actually produce them. It's a classic scenario when demand heavily outstrips supply, you have essentially total pricing power, Nvidia can pass these rising input costs like the surging prices of high bandwidth memory from suppliers like SK Hynix. They can pass these costs right on to their customers without hurting order volumes.

But it's also important to note, they have millions of developers locked into their proprietary CUDA software ecosystem and building or optimizing an AI model for anything else takes months of engineering work. There's a real lack of viable alternatives that work out of the box. A lot of the tech giants choose to pay Nvidia's premium prices rather than to risk falling behind in the AI race, and they're buying in so doing from Nvidia, really what's an entire ecosystem, not just the silicon. Now, for me, where I would maybe start getting a little bit nervous or at least questioning what's happening behind the scenes is if gross margins were starting to fall down towards that 70% floor. It might tell us a bit of a story about what's happening on the ground. It could indicate that supply would have caught up with or exceeded market demand, could also mean that some of those cheaper competitive architectures like AMD’s MI 300 series or hyperscalers’ internal custom chips, which is another piece as well to consider, might have achieved some software compatibility that bypasses that market. Now, I do not think that we are anywhere close to that reality. I also don't think to be clear, this is a winner-takes-all scenario. But those are some things to watch as we get deeper into the AI race and the AI revolution.

Jon Quast: Obviously, on this podcast, we don't do an earnings preview for all the companies. The reason that we're doing it for Nvidia today is not for so much completely Nvidia’s sake. Obviously, we're talking about Nvidia stock. But there is, in my opinion, a 0% chance that something good would happen for Nvidia that wouldn't have economic ripples throughout the stock market, or conversely, something bad would happen with Nvidia, and we wouldn't see the ripple effects from that, as well. I guess here my question to you guys is, going into this earnings report, one, do you own Nvidia stock personally? What are the connected places in the market that you'll be watching for that ripple?

Rachel Warren: To answer your first question, Jon, no, I don't currently own Nvidia stock heading into earnings, part of it's the valuation. I'm now just happy to watch this one from the sidelines. I think any statement from management that would trigger an effect across the entire sector. I don't think it would be about things like a manufacturing delay or even a slight margins, actually, to be clear, to go back to our prior conversation. I think it would be maybe any commentary from Jensen Huang that would indicate some type of deceleration or plateauing in hyperscaler capex. Now, we're not looking at a scenario anytime soon where this is likely to happen. I think what we are seeing is the hyperscaler balance sheets are very strong. We're looking for another double digit increase in AI capex spending heading into next year and honestly, the competitive pressure among the tech giants to build out infrastructure is so intense, they can't really afford to blank or to slow down the build-out. We've seen all the big tech management teams saying that the risk of underinvesting in AI infrastructure vastly outweighs the risk of overbuilding. I think it's also important to note, the Microsoft, Alphabet, Meta, these are companies that are generating tremendous cash flow from their core advertising and cloud businesses. They're putting that back into data centers to secure market share. The Cloud providers are seeing huge backlogs of enterprise customers also waiting for capacity, so that near-term demand pipeline remains filled. Any commentary from Jensen Huang about a slowdown in the build-out would be key, but I don't think we're going to be seeing that anytime soon.

Matt Frankel: I don't own Nvidia, I mean, at least not directly. By ETF ownership, I've calculated it. Nvidia is something like 3% of my total portfolio just indirectly. But I'll be watching the results really closely because Nvidia's performance can have ripple effects on so many other companies and not just the hyperscalers, which that's definitely part of it. I mean, Nvidia's numbers, their future guidance, the commentary they give it gives a sense of the pace of the AI build-out. That could have a big implications for networking companies like Cisco and Arista Networks, for example, that are direct winners when these video chips are installed and have to be linked together. Nvidia's tone on future demand, it affects how companies like, say, applied materials, which builds the equipment that semiconductors are made with. They can forecast future demand, and investors can forecast future demand based on what Nvidia is doing. Those are just a couple examples. I mean, we could spend a whole episode on all the companies that are affected by Nvidia in one way or another, and I don't even know if that would be enough, but there are a lot of ripple effects that we're going to see in the wake of Nvidia's announcement. Nvidia might not even be the biggest stock to move or the stock movement on its announcement.

Jon Quast: When we are talking about a $5 trillion company, you better believe that there will be some movement around the market. Thank you all for sharing your thoughts on that, but we are not done because after the break, we're going to take a mailbag question regarding data centers. You're listening to Motley Fool Hidden Gems Investing.

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Jon Quast: Welcome back to Motley Fool Hidden Gems Investing. We'd love to take questions from our mailbag, and I'm going to go ahead and read this one. This comes from a listener in Bogota, Colombia. Thank you for listening to our show. Basically, the premise of the question is pointing out that back in the ‘70s, a computer used to fill a room, and now we can carry it around in our pockets. Computing has a history of doing more with less. Here's the question. What happens to all this spending if data centers follow the same path? If chips and cooling get efficient enough that the same workloads need far less physical infrastructure, does today's build-out end up looking overbuilt? Or does demand grow fast enough to absorb whatever efficiency gains show up? Would love to hear your thoughts. Thanks, and that's from Nico.

Matt, I want you to answer this question first. Essentially, the question is, in the past, computers became more efficient, we could do more with less. Therefore, it's reasonable to assume in the future with AI, we can do more with less. The question is, are we building way too much physical infrastructure if that's the case? You have an interesting observation here about two kinds of overbuilding. One, you have supply and demand temporarily out of balance, and the other you have an evaporation of demand completely. Just walk us through what you're thinking.

Matt Frankel: I know the commercial real estate industry very well, and this is not a technical question. This is a real estate question. There are two kinds of overbuilding you see in real estate. Just the first one, a few years ago, self-storage had a surge of demand during the pandemic. Everyone wanted to declutter their space because they were stuck in their homes. By 2023, markets had too much supplies, these were very easy to build. They're a little more than prefab buildings in most cases. But after a couple of years of little to no development, the market started to reach equilibrium. We're also seeing that happen in the warehouse space right now as ecommerce demand was really pulled forward.

The other type is what happened with office space. Office space has oversupply issues because of a permanent structural change. People are working from home. The three of us are working remotely as we record this. I mean, there's a lot less need for office space than there used to be, and that's not going to reach equilibrium until offices are demolished, turned into other things. It's a great question of what basket we're going to be in. When it comes to data centers, we are going to see some overbuilding at some point. Even if it’s very temporary, there’s a surge in development, and there’s a chip shortage or a power shortage or whatever, there’s going to be some supply-demand imbalance at some point. But it’s a really great question of whether these are going to be temporary supply-demand issues or a more structural office-type problem if chips and cooling do become more efficient and less space is needed.

Jon Quast: Well, and that's really the question. Which basket do we fall in because there are profound differences in the implications of those answers? I would say that on the one hand, I can make the argument that there is no imbalance right now because I just saw some research this morning saying that Data Center vacancy is only at 1%, whereas more historically, it's closer to 5% and already sold out with what is coming online. It seems like demand is still pretty high, but assuming we can do more with less with AI in the future, I guess my question is, are we building the physical infrastructure based on AI today, or are we building the infrastructure for the AI of the future?

Matt Frankel: I think we're going to see a self-storage situation unfold here. I mean, let me unpack that a bit. Historically, the more technologically efficient something gets, more consumption happens. The question is predicting that chips will become far more efficient and take up less data center center space over time, a prediction that's likely to be accurate. But the overbuilt thesis assumes that companies that need data center space like the anthropics, the open AIs, the Googles, just want to do the same amount of work with less space because they're more efficient. But more efficient compute will unlock workloads that aren't economical before. I mean, do you think Apple's factory space has gotten bigger or smaller since PCs took up a whole room and now can fit in your pocket. Do you think they need more or less factory space now. The way I'm asking that, I'm sure you know the answer. I'm sure the same thing is going to apply here over the next decade or two, although we're going to see supply-demand balances along the way. But I’m also assuming, and it’s a pretty big assumption, that chips and equipment will not only become far more efficient but will become cheaper based on the amount of compute, like how PCs did over time. Now, the data center build-out right now is very capital-intensive, and honestly, that’s the biggest bear case to everything I just said.

Jon Quast: But, Rachel, there is an official term for what Matt has just walked us through and just introduced to us. What is that official term, and how does it work?

Rachel Warren: I mean, this is very much bringing us back to this foundational concept in economics known as the Jevons paradox. In the 19th century, there was an economist named William Stanley Jevons, and he observed that when steam engines became more fuel-efficient, coal consumption didn’t actually decrease. It skyrocketed, and because steam power became cheaper and more practical, there were entirely new industries that adopted it and even formed from it, and we are seeing that play out with AI data centers right now. Obviously, it's a different time, but this is very much a concept in my view rings true. I mean, when we are seeing these companies find ways to make AI chips or cooling systems more efficient, it drastically lowers the cost of a single AI computation or token, and lower costs make AI economically viable for a new wave of applications that may be used to be too expensive to run.

For instance, if inference costs drop significantly, a company can pivot from using AI occasionally to running really complex continuous AI agents across their entire supply chain. That's just a basic example. What you see when you look at this concept and you bring it forward into the AI and Data Center era is that rather than shrinking the physical footprint, efficiency can act as an accelerator for demand. Tech giants aren't really looking at efficiency gains as a way to downsize their data centers. They see it as a way to extract vastly more capability out of the infrastructure they're currently building, and we are seeing a huge appetite for compute that doesn't appear anywhere close to slowing down. In my view, I think that the current build-out is unlikely to result in overcapacity because demand is scaling at a pace that is much faster than hardware is sinking.

Jon Quast: Of course, the counterargument to Jevons Paradox, especially when we look at the historical example, you had coal, but you also had a ton of businesses lined up with real demand on the other side of that coal price coming down. I think that the counterargument here with AI is that a lot of the demand is perhaps being subsidized, and that does have a finite lifespan. At some point, it will need to be financed with cash flows and so, is the demand really there? I think that's a question that is really pertinent to this discussion. However, if I'm going to stake my claim on one side of this or the other, I would say we're probably not overbuilding by a whole lot right now because demand is so high, but that's just my take. Coming up after the break, we are going to dip back into the mailbag a second time, and we're going to talk about some acquisitions. You're listening to Motley Fool Hidden Gems Investing.

Welcome back to Motley Fool Hidden Gems Investing. I do want to point out that we do have listener questions on this podcast. You can email us at podcast@fool.com. Keep it short, keep it foolish, and remember that we can't give personalized investing advice. But if you can meet all those three requirements, then email us at podcast@fool.com, and we'd be happy to consider your question for this podcast and we're going to take a second one today, and he's done such a good job at keeping it short and Foolish here. Here's the question from David. I've noticed that when acquisitions or possible acquisitions are announced, the company being purchased, i.e Warner Brothers Discovery or PayPal, has a stock price surge.

What are the benefits for investors holding those companies post-acquisition, and what happens if the acquisition is not allowed by the courts, Rachel?

Rachel Warren: A few really great questions here. The benefits of holding a stock post acquisition it really depends on how the deal was structured. If it was an all-cash deal, you're not going to actually hold anything once the transaction finishes. Your shares are wiped out; they’re converted into cash at that final buy-up price. Now, if it's a stock-for-stock swap, your shares are actually turning into equity in the new combined company. Now, we hear a lot about management when they announce an acquisition, talk about the realization of synergies. It sounds like a very nice fancy buzzword. What does it mean? Well, the idea is the combined businesses can eliminate a lot of the duplicate corporate expenses. They can merge their sales teams. They can use their combined size to get maybe much lower interest rates on corporate debt.

What does that mean for you as an investor? Well, you're essentially betting that these two companies together will be worth far more than they ever were apart. Maybe that's a benefit for your long-term portfolio. Now there is another question here. What happens if the acquisition is blocked by the courts? Now, typically, the target company’s stock will give back its acquisition premium. We'll see declines, but there can be some damage that happens in the background. You can see a company that's stuck in corporate limbo. Management is obviously dealing with a potentially protracted legal battle. This can be an area where competitors will use that window of uncertainty to swoop in.

There's actually a lot of examples of this. One would be when Adobe tried to buy the design platform Figma a few years back for a $20 billion price tag. That was obviously a deal that did not come to fruition in the end. I think it dragged on about 15 months. There was heavy regulatory scrutiny before it was ultimately called off. Figma, of course, kept running its day-to-day business, but they were legally bound by the standard merger covenants that restricted them from executing major independent shifts or financing moves, slows down product launches, when the deal collapsed, Figma used the $1 billion cash breakup fee from Adobe to aggressively grow again. But of course, that was a major period of friction for them, and Adobe, of course, had to pay out $1 billion. That's just one example.

Matt Frankel: I mean, to directly answer the first part of that question, yes, the target generally spikes after the deal because the acquirer almost always has to pay a premium in order to get the company's board and shareholders to say yes to a takeover. I mean, there's not much motivation if your stock's trading for $100 and then Adobe comes in and swoops in and says, well, we'll give you $100 a share for the entire company. Why would you do that? It depends on if it's an all-cash deal, if it's a cash-and-stock deal. That's really where you have a decision to make. When it's a cash deal, you generally have what I call a regulatory gap between what the stock price initially jumps to and what the acquisition price is. Once you get over that regulatory hump of will this deal be approved? That's when you'll see that gap really start to close, and it'll really gravitate toward the cash price of the deal.

With a cash-and-stock deal, as Rachel mentioned, you'll have exposure to the combined company after. Usually the acquirer is bigger, so you really need to decide if you want to own the acquirer after the stock. Sometimes, for me, this answer has been yes, when Rocket Companies acquired Redfin, I was a Redfin shareholder. Now I'm a Rocket shareholder because I like their business. At other times, it's been no. I wanted to emphasize something Rachel mentioned at the end with the Figma and Adobe deal. A lot of these deals have breakup fees, and sometimes if there's a bidding war happening, like with Warner Brothers Discovery like the question mentioned, you'll see a pretty hefty breakup fee, which is a deal sweetener. There's a $7 billion breakup fee if the Paramount-Warner Brothers deal falls through. Some deals have pretty big safety nets baked in, so in that case, I wouldn't expect Warner Brothers to fall all the way back to its pre-announcement price because of that fee. But that's very deal-by-deal, and it's really worth knowing.

Jon Quast: I think that one of the pieces of advice that Warren Buffett gave out one time was with these things, if you're going to consider these stocks, always ask yourself, what happens to my stock if the deal falls through? I can personally attest to buying iRobot when Amazon announced it was going to acquire it, and that wound me up with a zero in my portfolio for that. Make sure you know how likely the deal is to go through and what happens if it doesn't. I didn't fully assess those risks at the time. Thank you to both of you for bringing that to the table and pointing out the differences here.

As always, people on the program may have interest in the stocks they talk about, and The Motley Fool may have formal recommendations for or against, so don't buy or sell stocks based solely on what you hear. All personal finance content follows Motley Fool editorial standards and is not approved by advertisers. Advertisements are sponsored content and provided for informational purposes only. To see our full advertising disclosure, please check out our show notes. Thanks to our producer Dan Boyd and the rest of The Motley Fool team behind the glass. For Matt, Rachel, and myself, thank you so much for listening to our show today, and we will see you again in the next episode.

Jon Quast has positions in Advanced Micro Devices. Matt Frankel, CFP® has positions in Amazon, PayPal, and Rocket Companies and has the following options: long January 2027 $75 calls on PayPal, long January 2027 $95 calls on PayPal, short January 2027 $135 calls on PayPal, and short January 2027 $85 calls on PayPal. Rachel Warren has positions in Alphabet, Amazon, and Apple. The Motley Fool has positions in and recommends Adobe, Advanced Micro Devices, Alphabet, Amazon, Apple, Arista Networks, Cisco Systems, Figma, Meta Platforms, Microsoft, Nvidia, PayPal, Rocket Companies, Taiwan Semiconductor Manufacturing, and Warner Bros. Discovery. The Motley Fool recommends the following options: long January 2028 $330 calls on Adobe, short December 2026 $62.50 calls on PayPal, and short January 2028 $340 calls on Adobe. The Motley Fool has a disclosure policy.