AI Spending Could Ignite a Historic Market Boom After 2026 — Tom Lee, CNBC & Schwab Market Update

[00:00:00] Speaker 1: money moving downstream. So there's going to be software rallying and beneficiaries of AI. But between, let's say, June and October, we do have to digest potentially three major IPOs coming. And the market will try to understand Kevin Warsh's new sort of model for inflation. But I think the market always tests the new Fed. And then we have that normal seasonality around midterms. And so I think we could have a drawdown that'll feel like a bear market. And as you know, that February to April was just a 9 percent decline, but it felt like a crash. And so I think markets are going to really struggle if we start to have a drawdown. And then, of course, from October, I think that's [00:00:41] Speaker 2: when a very strong rally starts. Andrew, I was going to say how bad you've been on crypto, but [00:00:47] Speaker 3: I don't know. I was going to go to a slightly different place and we could do that, too. But I was going to ask him about Mark Cuban. I don't know if you saw Mark Cuban said that he's now dumped or sold all of his Bitcoin, given that he no longer believes it's acting as a hedge against inflation or anything else, argues gold is proven to be a better bet and that Bitcoin has not acted the way it should if it's supposed to be digital gold. What say you? Well, you know, [00:01:17] Speaker 1: on the one hand, I think Mark is right. Crypto has been disappointing because crypto should move with, you know, equity markets and it should be rallying with software. Software has really started to rally big and crypto hasn't moved. So I think there are what what I call, quote, rage quitting people selling here as if something is wrong. I mean, one, I think that's what always happens at the end of crypto winter. You know, if someone asked me, is the thesis for Bitcoin or Ethereum broken? You know, it's absolutely not. Because one, the more work we do and we're hearing it from founders like Palantir, Bitcoin and Ethereum are really the future of money because mass and compute or compute and energy, however Elon puts it, really are what's scarce. And you're going to need to control agent systems. And as age AI systems evolve, right? We're now talking about using commerce and operating websites. You need decentralized identity and verification. That's really what crypto does. And we know Wall Street wants to go towards tokenization. It's a vast improvement in efficiency of the of actually how money moves. And it's an innovation. Well, that only happens on Bitcoin and Ethereum and other smart contracts. So the future isn't changed. But the spotlight today is, of course, on semis, memory, starting on software. But as as people focus downstream into the future, that's really, I think, when the bid comes for [00:02:38] Speaker 2: Bitcoin and Ethereum. Because when you talk about stocks, it's so easy for you. You got you did it. Ten dollars times four. That's, you know, forty dollars. Put a multiple. That's 800 points. Why do you even try with Bitcoin or Ethereum? What's your your comparable analysis to be able to come up with anything to make predictions about Bitcoin or Ethereum? There's there's nothing that you can base [00:03:05] Speaker 1: it on, Tom, except maybe psychology or sentiment or something. Yeah. Well, there's yeah. Actually, market sentiment is plays a huge role because it's sort of essentially risk premium. But there are two proven ways to value crypto. One, of course, is just network usage because wallets and activity per wallet still explain, like even now, 87 percent of the rise of Bitcoin. So as long as more people use it and they're transacting it, the value of Bitcoin should go up. It's a network effect. And the second is the umbrella value of gold. You know, gold at when it hits 5000. If Bitcoin had the same network value as gold and gold is not as scarce as Bitcoin, that would put Bitcoin at around 2 million. So to me, I think there's still two ways to look at the value. And of course, for Ethereum, it's been shown for every dollar of tokenized assets, you know, tokenized dollars or others, it's created one dollar value for it for ETH, the coin. So if you believe Wall Street's going to [00:04:08] Speaker 4: tokenize Ethereum's price should go up a lot. Of course, that does not tell us the story as this stock is something like 20 percent off its lows that it made just a few sessions ago and something like, I don't know, 35, 40 percent off its highs that, of course, it made in October, November of last year. Let's bring in our guest here. You know her well, Marley Caden. She's the host of Trading 360, which comes up next as well as Market on Close here on the Schwab Network and Marley. Palantir is just a fascinating company, not only from a trading standpoint, but the projects it's working on, the space it's in. You throw in the volatility. This is like a recipe of a next-gen investing type [00:04:49] Marley Caden: of name. It is. I mean, I feel almost like we're in FOMO by accident. We're just doing it in the wrong show right now, but I mean, you highlighted some of the moves in Palantir. I mean, down 26 percent just this year after three consecutive years of triple-digit gains. So, I mean, taking a look at the price action in this name, extremely volatile, but having a nice day today. We are trading up almost 4.5 percent higher after DA Davidson upgraded the company. They have a buy rating now as opposed to a neutral, which they held before. New price target, 175. That's up from 165. Both were above where we are now. We're at 1:31.48. They say the company has "grown" into its valuation as its profits are up significantly and the stock's multiple has come in. This provides investors with what they are calling the gift just in time for the United States of America's 250th birthday. They say that they think Palantir has several competitive advantages over all the other software companies that are becoming more pronounced due to AI. They think these recent developments show why customers will use Palantir as a way to orchestrate AI models. And I want to break this down because it's a little complex. The company can now swap the AI model underneath its solution, which then removes the biggest perceived threat to its business model, which is the notion that companies could potentially go to Anthropic or OpenAI to solve their problem. If you've been watching India lately, you probably [00:06:03] Speaker 6: noticed something that doesn't seem to make much sense. The business getting keep stronger and artificial intelligence demand hasn't disappeared. Wall Street is still overwhelming. They recommend buying the stock and yet Nvidia has spent months moving sideways while many other AI's names grab the investor's attention. So what's really happening? Is the market quietly telling us that Nvidia's best days are behind it or is this simply a rare opportunity where the stock prices has fallen behind the business itself? Let's dive in. One thing has become very clear over the few weeks is the AI investment story is no longer just about Nvidia. The market is beginning to separate the entire AI ecosystem into the different layers. At the center of sits Nvidia and around Nvidia are companies supplying memory, networking, cooling, manufacturing equipment, and power infrastructure. Every one of these businesses depend on AI spending continue. That's why investors are starting to ask important questions. Instead of buying Nvidia itself, should they buying the company is benefiting from Nvidia's success. Memory has become one of the best example. Without advanced memory, Nvidia, GPU simply cannot deliver the performance required for the modern AI models. Every larger models require more memory and every AI agents need more context. Every inference is required to consume memory bandwidth. That's why companies like Micron and SK Hynix has suddenly become some of the hottest name in the semiconductor industry. Micron continues talking about the demand exceeding the supply. Customer signing long-term agreements, production remains constant and yet the stocks still trade at surprisingly modest valuation compared to many other AI winners. At the same time, SK Hynix has become the dominant supplier of a high bandwidth memory and one of the most important components inside the Nvidia's latest AI system. Now that American investors have easier access to SK Hynix through the NASDAQ listing, many portfolio managers see another way to gain exposure to AI build-out. That doesn't mean Nvidia has become less important. Actually, it's the opposite. Every discussion about memory eventually circles back to Nvidia. If Nvidia ships more GPUs, then memory demand increases and if Nvidia launches faster ships, then customers need even more advanced memory. If AI infrastructure spending accelerates, nearly everyone across the semiconductor supply chain will get benefits. That's why Nvidia remains the heartbeat of this entire industry. The interesting part is that Nvidia values entail a very different story than its business. Revenue continue growing rapidly and margins remain incredibly strong. Free cash flow keep climbing and its software ecosystem continue expanding and the year the stock trade added to the cheapest valuation in the years. That disconnect is forcing investors into two different camps. The first group believes Nvidia is simply on the scale. Their argument is straightforward. The company still dominant AI computing. Its competitive advantage hasn't disappeared. Its customer ways continue expanding and the new growth opportunities like enterprises AI, robotics, solution AI and influencers could keep demand growing for the years. To them, today values look unusually attractive. The second group sees things differently. They argue that Nvidia has become so successful that expectation has reached impossible levels. Eventually revenue growth has too slow. And the competition from custom AI chips will increase and large cloud providers will continue designing their own silicons. And once growth normalized, Nvidia could look more like a traditional semiconductor company.