Talk Your Book: AI Winners & Losers

0:00Ben Carlson:Today's Animal Spirits Talk Your Book is brought to you by Alger. Go to Alger.com to learn more about ATFV. That's the Alger 35 ETF. Concentrated portfolio. ATFV. Alger.com to learn more. Welcome to Animal Spirits, a show about markets, life, and investing. Join Michael Batnick and Ben Carlson as they talk about what they're reading, writing, and watching. All opinions expressed by Michael and Ben are solely their own opinion and do not reflect the opinion of Ritholtz Wealth Management. This podcast is for informational purposes only and should not be relied upon for any investment decisions. Clients of Britholtz Wealth Management may maintain positions in the securities discussed in this podcast.

0:44Ben Carlson:Welcome to Animal Spirits with Michael and Ben. On today's show, we are joined by Dan Chung. Dan is the CEO and CIO and a portfolio manager at Alger. And what we talked about today was their concentrated portfolio, which in a concentrated market, having a concentrated portfolio has to either really easy or really hard, right? Because you could do a closet index of a concentrated positions, but if you take away from one of the current concentrated positions, you're taking a huge bet. You know what I'm saying? I do. So back in my days of manager due diligence in the endowments and foundations days, I really liked when a portfolio manager was honest because I feel like you don't always get honesty out of these people.

1:24Ben Carlson:Not that they're trying to be dishonest, but they're trying to put forth, they want you to trust them. They want you to assume that they know everything, correct? So I like it when a portfolio manager is willing to go, well, gee, I don't know, or what if? And I liked how as our conversation progressed, Dan talked about meta. He says, we own meta, but I don't know if they're gonna be one of the losers from this whole thing. And I like that sort of self-awareness of going, man, this is a proven company, but what if they're one of the heads in the chopping block here? I like that self-awareness and like, hey, it's possible.

1:58Ben Carlson:One of our holdings could be a loser from AI. We don't know yet.

2:01Michael Batnick:Yeah, the market is clearly saying that Meta is not going to be an AI winner. And it's very unclear whether the market is very right or very wrong. Nobody can see the future. So it was a, I agree, that was a highlight of the conversation. Because on the one hand, man, it's the greatest advertising platform in the world. It's really cheap. I mean, 14, 15 times earning, that's a severe discount. Forget about to itself, to the market. So you'd feel like a donkey selling it here. But on the other hand, the market's not stupid. They know that. There's legitimate questions as to the sustainability and the growth rates that they're getting from the AMO's and the spend is a whole other story.

2:39Michael Batnick:So yeah, I enjoyed that part of it. Because another manager could be like, oh, this doesn't make sense. You're going to bet against Mark Zuckerberg. Look at his track record. Of course the market has it wrong. Who knows?

2:51Ben Carlson:Yes. I find it endlessly fascinating to think about the AI winners and losers. It's like the carnival game where you're shooting the water gun and the horses are going up and back and forth. Good analogy. That's what it really feels like. And I think as a portfolio manager, you have to, at times, rip your hair out of your head to be like, I can't believe the market isn't seeing this, that they should be a winner and they should be a loser or whatever it is. And I can't believe this company that we don't own anymore is doing so well. How is it not? So anyway, that part has to be entertaining and also stressful.

3:22Ben Carlson:Anyway, we had a really fun conversation with Dan about all the AI winners and losers, how they're thinking about the incumbents, the newer companies that are coming up, and more. So here's our talk with Dan Chunk from Alger.

3:36Michael Batnick:Dan, welcome to the show. Thank you, Michael. Your resume looks almost as impressive as mine. You've been with the company for quite a while, but tell us who you are. Why are we talking to you? Okay. So I'm CEO and chief investment officer and a senior portfolio manager at Alger. I've been here since 1994 when I joined in the Alger Analyst Training Program. In the 90s, I was known as the tech analyst and the head of tech here. And before that, I had a career as a corporate lawyer. So you've been in this business for quite a while, at one place for a long time, which speaks volumes to the company that you're at, obviously.

4:14Michael Batnick:Let's go right into the comparisons. What is different? And let's frame it this way. What is different about the technological environment? And go wherever you want to go with this question versus the mid to late 90s when you were starting your career. Yeah, that's a great question because a lot of people are making comparisons. But I think the differences between the two periods are actually vital to understand. The main comparison, of course, is simply that AI, just as in the 90s it was the internet, is booming. And of course, it's driven by a technological revolution. But the differences are very stark in my mind.

4:55The biggest one being actually that the current leaders in the AI investment boom are very different than the leaders in the 1990s internet boom. And in particular, the companies today, whether it's Microsoft or Amazon or Google or Meta or Oracle or, yes, Anthropic or OpenAI. But in that first group, and I, of course, have to include NVIDIA, we are talking about companies with incredibly strong fundamentals, real revenues, massive profits, highly profitable companies that have been leaders, well, like Microsoft for more than 30 years. Others, like Amazon, for 25-plus years, and NVIDIA itself, a leader for decades.

5:41The leaders have strong fundamentals. They are investing in what they see as the largest opportunity of their generation, which is AI. And that itself is strikingly different than the 1990s, where the leaders were often companies that were not profitable, minimal revenues. They were innovators, but they were very small companies like Amazon when it went public that basically had a million dollars of revenue and was selling books online. Or Yahoo, which, yes, went public with more revenues than that, but was a fledgling company, not established or proven, and not a leader in advertising. So it's a very different generation of leaders leading right now in AI.

6:22And I think it matters a lot, not only in the quality of what they're investing in and the confidence that investors should have that these companies, as a group at least, are pretty mature, pretty responsible, essentially know what they're doing. Versus the companies in the 1990s were highly improving, were amazing companies like Amazon, but had to prove themselves and were doing absolutely everything they could. And part of what they did is they threw out the cookbook from the 1980s and implemented their own playbooks. And yes, some of them worked, but as we know, many of them failed. I think this generation of leaders, clearly, these are proven leaders here.

7:00Ben Carlson:As someone who enjoys following the markets, I think that watching this whole thing play out is very entertaining. I'm curious for you as a portfolio manager, do you find trying to pick through the winners and losers of this whole AI revolution, do you find it fun and exciting or is it really stressful for you? How do you view this type of environment? I feel like I'm incredibly fortunate as one of the few investors that I know of who was both an internet tech investor in the 90s. Again, I headed Alger's tech investing by the end of the 90s, who's still investing today and gets to see this in the AI phenomenon that we have.

7:40In addition, of course, I've got some really, really talented, very experienced portfolio managers and analysts. And so I'm very excited about the opportunity. I think it is a bigger, stronger, and actually better opportunity than the internet itself was. And it's really an exciting time to be a fundamental bottoms-up investor.

8:01Michael Batnick:All right. I know you just said bottoms-up. I want to get to the bottoms, but let's stay on top for a second. I agree with you, incontrovertible, what you said earlier about the differences in these companies. very different. But just because there are as many differences, maybe more so than similarities, I don't think that's a green light that this thing can go on forever and that there's not any risks lurking on the horizon. Surely there's no shortage of potential dangers out there. If there were one thing that you see today that has you a little bit nervous that, yes, this is transformative.

8:34Michael Batnick:Yes, these companies are insanely profitable. They are pedal to the metal, like all that's stipulated. What is one or two things that you see today that does make you think, I don't like what I'm saying here? There's a couple of things. So one of them, and it's very similar to the 90s in this regard. So let's look about fiber optics, right? Because in the 90s, that was the big thing. Laying down fiber optics, the big race. The race was ultimately justified, but there were many, many, many losers of individuals. companies that spent a ton of money, didn't have the management teams, didn't have the strategies, didn't have the technology, and ended up failing.

9:16With AI, first of all, I think the overall, quote, spending of this across AI, in some sense, is going to be justified. And we're already seeing it justified by the tremendous revenue growth of, for example, the leading models like OpenAI and Anthropic, which together are growing faster than anything we've ever seen. So clearly, that That means the opportunity is big. But I think what is also equally clear is that the disruption that is going to occur, not just in internet companies, not just in tech companies, not just in software companies, but across many industries, I think the threat of disruption is, of course, also increasing.

9:53And there will be companies that are probably disrupted faster than we've ever seen before by basically AI competitors or competitors who adopt AI and use it more effectively. than others. And so I think that's one of the biggest concerns I have. From a market perspective, what actually does concern me is sort of sometimes the lack of nuance that we're seeing in the market or just fundamental understanding that it's natural to have 100 competitors chase a big market. And it's also natural that 30 to 40 of those will fail. A whole bunch in the middle will be okay. And you'll have maybe 10 winners at the top.

10:33because what we're seeing in the market around the volatility is almost like, you know, right now there's a lot of consternation about the capital spending and in particular about open source models versus the leading models, which are closed. And it's causing very kind of almost emotional knee-jerk reactions, which is making the market really volatile. And so that is a dangerous sign in and of itself, right? As experienced market investors, we know when you see fundamentals being somewhat ignored and the market really reacting in a hyper-volatile way simply around sentiment or a newsflash coming from one company, you do have to worry, like, is that a sign of excess frothiness in either direction?

11:14Ben Carlson:How do you think about risk management in a world like that? Because you're right, the whole Leopold situation at situational awareness was, hey, this guy laid out the next 10 years and he seems like he's on the right path, but expectations got pulled forward and too much risk. And even Sam Altman on a recent interview said, listen, this stuff is actually like the technology is there, but the adoption is slower than I would have expected because there's so much inertia. So I feel like the timing of this stuff, you can be right, but be on the wrong time horizon or, you know, right, but by the wrong magnitude.

11:42Ben Carlson:So how do you even think about risk management in a situation like this where, hey, listen, fundamentally, I was right, but the expectation, there's a mismatch between the expectations and the herd mentality and all these things. It's, it's, it makes for a challenging environment, even though you could be right on the fact that this technology is going to be transformational. Absolutely. So the way we manage risk at Alger is, first of all, to look at the fundamentals of the companies. We're fortunate that many of the companies that are doing really well right now are well-seasoned companies. So not just NVIDIA, but most of the semiconductor companies have been around forever.

12:16Micron, Western Digital, the semiconductor equipment companies. Same thing with most of the software companies. Whether they're going to be AI winners or losers, Oracle, ServiceNow, Salesforce.com. These are big established companies. So we're careful about looking at a scenario-based analysis of what are their risks, what are their likely outcomes, and of course, maybe what are their bull case, the optimistic upside for these companies. And the way we manage risk at Alger is to consider essentially the risk reward in their stocks based on different scenarios. So you can take a bearish case of a company, think that it'll be moderate growth, but still They'll also say, but it's going to be worth X and Y based on its free cash flow and revenues and a lower multiple.

13:00And you can also look at the same company and say, if it succeeds in AI, increases its growth rate, margins improve, it'll get a higher multiple. So we're very careful about position size in our portfolios around risk reward as we see it from the fundamentals and the price targets that they imply. The toughest part, as we alluded to in the earlier question, is with so much volatility in the market, we're sometimes seeing these prices change really very rapidly and a little bit more rapidly than they should in the sense of the fundamentals aren't changing that quickly. And the software stocks are the best example of that.

13:35And many of them were 40, 50 % down at their lows this year. Many of them have now rallied 30 % from those lows. Not that much of that is really based on the fundamentals.

13:44Michael Batnick:You mentioned these baskets of stocks, the AI winners, the software losers, whatever the theme of the day is. And you see all these stocks move together, but that's short-term stuff. We know that over time, even though they move together on a day-to-day basis, if you zoom out a little bit, three months, six months, one year, three year, the market does a good job of separating the winners from the losers. Not every day, not every week or month, but eventually the market sorts, all right, these are the companies that are doing well. These are the companies that are under pressure. And what you do at Alger, and we're talking about the Alger 35 ETF, the ticker for this is ATFE.

14:22Michael Batnick:V. This is not a closet index fund. You guys are really going for it. So for example, this data is a bit stale, but we're looking at data as of the end of April, April 30th. And again, I know it's stale because we're in August, but just for the sake of conversation. NVIDIA, which was a large company, 7.8 % of the S &P 500 at the time, you had a 14.3 % weighting. So a 6.5 % active share in NVIDIA. Nebius, not even in the index, you guys had a 5 % position in. Western Dig, a 0.2 % weighting, again, as of the end of April 30th. 24 basis points in the S &P, you guys were at 4.8%. So the top 10 holdings as of that date were 64%.

15:09Michael Batnick:People are worried that the S &P 500 is concentrated. You guys are really leaning into it. So where does that conviction come from? Yeah, Alger 35 is a best ideas across Alger portfolio. And the conviction really comes from a couple of things. One is we've been doing this for 62 years. I've been doing it for 30 plus. Even my portfolio managers who are quite a bit younger than me have been doing it for 25, you know, 20 years. We have a great team. We have a lot of experience in high growth, in dynamic change, in disruption in industries. I mean, these are actually the kinds of events where Alger really leans in and understands that the opportunities are the greatest.

15:53So first of all, it is expert analysts and portfolio managers that are experienced in industries that go through revolutions like this one. Second, careful, detailed, fundamental modeling of companies. Every single one of them that you mentioned and all that we own, detailed financial models, P &Ls, cash flows, and also close contact with the management team, but also a lot of research around and outside of the company itself, of course, to understand its competitive positioning, the quality of its management, the quality of its products, and ultimately, of course, the value of its stock relative to competitors.

16:26And so it's hard work. There's a lot of good companies out there. At Algebra 35, we're focusing in on what we think are the best companies with the biggest moats, the best opportunities now, but also the best opportunities longer term. And you've mentioned some of the companies that we've identified as winning now and winning probably long term. Nebius is one we're really proud of. I mean, this company, when we first invested in it, was a small cap. It's now a$50 billion plus market cap. What we identified there was excellent AI data centers, even before AI data centers was sort of a fad. I mean, now it's, everybody seems to be, well, actually, every state seems to be stopping AI data centers, even as everybody wants to build an AI data center.

17:05But Nebius, we identified a couple of years ago, not just because of their data center capabilities, but because of their software capabilities that make them a platform for developing AI upon. And of course, in the last years or so, it's really come true as they've won a tremendous amount of contracts for developing on their platform.

17:22Ben Carlson:Can you explain how a company like that, it seems like in the last, I don't know, 12 to 15 months, just went absolutely vertical. how does it almost seems like there are these companies that are being discovered late to the game it's not like you know AI is the chat GPT moment was in 2022 what is it that it seems like there's a the catch-up period happens so quickly with some of these stocks now like how are they missed essentially so with AI right now we have like sort of a long-term investing it's not a plan because it's not as detailed as a plan but it's certainly an overarching strategy of understanding the sequence in which things will happen in a buildout like this.

18:02And we understood two and a half, three years ago that, yes, semiconductors NVIDIA was going to lead, but the AI data center was going to be a center of focus. And so we invested in not only semiconductors that were leading it, but also the providers of data center technology. And also, for example, even things like liquid cooling into data centers, so companies like Vertiv, and frankly, even outside of tech in energy stocks that we knew would be supplying electricity, companies like Talon and GE Vernova. The identification of a company like Nebius is really something you have to be a fundamental investor.

18:38Because the first question is, we had the plan. We say, okay, data centers are going to grow. We confirmed with cloud providers that the need for data centers and that AI data centers are not like other data centers. They're going to be architected differently. Then we just did the very basic research of saying, okay, who are all the data center providers in the world, the big or small, we didn't care. We went across the whole landscape globally. Then we said, okay, which ones seem best prepared for AI data center computing? They have the resources, they have some experience. And actually, when we first saw Nebius, we're a very small company, but we were like, wow, these guys are way ahead of the curve.

19:12Now, part of the reason they were undiscovered is that the company stock trades in the Netherlands and the company is based there. And actually they came out of a former Russian internet company called Yandex. And so they weren't on the, if you will, the US radar screen. And I would say, you know, buried there in Europe was this small cap company with a lot of AI experience and a lot of internet experience. And so we, you know, we narrowed it down to that and other lists. And then we met with the company, built our models, understood other value. There's other aspects to value in Nebius that actually we thought very interesting, which includes, they also have a very big position in a company called ClickHouse, which is an AI database for unstructured data.

19:55So videos, photos, unstructured data. And they also have actually, oddly enough, an asset in an autonomous driving technology that was once in Russia and then got shut down in Russia after the Ukraine-Russia war. Was that Yandex? Yeah, it was a Yandex. They were all Yandex properties. So the funny thing is, as this little company became more complicated, and this is the value, I think, of fundamental analyst-driven research, we got more interested as investors. We're saying, wow, this little company has a lot of really interesting assets. And I say that as fundamental investors, because if you were a purely quant investor, there would have been nothing to see here.

20:35I mean, low revenues, no profits. You wouldn't have probably seen that it had assets coming out of Yandex that were quite interesting. They were just shareholding positions. We got more and more interested when we met with the management and their history and an incredible culture, by the way. I mean, maybe I'm going on too long about it, but we really do admire the management and the CEO here in particular. Arcady is amazing. But these guys had to leave Russia in the middle of the night for fear of basically being seized. And they did that. The people fled, went all over the world, but they kept themselves together, a core of it as a company.

21:12And they worked really hard for a long time to just stay together, be a company, build these products. And they happened, of course, have the vision, and hats off to Arcadia and his entire management team, his CTO also in particular, that they had the vision like AI data centers are going to require a different kind of platform than your typical data centers, and we want to be there.

21:33Michael Batnick:And there they were. The neoclouds are often cited in the circular financing bear case. When you hear this, I'm sure it drives you crazy. What is it that the bears are not understanding about these relationships and why it's not looking anything like the dot-com implosion? So I would say that in the case of some of the leading neoclouds like CoralWeave and Nebius, this is not circular financing. This is, I mean, these companies, first of all, they are building real assets. They're building the leading edge of AI data centers, right? They are building them and equipping them with, you know, NVIDIA's leading edge, server chips seem to be, you know, Vera Rubin is coming out now, is there already.

22:20So, I mean, that's an asset. It's a real asset that they're building. Call it an office building if you want. The circular financing, which again, I remember from 1999, what it looked like was VC gives you a billion dollars and gives you a$2 billion market cap for a company that has no revenues, but you're an internet startup that has.com in its name, right? You know, something.com. And you're, of course, trying to follow on the success of Amazon or an eBay or Yahoo. And then what do you do? You don't have many assets. You spend, of that billion, you spend$500 million on advertising, you know, on Yahoo and other services to try to do what?