Momentum vs. fundamentals in the AI trade: Insights from BlackRock

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Eloise Goulder: Hi, and welcome to J.P. Morgan's Making Sense. I'm Eloise Goulder, and today I'm delighted to be joined by Helen Jewell, International CIO of Fundamental Equities at BlackRock, to discuss the impact of AI on markets. So, Helen, welcome and thanks for being here.

Helen Jewell: Great to be here. Thanks for having me, Eloise.

Eloise Goulder: So, your business is in fundamental equities, in bottom-up fundamental stock picking with a long-term focus. What does it mean to be long-term?

Helen Jewell: Well, that's a great question. What it really means is focusing on the earnings that a company is able to deliver over the longer term and trying to look through the day-to-day noise that you see in the market.

That is actually a much more difficult than it might seem, because as investors, you are, by your very nature, thinking every day about that mark to market. But as long-term investors, you have to focus on the real things that matter. You have to focus on which of the companies that you are looking at have got a moat around that earnings. You have to look at the key themes that you are seeing which, of course, at the moment is the AI space. So, whether that's semiconductor companies, tech, hardware, memory names—the key thing that we're trying to do is work out which one of those will really deliver earnings growth over the longer term and which of them are getting a real bid, not because the earnings are going to go up, but instead, because people are just basically making a short-term bet on the short-term performance.

Eloise Goulder: And you mentioned the short-term there, and so many market participants are short-term orientated. So, Helen, what are the benefits of being active and long-term, in your view?

Helen Jewell: Well, the key thing is that if you are long-term and active, you will see the benefits of compounding coming through. In the first few years of any share price, what you tend to see is that the valuation, the multiple that you pay, actually matters more than the earnings. But there is a lot of research that shows that after those first few years, the earnings matter more than anything. And so that, again, is what we're focused on. But what you're looking for here is a function not just of the earnings growth, but also the return on capital. I know some people don't think this, but not all growth is good growth. If you're a company that is growing, but actually eroding returns at the same time, that is not a good thing from a long-term investment perspective. And that is a challenge, to be honest, Eloise, with the markets at the moment, because the market has been focused on growth rather than focusing on the quality of that growth. And it's so important to understand the benefits of compounding. If a company is growing and returning high returns on that growth, high returns of capital, it can effectively reinvent itself on an ongoing basis. So it's in a really, really strong virtuous cycle. It generates good growth. It reinvests that growth at high returns. And then those high returns generate even more growth going forward.

So you're in this perpetual cycle that is really, really beneficial from a long-term investment perspective. It's a little bit like Trigger's broom in Only Fools and Horses, where effectively he said he only had one broom. But when he was pressed, he actually said, I've only had to change the head five times and the stick 10 times. In his mind, it was the same broom. But actually, what he'd been able to do is reinvent the broom a million times.

Eloise Goulder: I love that analogy. Never heard that before. And indeed, this idea that if you're throwing off significant growth and significant returns on your capital base, then indeed, you can reinvest that and you can reinvent yourself and you can pivot the business to wherever the future opportunities lie.

So coming back to AI, we've obviously seen a phenomenal run in AI-related segments, most notably, as you just said, across memory names, across semiconductors and across AI infrastructure this year. These sectors are high growth in terms of revenue growth and earnings growth, driven by the scale of AI CapEx. But Helen, what's your view on the quality of this growth and the extent to which this is high return on capital type growth?

Helen Jewell: I think the challenge is that the market doesn't really know at the moment. What we're definitely looking for is growth where the return is higher than the cost. So the return on equity is higher than the cost of equity. And that is a big thing that we'll need to really differentiate within the AI theme at the moment. The challenge is that the market year to date has been really driven by momentum. And momentum has been exacerbated by things like leveraged ETFs. Then on top of that, you have a large retail investor base. And you have systematic strategies. And they're also active investors who maybe don't think necessarily from a long term earnings perspective.

So at the moment, the market has been driven by momentum. But that's not to say that everything we're seeing in the AI space is low quality growth. The problem is that the market at the moment does not seem to be discriminating based on future return on capital. We know that not all AI is created equally. We know that at some point, the AI CAPEX spend from the hyperscalers will exceed the demand for that CAPEX. But we don't know exactly how that will play out. So the market is basically putting everything in the same bucket. If you think just a year ago, all tech was outperforming, whether it was software, semis or hardware. And yet the market this year has really differentiated between software and hardware, software being a loser, and hardware being a winner. I think it is far, far more nuanced than that. And that is the thing that you really need to factor when you're thinking about portfolios and portfolio construction.

Eloise Goulder: I'd love to dig into this point, Helen, because as you say, the perceived winners in the AI space have been semis, hardware, memory. They're the segments that have outperformed so disproportionately year to date. How would you begin to differentiate within them?

Helen Jewell: Well you know me Eloise, I always like to bring it back to the basics. So return on capital matters. Longevity of growth matters. Cash flows matter. And at the moment, when you're looking at the tech segment as a whole, not all of these numbers are particularly good. Cash flows for the Mag 7 have dropped sharply given the scale of their CapEx spend. The market doesn't seem to have decided yet whether this is a replay of the infrastructure spend for telcos back in the late 90s, early thousands, or whether this is more like the cloud spend that we saw a decade or so ago. And that is in the balance when it comes to AI CapEx.

Now, our economists expect the AI CapEx impulse to actually fade from 2027 onwards. So what I mean by that is that although the spend will continue to grow, the rate of that growth will actually start to fall. And that means that the supernormal future growth won't necessarily come through in the way that we've seen in the last couple of years. So that is the key question, the key unknown in the market. But also, Eloise, the key opportunity in the market, because the market is pricing all of these things equally, when they simply won't be equal. So as active investors, that provides us with a real opportunity.

Eloise Goulder: So to the extent that you can identify stocks in these segments that have really outperformed, but where the return on capital is actually not that impressive, or the longevity of the growth is actually not that impressive, or because the cash flow itself isn't necessarily growing that strongly, even if earnings are, in all of those cases, differentiating and potentially finding underweights is the goal.

Helen Jewell: Exactly. And everything you said there was unknown and uncertain at the moment. It's really, really difficult to know exactly how the return on investment from AI is going to play out. And until we have more granularity on that, and we will get more granularity, the market is basically going to do what it's done at the moment, which is lump everything together. And that is when it becomes exposed to the momentum trade. And the quality growth names that rely on some kind of certainty on how that earnings will play out has underperformed. So we just need that certainty, that granularity to start to come through.

Eloise Goulder: So which data points will you be tracking to get a better handle on those questions?

Helen Jewell: There's two areas that we're always looking at. One is where there are real bottlenecks in the market. And the memory companies is where we're really seeing that. I was fortunate enough to be out in Korea a few months ago visiting some of the big memory names. And when we asked the CEOs, how long is your current order book for memory, they said three years. So even if we had placed an order that very day, we would not get anything through for three years. So that is an obvious bottleneck. And that then gives you a real certainty on what that earnings will look like. On the other side of things, we're looking at areas where you're seeing more commoditization. So for example, around the large language models, the LLMs, if these are starting to be commoditized, if what we're seeing is the consumers of the LLMs, the users of the LLMs, trying to diversify between the models that they use, that obviously is a bad thing and negative for the LLM providers. So they're not really data points per se, but they are more case studies of where you are seeing the real focus on scarcity versus the opposite, where you're seeing much more of a commoditization of what previously perhaps had been more scarce.

Eloise Goulder: And turning to the perceived losers group, the area that's underperformed has been software, as you mentioned. Helen, how do you think about differentiating within this segment?

Helen Jewell: So this again is a really interesting one from an example of where the market has just been indiscriminate. The view in terms of software has been that the future earnings potential has been disrupted and all of the names have been put into the same bucket. What they’re basically saying, the market is saying, is that the terminal value of these companies is going to be zero and zero quite soon. And the last time in my career that I remember saying that is when we were talking about the energy names. And that wasn't the case for the energy names. Certainly not in the near term. I think when it comes to the software, the two areas that we should focus on is the ones that have got valuable data sets and the ones that they've got a really, really useful use case for the end consumer. The market at the moment is really not valuing either of those things. It is assuming that if you can utilize any of the models, that you will do that rather than using any kind of software interface. I don't think that will be the case. I think actually, again, the terminal value is a lot, lot longer out than perhaps we think at the moment. Similarly, data sets. Data sets are incredibly valuable. And data that has been collated in a structured way over a very, very long period of time is very difficult to replicate quickly.

So again, I think that the market is really overestimating the damage that is being done to those kind of companies. Now, I don't think we've got enough confidence in the short term to be able to say there is a catalyst for this view to change. But if you, again, are a long term investor who is willing to look at these valuations and think, actually, from a valuation perspective, these look really interesting, you are potentially getting a company, maybe low growth, low return on capital, but certainly a company that has got earnings potential going forward that isn't currently priced in.

Eloise Goulder: Interesting. And talking of valuation, what sort of models do you utilize in order to determine fair value for all of these companies? You know, you're looking at earnings growth, you're looking at cash flow growth, you're looking at return on capital. How do you put that together in a valuation framework?

Helen Jewell: So whenever we're looking at valuation, we're looking at the future earnings. And we're looking at the multiple that the market is willing to pay for that. And that always goes back to what the future earnings growth will be, what the return will be, and also what the risk free rate is. So if interest rates increase, then on the whole, what you will see all else equal is valuations will come down.

When interest rates fell close to zero, post the financial crisis, we found the price investors were willing to pay for growth increased significantly. And then when we saw that reverse a few years ago, we saw a big reversal in that. But 25-bit shifts don't really have a massive change in terms of the actual valuation of companies.

So what it really comes down to is a couple of other things. The most important is the likelihood of the moat being sustained in the long term. And that is what is key right now. Because the longer any of these moats around the earnings will be sustained, the higher the valuation should be. And that is going to be dependent on not just the pace of structural change within AI, but also other things for example, government policies and the geopolitical world order. So that can be really, really challenging to get right. But it is something as fundamental investors that we try to do.

The other thing I'd like to just mention, and this is something we've talked about previously, is the premium for structural growth, which historically has been pretty high. What you've historically had is buyers with a long-term view. And if you have buyers with a long-term view, they care about getting these companies, and they are basically willing to almost pay whatever price it takes to get them. So what you saw historically was a real premium for structural growth, 10-20% above what might be normally expected for any company that has got that level of earnings growth, if that growth has got high returns. The issue at the moment, Eloise, is that we are now seeing more and more short-term investors come in. And that has eroded the premium away because there are fewer investors around willing to pay an additional premium for that structural growth. So the challenge is really understanding how big that premium really should be.

Eloise Goulder: And Helen, it was so interesting to hear you speak earlier about this increase in presence of momentum exposed investors, because certainly if we look at market structure over the last six years or so, there has been a phenomenal change. And if you dissect what are the main drivers of that increase in volumes, it's really fourfold.

First of all, there's the retail investor who in U.S. equities in particular have really shot up in share of volumes post-Covid, now representing 20% to 25% of volumes on a daily basis. Second of all, you've seen these shorter dated options, including zero day to expiry options, which now make up about half of S&P 500 options volumes, having been less than 5% of those volumes in 2020. Third of all, you've obviously continued to see this growth in passives and ETFs over many years. Finally, you mentioned quant strategies. Well, if we look in our prime book, we do see that quant hedge fund exposures have grown more than any other hedge fund category over the last couple of years. And of course, if we look at those four market participant changes, many of those investor types have shorter holding periods. Many of those investor types are more trend or momentum exposed. So Helen, how do you navigate investing in the knowledge of all of those market participants too?

Helen Jewell: Yeah, exactly right. What we're seeing is a much larger proportion of the market holding stocks for only a few months on average, according to some of the data that we look at. So whilst you might see some of the investors in the market looking at longer term forces, there is a bigger group that are playing nearer term catalysts. And there's also I think, a much bigger group of investors who have a predisposition to really buying the dip. You and I grew up in an environment, we saw the global financial crisis. And that means that we've always got this nervousness around the markets and what the market is signaling. But if you've only ever seen the market go up, then you buy the dip, that means that you have more of the momentum trade. And we end up again in this cycle, which really is a part of the market that we've not seen before.

 Eloise Goulder: But Helen, how do you really think about the retail investor? Because we know that collectively, the retail investor is a very significant force in volumes globally, particularly in the US and in many pockets of Asia. And yet we know that they're also a very heterogeneous group. You have the younger cohort, but you also have the older or high net worth type cohort. You have the buying the dip mentality, and the shorter-term mentality. But you also have the much longer-term investing mentality. You have those that focus on social media, and meme stocks and those that probably don't. And you certainly have many retail investors who focus on longer term structural themes, potentially very similar to many institutional investors. So Helen, how do you think about this group and investing alongside this group?

Helen Jewell: It's really difficult to know. What it does mean, though, going back right to that very first question you asked me about being a long-term investor, who ignores the noise, it does make it more difficult for that group, because you're seeing the market move quite significantly on any given day. Now, we've seen, as you mentioned, things like the Kospi move up and down by plus and minus 20%. And that can be really challenging. It means that long term investors, just need to hold their nerve that little bit more when they're thinking about ignoring the noise.

Eloise Goulder: And your point that if you can truly compound value accretive growth over multiple years, you do as a company have potential to invest and pivot into the areas that have greatest potential. And so if your holding period is long enough, you as an investor can be exposed to those very companies.

Helen Jewell: That is 100% correct.  Companies that have got strong earnings growth and high returns on capital will do well over the long term. The two things that perhaps aren't always super clear is how long is the long term? And secondly, how much day to day pain and volatility will it take before that theme comes through of being a long-term winner? And that is the challenge of the market that we're facing today.

Eloise Goulder: So Helen, before we close, you have an expanded remit, you're now CIO for fundamental equities across Asia, as well as Europe. And the Asia region has had a phenomenal run over the last year. So what are your observations on the similarities and the differences in investment approach across both those regions?

Helen Jewell: So let's start off with having a look at the companies. Now the similarities is that it is the AI theme that really is playing out. But what we see in Asia is that the dominant growth drivers are a lot of the chip companies. Whereas actually in Europe, a lot of them are in power generation, in things like cement and concrete, and all the elements that you need, for example, for data centers. So the types of companies that we are seeing being the real drivers of the market are slightly different.

The other key difference is the market participants. So the retail participant, that is much more of a trend that we are seeing in Asia, particularly when it comes to things like leveraged ETFs. We haven't really seen much of that within the European market. And that means that the focus on momentum is much, much greater in Asia than it is in Europe. But let's also bring it back to the key similarity between all of the markets that we look at globally. Long term, they will all be driven by earnings. That is the 101 of investing. And that is the key thing that we always need to remember as we're building our portfolios.

Eloise Goulder: Thank you, Helen, for such a thought provoking discussion on a very topical theme. What is the appropriate price to pay for high growth, high return on capital companies? And how indeed do you identify them? So thank you so much for sharing your thoughts with us today.

Helen Jewell: Thanks, Eloise. It's great to be here.

Eloise Goulder: Thank you also to our listeners for tuning into this Making Sense podcast. If you have questions or if you'd like to get in touch, then please do go to our website at jpmorgan.com/market-data-intelligence. And with that, we'll close. Thank you.

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