Transcript
[THEME MUSIC]
Welcome to Market Perspectives, a Mercer Advisors Podcast. In today’s episode, we’re going to look back over the last 10 to 15 years and examine the question, did low interest rates create an AI bubble? I’m joined today by Will Rockett, the Sr. Director of Investment Strategy at Mercer Advisors. Will, thanks so much for being here with us.
Thanks, Josh.
So this is a great question. We’ve talked before on the podcast about just the incredible run in tech stocks over the last decade. We’ve talked about the Magnificent Seven stocks, which are Amazon, Apple, Facebook, Google, Microsoft, NVIDIA, and Tesla, which have had just an incredible run.
And if you invest in these great companies, you felt like a great stock picker, right. But then starting last year, we started to see the great rotation where some of these stocks struggled a little bit, and the rest of the market caught up.
So we’ve talked about this topic a lot. And now we’re stepping back and saying, OK, what drove these companies to such heights over the past 10 years? And with the benefit of hindsight, was this maybe a little bit of a bubble?
So, Will, set the stage first for us. Talk about how significant was the growth of these tech companies and this story about an AI revolution in driving the US stock market over the past 10 years?
So, Josh, let’s talk about the size of some of these companies. And the Mag Seven you mentioned, let’s just talk about the top 10. So the top 10 largest stocks in the US went from being about 17% of the market to almost 38% of the market. So this is by far the most concentration at least in the last 30 years.
And I think what we want to talk about today is, what got us to this point and where do we go from here in terms of the performance of these stocks going forward? Not just saying that, I mean they’re great companies. These companies are throwing off cash flow. They’re great companies. But what about the stocks and the stock value going forward? I think that’s what we want to get into today and see where we land.
And what was the key market narrative about these companies? What was the common thread of why so many of these companies were doing so well, became companies with trillion dollar market capitalizations? What was the story behind it, the narrative.
Sure. Well, I mean, I think many adults, sometimes we learn really interesting things from our kids. So our kids are showing us that these ChatGPT and more recently, generative AI is just driving so much usage and adoption. And this has been a function of not just the tech infrastructure, but the data availability, the cloud computing.
All of these parts have just been significantly built up over the last 10 years. And we’ve seen this growing range of applications. And just it’s becoming embedded in the fabric of businesses. I know, I also do some adjunct teaching at Fordham University.
Are all your students using it now to submit their papers?
Yeah, it’s interesting. So I think instead of trying to say, don’t use it, we’re saying, well, maybe you should use it and then see the data that comes out from it. Let’s analyze that. Is that actually accurate? Is it what’s going on versus saying, don’t use it? So trying to embrace it more.
But the point is it really is becoming everywhere.
It’s everywhere. And I think where we got and how we got here comes from the investment in these companies, in this industry. We saw over the past 10 or 15 years, just massive venture capital fund investments into AI. This was in part driven by massive dollars into venture capital funds from individual investors and institutional investors.
So I think what we want to just think through here is that these companies, many of them, are just thriving. But let’s look at the stock price, the stock valuation as an investment opportunity now going forward.
So the big picture question we want to ask here was, what happened with these companies, in some sense a bubble? And so let’s introduce the concept of bubbles. What do we actually mean by the term bubble? And how would we evaluate whether or not these companies experienced one?
Sure. So think about the market price of an investment relative to its intrinsic value, what it is worth on books? What is something worth on someone who would pay for that asset? And many times the price of an asset in a bubble can rise above that intrinsic value. And it’s driven a lot by speculation of growth rates to come and investor enthusiasm around the industry, which we have a lot of right now in AI, certainly.
Right. And so bubbles, they can be —
they can happen to trivial things. Like, one of the first famous examples is, there was a tulip bubble where people in the Netherlands in the 1600s were paying an insane price for tulips because they thought they’d be able to sell them to someone else. Completely disconnected from the real value of a tulip. That’s the fundamental thing.
Or you think about what happened with Beanie Babies in the 1990s. Same thing, like a trivial asset. But people thought, hey, I can buy this and sell it to someone else at a greater price. Completely disconnected from any reasonable assessment of what a Beanie Baby would be worth.
But then there’s also bubbles that happen to meaningful industries. And there’s two in our lifetimes. The tech bubble in the late 1990s is one example. And then another one is what happened with real estate about in 2000 —
in the early 2000. So set the stage for us. What are some of the lessons from the meaningful bubbles that we’ve lived through?
I always appreciate your historical anecdotes, Josh, especially going from tulips centuries ago to Beanie Babies just a few decades ago. And let’s go back to a few decades, late ’90s. And when I started my career in finance, and we had the dot-com bubble.
We had 10 years roughly after that, the real estate bubble. And I think just to differentiate then versus now, those two versus today.
Those in the dot-com bubble, those were companies filled with very little cash flow and just off the charts valuation on just unbound revenue growth. A lot of investor enthusiasm and speculation, just no earnings.
And then from a real estate perspective, we had subprime lending, adjustable interest rates, and just this manufacturing of these structures using subprime debt that were just not well understood. A big bet and a different conversation on just the lack of accountability and leading to that vicious cycle.
But today, many of these AI public companies and the private companies, where we have some information, have good cash flow. It might not be a bubble like 2000 or 2008, but we can question whether the high growth rates built into these current valuations of say, the Mag Seven are sustainable.
And the growth has just really been fueled by massive venture capital investment and also debt raised by these companies. I think maybe we’ll get into that a little bit later.
I think one of the interesting things when you think back on the dot-com bubble or you think back on the real estate bubble, is that it wasn’t necessarily obvious on the way up that you were in a bubble, right.
With the tech companies, people thought, yes, they don’t have revenue now, but eventually the internet’s going to be huge. And they were right that the internet was going to be huge. It was just that a lot of these specific companies weren’t going to be the ones that got there, and people weren’t being careful in that evaluation.
And I think with real estate, there’s a similarity in the sense that homes, people need homes to live in and all of that. They weren’t speculating on Beanie Babies. But they had just overdone it. And you didn’t realize until too late how much you’d overdone it, how much you’d overpaid.
And in most places in the country, home prices actually eventually did get to those types of levels. It was just too far and too fast for what the economy of the year 2005 was going to be able to sustain. And so how do you think about those lessons and how you don’t really know until the asset price bursts that you were in a bubble?
Yeah, I liked what you said before about just being all in these investments. And there’s nothing wrong with being in these speculative investments, but it’s almost thinking through how much of your portfolio do you want to take a bet on.
And I don’t want to —
we have a lot of very smart investors, who I’ve learned a lot from over the last couple of years on just how they have done stock selection over the last 10 or 15 years. And I think what we should think about, and maybe to go to your history lesson to add one of my own, let’s consider the last 90 years of investing.
So since after the roaring ’20s, in the ’30s, we had regulations of markets. We had more transparency, more efficiency, and we’ve seen a number of growth cycles of different sectors. And the early days are always the most rewarding. So how about one that’s a little bit may be more applicable here.
So dot-com in 2008, we just said those bubbles were a bit different. So what about the Nifty 50? This is before our lifetimes, Josh. But these are the blue chip stocks like Xerox and Coke and IBM.
And these had sky high valuations and just not as much concern for risk. But just the growth was going to continue.
And leading up to this, it was 1973, ’74 market crash, where if you very overweight the Nifty 50, your portfolio likely decreased more than this average diversified portfolio.
So the last 10 years, AI has been growing like a weed. And these stock prices have been growing.
So now it’s thinking through what’s next? How much do you have in them? What should you do now?
It’s interesting that with all of these bubbles, it’s never just an economics question. And that’s what leads to it getting overdone, right?
Yeah, I think there’s something to be said for just the feelings that accompany the cycle of investing in something, especially when you’re winning. So behavioral finance is something which is incredibly interesting.
And if you think about maybe just a couple of themes from that overconfidence, right, overconfidence in the Nifty 50, maybe some overconfidence today in the Mag Seven, where you think past returns will continue, and maybe you’re underestimating the risk.
We saw in January significant selloff in NVIDIA just with the DeepSeek news.
And that type of risk is called idiosyncratic risk. It’s for that stock, that company. And you don’t have that same risk with a diversified portfolio.
And I guess think about recency bias, we always talk about the market just pops back up right after dot-com, after ’08, after the pandemic. And what comes from that? Is there some recency bias of just looking back at the recent past to determine what’s going to be the next 10 years? Was the last 10 years equal the next 10 years in terms of investment results? And we don’t think that’s going to be the case.
So looking back at the performance of these AI-related tech stocks in recent years, what’s the case that these stocks might have been in some sort of bubble? What I mean, we have the narrative about AI. But what other factors would we point to to say, hey, maybe things got a little bit–
there’s a possibility that things got disconnected from their fundamentals?
Yeah, I mean, how big a bubble gets is how much air is put into it.
Helium, the ratio of helium in the actual balloon. So let’s look back at the last, let’s call it 15 years. So since the Great Financial Crisis in ’08, starting, say, in 2009, we had near zero interest rate environment.
So the Federal Reserve was going through a series of quantitative easing programs, the QE, which began after the Great Financial Crisis. And went through late 2010s, like 2016, ’17. And what that was doing was like they were buying treasuries. They were buying mortgage-backed securities.
They were buying other securities, typically fixed income securities, to keep interest rates incredibly low. And from their perspective, that would help stimulate economic growth because more people would borrow, more projects, and have a positive return profile, if you pay less interest on your debt.
So the basic mechanic is it forces investors out of bonds because interest rates are so low and into other assets. And this was certainly a theme since 2009 of just dollars going into AI stocks.
Right. From 2009 to 2015, they had their rate at zero. They briefly raised it up. They only ever got to about 2.5%, which is quite low, in a historical context. They got to about 2.5 before the pandemic. Pandemic happens.
They go back to zero again.
So for almost for the majority of that period, from 2009 to 2022, we were at zero or very low rates for a very long period. And like you look at the historical chart, and there’s no other period like that where rates are that low for that long. And so combined with the narrative that was going on, what do we see the impact of zero rates having been on these tech stocks?
Let’s look at just two examples. Let’s look at Apple and Microsoft. I remember when Apple first issued publicly traded bonds, it was like 2010, 2011. But if you look at Apple’s financial statements in 2009, they had zero long-term debt. If you look at their financial statements, their balance sheet in 2019, they have $92 billion of debt.
If you’re Apple and you’re looking to grow, why not borrow at these incredibly low interest rates to finance, right? Why dilute equity? Just borrow money really cheap, right, lower than the rate of inflation.
Same thing for Microsoft. I think Microsoft in 2009 had not too much debt. I think it was about $3 billion. And then by the end of 2019, they had $63 billion in debt. So two examples of just low interest rates financing these two publicly traded companies.
And this certainly happened a lot in private markets as well, venture capital, private equity. All of these are fueled by a significant amount of debt. And if that debt is really cheap, it just allows a lot of upside for growth in the equity investment, as well as just more dollars to be able to invest it in because you’re not paying as much interest on it.
There’s a lot of business ideas or capital expansion programs or whatever that are a lot easier to pencil out. The interest rate on that thing is 3% instead of 7%. I mean, it’s the same way for a home buyer that it’s a lot easier for your mortgage to pencil out at 3% than at 7%.
It’s just in this case, you’re building factories or you’re launching new computing centers. But you’re investing in a way that you wouldn’t necessarily if interest rates were higher.
Yeah, look at it now. Interest rates are higher. Mortgage rates are higher. Corporations borrowing money is higher. Like, this is a different environment than it was in 2009 through 2022.
So in 2022, that’s when the era of ultra low interest rates stopped quite abruptly. There was inflation at that point. The Federal Reserve started raising interest rates very quickly to try to slow down that inflation. And we see that the moment those rates shoot up, the hiring at these Magnificent Seven companies, just I mean it completely — it almost completely stops in aggregate.
There’s this amazing chart where you see in the decade before interest rates increased, that these companies were hiring, growing their headcount by 10% or 20% a year, which is a measure of how much they’re investing when they’re investing that heavily in their workforce.
And then suddenly in 2022, the hiring across these companies is almost zero. It looks as if these interest rates put a brake on hiring in these companies.
Now, I think the hard question here, though, Will, is like, what do we do with this as investors? Even if you knew that these tech stocks weren’t going to go up forever, it’s pretty hard to figure out when the music is going to stop. So what do you do as an investor knowing that bubbles can be forming in financial markets?
And I think, like we said before, Josh, we’re not necessarily talking about a dot-com bubble burst here. These are strong growing companies. And we’re really talking about valuation. Is the stock worth the price?
And if we look at the data, the data suggests that if you look at the company’s stock performance since becoming one of the largest 10 stocks in the S&P 500, their performance over the next 10 years has lagged that of the S&P 500. That’s just like the data going into our conversation here.
So is it likely that that’s going to continue? Well, the data suggests that. Is it possible that one or other tech stocks or AI stocks will continue to outperform the market? Absolutely. I think going back to what you said before on real estate and the dot-com bubble, just not having all your eggs in that basket.
We believe in this diversification across public markets and private markets, and the ability to get return from stocks, not just based on their size, the Mag Seven being the seven largest companies in the S&P.
And there’s really interesting factor-based investing ideas that are being evolved today. And just in addition to investing in companies in a large percentage of your portfolio because they’re big, the S&P 500 was one about 33% the Mag Seven in January.
You can also invest in companies because of other factors than their size. So I think that’s a diversified portfolio going forward. And if you’re in a stock or stocks that have run up in value, there are methods to gradually or quickly sell down some of that position in a very tax-efficient way. And those are conversations we’re having with investors today as well.
Right. I mean we’ve talked a number of times about the challenge of diversifying a really concentrated position. And people that have been heavily invested in these companies might be in exactly that situation, where they have this huge holding, all in one of these companies that’s done so well.
And they’re not sure how to get out of it because of the capital gains that they might incur. Really interesting situation that’s arisen because of what’s happened in tech stocks.
So, well, before we wrap up, what’s the outlook going forward here? How do you think about what we do given where these companies are?
So let’s think about that in two paths. Like one, if you’re listening, you have some AI or tech stocks or a big portion of your portfolio, if you’d like to diversify out of some, you have concerns about your tax bill, we can help. I think a conversation with a financial advisor would be a good next step.
Two, if you’re still thinking that the stocks that I own are concentrated and will continue to run in the way that they have. I think let’s rephrase this bubble conversation to a valuation issue. Are these stocks worth their current prices with the growth rates that are implied with these current prices?
We’re not in that ultra low interest rate environment we were through 2022.
Josh, you mentioned this, this is not a new story anymore, right? AI is in its first chapter. So will the enthusiasm be replaced by something else? And will the dollars going into all these stocks, that technical factor continue?
And I think just that data would suggest that we wouldn’t expect these companies to be the real winners of the next decade. Obviously, there’ll be some exceptions, but how much of a bet are you taking? How much risk are you taking?
So we’re not saying, don’t invest in these companies, but we’re saying, think about how much you have invested in these companies, how the stocks of these companies have performed up and to this point, that very fertile environment for them to grow over the last 15 years.
And just thinking through, OK, over the next 10 years, how should I be positioning my portfolio to have the best risk-adjusted returns going forward and not be taking too much downside risk? And taking some of those chips off the table that you’ve won really over the past 10 or 15 years.
Will, thanks so much for this great discussion today.
Thanks, Josh.
If you’re already a Mercer Advisors client, this is a great topic to reach out to your advisor about. If you’re thinking about these issues and not sure how you want to move forward, great time to reach out to your advisor.
If you’re not a Mercer Advisors client but you’re interested in more information, visit our website, merceradvisors.com. It starts with a phone call.
Thanks so much for being here with us today. This has been Market Perspectives.
[THEME MUSIC]
MUSIC]
