Over the past several years, Ed Cass has seen first-hand how labour issues, political tensions and technological change have impacted asset prices. In this conversation, he reflects on the rapid advancement of AI, the Fed pivot, and why the current investment landscape is unlike any we’ve seen before.
How have recent geopolitical tensions challenged your investing process?
Ed Cass: Well, for the last three or four decades, countries largely worked together with a similar agenda within a rules-based international order. And one of the things we’re all struggling with now is whether we’re on the verge of a breakdown of that order—and what that will mean for investors. A different emphasis on industrial policy or security policy for instance, can have big implications on how the overall economic system functions.
This is a relatively new thing, at least in terms of our economic experience, and it’s tough to gauge it. We don’t have great economic data going back over six centuries, say, when there was a lot of geopolitical conflict that you could express in terms of impact on asset prices. That’s in essence, our challenge now.
How has this changed your thinking as a long-term investor?
Ed Cass: One of the big assumptions we make when we look at asset prices globally is the convergence of economies over time. Emerging economies will gradually increase their GDP per capita, they’ll open their markets and capital flows will become more global. If you believe in that, then there’s a pretty strong forward connection between GDP and the size of investment universe. And when we think about diversification and asset allocation, the size of the investment universe 10 or 20 years out is one of our starting points.
Arguably, some of the things we’re seeing globally right now could challenge that convergence path. If China doesn’t have the same objective goals as the U.S., Europe and developed countries, if it puts more emphasis on social goals than purely economic ones, does that impact the rate of convergence of markets over time? That’s probably the biggest implication for us in terms of how we think about where we’re going as an investor.
Right now we’re looking at what we thought five to 10 years ago in terms of where GDP per capita would be in China and India. Are they on the same convergence path or are they starting to deviate from that? And if so, what does that mean in terms of our future allocation of assets?
How do you go about building a portfolio that’s resilient to these kinds of shifts?
Ed Cass: You just have to continually challenge the beliefs you had when you went in. I think that’s a trap that a lot of people have fallen into over the years and it’s one we try to protect ourselves against.
We examine our beliefs, and we try to set the criteria for when we’re going to change our mind up front, as opposed to in the moment. In the moment, it’s always very hard to be objective. That’s where a lot of people have lost their way over the years.
So interest rates…
Ed Cass: One of my favourite subjects.
The Fed’s hinting at rate cuts. Markets expect the Fed to cut even faster than it’s hinting. How does that change things in terms of opportunity?
Ed Cass: So this gets to the heart of a basic point we don’t always appreciate. It’s not what happens in the economy that matters, it’s what happens in the economy relative to what’s embedded in asset prices. All else being equal, if you said interest rates in the U.S. were going to go down by 300 basis points over the next year, it should be really good for asset prices. It lowers the cost of funding, it lowers the discount rate, it’s arguably a boost to earnings through the lower interest charge.
But the market already has six easings priced in over the course of the next year. So you need eight easings, 10 easings to be beneficial to asset prices. Looked at through that lens, you say, well, the bar for investing in risky assets is pretty high because the inflation process has been sticky at times. That’s a long way of saying that when you think about interest rates, you’ve probably seen most of the easy money made.
How would you characterize the current transition to AI?
Ed Cass: Well for us, the question is, how is the technology going to be used and what’s the implication for asset prices? Part of the problem is it’s just really hard to tell—given what we know about AI right now—to say who’s going to win in the future. We don’t know the future capabilities. We don’t know what the business model is going to be. We don’t know who the winners and losers are going to be from a proprietary versus open AI standpoint.
So we’re back in that land where we’re going to have to make assumptions. One of the things we’ve been doing is, again, trying to set up the criteria. What are we assuming in terms of who the winners and losers are going to be? How do we think that’s going to flow through in terms of economics? How do we think that’s going to flow through in terms of asset prices? Then we try and compare our assumptions against what we see.
The hype over the last 12 months has been exponential.
Ed Cass: Although the underlying technological building blocks that enable AI (e.g. AI models and accelerated computing systems) have been advancing on an exponential trajectory, I’m not convinced the impact has been exponential. A lot of CEOs told me six months ago they were going to replace 10,000 workers, 20,000 workers and save billions of dollars in terms of operating costs. But we really haven’t seen that come through in the data yet.
There’s an active debate about how fast companies can adopt AI—and whether it’s going to be as fast as what’s embedded within asset prices. The prevalent view is that barriers to adoption are much lower with AI than they were with past technologies. People have talked about adoption cycles getting faster and faster, but when we look back over history, that wasn’t generally the case with respect to big transformative technologies.
If you want to rewire your manufacturing process for AI, it’s not a question of just dropping AI down on the floor. You’ve got to rewire the floor. You’ve got to lay out a huge capital-intensive budget to design a new factory. It’s not just a simple drop down of code.
Do you think we’re in an AI bubble?
Ed Cass: Depends how you define a bubble. Certainly, the stocks are aggressively priced, and some will have to do a lot to hit what’s embedded within that pricing.
We’ve taken a look at the lead up to the internet bubble and it looks really similar to where we are one year into AI. With the internet bubble, that process lasted three or four years. With AI, we’re only one year in. So, we have a long way to go before extrapolating from where we are now to where we were then. Asset prices and Magnificent Seven stock prices are aggressive, but they’re priced nowhere near as aggressively as stocks were priced in the late 1990s.
Do you think AI can replicate human reasoning in the investing process?
Ed Cass: We’ll have to wait to see. The biggest impact we’ve seen from AI so far is an increase in efficiency—not an epiphany in terms of outcomes. It’s helped people perform their jobs quicker and faster. It’s allowed people to allocate more of their time to interesting problems, as opposed to mundane ones. But the causal reasoning isn’t there yet within generative AI to provide an entirely different answer.
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