The 2027 Long-Term Capital Market Assumptions

[00:00:00] Speaker 1: Welcome back to Insights Now. I'm your host, Gabriela Santos, Chief Market Strategist for the Americas here at J.P. Morgan Asset Management. Every year around this time, we publish our long-term capital market assumptions, our flagship thought leadership piece across our asset and wealth management businesses. It's one of my favorite pieces of research to work on because we zoom out from the day-to-day headlines and think about the major secular forces driving economic growth, asset class returns, and portfolio construction over the next 10, 15 years. These LTCMAs drive around $1.2 trillion in long-term investment portfolios across our asset and wealth management. So to discuss the 2027 versions, key thematic takeaways, I'm really pleased to be joined by Stephanie Aliaga, Global Market Strategist, and Tim Lintern, Portfolio Manager and Quantitative Researcher for Quantitative Solutions, both here at J.P. Morgan Asset Management. So Steph, Tim, welcome to Insights Now. Thanks for having us. So Steph, what are the three key themes that we're seeing drive the economy, returns, portfolios over the next 10, 15 years? Absolutely. And it is such a [00:01:24] Steph: lift and also such an honor to be a part of such an awesome team across the business that puts together these assumptions each year. This year, when we put together our heads and we were looking at the changes that we needed to make, we really outlined three primary themes behind these changes. So they're not new to our LTCMA readers or to many of us, but they continue to be really important. So one, economic nationalism, this continued trend of countries looking inward and prioritizing strategic industries. And two is, of course, artificial intelligence, not only the continued advancement of the technology, but actually a lot of progress that we've seen around adoption. And then three is we found that those two themes have really resulted in a significant rewiring of capital flows to different sectors and different geographies as a result of this. So just a little bit about each of these three. So first, economic nationalism. Of course, you've seen economies continue to focus on their domestic ecosystems as it pertains to AI for the US and China. But in Europe, you also have this continued shift towards increasing investment in defense and in energy. So those two are helping drive capital growth and those economies. But they can also drag on growth, particularly for those economies that are really curbing back immigration. So in the US, that's been a pretty big headwind. And last year, it resulted in a pretty meaningful downgrade to US growth. This year, while that's still there, we've gotten a lot more optimistic on the productivity front around AI. So we spent a lot of time focused on AI this year. And we really focused on how AI is going to impact two channels of productivity, TFP and capital growth. So TFP, how much more output you're getting from the same capital and labor, and then capital growth, as we are clearly in the midst of a massive industrial revolution. And then the capital rewiring is really interesting, too, because even though on the whole, we are more optimistic about global growth this year, our global assumption has been upgraded 10 basis points. Underneath the hood, there's a lot of divergence. There's divergence in AI leaders versus AI laggards. And there's divergence within economies. So we still see this case shaped expansion, likely persisting, and a lot of different economies across the globe. [00:03:36] Speaker 1: And I'd like to delve deeper, especially around the tech adoption theme that you mentioned. So I think we're very much used to being in the AI CapEx build out phase currently. But over the next 10-15 years, it's really about the adoption of AI and broader tech innovation. So how does this actually filter through? Tell us a little bit more about the real economy side and important nuances there between developing, emerging, and emerging regions? [00:04:02] Steph: Yeah, absolutely. I mean, a lot happens in a week in AI, let alone a year in AI. So this year, we realized we really needed to take a close, hard look at how we were measuring and forecasting AI's impact on the economy. So we drew upon a wealth of academic research. You know, we do think we have better data now. We don't have a full picture of what AI is doing to the labor market. It's a task, but we have a better picture. We ran our own task-based analysis. And ultimately, you know, when we looked at particularly in the US, we see a significant share of work exposed to AI that, you know, today, researchers estimate about 6% of work hours are performed to some degree by AI. We could see that resulting in like 40% of tasks being performed by AI by the end of our forecast horizon. So a significant diffusion of AI in the economy resulting in productivity upgrades. But it's not just that. It's also this CapEx boom, right? And so how do we estimate, okay, you have these massive $800 billion in hyperscaler CapEx this year. How much of that is going towards the US? How much of that is actually like productive capacity? So it's not offsetting in other investments that may have taken place. And what is that going to look out to? So we took the not so easy task of trying to forecast the AI CapEx boom out to 2040. But we fortunately have a lot of really great investment teams that we were able to to lean on for their insights on this. And I mean, if you add everything up, we're talking about a 14 trillion dollar AI CapEx boom, which is massive. We just talk about trillions now. I know, trillions, trillions, quadrillions. In terms of checking. AI world. Yeah, yeah, yeah. Well, you had [00:05:46] Speaker 3: Jason Yamada, and he was throwing out some very big numbers. He was. He was. He was. We're getting [00:05:50] Steph: desensitized a little bit, unfortunately, but we whittled it down to the impulse on growth. And I mean, it is a meaningful driver. Capital service is growing 2.3% in the US. So, you know, overall, like a really constructive outlook because of AI, and it's something that's not just a US story anymore. So we also map this globally. In Europe, you have very services dominant economies, right? So they are well positioned to adopt AI over the horizon versus economies like Korea and Taiwan that are really important in the build out. And they're investing a lot themselves. So you saw them a pretty meaningful growth upgrades this year. Taiwan up 50 basis points and South Korea 30 basis points. [00:06:29] Speaker 1: So in the real economy. In the real economy. Yeah. And for folks maybe hearing the comment you made around perhaps the expectation that 40% of tasks are done by AI. What are we assuming in these numbers [00:06:43] Steph: happens to labor? So we don't assume mass unemployment. I mean, this is important. Yeah. Yeah. Which is really key. And I think we draw upon a lot of history from this, but also the reality that higher productivity should increase the size of the overall economic pie and result in a lot of new tasks and a lot of new jobs and industries that over our horizon should keep employment at full employment. During, you know, at times there could be more pockets of disruption, but we look at 10 to 15 years. [00:07:10] Speaker 1: Yeah. And when it comes to, all right, that's the real economy side. What about inflation? Yeah. Not just tech adoption, but how do the three themes affect our inflation outlook? [00:07:19] Steph: Yeah. So it is common knowledge and theory that higher productivity should reduce inflation because it means that the economy now has a higher capacity to produce. So more supply reduces cost pressures. But when we look at AI in particular, we really see different channels kind of occurring, some of them being inflationary. I mean, right now we have this massive AI build out. You hear supply constraints every few minutes from these hyperscalers. You have surging memory prices, and that is passing through. We're spacing the early innings of that into consumer goods, right? So we do think the early innings of this is probably more inflationary. But over the course of our horizon, you should see that, you know, begin to assuage because the economy is going to ultimately fix itself to correct for the supply bottlenecks. And we do think productivity could be disinflationary. We're just not sure how disinflationary in some cases, because it also increases income. And how is that spent? So ultimately, you know, it is it is an outlook of some uncertainty on that inflation front. We do think net net, we're probably looking at not much change there, but the potential for more significant inflation volatility along the way. Yeah, and that's important. We'll talk about [00:08:27] Speaker 1: that when it comes to portfolios. So Tim, how exactly is this huge topic of tech adoption actually feeding through return assumptions on the public market side? Yeah, thanks a lot, Gabby. We think of this [00:08:40] Speaker 3: theme tech adoption and AI in particular, as the key reason to be optimistic about investment returns pretty broadly, but especially in equities. I'll start there where we've raised our equity assumptions this year. And part of this story is really about more conviction in corporate's ability to gain from this AI phenomenon through the 10 to 15 year period. Now, we're starting to see that already. And the major driver and the mechanics of our numbers is really on margins. So we've raised our forecast target margin for developed markets globally, especially in the US, where we've got more more conviction in, again, corporate's ability to really keep those productivity gains in margin improvement. And, you know, if I think about some of those stats that we spoke about earlier this year, the amount of tasks that can be automated, operating leverage from a lot of this opportunity, you know, there's a very optimistic story to be told about costs of different kinds of cost inputs, as well as different revenue streams. And, you know, if you go speak to some of our equity analysts who are looking not over 10 to 15 years as directly, but give us a bit more insight over that shorter term horizon, we're still seeing quite a lot of good news coming through. And to your point, Gabby, it's not just about the capex winners, it's starting to see the benefits of this technology proliferate through the economy. We can talk about healthcare companies and drug discovery, we can talk about banks automating underwriting, we can talk about manufacturing and downtime practices. Another point I'd mention on this is that AI also on balance, opens us up to the opportunity of some of these more frontier technologies becoming more relevant over our 10 to 15 year time horizon. You know, everyone's sort of playing futurist to some degree. But, you know, we were at one place for autonomous vehicles, and we're at another place this year. And it just feels that on balance, we're, we're closer to a bit of a role out there. Same with humanoid robots, we've spoke about quantum computing with some of our analysts as well. Again, these aren't core factors in our in our forecast, but just open us up to maybe the idea that innovation can accelerate even further over our forecast period. [00:11:00] Speaker 1: And this is a really important point that you've hammered home in all the many hours of discussions we had during this process, that it isn't just as simple as looking by market, which one has higher exposure to tech and upgrading margins. You did so much work across sectors. [00:11:15] Speaker 3: Yes, exactly. Yeah, Steph and I worked quite closely on taking a lot of these reams of academic studies, thinking about the different types of exposure for different industries and different regions by by sector, or how much of their tasks can be can be automated by AI. I mean, clearly, there's a wide range of potential forecasts here. But we're starting to see this kick into gear. I mean, we were talking about this last year as well. And year over year, we just gain more conviction that this theme really has legs. [00:11:45] Speaker 1: Yeah. And overall, I think we're taking very much a glass half full view here when it comes to the economy, when it comes to equities. What are some of the risks around that? [00:11:55] Speaker 3: We can't shy away. We're on the optimistic end of the spectrum, I think. And we're really excited about this stuff. But, you know, humility over 10 to 15 year forecasts, where could this really be wrong? I think of two central types of risk for investors. The first is really about the central idea that the capital is being misallocated. So if we're wrong, and we get what, you know, neater emails, an agent to book us a restaurant, you know, and that's it, then this big investment wave is going to be a misallocation of capital. And that's going to lead to depreciation on balance sheets. You're not going to see that free cash flow come back. And our equity returns are going to look too high, I think. But, you know, again, as I mentioned, year over year, we feel kind of less worried about that than than we did before. A more central risk, I think, and a very interesting one in my view is, is really about where the gains of AI are kept and proliferate over the economy. You know, if you look at the past few decades, for tech investors, especially, there's been a sense that tech investment, for tech investment, bigger is better. You know, barriers to entry have been quite high. Size has been a real benefit in this economy. And, you know, a lot of these large companies in our indices can generate very high margins. I mean, look at some other cloud margins, you know, semis, data and data to platforms. There's a risk, I think, for equity investors that AI is is just increasing competition over the long run, and that maybe margins are not as sustainable as we think they might be in these forecasts. Now, that's actually probably a good outcome for the economy. So I think for investors, it's not a reason to to be too worried. But maybe it changes the composition of where we see the best returns coming from in the in the forecast period. And tie back to the message that Steph was [00:13:55] Speaker 1: giving around productivity, the capital stock, raising overall economic growth assumptions. Can you can stuff be right about the macro numbers? And then when you look at your forecast regionally, still end up [00:14:08] Speaker 3: with some disappointing returns over this horizon? Yeah, totally. Yeah, this is a central idea to our long term forecasting framework. It's probably best expressed in our EM Asian numbers. So our forecasts for Korea and Taiwan have actually come down somewhat this year, even as we've increased our GDP expectations in this region. And just to outline that on the on the growth side, you know, all that Stephanie was talking about this huge capital investment boom, you know, EM economies in general, some some way to catch up to the technological frontier in some places, we're still quite positive on EM GDP growth in general, relative to developed markets. But on at least on the equity side, the returns have flipped. So for the first time in a while, I think ever in our forecasts, our 10 to 15 year forecasts for EM economies in equities, excuse me, and our below the EM equities. And that's a real change. And a lot of that is really driven by these very semiconductor heavy markets where, again, we can say something very positive about the outlook for this, this technology and these industries. But your starting point is really extreme. Yeah, I mean, margins are through the roof, we just don't think that over 10 to 15 years, these companies can sustain such elevated profits. And so through the through the process of putting the assumptions together this year, we've been really focused on where that handoff can happen from, you know, the capex winners today, to the to the AI beneficiaries tomorrow. And you know, in a market like the US, where you have maybe a little bit more balanced, different types of company, large company, you know, in the index, you've got that that handoff, which we think maybe looks a little smoother. Whereas in these highly, highly concentrated EM Asian indices, a lot of the long term forecasts, you just have to be eyes wide open about it is a very central, like a call on on some of these key semis companies. You know, MSCI EMs now what 50% career in Taiwan. And you know, I remember when it was almost 50 China, you know, the changes are really, really large, right. So I think for the long term, being very focused on those changing compositions, and really the kind of economic claim you're making, can really get you a different return outcome, even if you're bullish on the on the macro or the tech. [00:16:31] Speaker 1: And also important, this nuance you guys are teasing out, which is that we are optimistic, glass half full on tech adoption. But we are not including in the numbers that margin stay at 80% [00:16:41] Speaker 3: plus. Yeah, exactly. Yeah, I mean, I mentioned raising our target margin in a lot of markets. But our margin forecasts are really not too, too euphoric at all, in many cases, lower than where they are today. But a level that looks quite elevated relative to history and a healthy level [00:16:59] Speaker 1: of profitability. Of course, tech adoption huge theme for the equity side. But we also have those other two themes, economic nationalism, capital rewiring, how did those affect the numbers that you? [00:17:12] Speaker 3: Yeah, on economic nationalism, I think of the most compelling impact is really on bonds. So we're talking about defense spending, energy security, critical minerals, all of this stuff is compounding with some of the fiscal side that you mentioned, Stephanie, to impact bond markets, and I'd say two key ways. So firstly, larger investment. So all of that spending, raising issuance and steepening yield curves. And then secondly, this idea of some of these populist policies or economic nationalism really impacting the inflation side. So the immigration stuff that you mentioned, tariffs, the de-globalization that we've spoken about in the LTCMAs for many years, raising inflation and risks to inflation over the forecast period. And so you take that all together. I mean, we've been doing this over the past few years, really. But look at where yields are today. Starting curves and bond returns actually look quite good to investors over the longer run. Clearly risks around that and fiscal's probably quite central to that. But over the 10 to 15 year period, we're anchored really on the higher starting yield. So that can really help investors on a strategic basis. And then on capital rewiring, I actually think going back to Asia is a really interesting story here, where in EM equities, over recent decades, issuance has been a real drag on returns. So IPO activity, index inclusion, all of that side has just diluted earnings per share for EM for really many years. And we still have a bit of that in the forecast, but things really starting to change too. So China starting to see a buyback impulse over recent years in China. In Korea, we've got the flip side of what I just described. So yes, margins are high, but they're also sitting on all of this cash now, which they're going to give out to shareholders to some degree. In Japan, we've spoken about the shareholder reform kind of dynamics, better ROEs over time. And again, that capital rewiring story is just changing where returns come from, and I think changing their roles in portfolios as a result. That's such an interesting theme, [00:19:34] Speaker 1: and this idea that you need to reward your domestic capital if you want it to stay there. Yeah, exactly. It's a huge theme in Asia. Yeah. And Gabby, I know that you've [00:19:43] Steph: done a lot of work in really trying to distill all of these themes into the volatility and risk assumptions for investors and portfolios. So what were the big changes that you saw there this year? [00:19:54] Speaker 1: Yeah. And so we've talked a lot about the return assumptions. And just to put a bow on it, I mean, the whole efficient frontier has shifted upwards. For a balanced portfolio and a balanced plus alternatives portfolio, it is a significantly better outlook over the next 10, 15 years. And just the starting point specifically for fixed income versus other asset classes has gotten even more interesting, given this huge move we've seen in yields this year. But we also need to think really carefully about risk and how the different types of shocks are changing, how relationships are changing between asset classes and within asset classes. So this is where later in the book, we get a little bit into this. So speaking a little bit about the types of shocks, you know, for 20 years there, post-financial crisis, pre-pandemic, we were only worried about demand side shocks or let's call them recession. And for that, your typical 60/40 or negative correlation between stocks and bonds, that was a good place to be. That was enough diversification for recession risk. Now, it's been a few years now that we've been talking about in the LTCMAS, this other type of shock, which is more a supply side or inflation shock. And that's really coming to the forefront, especially when it comes to these economic nationalism factors. It doesn't maybe get reflected in the inflation average number. It's more in the inflation volatility, the rates volatility and the shift in correlation between stocks and bonds that we see continuing to shift higher and be marginally positive. So that's a really important type of risk to think about. And that's where, unfortunately, bonds aren't going to do the full job. And so we talk a lot about diversifying your diversifiers. Real assets offer a lot there, which includes things like infrastructure, transportation, real estate, you could put commodities in there, where alpha, whether it's quantitative, fundamental, tactical, has a lot to offer, not just to boost the return, but also as a diversifier. So that's another big theme, demand side and supply side shocks. Besides that, though, listening to you over all these months, it's more the things that could come out of left field here. Maybe it is capital misallocation and a boom and bust around this AI theme, or maybe it's safety around AI or capital rewiring. All of a sudden, you get this return of capital that used to be, let's say, in dollar assets all of a sudden. So it's these non-easily modeled types of shocks that we need to incorporate as well. And that's why we spend so much time on the paper thinking about ways to have some thematic diversification where we may be bullish on AI and someone may agree with us or someone may disagree and be bearish on the tech adoption theme. But we created a framework to try to analyze how portfolios are exposed to different themes and how you could shift some of the assets you have to have some more thematic diversification in light of all these different types of shocks. [00:23:22] Steph: And are there any other themes that investors should be really mindful of when it comes to portfolio construction? [00:23:27] Speaker 1: So what we did in the portfolio construction piece with Xiao Xiao from your team and quantitative solutions is think about let's look holistically across asset classes, public, private. Let's analyze the return streams using a thematic basket of these three themes. And let's see how they move together. So how much tech adoption is driving not just U.S. equity returns, but emerging markets, private equity, venture capital, private credit. There's just the tentacles of AI are everywhere. [00:24:02] Speaker 3: You can see the hidden correlations that you don't think about in a lot of the asset classes that we think about. [00:24:10] Speaker 1: And how, you know, just looking historically to do this analysis, it looks a certain way, but based on this $14 trillion of finance, which a lot of it is going to come from debt issuance, those shifting correlations are going to show up in other places as well. Think investment grade corporate bonds, right? Start behaving more closely with the tech adoption theme. And because we are glass half full on the theme, if you just do, you know, your usual optimization of a portfolio, you would end up with a portfolio that has a high exposure to the tech adoption theme just because of the numbers and because of the rising representation. So if one does want to take that down, really, it goes back to real assets, again, a big winner here, and it goes back to duration or government bonds. So another plug for bonds there, not to be completely forgotten there. And then when it comes to economic nationalism, that theme is one that really comes out, as you said, in steeper curves, more unstable correlations. So again, real assets, a big winner. Last thing is hedge funds with the capital rewiring. We see that as a way to actually positively increase exposure to that capital rewiring theme, which otherwise is a bit harder to come through in portfolios. So not just regional diversification, asset class diversification, but thematic diversification, looking holistically across portfolios. So in the final time that we have, it's tradition here in Insights Now to talk a little bit about whatever you're reading, watching, listening to that you would first recommend to our watchers and listeners, but also that informed your thinking around all of this long-term work. So Steph, we'll start with you. [00:26:05] Steph: Steph Lee: So I would say trying to craft a methodology around estimating AI's impacts on the economy is no easy work. But I've been so grateful to the wealth of body that a lot of economists have been writing and researching around this impact. And so we leaned heavily on Jerome Asimoglu and his research around mapping AI's impacts on task automation to the broader economy. I'd also say I've loved listening to the chief economist at the model lab. So Peter McCrory, old colleague, JP Morgan alum, he's chief economist at Anthropic and that Economic Research Institute is putting out amazing work that's helped us to inform and anchor where our starting points are around AI adoption. So I would say keeping up with those, the chief economist or open AI, and then, you know, saying subscribe to the NBER and reading a lot of the research that continues to come from these academics. [00:26:56] Speaker 1: Steph Lee: And with some hefty dose of some checks and balances around some of the perhaps Anthropic. [00:27:02] Steph: Steph Lee: Yes, yes, absolutely. Absolutely. I thought you were going to say like using AI to help you read all of it too. [00:27:06] Speaker 1: Steph Lee: Well, you don't have to tell us how much you do. But anyway, Tim, what about you? [00:27:12] Speaker 3: Steph Lee: Yeah, you know, in the LTCMA process, it's really a privilege to spend some time thinking about these very big macro forces that are impacting the economy. One that came up a lot in our discussions this year, very live right now is this question of global imbalances. And for those interested, I'd recommend seeking out the back and forth between articles and on, I guess, inevitably on Twitter, between Gita Gopinath and Brad Setzer. So, you know, on the face of it really, it sounds like one of the dullest things in the whole world. So two wonks talking about currency policy and global savings. But you pull on this thread and you realize that this is, you know, this is about, if you think about, it's really about China's trade export service. You know, it's really about where factories get built, where innovation happens, how prices are formed. And you realize that these, you know, perhaps seemingly dry topics are really impacting our lives, not just our numbers and LTCMAs, but our welfare on a day-to-day basis and a great, a great debate. So yeah, go check it out. [00:28:18] Speaker 1: Excellent. So thank you so much, Steph, Tim, and thank you for listening and watching. And of course, you can also check out our full 2027 long-term capital market assumptions on our website at jpmorgan.com/ltcma. Thank you so much for joining us for our discussion and how to think about the three major themes driving economic growth, market returns, and portfolio construction. See you soon. [00:28:47] Speaker 4: This material is for information purposes only. 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