Thoughts on the Market

The AI investment boom is reshaping capital markets, creating opportunities and raising questions about leverage and risk. Vishy Tirupattur and Dan Toscano discuss what this means for the credit cycle and the broader financial system.
Read more insights from Morgan Stanley.

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Vishy Tirupattur: Welcome to Thoughts on the Market. I am Vishy Tirupattur, Morgan Stanley's Chief Fixed Income Strategist.
Today, a special conversation with one of the most seasoned professionals in credit at Morgan Stanley, Dan Toscano, on AI, credit, and the interplay between them.
It's Thursday, November 5th at 11am in New York.
Dan, last time we chatted here, you were very constructive on the potential for AI to be transformative in the economy and markets, and even more constructive on the role that credit markets will play in enabling that transformation.
So, any way we cut it, we are talking about trillions of dollars of CapEx involved in the context of AI buildout. How are you thinking about the AI thesis, AI CapEx thesis and the role that the credit markets are playing?
Dan Toscano: And every time I talk to you, the numbers go up. These numbers continue to expand. The opportunity set continues to expand for our clients. And I would say that nothing surprised me of what we've seen over the course of 2026.
This is not simple, and this is not easy. And there are, as our CEO likes to say, known unknowns. And they factor heavily in the sentiment of investors. And when you're deploying trillions of dollars of capital in a way that has never been deployed in our lifetimes, there are bound to be air pockets.
And so yeah, it's gone as I thought it might. And it just keeps getting bigger and bigger. And it's interesting to me that a lot of the discussion out in the marketplace these days has moved a little bit away from ‘what is this and how does it work’ to ‘what's the value proposition?’ And I think ultimately, that's the biggest question.
And credit investors are asking that question in the form of trying to understand what can go wrong. It's the essence of a credit investor. And equity investors, although that's not my area of expertise, are asking, "What's the upside? And how should I value it today when a lot of these companies are going public for the first time?"
Vishy Tirupattur: The markets are really questioning the return on the invested capital. How soon the returns will get realized? And monetization is the key word here.
But at the back of this, we see that the level of rates have increased pretty meaningfully. Spreads have widened. So, overall borrowing costs for issuers here are clearly higher.
So, on the back of this, do you see this as really a structural supply concern? The markets having to absorb a lot of supply. Or do you see this as being something larger than that? Is it a sign of a larger challenge within the credit markets?
Dan Toscano: Yeah. I mean, there's a lot to unpack there. But look, I would say this. On the topic of, you know, what is the return? What is the value proposition? I've heard, really, two schools of thought from the marketplace. One is we think the return value proposition is high. And you've done some work on the early stages of this to value it.
So, I hear people saying there's almost unlimited upside here, and I hear people saying, "I don't know what the value proposition quite is." I haven't really heard anyone say I think this is a stinker. And I think that's, you know, somewhat emblematic of the world we live in.
But in terms of the cost of capital, I don't think we're seeing any of that in… Obviously underlying rates behave independently, and they're a function of a lot of factors, many of which are positive. And I keep reminding people that the backdrop that we conveniently pass by when we talk about this is an economy that is strong. Issuer earnings have been into the double digits quarter after quarter.
And that's not something I would take for granted. And that can change. And it's done that despite energy instability, all the other things that are impacting the consumer. And yet, you know, we're producing earnings growth and cash flow that are significant.
But back to your question about spreads, in particular. I mean, look at where spreads are today. They are, in my opinion, tight. I think we were at the all-time tights over the course of this year. And so, it's hard for me to sit here and say all this AI-related financing is driving up the cost of capital.
We don't see it in spreads. And, you know, I think the debate around the impact of the trillions of dollars that need to be raised in all markets has yet to play out in the marketplace. People are talking about it, right? It's understanding that volume is coming in scale really hasn't happened, when you think about it. But the market I spend the most time in, non-investment grade credit markets, it's been quiet now for months.
Vishy Tirupattur: In all my years of talking to you and learning from you, the one thing that's always stood out for me is: details matter. And especially when we talk about leveraged credit. So, in the context of AI financing in the leveraged credit market or the broader credit market, what type of details matter?
Dan Toscano: Look, I think that it's evolving. We've talked, I think the last time we were here, we talked about the documents. You know, the documents matter. Investors are always complaining that the terms are too loose. But in the case of what is essentially project finance, I would say details matter in all caps. And put as many exclamation points after that as Elaine Benes would allow, if you remember the Seinfeld reference.
Vishy Tirupattur: Indeed, I do.
Dan Toscano: And so, you know, understanding the details of the lease. And to me, the fundamental question that underpins details matter is: what can go wrong? And if something goes wrong, what happens? And who's taking what risk?
And you'll find that in the documents if you read them closely – in project financing – toll roads and power plants going back decades.
You know, project finance and structured credit is not a new phenomenon. How and when does cash get disbursed? And who controls those decisions?
So, you can protect yourself [so] that if something's going wrong, you don't have cash hemorrhaging out of the system uncontrollably. Things like that, they really matter.
Vishy Tirupattur: You know, one other thing that I keep thinking about is whether the constraint is people or power availability, cost of capital or, you know, potential policy constraints. You know, some sort of a slowdown in AI CapEx is viewed rather cautiously by the equity markets.
How do you think credit markets will handle, you know, a slowdown for any number of reasons in the pace of CapEx spend?
Dan Toscano: Yeah. Well, I mean, I think the pace of CapEx spend gets measured against [a] company's ambitions. Not anything else. It's – We see an opportunity, we would like to take advantage of that opportunity. And in order to do so, we need to build capacity, right?
So, what happens? Client says, "I want this thing built yesterday, not in a week." Okay. So, if it slows down relative to someone's ambitions, it doesn't really create a problem in my mind. All it means is gratification delayed.
So, I think this can speed up, I think it can slow down, as fast as people are comfortable. And when I say people, I mean investors putting capital behind management teams. But I also think management teams feeling comfortable that they can control what they're doing and when they're building capacity… If they're buying chips or selling chips or trafficking in compute, they can speed up or slow down based on the environment around them without consequence.
I think people get worried. And here's one element of timing that does matter, is, you know, once you put a shovel in the ground. And by shovel, I mean dollars, right? Time is money. And there's a lot of work being done around managing the cash flows, leading up to the construction of a data center, throughout the construction itself, which can take 12 to 24 months. And that assumes an environment that is friendly and conducive toward building data centers.
And that's where it really matters.
Vishy Tirupattur: So last question for you, Dan. I know you're a big UConn basketball fan. Other than the UConn basketball team prospects, what keeps you up at night in the context of AI financing?
Dan Toscano: Yeah. Look, I mean, AI keeps a lot of people up at night. It doesn't keep me up at night. What keeps me up at night is UI.
Vishy Tirupattur: U of I, University of Illinois, Fighting Illini, ranked number three ahead of UConn, may I remind you.
Dan Toscano: December 4th, United Center, Chicago, Illinois, I will see you there.
Vishy Tirupattur: I'll see you in Chicago, Dan. Thanks for taking the time to talk to us.
Dan Toscano: My pleasure, Vish. Great to see you.
Vishy Tirupattur: And thanks for listening. If you enjoy the podcast, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.

Dan Toscano is a member of Morgan Stanley’s Investment Banking Division and is not a member of Morgan Stanley’s Research Department. Unless otherwise indicated, his views are his own and may differ from the views of the Morgan Stanley Research Department and from the views of others within Morgan Stanley.

Democrats delivered a stronger-than-expected performance in the midterms. Our Head of Public Policy Research Ariana Salvatore examines what the results could mean for Washington’s policy priorities, the balance of political power and the investment landscape.
Read more insights from Morgan Stanley.

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Ariana Salvatore: Welcome to Thoughts on the Market. I’m Ariana Salvatore, Head of Public Policy Research at Morgan Stanley.
Today, I'll be talking about the results of the U.S. midterm elections: what the Democratic party's stronger than expected performance means for Washington, and how investors should be thinking about the implications.
It's Wednesday, November 4th, at 10am in New York.
Yesterday's elections delivered a much stronger result for Democrats than most had anticipated. Beyond the headline outcomes, Democrats expanded their margins in traditionally Republican areas and demonstrated a level of competitiveness in places that would've seemed unlikely just a few months ago.
But for investors, the more important question is what these results actually change from a policy perspective. We see three main takeaways.
First, the near-term market reaction has been somewhat complicated, particularly around the AI trade. Our U.S. equity strategists have flagged the midterms as a clearing event, although a larger Dem sweep than what was expected could introduce a little bit of volatility.
Now last night, we saw a fairly clear risk-off response. Treasury yields moved lower, the dollar weakened, and equity futures declined. One of the biggest areas in focus was Texas, where the governor's flip raised questions around potential restrictions on data center development and what it could mean for the broader AI trade.
That's an important issue given how central access to power, permitting, and geography have become to the AI investment thesis.
But we think it's important to distinguish between political ambitions and the ability to actually implement them. In Texas, for example, the incoming Democratic governor would still face a Republican-controlled state legislature.
That, in essence, limits the scope for some of the more ambitious changes that require legislation pertaining to tax policy or empowering local communities to negotiate. Of course, that doesn't eliminate the policy risk, particularly through executive and regulatory channels. But it does suggest that some of the more aggressive scenarios that investors initially contemplated may be difficult to implement.
Second, we don't think the election fundamentally changes the direction of several executive-led policy areas, including deregulation. We've been expecting a pull forward in M&A activity early next year, and that remains our view.
Politics are, of course, not the only factor. Economic conditions, the rates backdrop, and CEO confidence all matter. But the Trump administration continues to be perceived as favorable toward deal-making, and the agencies responsible for reviewing transactions remain central to that process.
The difference is likely to be a greater degree of congressional oversight. That can create headlines and add some additional uncertainty, but it's worth distinguishing between congressional scrutiny via things like investigations and hearings and actual regulatory authority. Ultimately, the agencies still drive merger approvals and financial sector deregulation, and we don't think the election meaningfully reverses that trend.
Third, the legislative implications are likely to be more limited than the political rhetoric might suggest. We've been anchoring investors to what we call our cohesive Democratic majority scenario.
Under that framework, the most consequential potential legislative change is a delay in the implementation of the SNAP and Medicaid spending reductions under the One Big Beautiful Bill Act. We think that could present a modest upside risk to our growth forecast to the extent that maintaining those benefits supports household spending.
Beyond that, we think the next two years will be characterized by considerably more political noise than substantive legislative change. And remember, the president is the story for markets. Executive-led authorities around tariffs, geopolitics, deregulation, and export controls have all been the key factors for markets.
So, what's the bottom line for investors?
We think the election delivered a more substantial political shift than anticipated, but the market and policy implications are more nuanced. For AI, the focus should remain on the distinction between state-level political constraints and the broader national imperative to support infrastructure development.
For Financials and M&A, we think more oversight is to come, but relatively limited changes to the trajectory. And on fiscal policy, delaying certain spending reductions can create a modest upside risk to growth.
Finally, we'd caution against extrapolating these results directly to the 2028 presidential race. There's still a significant amount of time between now and then, the political environment can change considerably, and issues don't carry over cleanly from one election to the next.
For now, our view is that investors should distinguish between a meaningful change in the political landscape and much more limited change in the policies that ultimately drive market outcomes.
Thanks for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.

Our analysts Andrew Percoco and David Arcaro break down how AI’s surging energy demand could reshape the way we produce, store and use power.
Read more insights from Morgan Stanley.

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Andrew Percoco: Welcome to Thoughts on the Market. I'm Andrew Percoco, Morgan Stanley's U.S. Autos and Shared Mobility analyst.
David Arcaro: And I'm Dave Arcaro, Morgan Stanley's U.S. Power, Utilities, and Clean Tech analyst.
Andrew Percoco: Today, why the AI power crunch could transform how we generate, store, and consume electricity.
It's Tuesday, November 3rd, at 10am in New York.
Andrew Percoco: So Dave, the whole AI power shortfall and, you know, how data centers [are] creating a power crunch is not necessarily a new topic. I think we've had many conversations, many people listening have probably heard this is, kind of, being a bottleneck for AI deployment.
But I'm curious, how have your views around the role of distributed power changed in terms of its role in solving some of the shortfalls in the market? I think there's a lot of debate in the industry around whether or not these solutions are "bridge." Or whether they're structural and they can be truly long-term sources of supply to the market.
So maybe just help us think about, you know, how our views have really changed, as it relates to distributed power specifically.
David Arcaro: One of the things that we have seen is that the shortfall has grown in our estimates over the last several iterations. We're now looking at upwards of an 80 gigawatt shortfall by 2029.
And how do we solve that? Well, I'd say we've leaned more into on-site power, bringing your own power. What is that? You know, if you are still waiting for years for a grid connection from the utility, what can you do as an alternative? You can bring your own power. You could bring small scale power equipment to get the high reliability in a much faster timeframe than you would waiting for the grid in comparison.
And so we're seeing that increasing extremely rapidly in popularity among hyperscalers and data center developers. And we're seeing them much more, being willing to consider it on a long-term basis.
What used to be, "Hey, I need to cover a few years just to bridge until I have line of sight to getting a connection to my utility…" Now we're seeing actually 15, 18, 20-year contracts for these, you know, what used to be considered just smaller scale, less attractive solutions.
They're now long-term, with what looks like much more permanent considerations for highly reliable data center AI power.
Andrew Percoco: I think there's a preconceived notion in the market that the grid's going to catch up; and that we won't need these solutions longer term. Or that we're building too much of it and there's too much manufacturing capacity coming to the market.
So maybe we can segment those into two separate questions.
Like one, what is actually the bottleneck? I think everyone thinks of it as a power generation bottleneck. But I think you've done some interesting work around how there's also transmission and distribution bottlenecks that don't get solved as quickly as the power generation. So maybe you can talk to that.
But then secondly, when we think about the long-term, you know, case for distributed power. Are there certain types of technologies that maybe screen better or more favorably? Or certain characteristics of certain technologies that screen more favorably when you think about this being a structural source of power rather than maybe a short-term fix?
David Arcaro: Yeah. The bottleneck is very often in the utility space. Utilities are seeing such an unprecedented demand for electricity from the data center industry. They're scrambling to keep up with it. They're not used to growing this fast, and it's often their electric transmission network that is falling behind.
It's the long distance power lines and substation equipment that the utilities are really trying to react [to] – and to grow alongside the data center industry. But we expect them to fall short; and pretty meaningfully short. You know, this is large scale infrastructure that takes years to develop and build.
So, then when it comes to onsite power, as you're growing alongside that constraint or trying to avoid that constraint. We're seeing that data centers, they're very much prioritizing speed. The quicker they can get the power the better.
But you know, more and more we're seeing other factors come into play. How supportive is the community for different applications? You know, what's the air emissions profile, the water use, the noise consideration? What are the overall emissions that you're considering here? And then also what are the operational characteristics of that equipment?
So, we've looked carefully at those. And we come down to these technologies, fuel cells, engines, turbines. The industry's really pursuing all of them in this chase for quick time to power, and to get around that bottleneck.
Andrew Percoco: And to that point, it seems like what matters to maybe the developers is changing. It used to just be cost, then it was cost plus time. And now it's cost plus time plus noise and emissions, [be]cause obviously there's always a lot of political pushback.
Take that maybe one step further and say it's not just the data center market that is looking at these technologies now. It's also commercial and industrial applications where obviously, you know, there's a big trend to onshore manufacturing; a re-industrialization of the U.S. And our teams have collaboratively estimated I think 10 gigawatts a year of incremental demand for power just from industrialization of – or reshoring of the U.S.
But one technology we haven't talked about yet is energy storage. And this is part of the... When I think about the auto industry, this is obviously where they play a somewhat critical role, which I'll talk about in a second.
But Dave, just help us understand: where is energy storage being used? And how big is that market for data centers specifically?
David Arcaro: Yeah. Storage has a number of applications out there, and one of the fastest growing applications is going to be with data centers. You know, they consume power in such a new way that data centers are ramping up and down instantaneously.
Massive quantities of electricity load, going up and down instantaneously, which is not what the grid is capable of handling, and even some of this on-site power equipment isn't ready to accommodate such quick changes in load. And so we're seeing battery storage as the solution in a growing proportion of data centers around the country.
We're expecting even by 2030, it's such a fast-growing end market, a fast-growing TAM, that we would expect the data center demand for battery storage in 2030 to even exceed the grid demand for battery storage in that year in terms of the incremental, new projects that are added in that year.
So it absolutely – a very fast-growing opportunity for lithium-ion battery storage being added to data centers.
Andrew Percoco: Yeah, I mean, that makes a lot of sense, and I think that corroborates what we're hearing and seeing in the auto industry. Where you are seeing a number of companies explore energy storage as a new end market to essentially reutilize their low-utilized capacity or underutilized capacity as it relates to EVs – just given the lower than expected demand there.
Obviously Tesla, a very obvious player in the market that has a very large energy storage business in the U.S. Ford is now building an energy storage business in the U.S. and has started to build a rather large backlog.
So, I think there's some obvious ways in which the auto industry is essentially, you know, taking the opportunity where EV demand has been lower to reutilize that in the energy storage market, which is faster growth. And in potentially some cases, you know, higher margin than they've seen in the EV industry.
So, that – to me – is like the most obvious opportunity for the auto industry in terms of how they can participate in the growth in AI power infrastructure.
The second derivative would be, you know, power generation itself. And we've seen some suppliers, auto suppliers essentially; take their automotive grade technology and repurpose it into turbine generators, into energy storage systems, into microgrid inverters to essentially serve this market with existing technology that they manufacture today for vehicles. Just repurposing it for the data center industry.
So, you know, it's an auto industry that hasn't really seen much growth over the last five years, so it's a very interesting opportunity for these companies to, with very little incremental capital investment, find areas of growth outside of their traditional sub-sectors.
David Arcaro: And as we're looking for new creative sources of power, electric vehicles are an area that some are exploring to become a source of power rather than just consuming it. I guess, how meaningful could vehicle-to-grid technology become for the broader energy system?
Andrew Percoco: I think over time it could be fairly significant. I mean, today if you look at California, there's some existing vehicle-to-grid or home-to-grid systems or programs in place. And they dispatch between 500 to 1,000 megawatts of power to the California grid during peak periods of time.
So, it is fairly significant. It's fairly isolated to California 'cause there's a very high degree of EV penetration and also residential solar with battery storage. So [it] makes it a somewhat of a unique market to be able to provide that.
But over time, as we start thinking about, you know, 20, 30, 40 percent of annual EV sales or annual vehicle sales being EVs across the U.S., that's when that could start to become a much more significant contribution to the overall power supply.
So it's probably more of a 2030 plus conversation, if I'm going to be honest in terms of when it starts to move the needle. But in places like California, you are already starting to see it, you know, contribute fairly significantly during peak periods of time.
Andrew Percoco: All right. Well, I think we can wrap it there. So Dave, thanks for taking the time to talk.
David Arcaro: Great speaking with you, Andrew.
Andrew Percoco: And thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen and share the podcast with a friend or colleague today.

Stephen Grambling explains how changes in booking habits could redirect billions in travel industry spending.
Read more insights from Morgan Stanley.

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Welcome to Thoughts on the Market. I’m Stephen Grambling, Morgan Stanley’s U.S. Gaming, Lodging, and Leisure analyst.
Today: how AI could transform hotel bookings and reshape the economics of the travel industry.
It's Monday, November 2nd, at 10am in New York.
So, we all love dreaming about and going on vacations, right? But you know what we don’t love as much? Scrolling through dozens of hotel listings, comparing prices across websites, contemplating where and how much we can use our rewards or maximize points or wondering if we’re getting the best deal for the right experience.
So, imagine the relief of having an AI assistant understand you and your families’ preferences, all of your status and loyalty points, aggregated details and reviews of all the hotels you’ve ever travelled to and might want to travel to – and all you need to do is evaluate locations? Then it finds the right hotel and books it for you.
That future is coming into focus, and it could reshape the economics associated with the marketing and distribution behind the $640 billion global hotel industry.
We estimate that every year the lodging industry spends between $22 to $55 billion on marketing. Add roughly $30 billion in fees collected by online travel agencies, or OTAs, and we're talking about $55 to $85 billion in spending that AI could influence.
Today, when you book through a third-party travel website, hotels typically pay commissions of 10 to 20 percent if it’s a branded hotel, or 20 to 30 percent if it’s independent. Booking directly through a hotel's website costs the brand closer to only 5 percent. That difference can have a meaningful impact on profitability for their owners.
As AI agents increasingly help travelers find hotels, compare options, and potentially book on their behalf we could see a major pivot in brand preference and booking channel. In our analysis of hotel searches across eight U.S. destinations, traditional search engines directed travelers to official hotel websites just 13 percent of the time. With AI-powered searches, that jumped to 97 percent.
But perhaps the most interesting finding involves loyalty programs. When we told the AI agent that a traveler belonged to a hotel loyalty program, 100 percent of the resulting links pointed to official hotel websites. When we specified a membership in an online travel agency's loyalty program, the results shifted entirely to that third-party booking platform. That means the AI agent is already factoring in your rewards, memberships and loyalty preferences into travel recommendations.
We saw similar effects in Europe.
For major hotel brands, this creates a significant opportunity. Their large loyalty programs and established customer relationships could help drive more direct bookings at a lower cost. And even small shifts add up. We estimate that moving just 1 percent of bookings from third-party platforms to hotel websites could boost hotel owners' EBITDA by roughly 0.1 percent to 0.5 percent.
Looking ahead, we expect hotel margins to start benefiting from these savings in the second half of 2027, with further gains in 2028.
Independent and boutique hotels could also profit as AI gets better at matching travelers with unique properties that fit their preferences. Meanwhile, online travel agencies aren't going away. Their extensive hotel inventories, loyalty programs, and scale in payments and fulfillment remain important competitive advantages.
For now, AI-driven referrals still account for only a small fraction of travel website traffic. But as AI platforms develop their own advertising and commission models, the economics could change.
So, what does this mean for the travel industry?
AI could help hotels attract guests at a lower cost while making it easier for travelers to find the right stay. Hotel brands have an edge with their loyalty programs; whereas online travel agencies can leverage unique inventory, boosting independent hotels. It's too early to declare an outright winner but expect more from us as this battle evolves.
Thanks for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.

It appears that credit investors have gotten most of what they’ve wished for over the last decade. Our Global Head of Fixed Income Research Andrew Sheets considers whether there could be unintended consequences.
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Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Global Head of Fixed Income Research at Morgan Stanley.
Today, how spooked should we be about the credit markets?
It's Friday, October 30th, at 2pm in London.
I grew up watching The Simpsons, and I've always had a soft spot for their Halloween episodes. One in particular that's burrowed pretty deep in my memory involves a cursed monkey's paw.
It technically granted wishes to whoever held it, but with unintended consequences. For example, Lisa wishes for world peace, the entire planet disarms; and then aliens invade and take over. That sort of thing.
Keep that monkey's paw in mind.
Credit markets are going through their own jittery episode. After a long period of support, central banks are raising rates and shrinking their balance sheets. Thanks in part to this shift, global yields have risen. And since bond prices move inversely to yields, they've driven negative total returns.
Then there's the AI boom, maybe the defining economic story of 2026. Morgan Stanley estimates that close to $900 billion of CapEx will happen this year, roughly double what we saw last year and triple the levels of 2024. And we think this growth continues, with hyperscaler capital expenditures reaching about $1.5 trillion next year – almost the size of the entire U.S. defense budget.
All that spending requires financing, and credit markets have been a key source of it. Heavy supply from this relatively new sector – technology – has pushed up both yields and spreads, especially because these issuers have often been willing to price their debt pretty cheaply, relative to the rating.
These higher yields haven't slowed down the largest tech companies, given their considerable financial resources. But it has caused ripples further down the chain. Lower-rated credits with more leverage and slower growth are being more impacted by these higher borrowing costs. And the presence of these new technologies has increased fears of disruption to existing business models, especially in sectors like telecom. And as a result, the dispersion between credits has increased.
Scary stuff. Or is it?
If you'd spoken to a credit investor over the last 10 to 15 years, you would have heard a litany of wishes. If only central banks stopped intervening in markets, compressing credit risk premiums. If only yields weren't so low. If only the growth backdrop was better.
These investors wish that the technology sector would finally issue bonds, given its extremely low weight in credit markets, which are heavily skewed towards slower-growing sectors like banks, utilities, and telecom. They wished for new bonds that were highly rated, yet also would have high spreads. They wished for a new issue premium, which had compressed sharply.
And maybe, just maybe, in their wildest dreams, they hoped they could get it all. New bonds that were highly rated in a fast-growing sector issued at a large new issue premium. And hopefully a lot of it.
They also from a business sense wanted dispersion. The case for active credit management relies on the idea that there are differences in credit performance that a skilled analyst can capture. If everything just moves together, well, just buy the index.
We got our wish. Yields are high, with investment-grade credit yielding close to 6 percent in the U.S. and over 4 percent in Europe. Spreads have widened, and there's no central bank intervention to distort this. The AI boom is resulting in record levels of highly rated bond supply in a new sector, often at a significant discount for the rating. And all of this, and more, is driving significant dispersion.
Granted, like the monkey's paw, the reality of this wish may feel different from what investors imagined. But unlike it, we don't think this is a Halloween tale.
The fact that current conditions check so many boxes of what investors were looking for and address so many underlying needs is a good, healthy thing in our view. The path is hardly straightforward.
But for now, we're less frightened of this story.
Thank you, as always, for your time. If you find Thoughts on the Market useful, let us know by leaving a review wherever you listen. And also tell a friend or colleague about us today.
And of course, Happy Halloween.