Quality Matters Again

Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Global Head of Fixed Income Research at Morgan Stanley.

Today, what can Odysseus teach us about investing?

It's Friday, July 24th at 2pm in London.

Like many of you, this week I saw The Odyssey. The enduring appeal of this story more than 2,700 years after it was composed is a reminder that some themes are universal. Pride, resourcefulness, determination, self-control, or the lack thereof, mattered to both an ancient Greek dinner party and resonate with anybody investing today.

But drawing lessons from the past is also tricky.

We do not have that much financial history, and markets contain too many variables for the same combination to align twice. Some judgment, art, and dare we say storytelling is always involved in deciding which historical periods best describe the present.

Those disclaimers aside, we've argued in our year ahead outlook that 1997 to 1998 and 2005 to 2006 are some of the most useful templates for the current backdrop.

That remains our view.

They suggest a cycle that has further to run, equities outperforming credit, and a preference to own volatility. Both of these periods were defined by a sharp rise in corporate activity. That is certainly what we're seeing today.

We forecast U.S. capital expenditure to rise 23 percent in 2026, and 26 percent in 2027. AI is the biggest driver of this spending but build-outs in energy infrastructure are also playing a role. And increased corporate CapEx is certainly a global story, especially in Asia.

Then there's M&A, which also rose significantly in these two past historical periods. As recently as early 2024, global M&A volumes were unusually depressed, some of the lowest levels in over 30 years, adjusted for economic size. But that's no longer the case. And more recently, M&A is currently running up 64 percent relative to a year ago.

Important current macroeconomic data also looks somewhat similar to these past two periods. The current levels of U.S. core PCE inflation, the unemployment rate, and the 10-year yield are pretty close to the averages seen in 1997, 1998, 2005, and 2006.

And the U.S. 2s10s yield curve, well, it broadly flattened then, and it has broadly been flattening today.

A third similarity, maybe less obvious but no less important, is deregulation. Both 1997 and 1998 and 2005 to 2006 saw significant financial deregulation. And we're seeing that again now. From the Basel Endgame to NAIC risk weights to Solvency II changes to savings reforms in Europe, Korea, and elsewhere, the current trend appears to be on a firmly deregulatory path.

Even more simply, 1997 and 1998 and 2005 to 2006 provide interesting narrative bookends to two ways that I often hear the current environment being described.

The late '90s? Well, that was defined by rising excitement around a transformational new technology – then the internet – and the prospect of a more productive future. Sound familiar?

And the mid-2000s? Well, that was defined by a very unequal economy and rising consumer stress – but growth that was still supported by a seemingly inexhaustible investment demand from a rising market force. Then that force was emerging markets. Today, it's AI. Again, somewhat familiar.

If these periods serve as a guide, the cycle probably has further to run, and corporate aggression should favor equities over credit.

But if we learn anything from the trials of Odysseus, the journey can throw up plenty of surprises along the way.

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.

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 why we still expect robust AI capital spending in spite of some rising political pushback.

It's Thursday, July 23rd at 10am in New York.

It should be no surprise to our listeners that data center pushback, a topic that we've been following for some time, has been growing louder. But in 2026, it's accelerated meaningfully. Data we track suggests that an estimated $156 billion of projects were canceled or delayed in 2025. This year alone, in just the first quarter, we've seen almost that same exact number.

The opposition is coming from several directions.

Communities are raising concerns about rising electricity bills, environmental pressures related to water use, and the local quality-of-life effects of large-scale construction. But it's also coming from lawmakers across the aisle. State legislatures with both Democratic and Republican lawmakers have been advancing this type of policy.

At the same time, we're forecasting a little less than a trillion dollars of AI CapEx this year alone, and we think it's an increasingly important component of the macroeconomic growth outlook.

So how do we square that circle?

First, and most importantly, we think this is primarily a supply-side risk rather than a demand-side one. Said differently, we don't expect the backlash to materially reduce projections for compute demand. Instead, it could widen the gap between that demand and the industry's ability to bring new capacity online through things like permitting delays, grid interconnection constraints, and local opposition.

Despite that more difficult political and infrastructure environment, our internet team, led by Brian Nowak, remains constructive on AI capital spending. Our broader thematic estimate for total AI CapEx, including the neo-cloud providers, stands at approximately $870 billion in 2026, and we actually see risks skewed even higher from here.

So why is spending still increasing as the environment for building data centers becomes more challenging? There are a few reasons.

First, the AI ecosystem remains compute constrained. The urgency to invest has not diminished. In fact, growing social opposition and political uncertainty ahead of the 2028 presidential election may actually be encouraging hyperscalers to begin projects earlier, which our credit strategists outline as a potential scenario—a pull-forward of demand before the political and execution risk grows even louder.

Second, the timelines associated with data center construction have become longer. From groundbreaking to operational launch, projects can now take as long as three years or even more. That gives companies a strong incentive to begin developing future capacity well in advance, even if the political pushback is strong.

And third, the underlying demand signal is not slowing. Global weekly token usage, which our analysts view as an important proxy for compute demand, has increased since early January. It's rising and continues to do so throughout the course of this year.

So, in short, the pushback is real, but it appears to be reshaping the buildout rather than stopping it.

That's why our base case is for a conditional buildout. We think projects are likely to face greater scrutiny, longer delays, and more requirements related to environmental impact and community benefits.

But ultimately, we still think they cross the finish line. That could mean higher costs, longer development timelines, and greater geographic dispersion of projects away from the largest existing data center markets.

It could also accelerate the shift toward on-site and behind-the-meter power generation. Fuel cells, turbines, and energy storage are becoming increasingly important as operators look for ways to reduce their reliance on lengthy grid interconnection processes, and that can benefit companies that are able to bring those solutions to the forefront.

Meanwhile, our U.S. equity strategy team maintains a relative preference for hyperscalers over semiconductors over the next several months. As you heard our CIO and Chief Equity Strategist Mike Wilson explain yesterday, that's because the team sees the hyperscalers as early in discounting the market's renewed focus on CapEx discipline.

Further, they retain compelling AI optionality through strong core businesses, leadership potential at the agentic application layer, and an underappreciated cost-efficiency lever.

Putting it all together, we see the growing pushback against data centers as representing a genuine risk to the pace, cost, and geography of the AI infrastructure buildout.

But again, this isn't just a demand story; it's a supply story. And somewhat paradoxically, the scarcity and uncertainty created by these constraints could actually end up pulling capital spending forward rather than reducing it.

As we've said before, the AI race is increasingly moving beyond the question of who can build the best model. It's becoming a competition over who controls the infrastructure, supply chains, and energy systems required to scale those models.

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.