Third quarter commentaries are now live!
This quarter, Jeff Hyrich discusses where we believe we're finding opportunities in the markets today while Derek Skomorowski explains why he believes a piñata is the perfect metaphor for private credit.
A few charts worth discussing
“Morgan Stanley’s tech momentum index has already seen more daily moves exceeding 5% in either direction in 2026 than in 2000 and 2001 combined. The split between big up days and big down days is also intriguing. I wonder how many people would guess that declines of more than 5% accounted for 41% of those outsized moves in 2000 (15 of 37 days), compared with 57% so far in 2026 (37 of 65 days).”
“Private investors now own about 70% of U.S. federal debt, including hedge funds holding nearly a tenth of the Treasury market, raising concerns about how quickly yields could shift if better opportunities emerge elsewhere.”
Other charts worth pointing out
U.S. TV-viewing time by distributor
Monthly household childcare costs by amount
Retail chain locations across housing markets
Relative home values vs. proximity to retail chain locations
Monthly corporate AI token spending
10-year bond yields – U.S. vs. China
Relative returns by region – MSCI Growth vs. Value Indexes
Relative returns by region – Small vs. large caps
Relative returns by region – MSCI Cyclicals vs. Defensives
Relative returns by region – Momentum Indexes vs. markets
Forward P/E ratios – small vs. large caps by region
Capex growth by investment cycle
Who’s paying for the AI build-out? Probably you
Stijn Van Nieuwerburgh of Brookings estimates the AI infrastructure boom will cost the equivalent of 3.6 per cent of US GDP a year over the eight-year period to the end of 2032 — equalling the annual spending on the railroad boom of the late 19th century, plus the interstate highway projects of the mid-20th century, plus about two-thirds of the electrification spending of the early 20th century. Total bill: $10.3tn, an estimate including only tangible expenditures, not intangibles such as software.
Who pays? Substantially all of the profits of some of the world’s most profitable companies — the so-called hyperscalers — have been staked. Add to this the new debt these mega-companies are taking on directly or guaranteeing, supplemented by more speculative debt and equity financing for smaller companies. Almost every big pool of capital, from every corner of the developed world, has been tapped. In short, if you have invested savings, you are financing the AI build-out.
The details are not easy to nail down, but hyperscalers’ direct investments are the most transparent. Alphabet, Amazon, Microsoft, Meta, Oracle and SpaceX are expected to generate $760bn in cash flow this year. All of this and more will be invested, meaning “free cash flow” will be negative, a situation Wall Street expects to persist for several years, even as profits at the companies are projected to grow at a breakneck 30 per cent a year.
Equity investors can console themselves with the idea that a big chunk of the hyperscalers’ investment converts into profits at semiconductor companies. But remember that these companies are investing heavily, too: capital expenditures at the 30 largest are set to pass $200bn this year, double the level of three years ago, and to grow from there.
There is another layer of financing flowing from the hyperscalers and chipmakers: equity investments in AI labs and other AI start-ups. Nvidia, for example, carries $94bn in private and public equity investments on its balance sheet, including stakes in OpenAI, Anthropic and CoreWeave. In a gold rush, it is often said, the real profits are made selling picks and shovels. In the AI gold rush, the shovel companies are investing part of their profits to buy mines.
The six hyperscalers and the big global chipmakers together are worth $31tn, or a staggering 20 per cent of the world’s stock market capitalisation. American families hold a particularly big portion of this equity risk: stocks account for almost a third of household assets, not including the equities backing pension entitlements.
Turning to debt. So far this year, $466bn in AI debt has been issued, according to Morgan Stanley. This figure may not be comprehensive, given the rainbow of asset-backed securities, convertible bonds and preferred shares that have come to market. Despite the intrinsically speculative nature of investment in a new technology, the debt supporting data centres is mostly rated investment grade — either because it carries guarantees from the highly rated hyperscalers, or is secured against the GPU chips. Is it a bit worrisome that a group of companies that are devoting all of their profits to a set of projects is also guaranteeing a lot of the debt financing of those same projects? And that much of the rest of the debt is secured against physical assets that will become less valuable if demand for AI services disappoints?
It is. But there is no way for AI infrastructure to be built without the investment-grade bond market. Over $2tn of US IG bonds were issued over the past year. Whatever needs to be done to secure investment-grade ratings will be done. This is the same reason why the hyperscalers are issuing bonds in the UK, Canada, Switzerland and Australia.
The significance of the investment-grade ratings, from the point of view of savers, is that they allow AI debt a bigger role backing pensions, annuities and life insurance policies. If you own any of these things, you are increasingly invested in AI infrastructure.
This week’s fun finds
A little comfort goes a long way. Shakira from the Compliance Team, served up a lunch that was tasty, filling and tough to resist.
Winner, Winner: The Chicken McNugget Story
In March 1980, McDonald's put a new item on the menu at 15 restaurants in Knoxville. Within weeks, Chicken McNuggets made up 20% of sales at those stores, and within 100 days its supplier had built another plant to keep up with demand. The success looked instant, but refining the process had taken years, and the full story, from chicken to Chicken McNugget, spans three decades.
