(Bloomberg) — Enthusiasm for Big Tech and its huge investments in artificial intelligence is powering the stock market to record highs again. With a resilient economy and scorching demand, there’s seemingly only one obstacle that can derail this ride: higher interest rates.
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Technology companies are historically sensitive to Treasury yields because their high market valuations are based on growth estimates, with bigger profits anticipated sometime in the future. This is particularly true with AI-related capital expenditures, which aren’t expected to fully pay off for years.
In this forward-looking equation, interest rates help Wall Street determine the value of those future profits in today’s dollars. In essence, the more rates go up in response to rising inflation, the less those earnings are worth, putting selling pressure on the shares.
“Stocks with higher multiples tend to sell off when rates rise,” said Maria Llerena, director of financial research at Domini Impact Investments.
Last week’s relatively subdued readings for consumer and producer prices tamped down expectations that the Federal Reserve will hike rates when it convenes next month. That helped to drive the S&P 500 Index to another all-time high on Thursday and pushed the tech-heavy Nasdaq 100 Index within 2% of its first record since early June.
In the big picture, however, inflation remains well above the Fed’s 2% target. Traders are pricing in at least one interest rate hike by the end of the year. And the yield on 30-year US Treasury bonds is hovering around the highest it’s been since 2007, while Thursday’s long-bond auction drew the highest yield since 2001.
All of which represents a real risk for the major AI spenders, who are increasingly being forced to finance their ambitious capex plans by selling long-term debt.
For example, Google parent Alphabet Inc. has $27 billion of bonds that are due in 2056 or later, Amazon.com Inc. has roughly $32 billion, and Meta Platforms Inc. has about $21 billion. The companies along with Microsoft Inc. are projected to spend $740 billion combined on AI computing infrastructure in 2026 and another $1 trillion in 2027. All are facing questions about when, if ever, those investments will generate proportionate returns.