The chart below shows similar anomalies in bonds of two other hyperscalers — Alphabet and Meta Platforms — and chipmaker Nvidia NVDA.O, which isn't building data centers but is rapidly scaling its own production capacity.
In each pair, the bond floated more recently has a far greater amount outstanding than the older issue, along with a yield and spread that are 15 to 22 bps greater.
In the credit universe, these differences are far from trivial. The gap was twice as big as the spread differential between the average AA-rated and A-rated corporate bonds on the same date, according to ICE Indices.
While this pricing gap was not seen at fellow hyperscalers Microsoft and Amazon, that's because there were no comparable matched pairs of bonds. Where the conditions were present, the pricing anomaly was consistent.
What accounts for this? The sheer size of the hyperscalers’ financings appears to make them difficult for the market to absorb.
Bonds with $3.5 billion to $4.0 billion outstanding are very rare. They rank among the top 1.5% in the investment-grade corporate universe. Having so many of these giant issuances arrive in a short period of time is bound to cause market indigestion.
That’s particularly true because institutional investors’ diversification requirements mean they must avoid becoming overly concentrated in a single sector, especially one that faces the serious risk that its colossal investments in AI will fail to pay off with adequate returns.
Moreover, with hyperscalers expected to continue making mammoth additions to debt supply, these anomalies could intensify.
The net result is that conventional assumptions about debt valuation have been challenged. Essentially identical risks are now being priced differently, subverting a fundamental assumption held by participants in the $10 trillion investment-grade U.S. corporate bond market.
That matters beyond the trading desk. Credit markets exist to allocate capital efficiently by pricing borrowing costs in line with risk. When that mechanism breaks down, capital can flow to the wrong places, resulting in a suboptimal economy.
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