SpaceX and OpenAI are reportedly targeting IPOs in 2026, with implied valuations of $1.25 trillion and $852 billion, respectively, which would make them the largest U.S. IPOs in history. The article argues both would debut at very rich valuations, with price-to-sales multiples around 69 for SpaceX and 65 for OpenAI, and warns that large IPOs have historically underperformed after listing. It recommends investors wait for a better entry point rather than buying immediately on debut.
The setup is less about the IPO itself and more about where marginal capital comes from. A pair of mega-debutants with extreme sales multiples will likely absorb a large amount of speculative risk capital, which is usually funded by de-risking in the closest liquid proxies: high-multiple software, AI infrastructure, and any “next big thing” listed basket. That creates a near-term relative-value short in crowded growth names even if the broader market stays constructive. The second-order effect is a supply overhang in venture-backed AI. If these listings re-rate poorly after the first few weeks, private-market marks across late-stage AI funds will get repriced lower, tightening follow-on financing and making public-market comparables harder to defend. That can actually help incumbents with durable cash generation, because they become the “safe AI beta” once the IPO halo fades. The market may be underestimating the duration mismatch. IPO enthusiasm can persist for days, but the fundamental burden here is measured in years: revenue has to compound into the valuation before margin discipline matters, and the longer profitability sits out, the more vulnerable these names are to multiple compression as rates remain restrictive. The main contrarian point is that a failed first-year post-IPO trade does not mean a bad long-term entry; it often creates a much better setup 6-18 months later once lockups expire, growth normalizes, and the hype premium drains out. In the existing tape, the clearest signal is not to chase the first print but to watch for dislocation in profitable AI beneficiaries versus speculative AI narratives. If the IPOs open hard and then fade, that is usually a short window to fade the weakest revenue-quality names and rotate into companies with actual free-cash-flow support.
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