What ‘IPO' really stands for — and whether you should be buying SpaceX and the AI giants

The article warns that IPOs are often overpriced and underperform the market over time, citing that since 1990, 52% of new listings lagged the S&P 500 in the first month, rising to 70% by one and two years out. It argues that hype around upcoming AI and tech listings such as SpaceX, OpenAI, Anthropic, Databricks, and Anduril increases overconfidence and favors caution over chasing new issues. The piece is largely opinion-based and unlikely to move markets materially.

Analysis

The key market implication is not that IPOs are generically bad, but that late-cycle enthusiasm in private markets is being monetized into public liquidity at exactly the point when marginal buyers are most overconfident. That usually transfers return potential from public investors to insiders, while also creating a post-listing supply overhang as employees and early backers diversify into strength. In a frothy AI tape, the first-order move can still be up, but the second-order effect is that every successful debut raises the probability of a broader “good news is already priced” regime across the sector.

For UBER specifically, the article is a sentiment negative for the entire “late-stage disruptor” basket because it normalizes skepticism toward high-profile growth listings and reminds investors that brand-name winners often underperform after the initial excitement. That matters for UBER less as an operating company and more as a benchmark: if capital rotates away from speculative growth and toward cash flow, UBER should hold up better than the next wave of pre-profit IPOs. The relative-value opportunity is to prefer public, scaled platforms with improving margins over freshly listed peers that still need multiple years of execution to justify valuation.

The contrarian read is that the most obvious short—new IPOs—can become crowded and expensive to express directly, especially if the debut is engineered to be scarce and the float is tight. The better trade is usually to fade the second derivative: short the basket of likely post-IPO beneficiaries in late-stage private markets, or own liquidity-rich incumbents that gain share when capital markets close the valuation gap. A reversal would likely require either a broad risk-on liquidity shock or one or two monster debuts that reset the narrative and pull more capital into the asset class, but that is a weeks-to-months catalyst, not a structural one.

Key Decisions for Investors

• Do not chase first-day prints in forthcoming AI IPOs; wait 30-90 days post-listing for float expansion and lock-up pressure, then reassess. Expected edge improves materially once insider supply begins to hit the tape.
• Relative-value long UBER vs short a basket of upcoming pre-profit AI IPOs/late-stage private names when they list. UBER has the benefit of existing liquidity, proven demand, and less binary post-debut supply risk.
• If access exists, buy put spreads on the first two major AI IPOs into their debut month. Structure for a 2-3x payoff if post-listing mean reversion resembles prior high-hype debuts; keep premium small because squeezes are possible.
• Overweight profitable software/platform names with strong free cash flow and public market liquidity over venture-backed comps. The trade benefits if the market re-rates away from story-only growth over the next 3-6 months.
• Set a tactical alert for any IPO trading >20% above issue price for five sessions: that is typically where secondary sellers and insider hedging intensify, creating a better short entry than the open.