AI Super IPO Wave Arrives: How Going Public of OpenAI, Anthropic, and SpaceX Will Reshape Global Liquidity?

In June 2026, the first full trading week, the U.S. capital markets迎来了 an almost unprecedented window period. SpaceX officially priced at $135 per share at the end of May, with a valuation of $1.77 trillion, entering the countdown to IPO; OpenAI and Anthropic submitted S-1 filings secretly within just a few days, with the latter valued at $965 billion and the former over $852 billion. The combined valuation of the three exceeds $4 trillion, historically concentrated within the same time window. The true impact of this IPO wave on U.S. stocks is not merely the short-term absorption capacity of new shares, but the long-term liquidity reallocation triggered by structural mechanisms. For the crypto market, the transmission path is even more complex—funding attention and risk appetite shifts have already begun to show signs.

The IPO Panorama of the Three Giants: From Financing Race to Public Market Pricing

Valuation size constitutes the first dimension for understanding this IPO wave. SpaceX, priced at $135 per share with an estimated valuation of about $1.77 trillion and raising approximately $74.4 billion, surpasses Saudi Aramco’s 2019 record. After completing Series H funding of $65 billion, Anthropic’s valuation rose to $965 billion, overtaking OpenAI. Since completing a $122 billion funding round in March, OpenAI’s valuation is about $852 billion, and in the same week of submitting the S-1, it plans to initiate a new employee stock transfer program. The three companies’ total valuation ranges from approximately $3.6 trillion to $4 trillion, depending on the final pricing stance for SpaceX and the valuation anchor at OpenAI’s official listing. Their simultaneous filings within the same window are unprecedented in U.S. stock history.

The deeper difference lies in valuation logic. SpaceX’s $1.77 trillion valuation is essentially assembled from three parts: its own business (rocket launches and Starlink), the separately valued and merged xAI (about $250 billion), and the “founder premium” brought by Elon Musk’s personal brand. The prospectus discloses $18.7 billion in revenue for 2025, but due to a sharp increase in AI capital expenditures after merging with xAI, net losses in 2025 reached $4.94 billion, compared to a profit of $791 million in 2024. The gap between valuation and fundamentals puts its pricing capacity to the test.

Anthropic presents a completely different narrative. Its annualized revenue has already surpassed $47 billion (only $9 billion at the end of 2025), with revenue growth exceeding 400% in just over a year. But there is an essential difference between revenue growth and profitability: analysts expect Anthropic might break even by 2028, while OpenAI’s profit target is set for 2030, a two-year gap. OpenAI’s revenue is around $5.7 billion, but its cost structure is heavily weighted, with deep negative profit margins. This contrast reveals the core dilemma of the AI track: high revenue growth does not equal profitability; the phase of burning cash to build infrastructure is far from over. After these companies go public, valuation logic will shift from the primary market’s “fundraising capability orientation” to the secondary market’s “revenue → profit → free cash flow” pathway. This transition means that companies once enjoying high valuation premiums in private markets may face valuation reassessment after listing.

Rob Arnott’s “Leakage Pressure” Framework: Why the Impact Is Structural

Analyzing the liquidity issues above requires a systemic explanatory framework. Rob Arnott, founder of Research Affiliates, recently proposed a comprehensive analytical logic, with the core proposition that: mega-IPOs exert pressure on markets not through one-time capital withdrawal, but via “leakage, leakage pressure”—a structural, multi-repetition, gradually spreading effect driven by index rebalancing mechanisms.

This framework involves three progressive logical levels. The first is short-term psychological impact. Market attention to giants like SpaceX is extremely high, and investors tend to concentrate subscription funds before listing, causing short-term liquidity pulses, but with limited impact magnitude. For example, Nasdaq’s rapid inclusion rule states that SpaceX can be included in the Nasdaq 100 index after just 15 trading days. This mechanism is neutral or even beneficial to new stocks—passive funds tracking the index must buy in accordance with the rules, providing short-term support.

The second level is the medium- to long-term index rebalancing pressure—Arnott’s core concern. When SpaceX, Anthropic, and OpenAI are gradually included in the S&P 500 and Nasdaq 100, passive funds tracking these indices must periodically adjust holdings to maintain weight compliance. Each inclusion and rebalancing requires index funds to sell existing large-cap stocks to make room for the new trillion-dollar entities. JPMorgan’s estimates provide a concrete reference: if SpaceX gradually releases about 50% of its circulating shares, passive funds tracking major indices might be forced to sell roughly $95 billion worth of stocks from “the Big Seven tech giants” and other large-cap constituents. This is not a one-off event but a cycle that repeats with each rebalancing, each lock-up expiry, and each secondary issuance. Arnott calls this “leakage” because the pressure is small but persistent.

The third level is that the scale of passive investment amplifies this effect. Arnott notes a key difference: during the dot-com bubble, index investing accounted for only about 10% of the market, whereas now it’s roughly 50%. The mechanical nature of passive fund weight constraints means that when new mega-companies are added, index funds “must buy,” but to accommodate the new weights, they “must sell” existing holdings. This process is driven purely by rules, not valuation logic. Consequently, rebalancing flows are predetermined and unrelated to company fundamentals.

From historical data, the total U.S. stock market cap is about $75 trillion. Short-term absorption of a single IPO is not the core issue. The more significant challenge is medium- to long-term: Goldman Sachs analysts point out that historically, large IPOs with less than 10% free float tend to see the float increase to about 46% after one year. Just this incremental supply could add roughly $1 trillion worth of stocks to the market by 2027, not counting subsequent issuances. While the exact listing timing of Anthropic and OpenAI remains uncertain, even a delay of a few months makes this supply pressure inevitable. Therefore, Arnott’s framework leads to a key conclusion: after mega-IPOs, the market’s risk is not a sudden crash but a slow, predictable, index-driven outflow effect. This gradual, widespread impact will slowly alter liquidity distribution and relative valuation relationships.

Capital Competition in the Crypto Market: From Narrative Competition to Genuine Outflows

The crypto market cannot exist independently of this macro capital wave. Data on capital flows at the end of Q2 2026 show that AI narratives have already manifested as quantifiable capital outflows from crypto.

In the first week of June 2026, four major semiconductor ETFs recorded a combined net inflow of about $3 billion, with a total inflow of approximately $21 billion year-to-date. Meanwhile, BlackRock’s Bitcoin ETF has experienced nearly $2 billion in net outflows since May 20. The overlapping timing—SpaceX’s roadshow launch and continuous outflows from Bitcoin ETFs—suggests that some investors are withdrawing from volatile crypto assets and reallocating to AI themes and public markets.

This capital shift is not merely short-term speculation but driven by structural shifts in risk preferences. Years ago, “risk appetite” was almost synonymous with crypto allocation, but now more compelling alternatives have emerged. Stocks related to AI infrastructure continue to strengthen, and the listing of companies like SpaceX, Anthropic, and OpenAI is attracting speculative capital. A Reuters report summarized this phenomenon as: investors prioritize short-term equity opportunities over crypto exposure, with the surge in tech enthusiasm contrasting sharply with declining digital asset appeal.

For the crypto market, the more critical variable is not the capital withdrawal on IPO day but the medium- to long-term risk preference transmission driven by the “leakage pressure” framework. When stock market volatility increases due to ongoing rebalancing, combined with macro liquidity pressures, investors tend to reduce exposure to high-beta assets, which could lead cryptocurrencies to remain range-bound over longer periods rather than breaking out unilaterally. Although Arnott himself has not directly analyzed crypto markets, the macro risk transmission logic applies. Notably, one of the main reasons for capital outflows from crypto now is the attractiveness of AI narratives as substitutes; once multiple mega-IPOs land and this narrative effect diminishes marginally, whether crypto assets will see capital inflows depends on external variables like interest rate expectations and regulatory developments.

Empirically, these two asset classes do show some observable substitution effects. But it’s crucial to clarify that the substitution mainly occurs at the risk appetite level, not in total capital volume. For example, recent outflows from Bitcoin ETFs are around $2 billion, while the new stock supply from SpaceX alone is roughly $74 billion—orders of magnitude apart. This indicates that the impact on crypto is primarily marginal—AI IPOs create a direct diversion for the most risk-seeking, short-term beta chasing capital, but do not fundamentally alter the overall capital stock in the crypto market.

Historical Reference and Boundary of Projections

Comparing the current window with historical experience helps calibrate expectations but must avoid oversimplified analogies. A common narrative is that major stock crashes in history are associated with concentrated mega-IPOs. Such correlations often overlook the time scale and causality direction. A more precise historical reference is the IPO boom during 1999–2000 internet bubble, but two fundamental differences exist: first, the revenue base of leading AI companies today far exceeds that of internet firms in 2000—Anthropic’s annualized revenue surpasses $47 billion, whereas Amazon’s revenue then was only about $2.8 billion, indicating a different maturity level; second, Arnott points out that passive investment share has risen from 10% to 50%, fundamentally changing market mechanics.

Thus, from historical analysis, several relatively certain judgments can be distilled: first, massive supply appearing after IPOs will attract passive fund inflows into included stocks, but this is at the expense of other components’ outflows, not net new capital; second, initial float percentages are usually low, making short-term shocks manageable, but medium- to long-term pressures grow as lock-up expirations and secondary offerings release more shares; third, capital competition across sectors is not linear—“AI” is a framework, with sub-sectors like infrastructure, applications, hardware, etc., further redistributing funds.

Conclusion

The concentrated IPOs of Anthropic, OpenAI, and SpaceX are not isolated market events but markers of the AI industry’s transition from primary market financing to secondary market valuation. Arnott’s “leakage pressure” framework offers an effective analytical tool: the real market impact is not the brief volatility on IPO day but the repeated, multi-year, gradually spreading structural liquidity pressures driven by index rebalancing. For traditional equity markets, this implies a re-pricing of the relative relationships between large-cap leaders and small/mid-cap stocks. For the crypto market, the influence mainly propagates through risk appetite—when market attention to AI equity assets reaches historic highs, crypto, as the highest-risk, most beta-sensitive asset class, faces direct competition.

For investors, the core strategy is not simply “buy AI” or “withdraw from crypto,” but understanding the flow logic across asset classes and sectors, monitoring rebalancing points, and viewing the IPO wave as a dynamic, ongoing process—rather than a one-off market event.