When Will AI Trading Bottom Out? The Market Eyes the "Prisoner's Dilemma" Behind Meta's "Massive Bond Issuance"

Over the past week, AI trades have faced a fresh round of sell-off pressure, while both the U.S. stock and bond markets have come under simultaneous stress. Nasdaq saw its worst single-day performance in months, U.S. high-yield bond risk premiums climbed to a 17-month high, and CCC-rated junk bond yields spiked to their highest level since 2020. While major stock indices saw limited surface volatility, risk repricing in underlying assets has accelerated.

One of the main sources of market concern is Meta’s announcement of a massive financing plan following its Q3 results. According to a research report released by Barclays on October 23, Meta chose to raise funds ahead of time partly because other companies in the AI ecosystem have already started or plan to start fundraising, and the capital market’s absorption capacity is becoming increasingly constrained.

This reveals the “prisoner's dilemma” faced by AI giants: each company is motivated to be the first to raise capital, but if all large players speed up bond issuance, the resulting surge in supply could push up financing costs and ultimately squeeze all participants’ capacity to raise funds. At the same time, hedge funds are continuously deleveraging, while credit spreads among AI-related assets are widening as well.

Therefore, when AI trades will find a bottom depends not only on the profitability of tech giants, but also on the market’s ability to absorb a dense stream of bond issuance and whether the persistently rising financing costs will further impact the AI industry chain.

Indices Remain Calm on the Surface While AI Positions Face Mass Liquidation

Over the past week, headline index moves masked violent divergences among individual stocks. Goldman Sachs data shows that its long-short basket of AI beneficiaries and risk stocks has fallen about 55% from the June highs, giving back all year-to-date gains; momentum strategies also saw a sharp pullback, plunging to their most extreme levels since the 2008 financial crisis.

On Thursday, the S&P 500 Index fell 1.2%, though 335 constituent stocks still posted gains; the equal-weighted S&P 500 Index rose by 0.7%, but the market cap-weighted SPY closed lower. According to Goldman Sachs, hedge funds deleveraged on seven out of the last eight trading days, and Thursday’s sell-off was entirely driven by long position unwinding.

This indicates that the recent adjustment is not just a reevaluation of AI valuations but also a concentrated clearing of crowded positions. Whether this position adjustment can bring about a sustained rebound still depends on whether credit market stress will ease.

Credit Risk Concentrates on Lower-Rated Borrowers

According to Bloomberg, the average risk premium for U.S. high-yield bonds has risen to a 17-month high, while the primary market saw the largest wave of deal withdrawals this year; CCC-rated junk bond yields climbed to 15.85%, a new high since 2020, and the yield spread with BB-rated bonds is nearing the peaks seen in 2016 and 2020.

The leveraged loan market is also under pressure. The volume of deeply distressed loans trading below 60 cents on the dollar has risen to its highest level since March 2020. JPMorgan data shows that in the past 12 months, the volume of loans trading at or below 80 cents on the dollar has surged by nearly 90%.

Notably, while CCC bond spreads have widened substantially, the overall credit market has not simultaneously deteriorated, indicating risks are being concentrated among issuers with weaker debt-servicing capabilities. Robert Cohen, Director of Corporate Credit at DoubleLine Capital, pointed out that some CCC-rated borrowers may face debt restructuring, but this does not signal a reversal of the entire credit cycle.

Goldman Sachs data shows that across investment grade, high-yield credit derivatives, and lower-rated cash bonds, spreads in various rating segments have all reached cyclical highs. R. Lakshmanan, Head of Asia-Pacific Corporate Credit at CreditSights Singapore, believes that after a series of global risks impacting the market, a trend of sustained credit repricing is gradually taking shape.

Meta's Bond Issuance Highlights AI Funding "Prisoner's Dilemma"

Meta’s fundraising plan puts the contradiction between AI capital expenditures and credit market supply into the spotlight. The company has narrowed its capex guidance for 2026 to between $135 billion and $145 billion, expects fourth quarter spending to reach $49 billion to $59 billion, and, post-dividends, free cash flow has turned negative. Management also expects to raise tens of billions of dollars starting from this fall.

Barclays noted in its report that while revenue growth among mega-cap tech companies is materializing, capital expenditures continue to rise, shifting the financing issue from “Can we raise funds?” to “When to raise, how much to raise, and what method to use.”

In its filings, Meta mentioned that since other companies in the AI ecosystem have already started or plan to start raising funds, the capital market’s ability to absorb new supply is becoming increasingly limited, thus making early fundraising a practical necessity.

However, when all companies rush to raise funds, individually rational decisions can translate into overall market pressure: a wave of new bond supply floods the market, pushes up issuance costs, and restricts the narrowing of credit spreads. To avoid excessive leverage hurting credit ratings, companies are also considering equity financing, convertible bonds, asset-backed securities (ABS), and off-balance-sheet financing channels.

Barclays believes that the supply of AI-related funding will continue to limit the space for credit spread compression in the short term.

AI Credit Divergence Intensifies, Market Shifts to Single-Bond Pricing

Barclays estimates the scale of AI-related credit assets at about $680 billion, spanning mega-cap tech companies, semiconductors, data centers, and hardware firms. These assets account for roughly 7.5% of the investment-grade bond index market value yet contribute about 13% of the index’s duration risk (DTS).

Overall, the spread premium for AI credit assets relative to the investment grade index is about 35 basis points, with bonds longer than 10 years seeing a premium as high as 55 basis points. At the same time, the one-year dispersion in credit spreads among AI issuers has risen from 24 to 65 basis points; even after excluding Oracle and data center segments, this measure still climbed about 60% to 37 basis points.

Since mid-September, the credit spread widening for Oracle, Meta, SpaceX, and a number of data center operators has significantly outstripped the index, while short-duration bonds for Microsoft, Google, and Amazon have proved relatively resilient.The market has begun to differentiate based on issuers’ financing needs, balance sheets, and long-term risks, rather than treating AI as a homogenous credit theme.

The yield curve also reflects pressure at the long end. Barclays’ data shows that in the past year, the average 2-5 year, 5-10 year, and 10-30 year yield curves for mega-cap tech companies have steepened by 137%, 140%, and 68% respectively. Among them, Meta’s 10-30 year curve spread reached 68 basis points, the steepest among its peers.

A steeper long-end curve reflects increased risk compensation demanded by investors for long-term debt. As AI companies continue to ramp up capital expenditures, the market must judge not only whether investments will translate into revenues, but also assess financing scale, improvements in cash flow timelines, and the impact of new bond issues on financing costs.

Therefore, whether AI trades can find a bottom hinges on the market’s ability to digest massive new fundraising, whether credit spreads can stabilize, and if risk differentiation among AI firms continues to expand. Until these pressures ease, periodic rebounds will remain capped by rising financing costs.