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Fortune AIPublished: Jul 1, 2026, 19:00 JST1 min read

Leveraged bets hit $1.4 trillion(約220兆円) as AI stocks dominate risky borrowing

Leveraged bets hit $1.4 trillion(約220兆円) as AI stocks dominate risky borrowing

Key takeaway

  • Investors have borrowed about $1.4 trillion(約220兆円) to amplify their stock bets, with leverage concentrated heavily in AI companies.

  • This creates market risk because forced sales to cover losses could trigger sharp declines across equities.

  • Goldman Sachs warns that Japanese margin borrowing has also hit its highest level since the 2008 financial crisis.

3 Key Points

  1. What happened

    Net margin borrowing in U.S. equities has reached about $1.4 trillion(約220兆円), equivalent to 1.8% of all U.S. stocks, according to Goldman Sachs analysts. Investors are using borrowed money to magnify their bets. Separately, margin purchases of Japanese equities have climbed above $30 billion(約4.8兆円), the highest level since the Great Financial Crisis.

  2. Why it matters

    When leveraged traders are forced to cover losing bets, they must sell other stocks to raise cash, which can magnify selling pressure across markets. Goldman Sachs notes that investor leverage remains very concentrated in the AI ecosystem, creating concentration risk. This matters because a sharp move against AI stocks could trigger broader market stress.

  3. What to watch

    The stability of AI-focused positions and whether margin calls in that sector spill into broader equity selloffs. The article also highlights that the Magnificent Seven tech stocks have underperformed the S&P 500 so far this year, suggesting some cooling in the rally that has driven much of the leverage buildup.

Ask the AI about this article →

FAQ

How much is borrowed and what does it represent?
Net margin borrowing is at about $1.4 trillion(約220兆円), which is equivalent to 1.8% of all U.S. stocks.
Why is concentrated leverage in AI specifically a problem?
If AI stocks decline sharply, leveraged investors may be forced to sell other holdings to cover losses, amplifying selling pressure across the broader market and triggering stress beyond the AI sector alone.

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