Key Takeaways
- • Index funds held 53.7% of all fund assets by June 2026, surpassing actively managed funds, according to Morningstar; in U.S. stock funds the share was 63.8%.
- • The top 10 holdings of the S&P 500 now account for close to 40% of S&P 500 index fund assets, a record level, versus an average of 23% over the past 50 years.
- • Michael J. Francis, president of Francis LLC, argues that growing concentration in AI-linked mega-cap stocks has pushed S&P 500 diversification to an all-time low.
- • Francis cites the 2000-2002 tech bust as a precedent: the Dow fell 37%, the S&P 500 fell 49%, and the Nasdaq Composite fell 78%.
- • Suggested diversifiers include value index funds, equal-weight S&P 500 funds, and short-term or floating-rate bond funds.
Summary
According to Morningstar, index funds held 53.7% of all fund assets by June 2026, and 63.8% of assets in U.S. stock funds. Francis notes that market-capitalization weighting means the largest companies exert the greatest influence on index performance. The top 10 holdings of the S&P 500 have averaged 23% of fund assets over the past 50 years and now make up close to 40%, meaning roughly $40 of every $100 invested in an S&P 500 index fund goes into just 10 companies.
Francis argues that many of these top holdings are tied to a common technology and AI theme, which he says has left the S&P 500's diversification at an all-time low. He draws a historical comparison to the 2000-2002 tech bust, when the Dow, with about 12% technology exposure, fell 37%, the S&P 500, with about 33%, fell 49%, and the Nasdaq Composite, with 70%, fell 78%.
To reduce concentration, Francis suggests value index funds, which are typically underweight technology; equal-weight S&P 500 funds, which hold each company in equal proportion but carry higher rebalancing costs; and non-correlated assets such as short-term and floating-rate bond funds, which he says offer protection against rising rates. He identifies two risks to the AI investment theme: higher interest rates given the heavy borrowing needed to finance AI infrastructure, and Chinese competition that could lower the cost of computing and undercut data center economics. He concludes that investors should understand their risk exposures and adjust portfolios to a risk profile they can tolerate.
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