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NewsStructural3 min readDisconfirmAI Editorial

Marks Memo: AI's Concentrated Dependence on Stock and Bond Markets Is Eroding Diversification Assumptions

In his latest memo, Howard Marks argues that artificial intelligence has created a simultaneous single-factor dependence for both equity and bond markets—42 AI-related companies accounted for approximately two-thirds of the S&P 500's gains since January 2024, while AI-related debt issuance reached $600 billion. This level of concentration undermines the cornerstone of modern investing: sufficient diversification, leaving all investors, not just those in AI, exposed to systemic fragility.

2026-11-11 16:00 GMT+8

In a memo published on November 11, 2026, Howard Marks presents an argument distinct from common discussions on AI investment: the issue is not whether AI itself is overvalued, but rather that AI has simultaneously become the single point of dependence for both the stock market and the bond market. This degree of concentration is unprecedented in history, and what it erodes is precisely the fundamental premise upon which investors rely to manage risk.

On the equity side, Marks cites J.P. Morgan data indicating that since January 2024, 42 AI-related companies have contributed approximately two-thirds of the price gains in the S&P 500. FactSet reports further show that Alphabet and Amazon alone generated combined book gains of $151 billion in the second quarter from equity investments in Anthropic and SpaceX (which now includes xAI), making them primary contributors to S&P 500 earnings. For 14 consecutive quarters, the "Magnificent Seven"—predominantly hyperscale cloud service providers—have seen their earnings growth outpace that of the rest of the S&P 500 constituents.

On the credit side, according to Goldman Sachs, global debt issuance related to AI this year has approached $600 billion, with approximately $400 billion flowing into the U.S. investment-grade bond market. This represents more than one-fifth of the total supply in that market, raising the share of AI-related bonds in the Bloomberg USD Investment Grade Corporate Index to approximately 12%. Marks points out that the AI industry may require an average of $1 trillion in new capital annually in the future, with hundreds of billions of that amount likely to be raised through debt financing.

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This trend toward concentration stands in sharp contrast to the principle of diversification. Marks cites Michael Milken’s pioneering of the sub-investment-grade debt market in 1977-78 as an example, noting that the market accepted risk on the premise of sufficient diversification to ensure that a few defaults would not undermine overall portfolio performance. However, current stock and bond markets are highly dependent on a single factor: the success of AI.

Marks further questions the predictability of AI. Citing an assessment by Claude, he notes that the overall predictability score for AI is only 3 out of 10, with core variables of interest to investors—profit size, distribution patterns, and speed of realization—scoring as low as 2. He specifically mentions that although frontier AI labs such as OpenAI and Anthropic are regarded as industry leaders, their predictability scores are comparable to early-stage venture capital, falling into the category of 'practically unknowable.'

Marks believes this concentrated dependence constitutes a 'fault line' running through portfolios, with potential impacts far exceeding the AI sector itself. He reminds investors that in areas of extreme uncertainty, accepting 'that you do not know everything' is necessary. He concludes by quoting Warren Buffett from 1979: The future is never clear, and uncertainty is actually the friend of the long-term value buyer.

Sources

  • oaktreecapital.comOaktree Capital↗
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