10 Stocks Drive 70% of S&P Gains: The "Underwater Bear Market" and Fragile AI Supply Chain Beneath the Illusion of Prosperity

The apparent prosperity of the S&P 500 index is masking the most extreme structural rifts within U.S. equities in nearly a quarter of a century.

According to the latest research report by Charlie McElligott, Cross-Asset Strategy Chief at Nomura Securities, and data compiled by The Kobeissi Letter, since the S&P 500 index cumulative gained 23% on March 30, a mere 10 mega-cap stocks have accounted for up to 70% of the broader market's gains, while the remaining 490 constituents contributed a meager 30%.

On this "severely distorted" contribution ranking, semiconductor and core AI assets dominate:

• Nvidia: Accounts for 13% of the index return contribution (pulling the broad market up by 3 percentage points), firmly the #1 driver;
• Micron, Apple, Microsoft: Each contributes 9% (each pulling the broad market up by 2 percentage points);
• AMD: Contributes 8%;
• Alphabet: Contributes 7%;
• Intel and Amazon: Each contributes 5%;
• Broadcom and Meta: Each contributes 3%;
• The remaining 490 stocks combined: Contribute only 30% (collectively pulling the broad market up by 7 percentage points).

Deep Dive: From "Structural Divergence" to an "Underwater Rolling Bear Market"

The initial brief only revealed the high concentration of gains, but the Nomura Securities report further discloses a grimmer micro-ecosystem beneath the surface—"the index stagnates, while underneath it is already a rolling bear market."

1. Breadth Collapse: One-sixth of constituents have halved in value

Although the S&P 500 index is just one step away from its historical peak, the damage at the constituent level is staggering:

• 85% of constituents have retraced more than 10% from their respective historical peaks (entering technical correction);
• 59% of constituents have retraced more than 20% (entering bear market territory);
• 41% of constituents have retraced more than 30%;
• 26% of constituents have retraced more than 40%;
• As many as 17% (nearly one-sixth) of constituents have declined by over 50%.

Over the past month and a half, rate-sensitive sectors faced comprehensive sell-offs: Healthcare (-3.5%), Consumer Discretionary (-3.6%), Utilities (-4.6%), Industrials (-5.8%), Financials (-7.7%), Materials (-7.9%), and Real Estate REITs (-9.8%). Across the entire S&P 500, only TMT (Technology, Media & Telecom) and Energy sectors managed to barely post positive returns over the past month. The so-called "bull market" is actually driven almost entirely by a handful of AI darlings carrying the load alone.

1. Correlation at Unseen 25-Year Lows: Beware of a "Volmageddon" Repeat

Nomura Securities derivatives data shows that the 1-month realized correlation of the S&P 500 index has fallen to the 0.7th percentile over the past year, with implied correlation sitting at the 1.8th percentile.

Strategists at Goldman Sachs and Nomura simultaneously point out that over the past 25 years, there have been only two extreme scenarios where realized correlation dropped to such lows: once on the eve of the 2007 global financial crisis, and again during the early 2018 "Volmageddon."

The broad market's superficial low volatility (S&P 10-day actual volatility is merely 7, with recent monthly amplitude only 0.8%) is suppressed by a massive selloff in zero-days-to-expiration (0DTE) options and quantitative volatility premium strategies (QIS), creating a "market maker's positive gamma prisoner's dilemma"; however, the average volatility of constituents stands at 8.9%, causing the gap between the two to spike to 8.1 percentage points, reaching the 95th percentile over the past 30 years. The market has not eliminated risk; it has merely locked severe oscillations into individual stock levels.

Fragile Pillars: Risk of Falsehood for Genuine AI Demand

This false prosperity sustained by 10 stocks rests on a fragile assumption: that high capital expenditures (Capex) in upstream computing infrastructure can quickly spawn killer commercial returns downstream, thereby spilling over and boosting the productivity of the other 490 traditional enterprises.

However, key premises of this chain are showing cracks:

1. Rumors of OpenAI Revenue Missing Expectations: According to The Financial Times, OpenAI's actual annualized revenue is approximately $20 billion, falling short by over $50 billion from the nearly $70 billion projection previously pitched to investors. This directly undermines the realization logic behind the high valuations of hardware suppliers like Nvidia, Broadcom, and Micron.
2. Chain Reaction of European Energy and Interest Rate Volatility: The structural shortage of European diesel refining capacity (Crack Spread) highly resonates with one-year interest rate volatility in the Eurozone. Macroeconomic rates maintaining sticky "higher for longer" dynamics drive up borrowing costs for traditional non-AI industries, continuing to pressure valuations.

When capital stakes everything on Nvidia and the top 10 stocks, market call skew has been pushed to a historical extreme of 99.6%—almost nobody is buying downside hedge protection, and all institutions fear missing out (FOMO). This trend, lacking breadth support and extremely one-sidedly crowded, often means that the moment the leading stocks' earnings reports or core narratives show even the slightest crack, fragility at the broad market index level will be multiplied exponentially.

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