Author: Shenchao TechFlow
10 stocks drove 70% of the S&P's gains: The "underwater bear market" and fragile AI supply chain beneath the surface of false prosperity
According to the latest research report by Charlie McElligott, Head of Cross-Asset Strategy at Nomura Securities, and data compiled by The Kobeissi Letter, since the S&P 500 rose 23% on March 30, just 10 mega-cap stocks accounted for 70% of the entire index’s gain, while the remaining 490 components contributed only 30%.
On this highly distorted contribution ranking, semiconductor and AI core assets dominate:
Nvidia: Accounts for 13% of the index's return contribution (driving the market up by 3 percentage points), firmly holding the top position as the primary engine;
Micron, Apple, Microsoft: each contributed 9% (each pulling the market up by 2 percentage points);
AMD: contributes 8%;
Alphabet (Google): contributed 7%;
Intel and Amazon: each contribute 5%;
Broadcom and Meta: each contribute 3%;
The remaining 490 stocks combined: contributed only 30% (collectively driving the market up by 7 percentage points).
Incremental penetration: From "structural divergence" to "underwater rolling bear market"
The original news brief only revealed the concentration of gains, but the Nomura Securities report further exposed a more severe micro-ecosystem beneath the surface—“the index has stalled, while beneath the surface, a rolling bear market has already taken hold.”
Broad-based collapse: One-sixth of the components have halved in value
Although the S&P 500 is just one step away from its all-time high, the damage at the component stock level is striking:
85% of the component stocks have declined more than 10% from their respective all-time highs (entering a technical correction);
59% of the component stocks have declined by more than 20% (entering bear market territory);
41% of the component stocks have declined by more than 30%;
26% of the component stocks have declined more than 40%;
Even 17% (nearly one-sixth) of the component stocks declined by more than 50%.
Over the past one and a half months, interest-rate-sensitive sectors have experienced broad 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, and telecommunications) and energy have barely posted positive returns over the past month. The so-called “bull market” has been driven almost entirely by a handful of AI favorites.
25-year low correlation: Beware of a repeat of the "volatility apocalypse"
Nomura Securities derivatives data shows that the 1-month realized correlation of the S&P 500 has fallen to the 0.7th percentile over the past year, while implied correlation is at the 1.8th percentile.
Analysts from Goldman Sachs and Nomura simultaneously noted that in the past 25 years, extreme scenarios in which correlation dropped to such low levels have occurred only twice: once just before the global financial crisis in 2007, and again in early 2018 during the “Volmageddon.”
The apparent low volatility of the broader market (S&P 10-day realized volatility at just 7, with a monthly range of only 0.8%) is being suppressed by a “market maker positive gamma trap” driven by massive selling of same-day expiring (0DTE) options and quantitative implied volatility premium strategies (QIS); however, the average volatility of constituent stocks is as high as 8.9%, creating a gap of 8.1 percentage points—the highest in the 95th percentile over the past 30 years. Risk has not been eliminated; it has simply been confined to individual stocks.
Fragile pillar: The real demand for AI faces falsification risk
This artificial prosperity, sustained by ten stocks, rests on a fragile assumption: that high capital expenditures (Capex) in upstream computing infrastructure will rapidly generate blockbuster commercial returns downstream, which then spill over and boost the productivity of the remaining 490 traditional companies.
However, the key premise of this chain is beginning to show cracks:
Rumors of OpenAI's revenue falling short of expectations: According to the Financial Times, OpenAI's actual annualized revenue is approximately $20 billion, a gap of over $500 billion compared to the nearly $70 billion previously projected to investors. This directly undermines the valuation rationale for hardware suppliers such as NVIDIA, Broadcom, and Micron.
Chain reaction of European energy and interest rate volatility: Structural shortages in European diesel refining capacity (Crack Spread) are highly correlated with one-year interest rate volatility in the eurozone. Persistent macroeconomic interest rates maintained at a “higher for longer” level continue to elevate borrowing costs for traditional non-AI industries, keeping valuations under pressure.
When capital has bet all its chips on the top 10 stocks, such as NVIDIA, the market's call skew has been pushed to a historical extreme of 99.6%—almost no one is buying downside hedging protection, and all institutions fear missing out. This one-sided, overcrowded move, lacking broad-based support, often means that even the slightest crack in the earnings or core narrative of the leading stocks will exponentially amplify fragility at the broader index level.
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