Structural divergence intensifies behind AI boom: 59% of S&P technology stocks have entered bear market territory.

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Internal fractures in AI trading are widening. What appears on the surface as Wall Street’s “momentum factor unwind” is, in essence, a hidden correction in the AI sector—a correction whose intensity and speed have reached levels not seen since the COVID-19 pandemic.

According to Goldman Sachs data, its momentum pair portfolio has fallen 27% from its peak on June 22, with a five-day decline in magnitude and speed unmatched since the pandemic.

Meanwhile, among S&P 500 technology stocks, 59% have dropped more than 20% from their highs of the past 252 trading days—according to the standard definition, entering bear market territory. This figure reveals a key reality: the prosperity of the AI rally is highly concentrated in a few leading names, with many tech stocks already left behind.

Semiconductor stocks are also displaying technical warning signals—the Philadelphia Semiconductor Index constituents have broken below their 50-day moving average for the first time since April this year. UBS trading desk characterizes the current trend as “controlled risk reduction” rather than panic selling, believing this round of correction is primarily driven by systematic factor flows. Investors are actively cutting high-beta, high-consensus long positions after catalysts for disappointment appear and before key supply events arrive.

Momentum Equals AI: A Misread Sector Correction

Wall Street’s attribution of recent volatility to momentum factor unwinding masks deeper structural issues. According to Goldman Sachs Marquee platform data, the correlation between momentum factors and AI trades exceeds 95%, making the two nearly identical.

This means that the dramatic fluctuations in momentum factors essentially reflect concentrated exposure in AI holdings—longing AI winners and shorting software stocks seen as AI losers form the mainstream factor structure in today’s market. Goldman Sachs Prime data shows momentum factor exposure has significantly retreated from its peak and now sits at the 60th percentile of the past year.

Historical data from Morgan Stanley’s Quantitative and Derivatives Strategy team shows this momentum drawdown ranks seventh in magnitude over the past decade, but in terms of speed—reaching this level in just 14 days—it is the fastest on record.

AI Volatility Surges, Disconnected From Broader Market

Goldman Sachs data shows volatility in momentum factors (i.e., AI trades) has climbed to its highest level since the pandemic, while overall S&P 500 volatility remains moderate. This divergence indicates that current stress is highly concentrated within AI-related holdings and has not yet spread to the broader market.

UBS trading desk’s assessment supports this observation, noting that the current selloff displays “controlled risk reduction” characteristics, primarily driven by systemic and factor flows. Core pressure is focused on crowded exposures to AI, semiconductors, and memory, rather than across-the-board market panic.

Nonetheless, UBS retains a cautious tone—its comment that there is "no need to panic for now" implicitly signals uncertainty about future developments.

Insiders Buying Against the Trend: Historical Signals Worth Watching

While institutional investors accelerate risk reduction, tech company insiders are buying against the trend. Market data indicates a noticeable uptick in insider buying activity recently.

Historical experience suggests that active insider buying rarely coincides with major market tops, though their timing skills are not always precise. For investors searching for bottom signals, this trend may carry some reference value.

Mega Cloud Providers vs. Semiconductors: New Rotation Logic Within AI

The current market focus has shifted from "whether to continue holding AI" to "how to make structural adjustments within AI." It is reported that "long mega-scale cloud computing providers, short semiconductors" is quickly becoming Wall Street's most watched trading strategy this summer.

Behind this rotation logic is a reevaluation of AI value chain distribution—against the backdrop of questioned marginal returns on computing power investment, cloud infrastructure operators directly benefiting from AI applications are seen as having stronger earnings certainty than upstream chip makers.

With 59% of S&P tech stocks having entered bear market territory, this figure itself highlights how concentrated the AI rally is. For investors, the current market environment tests not only their belief in the long-term AI narrative but also their structural stock-picking skills as sector divergence intensifies.

Risk Warning and DisclaimerThe market carries risks; investments should be made cautiously. This article does not constitute personal investment advice, nor does it take into account the specific investment objectives, financial situation, or needs of individual users. Users should consider whether any opinions, viewpoints, or conclusions in this article are suitable for their particular circumstances. Investing based on this article is solely at your own risk. ```