US stocks hit new highs 14 times within a month, momentum stocks soared, Goldman Sachs revisited a 40-year history: similar market conditions usually pull back after about a month

The wave of AI is pushing the U.S. stock market toward a highly concentrated one-sided rally. The S&P 500 index has hit 14 new all-time highs in the past month, with a year-to-date increase of 10%, but this rally has been almost entirely driven by technology and AI-related stocks, with market breadth narrowing to one of the lowest levels in decades.

According to Windy Trading Platform, Goldman Sachs’s weekly U.S. stock strategy report released on May 15 states that the TMT sector, centered on technology, media, Amazon, and Tesla, contributed 85% of the S&P 500’s gains this year; excluding TMT, the index only rose 3%. Nvidia accounts for about 9% of the S&P 500 market cap but contributed 20% of the index’s total return this year. Meanwhile, Goldman Sachs’s momentum factor (GSMEFMOM) surged 25% over the past three months, marking one of the strongest gains on record, with hedge funds’ total leverage and net exposure to momentum factors approaching five-year highs.

Goldman Sachs warns that since 1980, similar momentum surges of this magnitude have occurred 11 times, after which the momentum factor typically peaks and declines about a month later. When the S&P 500 is near high levels, such momentum surges often signal below-average returns in the following months. Goldman Sachs maintains a year-end target of 7,600 points for the S&P 500, implying only about 1% upside from current levels.

Market Concentration Hits Extreme Levels, “One Big Trade” Dominates

The structural features of the current U.S. stock market have attracted widespread attention. Goldman Sachs’s report points out that while the S&P 500 has hit 14 new highs in the past month, the proportion of stocks trading above their 200-day moving averages within the index has continued to decline. Currently, the median stock in the S&P 500 is about 13% below its 52-week high, with market breadth compressed to one of the narrowest levels in decades.

The core driver of this pattern is AI trading. The information technology sector has contributed approximately 659 basis points to the S&P 500’s gain this year, accounting for 66% of total returns; communication services contributed 132 basis points, or 13%. The top ten contributing stocks collectively accounted for 84% of the index’s gains this year, led by Nvidia, Google, Micron, and Broadcom.

Several fund managers told Goldman Sachs that, in the current market environment, it is extremely difficult to find investment opportunities unrelated to AI themes. Goldman Sachs characterizes this phenomenon as a “One Big Trade” — the market is no longer a “collection of stocks,” but a highly homogeneous, directional bet centered around AI.

Historical Patterns of Momentum Surges: Short-term Continuation, Mid-term Pressure

Goldman Sachs’s systematic study of momentum factor trends since 1980 shows that the current situation closely resembles 11 comparable historical scenarios. In these cases, after the momentum factor gains 20% or more within three months, it usually continues for about another month, averaging an additional 6% increase, before turning downward over the next two to three months.

For the overall S&P 500, when a momentum surge occurs near high levels, subsequent returns tend to be weak. Data shows that in five instances when the S&P 500 was within 5% of its all-time high at the time of a momentum surge, median returns after 1 month and 3 months were -0% and -0%, with only a 20%–40% probability of positive returns. In contrast, when momentum surges occur when the index is at low levels, the median returns over the next 3 to 6 months exceed 8%.

The most comparable historical cases include mid-1998, late 1999, mid-2015, and late 2021. Goldman Sachs believes that macroeconomic trends and AI investment prospects will be key variables determining the future trajectory of the momentum factor and the broader market. An unexpected reversal in AI investment sentiment or a sharp deterioration in macro conditions could trigger a “downward correction” in momentum; conversely, an unexpected macroeconomic improvement could lead to a “catch-up rally” in lagging stocks.

Earnings Upgrades Support the Rally, but Structural Divergence Is Clear

Unlike the bubble-like rallies of the late 1990s or 2021, Goldman Sachs points out that this rally is supported by certain earnings fundamentals. Since the beginning of the year, the consensus estimates for the S&P 500’s EPS in 2026 and 2027 have been upwardly revised by 8% each.

The main sources of upward revisions are highly concentrated: EPS estimates for AI infrastructure-related stocks in 2027 have been cumulatively increased by about 32% this year; the energy sector has been revised upward by about 19%. Excluding these two categories, the 2027 EPS estimate for the S&P 500 has nearly flatlined. However, Goldman notes that this sideways movement is better than typical downward revisions, and in the past month, EPS revision breadth across all sectors has been positive, with more upward than downward revisions.

At the industry level, recent stock price performance generally aligns with EPS revisions, but there are notable divergences. The energy sector’s 2027 EPS estimate was raised about 26% before the war, yet the sector’s year-to-date gain is only about 4%. Conversely, the semiconductor sector’s stock prices have significantly outpaced earnings revisions, which Goldman attributes partly to technical factors like leveraged ETF inflows and market expectations of long-term profit growth exceeding analyst forecasts.

How Investors Should Respond: Diversification and Hedging with Low-Momentum Stocks

In the face of a highly concentrated AI momentum rally, Goldman Sachs offers two strategies for investors.

First, hold some low-momentum stocks as a hedge. Goldman’s research on the most intense momentum reversals over the past 100 years shows that in these scenarios, lagging stocks (i.e., low-momentum stocks) not only outperform relatively but also achieve absolute positive returns. Goldman has selected 25 S&P 500 constituents currently at the low end of the momentum factor but with recent upward EPS revisions, for investors’ reference.

Second, construct an “Insensitive Portfolio.” Goldman has screened stocks from the Russell 1000 index that are least sensitive to AI trading and U.S. economic growth expectations, while also having positive EPS revisions. Over the past year, these stocks’ AI and economic growth factors explained only 13% of their median daily return variation, far below the 30% for median Russell 1000 stocks. The selected stocks include multiple from energy, consumer staples, healthcare sectors, with a median market cap of about $25 billion and a forward P/E ratio of roughly 17.

On sector allocation, Goldman notes that consumer staples are the least correlated with AI and momentum factors, while healthcare and REITs have only mild negative correlations. Given the potential for economic slowdown in the coming quarters, holding defensive sectors with limited sensitivity to AI could be attractive for diversification.

All the above insights are from Windy Trading Platform.

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