U.S. Equity Markets Exhibit 'One Big Trade' Characteristics; Caution Advised as Momentum Factor Nears Short-Term Peak
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U.S. Equity Markets Exhibit 'One Big Trade' Characteristics; Caution Advised as Momentum Factor Nears Short-Term Peak
The S&P 500 has reached new highs driven by AI and momentum factors, but market breadth has narrowed significantly. Historical evidence suggests such sharp momentum rallies are often followed by short-term pullbacks; investors are advised to allocate to low-sensitivity portfolios to hedge risk.
- The S&P 500 is up 10% year-to-date (YTD), with technology stocks contributing 85% of the return; excluding tech, the index is up only 3%.
- The momentum factor surged 25% over the past three months—the strongest rebound on record—and hedge fund leverage is near a five-year high.
- Historically, similar large momentum surges have typically peaked within one month and reversed over the subsequent two to three months.
- Consensus EPS estimates for the S&P 500 for both 2026 and 2027 have been revised upward by 8% YTD, primarily driven by AI capital expenditure and energy prices.
- Consumer Staples exhibits the lowest exposure to AI and momentum factors, making it well-suited as a defensive allocation within diversified portfolios.
- Low-momentum stocks have not only outperformed relatively during prior momentum reversals but also delivered positive absolute returns.
Report interpretation
Overview
This report analyzes the structural characteristics of the U.S. equity market in the first half of 2026, driven by the artificial intelligence (AI) boom. It identifies a 'One Big Trade' dynamic—namely, the S&P 500’s gains are highly concentrated in technology stocks and the momentum factor, while market breadth has narrowed markedly. Although the index continues to reach new highs, historical data suggests such sharp momentum rallies often presage near-term market weakness or reversal. Drawing on episodes since 1980, the report examines how macroeconomic context and AI investment prospects may shape future performance, and proposes constructing a 'low-sensitivity portfolio' and using low-momentum stocks as hedges.
Core views
Market Concentration and Extreme Momentum: The S&P 500 is up 10% YTD, with the TMT sector (Technology, Communication Services, Amazon, and Tesla) accounting for 85% of that return; excluding TMT, the index rose only 3%. NVIDIA alone contributed 20% of the S&P 500’s total return. Meanwhile, Goldman Sachs’ momentum factor (GSMEFMOM) surged 25% over the past three months—one of its strongest rebounds on record. Hedge funds’ aggregate leverage and net momentum exposure have also approached five-year highs, signaling elevated positioning congestion. Historical Patterns and Short-Term Risks: Since 1980, there have been 11 instances where the momentum factor rose more than 20% over three months. On average, momentum continued rising another 6% over the following month—but then declined over the next two to three months. Sharp momentum rebounds occurring when the S&P 500 is at elevated levels have often preceded sub-par returns over the ensuing months (e.g., mid-1998, late-1999, late-2021). Thus, the current macro backdrop and AI investment outlook will be pivotal in determining the trajectory of both the momentum factor and broader equity markets. Structural Divergence in Earnings Revisions: The recent surge in market momentum coincides with a spike in near-term earnings expectations. Consensus EPS estimates for the S&P 500 for both 2026 and 2027 have risen 8% YTD. However, this growth is largely attributable to higher AI infrastructure spending expectations and rising energy prices. Excluding AI infrastructure and energy companies, the S&P 500’s 2027 EPS forecast has remained flat YTD. Nonetheless, EPS revision breadth across all S&P 500 sectors turned positive over the past month, indicating broadening improvements in earnings expectations. Defensive Strategies and the 'Low-Sensitivity Portfolio': Given the market’s tight linkage to AI narratives, investors face challenges identifying non-AI-related opportunities. The report constructs a 'Low-Sensitivity Portfolio' comprising Russell 1000 constituents with positive EPS revisions and minimal sensitivity to AI trades and U.S. growth pricing. Consumer Staples exhibits the lowest exposure to both AI and momentum factors. Moreover, historical evidence shows holding low-momentum stocks is an effective hedge against momentum reversals—during past momentum collapses, these former laggards not only outperformed relatively but also delivered positive absolute returns.
Analysis framework
The report employs a hybrid methodology combining historical comparative analysis and factor decomposition. First, it quantifies the concentration of the S&P 500’s gains—i.e., the 'One Big Trade' phenomenon—by decomposing sector- and stock-level contributions to index returns. Second, using Goldman Sachs’ proprietary momentum factor (GSMEFMOM) and AI long-short baskets, it compares current market style dynamics with historical analogues (e.g., 1998, 1999, 2021), particularly focusing on post-rally behavior after sharp momentum rebounds at elevated index levels. Finally, via correlation analysis and regression screening, it constructs a 'Low-Sensitivity Portfolio' minimally correlated with AI and macro cycles, supplemented by earnings revision breadth ('Revision Breadth') to assess the breadth of fundamental support.
Methodology notes
Momentum Factor
The report uses the momentum factor to measure the return differential between the best-performing and worst-performing stocks over a given period. A sharp rise in this factor signals intense investor focus on recent winners—a hallmark of overheated sentiment and historically associated with subsequent mean reversion (reversal).
Market Breadth Analysis
Market breadth is assessed by calculating the proportion of stocks in the index trading above their 200-day moving averages. The report observes that although the index hits new highs, breadth is declining—indicating gains are driven by a narrow set of mega-cap stocks. Such divergence serves as an early warning signal of market fragility.
EPS Revision Breadth
EPS revision breadth measures the net percentage of companies raising versus lowering earnings forecasts. The report uses this metric to determine whether earnings improvements are confined to a few AI leaders or spreading across broader economic sectors—thereby gauging the fundamental health of the bull market.
Asset mapping & comparison
Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).
- NVIDIA (NVDA)Core beneficiary of the AI trade and primary driver of index gains
- Strengths
- Represents 9% of S&P 500 market cap but contributed 20% of YTD return; largest beneficiary of AI infrastructure spending
- Weaknesses
- Valuation embeds extremely high long-term growth expectations, rendering it vulnerable to sentiment reversal
- Comparison
- Exhibits the highest market influence and capital concentration among semiconductor peers
- Risks
- Slowing AI capex, momentum factor reversal
- Consumer Staples SectorCore component of the low-sensitivity portfolio, used to hedge AI- and macro-related risks
- Strengths
- Lowest sensitivity to AI trades and growth pricing; recent EPS revisions are positive
- Weaknesses
- Lower upside participation in bull markets relative to tech stocks
- Comparison
- Exhibits lower correlation with AI baskets than Energy or Consumer Discretionary
- Risks
- Deeper-than-expected consumption decline amid recession
- Low-Momentum Stock PortfolioTool to hedge momentum reversal; historically delivered absolute returns during momentum collapses
- Strengths
- Relatively low valuations, positive recent earnings revisions, and potential for catch-up gains
- Weaknesses
- May continue underperforming strong performers in the near term
- Comparison
- Complements high-momentum tech stocks
- Risks
- Persistent extreme market dispersion, prolonged marginalization of low-momentum stocks
Key data
- S&P 500 YTD Return10%As of mid-May 2026
- Tech Contribution to Return85%TMT sector (including AMZN and TSLA) accounted for the vast majority of gains
- 3-Month Momentum Factor Gain25%Goldman Sachs’ momentum factor posted a historically strong rebound
- S&P 500 EPS Forecast Upgrade8%Consensus EPS forecasts for both 2026 and 2027 upgraded 8% YTD
- NVIDIA’s Contribution to Index Return20%NVDA accounts for 9% of S&P 500 market cap but contributed 20% of YTD return
Impact & implications
The report concludes that U.S. equities have evolved into a 'One Big Trade' centered on AI and momentum factors. This extreme concentration renders markets exceptionally sensitive to shifts in macro data and AI capital expenditure trends. For investors, this implies heightened 'momentum reversal' risk should AI prospects deteriorate or macro conditions turn turbulent. Consequently, the risk-reward profile of chasing tech stocks alone is deteriorating. The report recommends maintaining core holdings while enhancing portfolio resilience—via allocations to low-sensitivity sectors like Consumer Staples or by holding low-momentum stocks with positive earnings revisions—to navigate potential volatility.
Risks
- Deterioration in AI investment outlook triggering a 'catchdown'-style momentum reversal
- Severe macro deterioration causing volatility spikes and risk aversion
- Unexpected strong macro improvement leading to rotation from winners to laggards ('catch-up' reversal)
- Continued narrowing of market breadth, amplifying the impact of individual large-cap stock volatility on the index
What to watch
- Trends in AI capital expenditure expectations
- Proportion of S&P 500 constituents trading above their 200-day moving averages (market breadth)
- Whether Goldman Sachs’ momentum factor (GSMEFMOM) peaks and begins to decline
- Relative performance of defensive sectors such as Consumer Staples
- Direction of macro growth expectations (e.g., GDP forecasts)