AI and Momentum Have Become the Same Big Trade in U.S. Equities

Overview

This Goldman Sachs U.S. weekly strategy report focuses on the AI trade, the Momentum factor, and the concentrated rally in the S&P 500. The report notes that the recent record highs in U.S. equities have been driven primarily by AI-related stocks, TMT, and a small number of large-weight names, while market breadth has actually weakened. Many portfolio managers worry that the current market looks less like a diversified stock market and more like a single large trade driven jointly by AI and Momentum.

Core views

The report's key views are: First, the AI trade remains the main driver of U.S. equity gains, with the S&P 500 up about 10% year to date, TMT contributing about 85%, and NVDA alone contributing about 20% of the index return. Second, the Momentum factor has risen by about 25% over the past three months, with its long side concentrated in Semiconductors, Tech Hardware, AI-infrastructure-related Capital Goods, Energy, and Transportation, while its short side includes software and business services companies hurt by concerns about AI disruption; as a result, Momentum and the AI basket are highly linked in performance. Third, history shows that similar sharp Momentum rallies often continue in the near term, but are more likely to fade over the following two to three months; if the surge occurs when the index is already near highs, S&P 500 returns over the next three to six months are usually weaker. Fourth, unlike the late 1990s or 2021, the current rally is supported by real earnings estimate upgrades, but those upgrades are highly concentrated. Fifth, investors should continue looking for earnings growth and positive earnings revisions while reducing reliance on a single AI/Momentum theme.

Analysis framework

The report combines historical event studies, factor performance, sector earnings revisions, market breadth, portfolio correlation, and theme basket performance. Goldman Sachs compares 11 historical episodes since 1980 in which the Momentum factor rose by more than 20% over three months, and distinguishes between periods when the S&P 500 is near highs and periods when it is not; it also uses the GS AI long-short basket, the Momentum factor, equal-weight sector excess returns, the EPS revision factor, and Russell 1000 stock screens to identify investment opportunities with lower sensitivity to AI and growth pricing but positive earnings revisions.

Methodology notes

• Factor analysisMomentum factor

  GSMEFMOM

  This factor is an equal-weighted long-short portfolio that compares the performance of the top and bottom quintiles of S&P 500 stocks ranked by trailing 12-month returns, and is used to measure the market's preference for trend continuation.

• Theme basketAI basket pair

  GSTMTAIP vs. GSTMTAIR

  The report uses GS AI long-short basket pairs to measure stock or sector sensitivity to the AI trade and to observe how closely they move with the Momentum factor.

• Earnings revisionsTwo-year forward EPS revisions

  Consensus EPS revisions for 2026 and 2027

  The report judges whether fundamentals support recent price performance by looking at upward or downward revisions to consensus EPS estimates, and compares sector returns with the magnitude of 2027 EPS revisions.

• Risk diversificationInsensitive Portfolio screening

  Stocks with low sensitivity to AI and growth pricing

  The report screens Russell 1000 stocks with positive recent EPS revisions and the lowest sensitivity to AI trade and U.S. growth pricing in order to find allocation opportunities that do not rely entirely on the AI theme.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• S&P 500

  The core market vehicle for the AI and Momentum theme

  Strengths

  The index continues to hit new highs, and consensus EPS estimates for both 2026 and 2027 have been revised upward, with some of the earnings revisions backed by fundamentals.

  Weaknesses

  The contribution to gains is highly concentrated; returns excluding TMT are much weaker, and the median constituent remains about 13% below its 52-week high.

  Comparison

  When the S&P 500 is near highs and experiences a Momentum surge, subsequent three- to six-month returns have historically been weaker than in periods when the index is not near highs.

  Risks

  AI expectations roll over, market breadth keeps narrowing, rates or volatility rise, or crowded positions are de-risked.

• AI-infrastructure-related stocks

  An important source of this round of earnings upgrades and market Momentum

  Strengths

  Rising AI-capex expectations have driven meaningful EPS upgrades for related companies, with Semiconductors and Tech Hardware standing out.

  Weaknesses

  Valuation and price may already be discounting longer-term growth, and short-term earnings revisions may not fully explain the size of the price move.

  Comparison

  AI-infrastructure stocks have seen 2027 EPS estimates revised up by about 32% year to date, far above the S&P 500 average of about 8%.

  Risks

  A slowdown in the AI investment cycle, downward revisions to capex expectations, a reversal in capital flows, or regulatory and supply-chain constraints.

• Momentum factor

  A trend factor highly synchronized with the AI trade

  Strengths

  Up about 25% over the past three months, and historical patterns suggest that similar surges can continue for another month in the short term.

  Weaknesses

  Positioning and exposure are near five-year highs, and history shows that sharp surges are often followed by weakness over the next two to three months.

  Comparison

  The current Momentum long side tilts toward Semiconductors, Tech Hardware, AI-infrastructure Capital Goods, and Energy, while the short side includes software and business services names exposed to AI disruption concerns.

  Risks

  A pullback in the AI trade, rising macro volatility, catch-up moves by laggards, or risk reduction by leveraged investors.

• Consumer Staples

  A defensive sector with low sensitivity to AI and Momentum

  Strengths

  The report views this sector as one of the least exposed to AI and Momentum currently, and as having defensive allocation value if the probability of an economic slowdown rises.

  Weaknesses

  If the market continues to favor AI and high-Momentum names, Consumer Staples may underperform on a relative basis.

  Comparison

  Energy and Consumer Discretionary also show low AI exposure, but they are more closely tied to geopolitical or macro factors; Health Care and Real Estate show only modest negative correlation.

  Risks

  Changes in interest rates, shifts in consumer demand, or a continued rise in risk appetite that leaves defensive sectors out of favor.

• Energy

  A sector with strong EPS revisions but relatively weak stock performance

  Strengths

  Its 2027 EPS estimates have been revised up the most among sectors, with the report noting an increase of roughly 26% since before the war.

  Weaknesses

  Corresponding sector returns are only about 4%, clearly lagging the magnitude of the earnings revisions.

  Comparison

  Unlike Semiconductors, Energy has strong earnings revisions but weaker price response; Semiconductors, by contrast, have seen price gains that exceed recent earnings revisions.

  Risks

  Energy price volatility, changes in the geopolitical path, or the market's unwillingness to pay a higher valuation for cyclical earnings upgrades.

• Low-Momentum stocks with positive earnings revisions

  A potential hedge tool for AI-trade participants against a Momentum reversal

  Strengths

  Historical research shows that in the sharpest Momentum reversals, the prior laggards not only outperform relatively but also rise in absolute price terms.

  Weaknesses

  If Momentum continues to surge, low-Momentum stocks may keep lagging in the near term.

  Comparison

  The report highlights 25 current Momentum short names that also have positive 2026 and 2027 EPS revisions as candidates.

  Risks

  Earnings revisions may not materialize, the market may continue to favor high-Momentum leaders, and stock-specific fundamentals may remain highly dispersed.

Key data

• S&P 500 year-to-date returnAbout 10%Performance year to date as of the Thursday referenced in the report.
• TMT contribution to S&P 500 year-to-date returnAbout 85%TMT includes Information Technology, Communication Services, AMZN, and TSLA.
• S&P 500 return excluding TMTAbout 3%Shows how concentrated the index advance has been.
• NVDA contribution to S&P 500 year-to-date returnAbout 20%NVDA's market-cap weight in the S&P 500 is about 9%.
• Number of S&P 500 new highs in the past month14 timesOccurred alongside weakening market breadth.
• Median S&P 500 constituent distance from 52-week highAbout -13%Reflects stock-level dispersion beneath the index highs.
• Three-month Momentum factor gainAbout 25%One of the strongest three-month surges in history.
• Number of comparable historical Momentum surges11 timesIndependent three-month Momentum gains of more than 20% since 1980.
• Average one-month follow-through after comparable historical eventsAbout 6%The report notes that the current gain already exceeds that historical average follow-through.
• Year-to-date revisions to S&P 500 2026 and 2027 EPS consensusUp about 8% eachDriven mainly by AI-capex-related companies and Energy.
• S&P 500 2027 EPS estimates excluding AI infrastructure and EnergyBasically flatShows that the source of earnings upgrades is not broad-based.
• Year-to-date long-short return of the EPS revision factorAbout 8%This factor compares S&P 500 stocks with the strongest versus weakest recent two-year forward EPS revisions.

Impact & implications

For portfolios, the report suggests that the tight linkage between AI and Momentum makes market direction more dependent on the outlook for AI investment and the macro backdrop. If AI-capex expectations are revised down, if the macro outlook deteriorates sharply and triggers risk reduction, or if the macro outlook improves sharply and causes laggards to catch up, Momentum could reverse. Conversely, as long as AI earnings revisions and capital flows continue to support the trade, the short-term trend may still extend. A more resilient approach is to retain AI-benefit exposure backed by earnings, while using low-Momentum stocks, low-AI-sensitivity stocks, and defensive sectors to reduce dependence on a single theme trade.

Risks

• A downward revision to AI capex or AI earnings prospects could trigger a 'catch-down' reversal in Momentum.
• A severe deterioration in the macro outlook could raise volatility in equities or bonds and force investors to cut risk.
• A sharp improvement in the macro outlook could also lead laggards to catch up, reversing the Momentum long-short structure.
• The concentration of gains in the S&P 500 is too high, and declining market breadth may amplify both index volatility and factor volatility.
• Hedge fund Momentum exposure and leverage are near five-year highs, increasing the risk of a rapid de-leveraging.
• In some sectors, stock prices have clearly run ahead of earnings revisions, so valuations could come under pressure if long-term growth expectations are not met.

What to watch

• Orders, earnings guidance, and changes in 2026 to 2027 EPS consensus for AI-capex-related companies.
• S&P 500 market breadth, especially the share of constituents above their 200-day moving average and changes in the median distance from 52-week highs.
• Whether the correlation between the Goldman Sachs Momentum factor and the GS AI basket remains elevated.
• Whether hedge funds' gross leverage and net exposure to Momentum remain near or above five-year highs.
• Relative performance of low-AI-sensitivity sectors such as Consumer Staples, Health Care, and Real Estate.
• Whether low-Momentum stocks with positive EPS revisions begin to outperform, which could serve as an early signal of a Momentum reversal.
• Whether stock performance in sectors such as Energy and Semiconductors continues to diverge from their 2027 EPS revisions.