Goldman Sachs raises S&P 500 target: earnings growth remains the main driver of US equity gains, but the path will be bumpier

Overview

This is a Goldman Sachs US equity portfolio strategy report. Its core judgment is that, although US equity valuations remain at historically elevated levels, market concentration is high, and uncertainty persists around AI and the macro outlook, strong earnings growth and upward revisions are still sufficient to drive the S&P 500 higher. The report raises the S&P 500 year-end target from 7600 to 8000 and expects it to reach 8300 over the next 12 months. Goldman Sachs also emphasizes that the upside path will not be smooth; excessive short-term momentum, crowded AI trades, oil price shocks, interest-rate changes, and geopolitics all require investors to place greater emphasis on risk management.

Core views

First, the S&P 500’s gains so far this year have been driven mainly by upward earnings revisions rather than valuation expansion, and Goldman Sachs expects this pattern to continue. Second, AI infrastructure investment is an important source of earnings growth, with semiconductor, power infrastructure, industrial, and utility-related companies benefiting significantly, although depreciation pressure and free cash flow uncertainty at hyperscalers will partly offset the gains. Third, the current P/E multiple of around 21x is already at a historically elevated level, so future index gains will depend more on EPS growth than on valuation re-rating. Fourth, the speculative frenzy and fundamental deterioration often seen at the end of past high-valuation, high-concentration bull markets have not fully appeared, but some yellow flags are accumulating. Fifth, portfolios should hold stocks with strong earnings revisions and relatively low correlation with AI trades, while options can be used to express or hedge views.

Analysis framework

The report uses a top-down equity strategy framework, decomposing S&P 500 returns into EPS growth and valuation multiple changes, and combines earnings season data, AI capex forecasts, P/E scenarios, speculative trading indicators, risk appetite indicators, momentum factors, market breadth, and macro variables to assess subsequent returns. The asset allocation recommendations focus on earnings revisions, beneficiaries along the AI capex chain, low-AI-correlation earnings-momentum stocks, and options-based risk management.

Methodology notes

• 股票策略EPS增长与P/E倍数拆解

  Decomposing index returns into earnings growth and valuation multiple changes.

  The report argues that the S&P 500’s rise so far this year has mainly come from upward revisions to forward EPS expectations, while the P/E multiple has actually declined; the base case going forward assumes the P/E remains around 21x, with EPS growth driving further index gains.

• 盈利分析盈利修正动量

  Using upward earnings revisions to identify industries and stocks with stronger relative performance.

  Goldman Sachs notes that stocks with the strongest recent earnings revisions have typically outperformed, and expects short-term earnings trajectories to continue determining share price trajectories in an environment where macro and micro uncertainty remains high.

• 主题投资AI资本开支传导

  Analyzing how hyperscaler capital expenditures transmit into the earnings of semiconductor, power infrastructure, industrial, and utility companies.

  The report views AI infrastructure investment as a core source of S&P 500 earnings growth, while also highlighting hyperscaler depreciation expense, free cash flow pressure, and validation of enterprise AI application returns as key subsequent constraints.

• 风险监测投机交易与风险偏好指标

  Observing bull-market overheating risk through speculative trading, IPO supply, momentum factors, and market breadth.

  The report believes current risk appetite and momentum already show signs of overheating, but retail trading, speculative trading indicators, and IPO activity have not yet reached the extreme levels seen at the end of past bull markets.

Asset mapping & comparison

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

• S&P 500

  The core forecasting target of the report and the benchmark for the US equity market.

  Strengths

  Strong earnings growth, upward EPS revisions, and investor sentiment that is still not extreme; under the base case, the year-end target is raised to 8000.

  Weaknesses

  The P/E of about 21x is at a historically high level, index concentration is elevated, and there is limited room for valuation expansion.

  Comparison

  The S&P 500 has risen about 10% so far this year, forward EPS expectations have risen about 15%, and the P/E multiple has fallen about 4%.

  Risks

  AI sentiment volatility, rising interest rates, oil price shocks, slower economic growth, geopolitics, and midterm election seasonality.

• AI infrastructure stocks

  An important contributor to S&P 500 EPS growth and the core main theme of the current US equity rally.

  Strengths

  Capex expectations have been raised sharply, forward earnings are improving in tandem, and these stocks are expected to contribute roughly half of S&P 500 EPS growth in 2026 and 2027.

  Weaknesses

  Price gains and earnings expectations have already been revised up substantially, raising the hurdle for further upside surprises.

  Comparison

  Since February 27, S&P 500 AI infrastructure stocks have risen about 33%, versus about 9% for the S&P 500 and only about 1% for the equal-weight S&P 500.

  Risks

  Insufficient realization of AI investment returns, excessive valuation expansion, narrow market breadth, and momentum factor volatility.

• Semiconductor and memory stocks

  Direct earnings beneficiaries of the AI investment boom.

  Strengths

  Companies such as NVDA and MU are widely expected to contribute significantly to S&P 500 EPS growth in 2026, and semiconductors sit at the front end of the AI capex transmission chain.

  Weaknesses

  Some memory earnings are cyclical, and the market may assign valuation multiples below the average level.

  Comparison

  The report notes that the recent share price performance of some semiconductor stocks has already outpaced upward revisions to forward earnings.

  Risks

  Overestimation of cyclical earnings, excessively rapid multiple expansion, and slowing AI infrastructure demand.

• Hyperscalers AMZN, GOOGL, META, MSFT, ORCL

  The main spenders on AI capex and also the key entities for validating the long-term returns of AI applications.

  Strengths

  Revenue and margin expectations received positive revisions after the Q1 earnings season, and market confidence in returns on AI capex has improved.

  Weaknesses

  Rising depreciation expense will weigh on earnings, and growth in net income and free cash flow is diverging.

  Comparison

  AMZN, GOOGL, META, and MSFT trade at an aggregate P/E of about 24x, near the low end of the past decade’s range, but their price-to-free-cash-flow multiple exceeds 150x.

  Risks

  Persistently high capital intensity, uncertainty around long-term free cash flow, and slower-than-expected realization of enterprise AI monetization and productivity gains.

• Power infrastructure, industrial, and utility-related stocks

  Indirect beneficiary assets of AI infrastructure buildout.

  Strengths

  The report believes power infrastructure-related stocks present prominent opportunities in the AI buildout chain, and some industrial and utility companies are also seeing earnings improvement.

  Weaknesses

  They are more heavily affected by macro growth, interest rates, and input costs.

  Comparison

  Compared with some semiconductor stocks whose valuations have already expanded, power infrastructure and some hyperscalers have seen market cap increases that are relatively more moderate versus incremental earnings.

  Risks

  Changes in capex pace, rising interest rates, project execution risk, and regulatory risk.

• Low-AI-correlation earnings-momentum stocks

  Used to balance AI exposure and diversify portfolio risk.

  Strengths

  They have earnings tailwinds and revision momentum while maintaining relatively low correlation with AI trades.

  Weaknesses

  If the AI theme continues to become extremely concentrated, they may underperform high-beta AI assets in the short term.

  Comparison

  The report uses an 'insensitive portfolio' as an example, screening for stocks with low sensitivity to AI and growth pricing, at least 5% EPS growth in 2026 and 2027, and upward earnings revisions.

  Risks

  Slower macro growth, failed sector rotation, and reversal in earnings revisions.

Key data

• S&P 500 year-end target8000Raised from the previous 7600, implying about +6% return by year-end.
• S&P 500 3-month, 6-month, and 12-month forecasts7600 / 8000 / 8300Corresponding to return forecasts of about +1%, +6%, and +10%.
• 2026 S&P 500 EPS forecast$340, +24% year over yearGoldman Sachs’s raised forecast, reflecting a strong Q1 earnings season.
• 2027 S&P 500 EPS forecast$385, +13% year over yearAI investment beneficiaries are still expected to contribute important incremental gains.
• Q1 2026 S&P 500 EPS growth+18% year over yearStill very strong even after excluding some one-off special gains.
• Q1 earnings growth for the median S&P 500 company+14% year over yearEven excluding the contribution from the largest tech stocks, it was still one of the few strong quarters in the past decade.
• Current S&P 500 P/Eabout 21xNear the 88th percentile of the past 40 years, though Goldman Sachs believes it is close to fair value under the current model.
• 2026 capex forecast for hyperscalers$754 billion, +83%Covers AI infrastructure investors such as AMZN, GOOGL, META, MSFT, and ORCL.
• 2027 capex forecast for hyperscalers$905 billion, +20%Goldman Sachs believes consensus expectations for 2027 still have upside risk.
• AI productivity contribution to S&P 500 EPS growth+0.4 percentage points in 2026; +1.5 percentage points in 2027Depends on whether enterprise AI applications and productivity gains can gradually materialize.

Impact & implications

The investment implication is that US equities can still deliver positive returns, but portfolio construction should shift from simply chasing valuation expansion toward identifying earnings upgrades and earnings quality. The AI infrastructure chain remains the core of earnings growth, but high expectations also raise the hurdle for delivery; semiconductors and power infrastructure have direct beneficiary logic, while hyperscalers simultaneously offer long-term AI gains and near-term depreciation and free cash flow pressure. Goldman Sachs recommends that investors maintain AI-related earnings exposure while also allocating to stocks with strong earnings momentum but low AI correlation, and use options in the current low implied volatility environment to express views or hedge risk.

Risks

• Oil price shocks and risks related to the Strait of Hormuz could weaken consumer spending, raise inflation, and compress profit margins.
• If inflation pressure rises or the Federal Reserve has less room to cut rates, valuation multiples may come under pressure.
• Whether AI capex and AI earnings can translate into long-term free cash flow still needs to be validated.
• Narrow market breadth, strong momentum factors, and high concentration could amplify drawdowns.
• A P/E of about 21x is at a historically elevated level, leaving limited room for further valuation expansion.
• Semiconductor and memory earnings may be cyclical; if the investment boom slows, both earnings and valuations may come under pressure.
• Geopolitical uncertainty and midterm election seasonality could slow short-term returns.
• Increasing IPO supply and rising risk appetite may gradually approach the risk characteristics seen at the end of historical bull markets.

What to watch

• Whether forward S&P 500 EPS expectations continue to be revised upward, especially the 2026 and 2027 forecasts.
• Whether AI infrastructure capex, order backlogs, and supply-demand gaps continue to support earnings for semiconductors and power infrastructure.
• Depreciation expense, margins, free cash flow, and guidance on AI investment returns from hyperscalers.
• Whether the S&P 500 P/E remains stable around 21x, or is re-rated due to interest rates, growth, and AI uncertainty.
• Speculative trading indicators, retail trading activity, IPO supply, market breadth, and momentum factor volatility.
• Changes in oil prices, inflation, consumer spending, and Federal Reserve policy expectations.
• Whether geopolitical improvement drives short-term catch-up in cyclical stocks and consumer discretionary.
• Whether options implied volatility remains low, thereby supporting the use of options to express or hedge views.