Goldman Sachs Projects U.S. Stocks to Underperform Global Markets for Next Decade
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This analysis is based on Goldman Sachs’ comprehensive Global Strategy Paper “Building Long-Term Returns: Our 10-Year Forecasts” [3], published on November 12, 2025, which projects a fundamental shift in global equity performance dynamics over the next decade.
The forecast was released during a period of relative market stability, with major U.S. indices showing modest performance over the past 30 days: S&P 500 (+0.27%), NASDAQ Composite (+0.31%), and Dow Jones (+1.07%) [0]. Current market data shows the S&P 500 trading at elevated forward P/E ratios of approximately 21-23x, supporting Goldman’s valuation concerns [1][2]. The SPDR S&P 500 ETF (SPY) currently trades at $672.85 with a P/E ratio of 28.41, indicating valuations significantly above historical norms [0].
Goldman’s forecast reveals a dramatic divergence in expected returns across regions:
- United States: 6.5%- Ranks in the 27th percentile historically since 1900, well below the historical median of 9.3% [1][3]
- Europe: 7.1%- Supported by a substantial 3% dividend yield [1][3]
- Japan: 8.2%- Benefiting from policy-led improvements and rising dividend culture [1][3]
- Asia ex-Japan: 10.3%- Driven by 9% EPS growth combined with 2.7% dividend yield [1][3]
- Emerging Markets: 10.9%- Highest projected returns globally, led by China and India [1][3]
Goldman acknowledges AI as a “wild card” that could dramatically alter outcomes, though their forecast doesn’t explicitly model AI productivity gains [1]. Separate Goldman research suggests AI benefits will be “broad-based rather than confined to U.S. technology” [1], creating uncertainty about whether U.S. tech dominance can continue or if global convergence will accelerate.
The forecast assumes U.S. dollar depreciation, which would significantly benefit non-U.S. equities when translated to USD terms [1][3]. However, the timing and magnitude of currency moves remain uncertain, adding another layer of complexity to the projections.
The S&P 500’s heavy weighting to technology (26% profit margins vs. 13% for the rest of the index) creates asymmetric risk profiles [1]. While this provides arithmetic upside if tech dominance continues, it also creates significant downside risk if this trend reverses. Goldman suggests S&P 500 equal-weight indices (RSP) may outperform cap-weighted aggregates, indicating opportunities within the U.S. market despite overall underperformance concerns [2].
Goldman Sachs’ forecast represents a significant paradigm shift from the past decade’s U.S. equity dominance. The projection of 6.5% annualized returns for U.S. equities ranks in the 27th percentile historically and reflects concerns about elevated valuations, extreme market concentration, and limited earnings growth potential [1][3].
The forecast suggests emerging markets (10.9%) and Asia ex-Japan (10.3%) will significantly outperform developed markets, driven by stronger earnings growth and attractive dividend yields [1][3]. However, the report acknowledges substantial uncertainty around AI’s impact, currency dynamics, and regulatory environments.
Current market conditions support Goldman’s concerns, with the S&P 500 trading at elevated valuations (forward P/E of 21-23x) and showing extreme concentration in mega-cap technology stocks [1][2][0]. The technology sector’s outperformance (+2.20%) despite these concerns highlights the ongoing dominance of “superstar” companies [0].
The analysis reveals several critical monitoring priorities: technology sector fundamentals, currency and flow dynamics, corporate profitability trends, and global economic divergence patterns [1]. These factors will be crucial in determining whether Goldman’s projections materialize or if unexpected developments (particularly in AI) alter the trajectory.
It’s important to note that Goldman’s scenarios range from 3-10% [1], and historical instances of forecasts underpredicting actual returns suggest maintaining flexibility in strategic allocation decisions. The forecast represents one viewpoint among many, and actual market outcomes may differ significantly from projections.
Insights are generated using AI models and historical data for informational purposes only. They do not constitute investment advice or recommendations. Past performance is not indicative of future results.
