Goldman Sachs trading team's three major US stock trades in 2026: Focusing on the next step of "AI trading"

Goldman Sachs trading department will focus on the deepening stage of AI applications in US stock investments in 2026, shifting from infrastructure investment to actual productivity improvement. This shift reflects the market's more cautious evaluation of which companies can truly transform technology into profitability after experiencing three years of AI frenzy. Three major thematic trading strategies summarized by Goldman Sachs derivative strategist Brian Garrett include: longing for companies that use AI to enhance productivity, shorting optional consumer goods companies targeting low-income groups, and pairing trades by longing for high-quality AI stocks while shorting vulnerable AI stocks. Analysis indicates that these strategies aim to capture market opportunities in the "K-shaped recovery" of the US economy and the differentiation of AI applications. It also reflects the transition of AI technology from the investment phase to the application phase, as well as the market's increasingly stringent screening criteria for AI-related investments. Goldman Sachs Chief Market Strategist Tony Pasquariello pointed out in the first report of the year that the macroeconomic background is still favorable to the stock market in 2026. Goldman Sachs economists expect global economic growth to be 2.8% in 2026, higher than the market consensus of 2.5%, with all regions expected to continue expanding and the Federal Reserve further moderately cutting interest rates. Ashok Varadhan, co-head of global banking markets at Goldman Sachs, explicitly stated in a recent podcast that "the US is the preferred investment destination." This judgment is based on Goldman Sachs economists predicting that the US economy will grow by 2.6% in 2026, significantly higher than the market consensus of 2.0%, with growth driven by reduced tariff drag, tax policies, and loose financial environment. AI applications entering the productivity enhancement stage Goldman Sachs has launched the US AI Productivity Beneficiary Index, shifting its investment focus from "infrastructure" such as semiconductors and data centers to actual application of AI technology in companies that reduce costs and increase profit margins. The index consists of non-tech, non-AI companies, but all have specific plans to integrate AI into their workflows. The index has outperformed S&P 500 equal-weighted index since the third quarter of 2024. Goldman Sachs expects this trend to continue, as the potential impact of AI application on labor productivity on earnings per share is higher than that of the S&P 500 and Russell 1000 indices. Companies in the index cover industries such as banking/insurance, retail/warehousing operators, transportation/logistics, healthcare, and food service. Goldman Sachs believes that these companies have the greatest potential to improve operational efficiency through AI technology, and the effects have begun to appear in their financial reports. Shorting low-income consumer sectors in a K-shaped economy Goldman Sachs trading team stated that despite strong GDP growth in 2025, the labor market performance was weak, especially with negative employment growth in summer months, resulting in the unemployment rate rising from 4.1% in June to 4.6% in November. The characteristics of the K-shaped economy continue to be significant, with low-income groups continuing to bear high price pressures while high-income groups see a significant increase in asset wealth. The low-income consumer non-essential company index recommended by Goldman Sachs underperformed the S&P 500 and S&P 493 indices in 2025. The bank expects this theme to continue in 2026, as low-income consumers continue to struggle with affordability crises. Goldman Sachs US macro team's report on December 1st stated: "The pressures facing low-income consumers including more limited borrowing capacity and weaker income growth as well as a slowdown in immigration, may be reflected in underperformance...Our income growth distribution forecasts suggest that low end consumption will continue to underperform in 2026, with weak job growth and OBBBA cuts to SNAP and Medicaid assistance benefitting low-income families." According to a previous article by Wall Street News, a survey by the University of Michigan in early December showed: "Consumers saw slight improvements in several dimensions compared to November, but the overall sentiment remains low, with consumers continuing to mention the burden of high prices. Similarly, labor market expectations have improved slightly, but still relatively dim." Market shift towards screening quality AI stocks After three consecutive years of soaring AI trading (Goldman Sachs AI Index has risen by about 284%, while the S&P 500 has risen by about 80%), the market is beginning to more carefully evaluate the fundamentals of AI stocks. In recent months, many negative news have shaken investor confidence, prompting the market to refocus on profitability, balance sheet strength, credit quality, and free cash flow, among other traditional indicators. Two months ago, Goldman Sachs divided AI stocks into "high-profit AI" index and "fragile AI" index, using balance sheet strength, credit quality and free cash flow resilience as differentiating factors. The paired trading index recommended by Goldman Sachs, longing for high-profit AI stocks and shorting fragile AI stocks, aims to benefit from the market's increasingly stringent screening. Key differentiation indicators for this strategy include net profit margin, earnings per share, debt levels, free cash flow, and credit ratings. Goldman Sachs believes that this paired trading can isolate quality from fragile stocks, adapting to the market's trend of increasingly stringent standards for AI investments. This article is reprinted from "Wall Street News"; GMTEight editor: Yan Wencai.