Don't fight the earnings cycle! Will the US stock market break 8,000 points this year?

date
14:28 16/09/2026
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GMT Eight
Jefferies expects that, driven by the dual engines of an AI investment frenzy and corporate earnings rising above expectations, the S&P 500 is projected to surge to 8,000 points by the end of 2026 and further reach 9,000 points in 2027.
Wall Street may be severely underestimating the explosive power of the current earnings cycle. According to GMTEight, Jefferies issued a clear warning in its latest research report on September 14: Don't fight the earnings cycle. Driven by the dual engines of the AI investment frenzy and corporate earnings rising above expectations, the S&P 500 is expected to surge to 8,000 points by the end of this year (2026), and further reach 9,000 points in 2027. The report argues that despite macro headwinds such as rising 10-year Treasury yields, sticky inflation, and the midterm elections, corporate fundamentals will still be the core DRIVE determining returns. Jefferies' core logic is clear and powerful: in a cycle where earnings growth exceeds twice the historical average, fighting the earnings trend is dangerous. In addition, Jefferies believes that AI-driven earnings expansion is spreading from the Magnificent Seven to the broader market, providing a more solid foundation for the market. Investors should focus on overweight sectors with strong earnings revisions and macro support, such as technology, financials, healthcare, and materials, to seize this rare earnings super-cycle amid concerns about valuation compression. At the same time, however, Jefferies also specifically pointed out two core risks in the report: first, a substantial slowdown in earnings growth for AI-related companies, which would directly shake the foundation of the entire bull market logic; second, the continued rise in 10-year Treasury yields, which would create systemic pressure on the stock market through the valuation compression channel. Earnings expectations are severely underestimated, with the S&P 500 targeting 8,000 points Jefferies' base-case forecast is highly aggressive and entirely earnings-driven. The report points out that the target price for the S&P 500 at the end of 2026 is 8,000 points, based on earnings per share (EPS) reaching $373 (up 35% year over year, far above the market consensus of 29%) and a price-to-earnings ratio of 21.5 times. Looking ahead to 2027, the index will reach 9,000 points under the base case, based on EPS of $450 (up 20.8%) and a price-to-earnings ratio of 20.0 times. Under the most optimistic "bull" scenario, the S&P 500 could even break through 10,500 points in 2027 (EPS reaching $500, up 34.2%); while under the "bear" scenario of a sharp earnings slowdown, the index could fall back to 6,900 points. The bank's core logic is that the market is pricing in five consecutive years of double-digit, above-average returns for the S&P 500, which in history since 1970 has only occurred in the late tech boom of 1995-1999. As long as earnings expectations remain strong, the current valuation level (weighted model at the 76th percentile) is manageable. AI remains the core engine, but market breadth is substantially expanding The report's most central argument is that the market is systematically underestimating the power of the earnings cycle, and there is still significant room for upward revisions. Jefferies believes that the core of the earnings story remains artificial intelligence (AI), but it is no longer exclusive to a handful of giants. Data shows that about 46% of the S&P 500's weight has direct or indirect exposure to AI and data center spending. Earnings for these AI-related companies are expected to surge 60% this year and slow to 24% in 2027. At the same time, market breadth is improving significantly. Although the Magnificent Seven's 2026 earnings expectations are as high as 45%, earnings expectations for the rest of the S&P 500 have also improved substantially to about 24%. By 2027, more than 40% of S&P 500 constituents are expected to see earnings acceleration. Jefferies believes that this cross-industry upward revision in earnings and sales expectations indicates that fundamentals are becoming healthier and more diversified. The Magnificent Seven face rotation pressure, but valuations have fallen to multi-year lows Although the Magnificent Seven still account for about 33% of the S&P 500's weight, the environment that drove their outperformance is becoming more complicated. Due to record AI investment, the Magnificent Seven now account for about 40% of total S&P 500 capital expenditure (only 16% in June 2023), causing free cash flow (FCF) for hyperscalers to turn negative, and it is not expected to recover until 2028. In addition, the group's earnings growth is expected to slow from 45% in 2026 to 17% in 2027. However, for contrarian investors, the good news is that the Magnificent Seven's valuations have been substantially reset. In absolute valuation terms, the group is currently at the 43rd percentile, the lowest level since January 2023; relative to the rest of the S&P 500, its relative valuation has plunged from the 98th percentile a year ago to the 9th percentile now. Macro headwinds: 10-year Treasury yields and fiscal deficits are the biggest tail risks On the Federal Reserve, the market currently prices about an 85% probability of a rate hike in September and about an 83% probability of one more hike before January 2027, but the terminal rate is only about 50-75 basis points above the current level. Jefferies economist Tom Simons holds a contrarian view, arguing that the Fed may not need to hike this year and expects policy expectations to shift toward rate cuts during the year. The bank believes that the real macro-level threat is not the Fed's short-term actions, but long-term borrowing costs. History shows that when the 10-year Treasury yield rises by more than 100 basis points within 12 months, the price-to-earnings ratio usually contracts by at least 1 multiple (yields have already risen by more than 60 basis points this year). The deeper crisis lies in deteriorating fiscal conditions: U.S. national debt has exceeded $40 trillion, and total debt servicing costs over the past five years have surged from about $350 billion to more than $1.1 trillion, already comparable to annual defense spending. The Congressional Budget Office estimates that the federal deficit will reach about $1.9 trillion in 2026 and increase to about $3.1 trillion by 2036. This sustained deficit spending and massive technology debt issuance will put upward pressure on long-term yields, potentially forcing further valuation compression. Responding to inflation and elections: the "safe haven" revealed by historical data In the face of sticky inflation and the upcoming midterm elections, there is no need for excessive panic. On inflation, the report argues that the current environment is more similar to the late 1980s/early 1990s and the mid-2000s than to the "Great Inflation" era of the 1970s. Historical data shows that in these two similar periods, the S&P 500's average annual returns were about 17% and 15%, respectively, and investors still earned substantial returns in an environment where inflation was above target. On the political front, prediction markets show that a "divided Congress" is highly likely after the midterm elections (87.5% probability that Democrats control the House, 47.5% probability that Republicans retain the Senate), with the most likely outcome being divided government. Jefferies believes that historical data shows legislative gridlock often reduces policy uncertainty, which is positive for risk assets. In the year after midterm elections, the S&P 500's average return has been as high as 13%. Historical data: Since 1978, in the 12 months after midterm elections, the S&P 500's average return has been 13.1%, with the median also at 13.1%, both significantly above the historical average. The sectors that typically perform strongest after elections are technology, consumer discretionary, and materials. This article is reprinted from "Wall Street See"; GMTEight editor: Li Fo.