CICC: Have U.S. stocks reached their bottom?

Recent fluctuations in the U.S. stock market have significantly intensified, with the "noise" from post-midterm election policies triggering market turmoil (The Implications of the Democratic Party's "Sweep" on Assets). A key factor is the current demand for AI facing a "transition" and high investment levels, among many other "issues," which have been exposed in advance (How to View the Recent Decline in U.S. Stocks?).

Of course, this rapid clearing may not be a bad thing for the long-term trend, as it helps digest overly high expectations and positions, which could actually be beneficial for a rebound when new catalysts emerge, although we need to wait for those new catalysts. It is worth noting that the gains in the U.S. stock market this year have primarily come from earnings contributions rather than relying on valuation expansion. After the recent pullback, valuations have also quickly declined. Apart from the Dow Jones, which has a valuation of 19.6 times and remains at the 86th percentile of its historical range over the past 20 years, the S&P 500 and Nasdaq have seen their valuations drop to 17.8 times and 20.3 times, corresponding to the 70th and 44th percentiles of the past 20 years, respectively. The Philadelphia Semiconductor Index has even fallen to 13.8 times, only at the 14th percentile of the past 20 years.

**Chart 1:** Valuations of the S&P 500, Nasdaq, etc., have clearly declined, with the Philadelphia Semiconductor Index even dropping to the 14th historical percentile.




Source: FactSet, CICC Research Department

This year's "K-shaped divergence" in the U.S. fundamentals has led the market to concentrate and rely on a few directions: 1) The U.S. Magnificent Seven (Mag7) contributed 22% of the S&P 500's gains since 2026, and at one point contributed 40% before the mid-October decline; 2) The five major cloud providers accounted for 20% of the S&P 500's earnings in the first three quarters of 2026, contributing 25% to the S&P 500's earnings growth; 3) The concentration effect among leading companies still exists, with the S&P 500 rising 8% since the beginning of the year, but the proportion of stocks above the 200-day moving average has decreased from 60% at the beginning of the year to 55%, with a particularly noticeable divergence in August and September. However, the current AI sector lacks catalysts at the model and application levels and is also facing policy uncertainties, while traditional demand is suppressed by high interest rates. In other words, the main directions are facing challenges, and traditional directions are yet to take over, explaining the overall turmoil.

**Chart 2:** The U.S. Magnificent Seven contributed 22% of the S&P 500's fluctuations since 2026.


Source: Bloomberg, CICC Research Department

**Chart 3:** The five major cloud providers contributed an average of 37% to the S&P 500's earnings growth in the first half of the year.


Source: FactSet, CICC Research Department

**Chart 4:** Market breadth also showed a significant narrowing in August, with the index maintaining a high level but the proportion of constituent stocks above the 200-day moving average clearly declining.


Source: FactSet, CICC Research Department

Therefore, the market needs two catalysts: either a significant breakthrough in AI or the Federal Reserve ending its tightening or even shifting to easing. Before that, we recommend a cautious wait-and-see approach: 1) Pay attention to whether there is a short-term liquidity negative feedback or further policy disturbances (the game before the new Congress takes office early next year); 2) Control positions to leave room for future allocations; 3) Adjust the structure, even within technology, to prioritize cloud providers and computing chip companies with low AI exposure or low valuations and greater bargaining power.

The first quarter of next year is a critical point: 1) A clear turning point for the Federal Reserve is expected to come early next year. The strong non-farm payrolls in October reinforced the probability of a rate hike in December, and inflation is more certain to decline early next year due to a high base; 2) The fourth-quarter reports to be disclosed in January next year. The ROIC of technology companies may continue to be under pressure, and AI will need to deliver new progress by then; 3) The new U.S. Congress will take office on January 3 next year. The policies from Trump before the new Congress takes office and the continuous statements from newly elected members may cause ongoing disturbances that the market needs to digest, and after the new Congress takes office, it may gradually desensitize. Therefore, by that time, either AI needs to make progress, or the expectations for Federal Reserve tightening need to decline, which may provide support or opportunities.

In "The Implications of the Democratic Party's 'Sweep' on Assets" and "How to View the Recent Decline in U.S. Stocks?", we have summarized the policy implications of the midterm elections and the liquidity disturbances following market turmoil. In this article, we further combine the quarterly earnings of U.S. stocks that have been largely disclosed to answer the question of the outlook for U.S. stocks from a fundamental perspective.

### Market Drivers: Earnings are the Dominant Force, AI Contributes 60% of Growth; Growth Rate Shows a Turning Point

First, strong earnings growth is the main driver of the U.S. stock market. From the beginning of the year to now, the gains of the major U.S. stock indices have all come from earnings contributions, with the S&P 500, Dow Jones, and Nasdaq rising by 8%, 7%, and 6%, respectively, while dynamic earnings grew by 29%, 17%, and 40%, offsetting the contraction in valuations. In the third quarter, S&P 500 earnings grew by 25%, a decline compared to the 32% and 56% growth in the first and second quarters, but still above the average quarterly earnings growth rate of 12% during 2023-2025.

**Chart 5:** The gains in the U.S. stock market this year have primarily come from earnings contributions rather than relying on valuation expansion.


Source: FactSet, CICC Research Department

Second, AI-related sectors contributed 60% of the earnings growth. Estimating the earnings situation of the AI sector based on communication services, information technology, and Amazon, the third quarter contributed 62% to overall earnings growth, down from 70% in the second quarter. Among them, information technology contributed 58%, supporting most of the growth in the AI sector, while communication services saw a significant slowdown in growth in the media and entertainment sub-industry, leading to a noticeable decline in contribution. This means that overall earnings growth is heavily reliant on AI; if the AI sector is excluded, the earnings growth rate in the third quarter may fall to 15%.

**Chart 6:** Information technology contributed 58% to this quarter's earnings growth, while the contribution from communication services dropped from 24% in the second quarter to 4%.


Source: FactSet, CICC Research Department

**Chart 7:** AI-related sectors contribute 60% to the overall earnings of the S&P 500.


Source: FactSet, CICC Research Department

Traditional demand's earnings in the third quarter were not poor, but high interest rates still dragged down earnings. In terms of growth rates, sectors such as energy (150%), semiconductor equipment (110%), real estate management and development (49%), and capital goods (48%) led, while transportation (-37%), telecommunications services (-34%), financial services (-14%), and insurance (-11%) lagged. In terms of contributions, sectors such as industrials, materials, utilities, and consumer staples collectively contributed 10% to earnings, while contributions from financials and real estate turned negative, dragging down overall growth by 7.5%.

Third, the growth rate has shown a turning point, marking the first slowdown since Q2 2025. In the third quarter, S&P 500 earnings grew by 25%, slowing compared to the first two quarters of this year. The market has become more "picky" about performance, not only requiring earnings to maintain high growth rates but also needing to continuously exceed expectations, which has increased the difficulty of surpassing expectations in the third quarter earnings reports. The proportion and magnitude of S&P 500 constituent stocks exceeding expectations both declined, with the proportion slightly dropping from 86% in the second quarter to 84%, and the magnitude of the exceedance significantly falling from 27% in the second quarter to 3.5%, the lowest level since Q4 2022. Among them, communication services, where Google and Meta are located, saw the largest decline, with earnings dropping from 99% above expectations in the second quarter to 19% below expectations in the third quarter.

**Chart 8:** The proportion of S&P 500 stocks exceeding expectations dropped slightly from 86% in the second quarter to 84%, while the magnitude of exceedance significantly fell to 3.5%.


Source: FactSet, CICC Research Department

### AI Direction: Revenue Lags Behind Investment; Returns Decline, but Still Exceed Costs; Can Withstand Interest Rates Dropping to 6~6.5%

1) Revenue lags behind investment. Capital expenditures are accelerating, free cash flow has turned negative, and external financing pressure is rising. The five major cloud providers' total capital expenditures in the third quarter increased from $181.5 billion to $230 billion, with a year-on-year growth rate accelerating from 87% in the second quarter to 118%. However, the growth rate of operating cash flow has significantly declined, dropping from 38% in the second quarter to 19% in the third quarter, with a total of $198 billion for the five major cloud providers, which is insufficient to cover the capital expenditures during the same period. This has caused the free cash flow of the five major cloud providers to turn negative from $4.8 billion in the second quarter to -$31.8 billion, with Amazon, Meta, Google, and Oracle all reporting negative free cash flow in the third quarter, further increasing external financing needs. In the context where AI demand has not yet broken through the "ceiling" of existing application scenarios and the investment return outlook remains unclear, the market's focus on financing costs and sources of funds has significantly increased, leading to heightened concerns about credit risk, with the CDS of the five major cloud providers rising to historical highs.

**Chart 9:** The total free cash flow of the five major cloud providers turned negative from $4.8 billion in the second quarter to -$31.8 billion.


Source: FactSet, CICC Research Department

**Chart 10:** The CDS of the five major cloud providers have also risen to historical highs.


Source: FactSet, China International Capital Corporation Research Department

2) Returns exceed costs. Marginal ROIC has further declined, but overall returns can still cover financing costs. With continued expansion of invested capital, new operating returns have not kept pace, leading the marginal ROIC of the five major cloud providers to drop from a peak of 44% in Q2 2024 to 6.1%, causing the overall ROIC to further fall to 15%. However, the overall ROIC remains above the current weighted average cost of capital (WACC) of about 10% for the five major cloud providers, indicating that cloud providers can still achieve excess returns.

Chart 11: The overall ROIC of the five major cloud providers has further declined from 16% in Q2 to 15%, with the marginal return rate also dropping to 6.1%


Source: FactSet, China International Capital Corporation Research Department

The decline in marginal returns has reduced the interest rate level that AI can withstand to 6~6.5%. Previously, we calculated that if the five major cloud providers maintained a constant ROIC, assuming the difference between ROIC and WACC narrowed to the average level of 8 percentage points before the AI trend emerged from 2015 to 2023, the corresponding safe asset interest rate that could be tolerated would be 7~7.5% (from "Is AI a 'Friend' or 'Enemy' to Traditional Demand?"). However, as marginal investment returns further weakened in Q3, the difference between ROIC and WACC has converged to historical averages, and combined with the return expectations for 2027, the safe asset interest rate level that AI can withstand has dropped to 6~6.5%.

Chart 12: Combined with the return expectations for 2027, the safe asset interest rate level that AI can withstand has dropped to 6~6.5%


Source: FactSet, China International Capital Corporation Research Department

3) The "heavy assetization" of cloud providers puts pressure on capital turnover. Further breaking down ROIC into after-tax operating profit margin (NOPAT/Revenue) and invested capital turnover (Revenue/IC), the after-tax operating profit margin of the five major cloud providers has continued to rise since 2023, increasing from 14.8% to 22.1% in Q3; however, capital turnover has continued to decline, dropping from a high of 109% in Q1 2023 to 66% in Q3, reaching a new low since 2015. Meanwhile, since Q2 2025, the improvement in profit margins has slowed and cannot offset the drag from capital turnover, which has also led to a continuous decline in the ROIC of the five major cloud providers.

Chart 13: Since Q2 2025, the improvement in profit margins has not been able to offset the negative drag from capital turnover


Source: FactSet, China International Capital Corporation Research Department

Further differentiation within technology, with some hardware segments still needing to digest growth expectations, cloud providers' pricing remains relatively reasonable. Some hardware infrastructure that incorporates higher growth expectations, such as network interconnection/optical modules, semiconductor manufacturing, and liquid cooling/temperature control, have recently seen significant valuation adjustments; for example, the valuation of the semiconductor manufacturing sector has quickly dropped from the 90th percentile at the beginning of October to around 20%. In contrast, cloud providers have not given significant valuation premiums for new profits, and the space for valuation adjustments is relatively limited.

### Traditional Sectors: Interest Rate Sensitive Segments Pressured by High Rates, AI's Squeeze Gradually Reflects

Traditional demand has not yet formed a comprehensive improvement. In terms of consumption, service consumption is stronger than goods consumption. Profits in consumer services, food and beverages, and tobacco, and automotive and parts grew by 12%, 8.7%, and 7.3%, respectively, while durable goods and clothing, and household and personal goods fell by 5.4% and 10.3%. The industrial sector shows more pronounced differentiation, with capital goods profits growing by 48.3%, and commercial and professional services growing by 16.2%, but transportation, affected by high oil price costs, fell by 37.1%. In the financial sector, bank profits grew slightly by 4.8% supported by net interest income, while insurance and financial services fell by 10.7% and 13.6%, respectively, due to fluctuations in investment gains and losses.

Growth remains resilient, but interest rate-sensitive growth segments continue to be under pressure. Recent macro data reflects that current U.S. growth remains resilient, with Q3 real GDP growing at an annualized rate of 3.4%, higher than the expected 3.2% and Q2's 2.2%. Besides AI-related investments, private consumption is also strong, especially in service consumption such as healthcare, dining, and accommodation. The October ISM manufacturing and non-farm data also significantly exceeded expectations, with the unemployment rate dropping from 4.2% to 4.1%. However, high rates continue to suppress residential housing and credit demand, with the 30-year mortgage rate rising continuously since the beginning of the year, peaking at 7.4% in October. Real estate sales remain low, with existing home sales slightly rebounding month-on-month in September, but the annualized sales volume is only 3.99 million units, and new home sales have also dropped to 676,000 units. On the other hand, weakening returns from AI may also begin to "crowd out" the physical and financial resource elements of traditional demand. As emphasized in "Is AI a 'Friend' or 'Enemy' to Traditional Demand?", the positive externalities brought by AI demand previously supported U.S. economic growth, but as AI requires more external funding to support investments, the crowding-out effect on traditional demand is also unavoidable, with AI issuing a large amount of debt and the Federal Reserve still needing to raise interest rates being a typical example.

Chart 14: Interest rate-sensitive segments such as housing sales have continued to be under pressure since 2023


Source: FactSet, China International Capital Corporation Research Department

A more significant recovery still requires a drop in interest rates to cooperate. We previously calculated using real estate and non-AI companies that the 10-year U.S. Treasury yield that traditional demand can withstand is about 4%. Although there is resilience now, high rates continue to squeeze the further release of residential housing and small business credit demand, reflected in insufficient credit expansion momentum in the household sector. In the short term, the resilience of growth and employment data makes the Federal Reserve lack immediate motivation to shift, but the weakness of traditional demand does not support larger rate hikes by the Federal Reserve. If AI expectations continue to weaken in Q1 next year, then market expectations for the Federal Reserve's tightening may decline, creating conditions for interest rates to fall and traditional demand to recover.

### Outlook Judgment: The Market Needs a Catalyst for Tightening to End or AI Progress, Early Next Year is a Key Node

Currently, the market's expectations for AI are in a "transitional" phase, with the key issue being the lack of new narratives and catalysts for demand and models, which will amplify the risks of credit and regulatory pressure. High-intensity capital expenditures continue to squeeze the free cash flow of cloud providers, leading to growing concerns about the speed of AI revenue realization and investment returns, similar to the logic of market concerns about private equity and credit risks when AI progress was insufficient at the end of last year.

In this context, the market needs two catalysts: either a significant breakthrough in AI or the Federal Reserve ending tightening or even shifting to easing. If neither occurs, it may affect investors' willingness to re-enter the market for bottom-fishing and will also amplify volatility. In the short term, attention needs to be paid to whether there will be negative feedback in liquidity or further policy disturbances (whether Trump will use this window for policy games before the new Congress takes office early next year). Q1 next year is a key verification point, with changes expected in Congress taking office, AI revenue realization during earnings periods, and inflation retreating.

Before this, we still recommend a cautious wait-and-see approach in the short term, focusing on whether negative feedback in liquidity or further policy disturbances will occur before the aforementioned catalysts appear. Currently, the S&P 500 index has returned to near the annual line, and previous adjustments have released some emotions, but the market still lacks new upward catalysts, and liquidity components and the December Federal Reserve rate hike may also bring further disturbances. Therefore, we suggest waiting for the aforementioned catalysts to appear and for investment return prospects to become clearer before making allocations. From an extreme scenario perspective, if the additional profit growth brought by AI expectations is completely "erased," dynamic profit growth may fall to 10%, assuming valuations fall to 16~17 times, then the S&P 500 index still has about 10% downside potential.

In addition to managing positions well, the holding structure can also be adjusted, even within technology, prioritizing cloud providers and computing chips with low AI exposure or low valuations and greater bargaining power. Recent market performance also reflects this difference, with segments that previously incorporated growth expectations more fully experiencing more significant adjustments, while cloud providers have been relatively resilient. Using the past 10-year average valuation as a reference, optical modules, semiconductor manufacturing, and power grid and distribution sectors still need to revise profits upward by 40~70% to match current pricing, while cloud providers retain nearly 20% profit revision space.

Chart 15: Overall U.S. stock valuations are currently not at extreme highs, but there is significant differentiation within the AI industry chain


Source: FactSet, China International Capital Corporation Research Department

Chart 16: Sectors such as optical modules, semiconductor manufacturing, and power grid and distribution that incorporate high growth expectations need to revise profits upward by 40~70%, while cloud providers have retained nearly 20% space for subsequent profit growth


Source: FactSet, China International Capital Corporation Research Department

### Source

This article is excerpted from: "Has the U.S. Stock Market Reached Its Bottom?" published on November 9, 2026.

Liu Gang, CFA Analyst SAC License No.: S0080512030003 SFC CE Ref: AVH867

Yang Xuanting Analyst SAC License No.: S0080524070028 SFC CE Ref: BXS665