The recent fluctuations in the U.S. stock market have noticeably intensified, with the "noise" from policies following the midterm elections triggering market turmoil ("The Asset Implications of the Democratic Party's 'Sweep'"). A key factor is also the current state of AI itself, which faces numerous "issues" such as unsteady demand and high investments that have been exposed earlier ("How to View the Dramatic Drop 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. This could actually be beneficial for the future recovery when new catalysts emerge, but it requires waiting for those new catalysts to appear. It is important to note that most of 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 declined sharply. Except for the Dow Jones, which has a valuation of 19.6 times (still at the 86th percentile of historical levels over the past 20 years), the S&P 500 and Nasdaq have fallen to 17.8 times and 20.3 times, which correspond to the 70th and 44th percentiles of the past 20 years. The Philadelphia Semiconductor Index even dropped to 13.8 times, just 14% of its historical percentile over the past 20 years.

Chart 1: The valuations of the S&P 500, Nasdaq, etc., have sharply declined, with the Philadelphia Semiconductor Index even dropping to the 14% historical percentile.

Data Source: FactSet, CICC Research Department

The "K-shaped divergence" in the fundamentals of the U.S. this year has led the market to concentrate and rely on a few directions: 1) The U.S. Mag7 has contributed 22% of the S&P 500's increase since 2026, and before the mid-October drop, it once contributed 40%; 2) The five major cloud providers accounted for 20% of the S&P 500's earnings in the first three quarters of 2026, contributing to 25% of the S&P 500's earnings growth; 3) The concentration effect among leading companies still exists, as the S&P 500 has risen 8% since the beginning of the year, but the percentage 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, current AI is lacking in both model and application layer catalysts, while traditional demand is dampened by high interest rates. In other words, the main directions are facing challenges, while traditional directions are yet to take over, explaining the overall turbulence.

Chart 2: The U.S. Mag7 has contributed 22% to the S&P 500's fluctuations since 2026.

Data 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.

Data Source: FactSet, CICC Research Department

Chart 4: Market breadth also showed a significant narrowing in August, with the proportion of constituent stocks above the 200-day moving average significantly dropping.

Data Source: FactSet, CICC Research Department

Therefore, the market needs two catalysts: either AI makes a significant breakthrough or the Federal Reserve ends tightening and even shifts to easing. Before that, we recommend a cautious watch: 1) Pay attention to whether there will be negative feedback in liquidity in the short term or further policy disturbances (the games before the new Congress takes office early next year); 2) Control positions to keep room for subsequent configurations; 3) Adjust structures, even within technology, prioritizing cloud providers and computing chip companies with low AI exposure, or those with lower valuations and greater bargaining power.

The first quarter of next year is a key point: 1) The opportunity for a clear shift by the Federal Reserve is expected to come early next year. The strong non-farm payrolls in October have reinforced the likelihood of a rate hike in December, and inflation is expected to drop in early next year due to a high base; 2) The fourth-quarter earnings report disclosed in January next year. The ROIC of tech companies may continue to face pressure, requiring AI to deliver new progress at that time; 3) The new Congress in the U.S. will assume office on January 3 next year. Policies from Trump before the new Congress takes office and the continuous statements from newly elected members may cause ongoing disturbances, which the market will need to digest; after the new Congress assumes office, the sensitivity may gradually diminish. So, by that time, either AI will have made progress, or the expectations for Fed tightening will have diminished, potentially providing support or an opportunity.

We have respectively organized the mid-term election policies and liquidity disturbances after market turmoil in "The Asset Implications of the Democratic Party's 'Sweep'" and "How to View the Dramatic Drop in U.S. Stocks?". In this article, we further combine the earnings of U.S. stocks for the third quarter, which have been largely disclosed, to answer the outlook for the U.S. stock market from a fundamental perspective.

Market Drivers: Earnings Are Dominant, AI Contributes Sixty Percent Growth; Growth Rate Has Reached an Inflection Point

First, strong earnings growth is the main driving force behind the U.S. stock market. From the beginning of the year to now, the main indices in the U.S. stock market have all seen gains driven by earnings, with the S&P 500, Dow Jones, and Nasdaq rising by 8%, 7%, and 6%, respectively, while their dynamic earnings grew by 29%, 17%, and 40%, offsetting the contraction in valuations. In the third quarter, the S&P 500's earnings grew by 25%, down from 32% and 56% in the first and second quarters, but still above the average quarterly earnings growth rate of 12% from 2023 to 2025.

Chart 5: The gains in the U.S. stock market this year have primarily come from earnings, not from valuation expansion.

Data Source: FactSet, CICC Research Department

Secondly, AI-related sectors contributed sixty percent of the earnings growth. Estimating the earnings situation of the AI sector from communication services, information technology, and Amazon, the third quarter contributed 62% to the overall earnings growth, down from 70% in the second quarter. Among these, information technology contributed 58%, supporting most of the growth in the AI sector, while the contribution from communication services has significantly weakened due to the sharp slowdown in the media and entertainment sub-industry's growth. This means that the overall earnings growth is heavily reliant on AI; if the AI sector is excluded, the earnings growth in the third quarter would have fallen to 15%.

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

Data Source: FactSet, CICC Research Department

Chart 7: AI-related sectors contributed sixty percent to the overall earnings of the S&P 500.

Data Source: FactSet, CICC Research Department

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

Third, the growth rate has reached an inflection point, slowing down for the first time since the second quarter of 2025. The S&P 500's earnings grew by 25% in the third quarter, a slowdown compared to the first two quarters of this year. The market has become more "picky" about performance, not only demanding high growth rates but also requiring constant acceleration of exceeding expectations, which has made it harder to exceed expectations in the third quarter earnings reports. The proportion and scale of S&P 500 components exceeding expectations have both decreased, with the proportion slightly dropping from 86% in the second quarter to 84%, and the extent of exceeds expectations significantly reducing from 27% in the second quarter to 3.5%, the lowest level since the fourth quarter of 2022. Among these, communication services, where Google and Meta are located, saw the largest decline, with earnings turning from exceeding expectations by 99% in the second quarter to falling short of expectations by 19% in the third quarter.

Chart 8: The proportion of S&P 500 components exceeding expectations slightly decreased from 86% in the second quarter to 84%, while the extent of exceeding expectations significantly dropped to 3.5%.

Data Source: FactSet, CICC Research Department

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

1) Revenue lags behind investment. Capital expenditures are expanding rapidly, operating cash flows have turned negative, and external financing pressure is rising. The combined capital expenditures of the five major cloud providers rose from $181.5 billion to $230 billion in the third quarter, with year-on-year growth 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, and the combined total of the five major cloud providers was $198 billion, which was insufficient to cover the capital expenditures during the same period. This 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; except for Microsoft, Amazon, Meta, Google, and Oracle all experienced negative free cash flows in the third quarter, further raising external financing needs. Under the backdrop that AI demand has yet to break through the existing application scenario "ceiling" and investment returns remain uncertain, market attention to financing costs and funding sources has significantly increased, leading to heightened concerns about credit risks, with the CDS of the five major cloud providers rising to historical highs.

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

Data Source: FactSet, CICC Research Department

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

Data Source: FactSet, CICC Research Department

2) Returns exceed costs. Marginal ROIC has further declined, but overall returns can still cover financing costs. With the continuous expansion of invested capital, new operating returns have not kept pace, causing the marginal ROIC of the five major cloud providers to fall from a high of 44% in the second quarter of 2024 to 6.1%, further reducing overall ROIC to 15%. However, the overall ROIC is still higher than the current weighted average cost of capital (WACC) of about 10% for the five major cloud providers, which means that cloud providers can still achieve excess returns.

Chart 11: The overall ROIC of the five major cloud providers fell from 16% in the second quarter to 15%, while the marginal return rate also declined to 6.1%.

Data Source: FactSet, CICC Research Department

The declining marginal returns mean that the interest rates AI can withstand have dropped to 6~6.5%. Previously, we calculated that if the five major cloud providers maintain their ROIC, assuming that the difference between ROIC and WACC narrows to the average level of 8 percentage points before the emergence of the AI trend from 2015 to 2023, the rates of safe assets that can be sustained would be 7~7.5% ("Is AI Transitioning From 'Friend' to 'Foe' of Traditional Demand?"). However, as the marginal investment returns further weakened in the third quarter, the difference between ROIC and WACC has converged to the historical average. Combining this with return expectations for 2027, the level of safe asset interest rates that AI can withstand has dropped to 6~6.5%.

Chart 12: Combining return expectations for 2027, the level of safe asset interest rates that AI can withstand has dropped to 6~6.5%.

Data Source: FactSet, CICC Research Department

3) The "heavy assetization" of cloud providers has created pressure on capital turnover. Further breaking down ROIC into after-tax operating profit margin (NOPAT/Revenue) and capital turnover (Revenue/IC), the after-tax operating profit margin of the five major cloud providers has continuously increased since 2023, rising from 14.8% to 22.1% in the third quarter; however, the capital turnover has steadily declined, dropping from a high of 109% in the first quarter of 2023 to 66% in the third quarter, reaching a new low since 2015. Meanwhile, since the second quarter of 2025, the slowing improvement in margins has failed to offset the drag of capital turnover, resulting in continuous declines in the ROIC of the five major cloud providers.

Chart 13: Since the second quarter of 2025, improvements in margins have failed to offset the negative drag of capital turnover.

Data Source: FactSet, CICC Research Department

Further differentiation within technology indicates that some hardware segments still need to digest growth expectations, while cloud providers' pricing remains relatively reasonable. Some hardware infrastructure, which is factored in with high growth expectations, such as network interconnect/optical modules, semiconductor manufacturing, and liquid cooling/temperature control, have recently seen significant valuation adjustments, for example, the valuation of the semiconductor manufacturing sector dropped rapidly from the 90th percentile at the beginning of October to around 20%. In contrast, cloud providers have not granted significant valuation premiums for new earnings, and the room for valuation adjustments is relatively limited.

Traditional Sectors: Interest Rate-Sensitive Segments Suppressed by High Rates, AI's Squeeze Becoming Evident

Traditional demand has not yet formed a comprehensive improvement. In terms of consumption, service consumption is stronger than goods consumption. Consumer services, food and beverages, and automobiles and parts saw earnings grow by 12%, 8.7%, and 7.3%, respectively, while durable goods, apparel, and household and personal products declined by 5.4% and 10.3%. The industrial sector shows more obvious differentiation, with capital goods earnings growing by 48.3%, and commercial and professional services growing by 16.2%, while transportation, eroded by high oil prices, fell by 37.1%. In the financial sector, banks saw a slight earnings increase of 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 income and losses.

Growth remains resilient, but interest rate-sensitive growth segments continue to be under pressure. Recent macro data reflect that current U.S. growth remains resilient, with a quarterly annualized growth of 3.4% in real GDP in the third quarter, exceeding the expected 3.2% and the 2.2% in the second quarter. Besides AI-related investments, private consumption has also been very strong, especially in service consumption such as healthcare, dining, and accommodation. The October ISM manufacturing index and non-farm payrolls significantly exceeded expectations, with the unemployment rate dropping from 4.2% to 4.1%. However, high interest rates continuously suppress the release of residential property purchase and credit demand, reflected in the insufficient credit expansion momentum in the household sector. In the short term, while growth resilience and employment data leave the Federal Reserve lacking immediate impetus to shift, the weakness in traditional demand does not support larger rate hikes from the Fed. If AI expectations continue to weaken in the first quarter of next year, it may create conditions for a reduction in the market's tightening expectations, facilitating rate declines and a recovery in traditional demand.

Prospects: The Market Needs Catalysts to End Tightening or AI Progress, with Early Next Year as a Key Node

The market expectations for AI are currently at a "transitional" stage, with the key issue being the lack of new narratives and catalysts without demand and models. This also amplifies the risks of credit and regulatory pressures. High levels of capital expenditure are continuously squeezing the free cash flow of cloud providers, leading to increasing concerns about the speed of AI revenue realization and investment return rates, similar to the logic in late last year when the market was worried about private equity and credit risks due to insufficient AI progress.

In this context, the market needs two catalysts: either AI achieves a significant breakthrough, or the Federal Reserve ends tightening and even shifts to easing. If neither occur, it may affect investors' willingness to re-enter the market for bottom-fishing and could amplify fluctuations. In the short term, attention should be paid to whether there is negative feedback in liquidity or further policy disturbances (before the new Congress takes office early next year, whether Trump will use this window for policy games). The first quarter of next year is a key verification point, with changes expected in the Congressional transition, earnings periods realizing AI, and inflation receding.

Before that, we still recommend a cautious watch in the short term. Before the aforementioned catalysts appear, pay attention to whether there will be negative feedback in liquidity and further policy disturbances. Currently, the S&P 500 index has returned to around the annual line, with previous adjustments having released some emotions, but the market still lacks new upward catalysts, and liquidity sub-factors and the December Fed rate hikes may also cause further disturbances. Therefore, we suggest waiting for the emergence of the above catalysts and clearer investment return prospects before proceeding with allocation. From an extreme point of view, if the additional profit growth brought by AI expectations is completely "erased," dynamic earnings growth may drop to 10%; assuming valuations also fall to 16-17 times, there may still be about a 10% downside for the S&P 500 index.

In addition to managing positions well, one can also adjust the holding structure, even within technology, by prioritizing cloud providers and computing chips with low AI exposure or those with lower valuations and greater bargaining power. Recent market performance also reflects this difference, with segments that previously had ample growth expectations experiencing more pronounced pullbacks, while cloud providers were relatively resilient. Using the average valuations over the past 10 years as a reference, sectors such as optical modules, semiconductor manufacturing, and power grid and distribution still need to revise upwards their earnings by 40-70% to match current pricing, while cloud providers have retained nearly 20% of earnings adjustment space.

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

Data Source: FactSet, CICC Research Department

Chart 16: Sectors like optical modules, semiconductor manufacturing, and power grid and distribution that FACTOR IN HIGH GROWTH EXPECTATIONS need to revise earnings upwards by 40-70%, while cloud providers have retained nearly 20% space for future earnings growth.

Data Source: FactSet, CICC Research Department

Source

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

Liugang, CFA Analyst SAC Certificate No.: S0080512030003 SFC CE Ref: AVH867

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

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