U.S. Equities Enter Mid-Cycle: Quality Takes Over from Momentum, Hyperscalers Preferred over Semiconductors

Overview

The report concludes that the U.S. business cycle has begun transitioning from early cycle to mid-cycle. As the post-recession operating leverage dividend moderates, investors will place greater emphasis on earnings stability, margins, free cash flow, and operational efficiency. The historic momentum drawdown may have bottomed, but the previous semiconductor-led leadership structure is expected to be gradually replaced by quality, insurance, healthcare equipment and services, software, and similar areas. Morgan Stanley still expects the S&P 500 to reach 8,000 by year-end 2026, but the Iran conflict, oil prices, and a rapid rise in long-end U.S. Treasury yields could prolong the recent correction.

Core views

Core views include: first, the cycle’s shift from early to mid-cycle will drive market leadership from low quality toward high quality; second, improvement in median earnings growth and revision breadth supports index resilience and broader market participation; third, semiconductors may rebound in the short term as crowding normalizes, but their medium-term relative performance may lag; fourth, hyperscalers combine lower relative valuations, strong core businesses, AI application-layer opportunities, and optionality to reduce operating expenses, offering better risk-reward than semiconductors over the next three months; fifth, the AI investment cycle still has room to run, but the market will require clearer evidence of adoption, returns on investment, and capex discipline.

Analysis framework

The report integrates business-cycle positioning, quality and momentum factor analysis, comparisons of three-month and twelve-month price momentum weights, earnings revision breadth, sector analogy price paths, relative valuation, and operating metric screening for AI adopters. The macro section combines the yield curve, ISM, inflation expectations, and Federal Reserve communication to assess index risks; the AI section validates the investment thesis through revenue growth, margin improvement, productivity, adoption scale, and capex returns.

Methodology notes

• Macro Cycle AnalysisEarly-Cycle to Mid-Cycle Transition Framework

  The stage of the business cycle determines the earnings quality and operating leverage characteristics preferred by the market.

  As the cycle matures, incremental cyclical operating leverage moderates, and the market typically rotates from low-quality stocks toward companies with stable earnings, higher margins, and stronger free cash flow.

• Factor AnalysisQuality and Momentum Rotation Framework

  Compare changes in sector and style weights in three-month and twelve-month momentum portfolios to identify leading turns in market leadership.

  Short-term momentum weights have increased for software, insurance, healthcare equipment and services, and factors such as high sales stability, low sales volatility, and high gross margins, while weights have declined for semiconductors, technology hardware, small caps, and high accruals.

• Market AnalogySemiconductor and Silver Stock Price Path Analogy

  Map the prior momentum drawdown path of silver stocks to the potential price rhythm of semiconductors.

  The SOX index bottomed near the level indicated by the analogy model; this path suggests semiconductors may rebound over the next few weeks, but could then continue to trade sideways or underperform the S&P 500.

• Fundamental Breadth AnalysisEarnings Growth and Revision Breadth

  Use median constituent earnings growth and high-frequency revision breadth to judge whether market participation can broaden.

  Median earnings growth has risen to 14%, and revision breadth has rebounded notably, supporting a shift from a market driven by a handful of leaders to broader participation.

• Thematic ScreeningConcentrated AI Adopter Screening

  Screen for companies that are already able to use AI to improve revenue, productivity, margins, or customer experience.

  The screen focuses not only on AI narratives, but also incorporates analyst feedback and verifiable indicators such as adoption scale, margin changes, operating cost savings, and product commercialization.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• S&P 500

  Bullish over the medium term

  Strengths

  High-quality companies have a relatively large weight, while median earnings growth and revision breadth are improving, supporting index resilience and broader upside participation.

  Weaknesses

  In the near term, it remains pressured by valuation sensitivity, long-end rates, and geopolitical uncertainty.

  Comparison

  Benefits more from a mid-cycle quality rotation than low-quality, small-cap, and pure early-cycle sectors.

  Risks

  A rapid move in the 10-year U.S. Treasury yield toward 5%, escalation of war, or a significant acceleration in oil prices.

• Hyperscalers and Mag 7

  Preferred over semiconductors in the coming months

  Strengths

  Relative valuations are low, core businesses are solid, and they also have optionality from AI infrastructure, application-layer growth, and operating expense reductions.

  Weaknesses

  Differences in capex, monetization ability, and operating quality across companies are widening, and performance within the group may diverge significantly.

  Comparison

  They have already outperformed semiconductors by nearly 20% on an equal-weighted basis over the past four weeks, and the report believes their risk-reward is superior over the next three months.

  Risks

  Imbalanced capex communication, insufficient evidence of AI returns on investment, earnings estimate cuts, and further valuation discounts.

• Semiconductors and the SOX Index

  Short-term rebound, cautious medium-term view

  Strengths

  Positions may recover after the historic momentum deleveraging, and the silver stock analogy points to a tactical rebound over the next few weeks.

  Weaknesses

  Earnings revision breadth has decelerated from elevated levels, and semiconductors have strong early-cycle characteristics.

  Comparison

  Their appeal declines relative to quality stocks and hyperscalers in a mid-cycle environment.

  Risks

  Further decline in momentum weights, tighter capex discipline, and questions about returns on AI infrastructure investment.

• AI Adopter Basket

  Positive

  Strengths

  AI has begun improving productivity, product development, customer service, revenue growth, and margins, while relative net margin is significantly ahead of the market.

  Weaknesses

  Companies vary widely in adoption depth, data advantages, and commercialization capabilities.

  Comparison

  Compared with AI enablers that rely only on capex expansion, adopters with verifiable operating benefits are more aligned with the quality rotation logic.

  Risks

  Adoption speed falls short of expectations, model costs and regulatory pressure rise, and efficiency gains fail to translate into profits.

• META

  Both AI adopter and enabler, but with near-term divergence risk

  Strengths

  Agentic coding is driving higher engineer output, and the company has potential growth optionality from NeoCloud, Meta AI Search, API revenue, subscriptions, and advertising revenue.

  Weaknesses

  The market is sensitive to the scale of capex and its alignment with sales growth.

  Comparison

  Recent performance has lagged MSFT, whose capex communication is more balanced and whose Azure and Copilot data are stronger.

  Risks

  Capex uncertainty, delayed realization of returns on investment, and execution of efficiency plans falling short of expectations.

Key data

• S&P 500 year-end target8,000 pointsMorgan Stanley’s index view for year-end 2026.
• Weight of high-quality companies in the S&P 500About 42%Above the roughly 28% weight of low-quality companies, making the quality rotation more favorable at the index level.
• Median earnings growth of constituents14%Earnings growth is accelerating, while high-frequency revision breadth is rebounding.
• Relative valuation of hyperscalers3rd percentile of forward valuations since 2023The report therefore believes this group offers relatively attractive value.
• Hyperscalers’ relative performance versus semiconductorsAhead by nearly 20% on an equal-weighted basis over the past four weeksThe report expects the relative advantage may continue over the next several months.
• Change in relative net margin of AI adoptersWidened by 50 basis points over three monthsTheir net margin is currently nearly 400 basis points above the overall market.
• META engineer output improvementUp 30% since the beginning of 2025Management attributes this to the adoption of agentic coding tools.
• META potential efficiency gainsSavings of $3 billion to $13 billion and 5% to 10% upside to 2027 EBITThe report also estimates that five potential business opportunities could together contribute about $10 of incremental 2028 EPS.

Impact & implications

Asset allocation should reduce reliance on a single semiconductor momentum trade and rotate toward companies with stable earnings, high gross margins, low sales volatility, and improving operating efficiency. AI allocation needs to shift from simply chasing infrastructure capex to also holding hyperscalers with reasonable valuations and return potential, as well as AI adopters already showing productivity, revenue, or margin improvement. At the index level, upside remains, but short-term consolidation and elevated volatility may persist until long-end yields, oil prices, and geopolitical risks become clearer.

Risks

• Escalation of the Iran conflict or renewed disruption in the Strait of Hormuz could drive a rapid rise in oil prices and pressure risk assets.
• An accelerated rise in 10-year or 30-year U.S. Treasury yields, especially a rapid move in the 10-year yield toward 5%, could significantly increase the cost of capital.
• The market may fail to adapt to the communication style of the new Fed Chair Warsh, leading to higher bond volatility and tighter financial conditions.
• AI capex growth may lack sufficient evidence of adoption, revenue, and returns on investment, triggering further valuation downgrades for related stocks.
• The short-term rebound in semiconductors may fail to continue, while earnings revision breadth and price momentum continue to deteriorate.
• Quality rotation and earnings broadening may fall short of expectations, putting pressure on the S&P 500 year-end target of 8,000.

What to watch

• Whether median earnings growth of S&P 500 constituents and high-frequency earnings revision breadth can continue to improve.
• The transmission from three-month momentum to twelve-month momentum, and changes in the weights of semiconductors, software, insurance, and healthcare equipment and services.
• Whether the 10-year U.S. Treasury yield rapidly approaches 5%, and whether bond volatility and funding markets remain stable.
• Warsh’s communication on the inflation target, policy reaction function, and rising long-end yields.
• Hyperscalers’ statements on AI capex, monetization paths, returns on investment, and operating expense discipline.
• Whether enterprise AI tool adoption, employee usage, and AI adopter margins rise further.
• Whether the tactical rebound in the SOX index can persist, or whether it weakens again along the path suggested by the silver stock analogy.
• Developments in Iran, the transport status of the Strait of Hormuz, and changes in oil prices.