Leeway Research

Investment thesis 14 min

In a Concentrated US Market, Selection Matters More Than the Sector

Breadth, interest rates and the financing of AI infrastructure explain more than the label of a supposedly cheap sector.

The assessment is produced by a discussion among several models, with continuous fact-checking and research. Jump to the method

Index concentration, interest rates and the financing of the AI boom are changing the rules of the game. Why investors should focus on three drivers rather than on sectors.

The Thesis at a Glance

  • The sector basket has changed. Financials and healthcare have already recovered part of their discount, consumer staples are not cheap on the available fair-value measures, and communication services are dominated by two AI-platform equities.
  • Three sectors share one factor. Regional banks, telecom and consumer staples are largely exposed to the discount rate applied to non-AI cash flows. Four sectors therefore create only the appearance of diversification.
  • Credit risk has moved. Most of the senior credit risk in AI infrastructure sits in private credit, infrastructure debt and securitisation rather than on regional-bank balance sheets.
  • Selection remains useful. A modest breadth allocation, selected bank franchises, healthcare businesses with identifiable earnings drivers and a limited set of risk hedges have a clearer rationale than a bet on whole sectors.

13.1% versus 11.8%

The equal-weight S&P 500 has done better than its capitalisation-weighted counterpart year to date (as of 12 September 2026), an early but incomplete sign that breadth is returning.

4–5%

A persistently higher ten-year Treasury yield would limit the absolute return from defensive equities even if they do better than the market.

Credit risk sits outside banks

Private-credit funds, infrastructure lenders and securitisation buyers carry much of the senior credit risk in the AI infrastructure build-out.

Three Drivers, Not Four Sectors

The allocation is easier to evaluate once the sector labels are replaced by the three mechanisms that can actually determine returns.

  1. 01

    Market breadth

    A lower valuation for the largest index constituents can allow the average company to do better, even if no defensive sector receives a broad re-rating.

  2. 02

    The rate path

    Long-term yields determine whether defensive equities offer a positive absolute return or only relative protection in a market decline.

  3. 03

    AI-project finance

    The direct funding risk is concentrated in private credit, infrastructure finance and securitisation rather than broadly in regional-bank loan portfolios.

The analysis

A common assumption is that financials, healthcare, consumer staples and communication services can recover because their relative valuations had fallen too far. The evidence now supports a narrower conclusion. Consumer staples are not broadly undervalued, regional banks and healthcare have already recovered part of the sentiment move, and communication services is primarily a view on the capital intensity and cash-flow conversion of a small number of platforms.

The common mechanism is market breadth. If the valuation of the largest AI-linked companies normalises on capital-adjusted free cash flow, the average company can do better even without a broad re-rating of defensive sectors. The rotation is likely to arrive in bursts: the gap may arrive in one or two reporting periods and partially retrace afterwards.

Portfolio construction should therefore separate independent earnings drivers from correlated rate exposure. Healthcare offers a demographic and earnings path that can be analysed separately. Banks require balance-sheet selection. Consumer staples require evidence that volumes and margins can stabilise. The financing chain for AI infrastructure creates a distinct risk case that is better examined in non-bank lenders than in regional-bank exchange-traded funds.

The Argument

The valuation premise has narrowed

As of September 2026, the broad valuation case has weakened. Consumer defensive, healthcare and financials no longer trade at an obvious aggregate discount on the available fair-value measures, while part of the regional-bank recovery has already occurred. Communication services appears inexpensive only at the sector level, where Alphabet and Meta dominate both market value and the underlying valuation judgement.

Breadth remains the theme, but historical sector averages are no longer enough as an investment target. A sector can look inexpensive because its long-term earnings prospects have changed, or expensive because a small number of businesses have temporarily raised the index hurdle rate for every other company.

The four labels conceal a shared rate exposure

Regional banks, telecom and consumer staples are different businesses, but all are sensitive to the discount rate applied to mature, non-AI cash flows. Their combination is therefore less diversified than it appears. Healthcare has a partly separate driver in utilisation, treatment demand and acquisitions and licensing, but public-payer exposure, medical-cost trends and regulation still require a separate analysis.

This distinction matters in an equity unwind. If long-term yields fall sharply, defensives can produce positive absolute returns as they did in earlier recessions. If yields remain elevated because term premium rises with fiscal supply, the more relevant precedent is 2022: relative outperformance with limited or negative absolute returns.

The financing chain changes the credit trade

Falling regional-bank share prices say little about who carries the main risk of AI projects.

Large data-centre projects increasingly use leases, special-purpose vehicles, GPU-backed lending and securitisation alongside hyperscaler funding. Private-credit funds, infrastructure debt vehicles and institutional buyers of asset-backed and commercial-mortgage securities appear to hold much of the senior credit risk. Banks often arrange, construct or provide transitional financing without retaining the same ultimate credit risk.

Regional-bank disclosures reinforce the need for discrimination. Capital-call lines, mortgage-bank warehouse funding and specialty finance are not equivalent to direct project lending. A general sell-off in lending to non-depository financial institutions (NDFIs) may therefore create a selection opportunity in banks with transparent, short-duration and well-collateralised books, while the more direct risk is held by fee-driven lenders and managers.

The return source is selection, not a sector bet

The coherent allocation is narrower than a sector bet. Market breadth can be expressed through equal weighting. Bank exposure belongs with consolidators and franchises whose funding and non-bank-financial exposure are visible. Healthcare should be split between managed care, tools and devices, and private-pay demand rather than treated as one valuation factor.

Telecom serves here as a dividend position. Branded consumer goods makers face a more structural test because retail media and private-label share can transfer economics from manufacturers to retailers. The clearest negative exposure follows the financing evidence: businesses whose fee growth and asset marks depend on uninterrupted funding for AI infrastructure.

The Allocation Structure

The ranking separates independent earnings drivers from exposures that depend on the same market regime.

RankLayerRationale
1Market breadthEqual weighting directly expresses a normalisation from index concentration to a broader set of corporate earnings.
2Selected bank franchisesFunding quality, balance-sheet duration and the composition of non-bank-financial exposure matter more than the regional-bank label.
3Healthcare earnings driversUtilisation, devices, diagnostics and managed-care pricing can be analysed separately from the sector multiple.
4Telecom incomeA covered dividend and operating cash flow can support a modest dividend position, subject to long-term yield sensitivity.
5Branded consumer goods makersFlat volume, private-label share and retail-media spending can reduce the profit pool and justify a lower long-term valuation.
6AI-project creditFee and commission income and asset marks are exposed when financing conditions tighten before AI infrastructure produces the assumed cash flow.
7Rate and fiscal hedgesCurve exposure and gold address the rate-path uncertainty that determines whether relative equity winners also deliver positive absolute returns.

The weakest allocation combines sector labels that share a discount-rate sensitivity while assuming that each will revert to an earlier valuation range.

The likely rate setting

concentratedMarket.regime.lead

Rates are likely to remain well above the levels of the 2010s over the long term. Persistent fiscal deficits, defence, grid investment and demographic spending can keep the term premium and the ten-year Treasury yield structurally higher than the levels that supported earlier defensive-equity re-ratings. A lower valuation for capital-intensive AI platforms would then broaden the market without necessarily creating a large absolute return in staples, telecom or other bond-like equities.

By the early 2030s, the more durable distinction may be between economic layers rather than sectors: businesses that own demand generation, payment or data; businesses that fund physical capacity; and businesses that merely supply it. The bank sector itself is likely to divide between scaled franchises with payment and deposit advantages and undifferentiated lenders whose funding becomes more easily replaceable.

The Investment Selection

The selection expresses distinct parts of the analysis. The company ratings on the cards are independent Leeway assessments; the position notes describe the thesis conditions rather than personalised investment advice.

The Business-Rating scores the quality of the business model, independent of the share price. The Market-Fit-Rating tests eighteen fundamental figures for how well the company currently fits the market; a negative reading implies expected negative performance. The Cycle-Rating places the valuation in the stock’s own history: a higher figure means the shares are historically cheaper. The Leeway-Score combines the three in equal parts. How the ratings are calculated

The recommendations since publication

From 15 September 2026 to 15 October 2026: Portfolio+3.3%ACWI+0.7%

Market breadth

Long

Equal weighting is the cleanest expression of the concentration thesis, but the timing of the gap remains uncertain.

Invesco S&P 500 Equal Weight ETF

RSP.NYSEARCA

Long

Role in thesis: Broad market-breadth exposure through an equal-weight S&P 500 fund.

Investment case: Equal weighting benefits if the largest index constituents lose valuation support while the average company retains earnings power.

What would invalidate it: The case weakens if AI cash-flow conversion strengthens and index concentration rises persistently.

Position and what to watch

Position: This is a strategic tilt against a capitalisation-weighted core rather than a leveraged pair trade.

What to watch: Monitor hyperscaler free cash flow, capital-expenditure guidance and the weight of the ten largest S&P 500 companies.

Principal risk: The gap has lagged for several years and can reverse if AI-platform free cash flow re-accelerates.

Your knowledge edge

Understand the real drivers of our portfolio

Look behind the scenes: see not only what we buy, but why. Get the complete view of our strategy.

  • Every position revealed: Access each holding in our portfolio.
  • Understand the investment thesis: See the exact role each security plays in our return.
  • See the connections: Analyse our long and short strategies in direct context.

Timeline and Checkpoints

The relevant evidence is concentrated in earnings, credit marks and the response of long-term yields to market stress.

WindowWhat happensWhat it means for the portfolio
September to November 2026Regional-bank results disclose deposit costs, office reserves and the composition of lending to non-depository financial institutions (NDFIs), while hyperscalers provide their first broad indications for 2027 capital expenditure.Cash flow against capital expenditure and the composition of bank credit exposure are more important than sector-level valuation labels.
December 2026 to February 2027Managed-care guidance, consumer-staples resets and year-end private-credit and business development company (BDC) marks create the densest group of fundamental tests.The evidence can validate the healthcare selection, challenge the staples case or reveal whether AI-project credit marks remain credible.
First half of 2027Bank merger activity, acquisition accounting adjustments and the first material depreciation effect from the 2024–26 AI capital-spending cycle become clearer.This period tests both the bank-selection case and the market’s willingness to value AI platforms on capital-adjusted cash flow.
Mid-2027 to the end of 2028The 2028 election cycle returns healthcare pricing to the political agenda while the conversion of AI revenue into cash flow either validates or challenges the investment cycle.Breadth could improve abruptly if cash-flow conversion disappoints, but healthcare multiples may remain constrained even when earnings grow.
2029 to 2031Bank consolidation, deposit-franchise differentiation and lower assumptions about long-term earnings prospects for branded consumer goods become more visible.The distinction between selected businesses and sector bets should become more pronounced.

Scenarios

The probabilities are working assumptions for portfolio construction, not forecasts.

PathWeightWhat happens
Orderly broadening 20% Long-term yields remain contained, banks disclose limited credit damage, healthcare prices hold and consumer-staples volumes recover. Equal weighting does better than the capitalisation-weighted index, and a broad sector allocation also produces positive returns.
Partial broadening 42% Market breadth improves slowly while sector performance remains uneven. The sector bet tracks the index with lower volatility, and the return comes mainly from selection in banks, healthcare and financing risk.
AI de-rating with falling yields 14% AI cash-flow conversion disappoints and long-term yields fall with growth expectations. Defensives do better in absolute and relative terms, while private-credit and leveraged infrastructure exposures weaken.
AI de-rating with sticky yields 16% The equity valuation reset occurs without a meaningful rally in long-term bonds. Defensives do better than the index but may provide little absolute return, while telecom remains vulnerable to the term premium.
Credit-led unwind 8% Stress in project credit reaches warehouse lines and capital-call commitments, causing an indiscriminate decline in bank equities. Gold and rate hedges are more useful than the equity selection in this branch.

Counter-arguments and Risks

These arguments result from stress-testing our fundamental assumptions.

The strongest counter-case is that AI infrastructure converts rapidly into durable, high-margin revenue. In that outcome, large platforms justify both their capital expenditure and their index weight. Their free cash flow re-accelerates, the cost-of-capital hurdle remains permanently higher for mature businesses, and an equal-weight allocation continues to lag.

A separate risk is that a credit event transmits more broadly than current disclosure suggests. Capital-call lines may appear remote in an ordinary drawdown but become correlated with private-credit and securitisation losses in a deeper stress. The bank-selection work would then fail at the point it is intended to provide protection.

Unresolved Market Factors

Open questions that cannot be conclusively answered using currently available market data.

The first unresolved question is cash-flow conversion. Operating cash flow, capital expenditure, leases, purchase obligations and depreciation disclosures in the next hyperscaler reporting cycle will be more informative than a debate about accounting useful lives. The market can apply a lower valuation per dollar of free cash flow without any formal accounting change.

The second is the rate path during an equity unwind. Earlier defensive episodes were helped by falling long-term yields. A fiscally dominated environment may instead produce a weaker form of protection: relative outperformance with limited absolute return. The first substantial day when investors flee risk assets and the ten-year Treasury yield does not rally will be unusually informative.

What Investors Should Watch

These measures test the allocation logic more directly than a broad claim that sectors are cheap.

  • The weight of the ten largest S&P 500 companies, with a sustained decline indicating a broader market.
  • Hyperscaler operating cash flow against capital expenditure, leases and purchase obligations.
  • Whether AI-related revenue is reported as a distinct line rather than inferred from management commentary.
  • The equal-weight versus capitalisation-weighted S&P 500 spread and whether breadth improves in other concentrated national markets.
  • Regional-bank lending to non-depository financial institutions (NDFIs), including capital-call lines, mortgage-bank warehouse funding and direct specialty-finance exposure.
  • Private-credit fundraising, data-centre financing spreads and reported marks on AI-linked project loans.
  • Consumer-staples unit volume, price and mix, gross margin and private-label share.
  • Healthcare’s index weight, managed-care pricing and utilisation, and evidence of demand in devices and diagnostics.
  • Bank of Japan policy, deposit repricing and capital-return progress at Japanese regional banks.
  • The ten-year Treasury yield and term premium during equity drawdowns.

What Would Falsify the Thesis

The analysis requires revision if these conditions persist.

  • AI revenue converts into sustained high-margin cash flow while capital expenditure and off-balance-sheet commitments stabilise.
  • The largest S&P 500 companies continue to gain index weight while equal weighting lags through a complete earnings cycle.
  • Consumer-staples volumes recover for two consecutive quarters with stable gross margins and durable pricing power.
  • A credit event materially impairs regional-bank book value through capital-call, warehouse or project-finance exposure.

How this analysis is produced

The assessment is produced in several steps. Independent model families answer the same question separately and then attack the results. What you read here has survived several rounds.

  1. Two independent first theses. The same opening question goes to several model families that cannot see one another. Disagreements are kept, not averaged away.
  2. Dated evidence. Every claim that depends on facts is broken into individual search questions and answered with dated, sourced web research. Question, answer, sources and timestamp are logged and remain traceable.
  3. Adversarial review. Several review roles attack the thesis from different angles: one hunts for the strongest refutation, one for the awkward edge cases, one tests whether a path from thesis to share price exists at all, one checks the timeline for contradictions. Each role raises its own questions, which are again answered with evidence.
  4. Merge, then the next round. The surviving theses are merged into one and attacked again. The counter-position and the unresolved tension on this page come out of that step. They were not bolted on afterwards to look balanced.
  5. Back to the start. The process runs again until there is a clear result and a list of tradable companies with structural advantages.

Any analysis can be wrong. That is why the falsification criteria and the counter-position sit on the same page as the thesis, not in the small print.

The numbers shown against individual companies do not come from this process. The Business-Rating scores business-model quality, the Market-Fit-Rating eighteen fundamental figures against the current market, the Cycle-Rating the valuation against the stock’s own history. They are documented under the Leeway scores.

Evaluate the selected companies with the three Leeway ratings

The Business Rating assesses business model quality, the Market-Fit Rating evaluates fundamentals in the current market regime, and the Cycle Rating contextualizes valuation within historical cycles. Evaluate each company with Leeway’s general equity analysis.

Company Valuation and Fundamental Analysis

The data is recalculated on a weekly basis and depends on the current market value of the company and the balance sheet figures of the annual financial statements. The market value changes continuously with price changes, the balance sheets are created annually and change the valuation massively. The time of the annual financial statements and the metrics used can be viewed under "Metrics". Further information on how the analyses work can be found as tooltips directly on the analyses as well as in our explanations.

General

The information is intended to support you in your independent decision-making in implementing investment strategies and serves purely informational purposes. Past performance is not a reliable indication of future performance. No warranty can be given for the completeness, correctness and accuracy of the listed content. The information does not constitute specific investment recommendations. We neither know you nor your financial situation and do not provide investment advice. Only licensed investment advisors with knowledge of your personal circumstances may do this. PWP Leeway UG (limited liability) is not an investment advisor and does not collect any personal data for the purpose of investment optimization. PWP Leeway UG (limited liability) is a provider of investment recommendations and investment strategy recommendations. As such, it is registered with and supervised by the Federal Financial Supervisory Authority (BaFin). The legal notices on the use of the website and the General Terms and Conditions of PWP Leeway UG (limited liability) also apply.

All price data are closing prices of the respective stock exchanges. Price information and master data are provided by an external service provider. Furthermore, public trading data, such as provided by Finra.org, is used to analyze market behavior. No warranty can be given for the completeness, correctness and accuracy of the listed content.

Disclosure of interests: To the best of our knowledge, Leeway and the persons responsible for creating or publishing the respective content do not hold a net long or net short position exceeding 0.5% of the issued share capital of any issuer discussed in that content at the time of publication. There are no other interests or business relationships that could conflict with objectivity, unless expressly stated otherwise in the respective content.

© Leeway
PWP Leeway UG (haftungsbeschränkt)
Leeway Icon