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Actionable insights — ETF Portfolio Update: An S&P 500 Alternative From Omaha

Measuring index concentration by shared driver rather than weight, testing a capex boom by the revenue it must produce, and replacing something by claiming its own selling points.
2026-MAY-10 · Compounding Quality (Substack) · Pieter Slegers / Team Compounding Quality · read ↗ · full analysis · transcript
How to read this page: three genuinely reusable analytical moves here — the correlation-versus-concentration distinction, the AI capex return chain, and the argue-on-the-incumbent's-own-merits structure — plus a currency caution about comparing two portfolios reported in different base currencies. Written post, so no timestamps.

1. Measure index concentration by shared driver, not by weight

The repeatable method
  1. Get the top-ten weight and compare it to the long-run average — that is the starting fact, not the conclusion.
  2. Then classify the top names by what actually drives their earnings, not by their sector label.
  3. Count how many share a single driver. That number, not the weight, is the concentration that matters.
  4. Check the historical analogues on the same basis, so you are comparing like with like.
  5. Then ask what your own portfolio owns that is exposed to the same driver through a different door.
Here: Christopher Bloomstran's point from the AGM. The top ten are "nearly 40%" against a 140-year average of 24% — but "in the past, even when the index was concentrated, the companies were usually not all tied to the same trend or idea." The Nifty Fifty spanned IBM, Coca-Cola, Xerox and Polaroid; in 2000 the top ten still held Walmart, Exxon Mobil and Citigroup, which "had nothing to do with the internet boom." Today: "8 of the 10 are now related to Artificial Intelligence."
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2. Test a capex boom by the revenue it must eventually produce

The repeatable method
  1. Take the industry's annual capital spending as a single number.
  2. Decide what return that capital must earn to have been worth deploying — 10% is a reasonable hurdle.
  3. Convert to required profit, then, at a plausible margin, to required revenue.
  4. Compare with actual revenue today, and with its growth rate.
  5. The ratio between the two is the burden of proof. It does not predict failure; it tells you what has to happen.
Here: "The hyperscalers are expected to spend $700 billion on AI infrastructure in 2026 alone. To earn a 10% return, they would need to generate $70 billion in profit… If AI businesses earn a 10% profit margin, they would need $700 billion in revenue… All AI-related revenue was estimated at only about $40 billion in 2025." Roughly a seventeen-fold gap, stated without claiming it cannot be closed: "AI revenue is growing quickly, but it still is very early in the journey."
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3. To displace a default choice, claim its own selling points one by one

The repeatable method
  1. Write down, honestly, why people choose the incumbent. Do not strawman it.
  2. Take each reason in turn and show whether the alternative matches or beats it.
  3. Only then add what the alternative offers that the incumbent cannot.
  4. Attach a number to the conclusion, sourced rather than asserted.
  5. State the residual reasons someone would still pick the incumbent.
Here: the four reasons for owning the S&P 500 are listed first — diversification, low cost, winners run and losers drop out, and a strong long record — then each is claimed for BRK.B: 26 listed holdings plus 60+ wholly-owned businesses; "there are no management fees to own Berkshire Hathaway stock"; Coca-Cola since 1988 and See's since 1972; and a better long-run record. Then the three extras: businesses "hard for AI to disrupt", $300bn+ of cash, and Greg Abel buying back stock. The number comes from a named third party: Bloomstran's $560-580 against a $475 price.
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4. Explain a valuation metric before you use it, and cross-check it with a second

The repeatable method
  1. State what the metric measures and why its construction matters.
  2. Give the current reading and the historical comparison that makes it meaningful.
  3. Cross-check with an independent measure, so the conclusion does not rest on one construction.
  4. Then link starting valuation to subsequent returns, which is the only reason the level matters.
Here: "The Shiller P/E Ratio, also called the CAPE Ratio, compares a stock's current price to its average inflation-adjusted earnings over the past 10 years. Using 10 years of earnings helps smooth out short-term market ups and downs… Right now, it's over 40. It approaches the valuation we saw before the 2000s dot com crash." Cross-checked on forward PE, and connected to outcomes via the JP Morgan starting-valuation chart. Framed by Klarman: "the price you pay for an investment determines its risk."
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5. Never compare two portfolios reported in different base currencies without stripping the currency out

The repeatable method
  1. Check the transaction currency and the reporting currency for each portfolio.
  2. If they differ, the return contains an exchange-rate move that has nothing to do with security selection.
  3. Restate both in a single currency before comparing.
  4. Report the currency contribution separately, so the underlying performance is visible.
Here: the non-American portfolio shows a 18.4% CAGR ($12,429.24) against the American 13.5% ($11,075.21) — but the European transactions are priced in euros and the profit-and-loss columns are converted to dollars, so a weaker dollar shows up as European skill. The text half-concedes it without naming it: "over time, I expect both portfolios to generate similar returns."
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6. Fix the transaction size and the cadence, so the only decision left is what to buy

The repeatable method
  1. Choose a fixed amount per purchase and never vary it for conviction or for the market level.
  2. Buy on a regular schedule, at the open, announced in advance.
  3. Let the choice of which holding to top up be the single judgement call.
  4. Keep a per-transaction record with the date, price and running return, so every decision is auditable years later.
Here: every one of the 37 transactions across both portfolios, going back to October 2023, is $500 or €500. This month's is MOAT for $500 at $100.80 and GOAT.AS for €500 at €31.61. The published tables carry date, quantity, price paid, current price, current value and profit for each — the best purchase being the January 2024 multifactor buy at +69.35%, the worst the March 2026 minimum-volatility buy at -2.95%, the only loss in either portfolio.
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7. Read your own worst-performing sleeve as a factor reading, not a mistake

The repeatable method
  1. Group holdings by the factor they express — quality, size, minimum volatility, multifactor.
  2. Look at returns by group rather than by holding.
  3. A whole factor lagging is a market condition; a single holding lagging within a working factor is a selection problem.
  4. Decide in advance whether a factor drawdown is a reason to add or to stop, and write the rule down.
Here: USMV is the American portfolio's weakest sleeve — two purchases up only +3.85% and +2.63% — and MVOL.L holds the only losing transaction in either book. Both are minimum volatility. Read against the 7 May Bloomberg chart showing quality down ~25% since Liberation Day while momentum is up ~9%, this is the same factor drawdown appearing in the ETF book — not a fund-selection error.
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Methods distilled from the archived Compounding Quality post for personal study. Not investment advice.