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Actionable insights — Portfolio Update: Buying more?

Naming the product that caused the derating, decomposing an expected return into its two bets, and publishing the losses next to the winners.
2026-FEB-15 · Compounding Quality (Substack) · Pieter Slegers · read ↗ · full analysis · transcript
How to read this page: each insight is a method used in this issue, written so it can be rerun on other names. Written post, so no timestamps.

1. Trace a sector derating back to a specific product release, not a mood

The repeatable method
  1. When a whole sector reprices, look for a dateable event — a product launch, a regulation, a single earnings call — rather than accepting "sentiment" as the cause.
  2. Describe precisely what the new thing does, and to whose revenue line. Here: a tool automating legal, sales and marketing tasks, which are seat-licence categories.
  3. State the market's inference in one sentence so it can be tested: AI agents replace software licences, therefore seat counts fall.
  4. Quantify the damage across named comparables over a fixed window, so the size of the repricing is on the record.
  5. Then decide, business by business, whether the inference actually reaches that company's revenue.
Here: "Anthropic recently released Claude Cowork… Those segments were once the bread and butter of SaaS… Investors worry that AI agents could replace many software licenses." One month: FDS −31%, SPGI −25%, MCO −21%, PAYC −19%.
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2. Publish an expected return with its assumptions separated

The repeatable method
  1. Write the projected return as an equation with named inputs: earnings growth, plus (or minus) the change in the multiple.
  2. Show both numbers explicitly — here, 13.6% Owner's Earnings growth and a multiple moving from 17.1x to 22.0x.
  3. Compute what the return would be on growth alone, so the reader can see how much rests on re-rating. Roughly a third of the 19.3% here comes from the multiple.
  4. Keep a second, more conservative figure alongside it (the 15.0% "expected return for Our Portfolio") so the headline number is not the only one on the page.
Here: "If Our Companies: Grow their Owner's Earnings by 13.6% / Valuation goes up from 17.1x to 22.0x (P/E ratio)… You can expect a return of 19.3% per year on avarage. That's ridiculous."
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3. Publish the profit and loss for every position, not just the winners

The repeatable method
  1. Chart unrealised gain and loss per holding in one image, sorted, with no aggregation to hide behind.
  2. Name the winners doing the work, and let the chart show how few they are.
  3. Leave the largest loss visible and unexplained if you have nothing new to say — the disclosure is the discipline.
  4. Cross-check the picture against the ratings: a name deep in the red and not in the top rating tier is the one to interrogate.
Here: "A few companies will drive the majority of your returns. For us, MEDP, GAW.L, and KPG.AX are doing really well right now" — roughly +$128,000 between them, against EVO.ST at about −$44,000, more than twice the next-worst position and not among the seven Strong Buys.
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4. Separate volatility from risk explicitly, and price the trade-off

The repeatable method
  1. State the alternative honestly: the risk-free return is the return you get for accepting no volatility.
  2. Attach a number to what you are asking for — 10% a year from equities — so the volatility is being bought for something specific.
  3. Make the position falsifiable by keeping it separate from the thesis: volatility being tolerable does not make any particular holding right.
  4. Test yourself against your own disclosure — this page argues volatility is a fee while showing a −$44,000 position.
Here: "Volatility is the price you pay for outperforming the market in the long term… You want a return of 10% per year via stocks? In that case you have to accept volatility." Closing: "If you can't stand the heat, stay out of the kitchen."
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5. Prefer growth that is already contracted over growth that is forecast

The repeatable method
  1. When a cheap stock needs future growth, ask what part of it is already signed rather than projected.
  2. List the agreements with dates and expected revenue, so the growth has a schedule you can check against.
  3. Separate the headwinds into structural and cyclical, and say which you expect to resolve without management action.
  4. Only then look at the multiple; a low multiple on contracted growth is a different proposition from a low multiple on hope.
Here: IPAR — Off-White (first sales 2027), Annick Goutal and Longchamp (late 2026), together "expected to generate over $100 million per year in 3-5 years," against headwinds named as "macro issues, consumer spending, competition, and tariffs."
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6. Reconcile this month's ratings against last month's, and explain the changes

The repeatable method
  1. Keep the Strong Buy list short and publish it in full each month.
  2. Diff it against the previous list and state what moved and why — additions and removals both.
  3. Reconcile the count of holdings against the disclosed weights; a mismatch means the sheet and the book have drifted apart.
  4. Name the holdings that are not rated Buy — "7 strong buys and 8 buys" out of 18 leaves three unaccounted for.
Here: the seven — BRO, KPG.AX, KNSL, TOI.V, CSU.TO, ZTS, NVO — against the six of ten days earlier, which included HGT.L and excluded Zoetis and Novo. No change is explained; the weight chart shows 17 names against a stated 18.
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7. Read position weight as a to-do list, not just a disclosure

The repeatable method
  1. Sort holdings by weight and compare that order against your conviction ranking.
  2. Flag every name where the two disagree — a top-tier rating on a bottom-quartile weight is an unfinished decision.
  3. Act on the gap deliberately, and say so when you do.
Here: CSU.TO is a Strong Buy at roughly 3.75%, one of the two smallest positions in the book. A week later the 22 February issue closes the gap explicitly: "Constellation Software has a low weight of 3.8% within Our Portfolio. It deserves a higher weight, especially at these valuation levels."
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Methods distilled from the archived Compounding Quality post for personal study. Not investment advice.