Stacking two documented premia in one fund, classifying a moat before believing in it, and timing a factor by a relative-valuation ratio rather than by a forecast.
1. Stack premia that are documented separately, and require both
The repeatable method
- Identify two return premia with independent long-run evidence and different causes — here a competitive-advantage premium and a size premium.
- Check the causes really are different; two factors driven by the same thing are one bet.
- Find (or build) an instrument that requires both conditions rather than blending them.
- Quantify each premium and note the source, so the claim can be re-tested later.
- Accept that requiring two conditions shrinks the universe — and check the universe left is still investable.
Here: "Since 2008, the Morningstar Wide Moat Index has beaten the US Market by 4% a year" and "small companies outperform the market by 3% per year." SMOT requires both: the Morningstar US Small-Mid Cap Index, filtered to wide or narrow moats, then to 115 names on momentum and price.
Watch for
- Both figures come from the index providers whose products they justify — treat them as marketing-adjacent evidence.
- Premia measured from 2008 include a specific regime; the size premium in particular has long stretches of not working.
2. Classify the moat by source before you accept that it exists
The repeatable method
- For any company you call durable, name which of the five sources applies: switching costs, intangible assets, network effects, cost advantage, or efficient scale.
- Write the specific mechanism in one sentence, naming the customer and what it would cost them to leave.
- If no source fits, the advantage is probably execution — which is real but not durable.
- Re-test the mechanism when the industry changes; a switching-cost moat can be dissolved by a new integration standard.
Here: one example each — FICO (switching costs: "banks have built their automated loan approval systems around them"), RMS.PA (intangible: "they'll never have the prestige"), V (network: the two-sided loop), COST (cost advantage: bulk buying → loyalty → volume → lower prices), UNP (efficient scale: "a market too small for it to make sense for competitors to enter").
Watch for
- Moats asserted from historical margins alone — high returns are the evidence of a moat, not the moat.
- Ratings agencies' "narrow" category being treated as the same thing as "wide" once it is inside a fund.
3. Test a growth forecast against the absolute money it requires
The repeatable method
- Convert the growth rate into an absolute amount of new revenue or profit.
- Compare that amount to something concrete the company already owns — a division, a product line, a competitor.
- Ask what would have to be invented or captured to produce it.
- Apply the same test in reverse to a small company: the amount needed is often trivially achievable, which is the size premium in one calculation.
Here: a $50m business needs $10m for a 20% year — "a few new enterprise contracts." AAPL needs $80bn, and "iPads and Macs combined generated $62 billion in revenue last year," so it "would have to invent an entirely new category bigger than both." Buffett in 1995: "now we need good big ideas."
Watch for
- The same test applied to your own holdings: BRK.B is used here as the example of growth slowing with size, one week after being upgraded to Buy.
- Large companies that escape the arithmetic through margin expansion rather than revenue — the test is about revenue, and it can mislead.
4. Time a factor with a relative-valuation ratio, not a forecast
The repeatable method
- Build one ratio: the valuation of the factor you want divided by the valuation of the thing it is measured against.
- Plot it over the longest history you can get and mark the mean.
- Act when the ratio is at an extreme, and size the action by how extreme it is — not by a view on when it reverts.
- Add a structural reason the mispricing persists, so you know what would end it.
- Keep buying on the schedule regardless; the ratio decides emphasis, not participation.
Here: SMID-cap forward PE relative to large-cap forward PE at 0.87 against a 1.15 average since 2004, the lowest of the whole series. The structural reason offered is coverage: 11 analysts per SMID security against 26 for an S&P 500 constituent, on a universe where small caps are 51% of listed securities by count. The action taken is small and scheduled: $500 into VB, €500 into IUSN.DE.
Watch for
- Composition drift in the ratio — today's small-cap index carries more unprofitable companies than the 2004 version, which can justify a permanently lower multiple.
- A cheap ratio staying cheap for years; this one has been below average since roughly 2021.
5. Keep a transaction log that shows every purchase, including the losing one
The repeatable method
- Record date, instrument, quantity, price and amount for every purchase — never just the current weights.
- Mark each line to market so the entry price and the result sit side by side.
- Report the portfolio CAGR alongside, so the log and the headline number can be reconciled.
- Leave the losers in the table. A log with no red line is a marketing document.
Here: eighteen American transactions (final value $11,481.46, CAGR 14.8%) and nineteen non-American ones (€12,771.13, CAGR 18.7%), each line showing quantity and entry price. Exactly one is negative: the March 2026 minimum-volatility purchase at €75.72, now €72.74, −3.94%.
Watch for
- A young log flattered by a strong start — the earliest 2023 entries carry most of the gain.
- Averaging into the biggest winner (VB, its fourth purchase) versus into the laggard: the log makes that choice visible, which is the point of keeping it.
6. Look through a fund's label to its actual holdings
The repeatable method
- Read the top holdings and the sector split before accepting the fund's description of itself.
- Ask which screen produced them — a value filter applied after a quality filter will systematically surface cyclicals.
- Check the concentration: what share of the fund is the top ten?
- Decide whether the exposure you are getting is the exposure you wanted, and say so if it is not.
Here: SMOT's top ten — Carnival, Acuity Brands, Masco, Gentex, Block, Bio-Techne, Royalty Pharma, Airbnb, Norwegian Cruise Line, Biogen, each 1.35-1.51%, so under 15% of the fund in total. Two cruise lines and a payments company at the top of a moat fund is the visible consequence of accepting narrow moats and then buying "the best-priced" survivors.
Watch for
- Momentum screens inside "quality" products, which quietly make the fund trend-following at the margin.
- The same look-through on your own book: the archive's other portfolio ETFs are named only in chart labels, without tickers, which makes them harder to check.
Methods distilled from the archived Compounding Quality post for personal study. Not investment advice.