And the name Leopold Aschenbrenner has been circling around for a while, but I think it is safe to say that it has never been trending more than right now.

Share

In 2024, he published an essay series called “Situational Awareness: The Decade Ahead,” arguing that AGI could arrive by 2027 and that the buildout of chips, compute, memory, and energy would be the investment story of the decade.

Then he did something I guess few had expected: he turned the essay into a hedge fund.

Situational Awareness grew from a few hundred million dollars to more than $20 billion in under two years. The fund was backed by names like Jane Street, the Collison brothers, Nat Friedman, and Daniel Gross.

Then… July happened.

AI stocks got destroyed. Core positions in his portfolio reportedly fell 35% to 47%. And because the fund was running leverage (the good ol’ LTCM story comes to mind) reported at around 4x, Leopold got smoked.

The prime brokers issued margin calls. The fund needed cash it didn’t have.

His conviction about AI’s long-term trajectory was correct, and it didn’t matter.

Within roughly a day, the bulk of Situational Awareness’s public equity portfolio, valued around $16 billion before the sale, was sold at a discount.

To the man in the illustration below.

Ken Griffin.

Aschenbrenner tripled his investors’ money in six months. And he still ended up as the forced seller, watching a wily 57-year-old carry his portfolio out the door, halfway through the year.

Subscribe now

The scene-of-the-accident investor

Griffin says he has spent his life “at the proverbial scene of accidents where other firms have gone awry.”

This is his playbook, and he has run it for decades:

Enron, 2001. The day Enron filed for bankruptcy, Griffin chartered a Gulfstream, put 16 people on it, and flew straight to Houston. Not the next week. The day. For several days his team interviewed Enron’s traders. What worked, what didn’t, how the business actually made money, who the best people were. Enron’s own head trader later wrote that Citadel probably interviewed several hundred employees, at every level and every function, essentially reverse-engineering the entire energy trading business through job interviews. Griffin then hired the leadership of Enron’s quantitative research team. He says Citadel has made $30 billion in commodities since.

LTCM, 1998. When Long-Term Capital Management imploded, 30-year-old Griffin went and met with its senior people. His question was specific: how does a levered financial firm lose 90% of its equity and still keep control of its business? He wasn’t gawking. He was taking notes. He has said that what he learned from LTCM’s survival mechanics was “existentially important” to Citadel a decade later.

Amaranth, 2006. Sowood, 2007. E-Trade, 2008. When Amaranth lost $6 billion on natural gas, Citadel and JPMorgan bought the energy book. When Sowood blew up a year later, Citadel took the distressed portfolio. The pattern is so established that when a levered fund gets in trouble, Citadel’s phone number is essentially the first call.

Notice what connects all of this?

Griffin treats other people’s blowups as discounted tuition.

Situational Awareness is simply the latest accident scene. And Griffin arrived, as always, with cash and a checklist.

The veteran’s secret: he was Leopold once

Griffin knows exactly what Aschenbrenner is feeling right now, because in 2008 he lived it.

Share

Citadel lost half its equity in 16 weeks during the financial crisis. This was a firm that had never even had a double-digit drawdown in almost two decades.

Griffin has described riding the elevator down from his apartment one morning thinking;

I hope we’re still in business at the end of the day.

He called Lloyd Blankfein at Goldman and asked when the carnage would end. Blankfein’s answer: a forest fire ends when there’s nothing left to burn.

But Citadel survived. Barely.

In 2008, firms like Citadel and Lehman had bank-like funding without bank-like backstops. Access to credit didn’t just get expensive in the crisis. It ceased. Griffin rebuilt Citadel so it could never again be the one forced to sell.

Which brings me back to what happened last week:

Both men had the same conviction about AI. The difference, however:

• One of them had a capital structure that could survive being right too early.

• The other had 4x leverage and lenders with margin clauses.

You can probably see for yourself which one has the more solid setup.

The machine that Ken built

Research first, always.

Griffin describes Citadel in one sentence: “It’s a research business first and foremost, and trading is simply how we monetize our research.” Whether it’s stock picking or hiring meteorologists to forecast weather for commodity trades, the edge is built before the trade is placed. The trade is just the cash register.

Study your winners.

Griffin argues most investors obsess over their losers and never dissect their winners. His view: you make money in this business when you have winners, so figure out what you got right and do more of it.

Play hardball.

There’s a book Griffin reportedly pushes on people at Citadel, an out-of-print title called “Hardball: Are You Playing to Play or Playing to Win?”

His summary of it: in business, you don’t play to win. You play to win by a landslide, because if you don’t, your competitors come back. The Enron jet story is what that looks like in practice.

Forge talent under pressure.

Citadel got around 100,000 applications last year. Griffin says he’s talking to candidates constantly. And he explicitly values people who have been through fire. His phrase: “It’s the price paid in losses and pain that converts into wisdom.”

Share

Seven things Griffin knows that a 450% return can’t teach you

1. Survival comes before returns.

Buffett says it as “never lose money.” Griffin lives it as capital structure. A 439% half-year means nothing if the structure underneath it can’t absorb one bad month. The first question about any position, any fund, any strategy: what has to happen for me to become a forced seller? If the answer is “a normal correction,” you don’t have a strategy. You have a countdown.

2. Leverage converts being right into being dead.

Aschenbrenner’s thesis is probably still correct. AI infrastructure will likely be built out roughly as he described. At 4x leverage, none of that mattered.

Yes, leverage can amplify returns. But it at the same time hands your conviction to your lender. And your lender has no conviction at all. Only collateral requirements.

3. Study accidents and be opportunistic.

Griffin flew to Houston the day Enron filed. He interviewed LTCM’s people while the scars were fresh.

Most of us read the post-mortem article a year later and move on. The discipline of asking “what exactly killed them, and am I exposed to the same thing?” while it’s happening is free education. This piece is my attempt to do exactly that.

4. Your edge has a half-life.

Griffin’s original edge, using math and software to price convertible bonds, was revolutionary in 1990 and is a free spreadsheet template today. His response was to keep building new edges for 35 years.

Whatever advantage you think you have, someone is commoditizing it right now. The durable edge is the ability to keep finding edges.

5. Adversity is an asset on the buyer’s balance sheet.

Griffin says people who started their careers in 2008 navigate crises “as if it’s a walk in the park” 15 years later. Pain compounds into judgment.

This is also why I’d hesitate to write Aschenbrenner off. The most dangerous version of him is the one that launches in 2029.

6. Position yourself to be the buyer when others must sell.

Griffin got a $16 billion portfolio at a discount because he spent 18 years after 2008 making sure Citadel would always have liquidity when the market doesn’t.

For us small investors, the equivalent is boring: cash reserves, no leverage, a watchlist with prices already decided. The Bunker exists precisely so that when quality goes on fire sale, you’re the one holding the extinguisher and the checkbook.

7. Time is the only filter that matters.

Aschenbrenner ran the most successful fund launch in memory for 24 months. Griffin has compounded for 35 years, and his most profitable years came after year 30. Every truly great record is long before it’s spectacular. Optimize for still being here in 2046.

Share

The twist at the end

Here’s the detail that reframes the whole story, and most of the coverage buried it.

Citadel already owned some of the same AI infrastructure names before this deal. Griffin isn’t betting against Aschenbrenner’s thesis. He’s basically betting on it.

He just structured himself so he could buy the thesis at a discount from someone who couldn’t afford to hold it.

Both men looked at the same future and agreed. The difference between them was never intelligence, and it was never conviction.

Leopold had a thesis. Griffin has a machine. And in markets, over any timeline that matters, the machine eats the thesis.

The question I’m sitting with this week, and the one I’ll leave you with: if your highest-conviction position dropped 40% next month, would you be the one buying more, or the one getting the phone call?

Griffin decided his answer in 2008. Aschenbrenner just got his. Make sure you know yours before the market asks.

Sources: reporting from Reuters, the Financial Times, the Wall Street Journal, Bloomberg, and CNBC on the Citadel and Situational Awareness transaction (July 2026); Ken Griffin’s public interviews, including his talks at Yale, Stanford GSB, the Milken Institute, and the Norges Bank Investment Management podcast; John Arnold’s account of Citadel’s Enron recruitment. Figures on the transaction are based on press reports citing people familiar with the deal and may be revised.

Nothing here is investment advice. It’s one investor thinking out loud in the Bunker.

I still remember the exact moment I opened One Up on Wall Street for the very first time. It was one of the first investing books I ever laid my hands on. The impact it had on my financial education was both immediate and profound. Before discovering Peter Lynch, the stock market felt like an impenetrable casino run by mathematical geniuses and Wall Street insiders.

Lynch shattered that illusion completely.

He taught me a foundational lesson right out of the gate. When you buy a share of stock, you are buying a piece of a living, breathing business. You must train yourself to think like a true business owner. You are acquiring a stake in real assets, real products, and real cash flows.

They are not lottery tickets.

Lynch revealed a brilliant truth that the financial industry actively tries to obscure. We everyday retail investors actually hold a massive structural advantage over the professionals. We have the freedom to look in smaller, underanalyzed ponds where Wall Street is simply not allowed to fish.

Here is exactly how Peter Lynch’s timeless philosophy fundamentally reshaped my approach to the market and how it can help you build serious, generational wealth.

Subscribe now

The Structural Edge in Underanalyzed Ponds

To understand your advantage as a retail investor, you first have to understand the severe constraints placed upon institutional fund managers. Wall Street professionals operate in an environment designed to restrict their freedom. They are relentlessly pressured to produce short-term quarterly performance to keep their clients happy.

Furthermore, massive mutual funds face strict liquidity rules. A fund managing twenty billion dollars simply cannot invest in a brilliant small company valued at fifty million dollars. Even if the fund manager bought the entire company, it would barely register on their overall performance sheet.

They are mathematically forced to buy large, heavily scrutinized mega-cap stocks. They also rely heavily on delayed analyst reports and committee approvals before making a single trade.

You and I face absolutely none of these restrictions. We have the ultimate luxury of patience. We can afford to wait three or four years for a brilliant business strategy to unfold. More importantly, we have the freedom to hunt in the underanalyzed ponds of small and mid-cap companies.

These are the exact spaces where a company can multiply its value ten times over. Finding these “tenbaggers” requires looking where the massive institutions cannot go.

Share

The Art of Observation and Local Knowledge

Your daily routine is the most powerful stock screening tool in the world. As everyday consumers, we interact with products and services long before they ever appear on a Wall Street earnings report.

You might notice a perpetually packed local restaurant chain expanding across your neighborhood. You might see a new software tool that everyone at your office suddenly refuses to work without. You might notice a specific brand of sneakers that every teenager in your city is suddenly wearing. That local knowledge gives you an incredible head start. You are watching a fundamental business trend unfold on the ground in real time.

Lynch also advocated for looking at the most mundane industries possible. He loved boring businesses. He loved waste management companies, funeral homes, and pest control services. These unglamorous sectors face very little competition and receive zero media hype. This quiet environment allows them to steadily compound their earnings over time while the rest of the market chases the latest technology fad.

However, observation alone is incomplete. He is not enthusiastic about this strategy if it is used recklessly. Buying a stock solely based on a crowded parking lot or a tasty sandwich is a guaranteed recipe for financial disaster. Liking a product is simply the catalyst for your research. It is the starting line. You must follow up your qualitative observations with strict financial verification.

You can see a good example of this in my Titan Test series, where I analyse the company Jack in the Box, which on the surface could be seen as a Lynch-style pick, but has fundamentals he would run away from.

Categorizing the Market to Ground Expectations

One of the most valuable lessons I took from Lynch is that you cannot treat every stock the same way. A major flaw among inexperienced investors is expecting every stock in their portfolio to double in price. To avoid this trap, you must categorize different types of companies to set accurate, grounded expectations.

Lynch broke the market down into six distinct categories:

Fast Growers

These are small, aggressive firms expanding their earnings at twenty to twenty-five percent a year. This category is the primary source of the legendary tenbaggers. They carry a higher level of risk, especially if their growth suddenly slows down. However, a portfolio only needs one or two successful fast growers to completely transform its overall return.

Stalwarts

These are massive, established companies that consistently grow their earnings at a moderate pace of ten to twelve percent. Think of global consumer brands and giant pharmaceutical companies. You do not buy stalwarts to get rich quickly. You buy them for downside protection. They provide incredible stability to your portfolio during rough economic recessions.

Slow Growers

These are mature, older companies that have essentially saturated their markets. They grow very slowly, usually matching the overall expansion of the broader economy. Investors buy slow growers primarily for their generous and reliable dividends. Utility companies are the perfect example.

Cyclicals

Cyclical businesses have revenues and profits that rise and fall closely with the natural rhythm of the economy. Airlines, automobile manufacturers, and steel companies fit this description perfectly. Investing in cyclicals requires extreme precision. Timing your entry and exit is everything. Buying a cyclical company at the peak of an economic boom will almost certainly lead to heavy losses.

Turnarounds

These are battered companies actively restructuring or recovering from near bankruptcy. The performance of a turnaround stock is largely untethered from the broader market. If management successfully fixes the underlying business model, the stock price can rebound violently. This category offers high rewards alongside very high risks.

Asset Plays

Asset plays are companies sitting on highly valuable hidden assets that the broader market has completely overlooked. A company might own prime real estate, valuable telecom towers, or crucial patents that do not properly reflect in their current stock price. Investing in asset plays requires deep patience. You have to wait for the rest of Wall Street to finally recognize the hidden value.

Categorizing a company dictates exactly how you manage the position. You will know exactly when to take profits and exactly when to buy more.

Share

The Financial Audit and Quantitative Discipline

Once a company passes your qualitative eye test and you have accurately categorized it, the business must survive a strict financial audit. Lynch popularized the concept of Growth at a Reasonable Price. This philosophy expertly balances the excitement of a growing business with the safety of a fair valuation.

You must verify these exact quantitative metrics before ever purchasing a share:

The PEG Ratio

The Price to Earnings Growth ratio is the cornerstone of this valuation method. To calculate it, you simply divide the company’s P/E ratio by its historical earnings growth rate. You want to target a PEG ratio of 1.0 or ideally lower. A ratio of 1.0 indicates you are paying a perfectly fair price for the company’s future expansion. If a company has a P/E of 20 and is growing earnings at 20 percent a year, the PEG is 1.0. This metric prevents you from wildly overpaying for hyped growth stocks.

The PEGY Ratio

When evaluating mature companies like stalwarts or slow growers, you must account for the cash they return to shareholders. The PEGY ratio modifies the standard formula by dividing the P/E ratio by the sum of the growth rate and the dividend yield. If a company grows at 8 percent and pays a 4 percent dividend, you divide the P/E by 12. Again, you want this final number to remain at or below 1.0.

Balance Sheet Strength

A company with zero debt cannot go bankrupt. It is a simple, undeniable fact of business. You must actively seek out companies with strong cash positions and very low debt obligations. A fortress balance sheet provides essential survival capital during severe economic downturns. It allows the business to crush its weakened competitors while the rest of the industry struggles to survive.

Institutional Ownership

You want the percentage of shares owned by large institutions to be as low as humanly possible. If the massive mutual funds and pension funds have yet to discover the stock, you have a distinct advantage. You can buy in early at a cheap valuation. Once the company continues to succeed, Wall Street will eventually notice. Their massive influx of capital will inevitably drive the stock price up, heavily rewarding early retail investors.

How to actually get a 10-bagger

Capturing a true tenbagger requires a very specific alchemy of small starting size, immense patience, and intense psychological pain tolerance.

You simply cannot get a tenfold return from a mature, trillion-dollar tech giant. You must hunt strictly in the underanalyzed territory of small companies where the math actually allows for massive multiplication.

Once you find a financially sound business with a huge runway for growth, the hardest part begins. You have to essentially do nothing.

You must hold the stock through the inevitable thirty or forty percent drawdowns, ignore every terrifying financial headline, and let the company compound its earnings over five, seven, or even ten years. The math of a tenbagger is remarkably simple, yet the execution requires a level of discipline that very few investors actually possess.

Subscribe now

The Psychology of Winning: Stomach Over Brain

The stock market guarantees heavy volatility. Your favorite stocks will inevitably plummet twenty or thirty percent at some point during your holding period. The broader market will suffer corrections. If you panic and sell your shares during these temporary downturns, your flawless fundamental analysis becomes completely worthless.

You have to trust the numbers. You must deeply internalize the fact that stock prices eventually follow earnings over a multi-year horizon. If the earnings continue to rise, the stock price will follow.

Retail investors must also learn to completely ignore macroeconomic noise. The financial media constantly obsesses over predicting interest rate hikes, inflation data, and the broader direction of the global economy. Lynch viewed this as a massive distraction. Time spent worrying about economic forecasts is wasted energy. You should focus your efforts strictly on the fundamental performance of the individual businesses you own.

Finally, you must stretch your time horizon. The compounding effects of the biggest winners rarely show up in the first few months. The legendary tenbaggers often require three, four, or five years to fully materialize. You have to let the business execute its strategy.

Peter Lynch proved that beating the market is entirely possible for the everyday investor. The opportunities are out there, waiting in those smaller ponds. We have the structural advantage. We have the local knowledge.

We simply need the discipline to do the financial math and the iron stomach to hold our ground.

Hey everyone,

Last month I told you about five businesses I was happy to sit on, and three I wanted to own but wouldn’t touch at the price.

Four weeks later, the portfolio looks meaningfully different.

And the honest reason is that I changed my mind about several of them.

Some of that came from the market handing me prices I didn’t expect. Some of it came from doing more work and concluding that my earlier self was simply wrong.

There’s a strain of investor ego that treats changing your mind as a weakness, as though the job were to be right on day one and never revise. I think that’s exactly backwards. The entire point of doing the work is to update when the work tells you to. Two of the names below I bought above the prices I publicly quoted you last month. One I chose over a business I’d previously called my single most interesting position.

I’ll walk you through each call. Especially the ones where I reversed.

This month I’m running seven positions, and instead of a mini-watchlist I’m handing you two full watchlists with fat pitch triggers and all.

Here’s the short version before the detail:

• A German software business I now bought above the price I quoted you four weeks ago, because re-reading how Buffett bought See’s Candy convinced me I’d been too cheap.

• A life-sciences monopoly trading at a free-cash-flow yield it rarely offers, which I bought after a fellow Substack writer talked me out of my own bias.

• A Latin American compounder I chose over the digital bank I called my most interesting position last month.

• Two serial acquirers I’m holding straight through the drawdown.

• And an aerospace business that just jumped on earnings.

The names and full reasoning are...

Read more

Subscribe now

Most people use AI for investing the same way they have used Google all these years.

They type a question. They get an answer. They move on.

And, well… that is not exactly how you should use it.

With AI, you are able to build your very own research partner, which is much more powerful and valuable than a search engine.

My own research partner, for example, holds sixty years of Buffett’s shareholder letters in its working memory. It has read every letter Nick Sleep ever wrote from the Nomad Investment Partnership. It knows my analytical framework in full: the specific tests I run, the order I run them in, and the exact reasons I reject most companies at the first gate.

Here is how I built it, and how you can build something similar.

Subscribe now

Why most people get this wrong

The generic prompt produces a generic answer.

“Is Medistim a good investment?” tells the model nothing about what framework you use, what return you need, what risks you care about, or what you already own. The answer you get back is the answer you would get from a financial blog written for nobody in particular.

The problem is not the AI itself.

No, the problem is the absence of context.

A model with no instructions will tend to find positives. It is trained to be helpful. But ‘helpful’, without further instruction, usually means agreeable.

That is an awful output for us investors, because we need the opposite.

You need a thinking partner who tries hard to find the reason to say no, who surfaces the argument against the company you are excited about, and who does not move on until the weakest link has been named.

The difference between a generic AI prompt and a properly built research setup is not small. It is the difference between a calculator and a co-pilot.

The context is everything. And the context has to be built.

Subscribe now

The foundation: what goes into the knowledge base

Before I run a single company through the system, three things are loaded into the model’s working memory.

1. My primary sources.

• All of Buffett’s shareholder letters from 1977 to 2019, organised into five clean decade-based files.

• All of Nick Sleep’s Nomad Investment Partnership letters.

• Summaries and transcripts of Berkshire annual meetings spanning 1999 to 2012.

Here is the first practical tip, and it is worth taking seriously: do not use PDFs.

A PDF of sixty years of Buffett letters is too large to upload in one piece, and the text extraction is worse than you think. The model reads compressed, imperfectly parsed text and produces imperfectly reasoned analysis.

The solution is simple. Convert to markdown (MD files).

In the case of the Berkshire letters, split by decade. Five files of eighty pages each upload cleanly, parse cleanly, and the model reasons from them cleanly.

It takes little time, and it is worth it.

By doing this, the model uses your specific, curated selection of primary material, organised the way you organised it. When the model cites Buffett on owner earnings or Sleep on the destination, it cites the letter, the year, and the argument. Not a paraphrase of a paraphrase.

Subscribe now

2. The framework document.

This is the most important file in the setup, and the one most people would never think to build.

This is an instruction set that never changes. It is what turns a general-purpose AI into something that thinks the way I think, applies the tests I care about, and produces output in a consistent format every single time.

If you take one idea from this article, take this one: write your investment framework down before you do anything else with AI. If you do not have a written framework, the model has nothing to apply. The framework is the foundation. Without it, you are just asking questions into the dark.

3. The research library.

Every completed analysis is exported as a clean markdown file and uploaded to NotebookLM. NotebookLM becomes the searchable archive: every company ever analysed, every trigger price ever set, every moat verdict ever written. When a stock approaches a price I set a year ago, I open NotebookLM, find the file in seconds, and read the original work.

This is the compound interest of a research operation. Each analysis makes the library more valuable than the one before it.

I then like to transfer these files to my reMarkable tablet and read the analysis in peace with a strong coffee (or a glass of wine) to get a deeper understanding.

Share

The actual workflow

Here is what happens when a new company comes across my desk.

Step one: the screener.

I export a list of companies screened from a financial data service (I use Börsdata, as I am Scandinavian and mostly look for, and feel comfortable owning Nordic companies).

The screener consists of financial metrics that I like to look for, such as a high ROIC, 5 year avg revenue growth, cash flow and more.

Sometimes the screener find twenty names, sometimes three hundred.

Then I export the results and upload it to Claude and ask for a triage: apply the three gates, reject everything that fails, tell me which eight to twelve names deserve a closer look, and why.

The model works through all of them. It rejects most immediately, with a one-line reason for each. It promotes the survivors with a paragraph explaining what earned them a second look.

What would take me a day of manual work takes the model twenty minutes.

Step two: the financial data.

Once Claude has filtered the screener and highlighted the companies that match my framework, I pull the trigger on the deep dive. I return to Börsdata and download the full financial history for each business. It’s a fantastic Nordic service that exports clean Excel files going back 15 to 20 years (you can use Finchat, Koyfin, or similar services for international stocks).

The model reads the raw data, identifies the correct metric columns, and runs Python to compute the numbers that matter: five-year average return on capital, incremental return on capital, owner earnings net of stock-based compensation, free-cash-flow conversion, gross margin trend over a decade.

Owner earnings is the number that counts. Net income plus depreciation, minus maintenance capital expenditure, minus stock-based compensation always, minus any significant working capital change. Not EBITDA. Never EBITDA. The model knows this because the framework document says so, in plain terms, with the reason behind it.

Share

Step three: the eight-movement analysis.

This is the core. The model runs the full framework.

The grizzly test: could a well-funded, intelligent rival take meaningful market share within five years? If yes, there is no moat.

The Patterson sentence: one sentence naming a specific structural barrier, not “customers like us,” explaining why a well-resourced competitor would find it prohibitively difficult to take share.

The eighteen financial checks, each with a pass or fail and a one-line reason. A single accounting artifact counted once, not as three separate failures.

Three-scenario DCF discounted at 12 percent. A destination cross-check: what does this business look like in fifteen to twenty years, and what are those mature earnings worth discounted back today?

An eight-dimension quality score. An inversion: two or three specific ways this becomes a permanent loss, each told as a short story, each with a named response I have decided on in advance.

The weakest link is named explicitly.

I also feed it additional screenshots and information from other services like Simplywall.st. This service has a great insider transaction and ownership overview for example, which also is factors I look for in my analysis.

Step four: the output.

A clean, self-contained markdown file. Plain language throughout. The verdict at the top. All the numbers in an appendix. A fat-pitch trigger price: the specific price at which the margin of safety is finally wide enough that I would act without hesitation.

The file goes into NotebookLM. The trigger price goes into the watchlist at my broker.

Subscribe now

What the AI does, and what it does not

The model applies the framework consistently. It does not get excited. It does not get tired. It does not skip a check because the business looks obviously good and the next one looks more interesting. Consistency is underrated in investment research, and it is the thing AI does best.

It runs the numbers without arithmetic errors. It structures the output the same way every time. And it plays devil’s advocate: instructed to try hard to reject the company, it finds the argument against. You may still buy the company. But you will have heard the case against it, in full, before you do.

What it does not do: decide whether the moat is real. It surfaces the evidence. The conviction is yours.

It cannot assess management with any texture. It cannot hear the difference between a CEO who is slightly evasive and one who is outright dishonest. It reads transcripts and letters. It does not read rooms.

And it cannot sit through a 40 percent drawdown without flinching, because it does not hold positions. That is temperament, and temperament is irreducibly human.

The AI does the legwork. You do the judgment. Neither works without the other.

Subscribe now

How to start, step by step

Write your framework down first. Even two pages. What do you require of a business before you will look at the price? What do you always check? What would make you walk away?

Then convert your primary source documents to markdown. Paste or export to a text editor, clean the headers, and save as .md. Split anything over a hundred pages into smaller files. Upload them to the AI project you are building.

Then write the instruction document. What should the model always do? What should it never do? What order should the analysis follow? What should the output look like? This file is the difference between a generic assistant and a thinking partner.

Then start the library. Every analysis you complete becomes a file. After thirty analyses, the library is the most valuable thing in the setup.

The process compounds. That is the whole point.

Get the ebook below:

Read more

Most investors never look here.

These companies are small. They trade in kronor and krone, and the research desks that move institutional money cannot build a meaningful position without moving the price against themselves.

But they are of high quality. And an excellent place for investors like you and me to look.

Why Nordic?

A few years ago, a fund called Alta Fox went looking for what actually drove extraordinary long-run returns. They studied over a hundred companies that returned more than 350 percent over five years. The winners clustered in Sweden, the UK, Germany, Norway, and Australia. They were mostly under two billion in market value. They had far less analyst coverage than names of comparable quality on the major US exchanges. And multiple expansion, the market finally repricing a mis-categorised business upward, contributed roughly two-thirds of the median return.

That is not a coincidence.

The Nordics sit at the centre of it.

• Sweden in particular has produced a remarkable density of quality serial acquirers: companies that buy niche industrial or software businesses, decentralise them, and compound the whole at high returns on capital for decades.

• Norway has produced niche medical-device monopolies and insurance compounders.

• Finland has produced diagnostic technology that is sold into operating theatres around the world.

These companies are often the dominant player in a niche nobody has heard of. They are poorly covered. They occasionally get mispriced in ways that a patient, attentive investor can use.

That is the pond I fish in.

What earns a place

The list starts with a hundred names from a screener and ends at thirteen. Most candidates fail immediately.

A name only makes the Nordic Watchlist when it clears every one of these:

A moat I can name in one sentence. A product surgeons would be slightly mad to rip out mid-operation. A certification that took a decade to earn and cannot be replicated in a hurry. A serial acquirer whose process compounds faster than any single business it owns. A market where the number-one position is structural rather than accidental.

A business that generates real cash. Owner earnings, the money a private buyer could actually keep after maintaining the competitive position, not headline profit. Companies that earn large accounting profits while consuming cash are excluded on the first pass.

High returns on capital held for years, not one strong year followed by mean reversion. The test is whether the business earns well on each new krona it reinvests, not just on the base it already had.

A destination. Where does this business land in fifteen to twenty years if management does nothing spectacular? If the answer is somewhere large and reasonably secure, it earns further scrutiny. If the answer is unclear, the analysis stops.

A strong balance sheet. Net cash, or leverage so modest that a bad year changes nothing.

For each name on this list, I work out what a private buyer would pay for the whole business based on the cash it produces, with a discount rate of 12 % and a margin of safety wide enough that a bear case barely loses money. That is the number I'm waiting for.

The part most people skip

Every name on the Nordic Watchlist has a Fat Pitch Price.

It is the specific price at which I would buy without hesitation, because the margin of safety is finally wide enough that I am being paid to be wrong. I do not approximate it. I calculate it on owner earnings, run three scenarios, and state a number.

Most of the time, the price never comes. Wonderful businesses rarely become cheap. The list exists so that when they do become cheap, because of a cyclical stumble, a bad quarter, a sector de-rating, or nothing more than a quiet market with no buyers that week, I already know what I think the business is worth and what I am willing to pay. The decision is made in calm, not in the middle of a drawdown.

Several names on this list are closer to their Fat Pitch Price than they have been in a long time. A few sit within a modest pullback of the trigger. Nordic small and mid-caps have had a difficult 18 months as rising rates and a cautious macro backdrop pushed institutional money toward larger, more liquid names. Some of the best businesses in the region are quietly on sale.

Get the full Nordic Watchlist

Below: all thirteen companies, the moat in one sentence for each, the single thing that would break the thesis, and the Fat Pitch Price with the margin of safety behind it.

This is my own research for my own book, not financial advice. Treat every name as the start of your own work, not the end of it.

Check out the watchlists here:

Read more

I have a confession to make before we get started. I am a quality-compounder guy. I want businesses that earn high returns on capital and reinvest them for a decade. Michael Burry is almost the photo negative of that.

He buys ugly things. He shorts beautiful ones. He has spent most of his public life betting against the very mania that made everyone else feel like a genius.

And I admire him anyway.

I have no desire to trade like him. I never could. What I admire is the temperament. The patience. The willingness to sit alone in a position, be hated for it, and keep sitting there because the math says you are right.

That is rare. Most of us cannot do it for a single week. Burry has done it for years at a stretch, with real money, while the crowd laughed at him.

So let me walk you through how he became a legend. Then let me show you what is worth stealing from him, even if you never short a single stock in your life.

Share

The kid who could not stop reading

Burry was born in 1971 in San Jose. At the age of two, he lost his left eye to a rare cancer called retinoblastoma, and he has worn a prosthetic eye ever since. He has said this shaped him into an observer. A loner. Years later, he recognized that he has Asperger’s after his own son was diagnosed first.

He once described himself with no varnish at all.

“My nature is not to have friends. I’m happy in my own head.”

Most people would probably never say it out loud. Burry says it the way you would report the weather.

He studied economics and pre-med at UCLA, then earned his MD at Vanderbilt. He started a residency at Stanford and never finished it. The reason is the whole man in miniature. He kept staying up at night doing something that had nothing to do with medicine. He was picking stocks.

He once worked so hard on both at the same time that he fell asleep standing up during a surgery.

In 1996, he started posting his investment ideas on a message board called Silicon Investor. The writing was good. Really good. He built a site called valuestocks.net that won a Best of the Web award from Forbes for stock picking, and won it twice. Vanguard noticed him. Joel Greenblatt noticed him. People with serious money started asking this anonymous surgeon-in-training to manage theirs.

That is the part I love. He did not network his way in, and he had no pedigree desk job at Goldman. He wrote clearly about businesses, year after year, and the work spoke for itself. The internet found him.

Subscribe now

Scion, and a fantasy novel

In 2000, he quit medicine and started a hedge fund. He funded it with a small inheritance and loans from his family. His mother put in $20,000. Each of his three brothers put in ten.

He named the fund Scion Capital.

Michael is quite the fan of The Shannara Chronicles, and the name Scion specifically hails from The Scions of Shannara, a 1990 fantasy novel by Terry Brooks.

This is one of Burry’s favorite books. He was nineteen when it was published (The TV show arrived much later, in 2016, and draws from a different Shannara story entirely - although I personally think it was a shame that it got cancelled).

I cannot tell you that Burry sat down and mapped that fable onto his career. I doubt he would claim it. But I read something into the choice anyway, and I think it is fair to. Here was a man who saw himself as an heir to a tradition.

The tradition of Graham and Dodd. Real value investing.

He took up a quest most people thought was foolish, inside a market that had effectively banned his kind of thinking and blamed it for missing the party. He named his life’s work after that idea.

That is what a name is for. It tells you who a person believes they are.

Share

The years that made him

His investing style was old-fashioned and strict. He built the whole thing on one book, Graham and Dodd’s Security Analysis from 1934, and he has said his stock picking is “100% based on the concept of a margin of safety.” He read 10-Ks the way other people read novels. Alone, for hours, in a dark office, hunting for the number that tells you what is actually there underneath the story.

And it worked, fast.

In 2001, the S&P 500 fell almost 12%. Scion was up 55. In 2002, the market fell again, down 22%, and Scion was up 16%. In 2003, the market finally turned and rose nearly 29%, and Burry still beat it, up 50%.

By the end of 2004, he was managing 600 million dollars and turning new money away. A lot of those early gains came from shorting overpriced tech stocks while the dot-com bubble was deflating. He was already running his whole playbook. Buy hated value. Short the fantasy. Wait.

Then came the trade that put his name in a movie.

The Big Short, and the revolt

In 2005, he started pulling apart the subprime mortgage market. He read the actual loan documents stuffed inside the mortgage bonds. He saw loans handed to people with no income and no down payment, then packaged and rated as if they were safe. He concluded the whole structure would come apart once the teaser rates reset. So he did something almost nobody had done. He went to Goldman Sachs and others and asked them to create credit default swaps so he could bet against specific subprime deals.

His own investors tried to fire him.

They did not understand the bet. Housing kept rising. Burry was paying premiums every month on a short that was not working yet, and his clients were furious about it. Some demanded their money back. He had to gate the fund to stop them from yanking it out. Picture that for a second. You have done the work. You are right. And the people whose money you are protecting are screaming at you for protecting it.

He held.

By the middle of 2007, subprime began to collapse, exactly as he had said it would. Scion made 725 million dollars for its investors. Burry personally cleared around 100 million. From its start in late 2000 to the middle of 2008, the fund returned 489 percent net of fees. The S&P 500 returned roughly 3 percent over the same stretch.

Then he closed it. The backlash, the IRS audits, the sheer exhaustion of being right while everyone fought him. He was done managing other people’s money. For a while.

This is the part Keynes warned us about, and Burry actually lived. The market can stay irrational longer than you can stay solvent. Being early and being wrong look identical for a long time, and they only separate at the very end. Most investors never reach that end, because they get shaken out, or talked out, or simply bored out of the position first. His real edge had nothing to do with a secret formula. He could just sit in the discomfort longer than you can.

Subscribe now

Cassandra in the wilderness

He reopened a fund in 2013 as Scion Asset Management. And then he spent the next decade building a second reputation, as the boy who cried crash.

I am going to be straight with you here, because this newsletter does not do hero worship.

A lot of Burry’s big public calls since 2008 have been wrong, or at the very least painfully early. In 2017, he warned of a global financial meltdown. The market rose. In 2019, he said index funds were the next CDOs, a bubble waiting to burst. They kept inflating and never burst the way he meant.

In June 2021, he warned of “the mother of all crashes.” Stocks rallied more than 50 percent from there. On January 31, 2023, he tweeted a single word. “Sell.” The market promptly ripped higher. Two months later, he tweeted, “I was wrong to say sell,” and went on to congratulate the buy-the-dip crowd for their nerve.

One writer tried to actually score his record and figured roughly 71 percent of his major bearish calls since the crisis were wrong on timing or size. The Financial Times described his performance since The Big Short as “distinctly ho-hum.” When he shorted Nvidia and Palantir in late 2025, Palantir’s CEO Alex Karp went on television and called the bet “bat-shit crazy.”

So yes. He gets mocked. Constantly. And harshly, if you ask me. Often by impatient people who treat every tweet as a date-stamped prophecy and then high-five each other when the market climbs the following week.

But look at what the mockers keep missing.

First, Burry picked his own nickname years ago. Cassandra. The priestess in the Greek myth who was cursed to see the future clearly and to never, ever be believed. He chose that name on purpose. It tells you, right on the label, that being disbelieved is the whole job.

The only thing he writes now, the project that has become his entire focus, is his Substack publication: .

Second, the scoreboard depends on what you actually measure. His macro timing calls have a poor hit rate. True.

Third, he said it better than I can when the Wall Street Journal labeled his early calls a failure. Being early and being wrong look identical in the short term and diverge completely over time. One reflects bad analysis. The other reflects the market refusing, for a stretch, to price reality.

I am not telling you Burry is always right. I am telling you the crowd’s way of grading him is lazy, and the man understood that before any of them did, and put it in the name on the door.

Subscribe now

What he just told us

Which brings me to the thing that made me want to write this piece in the first place.

A few days ago, Burry published this note on Substack:

He laid out a simple story. A stock falls from 100 down to 10. That is a 90 percent wipeout. Ouch…

A value investor steps in at 10, because the business is honestly worth around 30.

Then the thing keeps sinking, all the way to 5, because a stock that has fallen that hard stops tracking the business underneath it.

Our investor is now down 50 percent on his buy. He could have bailed at 8 and capped the damage. He sits tight instead.

So, he goes off to medical school, finishes his residency, becomes a surgeon, and a decade later, the stock trades at 30. From the bottom, that is a six-fold return. Roughly 20 percent a year. He says this maps almost perfectly onto Warner Bros. Discovery, and he points out that it usually does not even take the full ten years.

Then comes the line I keep rereading.

If you are sitting on a deep loss, you own that position at today’s price, full stop. Whatever it is worth from here is the only return you will ever earn on it. Dumping it just to make the bad feeling go away, to erase the memory and chase the next shiny idea, is usually the wrong long-term move.

Sit with that one. It dismantles one of the most common mistakes any of us make.

We feel the loss in our chest. We sell to make the feeling stop, right at the point of maximum pain, which is often right before the recovery. The market has no idea what you paid and would not care if it did. Your cost basis lives in your head. The company does not know it exists. The only question that matters is what the thing is worth from here.

I have a private name for my own version of this disease. The hot potato. The urge to sell a good business too early, to lock in some relief, to avoid sitting inside a drawdown. Reading Burry describe the same impulse in a stranger’s voice was uncomfortable in the way good advice usually is.

Share

What to actually steal from him

So here is what I take from Michael Burry, as someone who will never run his strategy:

1. Do the work yourself, in primary documents, until you know the business better than the people talking about it on TV. Burry beat everyone because he read the actual loan files and the actual filings while his competitors read the summaries.

2. Anchor to something real. A margin of safety is a hard number. It is the gap between price and what is genuinely there. Find that number underneath the narrative and build from it.

3. Treat your portfolio as one book, not a pile of tickers. When the headlines screamed that Burry had a “$900 million” short against Palantir, the real premium he had at risk was closer to 9 million. Copying his ticker without understanding the size, the structure, and the duration would have flattened you. The headline is never the trade.

4. Be willing to be hated. The best setups are uncomfortable by design. If everyone already agrees with you, the upside has already been handed out. The money tends to hide wherever the discomfort is.

5. Separate being early from being wrong, then be honest with yourself about which one you are. Burry has been both. The thing I respect is that when he is wrong, he says so out loud, in public, with his name attached. “I was wrong to say sell.” Most gurus would have deleted the tweet and pretended it never existed.

6. And the big one. Once you are down, you own it from here. Stop grieving your cost basis. Ask only what the business is worth now, and let that answer, rather than your feelings, decide whether you hold.

That is the real Burry. Forget the doom tweet and forget the movie. The actual man is stubborn, solitary, and a lot would consider him a little different from the rest.

He reads everything. He trusts his own math over the mood of the crowd. He sizes his bets with care.

And he is perfectly comfortable being the only person in the room who thinks he is right.

Until next time,

— Rob H.

I keep this The Money Mind series free for everyone. The only thing I ask in return is that you share this post with one friend who would find it valuable.

Share

What this guide covers

Scale economies shared is the most powerful business model in long-term investing. The idea is simple. A company earns a cost advantage as it grows. Instead of keeping that advantage as fat margin, it deliberately hands most of it back to the customer as lower prices, better service, or wider selection. The customer notices, and rewards the company with more business. That extra volume creates more scale, which creates a bigger cost advantage, which gets handed back again. The loop turns on itself, and it gets harder to attack every year it runs.

Most moats defend a position. This one widens it. That is the whole reason it sits at the top of the durability ranking.

(At the bottom are links to three full deep dives on live examples of the model: Nu Holdings, MercadoLibre, and Toast.)

One note on the name before we start. Sleep used both “scale economics shared” and “scale economies shared” in his letters. They mean the same thing, and this guide treats them as interchangeable.

Subscribe now

Where did the idea come from?

The phrase belongs to Nick Sleep, but the lineage runs deeper than one man.

Sleep (born in the UK in 1968) studied geography, not finance. He worked as a landscape architect, in department stores, at an IT firm, and as a sponsored windsurfer before joining Sun Life of Canada as an analyst and then moving to Marathon Asset Management in London in 1995.

His partner, Qais “Zak” Zakaria (born in Iraq in 1969), came from Deutsche Bank, where he covered Asian equities. The two met in their late twenties.

Marathon is the part of the story people forget. It was a London shop built around the capital cycle, the discipline of watching where capital floods in (and returns collapse) and where capital starves (and returns recover). Sleep’s mentor there was Jeremy Hosking, one of Marathon’s co-founders. The intellectual habit Sleep absorbed was to study the structural mechanics of an industry rather than guess next quarter’s earnings.

In September 2001, Sleep and Zakaria launched the Nomad Investment Partnership under the Marathon umbrella. It began investing on the 10th, one day before the 11th. They spun it out as an independent partnership in 2006 and closed it voluntarily in 2014 to focus on philanthropy.

The numbers are the reason anyone studies them. Over roughly thirteen years, Nomad compounded at about 20.8 percent a year before fees, against about 6.5 percent for the MSCI World Index over the same stretch. One dollar became roughly ten. They did it with almost no turnover, a handful of names, no leverage, and letters typed in Courier font that they mailed to partners a couple of times a year. By the end the portfolio was concentrated in a short list led by Costco, Amazon, and Berkshire Hathaway.

The seed of the whole framework was a single observation in Warren Buffett’s 2004 Berkshire letter about GEICO. Buffett pointed out that GEICO delivered real money to three groups at once. Customers saved roughly a billion dollars compared to what they would have paid elsewhere. Employees earned a large profit-sharing bonus. Owners earned an excellent return. Those benefits existed only because of scale. Sleep read that and asked a sharper question. If scale produces a pool of benefits, who gets it, and what does the split tell you about how hard the business is to attack?

That question became the robustness ratio, and the company that answered it most beautifully was Costco. Nomad made Costco its largest holding and never stopped writing about it.

Share

The mechanics of the flywheel

Here is the loop in plain terms, using a low-price retailer like Costco as the model.

The business buys in enormous volume, so it buys cheaply. It runs a lean operation, so its costs per dollar of sales are low.

Now it has a choice:

It can pocket the savings as a higher margin, or it can drop its prices.

Costco drops its prices. The customer gets goods cheaper than anywhere else, so the customer comes back and buys more. More sales means more volume, which means even better buying power and even lower costs per unit, which Costco hands back again as still lower prices. Round and round.

Sleep contrasted this with the ordinary “high-low” supermarket, and the contrast is the whole point. The high-low retailer runs an inefficient operation, charges high everyday prices to cover it, then slashes a few items on promotion to pull people through the door, hoping they buy full-price goods while inside. That trains the customer to wait for deals, shop around, and stay disloyal. It also forces the retailer to constantly reprice, and it makes volumes lumpy and unpredictable. The incentives in that system reward exactly the behaviour that hurts the business.

The scale economies shared system rewards the opposite. The customer is trained to trust the price every day and to consolidate spending with the one player who is always the cheapest. Sleep called customer reciprocation a super-factor in business performance, and he meant it literally. It is the engine that makes the loop spin.

Three things follow from this, and each one matters for an investor.

It works far beyond retail.

Sleep pointed to AirAsia, the low-cost Malaysian carrier, whose planes flew fuller than the high-fare flag carriers because low fares filled seats. He pointed to Amazon, whose total cost per dollar of sales (operating costs plus operating margin) was lower than some high-street rivals’ costs alone. That is a brutal fact. It means those rivals could price at break-even and still not undercut Amazon. The model is industry-agnostic. It shows up anywhere a cost advantage can be returned to customers in a way they will reward.

It lowers the probability of failure every year.

This is the single most important property, and it is what separates this moat from all the others. A patent defends a position until it expires. A brand defends a position until taste shifts. A scale economy shared business does not sit and defend. Every year it operates, it grows, the cost gap widens, prices fall further, the customer proposition improves, and the business becomes harder to dislodge than it was the year before. Sleep borrowed Peter Bernstein’s image of a cone of uncertainty that widens the further out you look. Costco’s obsession with sharing savings narrows that cone. The future becomes more predictable, not less, which is precisely backwards from how most businesses age.

Forget about the quarters. The destination is the question.

Because the model compounds its own advantage, the right question is never “what does this earn in year three.” It is “what does this look like as a mature franchise in fifteen to twenty years, and is that destination secured by the loop itself.” If the loop is genuine and the management is committed to it, the annual numbers are noise on the way to a destination you can describe.

Share

Why it beats every other moat

It helps to place the model against the alternatives. A durable business needs a moat. It does not need the most durable type. But when you are hunting for the rare position you can size large and hold for decades, the type matters, and scale economies shared has properties the others lack.

A statutory or regulatory monopoly is close to permanent, but it is static. It defends a fixed position and rarely grows the pond. A switching-cost moat deepens with use, which is excellent, but it locks in customers you already have rather than continuously attracting new ones on improving terms. A network effect is powerful when the leading position is structural, but network density can plateau. A brand commands pricing power, but it leans on advertising, and pricing power is the opposite instinct to sharing scale. Patents alone are weak, since they expire and get designed around.

For an investor with a long horizon, this links straight to compounding. The reason predictability matters is not comfort. It is that a predictable compounder is the only kind you can size to a large weight and then sit through three fifty percent drawdowns to own for twenty-five years. A lottery-ticket business with a huge but uncertain payoff cannot be sized and cannot be held, so you almost never collect it. The scale economies shared business, with its narrowing cone of uncertainty, is exactly the kind you can hold like that. The multiple then falls out of how long the durability lasts. Compound at 20 percent and you have a six-bagger in ten years, a fifteen-bagger in fifteen, and a ninety-five-bagger in twenty-five. The rate is the thing. The multiple is an output.

Share

The robustness ratio: how to measure the moat

This is the part most writing on the subject gets wrong, so it is worth doing carefully.

Sleep wanted a way to put a number on moat strength for businesses that compete on price. The robustness ratio was his answer. It measures how the pool of benefit created by scale is split.

The definition. In its full form, the robustness ratio is the combined distribution to customers and employees (through lower prices, better service, profit sharing, and the like) divided by the distribution to shareholders. In its simpler and more usable form, it is the amount of money customers save divided by the amount shareholders earn. It is, in one line, dollars saved by customers for every dollar kept by owners.

The two anchor cases. Sleep worked out two, and they are the reference points for everything else.

• GEICO sits at roughly 1:1. Customers saved about a billion dollars on their policies compared to the next cheapest carrier, and shareholders earned roughly a billion in underwriting profit. One dollar out to customers for one dollar kept.

• Costco sits at roughly 5:1. Sleep estimated that a Costco member saves about five dollars compared to shopping the same basket at an ordinary supermarket, for every one dollar Costco keeps. The arithmetic ran through Costco’s gross margin of about 11 percent against roughly 23 to 26 percent at a Walmart or a Kroger, adjusted for the membership fee.

So what does the number tell you?

Broadly, the higher the ratio, the harder the business is to attack on a like-for-like basis. A rival trying to take share from Costco has to find five dollars of customer value that Costco is already giving away before it even reaches Costco’s own thin profit. That is a very deep moat to cross.

Where the ratio applies, and where it does not. This is the boundary Sleep drew explicitly, and it is the most common misuse. The robustness ratio is appropriate only when the customer proposition is built on price. Costco, GEICO, a discount retailer, a low-fee financial product. It is not appropriate for a proposition built on advertising or aspiration. Sleep used the example of Nike trainers. Nobody buys Nike to save money, so measuring a price-based give-back tells you nothing about that moat. If the value a business delivers is mostly status, brand, or experience rather than price, the robustness ratio is the wrong instrument, and you should reach for a different moat test.

The interpretation is not “higher is always better.” There is a real tension built into the number. A higher ratio means a wider moat. It can also mean a less equitable split, where the business is handing customers so much that shareholders take very little. Costco’s 5:1 and GEICO’s 1:1 may be equally effective barriers against competition. A ratio even finer than GEICO’s may be perfectly sufficient to repel competitors in some industries. The ratio tells you how hard the business is to attack. It does not, on its own, tell you it is the better investment.

The caveats Sleep attached, which almost everyone drops. He was emphatic that the ratio is a thinking tool. It is plainly not a numerical magic bullet for measuring moats. Four specific warnings travel with it:

• A finer ratio can still be a powerful barrier. The number is not a leaderboard where 5:1 beats 2:1.

• A falling ratio is not necessarily a shrinking moat. It can simply mean the moat is no longer being widened as fast as it could be, while remaining perfectly strong.

• The ratio is most useful for spotting companies that are under-earning relative to their potential. This is its real power, and we will come back to it.

• The split should change for competitive reasons only, never to please the stock market.

Where the ratio earns its keep: spotting the under-earner. Here is the insight that turned the robustness ratio into a money-making tool rather than an academic curiosity. A business with a high ratio is deliberately leaving profit on the table. It is choosing to under-earn today in order to widen the moat and secure a larger, more certain destination tomorrow.

The stock market, which reads reported earnings, sees thin margins and a cheap-looking business, and misprices it. The patient investor who understands the model sees a franchise getting stronger every year while the income statement understates the truth. This is exactly why Costco’s share price went nowhere for years even as the business strengthened, and exactly why that period was an opportunity. The mispricing is the point.

The time dimension. The right split is not fixed for life. Early in a company’s development, it makes sense to reward customers disproportionately, because referrals and repeat business are what build the franchise. As the business matures, the bias can ease, and shareholders can reasonably take a larger slice. Push that too far, though, and the moat drains.

The capital markets will applaud the higher margins right up until growth stalls and the company enters what Sleep called growth purgatory, the place where a highly rated stock falls because investors finally notice that the reported profitability was borrowed from the future. Coca-Cola leaning too hard on its bottlers, Gillette cutting advertising, Home Depot boosting gross margins: these are the cautionary cases of harvesting a moat to feed quarterly earnings.

The harvesting trap is stated as a rule. When you find a scale economies shared business, watch the direction of the split as closely as the level. Margins creeping up while the customer proposition stops improving is the early signal that management has started to harvest the moat. That is the tide going out. It is the thing that ends these stories.

Subscribe now

How to use it inside a full analysis

The robustness ratio is one input, not the whole verdict. It answers a single question well: how deep is the moat for a business that competes on price? It does not tell you whether the destination is large, whether the company can reinvest its cash at a high rate, or whether management is honest. Those are separate tests.

In practice, it slots into the moat work alongside three other judgments.

First, the destination. Where is this business going in fifteen to twenty years? Can you describe it in two plain sentences without hedging, and is that destination secured by the loop itself rather than by a battle not yet won?

Second, the reinvestment runway. A high return on capital only compounds wealth if the business can redeploy its earnings at that high return for a long time. The robustness ratio tells you the moat is deep. The runway tells you whether the engine has room to run. A deep moat around a small, full pond is a fine income stream and a poor wealth builder.

Third, the mispricing. The most valuable setups are the ones where the robustness ratio and the income statement disagree. A high ratio that the market reads as “low margin, mediocre business” is the under-earning mispricing Sleep exploited at Costco.

If you can name the specific wrong heuristic the market is using (cyclical when it is structural, low-margin when it is deliberately reinvesting, stagnant when it is compounding), then you have both a quality thesis and a re-rating thesis in the same name. That is the combination that produces the largest long-run returns, where the growth does the heavy lifting and a multiple re-rating adds a kicker on top as the business proves its durability.

Price still comes last, and it still binds. A wonderful flywheel at a silly price is a watch-and-wait, not a buy. But for a genuinely secured, widening, scale economies shared business, the protection lies in the durability and predictability of the compounding, and demanding a deep bargain entry often just means never owning it at all.

The model in the wild: three deep dives

The clearest way to learn the model is to watch it operate in real businesses. Below are three live examples, each with a full deep dive. They are deliberately different. One is a near-perfect modern copy of GEICO. One is the textbook marketplace-plus-fintech flywheel. One is the honest edge case where the robustness ratio is harder to apply, which is itself the lesson.

Nu Holdings: the modern GEICO of financial services

If you want to see the robustness ratio in its purest modern form, look at Nubank. It built a digital-only bank with a cost to serve a fraction of what Brazil’s incumbent giants carry, and it handed that advantage straight back to customers as free or near-free products in a market long defined by high fees.

Customers reciprocated, mostly through word of mouth, which kept customer acquisition costs low and fed the loop. More customers mean more scale and more data, which lowers the cost to serve and sharpens credit underwriting, which funds an even better customer deal. The give-back is measured in fees the customer no longer pays, which is exactly the kind of price-based proposition the robustness ratio was built to measure. Nubank is the closest thing in this generation to the GEICO that started the whole framework.

Read the full Nu Holdings deep dive →

MercadoLibre: the Latin American flywheel

MercadoLibre runs two reinforcing flywheels at once. The marketplace loop is the classic version: more buyers attract more sellers, which widens selection and pushes prices down, which attracts more buyers. The scale economies shared mechanism shows up most clearly in logistics, where building out fulfilment lowers the per-parcel cost of delivery, which gets handed to buyers as faster and cheaper shipping.

Bolted to that is Mercado Pago, the payments and fintech arm, where rising volume lowers the effective cost of moving money and funds better products. This is a marketplace-plus-fintech compounder, not a passive listings portal, and the distinction is the whole point. The give-back runs through cost, selection, and convenience rather than a simple shelf price, which makes the robustness ratio a directional read here rather than a clean single figure.

Read the full MercadoLibre deep dive →

Toast: where the robustness ratio gets harder

Toast is the most instructive of the three precisely because it does not fit the Costco template cleanly. It is the operating system for restaurants, bundling point-of-sale software, online ordering, payroll, and payments into one platform. The scale loop is real. As Toast grows, it spreads its software investment across more restaurants and processes more payment volume, which lets it offer an ever more capable platform at a competitive, effective cost.

But the benefit it hands back is mostly capability and integration, not a lower headline price. That puts it nearer the boundary Sleep drew, where the proposition is partly about value delivered rather than purely about price saved. The honest read is that Toast blends scale economics with switching costs, and that the robustness ratio is harder to compute for it than for a pure discounter. That is the lesson: the model is a spectrum, and the cleanest measurement belongs to the businesses competing most directly on price.

Read the full Toast deep dive →

Frequently asked questions

Is scale economies shared the same as economies of scale? No. Economies of scale just means costs per unit fall as a business grows. That is common, and on its own it produces a fatter margin that invites competition. Scale economies shared is the deliberate decision to give most of that cost saving back to the customer as lower prices or a better deal, which triggers the reciprocation loop. The sharing is the part that builds the moat.

Does giving savings away just mean lower profits forever? In the short run, yes, margins look thin. That is the point. The business is choosing to under-earn today to secure a larger and more certain destination, and a widening cost advantage means per-share free cash flow can still grow steadily even on flat margins, helped by rising volumes and falling asset intensity. The reported income statement understates the franchise, which is the mispricing the patient investor exploits.

How is the robustness ratio different from gross margin or return on capital? Gross margin and return on capital measure how much the business keeps. The robustness ratio measures how much it gives away relative to what it keeps. A business can have a low gross margin and a very high robustness ratio at the same time, and that combination, low reported profitability sitting on top of an enormous customer give-back, is the signature of a deep and deliberately under-earned moat.

Which companies are scale economies shared businesses? The canonical historical cases are Costco, GEICO, and Amazon. Sleep also pointed to AirAsia. Live modern examples that exhibit the loop include Nu Holdings and MercadoLibre, with Toast as a partial case. The test is whether the business systematically returns its scale advantage to customers in a way that they reward with more business.

Why did Costco’s stock go nowhere for years if the model is so good? Because the market reads reported earnings, a business that deliberately keeps margins thin to widen its moat looks cheap and unexciting on those earnings. The franchise was strengthening the whole time. The gap between the improving business and the flat stock was the opportunity, and it is the clearest real-world illustration of why this model rewards patience.

Can the model break? Yes, in one main way. Management starts to harvest the moat, letting margins creep up to please the stock market while the customer proposition stops improving. The capital markets applaud right up until growth stalls and the stock falls. Watching the direction of the split, not just its level, is how you catch this early.

Key takeaways

• Scale economies shared is a business model where a company hands its growing cost advantage back to customers, triggering a self-reinforcing loop that widens the moat every year it runs.

• It is the most durable moat type because size becomes a weapon rather than a liability, and because it lowers the probability of failure over time rather than merely defending a fixed position.

• The robustness ratio measures the depth of the moat for price-based businesses. It is customer savings divided by shareholder profit. GEICO sits near 1:1 and Costco near 5:1.

• The ratio is a thinking tool, not a magic number. A finer ratio can still be a powerful barrier; a falling ratio is not necessarily a shrinking moat, and the instrument only fits propositions built on price.

• The ratio’s real power is in identifying businesses that are deliberately under-earning, which the market misprices on reported earnings. That mispricing is the source of return.

• The model breaks when management harvests the moat to flatter margins. Watch the direction of the split.

• Predictability is what lets you size a position large and hold it through deep drawdowns, which is how the compounding is actually captured.

Sources and further reading

• The Nomad Investment Partnership letters to partners, Nick Sleep and Qais Zakaria, 2001 to 2014. The primary source for both scale economies shared and the robustness ratio.

• Berkshire Hathaway annual letters, Warren Buffett, in particular the 2004 letter discussing GEICO, which seeded the framework.

• Richer, Wiser, Happier, William Green, 2021, chapter six on Sleep and Zakaria.

• Capital Returns, edited by Edward Chancellor, for the Marathon capital-cycle thinking that shaped Sleep’s approach.

It usually sounds something like this:

I hear this everywhere. I have to admit, the argument sounds incredibly persuasive. It sounds logical, grounded, and reassuring.

Yet, whenever I hear the consensus asserting a fundamentally new era because our spreadsheets are better or our trading apps are faster, a massive warning light goes off in my head. I firmly believe the single greatest blind spot in modern finance involves the assumption of markets as perfectly rational, calculating machines.

The danger today is not that every AI company is fake, or that the largest technology firms are empty shells. The danger is more subtle: investors can be right about the technology, right about the business quality, and still be catastrophically wrong about the price.

We look at forward-looking P/E multiples, we run discounted cash flow models, and we assume the math working on paper guarantees logical behavior from the human beings executing the trades. I think this completely ignores the raw, unadulterated power of human emotion.

When the market narrative eventually breaks, our collective, panicked, reptilian brains dictate the absolute bottom.

Here at Atomic Moat, my goal remains to offer learning, alpha, and entertainment. I want to sit down with you today and really unpack why the math of Wall Street cannot save us from the psychology of Main Street. Let us look at history, let us look at human nature, and let us explore why the modern architecture of the market might actually make the next panic worse.

Share

The Echoes of 1999: Euphoria in the Trenches

People arguing for a fundamentally safer market today often do so by painting a caricature of the late 1990s. Many dismiss the dot-com era as a time of foolishly buying empty shell companies with no business plans. There was plenty of that. I think we must look at real stories from that era to understand the investor mindset.

The people investing back then genuinely believed they were participating in a technological revolution destined to change human history. The crazy part is they were completely right about the technology. Their timing and price evaluations proved disastrously wrong.

Let me give you three specific examples from the 1999 to 2000 era. I believe these examples hold up a perfect mirror to the psychology we see today.

1. The Picks and Shovels Delusion: Cisco Systems

Today, everyone justifies the astronomical valuation of companies making AI chips or building data centers by calling them the “picks and shovels” of the AI gold rush. I think people forget this exact same analogy defined the narrative for Cisco Systems in March of 2000. Cisco made the routers and switches physically powering the internet. The logic was flawless. No matter which dot-com company won, they all needed Cisco’s hardware.

Driven by this undeniable logic, investors bid Cisco’s market cap up to $555 billion, briefly making it the most valuable company on Earth.

Its Price-to-Earnings ratio blew past 100. People said the earnings were real and the margins were incredible. Here is the fascinating part. The investors were completely right about the business. Over the next twenty years, the internet changed the world, and Cisco’s earnings actually grew substantially. Yet, an investor buying Cisco at the peak of that rational, logic-driven euphoria in 2000 saw their stock plummet by over 80 percent when the bubble burst.

It took more than two decades for the stock to merely get back to its year-2000 price. Having real earnings and real margins did not save investors from the devastating effects of a contracting multiple.

2. The Liquidity Mirage: TheGlobe.com

We often think today’s retail investors are unique in their ability to drive up speculative assets quickly. I believe we need to remember the IPO of TheGlobe.com in November 1998. It was one of the earliest social networking companies. The underwriters priced the shares at $9. When the market opened, the pent-up retail demand was so ferocious that the first trade executed at $87. It hit $97 by the afternoon and closed its first day of trading up 606 percent.

The founders became paper multi-millionaires before lunch. The financial press hailed it as proof of a new paradigm where retail investors could instantly recognize value the stodgy Wall Street banks had missed. A few years later, the stock was trading for pennies and faced delisting. The retail investors buying at $87 because of FOMO were completely wiped out. The speed of the market merely accelerated their demise.

3. Ignoring the Unit Economics: Pets.com

I think the details of Pets.com are what truly matter. Pets.com famously raised $82 million in its IPO in early 2000. They bought a $1.2 million Super Bowl ad. They possessed a wildly recognizable brand with the sock puppet. They were selling heavy bags of dog food online and shipping them via FedEx, meaning they lost money on literally every single transaction. In 1999, the market completely ignored the unit economics. Analysts invented new metrics, arguing sufficient “eyeballs” and market share would miraculously produce profits later. Less than 300 days after going public, Pets.com entered liquidation.

I look at the massive, multi-billion-dollar losses being subsidized today in the name of capturing the AI infrastructure market, and I see the exact same psychological mechanism at work. We are once again willing to forgive horrific current unit economics in exchange for a utopian vision of future dominance.

Subscribe now

The Dangerous Myth of the Rational Shock Absorber

I spend a lot of time thinking about the structural changes in the market over the last twenty years. Perhaps the most significant shift involves the massive, systemic migration of capital out of active management and into passive index funds and ETFs.

I think a lot of investors view this as a stabilizing force. They see it as a giant, unfeeling shock absorber for the financial system. The logic suggests trillions of dollars locked up in passive vehicles tracking the S&P 500 or the Nasdaq-100 insulates us from the emotional, manic day-trading of the past. Algorithms do not feel fear. They do not get sweaty palms, they do not panic upon reading a terrifying headline, and they do not sell because of a bad quarterly earnings call.

I believe this theory possesses a fatal, catastrophic flaw. It completely separates the tool from the user. Algorithms remain emotionless, whereas the human beings holding those index funds absolutely feel fear.

When the market narrative eventually shifts, human psychology takes the wheel. As Howard Marks always reminds us, the pendulum forever swings from flawless optimism to crushing pessimism.

We know from decades of behavioral economics that the pain of losing money is roughly twice as intense as the joy of making it. This principle of loss aversion is incredibly powerful. When everyday investors see their 401(k)s and brokerage accounts bleeding red week after week, they log in and hit the “sell” button.

At that exact moment, the supposed shock absorber instantly transforms into a turbocharger for the crash. The fund managers at institutions like Vanguard, State Street, or BlackRock do not sit down to analyze a tech giant’s balance sheet or evaluate its long-term cash flow before selling. They are mechanically and legally obligated to liquidate the underlying shares to return cash to their panicked clients. This selling is entirely blind, completely indiscriminate, and completely merciless.

A company could be generating record-breaking free cash flow, and its shares will still be dumped onto the open market because the ETF redemption mechanism demands it.

I think we also need to address the illusion of modern liquidity. People genuinely believe they are safer today because they can maneuver quickly with zero-commission apps on their phones. In my experience, liquidity acts like a coward.

It is incredibly abundant when the market is rising and everyone is eager to buy. The moment real panic hits, the buyers evaporate. Trying to exit a collapsing market on a smartphone resembles trying to evacuate a burning stadium through a single, narrow turnstile. Your lightning-fast connection speed merely ensures you and ten million other investors hit the bottleneck at the exact same millisecond.

Share

The Fast-Track Danger: The SpaceX Experiment

To see how this mechanical risk is actively forced onto the average investor, I think we should look at a real-time example. The colossal IPO of SpaceX is fascinating.

SpaceX represents the ultimate test of our modern market infrastructure. In the past, a company had to undergo a lengthy maturation period in the public markets to prove its stability before gaining an invitation into the major indices. Tesla went public in 2010. It only gained entry into the S&P 500 ten years later. It had to prove its survival capabilities.

Today, the rules have been altered to accommodate the hype. Major index providers now facilitate fast-track inclusions for mega-cap companies. I find this deeply concerning.

Shortly after SpaceX went public, large passive index funds were mathematically forced to purchase gigantic quantities of the stock to reflect its market weight. Millions of everyday investors, through their retirement accounts, automatically became shareholders at the absolute peak of the IPO frenzy.

This entire process bypasses any individual choice, due diligence, or risk assessment.

I believe SpaceX hitting a speed bump will have massive consequences. If the AI rollout faces delays, if the energy infrastructure costs spiral out of control, or if the technology simply fails to monetize as aggressively as projected, the resulting valuation collapse will severely hurt risk-hungry Silicon Valley venture capitalists and everyday investors alike. The passive ETF system will distribute that devastating, multi-hundred-billion-dollar loss directly into the pensions and savings of the broader public. The machine forces us to buy the top.

The Ape in the Room: NFTs and Unchanged Human Nature

It always strikes me as deeply ironic how the investment class of the 2010 to 2024 era spent so much time mocking the naive speculators of 1999. We looked back at the dot-com bubble and laughed at people buying companies with zero revenue based on clicks. I believe we spent the last decade building our own bubble, wrapped in a more respectable vocabulary. We stopped talking about eyeballs and started talking about quality software, recurring revenue, and total addressable markets.

The underlying delusion remains identical, regardless of what we buy in the markets. We believe an asset is a must-buy regardless of its price.

If you want undeniable, irrefutable proof of human rationality acting as a thin, fragile veneer, I think we only need to look back a couple of years to the NFT craze. Anyone arguing investors are more educated today must explain the Bored Ape Yacht Club.

In January 2022, the pop star Justin Bieber purchased a digital asset. He bought Bored Ape Yacht Club #3001. It was a cartoon JPEG of a sad-looking ape with tears in its eyes. He paid 500 Ethereum for it. At the time, that was the equivalent of roughly $1.3 million.

Let that sink in for a moment. A human being spent 1.3 million real, tangible dollars on a hyperlink to a PNG file. There was no cash flow here. There was no intrinsic value. There was no balance sheet, no physical asset, and no fundamental logic.

No, this was driven entirely by raw greed, the desperation of FOMO, and the greater fool theory. People dressed it up in the techno-utopian language of Web3 and the blockchain.

By the summer of 2024, the floor price of the Bored Ape collection had absolutely cratered. That $1.3 million ape suddenly traded for around $50,000. That represents a wipeout of over 96 percent.

To look at that psychological phenomenon involving billions of dollars globally and confidently claim today’s equity markets are governed by cool, educated rationality seems willfully blind to me. Human nature simply has not evolved since the Dutch tulip mania of the 1600s or the South Sea Bubble of the 1700s. We do not possess fundamentally different brains. We just have faster Wi-Fi and better pitch decks now. When the money is easy and your neighbor gets rich quickly, the logical part of the human brain simply shuts down.

Share

The Prophets of the New Paradigm

The 1999 bubble had its star analysts like Henry Blodget, who became a financial pop star overnight by predicting Amazon would hit $400 and projecting endless upside. Today’s tech boom has generated its own prophets. Back then, the company was nothing more than a digital bookseller, yet after debuting at a mere $9 a share the previous year, the stock was already trading at $240.

But today’s investors are seemingly smarter. We know that a traditional Wall Street analyst can be wrong and is heavily compensated to be bullish. We pat ourselves on the back for ignoring the suits, searching instead for the “right” people with the “right” insider knowledge. Today’s tech boom has generated its own completely new breed of prophets.

Today, I think we need to look at figures like Leopold Aschenbrenner. He is a brilliant AI researcher and a valedictorian from Columbia at age 19. He worked on OpenAI’s superalignment team. After leaving OpenAI, he published a massive 165-page manifesto called “Situational Awareness,” predicting the arrival of Artificial General Intelligence by the end of the decade. He then launched his own investment fund, backed by Silicon Valley royalty, pouring billions into the physical infrastructure required for AI, including power grids, cooling systems, and retrofitted crypto-mines.

His logic is incredibly compelling. His intellect is undeniable. His essays are masterful. I believe this exact dynamic perfectly illustrates how bubbles inflate. A visionary paints a mathematically plausible, highly optimistic picture of the future. The narrative takes hold, the capital floods in, and the market immediately prices the infrastructure companies as if that utopian future is already a historical fact.

The narrative completely replaces the calculator. When that narrative takes hold, investing morphs into participating in a religion.

The Floor is Real, and the Drop is Brutal

So, where does this leave us? I am often asked if things are fundamentally different today.

I think in one very specific, structural way, they are. Today’s tech mega-caps actually generate hundreds of billions in real cash, vastly differing from the empty shell companies of 1999. Microsoft, Apple, Google, and Meta are monetary fortresses. There is a fundamental floor to the market today. If prices fall far enough, massive corporate share buyback programs and deep-pocketed value investors will eventually step in and halt the slide. The companies will not go to zero.

But I believe that floor on a lot of companies sits terrifyingly far away from where we are trading today.

Let us do the math on multiple contraction. If a market darling is currently trading at 40 times its earnings, and a panic-driven recession shifts investor sentiment back to a historical, rational average multiple of 15, the stock drops by over 60 percent.

That catastrophic drop happens even if the company’s actual earnings stay exactly the same. The business can remain perfectly healthy and continue to grow. Meanwhile, the valuation multiple gets entirely wiped out. That premium we pay for hope, euphoria, and the illusion of a new paradigm simply disappears.

That is the incredible danger of buying anything at any price. An investor can be completely right about the quality of the company and simultaneously lose more than half their money because they were wrong about the psychology of the market.

Subscribe now

Surviving the Cycle

Navigating an environment like this requires a very delicate balance. Recognizing the fragility of the market requires careful navigation rather than blindly running in the opposite direction. Aggressively shorting a euphoric market is a fantastic way to destroy your capital. I am not enthusiastic about this strategy if it is used recklessly. The market can remain irrational far longer than any of us can remain solvent. Attempting to time the exact top is a fool’s errand.

Instead, I believe true alpha right now is found in maintaining a profound, humble respect for human irrationality. It means keeping your head when everyone else is losing theirs. It means understanding that when the tide turns, your passive index funds will offer no protection. The fast-tracked mega-caps will fall just as hard as the rest, and the compelling narratives of today’s market prophets will be entirely rewritten in the financial press overnight.

The spreadsheets, the DCF models, and the corporate margins are all very real. When the fire alarm gets pulled, all of those metrics become irrelevant. The tools of modern finance have become entirely digital. The fear that ultimately drives them remains profoundly, dangerously human.

Stay aware. Stay grounded. Remember that in investing, history rarely repeats itself exactly, yet it almost always rhymes.

Share

Disclaimer:

This is an opinion piece and not financial advice whatsoever. I am just a random guy on the internet with opinions. DYOR. And be careful with your money.

Once or twice a week, someone asks me the same thing. What is actually on your watchlist?

A list of great companies is the easy part. The hard part is that a great business and a great investment are not the same thing.

Overpay for a wonderful company, and you can sit on a flat result for a decade while it does everything right. Most watchlists tell you what is good and go quiet on what it is worth.

This one does both.

How I find them

I fish where the big funds cannot follow. Neglected smaller companies in places like Sweden, the UK, Germany, Norway, and Australia, mostly under a couple of billion in value, with thin analyst coverage and a founder who still owns a large slice.

Then I screen for the things that do not lie: a high return on capital held for years, earnings that turn into real cash, little or no debt, and profits being put back to work rather than paid away.

What earns a place

The screen hands me a hundred maybes. Almost all of them fail.

A name only makes the list when it clears every one of these:

• A founder or owner-operator still in the chair, with their own money on the line, not a hired hand collecting options.

• A moat I can name in one sentence. A product a customer would be slightly mad to rip out, a network that gets stronger as it grows, a niche monopoly in something like medical devices, or a serial acquirer that compounds by buying well.

• A balance sheet strong enough that the company controls its own fate.

• A long runway, room to keep reinvesting its own profits at a high rate for

  years, rather than a pond already fished out.

• A reason competitors lose. Ideally, a moat that widens as the business grows instead of one it has to keep spending to defend.

The part most people skip

For every company on the list, I publish a Fat Pitch Price.

It is the price I would pay today, no hesitation, because the margin of safety is finally wide enough that I am being paid to be wrong. I reach it the slow way, and then I wait, often for years.

Most of the time, the price never comes.

As I write this, several of these companies are closer to their Fat Pitch Price than they have been in a long time, and one or two sit within a modest pullback of it. That is rare. For most of the past few years, this list has been a waiting room. Right now, a few names are stirring.

Get the full list

The names, the rankings, the Fat Pitch Price for each one, the margin of safety behind it, and a plain note on why each moat holds and the one thing that would break it are below for paid subscribers.

This is my own inventory for my own book, not financial advice. Treat every name as the start of your own work, not the end of it.

Read more

You’ve probably never heard of him. And if you have, maybe his name is somewhat familiar, but you don’t know much about him besides that.

That’s partly because he doesn’t do interviews, doesn’t chase headlines, and reportedly shows up to the office looking like he’s been sleeping in his car. But since taking over the Contrafund in 1990, he has outperformed the S&P 500 by roughly 2% a year, every year, across dot-com bubbles, financial crises, and a global pandemic.

Two percent doesn’t sound dramatic. Here’s what it does to money over time: $10,000 invested with Danoff in 1990 is worth roughly $250,000 today.

The same money in an index fund gets you around half that.

The gap between “good enough” and “slightly better, sustained forever” turns out to be a quarter of a million dollars.

So. What’s the idea?

Subscribe now

He Learned One Thing From Peter Lynch, And He Never Forgot It

Danoff joined Fidelity as an analyst in 1986, four years before taking over the Contrafund.

His mentor was Peter Lynch, who ran the Magellan Fund to legendary returns and then retired at 46 because he’d made enough money and wanted to watch his kids grow up, which is frankly the most correct decision anyone has ever made, if you ask me.

Lynch’s lesson to Danoff was deceptively simple: a stock is not a ticker symbol. It’s a piece of a business run by actual human beings.

Those human beings have ambitions, blind spots, competitive instincts, and varying degrees of ability to allocate capital intelligently. Your job is to figure out which ones are exceptional before everyone else does.

Danoff took this and ran with it. He spent years cold-calling executives, sitting across from CEOs in conference rooms, asking the same questions over and over: Where is your growth coming from? What would have to be true for you to double earnings in five years? Who in your industry scares you, and why?

He wrote everything down. In composition notebooks. By hand. Thousands of them over thirty-plus years.

This is either inspiring or slightly alarming, depending on your personality. Either way, it worked.

The Only Metric That Actually Matters (According To Danoff)

Here is the entire Danoff investment thesis, compressed into one sentence:

That’s it. He calls this the Earnings North Star, and it’s his true north on every single investment decision he makes.

Now before you roll your eyes; yes, “buy good businesses” is obvious advice. The non-obvious part is what Danoff is willing to pay for those businesses, and how long he’s willing to wait.

Most investors look at a stock trading at 30x earnings and recoil. That’s expensive. They gravitate toward the stock at 15x earnings. It feels safer. It feels responsible.

Danoff does the opposite. Here’s his logic:

Company A: 15x earnings. Slow growth. Management focused on defending turf and paying dividends. This looks cheap.

Company B: 30x earnings. Growing earnings at 20% a year. Management is aggressive, hungry, eating market share for breakfast. This looks expensive.

Fast forward five years. Company B has compounded its earnings substantially. At 20% annually, earnings roughly 2.5x over five years. That 30x multiple? It’s been absorbed by the growth. The stock price has reflected the new earnings reality and moved considerably higher.

Meanwhile Company A is still trading at 15x its stubbornly flat earnings, exactly where you left it.

The “expensive” stock was actually the cheap one. The “safe” stock was the trap.

Danoff has been making this trade, in various forms, in various sectors, for thirty-five years.

Share

The Part Nobody Talks About: He’s Also Willing To Be Wrong And Move On

Here’s what separates Danoff from a lot of growth investors: he has no ego about his positions.

When the thesis breaks, he leaves.

When a sector’s earnings momentum shifts, he reallocates.

He rode retail giants through the 90s. He moved into software and tech as they became the dominant earnings engines of the 2000s and 2010s. He didn’t stay loyal to any industry because he’d built a position there. His only loyalty is to the earnings trajectory.

This sounds obvious. It is almost impossible to actually do in practice. Most investors hold declining positions too long because selling means admitting you were wrong, and admitting you were wrong feels terrible.

Danoff essentially treats this feeling as irrelevant data. The notebook doesn’t lie.

Either the thesis holds or it doesn’t.

The Awkward Part: Size

Managing $130 billion is not like managing your ISA.

When you decide to sell a position, you click a button and it’s done. When Danoff decides to trim a multi-billion-dollar holding, he has to do it over weeks.

Slowly, algorithmically, carefully. Because if he moves too fast he crashes the price against his own shareholders.

This is called the liquidity trap, and it’s a genuine constraint that gets worse as a fund grows. It’s the main reason some great investors cap their fund sizes or close to new money entirely. Danoff never did, which means he’s been operating with one hand partly tied behind his back for decades.

The 2008 financial crisis is the stress test that matters here.

The Contrafund dropped around 37%. On a $100 billion fund, that’s tens of billions of paper wealth gone in months. The question in that moment isn’t whether your spreadsheet is right. The question is whether you can look at the carnage, go back through your notebooks, verify that your best businesses still have dominant competitive positions, and hold.

He held. The subsequent decade rewarded him considerably.

Subscribe now

Three Things You Can Steal From Danoff Today

1. Write The Thesis Before You Buy Anything

Before deploying capital into any stock, write down (by hand if you’re feeling ambitious) exactly how this company doubles its earnings in the next five years. Not “the sector is growing” or “management seems good.” The actual mechanics. What markets are they entering? What’s the margin expansion story? What does the competitive landscape look like in five years?

If you can’t write two coherent paragraphs answering that question, you don’t have an investment thesis. You have a vibe. Vibes are not a portfolio strategy.

The notebook discipline also does something else: it gives you a document to return to when the stock drops 20% and you’re panicking.

Either the thesis still holds — in which case you hold, or buy more — or it’s broken, in which case you sell. The notebook removes emotion from the decision because the decision was already made when you were calm.

2. Ask The Competition, Not The Company

Corporate investor presentations are designed to make you feel good about investing. They are professionally produced optimism. Don’t trust them as your primary research source.

Instead, find the company’s fiercest competitor and read their filings, their earnings transcripts, their risk disclosures. Pay attention to how they talk about your target company.

If a direct rival grudgingly acknowledges that a competitor is winning, and that they’re losing customers to them, that their technology is better, that their sales team is everywhere… that’s more valuable than any glossy slide deck.

A begrudging compliment from a competitor is one of the best buy signals available to retail investors, and almost nobody does this.

3. Do The Annual Thesis Audit

Once a year, go through every position you own and ask one question: Is the original reason I bought this still true?

Not “is it down, so maybe I should wait to break even.” Not “I’ve held this so long it feels like part of my identity.” Just: is the thesis intact?

If yes, hold. If no, sell. Don’t wait for a recovery that may not come.

This is the one Danoff habit that most directly translates to individual investors and the one most people will refuse to do because it requires confronting decisions they’d rather not think about.

Share

The Human Being Behind The Fund

Danoff is famously not what you’d expect from someone managing this much money.

No bespoke tailoring. No exclusive clubs. Colleagues describe him as carrying a permanent air of barely-contained urgency:

Pockets stuffed with earnings reports, notebooks under his arm, scheduling 6am calls with obscure small-cap CEOs and then running straight into meetings with Silicon Valley founders in the afternoon.

He applies the same level of obsessive scrutiny to a $50 million position as to a $5 billion one.

His edge was never a proprietary model or a better Bloomberg terminal. It was the volume and quality of conversations he had with the people running businesses, sustained across decades. Somewhere in those notebooks is a record of almost every important public company in America, as seen through the eyes of their management teams, captured in real time.

That’s not a system you can automate.

Is This Strategy For You?

Yes, if:

• You can genuinely hold a stock for 5-10 years without checking it every morning

• You’re comfortable owning companies that look “expensive” by conventional metrics

• You can sit through a 30-40% drawdown without selling, because you’ve already written down why you own it

• You find businesses genuinely interesting rather than just as instruments for making money

Probably not, if:

• You need dividend income from your portfolio

• You enjoy trading actively and would go insane holding the same 20 stocks for a decade

• You want to time macro cycles and rotate between sectors based on economic forecasts

• You’ve never once read a company’s annual report and have no plans to start

The honest summary: Will Danoff is a growth investor who is better at growth investing than almost everyone else, sustained over an almost implausibly long time period. The edge isn’t a secret formula. It’s discipline, a notebook, an obsessive personality, and thirty-five years of talking to the people who actually run businesses.

The notebook you can start tonight. The thirty-five years, unfortunately, you’ll have to earn.

New to The Atomic Moat? If you want more multibagger lists such as this sent to your inbox, join 1,500+ other investors below.

Subscribe now

First, let’s kill the word

“Multibagger” is a clickbait word. I know it, you know it, and the algorithm knows it. So let me defuse it before we go any further.

A multibagger is a business that compounds its value at a high rate, held for a long time. That’s it. The multiple is arithmetic, not magic.

Watch how fast the arithmetic runs. A business that compounds intrinsic value at 20% a year turns into roughly a 6-bagger in ten years, a 15-bagger in fifteen, and a 95-bagger in twenty-five.

Berkshire became one of the great 100-baggers of all time the boring way: it compounded at around 20% for sixty years. Buffett bought predictable, wonderful businesses at fair prices and then did the hardest thing in investing, which is nothing.

“The big money is not in the buying and the selling, but in the waiting.” — Charlie Munger

So when I screen for “multibaggers,” I am really screening for three ingredients, and I want you to use the same three on every name below:

1. A durable compounding engine. A high return on capital that the business can actually reinvest, not just earn once. The return on the next dollar is what matters, not the average return on the dollars already spent.

2. A long runway. Room to keep redeploying cash at that high rate for a decade or two. A brilliant business with no room to grow is a lovely dividend stock and a poor wealth-builder.

3. Hold-ability. Enough predictability that you can sit through the three 50% drawdowns every one of these will hand you without selling at the bottom. This is the ingredient everyone ignores, and it is the one that actually decides whether you collect the multiple or just admire it from the exit.

There is a fourth thing that turns a good return into a spectacular one, and it is not what most people think.

For a real long-run winner the growth does the heavy lifting, tens of times over. The multiple re-rating is a 2x to 3x kicker on top. That kicker is not bargain-hunting. It is the market slowly admitting it had the wrong label on a business, and the day it admits that is the day your thesis pays you twice.

One last thing about where these live. A famous study of 104 stocks that returned more than 350% over five years found the winners clustered in Sweden, the UK, Germany, Norway, and Australia, with thin analyst coverage, and 84% of them started under $2 billion in market cap. Small, neglected, developed-market businesses are the pond.

Five of the seven names below are fishing in exactly that water. Two are not, and I will tell you which.

Disclaimer: All content is for informational and entertainment purposes only and does not constitute financial advice.

Subscribe now

The seven

These come in three flavours.

The compounding machines own the process of getting bigger. The fallen quality names are good businesses the market has thrown out with the bathwater. The asymmetric bets are smaller, spicier, and more binary, where the upside is large and so is the way you can be wrong.

Let’s get to it.

1. Teqnion (TEQ)

Building something for the next 100 years

What it is

Teqnion is a Swedish serial acquirer. It buys small, profitable, gloriously dull industrial companies, the kind that make connectors, transformers, lab equipment, and indication systems for military practice shooting, and then it leaves them alone to keep doing what they were already good at. Founder and CEO Johan Steene talks openly about building a company that lasts a hundred years, and he runs it like someone who means it: decentralised, cash-focused, allergic to head-office empire-building.

The numbers today

The stock trades around SEK 158, for a market cap near SEK 2.5 billion, which is about $255 million. Full-year 2025 revenue was roughly SEK 1.8 billion with net income near SEK 98 million, putting the shares around 28 times earnings. There is no dividend, by design. Every krona that comes in goes back out to buy the next business. The stock is up modestly over the past year and has spent twelve months bouncing between SEK 136 and SEK 189.

The runway

This is the part that matters. There are tens of thousands of small, owner-run industrial niche businesses across the Nordics and Europe whose founders will eventually want to retire and sell to a good home. Teqnion is a rounding error against that universe. A serial acquirer this size does not have a TAM problem; it has a “can we keep finding good deals and not overpay” problem. The engine is the acquisition process itself: the culture, the discipline, the decentralisation. The product could change entirely and the moat would still be there.

Why it could be a multibagger

The model is proven. Constellation Software, Lifco, Lagercrantz, and Indutrade all turned the same playbook into double-digit-to-twenty-percent per-share compounding for decades. Teqnion is early on that curve and small enough that its size edge is real, which is exactly the combination the data says you want. If Steene keeps buying well, a small base compounding in the high teens for twenty years is the whole multibagger story, and it requires no heroics.

What has to go right, and what could break it

A serial acquirer is only as good as its discipline. The headline P/E looks pricey because acquisition goodwill sits on the balance sheet and drags reported returns down; the honest way to judge Teqnion is the return on tangible capital and the return on each new acquisition, and that is the thing to watch every year. The risks are the obvious ones for the model: overpaying as it scales, diluting shareholders if it issues too many shares to fund deals, and the simple fact that the businesses underneath are lower-margin industrials, not asset-light software. None of that is fatal. All of it is worth watching.

Share

2. Röko (ROKO B)

Lifco 2.0, run by the man who built Lifco

What it is

Röko is the same serial-acquirer idea as Teqnion, scaled up and run by serious pedigree. It was founded in 2019 and chaired by Fredrik Karlsson, the former CEO who compounded Lifco into one of Europe’s great acquisition machines. Röko buys majority stakes in profitable European niche leaders, mostly businesses with EBITA between two and ten million euros, and keeps them forever under a decentralised model that preserves each company’s name and independence. It listed its B shares in Stockholm in March 2025.

The numbers today

The stock trades around SEK 1,900, for a market cap near SEK 28 billion, which is roughly $2.9 billion. That makes Röko comfortably the largest name on this list, and I want to be straight about that: at this size it is not a small cap, and it does not get my pure small-cap edge. It trades around 37 times earnings. Net sales were about SEK 6.2 billion for 2024, with adjusted EBITA margins around 20%, and in the first quarter of 2026 it grew organic sales 6% and total sales 9%, with three more acquisitions closed. It has done over thirty platform deals since inception.

The runway

Same answer as Teqnion, just with deeper pockets and a wider net across the UK, the Nordics, the Netherlands, the US, and beyond. The European long tail of family-owned niche businesses is effectively bottomless relative to even a SEK 28 billion acquirer. The constraint is capital discipline and deal flow, never market size.

Why it could be a multibagger

You are buying a proven operator running a proven playbook with a runway measured in decades. Karlsson has done this before at enormous scale, and the whole point of the perpetual-owner model is that it gets compounding-friendlier as the portfolio diversifies. If Röko sustains high-teens compounding of per-share value over fifteen to twenty years, the math takes care of itself.

What has to go right, and what could break it

The 37x multiple is the honest problem. It already prices in a lot of future success, which means the second engine, the multiple, has less room to help you and more room to hurt you if growth disappoints. The model runs on continuously deploying capital at good returns; the day acquisitions get too expensive or integration slips, the flywheel slows. And it is still young as a public company, so the seasoned track record is shorter than Lifco’s was when it earned its reputation. This is the quality-at-a-full-price name in the group. You are paying up for the pedigree.

Share

3. ChemoMetec (CHEMM)

Selling picks and shovels to the cell-therapy gold rush

What it is

ChemoMetec is a Danish company that makes the NucleoCounter, an instrument that counts cells, and then sells the consumable cassettes and reagents that the instrument eats every time it runs. It is a razor-and-blade business pointed at one of the best end-markets in science: bioprocessing, and the booming world of cell and gene therapy. Crucially, it does not bet on any single drug working. It sells the equipment that every lab in the field needs no matter whose drug wins, which is the cleanest way to own a gold rush.

The numbers today

The stock trades around DKK 315, for a market cap near DKK 5.4 billion, which is about $0.8 billion. It earns roughly DKK 10 per share, so it trades around 31 times earnings. The economics are gorgeous: gross margins around 91%, EBITDA margins around 50%, net cash, and a small dividend. Here is the kicker that makes it interesting right now: the stock is down roughly 72% from its 2021 peak of DKK 1,149, and it has traded between DKK 235 and DKK 804 in the past year alone. Analysts covering it carry an average target up near DKK 640.

The runway

Cell and gene therapy is still early, and every approved therapy and every new manufacturing line needs cell counting as a basic, repeated, non-negotiable step. The recurring consumables grow with the installed base, and the installed base grows with the industry. On top of that, management is now pushing a new “XM” platform and talking about a more software-and-licensing-shaped business over time, which is the kind of pivot that, if it works, re-rates the whole company.

Why it could be a multibagger

Start with a 90%-plus gross margin, net-cash, recurring-consumables compounder. Knock 70% off its price. Add a software transition that could change how the market values it. That is a recipe for both engines firing at once: earnings recovering as the cell-therapy cycle turns, and the multiple expanding as the market re-rates a saturated-looking instrument maker back into a growth compounder.

What has to go right, and what could break it

Even after a brutal de-rating, 31 times earnings is not cheap, so this is not a statistical bargain; it is a quality compounder you are buying at a fair-to-rich price after a fall. The reason it fell is real: the NucleoCounter base started to saturate and growth stalled, which is why the stock got cut in half and then some. The XM platform transition is unproven, and “we are becoming a software company” is a sentence that has humbled many a hardware business. Cell-therapy capital spending is also lumpy. You are betting that the franchise is durable and the next chapter works.

Share

Read more

I stumbled upon Toast the way I find a lot of names: out walking, with my headphones on.

Sean Barrett broke the company down on Business Breakdowns and made the bull case about as well as you will hear it: a restaurant that runs on Toast tends to stay, the share keeps moving its way, and after years of burning money, the cash has finally started to pile up. “A better company today than ever before”, he stated.

I came away genuinely interested, which does not happen as often as the size of my watchlist would suggest.

But interested is a looong way from invested.

A great story is where the work starts, and a good podcast, however persuasive, cannot answer the one question that decides everything for me: is the price low enough to give me a real margin of safety? So I ran home, pulled the filings, built the numbers myself, and went looking.

Here is what I found.

Note: I bought a sliver of Toast so it would have my attention (and to use that pun), because a name I own is a name I actually read. The position is tiny though, and that’s on purpose. I respect the business. So far I have refused to pay up for it.

If you’re in a rush

• They sell restaurants the one system the whole place runs on: the till on the counter, the software for the floor and the kitchen, the card processing under every order, and a growing stack of add-ons like payroll, lending, and marketing. Most of the money comes from a small slice of every card payment, which is why processing is the engine.

• The market loves them for taking share off Block and finally turning a real profit, and fears them as the next victim of the so-called SaaSpocalypse.

• What governs the outcome is the price I pay for a destination that is probable but not yet locked.

The internal verdict is a ‘Yes’ with an asterisk, so the published label is Watchlist, owned at an attention-only weight.

I am paying close attention.

Three MIT engineers and a point-of-sale that ran on a DOS prompt

The idea came from a bad dinner. Steve Fredette, Aman Narang, and Jonathan Grimm, all MIT graduates who had met building search software at Endeca (a company Oracle swallowed in 2011), were eating in Kendall Square and watched the staff fight with a point-of-sale system that kept crashing and rebooting to an antiquated DOS prompt.

Narang’s phrase for it later was that these systems were old and scary for the people who had to use them.

Subscribe now

So they built one. It started in Narang’s basement in 2011 as a humble consumer app for mobile payments and loyalty, then became the thing the restaurant actually runs on. That pivot is the origin of the moat. They went deep on one trade. They talked to restaurateurs for hours and built features a generalist would skip: real-time messaging to the kitchen about a dish that just sold out, software shaped around the rhythm of a Friday-night rush.

Chris Comparato ran the company as CEO from 2015 through the scaling years. On the first day of 2024, Narang, the co-founder, took the chair. Founder-led again, with the engineer who saw the crashing DOS prompt now allocating the capital.

The lesson the origin teaches, and the one I keep returning to, is that the vertical focus is the asset. A bear with a balance sheet could copy the software in a year. Copying fourteen years of restaurant-specific obsession is the part that breaks attackers.

Share

What you are actually buying

Picture a busy operator on a Friday night. Tickets are flying to the kitchen, a server is splitting a check four ways, a delivery order pings in, payroll runs Monday, and the whole thing sits on one system from one vendor.

That is what Toast sells: the restaurant’s operating system. They make most of their money the way a toll booth does, by taking a thin slice of every dollar that passes through.

The slices are uneven. Of $1,630M of revenue in the first quarter of 2026 (Q1 2026, USD, GAAP, 10-Q), the financial-technology line, mostly card processing, was $1,323M.

Subscription software was $268M.

Hardware was just $39M, and here is a tell worth holding onto: hardware runs at a gross loss of roughly minus $72M for the quarter (Q1 2026, GAAP, release).

They sell the terminals cheaply to get the system onto the counter, because once it is there and running the business, it tends to stay.

The interesting motion is underneath the headline. Annualized recurring run-rate grew 26 percent year over year to about $2.2 billion (as of March 31, 2026, company-defined non-GAAP, release), while locations grew 22 percent to roughly 171,000.

Recurring revenue is climbing faster than the location count, so each restaurant buys more over time: payroll, lending, marketing, and the new AI tools.

A crowded pond, and the edge I give up to fish in it

Toast is a $15 billion company on the New York Stock Exchange, followed by somewhere between fifteen and twenty-seven analysts depending on which estimate sheet you read.

Every line in the filing has been chewed over by professionals with better terminals than mine.

Owning Toast, I step into a ring with the most-resourced investors alive, on a name they all know cold. The too-big check, drift risk number two, fails outright: at this size, my position is a rounding error in daily volume, so the liquidity wall that usually guards my edge is absent.

What the crowd has not settled is the competition. Toast is the shark in a fragmented tank. Its gross payment volume grew 22 percent year over year to $51.3 billion last quarter, while Block’s Square, at a similar scale, grew about 10 percent.

Management says Toast now powers around a fifth of US small and mid-market restaurants, double its share of three years ago. The rivals are real and well-funded: Fiserv’s Clover, SpotOn, the legacy Oracle Micros boxes, and a coming wave of AI-native entrants. Taking a share of Block while the others circle is the evidence that counts.

Atomic Take: I am fishing where I hold no structural advantage, so I had better get paid for it in the price.

Falsifier: net location adds decelerate while a named rival’s accelerate.

What stops a rich, clever rival from simply stealing these customers

Run the grizzly test first: Put a well-capitalized, intelligent competitor in the room and ask whether it is still likely to lose. Mostly, yes. Restaurants do not rip out the system that runs their floor on a whim, and when they do switch, they tend to switch toward Toast, which is why the share keeps moving its way.

Here is the Patterson sentence, the one specific barrier in a single line. A well-funded rival would find it prohibitively hard to take meaningful restaurant share within five years, because Toast’s hardware, software, and payments are fused into the daily running of the business, and switching means retraining staff and risking a service meltdown on the one system a restaurant cannot afford to have go dark.

The moat model, named plainly, is high switching costs that deepen with every product the restaurant attaches. I want to be careful with the prettier label. Scale economics shared is the Nomad whiteboard’s most powerful idea, the Costco move where saved pennies are visibly handed back to the customer and volume follows.

Toast does some of this, ploughing scale into more product, twenty-plus updates in the spring release, a drive-thru system, and an AI marketing agent. The payment take rate is the profit, and they keep it rather than cutting it to chase volume. So I will call scale-shared a secondary, emerging feature here and lean the thesis on switching costs, which stands on its own as a first-class moat. The idiot-proof test passes: the installed base would survive five years of mediocre management.

Now the mis-categorisation sentence, the heart of any re-rating case. The market prices Toast through the heuristic of AI-disruptable horizontal software, when the right lens is a payments-and-hardware-anchored vertical operating system, where the physical till and the switching costs blunt the disruption and AI feeds the business more than it threatens it.

The Audit on that thesis: it is half-spent already. The stock fell from about $50 to about $26 on exactly this fear, so much of the re-rating I would be hoping for has either happened or been prepaid by the market’s panic. The spring is half-uncoiled.

Atomic Take: the moat is real and built from switching costs, and the cheap re-rating it once offered has largely been collected by the people who bought the panic.

Falsifier: blended payments take rate or net revenue retention falls for two consecutive quarters.

Share

The river of cash, and where the taxman is about to step in

Follow the one river. Money comes in the door, $6,446M of it over the trailing twelve months (TTM to Q1 2026, USD, GAAP-derived, my spreadsheet). A lot is spent paying the card networks because the payments line is reported gross, which leaves gross profit of $1,694M.

Then the sales force, the engineers, and the overhead take their share, leaving operating income of $364M (TTM, GAAP). The reported bottom line reads $412M of net income (TTM, GAAP), and here I slow down.

Two things flatter that number. First, the company has paid almost no tax, $5M on $131M of pretax income last quarter, because of a valuation allowance against past losses that the company itself says could be released within twelve months (Q1 2026, 10-Q). When it releases, a real tax bill arrives. Second, a chunk of pretax income is interest on the cash pile, which is real and recurring, and which is also not the operating business compounding.

Now the discipline. Munger’s instruction is to substitute the words “bullshit earnings” every time someone says EBITDA, and management does lean on an adjusted-EBITDA frame and a 40 percent long-term EBITDA margin target that steps around two real costs: stock-based compensation and tax. Stock comp ran about $54M in the quarter, roughly 3.4 percent of revenue (Q1 2026, 10-Q), and I expense it in full.

Do the honest build. Start from normalized net income with tax at 25 percent, about $314M, add back depreciation of about $55M, subtract a maintenance-capex estimate of about $45M (this is an asset-light software business, where depreciation is a fair proxy), and leave stock comp where it belongs, charged against the owner. Owner earnings land near $300M to $320M for the trailing year. On a $15 billion market value, that is an owner-earnings yield of about 2 percent.

Atomic Take: the business now genuinely drowns in cash, and the current owner yield is thin once you tax it properly and charge it for its stock comp.

Falsifier: stock-based compensation reaccelerates above 5 percent of revenue.

Subscribe now

The Geiger test, the turbine, and the reactor

Take the balance sheet first, the Geiger counter for fragility. Cash and marketable securities of about $1.77 billion sit against roughly $17M of debt, so the company carries net cash of nearly $1.75 billion (as of March 31, 2026, USD, 10-Q). Return on equity of 20.7 percent and return on assets of 13.3 percent on a trailing basis (my spreadsheet), both flattered a touch by the tax holiday. Nothing here keeps me up at night.

The turbine is the cash flow. Free cash flow was $115M in the quarter on the company’s own measure (Q1 2026, company non-GAAP, release), and cash from operations covers reported profit comfortably. The capex-intensity flag stays green: this is a light business that does not spend heavily to stand still, so checks fourteen and fifteen of my eighteen both pass, and the BNSF detector, the warning that a business eats capital faster than it admits, stays quiet.

The reactor is the income statement, and this is where the one real distortion lives. Blended gross margin reads about 26 percent (TTM, GAAP), which fails my 40 percent screen.

That single fact, the choice to report payment volume as gross revenue, mechanically depresses gross margin, net margin, and the ratio of overhead to gross profit all at once. It is one structural artifact, and I charge it a single time. Strip it back, and the underlying software-and-payments gross profit is the number that matters, and it is growing fast.

The Audit on any optical cheapness: there is none to perform, because the stock is not optically cheap. It trades around 20 times forward earnings and 37 times trailing, with an owner yield near 2 percent. The statements are clean. The price is the problem, and I will get there.

Atomic Take: a strong balance sheet and an asset-light cash engine, where the only “failure” is a reporting artifact I refuse to double-count.

Falsifier: free-cash-flow-to-net-income falls below 0.7 on a clean basis.

The people allocating the capital

Founder-led, disciplined, and lately profitable. Aman Narang sits in the CEO chair he co-founded the company to fill, with super-voting Class B stock concentrating control, a governance fact I keep an eye on.

The retained-earnings test, which asks whether a dollar kept turns into more than a dollar of value, now works: incremental operating margins were reported around 59 percent in the fourth quarter and roughly 68 percent for the full year, so the next dollar of gross profit drops a large share to the operating line.

The capital-allocation behavior is mostly the kind I want to see. The share count fell, from 589 million to 580 million, as buybacks of $378M year to date through early May (company release) outran the stock handed to employees.

Shrinking the count while founder-led is the right instinct.

I hold one honest reservation, tagged. Handing back this much cash so soon, while the incremental returns are so juicy, hints that the highest-return internal runway is not infinite.

At roughly $27 to $33 a share, against my central estimate near $23, those repurchases look fairly priced, so I credit them only mildly.

Atomic Take: the founder is back, the dilution has reversed, and the buyback is sensible without being a value gusher.

Falsifier: buybacks accelerate well above intrinsic, or stock-comp dilution resumes.

Subscribe now

Where this goes by the early 2030s

The destination question decides everything, and Nick Sleep framed it best: do not ask what the business makes in year three, ask what it looks like as a mature franchise in fifteen to twenty years.

The runway is genuinely long, and it is the kind that widens as the company digs. Beyond more US restaurants, there are international, retail, enterprise, the roughly 140,000 US drive-thru locations they just built a product for, and the fintech and AI layers stacking on top. This is a company that can enlarge its own pond; the trait that kept Amazon from being capped at “online retail is tiny.”

Here is the discipline, though. The destination is large and probable. It is not yet secured. It leans on continued share gains, on margins expanding the way the bulls model, on the AI vector cutting for the company, and on no recession knocking the wind out of restaurant spending.

A probable-but-unsecured destination earns my full margin-of-safety bucket, and I hold that line in the next section.

Compound a fading growth rate, say 20 percent decaying toward 10 as the pond fills, off a roughly $7.5 billion revenue base, and you get something like three times the revenue by 2032. Layer on margin expansion, and earnings might grow three to five times. That places the intrinsic business in a 3-to-5x band at the optimistic end over six years. A clean 5-to-10x by 2032 sits above that, out at the bull-of-bull edge, and I will not size to an edge.

Atomic Take: the runway is long and self-widening, and the destination is probable while it is unsecured, which sets the price bar high.

Falsifier: two years of sub-12 percent revenue growth with no macro shock to blame.

What is it worth, and am I overpaying?

Price comes last, and price is the binding constraint. This is the section that explains where I believe the fat pitch for Toast is:

Read more

Dislcaimer: None of this is investment advice, every figure here is rough and from spring 2026 (markets move — check the latest before you act), and you should absolutely do your own homework before putting a single dollar, or peso to work. I’m a guy on the internet with opinions, not your financial adviser.

Okay, settle in. I want to tell you about my favorite kind of business, and then introduce you to six small, mostly-unknown companies trying to become it.

Here’s the weird part: the thing that makes these businesses great is that they refuse to get greedy.

Let me explain.

The flywheel that runs backwards

Most companies, when they get bigger, do the obvious thing. They use their new size to squeeze better deals out of suppliers, and then they keep the savings. Bigger scale, fatter margins, happier shareholders. Makes sense.

A rare breed does the opposite. They get bigger, their costs fall, and then they hand the savings straight back to the customer as lower prices. They deliberately stay thin on margin. On purpose. Forever.

Why would anyone do that? Because it sets off a loop:

The investor Nick Sleep gave this loop a name: Scale Economies Shared.

His favorite examples were Costco and early Amazon; companies that treated every efficiency gain as something to give away rather than pocket.

Costco could jack up its prices tomorrow and mint a fortune this quarter. It doesn’t. It caps its markups by policy, makes most of its actual profit on membership fees, and uses its monstrous buying power to simply be the cheapest game in town.

The payoff is a customer base so loyal it’s almost spooky. And a moat that gets wider every single year, because every new member makes the whole machine a little bigger, a little cheaper, and a little harder to compete with.

That’s the magic.

Most moats erode over time, but this kind compounds.

The one test that separates the real thing from the fakes

Here’s how you tell a genuine Scale-Economies-Shared business from a pretender, and it’s almost embarrassingly simple:

Watch the margin line.

If a company is getting bigger and its profit margins are flat or even drifting down? That’s the tell.

It’s sharing the gains. (Costco’s gross margin has barely moved in decades. By design.)

If margins are climbing as it scales, then it’s pocketing the savings, not sharing them. That might be a perfectly lovely business, but it isn’t this one. Keep that test in your back pocket; we’ll use it at the end to bounce a couple of imposters off the list.

Why I hunt for the tiny ones

Costco is wonderful. Costco is also worth roughly a third of a trillion dollars. I think it is too much to expect that this is going to 10x from here very soon.

So I go looking for the small versions.

These are companies running this exact playbook but still valued in the hundreds of millions or low billions, in markets where the flywheel has barely started spinning. A $1.5 billion company that nails this can plausibly become a $15 billion one. A $300 billion one cannot make this move that easily.

Two more things I want before I’m interested:

A founder still at the wheel, ideally owning a big slug of the stock. Giving margin away is a decade-long act of discipline, and salaried managers cycling through on three-year bonus plans almost never have the stomach for it. Founders with their net worth riding on it do.

It is important to note that a price moat is not a lock-in moat. Nobody is stuck shopping at a discount store the way a company is stuck with the software it runs on, in comparison.

I have also written an article about switching costs that you can read here

The defense here is cheapness and trust, not switching costs. But this could make these businesses more fragile than they look.

With all that out of the way; here are six companies that follow the scale economies shared playbook and that could do a 10X from here, if they keep doing what they do:

1. BBB Foods — the one I’d start with

BBB Foods, which runs the Tiendas 3B hard-discount chain in Mexico, is the cleanest example on the list.

Picture a small, no-frills shop stocked with around 800 mostly own-brand products at rock-bottom, everyday-low prices. The scale crushes the cost of goods, and the savings go right back onto the price tag, which pulls in more shoppers, which builds more scale. Classic flywheel.

The runway is the exciting part: hard-discount is only about 3% of Mexican grocery spending, versus 24–38% in mature markets, so there’s a long way to grow into. Revenue has been compounding somewhere around 34% a year, and the founder still controls a big chunk of the votes.

The honest risks: it’s burning cash to open stores at speed, it leases every location (which flatters some of the headline numbers), Walmart’s Bodega and FEMSA’s Bara are competing hard, and the founder is in his sixties, so succession is a real question. But if you want to see the model in its purest, fastest-growing form, start here.

Share

2. Trial Holdings — the clever one

Trial Holdings runs everyday-low-price discount supercenters in Japan, but with a twist that most discounters can only dream about: it bolts a “Retail-AI” layer on top — smart shopping carts, in-store digital advertising, and a river of shopper data.

That data-and-advertising income effectively subsidizes lower shelf prices, which gives the flywheel an extra turbo.

It’s the most technologically interesting business here, and the founder is still steering.

The company is listed in Japan, which makes it tricky for a lot of foreign investors to actually buy, and it’s busy digesting a very large supermarket acquisition (Seiyu). Big integrations are exactly where retailers tend to trip.

Now let’s move on to one of the most attractive on the list, one the numbers:

Read more

He never picked a stock. He never timed a market. He freely admitted, in writing, that he had no idea what the market would do next, and neither did anyone else.

Yet Jack Bogle built the largest asset manager in human history and, in doing so, transferred an estimated $1 trillion in fees away from Wall Street professionals and back into the pockets of ordinary investors.

His weapon was a mathematical identity so simple it fits on a napkin:

Gross Return − Costs = Net Return

That equation doesn’t look like a revolution. Wall Street spent fifty years hoping you’d never notice it was one.

Subscribe now

The Origin Story

Jack Bogle and his twin brother were born into wealth on May 8, 1929, in Montclair, New Jersey. The timing was catastrophic. Within months, the Depression arrived and dismantled everything.

The family lost their home. They sold their possessions. His father, unable to bear the reversal, descended into alcoholism and eventually left.

Bogle grew up working, delivering newspapers, waiting tables, setting up bowling pins at a local alley. He got a precise, personal understanding of what it costs to earn a dollar and how quickly it can disappear.

He won a scholarship to Princeton, where he survived on work-study wages and developed the habit of reading everything. In 1949, a Fortune magazine article about the mutual fund industry caught his attention. The industry was young, loosely regulated, and making large promises about its ability to select superior stocks on behalf of investors.

Bogle spent his final two undergraduate years writing a 130-page senior thesis dismantling those promises. His central argument was blunt: mutual funds were not delivering on their claims, their fees were destroying the returns of the people they were supposed to serve, and their primary obligation should be minimizing costs, not maximizing the appearance of sophistication. He concluded that funds should aim simply to match the market, not beat it.

It was 1951. He was twenty-one years old.

Walter Morgan, founder of the Wellington Fund, read the thesis and hired Bogle immediately. Over the next fifteen years, Bogle rose to become CEO — disciplined, cost-conscious, relentlessly focused on the investor.

Then he made one catastrophic mistake.

The Firing

In the late 1960s, the market was euphoric.

Growth stocks were soaring. Bogle, under pressure to compete with flashier funds, and perhaps seduced by the bull market himself, approved a merger with Thorndike, Doran, Paine & Lewis, a Boston investment boutique known for aggressive, high-conviction growth stock picking.

The combined entity would manage Wellington’s conservative assets alongside the new firm’s speculative ones.

Then, in 1973 the market turned.

The growth stocks, built on optimism rather than earnings, collapsed. Wellington’s performance cratered. The board had seen enough. In January 1974, after a brutal internal vote, Jack Bogle was fired from the company he had spent his entire career building.

He was forty-four years old. His reputation was damaged. And the terms of his dismissal legally barred him from managing investments or running a fund advisory firm.

Most people would have left the industry. Bogle read the legal language very carefully.

Share

The Superpower

What the firing prohibited was specific: Bogle could not manage money or run an investment advisory firm. What it did not prohibit was administration; the back-office mechanics of running a fund: legal, accounting, compliance, operations.

Bogle went back to the Wellington board with a proposal. He would form a new company, owned not by outside investors or private partners but by the Wellington funds themselves. This company would handle administrative functions only. It would, technically, not be an investment adviser.

He named it The Vanguard Group, after the British flagship at the Battle of the Nile.

The board approved it, assuming they were signing off on a clerical subsidiary. They had just handed Bogle the keys.

The ownership structure he designed was unlike anything in American finance. In a conventional asset management firm, investors pay fees that flow to the firm’s owners; shareholders, partners, executives. The firm’s incentive is to grow assets and extract maximum fees. The investor’s return is what’s left over.

At Vanguard, there were no outside owners. The funds owned Vanguard. The investors owned the funds. Any profits generated by the management company flowed back to reduce the costs borne by investors. The structure had no mechanism for extracting money from investors because investors were the owners.

[Traditional Asset Manager]  ──> Fees flow to ──> Outside Shareholders & Partners
[The Vanguard Structure]     ──> Profits flow to ──> Lower Costs for Fund Investors

This made one outcome structurally inevitable: Vanguard’s costs would always fall toward zero.

In 1976, Bogle launched the First Index Investment Trust; the first retail index fund available to ordinary investors, designed to track the S&P 500.

It held every stock in the index in proportion to its market weight. It hired no analysts. It made no predictions. It sought no edge. It simply owned corporate America and waited.

Wall Street called it “Bogle’s Folly.” The mockery was genuine. What serious investor would deliberately settle for average?

The answer, buried in the arithmetic, was: a very rational one.

Active funds were charging, on average, 1% to 1.5% annually in management fees. Add trading costs, tax drag from frequent portfolio turnover, and the spread paid on transactions, and the real cost of active management was routinely 2% or higher per year. That sounds modest. Compounded over decades, it is catastrophic.

On a $100,000 portfolio growing at 7% annually over 30 years:

On a $100,000 portfolio growing at 7% annually over 30 years: a 0.05% index fund leaves you with ~$757,000.
A 1% active fund leaves you with ~$574,000.
A 2% active fund leaves you with ~$432,000.

The difference between the first and last number is $325,000, paid entirely in fees, compounded against you over decades.

The “average” return, captured at near-zero cost, beat the majority of actively managed fund because of arithmetic.

Share

The Graveyard

To own the market is to survive everything the market does to you.

There is no protection in Bogle’s approach. No analyst to raise cash when conditions deteriorate. No tactical allocation to shift into bonds at the first sign of trouble. When the dot-com bubble burst in 2000, index investors fell with it. When the 2008 financial crisis arrived, broad index funds lost roughly half their value in eighteen months.

Bogle’s entire architecture assumes you will not sell.

The moment you do, rattled by headlines, unable to stomach another month of losses, the mathematical advantage evaporates.

A 40% loss requires a 67% gain just to return to even. Selling at the bottom locks in the loss permanently and converts a temporary decline into a permanent one.

This is the only real skill the strategy demands: the ability to sit still while the world appears to be ending. It sounds easy. During a genuine panic, it is one of the hardest things an investor will ever be asked to do.

The Toolkit

Bogle’s philosophy reduces to three executable principles. They have been dressed up in many names by many commentators. The ideas themselves are deliberately plain, because their power comes from being followed.

Own the whole market, not pieces of it.

The moment you select individual stocks or sectors, you introduce the possibility of being wrong in ways that compound against you. The aggregate market, all of corporate America, all of its earnings, all of its dividends, grows over time because human productivity and commerce grow over time. That growth is yours to capture at near-zero cost. What you pay to capture it is the only variable fully within your control.

Make cost the first criterion, not the last.

Before evaluating any fund’s historical performance, calculate what it costs to own. An active fund returning 9% annually at a 1.2% fee has delivered 7.8% to you. A passive fund returning 8.5% at 0.05% has delivered 8.45%. The passive fund won because it was cheaper. Past performance shifts. Fees are contractual.

Remove yourself from the process.

Automate contributions. Set an asset allocation appropriate to your time horizon. Then do not watch it. The financial media exists to generate attention, not returns. Every analysis that makes you want to act is a cost, in fees, taxes, or mistimed decisions. The correct number of portfolio adjustments made in response to macroeconomic news headlines is, in Bogle’s view, approximately zero.

Share

The Human Factor

Bogle’s heart was always the problem. He suffered his first heart attack at 31 and would endure two more, plus a cardiac arrest, over the following decades. He lived for years with a pacemaker, acutely aware that his time was limited. In 1996, at 65, he received a heart transplant that granted him twenty-two additional years of uncompromising work.

He used them loudly. And, near the end, in unexpected ways.

Despite founding the firm that made index investing mainstream, Bogle spent his later years as a vocal critic of what index investing had become.

The explosion of exchange-traded index funds, which trade throughout the day like stocks, enabling precisely the speculative behavior he had spent his career fighting, troubled him deeply.

He was not opposed to indexing. He was opposed to trading. An ETF, he argued, was a vehicle designed to help people who couldn’t help themselves do exactly that, wrapped in the philosophy of a strategy that required them not to.

He was, in his final decade, openly at war with his own legacy. The idea had been captured and repackaged by an industry that had never fully understood it. Or, perhaps, had understood it perfectly and simply declined to follow it.

Had Bogle structured Vanguard as a conventional for-profit firm, his personal stake would have been worth tens of billions of dollars. Instead, at his death in January 2019, his net worth was estimated at around $80 million.

A substantial fortune, but a rounding error against what he had deliberately walked away from. He flew coach. He lived in the same modest house for decades. He kept a bagged lunch at his desk.

He once said, with characteristic plainness: “I have had a wonderful life. I have done what I wanted to do, and I have done it on my own terms.”

Subscribe now

The Verdict

Bogle’s philosophy is not a strategy for people who want to feel clever. It offers no stories to tell at dinner, no moments of vindication when a bet pays off, no individual genius to point at. What it offers instead is something rarer: a mathematically grounded approach to not losing to your own costs, your own impatience, and your own overconfidence.

This philosophy rewards you if:

• Your investment horizon is measured in decades, not quarters.

• You are more interested in the near-certainty of a good outcome than the remote possibility of a spectacular one.

• You can watch your portfolio fall 40% without interpreting it as a signal to act.

Walk away if:

• You believe you have an informational or analytical edge over institutional investors with billion-dollar research budgets.

• You need the engagement of active management to stay interested in investing at all.

• You cannot sit still.

The rest is just arithmetic. Bogle spent his life insisting that was enough.

“The greatest enemy of a good plan is the dream of a perfect plan. Stick to the good plan.”
― John C. Bogle

Some of this post is free to read. If the research is useful to you, consider becoming a Founding Member while the offer is still open.

The standard rate is $199/year. Founding members lock in $99/year, permanently, for as long as you stay subscribed.

As a paid subscriber, you get:

• Full Deep Dives & Valuation Teardowns: the comprehensive work that takes a full weekend to build. The 18-check framework applied in full, owner earnings DCF, conviction score, and the inversion checklist.

• Forensic Balance Sheet Analysis: looking under the hood for what others miss.

• The Live Multibagger Index: the highest-signal opportunities, tracked in real time.

• Portfolio & Watchlist: exactly how I allocate capital and what is currently in my investing universe.

• FINS: earnings numbers broken down clearly, without the noise.

Everything else (Money Mind, Simple Truths, Titan Test, and all deep dives published to date) stays free.

Secure 50% Off Today

Alright, let’s get to it!

I have had Nu on my radar for a very long time. If you’ve spent any time studying the legendary investor Nick Sleep, you know his framework of “Scale Economies Shared”, and NU is one example of a business that uses this model.

Scale Economies Shared is the idea that a company can win permanently by relentlessly dropping its unit costs and handing those savings right back to the consumer to lock in terminal loyalty. Costco did it. Amazon did it.

But admiration is one thing; entry price is another.

In a hyper-growth credit story, discipline is the only thing that keeps you from getting blown up.

So I watched, I modeled, and I waited. Recently, the market finally served up a price level I actually quite like: $12.29 per share. So I initiated a decent position.

Now that I have real skin in the game, it’s time to pressure-test the thesis. If you are a shareholder, or thinking about becoming one, you have to get comfortable with the structural tension of this business.

Let’s break down exactly what we are dealing with.

Subscribe now

If You’re In a Rush

• What they do: Nu is a digital financial services juggernaut. They monetize their massive user base through three primary engines: Credit Income ($3,173.3m), Float Income ($1,383.0m), and Fee Income ($759.1m), according to their Q1’26 managerial metrics.

• Why it’s hated: Wall Street looks at Nu and sees a “credit book” first, and a “software-like platform” second. Because of that, every single quarter turns into a tense courtroom trial over credit quality, non-performing loans (NPLs), and risk-adjusted economics.

• What fixes it: Keeping the core flywheel spinning. We want to see Average Revenue Per Active Customer (ARPAC) march higher than its current $15.9, and the Efficiency Ratio stay glued near its incredible 18% mark, all without late-stage delinquencies re-accelerating from the current NPL 90+ rate of 6.5%.

Atomic Position: I currently hold a long position with a cost basis of $12.29 per share. Because of that, you should treat my optimism the same way you’d treat a package carrying a tiny, polite amount of radiation. Do your own homework.

Atomic Take: Nu’s story is a beautiful compounding flywheel that is forced to operate under a harsh credit-cycle spotlight 24 hours a day, 7 days a week.

Falsifier: If the NPL 90+ metric starts trending upward for multiple consecutive quarters from its current 6.5% base, the entire “controlled credit machine” narrative shatters.

The Setup

Nu’s own presentation of their business is almost insultingly tidy.

They show you a beautifully simple equation: take a rapidly growing customer base, monetize them at higher rates over time, run it all on a highly scalable low-cost platform, and watch it translate into massive earnings.

Share

If you look at the Q1’26 investor deck, they plot it out perfectly:

• Total customers rising to 135 million

• ARPAC climbing to ~$16

• Efficiency ratio dropping down to 18%

• Net income hitting $871 million

On the surface, the quarter was an absolute powerhouse, delivering $871.4 million in managerial Net Income and a scorching 29% Return on Equity (ROE).

But if you’ve owned anything even remotely adjacent to the credit space for more than five minutes, you know how this game works. The ultimate villain in banking isn’t usually “revenue.”

No, the real villain is a lagging indicator that shows up late to the party wearing a trench coat: delinquencies, provisioning, and the brutal timing of cash flows.

This structural reality is exactly why Nu is such a love/hate object in the investing community.

It is a spectacular software platform narrative strapped directly to a traditional lender’s balance sheet. When things go right, that combination creates a legendary compounding engine.

When things hit a bumpy patch, it feels like an anxiety subscription.

The Market, The Bulls, and The Bears

• The Market View: “It’s a nice app with great tech. But credit losses are the ultimate tax on this business model. Eventually, that tax bill is going to go way up.”

• The Bull View: The earnings-generating formula is completely real, and more importantly, it is proving it can travel. Mexico officially reached break-even in Q1’26, proving that the exact same monetization formula can unfold successfully outside of Brazil.

• The Bear View: Fast growth mixed with credit expansion and shifting product mixes is a recipe for disaster. Eventually, a future quarter will hit where the risk-adjusted economics crack, and the stock’s valuation multiple will re-rate violently downward like a boring, traditional bank. Because at the end of the day, that’s what it is.

Share

This deep dive really boils down to one fundamental question: Does Nu pass the classic Nick Sleep “Scale Economies Shared” sniff test?

In other words, is Nu taking the benefits of its massive scale and reinvesting them directly into better products, lower prices, and a superior user experience to drive even more scale?

Or is it simply a very well-run lender that will always be held back by a permanent credit discount?

Atomic Take: The Q1’26 numbers absolutely shout “platform leverage,” but this thesis only compounds over the long haul if the credit metrics stay incredibly boring while the customer acquisition machine stays incredibly loud.

Falsifier: If the efficiency ratio begins to drift meaningfully above the ~20% band that management has targeted for the year, the “structural low-cost platform” claim starts to look very wobbly.

How the Business Actually Makes Money

Let’s start by looking at what Nu chooses to disclose, because that gives us a direct window into how management thinks about value creation.

They recently introduced a new Managerial P&L framework (which is a company-defined, non-IFRS measure).

They did this to better explain how value is generated across a platform that spans multiple countries and dozens of products. It’s worth noting that standard IFRS remains their official statutory basis, and net income, capital, and cash are fully preserved. But this managerial view helps us see the moving parts clearly.

In these Managerial P&L terms, Nu’s revenue is definitely not some mysterious banking blob. It is a highly distinct, three-engine system. Out of $5,315.5 million in total managerial revenue for Q1’26, the breakdown looks like this:

The Three-Engine Revenue Breakdown (Q1’26)

• Credit Income: $3,173.3m

• Float Income: $1,383.0m

• Fee Income: $759.1m

Total Performance: $5,315.5m

That specific mix matters immensely because it tells you exactly what kind of beast you are underwriting as an investor. If this were a pure credit story, you would be completely hostage to the cost of credit.

But when you have a digital platform that can grow float income and fee income right alongside its credit book, you get a beautiful extra layer of structural resilience. That is, assuming the diversification is real and not just an accounting costume.

Nu’s latest deck explicitly highlights this “fee and float diversification” as a powerful compounding trend, even while noting some typical Q1 seasonality on the credit side. All told, gross profit for the quarter landed at $1,877.7 million.

Now, let’s apply that Nick Sleep/Nomad lens.

“Scale economies shared” means that as the company gets bigger, its cost per unit drops significantly, and the company actively hands a big chunk of those savings back to the customer to lock in their loyalty and keep the loop spinning.

And I think the data points from Nu that track this loop are incredibly compelling:

• ARPAC reached $15.9, while their historical cohort curves show that their most mature customer cohorts have already reached a hefty $30.8 in monthly ARPAC.

• The cost to serve remained rock-solid at just $1.0 per active customer, which stands out as a massive competitive advantage against legacy brick-and-mortar banks.

• The efficiency ratio dropped to 18%, with management explicitly boasting on the earnings call about achieving a record-low efficiency ratio below the 18 percent threshold.

Atomic Take: This is about the cleanest setup for “scale economies shared” you will ever see in the financial sector. You have steadily rising customer revenue, an incredibly low and flat cost-to-serve, and an efficiency ratio that looks completely allergic to gravity.

Falsifier: If ARPAC growth suddenly stalls out while the cost to serve begins climbing north of that $1.0 mark, the compounding flywheel will start looking like a basic treadmill.

Share

What Went Wrong

Nothing actually “went wrong” this quarter in the catastrophic sense of the phrase. Instead, the anxiety here is entirely structural.

Any business model that is driven by high-growth credit gets judged on two completely different timelines simultaneously:

1. The Fast Timeline: This is the exciting stuff: customer growth, climbing ARPAC, and improving efficiency ratios.

2. The Slow Timeline: This is the quiet, lagging stuff: creeping delinquencies and the heavy burden of provisioning for bad loans.

During Q1’26, the portfolio behaved exactly the way credit portfolios typically behave during the first quarter of the year: early-stage delinquencies ticked upward, while late-stage delinquencies managed not to implode.

Looking directly at the headline metrics from the earnings release, the shift becomes clear:

• NPL 15–90 hit 5.0%, marking a noticeable step up from the 4.1% we saw in Q4’25.

• NPL 90+ landed at 6.5%, which was actually down a tiny bit on a sequential basis.

Because of this mix shift and credit expansion, the company’s risk-adjusted economics took a step backward. The Risk-Adjusted Net Interest Margin (NIM) landed at 9.5%, down from the 10.5% recorded in the previous quarter.

Management’s core defense across their call and investor materials can be summarized simply: regular seasonal trends, combined with aggressive growth and product mix changes, naturally required them to book higher provisions. They explicitly stated that they do not view this asset behavior as a structural degradation of the portfolio.

Saying “asset quality isn’t degrading” can be factually accurate in a narrow sense because late-stage NPLs remained stable.

At the exact same time, saying “risk-adjusted profitability got worse this quarter” is also 100% true because the risk-adjusted NIM compressed by a full percentage point.

Those two realities do not contradict each other.

Instead, they serve as a loud, clear warning label that your true margin of safety in an investment like Nu is strict, unyielding credit discipline.

Atomic Take: Q1 didn’t break the fundamental investment thesis for Nu by any means. What it did was give everyone a sharp reminder that this high-flying platform flywheel is still firmly attached to a credit engine that suffers real, seasonal bruises.

Falsifier: If the NPL 90+ metric begins climbing meaningfully past 6.5% while the risk-adjusted NIM continues to compress below 9.5%, then blaming “seasonality” will officially turn into corporate denial, in my view.

Subscribe now

Rebound Catalysts

When you are looking for things to go right with a business, you need testable milestones.

Let’s look at the actual gauges on the dashboard that will tell us if this machine is accelerating safely.

#1. Mexico Becomes a Repeatable Profit Machine

Nu tells us that Mexico officially crossed 15 million customers and reached break-even in Q1’26, proving that their signature “earnings-generating formula” can work outside of Brazil.

But here is the common-sense test: hitting zero once for a single quarter doesn’t prove a trend. The real test is whether Mexico can transform from an exciting “inflection point” into a massive, steady profit contributor to the group, all without dragging down that beautiful consolidated efficiency ratio.

#2. Artificial Intelligence Shows Up in Credit Outcomes, Not Just Productivity Anecdotes

Nu loves to talk about its multi-phase AI transformation, and to be fair, they have some fantastic productivity metrics to show for it. They claim engineering throughput is up 50% YoY and testing cycles are running 90% faster.

They also state that their AI Private Banker now serves over 15 million monthly active users, and their proprietary “NuFormer” model is fully live in production, making credit card decisions in Brazil and Mexico, as well as handling unsecured lending in Brazil.

If their AI is truly a competitive advantage in underwriting, it shouldn’t just stay a nice tech story. It has to show up in the numbers where it matters: credit limits growing safely with extreme resilience.

I want to see their risk-adjusted economics stabilize and hold firm even as the total loan book expands.

#3. ARPAC Keeps Climbing as Cohorts Mature

When you look at Nu’s customer cohort charts, management is essentially telling you: “Be patient, because patience gets paid.” While their headline ARPAC sits at $15.9 for Q1’26, their oldest, most mature customer cohorts have already climbed to a massive $30.8 in monthly ARPAC.

As long as new customers follow that exact same upward trajectory over time, the top-line engine takes care of itself.

#4. Efficiency Stays Within Guardrails While Launching New Bets

Nu is currently laying the groundwork for a U.S. expansion, but they are framing it as a highly disciplined, strictly capped experiment. They expect the maximum investment impact to remain below 100 bps on the consolidated efficiency ratio across both 2026 and 2027.

Management explicitly notes that this investment will be contained within the general ~20% efficiency range they have communicated for the full year.

The investor deck even uses the phrase “bounded cost to enter,” meaning they have intentionally built a roof over their potential downside.

Atomic Take: The perfect script for Nu from here is beautifully simple: we want the business to be incredibly boring in the places that cause sleepless nights (NPLs and efficiency) and incredibly loud in the places that create massive wealth (ARPAC growth and Mexican profitability).

Falsifier: If the consolidated efficiency ratio begins to meaningfully degrade despite this “<100 bps” U.S. spending cap, the narrative that they can fund major new expansions without breaking the core margin machine will face—and fail—its very first live test.

Share

Financial Quality Rubric (Score: 1 to 5)

Let’s look at this business through a classic, no-nonsense financial checklist to see exactly what we are buying.

Read more

Every IPO, at its core, is a theatrical performance.

There is a script. There is a cast. There are producers who have been working behind the scenes for years. And then there is an opening night, when the curtain finally rises and the audience, that’s you, buys a ticket at the box office and takes a seat in the dark.

What I find fascinating, and what I think most coverage gets badly wrong, is that nobody tells you that by the time you walk through the doors, everyone who actually matters has already seen the dress rehearsal. The critics got advance screenings. The investors who will make the most money were in the room when the script was still being written.

You? You’re buying a ticket on opening night. At full price. From the box office. For a show the cast is very motivated to sell you.

The IPO process is structurally tilted away from you.

And right now, with SpaceX, OpenAI, and Anthropic all about to hit public markets within months of each other, I think it’s worth sitting down and talking through exactly what kind of theatre you’re about to walk into.

Subscribe now

First, Let’s Talk About What’s on the Marquee

On May 20, 2026, SpaceX filed its IPO prospectus with the SEC. The company is expected to trade on Nasdaq under the ticker SPCX, with trading possible as early as June 12, depending on the final roadshow and pricing process.

The reported valuation target is around $1.75 trillion. On listing day, that would not quite put SpaceX beside Apple, Microsoft and Nvidia at the very top of the market, but it would put it in a ridiculous neighbourhood: potentially the seventh-most valuable public company in America.

To put that in perspective: the entire global IPO market raised $42.6 billion in Q1 2026. Even if these companies only sell a small slice of themselves, the proceeds could dwarf what the normal IPO market does in an ordinary quarter.

Then comes OpenAI, the company behind ChatGPT, a product now used by more than 900 million people every week. It is reportedly preparing for a possible public listing as early as September.

Then Anthropic, the makers of Claude, which is also reportedly circling the public markets with valuation talk somewhere near the trillion-dollar edge.

Put the three together and, if the reported targets hold, you are looking at well over $3 trillion in market value trying to enter public markets in less than a year.

Share

The Production You’re Joining (And Who Runs It)

Here is how an IPO actually works:

A private company, let’s use SpaceX as our example, hires investment banks. Goldman Sachs. Morgan Stanley. You know, the usual names.

These banks take the company on a “roadshow,” which is the industry’s polite word for a travelling sales performance. The “cast and producers” sit across from the world’s largest pension funds, sovereign wealth funds, and hedge funds. Together, they set the price. Together, they decide who gets seats.

Then the stock lists on an exchange, and you, an individual investor sitting at home, get to buy whatever’s left in the general admission section.

Ask yourself honestly: at which point in that production do you think the pricing most favors the general audience?

“Anytime anybody offers you anything with a big commission and a 200-page prospectus, don’t buy it. Occasionally, you’ll be wrong if you adopt Munger’s Rule. However, over a lifetime, you’ll be a long way ahead, and you will miss a lot of unhappy experiences.”

Charlie Munger, Vice Chairman, Berkshire Hathaway

A SpaceX S-1 prospectus is, almost to the letter, that 200-page programme. And much like a real theatre programme, it was written by the production’s own lawyers, it tells you what they want you to know, and it costs you nothing because the real price comes later.

The company and its bankers choose the exact moment to go public. They pick the moment most favorable to them: when sentiment is high, when the story is cleanest, when the numbers look best. They do not ring a bell and announce that now would be a great time for retail investors to buy their shares at a fair price.

The curtain goes up when the production company is ready. Full stop.

What the Historical Reviews Actually Say

Alright, let’s talk data, because the data is fascinating and I find it consistently ignored in the excitement around big IPOs.

Academic research on IPOs has found the same uncomfortable pattern, over and over: the opening-night applause is often much better than the long run.

The first-day pop, that exciting percentage you see on the news, has historically averaged somewhere around the high teens. That is the part everyone talks about. That is the champagne. That is the photo outside the theatre.

But over longer periods, IPOs as a group have tended to disappoint against the boring old market index sitting quietly in the background.

I think about this the way critics talk about opening-night reviews versus the longer run. Shows get standing ovations on opening night all the time. It takes a few weeks to know whether it’s actually any good.

Share

Here is the detail that really stings. The opening-night pop that makes the headlines? The one you see screaming across financial Twitter at 9:35am? I want you to understand that you almost certainly cannot access it at that price.

The best IPO allocations, the shares sold at the official offering price before the market opens, are reserved for the banks’ most valuable institutional clients. Research has shown this clearly: the IPOs with poor opening-night performance are easy to get allocations for. The ones with strong performance are quietly distributed to hedge funds and pension managers before retail investors can act.

By the time you see the pop, you’re watching a performance that opened without you. The people selling into that excitement are the ones who got in at dress rehearsal. They’ve already seen the show. They’re selling you their seats on the way out.

“I think buying new offerings during hot periods in the market is not anything that the average person should think about at all.”

Warren Buffett, Chairman, Berkshire Hathaway

Buffett has missed Amazon. He’s missed Google. He acknowledges both. His view is that owning great companies is one of the best things you can do with money. The IPO moment specifically is when the structural odds tilt hardest against the retail investor, and he has simply refused to play on those terms for seventy years.

It’s hard to argue with seventy years.

Now Let’s Read SpaceX’s Programme

Here is where I have to be honest: SpaceX is a legitimately extraordinary company.

It has done things that were supposed to be impossible. Reusable orbital rockets. The largest satellite constellation in human history. NASA contracts that previously went to companies ten times its size. The Falcon 9 launch cadence is something the aerospace industry still struggles to comprehend.

The S-1 reveals, for the first time, what the production actually looks like backstage. And backstage tells two very different stories.

The front-of-house story: SpaceX generated $18.7 billion in revenue in 2025, up sharply from the year before. On an adjusted EBITDA basis, the company produced about $6.6 billion in profit. Starlink, its satellite internet division, is a dominant machine in low-earth-orbit broadband, serving parts of the world that traditional networks either cannot reach or cannot reach profitably.

The backstage story: despite that adjusted profit, SpaceX posted a GAAP net loss of about $4.9 billion for full-year 2025. And in Q1 2026 alone, it lost roughly $4.3 billion.

Share

That gap between “adjusted EBITDA profit” and “actual loss” is not a rounding error. It is the show behind the show: depreciation, stock-based compensation, enormous capital spending, and, most unusually, the cost of folding Elon Musk’s AI empire into the SpaceX story.

Let that sit for a moment. When you buy SpaceX, you are not only buying Falcon 9, Starship and Starlink. You are also buying exposure to Grok, X, and Musk’s attempt to build an AI platform that competes, in one way or another, with the other two productions coming to market: OpenAI and Anthropic.

It makes the investment considerably harder to explain.

Then there is the governance question. I want to show this clearly, because it tends to get lost in the excitement about rockets and Mars colonies.

If Musk wants SpaceX to lean harder into AI infrastructure, Mars, Starlink, Grok, or some future project none of us has heard of yet, public shareholders will not be sitting around the table with a meaningful vote. They will own a piece of the production, but not the stage directions.

If he wakes up one morning and decides SpaceX should acquire X again, he can. You would own a piece of the production and have no say in the casting, the venue, or the running time.

In any meaningful governance sense, you’re a ticket holder. The production company runs the show.

The Bit the Programme Leaves Out

Peter Lynch, who ran Fidelity’s Magellan Fund to a 29% average annual return over 13 years, had a test for every investment he considered:

“If you can’t explain to an 11-year-old in two minutes or less why you own the stock, you shouldn’t own it.”

Peter Lynch, former manager, Fidelity Magellan Fund

I want you to try explaining the SpaceX investment thesis to an 11-year-old.

“It’s a rocket company, but also a satellite internet company, and now partly an AI infrastructure company, and it has exposure to Grok and X, and it may be valued around $1.75 trillion even though it just lost more than $4 billion in a single quarter, and the founder controls about 85% of the votes, and he also runs Tesla, X, xAI and Neuralink...”

You might lose the kid at “satellite internet.” Lynch’s point was never about simplicity for its own sake. It was that if you can’t articulate the thesis clearly, you probably don’t understand it clearly. And the IPO process is specifically designed to make you feel like you understand something you don’t have the backstage information to properly evaluate.

Here is the part I want you to really absorb: the information gap in IPOs is structural and deliberate. The insiders, founders, early employees, and venture capitalists, have lived with this company for years. They know the actual revenue trajectory. The real customer churn rate. They know the competitive threats that didn’t make it into the programme.

Every one of them is selling to you. The banks advising the deal earn their fees from the company, not from you. The analysts covering the IPO work for those same banks.

You, sitting at home reading a prospectus that runs hundreds of pages, with a deadline, are being asked to out-analyse all of that in the two-week roadshow window before opening night.

“If you’ve been playing poker for half an hour and you still don’t know who the patsy is, you’re the patsy.”

Warren Buffett

In the IPO game, the patsy has a name. It’s the retail investor who buys on opening night, reads the rave reviews in the financial press, and assumes they’re getting the same deal as the institutions who got tickets six months ago.

Subscribe now

So, What Will I Do?

I want to be clear: this article stops well short of calling these bad companies.

They could be extraordinary ones.

Starlink is a dominant business in low-earth-orbit satellite broadband, especially in places where terrestrial internet is weak, expensive or simply unavailable. Falcon 9 has an unmatched launch cadence. Anthropic is reportedly growing fast. OpenAI has more than 900 million weekly ChatGPT users and a product embedded in the workflows of students, developers, lawyers, founders, analysts and probably half the people pretending they are not using it.

These are remarkable performances.

The technology is real. The moats are real. The question I keep coming back to is the price at which you buy, and the moment at which you buy it.

Here is what I will do: grab some popcorn, read some Buffett and Munger, and wait for the reviews.

Every great production has a run that extends well past opening night. The lock-up expiration, often around 180 days after an IPO, is one of the first moments when early employees and investors may be allowed to sell more freely.

That does not guarantee a crash. Nothing in markets is that neat.

But it does change the supply of shares. It changes the cast of sellers. And it gives you something opening night does not: more information.

The first few earnings reports, stripped of the roadshow energy and the carefully rehearsed narrative, tell you what the business actually looks like when the lights come up on a Tuesday afternoon in a half-empty theatre.

Share

The Show Will Go On

We are living through a genuinely remarkable season. The companies that may come public in this cycle, a rocket company trying to make Mars real, the laboratory that helped turn AI into a consumer product, and the teams building the language models now reshaping work, are the kind of productions that define eras.

I keep coming back to Netscape.

The Netscape IPO in 1995 helped launch the internet era. The stock exploded on opening day. The phrase “Netscape moment” became shorthand for the arrival of a new technological age.

And yet the lesson was never simply “buy the IPO.”

The internet changed everything. Netscape itself did not become the enduring winner. The show ran for thirty years and is still running, but the money was not made by blindly buying every opening night. It was made by understanding which parts of the new world would actually endure.

The companies are real. The technology is real. The performances will be extraordinary.

“The only question that matters is at what price you’re being asked to buy a seat.”

Right now, you’re being asked to believe in SpaceX at a valuation of roughly $1.75 trillion, while it is losing billions under GAAP accounting, in a production where the lead actor controls the stage directions and public shareholders have very little say in the script.

What I might do: wait for the reviews.

Let the opening-night energy settle. Let the first earnings reports arrive. Let the lock-up calendar do what lock-up calendars do. The show will still be on. The seats may be better value. And you’ll know, finally, whether the production is as good as the programme promises.

One more thing. Bruce Hornsby's 'The Show Goes On' has been on repeat in my house this week. Make of that what you will.

Disclaimer:
This is an opinion piece. It is not financial advice. Think of it as the kind of conversation a well-read friend would share over a beer, someone with no financial interest in your decision. Make your own choices. Read the S-1. Speak with a licensed financial adviser. And remember Munger’s Rule: if it comes with a 200-page programme and a large commission, the curtain may not rise the way they promised.

I actually got the idea for this installment of The Money Mind from a comment a paid subscriber left on a recent portfolio update. They laid out a beautifully detailed, incredibly sharp bear case against one of my core holdings. It was the kind of feedback you can’t ignore; analytically tight and logically sound.

So… I couldn’t do much else but acknowledge his brilliant perspective, but the exchange reminded me of a fundamental truth about markets and life: the world is far too complex to determine with absolute accuracy.

In the long run, it is much healthier, and infinitely more profitable, to focus on being directionally correct.

And nobody embodies that truth better than the man featured in this issue of Money Mind.

Subscribe now

William Green spent years interviewing the world’s greatest investors for his book Richer, Wiser, Happier. He expected to find ruthless optimizers. What he found instead, again and again, was something far more disarming: people who had made peace with uncertainty, and built their entire advantage around that peace.

Tom Gayner is perhaps the purest expression of that finding.

Green profiles him not primarily as a stock-picker, but as a man who has constructed an entire life around a single, quietly radical idea: that you don’t need to be right. You just need to be directionally right. And that distinction, compounded over decades, turns out to be worth billions.

Who is Tom Gayner?

Gayner is the CEO and Chief Investment Officer of Markel Corporation, a specialty insurance company based in Richmond, Virginia. To call it unglamorous would be generous.

Markel doesn’t make headlines. It doesn’t disrupt anything. It insures niche, hard-to-price risks (collectible cars, summer camps, horse farms) and it has done so, profitably and quietly, for decades.

Gayner joined Markel in 1990 as an investment officer, trained as a CPA. He arrived with a ledger mindset: systematic, methodical, allergic to sloppiness. Over time, he became the architect of its entire capital philosophy.

Today Markel is often called a “Baby Berkshire”, a comparison earned through a genuine philosophical kinship with how Buffett thinks about business and time.

His personal track record across decades is one of the most consistent in institutional investing.

Subscribe now

The Accident of Float

To understand Gayner’s edge, you need to understand one structural fact about insurance companies: they collect premiums before they pay claims.

The money sitting in between (sometimes for years) is called the float. It belongs, technically, to future claimants. But until those claims arrive, it can be invested.

Most insurance companies invest their float conservatively, in bonds. Gayner invests Markel’s float in equities, and holds them for years, sometimes decades. Because the float is large, sticky, and doesn’t demand sudden redemption, he never has to sell into a bad market.

He simply waits.

This is a structural advantage most individual investors can’t replicate. But the philosophy underneath it, the willingness to sit still, to resist the pressure to act, is entirely transferable.

The Four Pillars

Gayner filters the entire universe of publicly traded companies through four questions. They are almost aggressively simple:

1. Is the business highly profitable, with strong returns on capital and low debt?

Not flashy revenue growth. Return on capital. He wants businesses that make more money than they consume.

2. Does management have both ability and integrity?

He treats these as inseparable. A brilliant but dishonest management team is worse than useless — they’ll find creative ways to enrich themselves at shareholders’ expense.

3. Are there reinvestment opportunities within the business?

A great business that can’t grow is a melting ice cube. He wants companies that can plow their own profits back into further growth, compounding internally.

4. Is the price fair?

Not cheap. Fair. He’s not hunting for distressed bargains. He’s willing to pay a reasonable price for an exceptional business, and let time do the work.

When all four align, he buys. Then, characteristically, he does very little else.

“Directionally Correct”

In Richer, Wiser, Happier, Green captures something essential about Gayner’s psychology: he is profoundly unbothered by being wrong in the short term, because he has thought carefully about what kind of wrong he can tolerate.

Gayner once described wanting to return to his college weight. His plan wasn’t a diet. It was to lose one pound a year for ten years.

Excruciatingly slow.

Entirely sustainable.

Completely successful.

This is the Gayner framework in miniature. He doesn’t ask: is this the perfect trade at the perfect price on the perfect day? He asks: is this the right direction? If the answer is yes, he acts. Then he waits. Then he compounds.

Green’s broader argument in the book is that the investors who survive and thrive across long periods share a particular kind of temperament; what he calls equanimity. In other words, the ability to remain calm when the crowd panics, and to resist action when action is not warranted. Gayner is his clearest example.

This runs against everything Wall Street rewards. Financial culture prizes speed, activity, decisiveness. Gayner prizes stillness. He’s made a fortune from it.

The Markel Style

What makes Gayner unusual even among patient, value-oriented investors is that he refuses to separate his investment philosophy from his values as a person and an employer.

Markel operates according to something called the Markel Style, a document that has guided the company’s culture for decades. Its logic inverts the standard corporate hierarchy: customers win first, employees win second, shareholders win third.

If you genuinely serve the first two, shareholder returns compound naturally as a byproduct. Exploit either group and the whole machine corrodes.

Subscribe now

The Markel Ventures Family

This is where the Markel Style becomes most visible. Rather than owning a collection of abstract equity stakes, Gayner has assembled what he calls a “family of companies” — unglamorous, capital-efficient businesses run by people he genuinely trusts, operating with a high degree of autonomy under a shared set of values.

The portfolio spans industries that couldn’t feel further apart. And that’s precisely the point.

A few that currently call Markel home:

Markel Food Group (AMF Bakery Systems)

If you’ve eaten a fast-food hamburger bun, there’s a reasonable chance AMF’s equipment made it.

The company manufactures industrial bakery equipment used by customers to produce billions of buns, crackers, cookies, and pizzas annually. It was Gayner’s very first Ventures acquisition in 2005. Chosen, he said, partly because bread has been around for thousands of years and seemed unlikely to be technologically disrupted.

Costa Farms

The largest producer of ornamental plants in the world, founded in 1961 by Jose Costa and now a third-generation family business stretching over 4,000 acres globally.

This is Gayner’s philosophy made literal: a business so unglamorous it sells houseplants, compounding quietly for generations.

Brahmin

A creator of fashion leather handbags with significant wholesale distribution and a growing direct-to-consumer business, founded in 1982. Gayner said when Markel and Brahmin were introduced, it was immediately clear they shared the same business vision and culture.

Buckner HeavyLift Cranes

A provider of heavylift crawler cranes serving wind energy, data centers, semiconductor manufacturing, nuclear energy, and space markets.

Boring by any surface reading. Structurally essential to almost every industry building the future.

Havco Wood Products

Manufactures laminated oak and composite wood flooring for truck trailers, intermodal containers, and truck bodies. Floor panels for freight trucks. It couldn’t sound less exciting. It also isn’t going anywhere.

Others:

• CapTech: An IT consulting firm.

• PartnerMD: A concierge primary care and executive health company.

• VSC Fire & Security: Fire suppression systems.

• Ellicott Dredges: Industrial dredging equipment.

• Metromont: Precast concrete.

• Cottrell: Over-the-road car haulers.

• Lansing Building Products: Building materials distribution.

• Weldship: Industrial and specialty gas storage vessels.

Read that list aloud and you get a picture of what Gayner means by “a diverse and resilient family.”

Experts in bakery equipment, car haulers, IT consulting, medicine, industrial gas storage, ornamental plants, precast concrete, construction, fire protection, furniture, dredges, leather goods, trailer flooring, building products distribution. Not a single one of them will ever trend on social media.

That’s the whole idea. Every acquisition goes through the same four-part test: strong returns on capital with low debt; management with equal measures of talent and integrity; reinvestment opportunities with capital discipline; and a fair price. The industry is almost irrelevant.

The character of the business and the people running it are everything.

Share

Who this is for, and who it isn’t

Gayner’s approach will bore you during bull markets. When meme stocks are doubling overnight and AI darlings are soaring, a portfolio of unglamorous, capital-efficient businesses will feel like a punishment.

You will be mocked, at least implicitly, by your brokerage app’s performance tab.

That is the price of admission. If you can pay it — if you can hold through that grinding underperformance without flinching — the math of compounding will eventually reward you in ways that the hype cycle cannot.

If you can’t, that’s worth knowing too. The first thing Gayner’s philosophy asks of you is honesty about your own temperament.

Green’s book is worth reading in full for exactly this reason. Its central argument is that the best investors are not the ones with the best models; they are the ones who know themselves clearly enough to build a strategy they can actually sustain.

Three things you can take from Gayner today

• The 48-hour rule. Before any trade, wait two days. Then ask: is this driven by a real change in the business fundamentals, or by anxiety and the need to feel like you’re doing something? Most of the time, it’s the latter.

• Apply the four pillars ruthlessly. Not as a checklist to rationalize a decision you’ve already made. No, use this as a genuine filter. If a holding fails any one of the four, ask whether you’d buy it fresh today. If the answer is no, that’s information.

• Think about direction, not precision. You will not call the top. You will not call the bottom. Neither will anyone else, consistently. The question is whether the trajectory of your portfolio — its quality, its time horizon, its underlying businesses — is pointing the right way.

Richer, Wiser, Happier by William Green is one of the most honest books written about what great investing actually looks like from the inside. If Gayner’s thinking resonates with you, I highly recommend you give the book a read.

Hey everyone,

There’s a version of investing that looks productive: checking prices daily, reacting to earnings drops, rotating into whatever narrative is working this week.

And then there’s the version that actually builds wealth, which mostly looks like doing nothing while trusting that the businesses you own are quietly compounding on your behalf.

The recent SaaS selloff and AI panic have created exactly the kind of environment where these two versions diverge. When macro narratives shift, the market sells first and asks questions later. Great businesses get priced as if their terminal value has evaporated overnight. For a patient investor, that indiscriminate selling is an opportunity.

This month I’m running five positions and watching three more closely.

1. A company with proven switching cost moat embedded in European labour law, sitting 50% below its peak while the market sleeps on a regulatory catalyst I expect to matter a great deal by 2028.

2. A serial acquirer of software micro-monopolies, near multi-year lows, compounding through a process that cannot be replicated by capital alone.

3. A professional information giant the AI narrative has cut in half — where I believe the market is confusing adjacent to AI with threatened by AI.

4. The clearest real-world example I have found of the framework Nick Sleep used to identify Amazon and Costco before they became obvious.

5. And a niche UK software company where the management compensation structure, when I share it, tends to genuinely surprise people.

On the watchlist: three businesses I want to own but won’t buy at current prices. One at €35. One at $130, with $6.5 billion in net cash and a 50% drawdown from the all-time high. And one I considered over a position I did buy this month. the business quality is arguably higher, but at today’s price I’d be paying nearly three times as much per dollar of earnings.

The names and full reasoning are below:

Read more

As I mentioned, I want you who’ve been in ‘the bunker’ since the beginning to get the best deal. Today, that Founding Member tier is officially open.

This is how pricing will work:

1. The first 35 subs will get everything for $99 per year (update: 35/35 spots taken). To sweeten this deal even further, these will be grandfathered at today’s level.

2. The price for an annual subscription is $199 after this.

3. Then, it will increase to $350 per year once we cross 100 paid subscribers.

Subscribe now

What changes when you upgrade

Just to reiterate: Money Mind, Simple Truths, and Titan Test stay free. All the deep dives published up to this point stay free.

The paid tier is a proper home for the work that goes deepest. By upgrading, you get exclusive access to:

• All upcoming Deep Dives & Valuation Teardowns: The comprehensive work that takes a full weekend or more to build.

• Forensic Balance Sheet Analysis: Looking under the hood to find what others miss.

• The Live Multibagger Index: Tracking the highest-signal opportunities in real-time.

• My Portfolio & Portfolio Moves: See exactly how I allocate capital.

• My watchlists: See what companies are currently in my investing universe. Watchlists are split into founder-led, Nordic quality, 100-bagger potential companies, and more.

• FINS: Earnings numbers broken down in an easy-to-understand way.

You all have helped build the highest-signal investing community I’ve been part of. If you value the models, the pushback, and the honest research we’ve shared over the last few months, this offer is for you.

Subscribe now

Thank you to everyone who has already stepped up to support the work. I don’t take it lightly.

Back to work.

— Rob

When I started Atomic Moat back in December last year, the goal was simple: build a research process I could trust, and share it honestly. No noise, no engagement bait, no lazy hot takes. Just the work.

What I didn’t expect was how many of you would show up for exactly that. Over 1,400 of you now. I get replies with your own models, pushback on my assumptions, and the occasional catch I missed entirely. This is the highest-signal investing community I’ve been part of. That’s on you, and I don’t take it lightly.

So before anything else: thank you. Seriously.

Where Atomic Moat is heading

I’m turning on paid subscriptions.

Let me be completely straight about what that means, and what it doesn’t.

Everything you’ve been reading (Money Mind, Simple Truths, Titan Test) stays free. Always.

The paid tier exists because the research has outgrown what I can sustain as a side project. Simple as that.

Every deep dive that’s already been published stays free. If you’ve saved something, shared it, or want to go back to it, it’s yours. The paywall only applies to what comes next.

What it adds is a proper home for the work that goes deepest: full valuation teardowns, forensic balance sheet analysis, and the live Multibagger Index dashboard. The stuff that takes a full weekend to build and deserves more than a footnote.

What’s coming next

In one week I’m opening a founding member tier.

A limited number of spots at $99/year, locked in permanently, no matter what the price becomes later. Those of you who have already pledged higher amounts than this will also get this deal.

If you’ve been here a while, if you open these posts, if Atomic Moat is part of how you think about investing: that offer is for you.

I want the people who’ve been in the bunker since the beginning to get the best deal.

Until then, nothing changes. The next post lands in your inbox exactly as it always has.

Back to work.

— Rob