On July 13, I published my deep dive on Dino Polska. The stock is up 27% since. That is pleasant to see. My estimated 5-year CAGR was in the range of 11-26%, with a weighted average of 16-17%, so it seems like that estimate is, as of today, well on track.

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Despite the recent rally, if you zoom out a little, over five years, the stock is still pretty much flat.

And of course, eleven weeks of price action could just as quickly reverse and tell me almost nothing about the intricacies of the business and the customer experience.

My research from a few weeks ago was also built from annual reports, store counts, demographic tables, expert interviews, and management commentary.

What it lacked was the view from inside the store. I have never stood at a Dino meat counter in a village of 2,000 people. I have never had to decide whether to walk to the nearest shop for a pack of butter or drive twenty minutes to a Lidl. My thesis leaned heavily on assumptions about how rural Poles shop, what they value and whether any of that is shifting, and I had no way of testing those assumptions from my desk in Düsseldorf.

For companies that operate in a region where you don’t live, that “understanding gap” is enormous. I have come to believe that understanding customers, what they need, what they appreciate and what slowly wears on their patience, should be a core pillar of every investment framework.

FICO is perhaps the freshest reminder. A business that looked like it had untouchable pricing power has lost almost three-quarters of its value, but it seems like it flexxed that pricing power muscle too much. Cracks in a thesis very often show up first among customers and the people (or regulators in this case) closest to a company’s products.

By the time they reach the income statement, the market has usually moved on.

Tiho Brkan shared a chart the other day on X, and privately, that has stuck with me and came to mind when writing this intro (see below).

His commentary on it is worth quoting in full:

“Fundamentals are forward-looking expectations. They project what might happen in the future, and the wisest of investors have several case scenarios (rookies anchor to one plausible future only). Here, it is all about the future, and when discussing fundamentals, we are reasoning with foresight. What is the key takeaway? Financials are what everyone gravitates to, as their difficulty is manageable. However, they have very little value and are often already discounted or baked into the price. Fundamentals are what everyone shies away from (or probably cannot even distinguish from financials), as they are extremely complex. However, that is where all of the value sits, as they are not discounted or baked into the price.”

Again, I bring up Tiho's take because it gets at why this follow-up arrived in your inbox today. In July I did the backward-looking work, and I also laid out where I think Dino is heading: the store rollout, the reinvestment runway, margin durability and the risks that could derail all of it. That is the foresight Tiho describes, the part of the chart where the value is. Foresight rests on assumptions, though, and mine were built from filings, industry data and demographic tables that I studied at my desk in Düsseldorf. They assume rural Poles will keep choosing proximity and a good meat counter over everything else, that the labor pool will hold up and that the competitive landscape looks the way the reports describe it. If any of those assumptions starts to crack, customers, employees and locals will notice long before it appears in a quarterly report, just as FICO's customers, lenders and regulators did. I wanted to hear from those people directly, to find out whether the future I sketched matches what they see on the ground.

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Thus, this brief follow-up to me deep dive is my attempt to understand Dino a little better, so I sent a list of questions to three people with boots on the ground or local roots or connections. Many of you will know:

• Michael from our community, where he is one of the most active voices, and he also writes Personal Finance Without Borders on Substack. He passed my questions to his partner, who grew up in Kielce and still has family in the Polish countryside, so those answers come straight from someone who knows these villages firsthand.

• Mathijs is one third of The Dutch Investors. He has owned Dino for two years and has visited five of its stores across two separate trips. I owe the connection to his fellow Dutch Investor Siem, who I joined on his podcast recently and was supposed to sit down with me again tomorrow, a conversation we had to push back because of the events I shared in my email yesterday.

• Jakub (Marlowe on X) needs little introduction for regular readers. He is a Polish independent analyst who studied at Jagiellonian University, started investing in the middle of the 2006 construction bubble and still talks to Dino staff when he is back home. He was spot-on about InPost, and I will never forget that our bullish podcast episode on the company went live one day before the acquisition offer was announced. You can’t plan timing like that. If you don’t follow his work yet, you can find him on X (link above).

Their answers confirmed parts of my thesis, complicated others, and raised a few risks I hadn’t even thought to worry about. You will learn why every shopper seems to bring up the meat counter unprompted, why one employee described working at Dino as “hard, hard bread,” who Dino is actually taking market share from (hint: it’s mostly not Biedronka), and why a demographic detail about who leaves rural Poland might matter more than any store count.

This is also the first post in a format I plan to repeat. Whenever I publish a deep dive, I might go back to people with firsthand expertise and run a short follow-up interview that pressure-tests what I wrote. Feel free to message me if you think a follow-up interview would fit to one of my prior (or future) deep dives. The next one is already lined up with Joe from Goldman Won’t Cover This on Intuitive Surgical.

Let’s start with the people who actually shop there.

Disclaimer: As of the date of publication the author owns shares in the company; but that may change. The interview guest may hold positions in the companies discussed. The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.

Intro

Mathijs: My name is Mathijs, co-founder and analyst at The Dutch Investors. Generally, I’m looking for companies with a strong market position, that structurally outperform competition, that generate high returns on capital and where management’s incentives are well aligned with shareholders. Dino Polska has been on my radar for around two and a half years now and I took my first stake two years ago. In the past two years, I have visited five Dino Polska stores in two different time periods to do research for myself and as part of research for The Dutch Investors.

Michael: Responses from my partner who grew up in Kielce (eastern Poland)

Jakub: Thanks for having me, René. I’m an independent equity analyst and investor, and I’ve published research since 2021. I’m Polish, I studied at Jagiellonian University, and I’ve been based in the UK since 2014, so I know Poland from the inside, though I now follow it from a bit of a distance.

I started investing in 2006, right in the middle of the Polish construction bubble. I remember watching pizza companies turn into construction companies, which tells you everything about where that cycle was. I sold about half my portfolio in August 2007, then watched the rest fall, with some stocks down 90%. I bought again in early 2009 and doubled my money, helped a lot by how cheap the market was. After that I spent about five years running my own businesses rather than following the market.

I came back to investing properly in 2019 with a quality-focused approach: high returns on capital, low debt, owner-operators. Since then, I’ve kept refining the strategy and the analysis, and the InPost work is where it showed up most clearly.

That history shapes how I look at Dino. I’ve seen what a boom in Poland looks like when balance sheets are weak, and Dino is the opposite of that. And the timing is interesting. At around 35 PLN a share, Dino has a market cap of roughly 35 billion PLN, about where it was in 2020. Since then, the business has grown a lot in stores, revenue and earnings, and the market has paid essentially nothing for that growth. That gap is what I want to talk about.

On the actual shopping experience

Mathijs: So, I’m not from Poland myself. However, the company I work for does have a large production location in Poland, so I also spoke to some colleagues from there. The main reason is location, which probably connects to the habit reason you’re referring to. From what I heard and saw, consumers shop there for daily groceries. So yes, meat, vegetables. Need toilet paper on Tuesday? Rush to Dino. Of course, the location-reason only applies to people living in rural areas. In cities, you will find more Zabka’s and Biedronka’s.

Michael: The main reason for choosing one over another is most likely the proximity, and then how well stocked they are. But for the basic day-to-day shopping, you get to choose from Dino, Lidl, Biedronka, Kaufland, Auchan, Tesco. I think these are the main supermarkets, and then sometimes also Netto. But yeah, for day-to-day stuff, usually you would just go to the one that is the closest because honestly, the price differences are not so much on the day-to-day products. And then if you are doing a bigger shop, or you need something specific, then this is where you would go to any of the supermarkets that would have it. I think for some of the young people who are now into the healthy lifestyle and eating fit, high-protein diet, then this is where they may prioritize Lidl and Biedronka because these discount shops have a lot of products that are basically their brand. And they have, yeah, they are those fit products for a very good price.

Jakub: Honestly, the biggest single factor is proximity, not price. There are two different shopping modes going on in a small Polish town. There’s the actual weekly shop, where you take the car and load up at Lidl, Aldi, Biedronka, Kaufland or Dino, and there’s the top-up trip: you ran out of cigarettes, or beer, or cream, or your kid wants crisps, and you just walk to whichever shop is closest. A lot of small local chains, the Globi’s, Zabka’s and Groszek’s of this world, live almost entirely off that second kind of trip. I’ve done it myself, popped into a Globi for pierogi because Dino was too far from where I was staying, even though I’d normally choose Dino given the option.

Mathijs: I don’t think so. If I had to choose, I would think Lidl and Biedronka offer more perceived quality of their products. Shops look nicer and are more modern.

Michael: Dino is known for having high-quality meat counter items. But everything else are products that are available in other shops.

Jakub: Where Dino does win on something other than proximity is the meat and dairy counter. Every person I’ve spoken to who shops there volunteers the same thing unprompted: the meat is good, it’s Polish, and the cheeses are good. That’s not marketing language, it’s what people actually say. And it’s backed by something real: Dino carries around 5,000 SKUs per store, roughly double what Biedronka or Lidl carry. So it doesn’t feel like a discounter to shoppers, it feels like a proper one-stop supermarket that happens to be priced competitively. That’s a real structural difference from the hard-discount model, not just a perception thing.

Mathijs: Again, I’m not from Poland. However, I do think Dino is less vulnerable to a shift to online grocery shopping, because people go there multiple times a week and do weekly shopping at Lidl or Biedronka (wider assortment, larger space).

Michael: From a perspective of someone who lives in a big city and has parents and siblings in the countryside, I think that there is a big divide between how younger people in the city versus younger people in the countryside shop. I think the city is very much bought into the crave of this healthy lifestyle, and maybe not healthy lifestyle, but just high protein and fit and so on and so forth. While in the countryside, in order to get these products, you would have to get out of your way. So I think that younger people in the countryside shop like their parents, just because of the infrastructure, the shopping infrastructure that is available in the countryside. The majority of them would not be using any e-commerce or online delivery apps, because the cost of that service in the countryside is more expensive, and so that often will be perceived as a waste of money to pay for the delivery as opposed to go and shop, unless you are in a certain social group that doesn’t really care about the cost of the food.

Jakub: On generational shift, I’ll be honest, I don’t have a real insight there. I can tell you how the two shopping modes work, but I don’t have evidence either way on whether younger rural Poles behave differently from their parents. I’d rather say that plainly than guess at a trend I haven’t actually seen.

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On local reputation and brand perception

Mathijs: I don’t know to be honest.

Michael: Don’t know

Jakub: On the labour dispute specifically, I did some digging myself, I spoke to staff at three different Dino stores in one town. Nobody brought up the dispute unprompted, and when I nudged the conversation toward working conditions, the answers were mixed but not alarmed. It’s physically hard work, long shifts, constant restocking, cross-trained across meat, bakery and till, and there’s essentially no benefits package beyond base pay. What makes it bearable, by their own account, is the local team and manager, not anything the company provides structurally. One phrase has stuck with me: one worker called it ‘hard, hard bread,’ and said the only reason she liked her store was that she liked her colleagues, not because of how Dino treats them as a policy matter. So it’s not glowing, but it’s also not the picture of crisis you’d get from the strike headlines. My read is that this is as much a sector-wide rural labour shortage as a Dino-specific failure. In the same conversations I heard that Lidl locally is so desperate for staff it reversed a rejection and accommodated a candidate’s preferred shift two months later.

Mathijs: I definitely don’t think that’s a factor in Poland.

Michael: They are all reasonably cheap. Dino isn’t perceived as a budget option. It really is about proximity.

Jakub: On stigma, I haven’t seen any. Nobody treats shopping at Dino, or at any of these discount-adjacent chains, as something to be embarrassed about. People shop wherever’s closest without a second thought, and that includes people who could clearly afford to shop elsewhere.

Mathijs: Don’t think so. I remember one media appearance when he allegedly crashed his Ferrari. So, that might have given him some (unwanted) attention.

Michael: The answer was who is Tomasz Biernacki? :D He is very low profile.

Jakub: On Biernacki, he’s genuinely invisible. Most Poles outside investing or retail circles wouldn’t recognize his name, let alone his face. He does no politics, no media, no personal branding. I actually find that refreshing, especially coming from following InPost, where Brzoska is constantly in the press and occasionally wading into political territory. It removes a lot of headline risk. The tradeoff is that it also means very little visibility into his intentions long-term, but as a day-to-day matter, he’s a non-factor in public life.

On competitive dynamics I can’t see from outside

Mathijs: Apart from Biedronka, Lidl, Dino and Zabka, I noticed a supermarket chain called Eurocash. They seem to be struggling and not keeping up with growth.

Michael: There are others: Stokrotka, Netto, Lewiatan. Then also larger scale ones like Auchan and Kaufland. On the smaller scale you have Zabkla (more in cities) and ABC (in countryside).

Biedronka and Lidl focus on towns while Dino can be in the middle of nowhere. Lewiatan is the real direct competitor in rural areas although this may differ in other parts of the country.

Some small towns also have one-off family-run supermarkets.

In many countries, the population is concentrated in towns or villages or cities, while Poland has this specific type of a village or a human settlement, whereby the population is not concentrated in one geographic area, but it may be concentrated along the road-front, which basically gives you long spread-out human settlements that may be far from the nearest village or the nearest town, but still needs to go and shop somewhere. This is very characteristic for Poland.

Jakub: The ‘just Biedronka and Lidl’ framing misses a whole layer. In my own small town alone there’s also Aldi, Lidl, Kaufland, Żabka, and then a long tail of smaller names: Lewiatan, Delikatesy Centrum, Groszek, PSS Społem, Wizan, Globi, Netto, Euro Market, Delfin. But I’d draw a sharp line between the first group and the second. The small local chains aren’t really competing with Dino in the way Biedronka is, they’re the ones getting displaced by it. Most of them are franchise networks or old cooperative structures with weak central buying power and aging stores, and Dino’s standardized, owned-real-estate format is eating their volume year after year. That’s a big part of where Dino’s growth actually comes from, not stealing share from Biedronka, but absorbing what used to go to a Społem or a small Lewiatan franchisee.

Mathijs: No. And I don’t think these companies can ever be profitable in rural Poland. The distances are too long and population is too spread. Similar companies even went bankrupt in major cities like Amsterdam and Rotterdam. Different country, but still.

Michael: No – haven’t noticed this for shopping.

Jakub: On quick-commerce, I’ve seen zero evidence of Glovo or Bolt Food or anything like that making any inroad into rural Poland. That’s a big-city phenomenon. The population density and income levels in these small towns don’t support a delivery-rider business model, so I don’t see it as a threat to Dino’s proximity advantage any time soon.

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On demographics and regional nuance

Mathijs: Or turn it around, Dino’s are profitable in villages with just 2,000 inhabitants. Lidl and Biedronka are not. So, if villages become too small to them and they leave, this will offer more potential customers for Dino?

Michael: Better to use data for this as it would just be anecdotal.

Jakub: On depopulation, I don’t have strong ground-level insight into east versus west specifically, but I’d flag something that complicates the simple ‘young people leave for the cities’ story. There’s been noticeable return migration of Poles who’d been working in the UK, and Ukrainian settlement reaching even small towns, not just the big cities. So whatever outflow exists is being offset, at least partially, by two different inflows. I wouldn’t assume net population in these towns is falling as cleanly as a simple depopulation model suggests.

Mathijs: To be honest, I didn’t notice any difference. Have been to Krakow and surrounding villages, between Krakow and Auschwitz. Not that different compared to the ones around Leszno in the West.

Michael: Eastern Poland is different from Western Poland. Eastern Poland historically has been poorer and more underdeveloped. And even though there has been some progress, it still remains like that, specifically at the eastern border, and now also with the Ukrainian conflict. These areas are depopulating faster. So that may impact whether shops can actually sustain themselves.

Mathijs: I don’t dare to answer this question. Really have no clue. My thesis is fully based on expansion in Poland.

Michael: No idea

Jakub: On adjacent-country expansion, I’ll be honest about where I stand: I haven’t seen any real signal from management that they’re planning to move into Lithuania, the Czech Republic or Slovakia. The whole model depends on owned real estate built specifically for this format, and a captive meat and logistics supply chain built around Agro-Rydzyna, which is very Poland-specific. That’s a harder thing to export than just replicating a store layout. My honest hope for this stock is much less exciting than international expansion, it’s that they keep doing exactly what they’ve been doing in Poland for another decade, the way Lidl and Aldi have done across their home markets, and that I get to just hold it. If, however, they decide to expand to other markets, I will gladly watch it unfold and hold through it. The alternatives are buybacks or dividends, each can be good ten years from now. I would hope for international expansion eventually though.

On regulation and local politics

Mathijs: I think these are well enforced and respected. Just like in Germany in my experience.

Michael: They do apply but Some shops like Lewiathan and Jablka have a way around it due to their model whereas Dino and other big companies are closed on Sundays.

It comes down to this: by law, company-owned shops cannot open on Sundays and “owner-operated” shops can. Because of their franchise model most leviathan shops are owned by independent entrepreneurs – these can open on Sunday. I think some Lewiatans are owned by companies (who own several franchised stores) and these ones can’t open on Sunday.

In theory, under the “owner-operated” exemption, the owner must personally work in the store on that Sunday. In practice that doesn’t happen for Lewiatan and Jablka (the same normal employees work on Sundays as other days)

Jakub: Sunday trading is properly enforced, not a paper rule with workarounds. Some Sundays are legally designated as trading days and the stores are open, others are closed, and Dino doesn’t have any way around that given its size. The only shops that can open on a closed Sunday are genuinely small, owner-operated ones where the owner is physically working the till themselves.

Mathijs: Don’t know

Michael: No idea

Jakub: On land and zoning friction, I haven’t come across anything, no disputes, no resistance from local shop owners showing up in local coverage. That’s a non-finding rather than a confirmed clean bill of health, since I haven’t gone looking specifically, but nothing has surfaced.

Closer

Mathijs: I’m a foreign investor myself :)

Michael: Depopulation/rural to urban migration is the main worry and it is happening everywhere.

It seems that more women have left rural areas for cities than men so you have a mismatch with more young single men than young single women in rural areas. If it continues like this, then depopulation could be even more of a problem.

Jakub: I’d push back on the framing a little. I’ve never needed Dino to be dominant. My thesis isn’t that they’ll own the Polish grocery market, it’s that they can keep opening owned-real-estate stores at a high return on capital in a fragmented space full of weak legacy competitors, for a long time. So the question I ask myself isn’t what threatens their dominance, it’s what breaks that reinvestment machine.

A few things would genuinely worry me. First, labour. Rural Poland’s labour pool is tighter than people assume, I’ve heard first-hand that Lidl is having to bend over backwards to staff a small-town store. If wage inflation keeps climbing there, that shows up in margin before it shows up in any headline.

Second, Biernacki himself. He’s completely invisible, no media, no politics, nobody in Poland even knows what he looks like. I actually like that, it removes a lot of the key-man drama you get with someone like Brzoska at InPost. But it cuts both ways: nobody outside the company has any real visibility into his succession plans or long-term intentions for a 51% stake.

Third, simple saturation. The easy small-town white space won’t last forever. Once it’s gone, growth capex either slows or moves into harder, more marginal locations, and that’s the point where you’d see whether the returns hold up. Who knows, maybe we’re there now?

If I had to name what would break the thesis rather than make me nervous for a headline or two, it’s one of those three.

Outro

A big thank you to Mathijs, Michael and Jakub, and to Michael's partner, for taking the time to answer my questions so openly and honestly. I have read their answers several times now, and each round left me with a sharper picture of Dino.

Several of them were comfortable saying "I don't know" when they didn't, and I value that just as much as the insights. If you enjoyed their perspectives, please support their work. You can find Michael at Personal Finance Without Borders, Mathijs and his partners at The Dutch Investors, and Jakub on X (I linked their respective online presences in the intro). I am looking forward to the next edition of this format with Joe on Intuitive Surgical, and if you have firsthand expertise on a company I have covered and would like to take part, my inbox is always open.

Ember Infrastructure Management's 615p proposal for Ashtead Technology has put one of my positions in a new light.

For now, the market is treating the approach with caution. The shares still trade at a noticeable discount to the indicated level, which tells me investors see the odds of a completed deal as moderate at best and expect any timeline to stretch well beyond twelve months.

I believe Ashtead's intrinsic value is higher than 615p, so I have not made up my mind yet on what to do exactly. Should the gap narrow, though, decreasing the expected forward return, opportunity cost starts to matter more and more, and selling could become the rational move, especially because I have some interesting-looking ideas on my radar.

In that case, a meaningful chunk of capital would need a new home, and I could also see myself diversifying the new funds across multiple ideas (Ashtead is now >20% of the portfolio).

As an investor, you always have to be ready. Opportunity rarely sends a calendar invite.

So I have started mapping out capital allocation scenarios. Seven companies currently rank highest on my watchlist, and in this new series I will walk through each of them using my perception change framework.

My Perception Change Framework:

• 2026-01: My “Perception Change” Framework – Technical Analysis (Part 3) - ($)

• 2026-01: My “Perception Change” Framework – Qualitative Instruments (Part 2) - ($)

• 2026-01: Playing a Different Game: When Fundamentals Aren’t Enough Anymore! (Part 1)

Every idea gets the same set of questions:

• Could now be an opportune moment to buy?

• Is sentiment bombed out, or is there still some air left to let out?

• What is the price trying to tell us?

• And beyond the supply and demand dynamics of the stock, which new qualitative insights have I picked up that change how I think about the business?

My original plan was to cram all seven into a single post. The further I got, the clearer it became that this would turn into a monster few people would ever actually finish. I sometimes wonder how many people actually read my 10,000-word+ deep dives. If you look at the cold, hard data of the number of 10-Ks that are actually downloaded by all investors globally (spoiler: it’s shockingly low), the actual number of readers of my deep dives may be disappointing.

Fun fact: Using the SEC's own server logs, Loughran and McDonald found that the average publicly traded company had its annual report requested only around 28 times by investors right after filing.

Anyway. Each idea now gets its own piece, short enough to read in one sitting over your morning coffee or on the train to work.

Two and a half of them are already written, so the rest of the series should land over the next seven to ten days.

Idea number one is a company where the CEO just put roughly $30 million of his own money on the line, and where I added to my own position only a few days ago.

Disclaimer:

As of the date of publication the author owns shares in the company; but that may change. The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.

Idea #1: Grab Holdings

What is the price trying to tell us?

Grab lacks a clean multi-year trend to lean on. After collapsing from its post-SPAC highs in 2021 and 2022, the stock built a slow uptrend off the late-2022 low of around $2.30, which eventually carried it to roughly $6.40 by September 2025. Nearly all of that advance has since been handed back.

The downtrend that started in September 2025 is the more useful line. It has multiple touchpoints, and it has not been broken, let alone tested and confirmed.

Even after the mid-teens rebound from last week’s low, the share price would need to climb roughly another 10% just to reach it.

What catches my eye is where the selling stopped. At $2.74 this months, Grab traded at its lowest level since May 2023.

Grab has punished its shareholders for a long time. The stock sits more than 80% below its all-time high, the five-year annualized return stands at roughly minus 21%, and even the three-year CAGR is negative.

The current down year, roughly minus 36%, followed three positive years, however, which makes the damage look less one-sided than the drawdown alone suggests.

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Anyone who bought Grab during 2023 or 2024 was still sitting on a gain as recently as last fall.

That is why sentiment in 2026 strikes me as rather bad, though not completely bombed out.

Volume is the more encouraging signal. September brought the heaviest trading of the past twelve months, with several sessions well above 100 million shares against a one-year average of roughly 50 million, and the spike clustered around the low.

As I argued in my perception change series, high volume near a trough is what capitulation tends to look like, so this might signal a bottom in the making. One heavy week does not confirm a reversal, though.

Short interest supports the negative sentiment read. At about 6.4%, it has more than tripled since mid-2024 and peaked at close to 8% this summer, which is notably high for Grab, although not extreme in absolute terms.

Should perception turn, that positioning could become fuel for the move.

All my prior analyses of Grab:

• 2026-05: Valuing Grab Holdings Post Foodpanda and Stash Integration - ($)

• 2026-05: Grab’s Q1 Paradox – Record Profits Meet the Indonesian Regulatory Wall - ($)

• 2026-05: Grab Holdings Ltd ($GRAB) – Master Piece - ($)

• 2026-04: Grab Holdings Ltd ($GRAB) – Part 4 - ($)

• 2026-04: Grab Holdings Ltd ($GRAB) – Part 3 - ($)

• 2026-04: Grab Holdings Ltd ($GRAB) – Part 2 - ($)

• 2026-04: Grab Holdings Ltd ($GRAB) – Part 1 - ($)

Which new insights change how I think about Grab qualitatively?

The full analysis starts here!

Become a paying subscriber to read the rest of this post (and access the next six ideas too), and get access to all of my other deep dives, my global watchlist, the WhatsApp community, the digital conferences, and more!

Read more

We start with Terence Tao’s idea that mathematics is moving from an era of proof scarcity to one of proof abundance, and ask whether investment research is next. From there we compare notes on how our workflows have changed over the past few months, what the latest models make possible, and where we let agents run unattended while still insisting on doing certain work ourselves.

We also dig into Mostly Borrowed Ideas’ claim of having built a last financial model from scratch, and Thomas Peterffy’s counterpoint that AI is far better at assembling facts than at projecting the future. The conversation closes on what becomes scarce once research is abundant – judgment, capital allocation, and the trust between investors who know each other.

If you want to go deeper, join our online community meetup on using AI in the investing process on October 3, 2026: [LINK]

FIND US

• Compound with René – compoundwithrene.com

• Compound with AI on Substack – aiinvestinghq.com/

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DISCLAIMER: The content provided on this channel should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. The stocks and funds discussed on this channel are examples only and may not be appropriate for your individual circumstances. Before making any financial or investment decisions, I recommend you consult a financial planner or advisor to take into account your personal investment objectives, financial situation, and individual needs. In no event shall René Sellmann be liable to any viewer for any damages of any kind arising out of the use of any content published on this channel, including, without limitation, any investment losses, lost profits, lost opportunity, special, incidental, indirect, consequential or punitive damages.

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Eight pillars, eight “BAMs,” each with its own attempt to invert the argument, the company history that starts with DARPA-funded battlefield research, a competitive landscape that shifted twice this summer, a management review, and a valuation model with margin assumptions and a granular breakdown of the drivers of topline growth.

Not everyone has an evening to spare for that.

So I condensed the whole analysis into a 19-slide companion deck. It follows the same logic as the written series. It opens with the hypothesis and the four developments that would prove it wrong, walks through how the company got here, how the business makes money, gives each of the eight pillars its own slide, and then covers competitive positioning, the customer, growth drivers, and valuation.

Here's one slide to give you a sense of how the argument gets compressed:

A quick note on my latest process: This is the first deck I built with Claude Design as opposed to building it with the regular Claude model (I should test 5.5 next, I guess), and the difference for me was the ease of editing. Instead of regenerating the whole thing every time something was off, I could make fine-tuned changes to the first draft slide by slide, adjusting a chart here, fixing overlapping items there, and tightening a headline until each slide looked like what I wanted it to.

I’m still unsure which model’s output I like better, though.

To get a feel for the quality of these decks, check out the companion deck I shared along with my Amadeus deep dive (you can find it here).

As a remnder, from now on every deep dive now comes with a companion slide deck. The whole hypothesis in compressed form – the thesis, the business, the competitive position, the valuation, and the case against – for the days when you don't have an hour to spare but still want a quick glance at it. Paid subscribers get both, always: the long written analyses and the decks, for every deep dive.

Download the Deck:

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Today, I want to start with a small experiment.

Imagine this … you are only allowed to use one metric to judge whether the stock market is cheap, fair, or expensive. You get no macro data, no margin analysis, no sentiment surveys.

You pick one metric and have to live with it for the rest of your life.

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The choice is between the Shiller PE (the cyclically adjusted P/E, or CAPE) and the regular P/E, on either a trailing or a forward basis.

Which one do you take?

Please stop reading here for a minute. Think it through, commit to an answer, maybe write your reasoning in the comments too before you read the rest of this post and before you look at what anyone else wrote.

Leave a comment

Once you’ve seen my argument or someone else’s, your own thinking gets anchored, and the exercise loses most of its value. If you change your mind by the end, leave a second comment and tell me what moved you.

Done? Good. Let’s go.

How a Comment Thread Led to This Post

This question came out of an exchange on Substack Notes. A reader – – argued that bears reach for the Shiller PE because the regular P/E doesn’t support their crash narrative.

His case against CAPE was pointed and, to be fair, pretty intuitive. The Shiller PE divides today’s price by the average of the last ten years of inflation-adjusted earnings. The largest companies have grown their profits so much over that decade that the average is stale.

Ten years ago, Wells Fargo was among the ten largest US companies by market value. Why should 2016 earnings carry the same weight as 2025 earnings when you are assessing today’s market?

He added that today’s megacaps sell worldwide and scale in ways that were unthinkable in the 1930s or even the 1990s, so maybe CAPE becomes useful again once these businesses mature.

Those are all fair points.

Despite that, my answer to the theoretical question I posed in the opening of this post and that I superficially discussed with FJ in the Notes comment section was still …

“I’ll go with the Shiller!”

And it wasn’t a close call for me.

Today, I decided to take the question apart properly and give it some more thought.

First, the numbers. They explain why the debate gets heated. As of September 1, 2026, the CAPE ratio stood above 41x, the second-highest reading in more than 150 years of data, according to multpl.com.

By one count, only 20 months since 1881 have been higher, all of them in 1999–2000 or 2026.

The regular P/E tells a much softer story. Multpl puts the trailing 12-month P/E at 26x, above both its 5-year average of 24.4x, its 10-year average of about 23-24x, and its long-term average of about 16x …

FactSet puts the forward 12-month P/E at 19.1, slightly below its 5-year average of 19.8 and roughly in line with its 10-year average of 19.0.

So, depending on which number you use, the market is either at dot-com levels or roughly at its ten-year norm.

That gap is massive and is what prompted the whole debate in this post.

Welcome to Compound with René. You can find an overview of the companies I shared a deep dive on in the visualization below.

If you haven’t subscribed, you can join 5,000 readers who enjoy the quality of the deep dives, the process-oriented pieces, the analytical insight, and the valuation discipline, here:

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My Three Lenses for Good Decision-Making

When I try to think clearly about a hard question, I test it against three cornerstones:

• common sense,

• empirical evidence, and

• theory.

Each one on its own is dangerous. Common sense without evidence produces confident stories. Evidence without theory produces data mining, and you end up finding patterns that don’t mean anything. Theory without common sense produces elegant models that fall apart the first time they meet with the real world. As one of my favorite sayings goes, “in theory, theory and practice are the same. in practice they are not.“

Good thinking tends to happen where the three overlap, so that is how I’ll structure the rest of this post.

Common Sense Test

Start with the common sense test. A P/E ratio is a price divided by a single year of profits.

Anyone who has ever owned a cyclical stock knows what that implies: the denominator can be badly misleading at exactly the moments when judgment matters most. I wrote a blog post titled “The 10 Hidden Dangers of the PE Ratio: The Definitive Guide to Wall Street’s Most Overused Metric“ this year, discussing some of the flaws of this metric - read it here:

At the bottom of a recession, earnings collapse and the P/E spikes, which makes the market look outrageously expensive just as it is cheap.

Conversely, at the top of a boom, earnings are inflated by peak margins, so the P/E looks reasonable just as risk is highest.

And this isn’t a hypothetical claim. GuruFocus records the all-time high for the S&P 500 P/E at 131.4, a reading from the 2009 earnings collapse, which was one of the best buying opportunities of the past half-century. A metric that flashes its most extreme warning at the best entry point is hard to trust as your only tool.

Common sense cuts the other way too, and I want to give my counterpart his due here. If a company tripled its earnings over ten years, and most of that increase is durable, then averaging in the smaller early years understates what the business earns today.

So common sense alone doesn’t settle anything. It tells me that one year is too noisy and that ten years may be too conservative.

Which of those errors is larger right now is an empirical question.

There’s one more point I’d push back on, though. The claim that the regular P/E sits within its normal range only holds for the forward version. Since 1871, the median trailing P/E of the S&P 500 is about 18, and today’s reading ranks around the 80th percentile of all recorded values.

Both metrics say the market is expensive. The disagreement is over how expensive.

Empirical Evidence Test

The empirical case for CAPE is the reason it became famous. A Vanguard analysis found that CAPE explained about 43% of the variation in subsequent 10-year returns between 1926 and 2011, which is high for anything in finance; yet, at the same time, the authors note that “although 0.43 is high for an asset whose returns are assumed to be random, it gives CAPE critics a reason to dismiss its value.“.

Other periods look even better: measured from 1975, the figure rises to roughly 85%.

Here’s another cool chart from the source above, showing the expected return on an equity portfolio over the next 10 years based on different CAPE starting multiples.

As far as I know, Cliff Asness also ran the direct comparison in his 2012 paper on the Shiller P/E (“An Old Friend: The Stock Market’s Shiller P/E“), testing the one-year P/E against the ten-year version, and found that the smoothed measure did a better job of forecasting long-horizon returns.

He also arrived at a similar conclusion as the authors further above:

“Ten-year forward average returns fall nearly monotonically as starting Shiller P/E’s increase.”

He also makes another important point which I want to stress myself:

“Even with the caveat above, I would, if trading on a tactical outlook, give the Shiller P/E some small weight, particularly when it’s above 30 or below 10.8 But I think this type of analysis is most useful not for a trading strategy but to set reasonable expectations.“

These tools are not timing tools. They simply help set reasonable expectations (in ranges) for very long-term returns.

And one more point from that research paper, as he raises exactly the same controversy I’m raising in this article:

“They point out that we had two serious earnings recessions recently (though only the tail end of the 2000-2002 event makes it into today’s Shiller P/E), including one that was a doozy following the 2008 financial crisis. They thus feel the final (the right end of the graph) strong earnings number is more relevant than that of the prior 10 years. In principle, we must grant that there are times that 10-year earnings may be misleading. They are by no means a panacea. If the last 10 years is much better or much worse than might be expected going forward, the Shiller P/E can indeed be locally “broken” as some would call it now. It’s certainly possible that one-year earnings could give a more accurate picture at such times. The question is, of course, are we in such a time right now? Not surprisingly, if one compares one-year earnings to history, things look much rosier, though the stock market is still not cheap. 11 Instead of a Shiller P/E that is in the 80th percentile versus history right now (expensive), the one-year P/E is in the 54th percentile since 1926 (trivially expensive). So we have to ask ourselves, is the argument against using the Shiller P/E today right? Are the past 10 years of real earnings too low to be meaningful going forward (meaning the current Shiller P/E is biased too high)? Quite simply put, not even close.“

Newer research also speaks directly to my reader’s Wells Fargo objection. The traditional CAPE compares today’s index to earnings produced by a partly different set of companies ten years ago.

A January 2026 working paper by Ma, Marshall, Nguyen, and Visaltanachoti rebuilds CAPE from the bottom up. It computes each current index member's own ten-year CAPE and then weights those by market cap.

“The Component CAPE ratio weights individual stock CAPE ratios by their market capitalization, whereas the traditional CAPE ratio is more closely aligned with earnings weighting.“

“The traditional and widely used approach divides the current index price level, based on the current components of the S&P 500, by the aggregate index earnings reported over the previous 10 years. However, because stocks are added to and removed from the S&P 500 index on an annual basis, there is a mismatch between the stocks used to calculate the price level and those from which historical earnings are derived. We estimate the CAPE ratio by ensuring index alignment between the component stocks in the price numerator and earnings denominator.“

The traditional version turns out to be closer to an earnings-weighted average. The rebuilt measure forecasts ten-year returns better, with an out-of-sample R² of about 58% versus 47% for the standard CAPE over 1974–2015, and it held up better in recent decades.

The twist to consider for this debate is that the improved version consistently reads higher than the traditional one. A more accurate CAPE made the market look more expensive, in fact, not less.

The forward P/E has its own evidence problem, and it’s bigger than most people realize. Its denominator is a forecast from analysts whose estimates have historically tended to start too high and get revised down. That pattern is weaker in strong economies, but it hasn’t disappeared. Right now, FactSet notes that since the end of June, the index has risen 1.8% while the forward 12-month EPS estimate has climbed 8.8%.

The forward P/E looks reasonable partly because expectations have risen faster than prices. That may prove justified. It’s also exactly how a forward multiple looks just before a disappointment.

Weight vs. Strength

A concept from Dale Griffin and Amos Tversky helps me here. In their work on confidence, they separated the strength of evidence (how extreme or vivid it looks) from its weight (how reliable and representative it is).

People overweight strength and underweight weight.

A single dramatic data point feels convincing, while a larger, duller sample gets neglected.

A trailing P/E is one year of profits. It carries plenty of strength and very little weight, since one year can be distorted by a margin peak, a tax change, a write-down, or a pandemic.

CAPE is the opposite: ten years of earnings, adjusted for inflation, so no single boom or bust dominates. It’s heavier evidence, even if it’s slower to register change.

When I can only have one input – remember this is only a thought experiment anyhow –, I would rather rely on heavy evidence that updates slowly than on vivid evidence that swings with the cycle.

That was the core of my answer in the Notes thread, and I still think it holds.

Still, weight comes with a price. The same averaging that protects CAPE from cyclical noise also slows it down when change is structural.

That brings us to theory.

Does the Mean Still Exist?

Every valuation metric compared against its own history rests on an assumption, usually unstated: that there is a stable long-run average for the ratio to revert to.

Statisticians call this stationarity.

If multiples were stationary, extreme readings would be informative, because they tend to fade.

However, multiples are non-stationary, and thus, the historical average is an artifact of a world that no longer exists, and comparing today to 1881 is like comparing a high-speed fiber-optic network to a horse-drawn mail carriage.

There are serious arguments that the market’s underlying attributes have changed. The index today is dominated by asset-light businesses with higher margins, global reach, and far lower capital requirements than the railroads and steel mills that made up the market of Shiller’s early data. Yet, businesses arguably suffer from shorter competitive advantages (depending on the industry; certainly in tech).

Then again, globalization has diversified revenue streams and lengthened growth runways. And if those shifts are durable, then a higher “normal” multiple is justified, and part of the gap between today’s CAPE and its long-run median of about 17 reflects better businesses and better growth opportunities rather than euphoria.

So a question to ask would be whether the last decade’s earnings growth is a new baseline, a “new normal,” or an unusually good stretch. For context, real earnings per share grew about 2.1% a year from 1871 to 2025, and about 2.5% a year from 1950 to 2025. From 2015 to 2025 the rate was about 7.3% a year. From 2016 to mid-2026 it was closer to 9%. Both are flattered by a weak starting point, since 2015 was hit by the energy collapse.

Back to my point. This is where mean reversion comes in, along with its less-discussed twin, mean reversion neglect: our tendency to extrapolate recent trends and forget that competition, regulation, and saturation tend to pull extreme outcomes back toward average.

Michael Mauboussin has done great work in this field. His work on base rates shows that high returns on capital fade over time for most companies, including very good ones. The fade is slower for the best businesses, but it still happens.

His writing on what a P/E multiple actually means also emphasizes that the ratio carries information about where a company sits in its cycle: a cyclical business at peak earnings will look cheap on current profits precisely when its earnings are most at risk. We discussed this above. Apply that logic to an index where the profits of a handful of firms sit near record highs, and a single-year P/E starts to look like a potentially peak-cycle reading.

Concentration is the part I find hardest to ignore. RBC notes that the top ten stocks made up a fairly steady 18–23% of the S&P 500 between 1990 and 2015, before nearly doubling to a record 40.7% in 2025.

S&P Dow Jones Indices calculated that concentration near 40% hadn’t been seen since the mid-1960s. History suggests leadership at the top of the index rotates.

The companies that dominated in 1965, 1980, and 2000 mostly didn’t dominate a decade later.

Saying it won’t be this way going forward is a bet against history, an assessment on the inside view, which tends to be a poor basis for high-quality forecasting.

Also, from 2003 through 2022, the equal-weighted index beat the cap-weighted one by roughly 1.5% a year, a pattern RBC partly attributes to periodic mean reversion among large-cap leaders.

Now link that back to the metric choice. If the earnings of today’s leaders hold up, the regular P/E is the more honest measure and CAPE overstates how expensive the market is.

If those earnings are closer to a cyclical or competitive peak, the trailing figure overstates the durable earnings base, and the regular P/E makes the market look cheaper than it is. In that case, CAPE is the better guide.

You can’t pick a metric without implicitly betting on how durable current profits are. Choosing a ratio means choosing a theory.

Where My Own Argument Cracks

I promised to stress-test my own view, so here is an attempt to invert my line of reasoning.

In the Notes thread, I argued that CAPE’s strength lies in comparing its current level to decades of history. At the same time, I believe multiples are non-stationary and that the attributes of the index today differ enormously from those of the 1920s or the 1970s.

Those two beliefs are in tension.

If the past has little to say about the present, then the long historical record is also the weak point in CAPE’s case.

My best resolution is this. Non-stationarity doesn’t hurt one metric while sparing the other. It also undermines any claim that a trailing P/E of 26 is “high” relative to a 150-year median of 18. Without some historical anchor, neither number means anything. One adjustment is to move the anchor. Compare CAPE against the post-1990 regime of asset-light, globally scaled businesses – weaking the weight of evidence (30-40 years of data is not as great of a sample size as it may seem …) – instead of the railroad era.

But even on that more generous baseline, 41 sits at the very top of the range, and the only comparable readings occurred at the height of the dot-com bubble.

There’s a second crack. I expect concentration to mean-revert, but I can’t prove it, and neglecting mean reversion has a counterpart: extrapolating mean reversion into places where the competitive structure has changed. Some of today’s leaders do have deeper moats and longer runways than their predecessors. If three or four of them sustain their current earnings power and earnings growth for another decade, CAPE will look too pessimistic in hindsight, much as it did through much of the 2010s.

The authors of the RBC Wealth Management paper “The ‘Great Narrowing’: S&P 500 concentration“ that I referenced above also point out exactly this, which is in line with FJ’s reasoning, I think:

“It is important to acknowledge that today’s concentration is not purely speculative and, unlike prior market peaks, the largest constituents of the S&P 500 are highly profitable businesses with strong balance sheets, durable competitive advantages and substantial free cash-flow generation. Many are returning capital to shareholders while continuing to invest heavily in growth, particularly in AI-related products and infrastructure.

Elevated concentration alone is not sufficient evidence of a bubble. Market leadership has narrowed in part because earnings, margins and cash flow have narrowed. That distinction matters and helps explain why valuations have been elevated for longer than many investors anticipated.“

Concluding Thoughts

If I could keep only one number, I would keep the Shiller PE. It carries more weight as evidence, it’s less exposed to where we are in the earnings cycle, its forecasting record is stronger over the horizon that matters for long-term investors, and recent research (with some twists to the metric!) has made it more robust to the very composition problem raised against it; now we only need websites to report it too.

The regular P/E, especially the forward version, rests on one year of profits or on one year of forecasts. In a market where ten companies make up close to 40% of the index, that is a narrow foundation.

The asterisk is important, though. I’d use CAPE to set my expectations for the next decade and not to decide what to do next month. I’m an active stock picker anyhow, and while in expensive environments it may be harder to find “no brainers,” I’d argue that if you only look hard enough, you can still find “gems” in almost every environment.

US market valuation levels seem high. Outside the US, I see lots of opportunities.

Where my reader and I disagree, I believe, is simply on how much of the last decade’s profit growth and the current index composition (in its weight) will prove permanent.

So what did you pick before you started reading, and did anything here change your mind?

Leave a comment

Leave a second comment if it did. If you think I’ve got it wrong, I especially want to hear from you.

Was the market repricing a temporary slowdown, or correctly recognizing that the monopoly years are over?

Answering that required going deeper into the underlying engine itself, so part two starts in 1995 with a prototype named after Leonardo da Vinci and ends with a valuation model tying everything else together.

A few things surprised me along the way too. The most consequential product in Intuitive’s history probably isn’t da Vinci 5, and the most consequential decision wasn’t a product at all.

The metric I worry about most has declined in four of the last five years, and it happens to be the one thing management’s long-term pay doesn’t depend on.

Here’s what part two covers (another 10,000-word analysis):

• Business History

  • The DARPA-funded battlefield research that became a business

  • Lenny, Leonardo, Mona, and a $314.5 million IPO before FDA clearance

  • The patent war that ended in a merger, and why I call it the most important decision in company history

  • Five generations of the same idea, and which machine I’d argue mattered most

  • The ten-year gap that explains today’s upgrade cycle

• How Intuitive turned third-party staplers into a billion-dollar business

• The key KPIs to track, and the flywheel connecting them

  • Plus: The one metric you have to calculate yourself, because Intuitive won’t hand it to you

• Whether 40% operating margins are a feature of the industry or of a monopoly inside it

• The Getty test: what’s certain about 2046 and what isn’t

• China, where domestic makers took half of 2025 procurement

• Dave Rosa’s thirty-year path to CEO

• What management is paid to deliver, and the gap I spotted in the incentive plan

• Insider ownership

• Identifying key growth drivers and assigning a revenue growth contribution range to each

• Where margins settle, and why management has capped its own upside on purpose

• Stock-based compensation, and what free cash flow looks like after it

• Base rates from Mauboussin, anchoring the inside view to the outside view

• My full valuation model, with a download link so you can change my assumptions

• Closing thoughts

One note before you start: If you haven’t read part one, the eight pillars of the hypothesis and the falsification tests attached to each can be found there (linked below), and I refer back to them throughout.

Part two works on its own, though you’ll get more out of it with part one in mind.

Read part 1 here:

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Shoutout to our WhatsApp community in which some of these resources are regularly shared – the power of swarm intelligence!

Subscribe below to not miss these kinds of posts in the future.

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Articles & Letters:

• Arnaud Bertrand: “The most important AI story in the world is happening in a place you’ve never heard of“ – This was a fascinating read; below is a little teaser

  “By now, it’s amply clear that the big bosses of US frontier AI labs are really, really scared of China. And, fascinatingly, part of the answer why might be a tiny place in Inner Mongolia that you’ve probably never heard of: Ulanqab prefecture. Heard of it? Didn’t think so. Even myself, who’s traveled to Inner Mongolia twice, had never heard of it before researching this story. This is because, at first glance, this place is pretty unremarkable. Check its Wikipedia page (https://en.wikipedia.org/wiki/Ulanqab) and you’ll see the only thing it’s famous for is being the birthplace of He Pingping, who briefly held the Guinness record for world’s shortest man. That’s it, that’s the list! Otherwise, it’s just a sparsely populated - 1.5 million people, minuscule by Chinese standards - stretch of windswept grassland on the Mongolian plateau. Except there is one number that tells you there is more to this place that meets the eye: this tiny prefecture consumes nearly 1% of all of China’s electricity - and that number is growing by double digit numbers every year. And yes, I did write **consume**, not produce.“

• Read this to protect your brokerage account: PSA: How Hackers Drained $1M From a 2FA-Enabled Brokerage Account

  • This strikes me as a major security gap brokerage companies need to close or accept responsibility

    “$1.1 million of life savings, gone. On paper, the account was not robbed. It was traded. And trading is the very purpose of brokerage accounts. Withdrawals are where the brokerage puts up walls: holding periods, callbacks, reversal windows, a fraud desk that treats a wire as their problem. A trade has none of that. It executes in seconds and is irreversible. The preferred trade for hackers are thinly traded, illiquid options that expire the same day. The hacker needs to sell the options they already hold, at an inflated price, to the victim’s account. […] new phishing uses fully functional sites that sit live between you and the real login and pass through whatever you type in real time: username, password, 2FA code. The brokerage, believing it has authenticated you, issues a session cookie, which says this person is logged in and verified, to the hacker, and your phone gets no new notifications. […] As for why they refused responsibility, Interactive Brokers was clear: ‘If you used your own username and password to log in to place these trades, then this is the client’s responsibility. We will not accept this compensation request.’“

• New Michael Mauboussin paper “To Free or Not to Free (Cash Flow).“

  “We recently published a new report called “To Free or Not to Free (Cash Flow).” Free cash flow (FCF) is a topic of interest for the hyperscalers. The main premise is that negative free cash flow is fine as long as the returns on investment are sufficient. In the report, we cover 5 areas: 1. We offer a working definition of FCF and examine where some leading technology companies (5 hyperscalers + 3 others) stand today using results and consensus forecasts; 2. We examine whether the acceleration of investment spending changes each company’s position within the life cycle; 3. We calculate return on incremental invested capital (ROIIC) for each of the companies; 4. We look at the relationship between free cash flow and ROIC; 5. We look at how consensus estimates have changed for sales, earnings before interest and taxes (EBIT), and capital expenditures. These drivers provide a sense of what determines ROIIC.“ - Mauboussin on X

  • I recently had AI create this visually pleasing illustration, showing that more mature companies sometimes manage to return to growth stages …

    

  • … and I thought it was very interesting how Mauboussin discovered that both Meta and Alphabet are pulling off exactly that.

    

• Waymo is entering Singapore

• Financial Times: “AI chatbots give wrong answers to financial queries ‘most of the time’“ (paywalled). Here’s a key chart that may pique your interest:

  

• Grab is acquiring BNPL company Atome. The slide deck is quite informative - couple it with the investor call (the Q&A part). I might write about it at some point.

  

• Reuters article on lawsuit, potentially involving LVMH that could cost the company billions: “LVMH signed a secret 2002 pact to buy Hermès heir’s shares. Now he says his fortune is missing“

  “Last year, he filed a lawsuit seeking €14 billion ($16 ​billion) in damages from whoever might be found guilty in prosecutors’ parallel probe into his missing fortune – which has targeted Puech’s now-deceased financial advisor and a lawyer who advised LVMH on its covert stakebuilding in the 2000s. At today’s share prices, Puech’s 6% stake in Hermès would be worth about $10 billion. Puech’s lawsuit names LVMH and its billionaire chairman as defendants, along with companies affiliated ​with Freymond.”

Podcasts & Videos:

• Speaking of LVMH, a pretty solid video on LVMH’s current situation shared by fellow writer over on X —> “LVMH: Why the discount isn’t what you think“

• As we mentioned Grab further aboe: Grab CFO Peter Oey appeared on CNBC Singapore discussing the Atome acquisition.

• The Meb Faber Show: Paul Kedrosky: Al is the First Bubble With Every Ingredient at Once

• David Einhorn on a Morgan Stanley podcast:

  “From poker investing lessons, to what he’s changed his mind about, how he invests in AI, and the personality trait that has made (and lost) him the most money, David Einhorn and Iliana Bouzali cover a lot of ground in the next episode of Morgan Stanley Derivatives’ Break the Playbook series.“

• The Master Investor Podcast with Wilfred Frost had Thomas Peterffy on the show. I’ve expressed previously how Peterffy reminds me in so many ways of the great Charlie Munger. I hope he has many more years ahead as I enjoy his witty humor, his sharp analytical takes, and his insights from inside IBKR.

• A 13-minute clip with Gavin Baker shared on X

  "AI models will go to zero. Data centers are commodity. Energy is commodity. Only two things in the whole stack have real value: data moats and reinforcement learning."

• A rare interview with Rob Vinall on The Investor’s Podcast with William Green

  • 00:00:00 - Intro

  • 00:03:46 - How Rob Vinall vaulted himself out of humble circumstances

  • 00:14:18 - Why he disliked working at Goldman Sachs

  • 00:17:02 - How he taught himself to invest during the dotcom crash

  • 00:24:12 - How Berkshire Hathaway’s annual meeting changed his life

  • 00:29:24 - How he launched a fund with no staff, no office & no track record

  • 00:38:56 - What he learned from Warren Buffett’s relationship with Ajit Jain

  • 00:47:52 - What qualities Rob looks for in outlier CEOs

  • 00:58:30 - Why he admires Mark Zuckerberg & disagrees with Meta’s critics

  • 01:00:43 - How Rob’s thinking about business moats has evolved

  • 01:02:14 - Why he’s betting a third of his assets on out-of-favor Chinese stocks

  • 01:14:09 - Why today’s momentum-driven market is ideal for long-term investors

  • 01:25:32 - How he survived the most traumatic year of his life

  • 01:37:31 - What drives him after 20 years of investment success

  • 01:42:13 - How to handle being rich without wrecking your kids

• I still need to listen to this podcast with Andrew Martin, who is the CEO of Fairlight Capital – the title has me very intrigued —> “Turning Over 70,000 Rocks“

• “'Big Short' investor Steve Eisman on AI: The companies are trying to manufacture a crisis” - a must-watch

• And on a similar note, Cal Newport: “AI Isn’t “Out of Control” — The AI Companies Are“

• Nubank “videocast” on its global ambitions with its CEO and chief growth officer

Other:

• By now, most of you might have come across this chart on open vs. closed models’ token volumes:

  

• Oppenheimer modelling 80% operating margins for Meta’s Muse

  • I just shared this on X:

    “How exactly do they get to 80% agentic model operating margins? Make no sense to me. I’m assuming you just ignore the infrastructure buildout and model training costs? And even if you do, common sense tells me these models would be nowhere close to that profitability level. Anyone?“

  

• I found this chart serves as good food for thought (not investing-related):

  

Pitching my own write-ups:

• If you haven’t read it already, check out my 4-part 126-ideas series:

• Or read my latest deep dive on Intuitive Surgical:

• Check out the Library to quickly access all previous write-ups:

In the current market environment of 2026, classic value investing – call it Buffett 1.0 investing – seems completely out of fashion.

Institutional investors spend billions chasing macroeconomic narratives, momentum trends, and high-flying technology multiples. Trump even began offering high-speed access to his market-moving announcements for $100,000 a month in August.

Institutional investors spend billions chasing macroeconomic narratives, momentum trends, and high-flying “AI-multiples.” Trump even began offering high-speed access to his market-moving announcements for $100,000 a month in August, and more than ten firms signed up, mostly high-frequency shops. Speed on a headline is what they are buying. The backdrop rewards it. Warsh's Fed raised rates on September 16, the ten-year yields around 5%, the top ten companies make up close to 40% of the S&P 500 against a 27% peak in 1999, and the five largest cloud providers have committed something like $700 billion of capex this year, increasingly on borrowed money.

And if market participants ever discuss Warren Buffett today, they almost exclusively study what I call Buffett 2.0. They analyze the legendary, late-stage strategist shaped by Charlie Munger – the investor who preferred deploying tens of billions into durable capital-light franchises with durable competitive moats, sometimes holding them for decades.

That mental model makes sense when managing a massive conglomerate like Berkshire Hathaway post-2000 (arguably way sooner already).

Scale forces giant capital bases into narrow corners.

Yet most investors overlook the fact that Warren Buffett’s legendary early performance was built on an entirely different foundation. Between 1957 and 1963, operating with under $10 million in partnership capital, he faced zero size penalties.

This was Buffett 1.0. He was an aggressive arbitrageur, a “balance sheet activist,” and a relentless and incredibly talented special situation investor.

While the finance world fixates on meme stocks, high-frequency trading algorithms, passive investing, or quality compounding, the playbook of early Buffett remains one of the most effective, under-studied avenues for generating asymmetric alpha.

Asset-based activism, corporate workouts, and severe balance sheet mispricings still deliver extraordinary results in today’s markets.

I recommend listening to my conversation with Jamie Halse and his activist approach in Japan.

To capture those returns, you must study the original partnership letters when his capital was nimble and his investment taxonomy was sharp.

Why did early capital allocation rely on three distinct engines?

To eliminate dependence on stock market advances, Buffett constructed a portfolio divided into three operational categories:

• Generals,

• Work-Outs, and

• Controls.

This tripartite architecture allowed him to generate superior returns while maintaining strict down-market capital preservation.

Generals represented classic undervalued securities where the partnership exercised no corporate control and had no fixed timeline for price realization. These positions carried massive individual margins of safety and generated substantial upside during rising markets. However, their market prices remained correlated with general market moves.

Work-Outs provided the defensive counterweight. These were corporate arbitrage commitments tied directly to specific corporate actions such as liquidations, mergers, spin-offs, and tender offers. The returns on Work-Outs depended on corporate schedules rather than market sentiment. To optimize capital efficiency, Buffett routinely used short sales to strip out broader equity market risk and deployed conservative bank leverage – capped strictly at 25% of net worth – solely to finance these predictable transactions.

“You will note on our yearend balance sheet (part of the audit you will receive) securities sold short totaling some $340,000. Most of this occurred in conjunction with a work-out entered into late in the year. In this case, we had very little competition for a period of time and were able to create a 10% or better profit (gross, not annualized) for a few months tie-up of money. The short sales eliminated the general market risk.“ – 1962 Letter

Controls formed the third pillar. When market prices remained depressed for extended periods, Buffett systematically accumulated dominant equity positions to force corporate change. Prolonged stock stagnation was welcomed because it lowered acquisition costs. Once control was secured, performance became completely insulated from Wall Street sentiment.

Decoupling portfolio performance from general market indexes required this structural variety. In static or declining markets, Work-Outs and Controls drove performance, allowing the overall partnership to compound capital while broad indexes faltered.

In case you missed it, I recently wrapped up my 126-idea series, in which I sorted the ideas found in the fund letters I track by:

1. Worst Performers: Quarter-to-Date (QTD)

2. Worst Performers: 3-Month Window

3. Worst Performers: 6-Month Window

How do you extract cash from non-performing assets?

The true genius of Buffett 1.0 lay in his appraisal discipline and aggressive balance sheet restructurings, best demonstrated by his investments in Sanborn Map Co. and Dempster Mill Manufacturing.

In 1958, Sanborn Map presented a glaring market inefficiency. The company’s stock traded at $45 per share, yet its underlying investment portfolio alone was worth $65 per share. Investors were pricing the core mapping business at a negative $20 valuation despite its historical stability. Board inertia caused this severe mispricing; nine directors owned just 46 shares combined and continuously slashed dividends while maintaining executive fees.

Buffett accumulated a 44% controlling stake alongside allied partners and engineered a tax-efficient corporate separation. Instead of liquidating the stock portfolio and incurring a massive corporate capital gains tax, he structured an SEC-approved exchange. Shareholders wishing to exit swapped 72% of Sanborn’s outstanding stock directly for underlying portfolio securities at fair value. The transaction eliminated over $1 million in prospective tax liabilities, unlocked immediate intrinsic value for exiting partners, and left the remaining business debt-free.

At Dempster Mill Manufacturing, Buffett demonstrated his quick-liquidation valuation framework. Ignoring optimistic book values, he applied severe haircuts to the balance sheet: 40% off inventory, 15% off receivables, and basic scrap values for physical equipment.

“We intend to use the same method or valuing our controlling interest in Dempster Mill Manufacturing at this yearend that we did at the end of last year. This involved applying various discounts to the balance sheet items to reflect my opinion as to what could be realized on a very prompt sale. Last year this involved a 40% discount on inventories, a 15% discount on receivables, estimated auction value of fixed assets, etc., which led to an approximate value or $35.00 per share”

He acquired majority control at an average price of $28 against a book value of $75 per share.

When original management failed to reduce operational drag, Buffett installed turnaround specialist Harry Bottle. Bottle slashed operating breakeven points in half and reduced excess inventory from $4.2 million down to under $1.0 million.

The extracted capital was funneled directly into a high-yielding securities portfolio managed by the partnership. By 1963, Dempster held $35 per share in liquid securities held inside a bank vault alongside $16 per share in productive manufacturing assets. The liquid assets alone exceeded the total acquisition cost of the entire company.

Blueprint of Buffett’s Early Partnership Days

To help sophisticated investors visualize these dense corporate finance mechanics, I distilled the core architectural frameworks from Warren Buffett’s 1957–1963 letters into a visual deck.

It breaks down the portfolio allocation models, governance turnarounds, and valuation frameworks into a clean structural format.

You can access the Blueprint via the note I shared with the slide deck as image files a couple of days ago (free to access for everyone):

Disclaimer: The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.

Downloadable Blueprint PDF

The complete image series above is free for everyone to review. Paying subscribers can access and download the Blueprint as a PDF so you can store it – and all old and future Blueprints – nicely on your computer.

Until next time, keep compounding!

(PDF download link below)

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We also examine how this plays out through the Total Return Formula – earnings growth, multiple changes, share buybacks, and dividends. You’ll see why low-growth stocks rely heavily on multiple expansion to generate outsized returns (making a re-rating to fair value the ideal signal to exit), whereas high-growth compounders derive most of their return from underlying earnings growth, making them far less dependent on multiple expansion to outperform over 5 to 10-year horizons.

Thank you to everyone who tuned into my live video! Join me for my next live video in the app.

Disclaimer: The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.

Laparoscopic surgery, the keyhole approach that spared patients from long incisions, was a gift to patients and a physical ordeal for the people performing it.

A surgeon would hold an 18-inch rigid steel tool inserted through a dime-sized opening. Because that opening acted as a pivot, moving the hand left sent the instrument tip right, and lifting the hand pushed the tip down – though twisting the handle along its axis stayed one-to-one. Surgeons call this the fulcrum effect, and learning to work against it took years, all while standing hunched over an operating table for six, eight, sometimes ten hours a day.

Chronic neck, back, and shoulder injuries ended careers early.

In 1995, Frederic Moll, John Freund, and Robert Younge founded a company to fix that.

They licensed DARPA-funded research originally meant to let surgeons operate on wounded soldiers from a distance, and built a prototype they named “Lenny,” after Leonardo da Vinci.

The goal was to eliminate the fulcrum effect by matching a surgeon’s hand movements one-to-one inside the body. When the da Vinci system received FDA clearance in 2000, it restored natural hand-eye alignment, added 3D high-definition vision, and introduced wristed instruments more dexterous than the human hand.

Surgeons stopped standing and started sitting, working from a console like pilots.

The company’s name says exactly what it set out to do: make complex minimally invasive surgery feel intuitive to the human mind and hand.

It worked. More than 20 million patients have now been treated on Intuitive’s systems, the installed base exceeds 11,000 da Vinci robots across more than 70 countries, and the stock is a 320-bagger since its IPO (and is now a $100 billion+ market cap company).

When the Best Business in Medtech Goes on Sale

Over the past five years, revenue and EBIT have both compounded at about 16.4% a year (almost a double), with net income, free cash flow, and EPS all growing around 14%.

Recurring revenue reached 84% of the total in 2025. Non-GAAP operating margins touched 42.1% in the second quarter of 2026.

There aren’t many businesses like this anywhere, let alone in healthcare.

And the stock is down roughly 40% from its peak.

Shares recently traded near $350, barely above a 52-week low of around $330 and far below last year’s high of above $600.

The forward P/E has fallen from 80+x in early 2025 at its most expensive to about 33x today, against a five-year mean closer to 50x, and EV/EBIT sits at 25.6x versus a historical mean of 43.2x.

On an earnings yield basis, this is the cheapest Intuitive has looked since 2016, while still growing 15% to 20%. The stock is practically flat over five years – half a lost decade.

So what happened? Three things, mostly. U.S. procedure growth slowed to 12% in the second quarter, which management blamed partly on patients deferring care after ACA subsidies expired.

Management then declined to raise full-year guidance despite a clean beat, and the stock fell 14% the next day.

A few days later, days after that, the FDA cleared Johnson & Johnson’s Ottava for ten general surgery procedures, the first credible challenger on da Vinci’s home turf in two decades.

“The system received marketing authorization for multiple procedures in general surgery, including Roux-en-Y gastric bypass, gastrectomy, cholecystectomy, splenectomy, gastric sleeve, small bowel resection, appendectomy, lysis of adhesions, fundoplication, and hiatal hernia repair. “We are pioneering a new category of surgical robotics with OTTAVA,” said Tim Schmid, Executive Vice President, Worldwide Chairman, MedTech, Johnson & Johnson. ‘This is the start of the next era in surgery as we deliver not just a new surgical robotics system, but a catalyst for fundamentally better surgical care that is informed by technology, guided by clinical insight, and delivered with care by Johnson & Johnson.’“ - J&A

Medtronic’s Hugo had already been cleared for urology in late 2025. After twenty years without a serious rival, Intuitive now has two.

And China adds another front, since in 2025, Chinese-made laparoscopic robots outsold imported ones in public tenders for the first time. Out of 90 laparoscopic surgical robots procured by Chinese public hospitals in 2025, domestic Chinese brands secured 47 units (approx. 52% of awarded volume), officially surpassing imported systems.

That’s the setup, and this deep dive is my attempt to work out which version of it is true:

• Is this a temporary repricing of a business whose economics and long-term growth runway are intact, …

• … or the market correctly recognizing that the “monopoly years” are over and the margins as well as the growth that came with them can’t last?

I’ll walk through eight reasons the business might be worth owning, and spend a good portion of the post trying to knock them down.

What this deep dive series covers (this is part 1):

We cover the key thesis structure along key pillars of my analytical framework:

• The 90-second eight-part bull case (”Bam Bam Bam Bam Bam Bam Bam Bam”)

• The business itself

• Unit economics analysis

• Beyond Miller’s 90-second pitch: A granular breakdown of each of the pillars (the core of the analysis)

• What went wrong

• Investment Slide Deck – the deep dive in a highly compressed + visualized form

  • Every deep dive now comes with a companion slide deck. It’s the whole argument in compressed form – the hypothesis, the business, the competitive position, the valuation, and the case against – for the days when you don’t have an hour to spare but still want the shape of the thing. Paid subscribers get both, the long piece and the deck, on every deep dive from here on.

• The origin story

• The customer

• The moat

• Is it a good business in a good industry

• Management and governance

• Growth drivers and forecasting

• Margins outlook

• Valuation (including a downloadable model)

• Other interesting findings

Disclaimer

As of the date of publication the author owns no shares in the company; but that may change. The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.

The Bill Miller-Style “Bam Bam Bam Bam Bam”-90 Second-Hypothesis

Every deep dive on this blog starts with a story Bill Miller once told about how to pitch a stock. I recently noticed that even Joel Greenblatt referred to this framework during his Special Situations class way back in the day. It’s the best antidote I know to the 40-page research report nobody finishes, which I will put together anyway, in a second step, for those who like the initial hypothesis and are interested in a more thorough analysis of the setup (in total 25,000 words).

Welcome to Compound with René. You can find an overview of the companies I shared a deep dive on in the visualization below.

If you haven’t subscribed, you can join 5,000 readers who enjoy the quality of the deep dives, the process-oriented pieces, the analytical insight, and the valuation discipline, here:

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Here’s how the former Legg Mason manager put it:

“I want to emphasize in your presentations that if you go into investing, you will realize that portfolio managers have ultra-short attention spans. And there is basically no successful portfolio manager of my acquaintance who has ever wanted to hear a story longer than 90 seconds. Peter Lynch, when an analyst came in to pitch him a stock, would turn on an egg timer for 90 seconds. The analyst had to complete the presentation within 90 seconds and be out of there. […] If you speak to a portfolio manager, the best thing to say is, ‘I want to talk to you about Homestore. It is at $2.25. The 52-week range is $2 to $4 and the all-time high was $100 in 2000. I think it is a buy for the following five reasons: 1. Bam 2. Bam 3. Bam 4. Bam 5. Bam. The stock is trading at $2 and change. I think it is worth $6 or $8 or whatever. Here is why I think it is worth that. Here are the risks.’”

I love that format because it forces discipline. If I can’t explain why a company is worth owning before Lynch’s egg timer rings, I probably don’t understand it well enough to put money behind it.

So here is my version for Intuitive Surgical (ISRG). The company that turned robotic surgery from a novelty into the standard of care is in the middle of its most important product cycle in a decade, with da Vinci 5 rolling into an installed base of more than 12,000 systems across its various systems (multiport, singleport & Ion).

At the same time, the first serious competitors are finally arriving with platforms of their own, and investors are asking whether a stock that almost never looks cheap has already priced in the good years. Remember that all investors should care about are the years ahead!

That tension is exactly why the stock and business deserve a fresh look now.

A quick word on vocabulary before the bams. You’ll notice I call what follows an investment hypothesis, and as my regular readers know, I do that on purpose in these deep dives. As a reminder, a thesis is a statement of belief, and once you’ve written one down, your brain starts hunting for evidence that you were right all along. Calling it a hypothesis keeps me more open-minded. It’s a claim that hasn’t been verified yet, and my job over the next sections is also to try to falsify it and present the counterarguments.

Here is the hypothesis in plain terms. The market tends to model a gradual fade in Intuitive’s procedure growth as its core markets mature and competitors show up. What I think it underweights is how much runway da Vinci 5, the push into benign general surgery, and the tiered XiR fleet add to that growth, and how long Intuitive’s lead can hold while every one of those extra procedures pulls high-margin recurring revenue through the installed base.

If that’s right, the fade comes later and slower than the price implies. It is one of my core beliefs that markets tend to misprice the durability of superior ROIIC and earnings growth rather frequently. That’s the bulls’ thesis here.

If the bulls are wrong, and growth slows sooner than later, the stock might still be expensive despite the large drawdown.

Have you tried listening to my write-ups in the Substack app? I think it’s a great experience, especially for my longer analyses. Get to know a business while taking a walk, doing sports, or lying on your sofa with your eyes closed 😉.

Miller Asked for Five Bams. For Intuitive Surgical, I Have Eight…

Here’s my 90-second pitch on why Intuitive is worth your attention right now (we will discuss each of these BAMs more thoroughly again further below):

• Bam #1 – A high-margin razor-and-blade model with ~80% recurring revenue: Intuitive has a massive global installed base of more than 12,000 systems, and each one works like a toll booth. Surgeons can’t operate without the instruments and accessories, hospitals sign service contracts to keep the robots running, and a growing share of systems sit on operating leases. Put together, more recently more than 80% of revenue is recurring (lots of charts follow further below; see teaser screenshot from X below), and switching costs climb every year a system stays in the medical facility, the staff gets trained on it, and OR workflows get built around it.

  

  • One caveat I’ll flag right away here is that the magnitude of recurring revenue depends on the period, and more importantly, on how you define recurring, and while leases lower the hurdle for hospitals, they also move capital risk onto Intuitive’s own books.

  

• Bam #2 – The da Vinci 5 inflection and a 10,000x compute flywheel: The new da Vinci 5 packs 10,000 times the computing power of prior generations, adds Force Feedback so surgeons can sense the pressure they’re applying to tissue, and improves ergonomics for the person hunched over the console for hours. The bull case is this widens Intuitive’s technological lead over late-arriving competitive platforms by five to ten years.

  • I want to be careful here, however. Computing power is an input, and hospitals pay for outcomes. The flywheel only turns if all that compute translates into better data, better instruments, better patient outcomes, and eventually results that surgeons can feel and administrators can measure. A 5–10 year lead is also the type of company claim you want to treat carefully, given that Medtronic and Johnson & Johnson, and Chinese players too, have plenty of money to throw at the opportunity.

  

• Bam #3 – TAM expansion and line-of-sight growth from 7M to 9M+ procedures: Intuitive’s addressable da Vinci procedure pipeline has grown from roughly 7 million to more than 9 million. Much of that comes from benign general surgery (gallbladder removals, hernia repairs, appendectomies), plus acute care and newer indications like cardiac procedures and nipple-sparing mastectomy. This is where the long runway comes from. Beyond the company-defined “line of sight”-TAM, there’s a global soft-tissue surgical market of around 23 million procedures, spanning open surgery and conventional laparoscopy, and Intuitive argues that roughly 20 million of those can and should be performed with a minimally invasive approach.

  • General surgery cases come in high volumes but at lower acuity, and reimbursement rarely rises just because a robot was used. That puts pressure on the hospital’s cost per case and, over time, on what Intuitive can charge per procedure. And generally, a TAM figure published by a company in an IR deck always deserves a haircut.

• Bam #4 – A tiered fleet strategy (XiR) that opens up ASCs and emerging markets: Refurbished Xi systems, branded XiR, give cost-sensitive buyers an economic way in. Plenty of Ambulatory Surgery Centers and international hospitals can’t justify a brand-new flagship, but they can justify a refurbished one that then also brings in high-margin recurring revenue. Think of it as a certified pre-owned car at a car dealership that has passed a strict multi-point inspection and comes with a factory-backed warranty. It widens the customer acquisition funnel and brings new surgeons onto the platform, and the idea is that it does so without diluting premium dV5 pricing.

  • At the same time, bears would argue that if U.S. hospitals that would otherwise have bought a dV5 start choosing XiR because it’s “good enough,” the tiered strategy could turn into a cannibalization dynamic to some extent.

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Anyway, yesterday evening one of those ideas popped up. It’s nothing groundbreaking, but it adds a helpful bit of nuance to how you view and react to drawdowns. I shared a quick version on X yesterday, but it deserved a full write-up:

Investor temperament has two breaking points – and they sit at opposite ends of the clock.

Warren Buffett often notes that once you possess ordinary intelligence, investing success has little to do with IQ. What you need is the temperament to control the urges that get others into trouble.

Howard Marks echoed this:

“Emotion is one of the investor’s greatest enemies.”

I’ve nodded along to that for years. But what does it look like in practice?

From my observations, most investors can handle moderate volatility reasonably well. They might get nervous when the market drops 3% in a day, or call a peer when a stock slides 10% to 20% over a few weeks or months.

But they still think rationally.

Michael Mauboussin splits an investor’s edge into four sources: informational, analytical, technical, and behavioral. The first three get competed away a little more every year. The behavioral edge – the one Buffett constantly stresses – belongs to whoever stays rational while everyone else panics.

So where exactly do investors crack? I believe, broadly speaking, there are two specific setups that push people over the edge:

1. The Sudden Shock: Sharp Volatility over a Short Timeframe

Two variables drive this reaction: the length of the window and the size of the move.

• Length: A 20% slide spread over six months is something most people can stomach. Compress that same 20% into a single trading session after a bad earnings report, and a good chunk of self-proclaimed “next Warren Buffetts” freak out. They sell the position because they cannot handle the uncertainty. They check their phone every 30 seconds to find hidden “news.” Etc.

• Magnitude: Plenty of investors can manage 20% over six months. But a 50% plunge over that same stretch causes many to throw logic out the window – regardless of underlying business performance.

Behavioral economists call this myopic loss aversion, a concept Mauboussin has written about for years. We feel the pain of losses roughly twice as intensely as the joy of equivalent gains, and the more frequently we check, the more losses we see.

A sudden drop hits both nerves at once, since everyone refreshes their brokerage app on earnings day, and when they see a -20% down move, they’ll refresh the app – or X app or their investing platform – again and again literally every 97 seconds...

2. The Long Grind: A Slow Loss (or Sideways Drag) Over Years

The second setup flies under most radars: a slow, grinding decline over an extended timeframe.

In fact, it doesn’t even have to be a loss. A position that does nothing for multiple years breaks people just as easily. In an era of short attention spans and immediate gratification, twelve months of sideways movement is unbearable for many.

But when investing in stocks with a long-term mindset, you have to prepare for multi-year flat return periods in individual equities. And they can still outperform tremendously with 20%+ CAGRs, despite periods of underperformance. Here’s a chart from a fund letter I keep coming back to.

Now picture a stock that is not only flat, but drops 20%, 30% or 66% over a couple of months, or years, and stays stuck there a looong time … Close your eyes and truly imagine the feeling of “feeling stuck” with the stock. You know the math of losses and gains is counterintuitive because a percentage loss requires a much larger percentage gain just to break even.

• Maybe you pitched it to your peers.

• Maybe you wrote about it publicly.

• Maybe you tied your online identity to it.

For three years, you sit on that paper loss while the underlying business performs perfectly fine. Most investors simply can’t take it – three years feels like an eternity. They question their thesis. They wonder if they missed something. They start believing that the business deteriorated even if it didn’t.

Price drives narrative.

And then they decide to cut losses. To cut the pain.

And usually that’s the worst time to do it. I’ve seen it time and time again, when multiple investors “just cannot take it anymore,” a stock subsequently starts rebounding and shoots up triple digits.

The painful truth is that this grind is closer to the norm than the exception. In their study Drawdowns and Recoveries, Michael Mauboussin and Dan Callahan examined more than 6,500 U.S. stocks between 1985 and 2024. The median maximum drawdown was a staggering 85%, and the drop from peak to trough took 2.5 years on average.

Two and a half years – just to reach the bottom.

Roughly 54% of those stocks never recovered to their prior highs, so the grind doesn’t even come with a guaranteed reward.

Great investors aren’t spared either. Charlie Munger’s partnership compounded at 19.8% annually from 1962 to 1975, yet suffered a brutal 53.4% drawdown between 1973 and 1974. Berkshire Hathaway itself has endured two separate 50%+ drawdowns. Munger argued that an investor who can’t calmly handle a 50% decline two or three times a century isn’t fit to own common stocks and deserves mediocre results.

Mouboussin and Callahan concluded that large drawdowns are simply the cost of admission for long-term outperformance.

Welcome to Compound with René. You can find an overview of the companies I shared a deep dive on in the visualization below.

If you haven’t subscribed, you can join 4,900 readers who enjoy the quality of the deep dives, the process-oriented pieces, the analytical insight, and the valuation discipline, here:

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Holding Is an Active Skill

Holding through these periods isn’t passive—it’s a deliberate skill. A story shared by @pitdesi illustrates this well:

“Once met a prospective LP. Minutes before the call, I looked him up and saw he was a schoolteacher... I was confused. His dad had invested in the Home Depot IPO and held on. Every $1K invested then is worth ~$17M today, beating Apple ($4.5M).”

@sidecarcap captured the core lesson:

“Love these stories. While there is luck involved, this is not getting lucky. Both the dad and teacher decided to hold. Most investors never come close to this outcome because they don’t try to. The first step is behaving in a way that puts the possibility on the table.”

When you map investor temperament across time, the pattern becomes clear: investors break at both extremes of the clock.

They crack when sharp declines hit hard or in rapid succession, and they crack when flat returns or slow drawdowns drag on for years. The middle of the spectrum is where almost everyone feels comfortable – and acts like a superstar investor.

As Peter Lynch put it:

“Everybody in the world is a long-term investor until the market goes down.”

The long end of the time spectrum is what many call time arbitrage – and it may be the last true edge no data provider can sell you. You have to earn it the uncomfortable way.

Across all the letters, I pulled together 126 distinct ideas complete with business breakdowns, investment theses, and key charts.

• Part 1 (explains the general idea of the approach and why it is valuable)

• Part 2

• Part 3

• Shameless Cloning 2.0: Pabrai’s Idea, Upgraded for 2026

After releasing the series, a community member reached out with a great suggestion:

Which of these high-conviction ideas have dropped even further since these managers bought in?

While each individual stock overview included a performance chart, hunting through 126 separate breakdowns across three parts to find the biggest laggards takes time.

To make things simple, I exported all 126 stocks as a CSV file and then imported it as a custom watchlist on Koyfin to be able to filter the list by performance and see which names have taken the biggest hits – and might be sitting at even more attractive valuations today.

1. Worst Performers: Quarter-to-Date (QTD)

2. Worst Performers: 3-Month Window

3. Worst Performers: 6-Month Window

When market or industry momentum, certain fund flows, or shorter term sentiment pulls down quality businesses, or more broadly, interestingly priced stocks, alongside broader (industry) noise, it often creates a better entry point than the one the original fund managers got.

Let me know in the comments which of these dips you think are genuine bargains versus value traps.

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I will attach the biggest laggards over each time frame as a screenshot below:

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I’m resharing this episode to reach a broader audience, so feel free to pass it along to anyone who might find it valuable. Let me know your key takeaways in the comments!

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Here is what we covered in the episode:

• My Backstory & Socials: What sparked ten years of continuous passion for investing, creating content, and leveraging productivity as a personal life hack.

• Hard-Earned Lessons & Mistakes: Why I gravitated toward quality investing early on and the power of writing down a framework.

• Research Process & Philosophy: Breaking down my complete process – from idea generation and business quality assessment to position sizing, valuation, and psychological discipline.

• Latticework of Mental Models: How I use “thinking tools” like inversion, margin of safety, legacy vs. reinvestment moats, and localized network dynamics to make rational decisions.

• Are We In an AI Bubble? My thoughts on the current environment.

Hope you enjoy the discussion!

As I recently shared, between roughly 2019 and 2023, I wrote a three-volume investment framework that runs to about 2,100 pages. Thousands of hours went into it, and most of those hours were spent doing something that looks inefficient from the outside: reading hundreds of books, listening to thousands of podcasts and YouTube videos, and trying to decode what I liked and didn’t like and writing down what I had understood in my own words.

Today’s Blueprint comes out of a small foundational piece of that project, pats of “Lesson 8.2.” of my framework. The companies that appear in it as examples are simply the businesses I was studying at the time. Slack was still a young growth case. Peloton was the vertical integration showcase, GameStop the fading incumbent, and the Switch OLED an open question about whether Nintendo would move to an iPhone-style hardware cadence.

I finished that work before generative AI existed, and I am glad about the timing. Writing the framework myself is what made the lessons stick.

I am publishing this particular Blueprint now because the market has made its lesson urgent. Sentiment is euphoric, and more importantly, the structure of price discovery has temporarily shifted in a direction that makes business analysis feel like a handicap.

Retail speculators carry leveraged single-name exposure. High-frequency shops and pod-based multi-managers work holding periods measured in weeks. Large institutional allocators have become functionally valuation-agnostic, because career risk punishes them far more severely for being absent from a rising name than for owning it at forty times sales. Robinhood built the interface that trained a generation to check a position the way you check a notification. I discussed these dynamics and some of the implications more thoroughly in the piece below (with which many investors resonated quite a lot).

Whether you can hold anything at all for more than a couple of weeks is now a real-world question for many “investors.”

Are you an owner or a renter?

My framework opens with a mindset shift. Pretend you are buying the entire company. Not a share. The whole thing, funded out of your own pocket, with no exit available for a decade.

Graham established the distinction in chapter eight of The Intelligent Investor, and it is the distinction between price and value. Look at what the exercise removes. When you own a business outright, nobody shows you a price every ninety seconds. Your information set collapses down to profits, returns on incremental capital, and competitive position, and those things move slowly, so your behavior moves slowly with them.

Reintroduce a live price quote, and you have handed yourself a second variable, far noisier than the first, that almost everyone reacts to.

One of Buffett’s best investments

The cleanest demonstration of what the ownership frame strips away is Buffett’s purchase of the Washington Post.

If you did not know, Warren Buffett's investment in The Washington Post Company was one of the most successful and famous investments of his career. By 1985, his initial $10.6 million stake had grown to $221 million, compounding at roughly 35% per year. Over 40 years, the investment grew to roughly $1 billion by 2013, representing a return of over 9,000%.

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Buffett did not calculate the stock’s beta. He ran no capital asset pricing model, checked no position on an efficient frontier, reviewed no average daily trading volume, and never asked whether the company belonged to an index. He valued the business and bought a piece of it at a substantial discount to that value. The full apparatus of modern portfolio theory was available to him, and he had no use for any of it, because none of it describes earning power.

On pro-rate stakes

There is a second-order point here that most investors miss. Public markets routinely price pro-rata stakes in excellent businesses at discounts you could never negotiate privately.

A strategic buyer taking out a whole company pays a control premium.

You, buying two percent of that same enterprise through an exchange on a panic day, get the discount instead.

Berkshire operates in both markets precisely because the public one is periodically the cheaper of the two. Your inability to acquire entire corporations costs you nothing. The temperament of the people you transact with, exploiting behavioral mistakes, leaning into behavioral edge setups … that is what pays you.

Then run the thought experiment in the lesson. Assume the market closes for ten years the moment you buy. No quotes, no marks. What would you need to believe about the business to be comfortable? Answer that honestly and you have defined your actual research agenda.

Can you say it in two sentences?

Assume you have accepted the ownership frame. How would you know whether you understand a business well enough to act as its owner?

My test: Describe the company along a handful of parameters (I use eight) in one or two dense, unambiguous sentences, specific enough that a layperson with no market exposure could repeat the business model back to you. Product, monetization, customer, geography, distribution. No jargon, no hedging.

Try it on something you own.

Bonus points for sharing it in the comments below!

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When I wrote the chapter in my book, I used Apple as the worked example, and the description took me considerably longer than the reading did. Two sentences had to carry the hardware suite, the software and services layer wrapped around it, the multi-channel distribution running from owned retail through third-party resellers, and a customer base split across middle- and higher-income consumers, small and mid-sized businesses, and educational institutions.

Every word in it does work, and cutting any of them changes what the business is.

The world-renowned multinational technology company Apple Inc. designs, manufactures, and markets high-end smartphones, personal computers, tablets, wearables, and accessories along with a variety of related software, services, peripherals, and networking solutions. Headquartered in Cupertino, California, Apple sells its products worldwide through its online stores, its retail stores, its direct sales force, third-party wholesalers, and resellers to middle to higher- income consumers, small and mid-sized businesses and educational institutions

Research of the University of Colorado

The reason the exercise works has a cognitive basis. Research out of the University of Colorado found that being made to teach a concept has a humbling effect, because articulation exposes the gaps that recognition conceals.

You read a sentence in a 10-K, it feels familiar, and familiarity passes for comprehension right up until you have to generate the sentence yourself.

That is overconfidence bias with an unusually cheap antidote. Teach it, and the holes announce themselves.

Which is why the input matters as much as the exercise. The parameters have to be filled from annual and quarterly filings, earnings call transcripts, and shareholder letters, not from a broker note or a thread summarizing a business on X.

It is also why I keep telling newer investors to start with a focused single-industry operator. A conglomerate makes you define all eight parameters four or five times over, across merged financials and a single management team, and that is a genuinely hard analytical task wearing the costume of an easy one.

Structure sets the ceiling on economics

Another parameter in the lesson is the one I find most underused. Consider the product profile, which sits on three continua rather than in three boxes.

• Goods against services, where services generally carry higher margins for the unglamorous reason that they tie up less physical capital.

• Consumable against non-consumable, where consumables produce recurring revenue because the customer runs out and has to buy again.

• Commodity against differentiated, which is the axis that determines whether you have pricing power at all. A commodity producer competes on cost, since every unit it makes is economically identical to a competitor’s unit. A differentiated producer gets to compete on something else, and branding alone can move a product a long way along that axis. You have a preferred brand of milk.

Distribution then reallocates the economics between the party that makes the product and the party that reaches the customer. The travel data I pulled at the time showed online travel agencies taking 44 percent of bookings in 2018 against 41 percent the year before, while direct bookings on the accommodation provider’s own website fell from 35 percent to 27 percent.

Direct-to-consumer structures keep more of the margin and hand the operator control over placement and presentation, which a retailer-dependent brand never has.

Operational form is worth being aware of too. Holding companies like Berkshire function as capital allocation hubs sitting above decentralized subsidiaries. Franchisors license the system and the trademark and earn royalties against almost no capital, an extremely attractive return profile when the concept travels. Vertical integration secures either the input or the customer relationship, and GrafTech is the tidiest case in the lesson: it bought Seadrift Coke to lock up petroleum needle coke, the one material without which its graphite electrodes cannot be made. That insulation from supply shocks and intermediary margin rarely shows up in a screen.

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Horizontal integration buys scale on the same tier of the chain, as Capri did in assembling Michael Kors at roughly 4.45 billion dollars of sales alongside Versace at 900 million and Jimmy Choo at 650 million.

Two parameters people skip deserve a mention: Customer concentration decides how much bargaining power the business actually holds. A diversified base means one departing buyer dents revenue instead of breaking it, and it keeps customers from dictating price and quality terms.

Geography decides where the shocks come from.

Balanced demand, concentrated supply. You want to know that before the next disruption, not during it.

Life cycle bounds all of it. Startup, growth, expansion, maturity, decline.

The attrition numbers are worth restating because they are worse than most people assume: roughly 40 percent of new businesses survive past year four, and about a third make it through year seven. Mature enterprises invert the trade, offering dominant positions and cheap capital alongside saturation and bureaucratic drag.

Fading incumbents almost never pivot in time, because by the point management concedes the model is broken, the window has already closed. Then ask the growth question properly. Is the next expansion tied to the core, or is it an adjacency the company has no right to win?

What I would write differently in 2026

One perspective shared in that lesson needs an amendment. I wrote that we prefer industries with an ultra-slow rate of change, because slow change lowers disruption risk and spares you from owning a business that has to reinvent itself successfully and repeatedly.

As a default, it still holds.

My own style has drifted – for better or worse. I hold more exposure to businesses with a wider range of outcomes than Buffett ever wanted, and I lean more technology-adjacent than he did, because some of those companies compound intrinsic value at rates the slow-change universe structurally cannot reach.

The cost of that drift is specific. The low-rate-of-change filter used to do my risk management for me at the selection stage, before a single euro was committed.

Give it up and the work moves to position sizing.

Owner Mindset Blueprint

I rebuilt the chapter as a condensed visual blueprint, anchored on the five-core-pillar framing I have used since the beginning.

That framing comes straight out of the core pillars of the Buffett and Munger approach: understand the business, then the moat, then management, then the balance sheet, then the price.

The Blueprint is below. Print it, keep it next to whatever you are working on this week, and run your largest position through it before you add to anything.

Then share it with your investing peers.

Understanding Businesses

12.7MB ∙ PDF file

Download

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Until next time, keep compounding.

René

Disclaimer: The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.

Thinking about edge – and carefully distinguishing between edge and skill – has been one of my most transformative theoretical breakthroughs as an investor this year.

Much of this clarity emerged from private exchanges with Tiho Brkan, who consistently sharpened my perspective on how market efficiency operates in practice. Tiho is an avid reader of Michael Mauboussin, whose institutional research deeply shaped my personal evolution as an investor over the past couple of years.

I explored complementary dimensions of this topic earlier this year in The Paradox of Investment Skill: Why Exceptional Thinkers Fail in Crowded Games and How to Measure Investing Skill: A Practical Framework to Isolate Your True Alpha. I think reading both pieces will make you a better investor, learner, and thinker.

To locate true structural edge today, you have to look directly at how the investing landscape itself has shifted underneath our feet. Mauboussin's research illuminates a defining friction in modern market microstructure. Between 2006 and 2025, over three trillion dollars migrated out of active mutual funds directly into passive index vehicles.

Looking at market structure today in 2026, rules-based passive strategies control well over a third of U.S. public equities. These passive entities trade strictly to accommodate fund flows or index rebalancings. They never evaluate intrinsic value or discount anticipated cash flows. This creates massive price-agnostic buying and selling across global exchanges.

Active investors face a structural puzzle. Highly talented managers struggle to outperform because they compete against equally brilliant peers in crowded strategies, while broader market mechanics are increasingly driven by non-fundamental capital flows.

My personal process when analyzing institutional literature like Mauboussin and Dan Callahan’s research involves rigorous structural extraction. I sit down with these long-form papers, pencil in hand, reading through each section twice to strip away corporate boilerplate. First, I highlight the core mechanical drivers. Next, I map out the economic feedback loops on paper to visualize how capital flows interact with human behavior. Finally, translating dense academic research into these visual blueprints forces me to clarify my own mental models.

Can High Skill Deliver Alpha Without an Uninformed Counterparty?

Skill reflects internal analytical processing capacity. Edge relies on external market frictions.

In their foundational work that served as the foundation of this blueprint, Mauboussin and Callahan unpack the Grossman-Stiglitz paradox, demonstrating that financial markets can never achieve absolute efficiency. Perfect efficiency eliminates all economic incentives to gather information, yet efficient prices require informed traders to process data.

Markets must exist in an efficiently inefficient equilibrium. Active management requires exploitable mispricings to recoup the substantial costs of gathering data.

Tip: Access all of Mauboussin’s writing here

Superior analytical skill yields zero excess return if your trade counterparty possesses identical information, operates on the same time horizon, and faces identical structural constraints.

Edge demands an asymmetry.

It requires identifying who is taking the opposite side of your transaction and pinpointing their explicit motivation.

You must verify whether your counterparty is trading based on

• flawed extrapolation,

• forced regulatory mandates, or

• temporary liquidity needs?

Without a clear answer to that single question, perceived skill is merely intellectual vanity.

Where Do Structural Inefficiencies Appear in Modern Markets?

Mauboussin and Callahan organize market inefficiencies into four distinct domains through the BAIT taxonomy – Behavioral, Analytical, Informational, and Technical.

• Behavioral inefficiencies stem from overextrapolation and correlated crowd beliefs.

• Analytical inefficiencies center on time arbitrage and narrative transitions.

• Informational inefficiencies arise from limited investor attention and task complexity.

• Technical inefficiencies develop through forced selling and leverage liquidations.

Examining these categories reveals how institutional market microstructure has evolved.

Fundamental long-only funds now account for less than fifteen percent of daily equity trading volume, down sharply over the past decade. Multi-manager pod shops leverage capital four to five times over to harvest short-term quarterly earnings variance, while retail trading accounts for one-fifth of daily volume.

Context matters. Capital moves fast.

Dear compounders,

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On September 8, Wise CFO Emmanuel Thomassin joined Goldman Sachs analyst Mohammed Moawalla on stage at the Communacopia + Technology Conference in San Francisco.

Most conference fireside chats are reruns of the last earnings call. This one had more meat on it than usual. I listened to it two days ago, and I went through the transcript again line by line this morning, and pulled out ten points that were either new to me or that management had never said this openly before.

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Wise wasn’t the only company I’m tracking appearing at the conference. Reddit’s Steve Huffman held his own fireside chat a couple of hours earlier the same day, and if I find anything in that session or others that adds to what I’ve already written in my Reddit deep dive, I’ll summarize it in a separate post.

And without further ado, let me unpack the new insights. Here’s a list of some of the things we will cover:

• Why Wise’s CFO thinks one of its best-known rivals could end up as a customer

• A new date for the Belgian remediation, and what’s next for Wise in the U.S.

• What Wise’s 50% margin target actually refers to

• When operating leverage will finally show up

• Whether a $170 million marketing budget is enough, and a telling word from the CFO

• A fresh mid-term target for Wise Platform

• The asset Wise has spent years building that you won’t find on its balance sheet

• Wise’s stance on stablecoins, and a Windows 95 anecdote

• Whether Wise is about to become an acquirer

• A bank that tried to build what Wise has, and gave up

Tip: If you access “The Library” and hit ctrl+F you can easily access all the previous write-ups on Wise I have published.

Disclaimer:

As of the date of publication the author owns shares in the company; but that may change. The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.

1. Will Revolut be a Wise Platform customer by 2031?

The most quotable line came at the very end of the session. Asked about the competitive landscape, Thomassin said Wise sees “no reason in our mind that Revolut should not use us in 5 years from now” as a Wise Platform partner.

“Well, I think like -- first I start with Revolut, I mean there is no reason in our mind that Revolut should not use us in 5 years from now. I mean, we’re completely agnostic and we don’t ask for exclusivity. We don’t dictate the price, they can charge whatever they want. And we -- the big advantage that we have is that we continue to build this infrastructure. And I’d like to talk about the kind of equation.

He described Wise as an agnostic infrastructure provider that asks partners for no exclusivity and doesn’t dictate their pricing, so they can charge their own customers whatever they like.

In his framing, Revolut isn’t even a direct competitor, since the two companies focus on different things. Wise wants to provide payment infrastructure to every bank, and fintechs like Revolut are part of that ambition.

§So that’s why in terms of competitions, we don’t look at Revolut as competitors because we are not focusing on the same thing. We are focusing on infrastructure that we want to offer to every bank, include fintech companies like Revolut.“

Wise has spent 15 years building proprietary infrastructure and direct connections into domestic payment systems, and Japan alone took four years to secure. A competitor wanting the same network would need massive amounts of capital and time, and it would have to subsidize losses along the way to match Wise on price. At some point, renting Wise’s rails becomes the rational choice, even for a rival as well-funded as Revolut.

I’ve been pointing this out myself on X for a while now, and it’s nice to see that Wise’s CFO apparently thinks so too. It’s also one more reason why I find the constant Wise-versus-Revolut comparisons unhelpful. Revolut is fighting for the customer’s home screen, and Wise would be perfectly happy to power the transfers behind it, for a fee.

2. Is the compliance overhang smaller than the headlines made it look?

I grouped the Brussels and U.S. compliance discussion and the U.S. update into one insight.

When Moawalla brought up the compliance concerns the OCC cited in denying Wise’s U.S. national trust bank charter (I covered the denial in detail here), Thomassin argued that Wise’s regulatory scrutiny isn’t unique. A fintech growing this fast will naturally attract more regulatory focus, other European fintechs are hitting the same wall as they scale, and remediation is, in his words, almost part of the industry.

Wise has been investing heavily in KYC and KYB for many years. Growth keeps raising the bar anyway.

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Thomassin also put a date on Belgium. The remediation Wise is working through there will be delivered by the end of the year, after which the regulators will come back and assess it.

“So for us, the remediation that we are facing, for example, in Belgium, the way the press is something that we will deliver by the end of the year and then the regulators will come back to us after observing the remediation. I mean, we can see that other fintech companies in Europe are facing the same kind of wall as they grow.“

As far as I can tell, Wise hasn’t communicated the year-end timeline for Belgium this explicitly before.

On the U.S. side, Wise has resolved all remediation items stemming from its prior consent order and is now waiting for state confirmation that everything has been remediated.

“The OCC applications happened a year ago. And since then, we've been doing a lot in terms of the business mature a lot, the compliance departments have been also like maturing. Looking back in some -- with some insight, I think like we would have reconsidered the application that we made because we were also like facing a consent order almost at the same time in the U.S. So we resolved all the remediation from the consent order, and then we're waiting for the confirmation of the state that everything have been remediated.“

My first reaction was that this makes the drama surrounding the Brussels investigation leak in June much less dramatic than it initially seemed. I still lean that way, but I want to be careful, because two separate tracks are running in Belgium. The remediation Thomassin referred to most likely relates to the supervisory plan the National Bank of Belgium put Wise into back in 2024, after it found missing proof of address for hundreds of thousands of customers.

The Brussels prosecutor’s probe is a different animal. It concerns roughly €500 million in suspicious transactions, and in June prosecutors said the investigation was nearing completion, that they were finalizing a direct summons before the criminal court, and that they would pass their findings on to the National Bank. A year-end delivery on the supervisory side is reassuring. It tells us little about how the criminal track ends or whether the prosecutor’s findings will flow back into the National Bank’s assessment, so I’d call the supervisory side on schedule and leave the criminal side as an open question.

The U.S. commentary was more candid than I expected. Thomassin reminded the audience that the U.S. is Wise’s largest single market opportunity, which is why the Austin office has grown to around 900 employees, why there’s a smaller office in New York, and why Wise listed on Nasdaq for visibility.

He also admitted that, with hindsight, Wise would have reconsidered its OCC application, since it was facing a consent order at almost the same time. For context, Wise’s U.S. entity paid a $4.2 million penalty last year after six state regulators found Bank Secrecy Act and AML violations.

Since the application, the business and its compliance department have matured a lot, and the U.S. regulatory setup has shifted as well. Wise originally wanted access to U.S. payment schemes through a federal account.

Following the denial, the OCC has given Wise the green light to reapply. There’s no firm timeline yet, but the next application will be filed under the GENIUS Act framework, incorporating the recent regulatory shifts around stablecoins.

This is where it gets interesting

Become a paying subscriber to read the rest of this post and get access to all of my other research, including valuation spreadsheets, deep dives (e.g. well-known mid- and large caps such as LVMH, Duolingo, Meta, Edenred as well as more hidden gems such as Digital Ocean, Ashtead Technologies, InPost, Timee, and MANY more), and powerful investing frameworks.

As a member, you get:

• Complete Access: Every deep dive in our library (65+ and counting). The most thorough analyses you will be able to get your hands on (including downloadable models).

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• The WhatsApp Community: Real-time discussion and networking with like-minded investors.

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• Downloadable Visual Blueprints: Direct access to high-resolution PDF reference sheets distilling timeless investment classics, insights from my proprietary investing framework, and essential valuation mechanics into structured visual architecture. Print them, save them, and build your own institutional reference binder.

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Consider a striking market anomaly that routinely plays out across equity markets: established mega-cap corporations with stable operating businesses frequently see their stock prices swing by 100% or more over a twelve-to-eighteen-month window.

Fundamental enterprise value does not move that fast. Wal-Mart, Boeing, and Disney do not double or halve their intrinsic earning power in a single calendar year.

Yet institutional market participants continuously trade these equities at wildly divergent valuations.

That’s your opportunity.

I've been re-reading through Joel Greenblatt's class notes from his lectures (well, the notes on lessons #1-#7). I highly recommend reading them yourself if you haven’t already. Or if you have a limited amount of time, maybe my visual blueprint attached further below is a valuable alternative.

Anyway … Looking back at Joel Greenblatt’s legendary Columbia Business School lectures delivered two decades ago, the core friction in capital markets described above remains unchanged. Today, high-frequency algorithms and automated execution algorithms dominate trading venues, but human emotion still dictates asset allocation. Institutional money managers remain chained to benchmark tracking errors, quarterly career pressures, and macro forecasting noise. These structural rigidities create systemic mispricings. Short-term market prices diverge from intrinsic values, offering disciplined capital allocators an enduring edge.

My process for analyzing these class notes as a basis for today’s blueprint involved working through the first seven classes (#1-#7) of Greenblatt’s "Special Situation Investing" course taught at Columbia Business School, fifty-five pages of raw, unvarnished transcripts.

I dissected the exchanges between Joel Greenblatt, value fund manager Richard Pzena, and independent investor Bruce Newberg. My objective was to strip away historical market backdrop context and isolate the pure corporate finance mechanics. I focused on translating raw classroom dialogue into an actionable mental model framework, visualized as a blueprint.

Why Does Capital Structure Distort Traditional Valuation Ratios?

Topics covered include how conventional valuation metrics, which are still heavily relied on in 2026, like Price-to-Earnings (P/E) and Price-to-Sales (P/S) obscure economic reality because they ignore corporate capital structures and differential tax regimes. A company trading at a deceptively low P/E of 5x might carry significant debt liabilities, making its total enterprise acquisition cost far higher than an unlevered peer trading at 10x earnings.

To evaluate pre-tax operating yield accurately, institutional allocators must evaluate Pre-Tax Operating Profit (EBIT) relative to Enterprise Value (EV = Market Capitalization + Net Debt). Enterprise Value represents the true cost of acquiring the entire business outright. Comparing EBIT to EV establishes an apples-to-apples earnings yield across varying debt loads.

Measuring business quality requires an equally rigorous treatment of capital. Return on Invested Capital (ROIC) must be calculated as EBIT divided by Tangible Capital, defined specifically as Net Working Capital (NWC) plus Net Fixed Assets (NFA). Goodwill must be removed from the capital base entirely. Goodwill represents historical, sunk acquisition prices paid in the past, rather than the ongoing tangible capital required to run the operating business today.

Furthermore, cash flow analysis requires scrubbing raw EBITDA. Depreciation represents actual physical asset decay. Investors must isolate Maintenance Capital Expenditures (MCX) – the spending required strictly to preserve existing operational capabilities – from expansionary growth expenditures. True normalized operating cash flow equals EBITDA minus MCX. Comparing this normalized pre-tax yield against a conservative hurdle rate anchored by 10-year Treasury yields (utilizing a minimum 6% baseline floor) establishes an objective hurdle for capital deployment.

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Can Corporate Profitability Escape the Laws of Competitive Gravity?

The second core framework centers on corporate mean reversion. When grouping equities by Return on Equity (ROE), high-profitability companies experience deteriorating returns over a five-year cycle as competitors enter lucrative sectors to capture excess profits. Conversely, low-profitability companies undergo capacity rationalization, cost restructurings, management changes, and industry consolidation that drive returns back up toward the 10% to 12% corporate average.

Market participants systematically fail to account for mean reversion. Analysts extrapolate existing operational trends infinitely into the future, overvaluing temporary market darlings and severely punishing distressed businesses. Value creation occurs when a business experiences operational deterioration and falls off its historical growth trajectory. The equity price collapses as market participants panic.

The critical skill lies in distinguishing between temporary operational setbacks and permanent capital erosion. When a fundamentally sound business with high tangible ROIC enters a temporary stabilization trough, the risk-reward ratio becomes asymmetrical. Investors do not need to time the exact bottom. Buying during business stabilization, while allowing a two-to-three-year window for corporate rationalization and market recognition, routinely yields exceptional returns.

How Do Non-Economic Sellers Create Asymmetric Bargains?

The most fertile hunting ground for asymmetric value exists in special situations where market participants face structural mandates to sell equities regardless of price. Corporate spin-offs, index removals, and tax-loss harvesting force institutional funds to liquidate positions for non-economic reasons. When an index fund dumps an equity position because the company was deleted from a benchmark, the selling pressure is purely mechanical. Price separates entirely from value.

Similarly, capital structure complexity creates mispriced optionality. When MIPS Technologies traded at $1.22 per share following an index deletion, the firm held $2.20 per share in net cash, placing the business at a negative Enterprise Value of negative $30 million to $40 million. Investors willing to analyze non-recourse debt structures, unbundle consolidated balance sheets, and evaluate asset coverage can structure positions where downside risk is strictly capped while operational upside remains open-ended.

Why Did I Translate These Lectures Into a Visual Blueprint Deck?

Raw corporate finance lectures and transcripts are dense, text-heavy, and difficult to digest quickly during active market hours. To execute these frameworks effectively in modern markets, visual clarity is paramount.

High-density visual architecture forces structured thinking, isolating core formulas, capital structure mechanics, and special situation decision trees into clear conceptual blueprints.

I converted these foundational lessons into a 6-part visual presentation deck. This visual deck breaks down Greenblatt’s formulas, capital structure adjustments, mean reversion curves, and special situation case studies into precise, easy-to-scan diagrams. It serves as a visual reference manual for institutional fundamental analysis.

Joel Greenblatt Classes 1-7

10.8MB ∙ PDF file

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Until next time, keep compounding.

Disclaimer: The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.

And they might in fact be getting tired of me bringing it up again. So I’ll keep this one short. And even if you are not interested in the business of Tiger, the post may still reveal how I think about downside protection.

Check out my recent summary of Seth Klarman’s book “Margin of Safety” in which he discussed the concept of downside protection at length:

As I’ve said before, my view is that the downside here – especially at these price levels – is unusually well protected, while the upside is wide open. If Hong Kong keeps functioning, if the CCP doesn’t suddenly decide to step in in some shape or form over the next ten years (which I think is pretty unlikely), this is one of the most asymmetric setups in my portfolio. If Beijing eventually decides otherwise, most of what I’m about to lay out will turn out to be misinformed. Well, at least to some extent. Because even in that worst-case scenario, though, Tiger is less exposed to HK than its peer, Futu Holdings, and at the current price, Tiger might “earn back its current EV” over a relatively short period of time.

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Before looking at the new angle on the limited downside, a quick nod to the old ones I have discussed – I’ve valued this company in many ways in the past: First, simple multiples. Then, a more careful version adjusting for all the weird items that make a broker’s reported earnings look misleading, the recent comments on normalized tax rates, etc, etc. I’ve of course conducted some multi-scenario valuation analyses.

And the ones I actually enjoyed doing most were the creative approaches. I tried to figure out the replacement value of their customer network using customer acquisition costs (CAC) – essentially asking what it would take in dollars and years to rebuild what Tiger has already built. And CAC in this industry and the region Tiger operates in only ever seems to move in one direction: up.

Access my latest update on Tiger’s Q2 here

Then I flipped the telescope around and valued that same network forward, discounting a range of lifetime value assumptions across customer cohorts.

Different methods, different assumptions, but they all pointed to a similar conclusion: Tiger is too cheap.

Disclaimer:

As of the date of publication the author owns shares in the company; but that may change. The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.

Three cents in Bangkok, one cent in Singapore?

That brings us to what actually prompted this post. Webull closed its acquisition of Pi Securities in Thailand at the end of August, paying around $100 million for roughly 99.36 percent of the company. Pi has somewhere around $3.1 billion in client assets, according to what Webull Thailand’s CEO told the local press at the closing briefing.

That means the buyer paid about three cents for every dollar of client assets they took on. Put differently, Webull paid about 3 percent of acquired client assets.

That’s real cash, an actual arm’s-length price agreed on by two motivated parties, not some random number I plugged into a spreadsheet.

Now hold that up against Tiger. Based on my estimate of Tiger’s enterprise value – roughly $600 million – the market is valuing its $60.7 billion in client assets at under one cent on the dollar. This means, if you could acquire all of Tiger’s shares outstanding without moving the stock price, you could acquire the current asset base for 1% of the asset value.

Spread across 1.32 million funded accounts, you’re basically being asked to pay about $455 per funded account for the entire business.

Meanwhile, Webull went shopping in Bangkok and “paid up” precisely because decent-quality accounts are expensive to acquire and take forever to pile up (that build-up time has a real cost too). Management basically admitted as much on their Q2 call, describing the deal as a way to grab active funded accounts at a fraction of the organic acquisition cost, compressing years of building into a single move.

“We recently announced the acquisition of Pi Securities in Thailand, which is expected to close at the end of August. This acquisition will increase our AUM in the region significantly and positions us for further growth in Thailand as we combine Pi’s expertise in the local market with our best-in-class technology platform. […]

And I think we’re still only in the early innings of that. In terms of the Pi Security acquisition, that is a strategic opportunity that we saw in Thailand. We do have a small but aggressively growing business organically in Thailand. And looking at this opportunity with Pi Securities, not only is it immediately accretive for us in terms of growing our APAC AUM, but it also introduces us to a significant amount of high-quality active trading funded accounts for a very low customer acquisition cost that we normally would have to pay a high price for that quality of account, and it would take a very long time to organically grow that over time. So it’s like a little boost of, I guess, I’m of the age. So a little testosterone replacement therapy for us in, I guess, in a casual way to say it.”

It’s the exact same argument I was making to myself a few weeks ago with my CAC work – except this time, someone actually wrote the check.

To be fair, the comparison isn’t totally apples-to-apples. Webull wasn’t just buying assets under custody. They got member seat number three on the Stock Exchange of Thailand, a top-five spot in TFEX volume, depositary receipt issuance capabilities, over 300 investment consultants, and a licensed platform that saved them years of waiting on greenfield approvals.

Control transactions always carry a premium. Plus, Pi’s assets sit inside an advisor-led wealth model with fatter take rates per dollar. So yeah, in theory, three cents for every dollar of AUC isn’t a magic ratio I can slap onto every broker out there.

But then again, I built the overview below with the help of Claude to get a feel for where other brokerage businesses actually trade on this metric. And a) the spread is very wide and b) the 3% is toward the lower end of the spectrum.

A caveat is that these are not the same asset pools. Robinhood’s total platform assets include crypto held on acquired platforms like Bitstamp and WonderFi, but exclude TradePMR’s advisory assets – which Robinhood non-custodially reports separately and does not count toward its core retail asset total. Schwab’s trillions are largely RIA custody and workplace plans, which is a custody utility rather than a trading platform. Nordnet’s savings capital includes pensions and funds. So comparing Tiger to IBKR and Futu is fair game. Comparing Tiger to Schwab is not.

The row I find hardest to look away from is Webull’s own. The market capitalizes Webull at roughly 16 percent of its customer assets while Webull turned around and paid 3 percent for someone else’s.

Tiger sits at the bottom of the table regardless, a third of where flatexDEGIRO trades and roughly a sixth of Futu, which is the closest structural comparison in the whole group given the shared Hong Kong exposure and the shared regulatory scar tissue.

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That brings me to the second cut, because a dollar of custody is not a dollar of custody. A dollar attached to a $200,000 account, on average, churns less, brings in more revenue, is more likely to buy wealth products, and stays put through drawdowns. A dollar sitting in a $2,000 account does none of that reliably. So here is the same universe measured by assets per funded account.

By far the best metric to measure how valuable the asset base is, is arguably the brokerage firms’ revenue yield on AUC.

Look at those middle two rows. Tiger’s average funded account carries roughly $46,000, which lands within a rounding error of Futu’s $46,700, and Futu trades at six times the multiple of client assets.

Whatever discount Tiger deserves, it is not a discount for hauling around a lighter, junkier account base. Robinhood, for context, runs at a quarter of that per account and gets valued at multiple times the ratio.

Also, ask yourself which asset a strategic buyer would rather own: Pi or Tiger? Tiger is roughly twenty times larger by client assets. It operates across Singapore, Hong Kong, Australia, New Zealand, and the United States rather than just one domestic market, and over 70 percent of last quarter’s new funded accounts came from Singapore and Hong Kong – not exactly low-value postcodes.

“Hong Kong, Singapore, they are pretty much the largest markets in APAC across the board.“ - Webull Q2 call

A significant portion of its tech stack (self-clearing capabilities, Tiger AI, etc.) has been built completely in-house for years, which is another thing money can’t buy off the shelf.

Admittedly, I don’t have as much visibility into the exact quality of Pi’s customer base, and their advisor-served clients are probably wealthier on average than a typical retail app user. But Tiger has been pretty vocal about chasing quality over quantity, noting that new high-quality users were bringing in over $25,000 each in net inflows early in Q3 and average AUC per account sits north of $40,000.

Tiger is also very focused on wealth management products and has built a significant, highly sticky “other revenue” line including offerings like its corporate Employee Stock Ownership Plan (ESOP).

So if anything, I believe Tiger deserves a higher ratio than Pi.

Final Thoughts

Here is why I keep coming back to the asymmetry. Two completely independent yardsticks are pointing in the exact same direction. On earnings, if you annualize (which one should always be careful with, fair!) the $42.8 million in non-GAAP net income Tiger pulled in during Q2, that same enterprise value drops to under four times earnings. On assets, the market is currently pricing Tiger at a third of what a strategic buyer just paid for a smaller franchise in a single, smaller, and less attractive market. Add in the fact that Tiger is profitable, growing client assets by 16.7 percent year-over-year, and pulling in record revenue, and the downside case starts to feel less like a gloomy forecast and more like common-sense math.

I’m primarily just documenting my thinking here. I’ve been wrong on Tiger before, but when the pop-up of the Webull transition popped up on my phone, I immediately thought I needed to apply that logic to Tiger and other brokerage business. Another thought exercise.

Disclosure: I own shares in UP Fintech (TIGR). This is not investment advice.

In late 2002, Estée Lauder announced a deliberate decision to reallocate capital into brand-building initiatives designed to strengthen its long-term pricing power and revenue trajectory.

The institutional reaction was immediate and punitive. Wall Street dumped the stock, driving a single-day decline of 15% because the additional marketing spend depressed next quarter’s reported earnings per share.

Around the same time, trading volume in Xerox implied that institutional money managers owned the stock for an average duration of less than four months.

Wall Street demands immediate gratification. That’s largely true today. And it was true twenty years ago when Nick Sleep started his investment partnership.

The modern asset management ecosystem already operated on hyper-compressed time horizons back then, where short-term price volatility is consistently mistaken for structural risk.

Professional fund managers frantically trade around quarterly data points, driven by job security concerns and index tracking mandates. This mechanical skittishness creates massive friction for traditional allocators. It also creates an extraordinary competitive advantage for those willing to look past the 18-month institutional horizon.

Deconstructing the Early Nomad Letters

Today, I spent my day systematically analyzing the early partner letters of the Nomad Investment Partnership spanning 2001 to 2004. My goal was straightforward. I wanted to extract the core mental models that transformed a small, unconventional London firm into one of the most remarkable compounding vehicles of our era. Nick Sleep and Qais Zakaria ran a true investment partnership as opposed to the standard fee-harvesting hedge funds you encounter all too frequently.

They built their edge on rigorous fundamental analysis, low portfolio turnover, and absolute return discipline.

Stripping away the daily noise of market commentary requires patience. It requires a willingness to re-examine received corporate finance wisdom.

My investing philosophy today is largely influenced by Sleep’s teaching. I even have a self-made book version of their letters, which I probably read five times or more.

When quarterly drawdowns hit my concentrated positions, I look straight through the market quote. I focus entirely on underlying business economics. If the ultimate destination of the firm remains intact – a concept Sleep formalized in his letters – price drops are welcome gifts. Drawdowns present prime buying opportunities.

Conversely, poor management behavior drives an immediate pass. I walk away from executive teams executing stock buybacks at cyclical tops or hesitating when high-return reinvestment opportunities emerge. Excessive compensation packages without genuine insider alignment reveal flawed incentives. I distrust corporate boards issuing dividends simply because industry peers do so.

Per-share capital discipline is truly rare.

My current portfolio reflects this deliberate time-horizon arbitrage. Positions like Tiger Brokers and Ashtead Technology face temporary operational headwinds, yet their multi-year trajectories remain completely sound. The market penalizes near-term uncertainty. I gladly take the other side of that trade.

Structural Frameworks for the Patient Allocator

The early Nomad letters establish several foundational mental models that remain vital for sophisticated investors.

The first framework centers on time horizon arbitrage through the equity yield curve. Borrowing concepts from fixed income analytics, the equity yield curve plots expected investment returns against holding duration. Up to 18 months, according to Sleep, equity markets display reasonable efficiency. Beyond two years, the curve steepens dramatically, offering potential returns reaching 35% annualized. Institutional fund managers rarely venture into this duration zone because average mutual fund holding periods hover around eleven months. They prize immediate liquidity over multi-year business compounding. You capture this return spread by holding quality assets far past the wall of institutional myopia.

The second mental model deconstructs business quality through scale efficiencies shared. Conventional executive teams treat growing scale as an opportunity to widen gross margins and extract immediate profits. Costco Wholesale inverted this incentive structure entirely. Management capped gross markups at 14% on branded goods and 15% on private labels. Every unit cost reduction achieved through rising purchasing scale gets returned directly to the consumer via lower shelf prices. The customer reciprocates with radical brand loyalty and $45 annual membership subscriptions. Sales density surges to industry-leading levels. High sales volume drives further purchasing scale. The competitive moat deepens automatically as the company grows. It operates as a perpetual motion machine.

The third model addresses mathematical underwriting and per-share discipline. Sleep approaches position sizing by targeting entry prices at fifty cents on the dollar of appraised intrinsic value, assuming a baseline 10% annual growth in underlying business value. If management allocates capital wisely, a dollar of intrinsic value compounds to $1.62 over five years, yielding a 26% annualized return from a fifty-cent entry point. Even if half of your investment decisions prove completely flat due to capital allocation errors, the aggregate portfolio still yields an annualized return around 13%. Math protects downside. Disciplined entry prices absorb analytical errors.

I mapped the 2001-2004 early Nomad principles into a clean 6-slide visual Blueprint deck below. This architecture translates Nick Sleep’s early letters into an institutional reference framework that you can deploy directly within your own research process.

Blueprint: 2001-2004 Nomad Letters

9.15MB ∙ PDF file

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Until next time, keep compounding.

Disclaimer:

The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.

Great research without distribution is a stranded asset. Over three to four years – if I recall correctly, between 2019 and 2023 –, I dedicated thousands of hours to building a rigorous, three-volume investment framework spanning roughly 2,100 pages.

I built it because I wanted an unshakeable system for evaluating businesses, understanding competitive dynamics, and allocating capital effectively.

Yet, experience teaches a clear lesson about publishing: even institutional-grade analysis, as my deep dives and market commentary, needs a clear distribution mechanism to create actual value for readers.

In $100M Offers, Alex Hormozi made a point that applies just as directly to equity research as it does to traditional businesses. He noted that if you put a hot dog stand in front of a starving crowd at 2 AM, you can sell terrible hot dogs and still make a fortune – because the crowd dictates initial success, not the product alone.

"If you put a hot dog stand in front of a starving crowd at 2 AM, you could sell terrible hot dogs and still make a fortune. It's not about the hot dog; it's about the crowd."

He followed that up in $100M Leads with an equally sharp reality check:

"You can have the best product in the world, but if nobody knows about it, you’ll still go out of business."

I am confident in the quality of my research. Very confident. I know the sheer volume of labor and market experience required to produce high-level fundamental analysis, and I don’t see many others with a similar value proposition out there.

If you don’t want to ever miss a new “Visual Blueprint,” make sure you are subscribed and on the email list!

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But product quality only dictates long-term reader retention. It does not solve the initial hurdle of attention.

To bridge that gap and make complex ideas vastly more accessible, I am introducing a new format to the publication: “Blueprints.”

Four Pillars for the Modern Investor

Blueprints are visual slide decks designed to condense heavy corporate finance concepts, valuation mechanics, and strategy frameworks into clean reference sheets.

Rather than replacing my long-form deep dives, they act as concentrated architecture for your investment process.

I am structuring this format around four core pillars:

• Summaries of essential investing books. The classic texts by figures like Seth Klarman, Warren Buffett, and Philip Fisher contain timeless wisdom, but their core mental models can easily get lost in dense prose. Visual blueprints bring those core frameworks back into sharp focus.

• Direct modules pulled from my proprietary investment framework. Distilling these core modules – attached below are two examples I already created (my systematic mental models for where to deploy capital geographically + specific tools from my idea generation toolkit) – allows me to share the most valuable insights from my three-volume set over time. It is a deep reservoir of material that will fuel content for years.

• The works of Michael Mauboussin. If I were forced to choose only one contemporary writer on stock picking to read for the rest of my life, it would be Mauboussin without hesitation. Periodically forcing myself to systematically reread and synthesize his essays on return on invested capital, expectations investing, and competitive advantages keeps my own edge sharp.

• General investing, market, and corporate finance concepts. This covers everything else.

On Algorithmic Lotteries & The Beauty of a Newsletter

Social media algorithms are notoriously noisy. They constantly push creators toward clickbait, macro-panic, or apocalyptic bear thesis content designed to generate outrage rather than clarity.

I refuse to play that game.

Substack built its own social feed, Notes, to help creators distribute work. Yet, social feeds remain black boxes. Unpredictable.

The numbers prove it. When I shared my visual summary of Michael Mauboussin’s paper on Competitive Advantage Periods on X, it became my most bookmarked post to date.

A short while later, my breakdown of Seth Klarman’s Margin of Safety pulled in nearly 300 bookmarks on the platform.

Investors clearly found value in these visual frameworks. But when I posted those identical visual blueprints to Substack Notes, the best-performing piece gathered roughly seven likes.

I just checked … Six.

I’m not even sure how many of you actually got to see any one of these slide series decks? It requires you to open the Substack Feed in the first place, which I’m not sure how many readers actually regularly do.

My hunch is very few.

If you do find value in the PDFs below, please let me know via the comments. This keeps me motivated to keep creating these Blueprints.

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So that discrepancy exposes a massive flaw in relying on discovery feeds. Algorithms change overnight. It’s a bit of a lottery. Reach disappears without warning. Building a publishing strategy around algorithmic luck makes zero sense when the underlying goal is delivering rigorous, institutional-grade analysis.

I prefer direct distribution.

That’s why I plan to distribute these "Blueprints” as regular posts too. And by publishing these Blueprints as standalone Substack pieces, I intend to route every issue directly to your inbox. You receive the complete essay, a slide deck that is easily digestible in five minutes and hopefully adds some value too, alongside a downloadable PDF version of it.

This format lets you take ownership of the material. You can store the PDFs on your desktop, file them by topic, and build a permanent reference library over time.

I may eventually curate these decks into a single master archive or restrict certain downloadable PDFs to paid subscribers, but my immediate focus is making sure you get direct access to these frameworks, which is why at the bottom of this post, I have attached downloadable PDF files for all the visual Blueprints created so far.

If you find real utility in these decks, share this post with fellow investors or forward it to someone who values high-quality research.

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PS: I also added a new tab to the homepage for the new format!

Disclaimer: The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.

From my Framework

IDEA GENERATION SERIES: Where Good Ideas Come From

Idea Generation I

8.85MB ∙ PDF file

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MARKET SELECTION PLAYBOOK: Where to Invest – The Intelligent Investor’s Geographic & Sector Selection Playbook

Where to Invest

11.1MB ∙ PDF file

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SETH KLARMAN: Margin of Safety – Capital Preservation in an Irrational Market.

Margin of Safety

10.9MB ∙ PDF file

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LAWRENCE A. CUNNINGHAM, TORKELL T. EIDE & PATRICK HARGREAVES: Quality Investing – Owning the Best Companies for the Long Term

Quality Investing

8.31MB ∙ PDF file

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MICHAEL MAUBOUSSIN: Competitive Advantage Period: The Neglected Value Driver

CAP Period

8.64MB ∙ PDF file

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Disclaimer: The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.