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).

I made it for two readers. The first is the person who asks me over coffee what I think about Reddit and has only fifteen minutes rather than an entire afternoon. The second is me, eighteen months from now, when the price has moved in one direction, and I want to know what I actually claimed.

Both of those readers need the same thing. A compressed version of the argument. So the deck opens where I think every case should open, which is on the hypothesis and the conditions that would refute it. No target price. No expected CAGR in bold on the cover just yet. Just the proposition that Reddit is a twenty-year-old asset in the first innings of learning how to charge for itself, and the specific readings that would tell me I had misjudged it.

From there, we cover everything else in compressed from with some stunning visualizations.

This is where it gets interesting!

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• Part 1 laid out the five pillars of the hypothesis.

• Part 2 walked through the business itself, how Reddit works, and where the money comes from.

Neither piece told you whether to buy the thing. That was on purpose, because a valuation built before you understand the machine producing the cash qualitatively, understanding it inside and out, is worthless.

The bulk of what follows is a granular decomposition of the growth engine, because with a business at this stage, almost everything rests on how fast revenue compounds going forward and what falls through to the bottom line. I’ll break the advertising model into its four component levers – users, engagement, ad load, and pricing – and think through each one separately rather than reaching for a blended growth rate that hides its own assumptions.

Some of those levers fight each other, which you might only notice when you start pulling them apart.

I’ll reverse-engineer what a Pinterest-style convergence in ARPU would actually require, take a view on where steady-state margins settle over the next five years, and then work out what exit multiple I’d be willing to underwrite for a business with these economics and this concentration. Meta turns out to be the instructive anchor there, I believe, though not in the direction you might expect. Licensing I’ll think about separately.

Around all of that the rest of the diligence a decision like this deserves: Management and whether the incentives are pointed the right way. Whether insiders have been buying with their own money. The balance sheet. A base-rate check to anchor my inside view against what usually happens to companies that look like this, because narrative can be seductive and history is not.

And then my model, assumptions exposed for you to disagree with, followed by a speculative thought I keep turning over about who might eventually want to own this business outright.

Valuation

1) Future Growth – What Growth Can I Underwrite?

I want to start by developing a defensible view of how fast revenue can grow over the next five years.

And I want to build that view from the bottom up rather than extrapolating the 61% Reddit recently printed, because I have naturally a very hard time underwriting such high growth rates for multiple years. That makes me miss some fantastic winners, but it also protects my downside, because underwriting such high growth that then never materializes usually ends up with you losing a lot of money. Effectively, you often end up with a double-whammy:

• The market punishes you because it assigns a lower multiple to the lower-growth stock than it did while the business posted stellar growth, and

• you end up with the disappointing growth.

Remember:

Total Return = Earnings Growth x Changes in Valuation x Impact of Buybacks + Dividend Yield

So let me decompose the advertising business into its constituent parts and rebuild it. Licensing I’ll handle separately at the end, since its trajectory depends on what happens in the corporate negotiating rooms rather than on any operating lever.

The framework I find most useful here, and which I shared in part 2, treats revenue as the product of four things. Call it ABCD.

• A is daily active users, or how many people show up.

• B is engagement, how much they do while they’re there, which determines how many impressions each user generates.

• C is ad load, the share of those impressions that carry an ad, currently running about one ad per six to eight posts.

• And D is CPM, what each impression clears at, which I estimate around $6.30 today.

A and B together produce impressions, C converts impressions into ad slots, and D prices them. The ARPU figure Reddit reports is simply B times C times D.

Break the business into those four pieces, and you can reason about each one independently, which is far more granular than picking a growth rate that “feels” right.

Starting with ARPU & and the Pinterest Gap

There’s a discrepancy worth flagging before we go further. Reddit’s reported U.S. ARPU (I repeat: that’s the U.S. figures only) for Q2 2026 is $11.85. BofA’s estimate for the same quarter was $10.00.

That’s a gap of more than 15%. I’m nonetheless going to use their figures as I want to understand what closing the gap to Pinteresting would do to the compounding rate.

My approach is to use company-reported figures when modeling Reddit itself, but to use BofA’s series when comparing Reddit to peers and thinking through what kind of compounding rate “closing the gap” would accomplish, because within the BofA table at least everything is measured the same way.

One thing leaps off that peer table and deserves a moment. Reddit has already passed Snap. Snap’s BofA estimated U.S. ARPU sits at $9.60 for Q2 2026 against Reddit’s $10.00, and Reddit is growing that line somewhere between 32% and 61% while Snap manages 10% to 14%. So the “massively under-monetized” story has already been half-answered against one benchmark, in a way.

The next question is whether catching up to Pinterest, sitting at roughly 2.4x Reddit’s level, is the next stop for Reddit. I think it very well might be.

If you work in marketing, I would love to hear your thoughts. What are you seeing on the ground? How durable is the ARPU trend Reddit has achieved?

Leave a comment

So if I take the Pinterest comparison seriously, what growth rate does it actually imply? On a trailing-twelve-month basis using BofA’s series, Reddit’s U.S. ARPU runs about $38.50 against Pinterest’s $96.60. Call it a 2.5x gap. Closing the gap would compound Reddit’s ARPU at 20.2% over five years.

The mistake I see people make here is treating that as a fixed target, when Pinterest’s own ARPU is compounding at something like 5 to 9% a year.

You’re chasing something that keeps moving. And it makes a difference! See for yourself.

Here is a clean comparison:

The spread between those two rows makes a difference as you can see. Twenty percent a year for five years gets Reddit to where Pinterest stands today, which is a genuine achievement but not “closing the gap” (if Pinterest keeps growings its ARPU) and might not be enough to justify today’s valuation (more on this below).

Actually converging, however, means sustaining something closer to 29%, and that requires Reddit to hold roughly half its current ARPU growth rate for half a decade. Not impossible when the levers are this untouched. I’d file it as the bull-ish case rather than the base case, though.

While I’m here, let me kill an idea I initially liked and then talked myself out of. My instinct was to take a convergence figure and add 3% for inflation on top. Don’t do this. It double-counts, twice over. Pinterest’s own 7% ARPU growth, which we assumed, already embeds ad-price inflation, so the “moving-target” number has it baked in. And more fundamentally, within the ABCD framework, inflation is the D lever – CPM growth is price growth (inflation + pricing power). Layering an inflation adjustment on top of a CPM assumption counts the same thing twice. Better to choose the CPM growth rate deliberately, note that it includes ambient ad-price inflation, and stop there.

Working through the four levers

Pricing

Starting with D, since we just talked about pricing. CPMs rose 40% year over year in Q2 2026, which is genuinely spectacular, which I however refuse to extrapolate.

“During the three months ended June 30, 2026, ARPU was $6.18, an increase of 36% compared to $4.53 for the prior year period, United States ARPU was $11.85, compared to $7.87 for the prior year period, and rest of world ARPU was $2.26, compared to $1.73 for the prior year period. The increase in global ARPU compared to the prior year period was due primarily to an increase in advertising revenue driven by an increase in pricing and an increase in ad impressions delivered. During the three months ended June 30, 2026, the price of ads increased by approximately 40% compared to the prior year period driven by improved performance across the full funnel of ad objectives and higher advertiser demand. During the three months ended June 30, 2026, ad impressions delivered increased by approximately 17% compared to the prior year period driven in part by ad load optimization and improvements, including new ad placements, and by increases in the number of users and user engagement.“ - Q2 10-Q

That figure is catch-up off a depressed base rather than a multi-year run-rate. What might sustain higher pricing over five years is the mix shift toward lower-funnel performance formats – e.g. financial services bidding up 25% a year against CPG’s 3% –, and eventually search being monetized.

What caps it eventually may the platform’s its pseudonymity. Reddit will never have the identity-level targeting precision that lets the largest platforms charge what they charge, and I think that’s a permanent structural ceiling rather than a temporary gap.

I’d underwrite 8 to 12% CPM growth over the next five years, call it 10%.

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Welcome back to my deep dive series, where we look into Reddit! In this second installment, we shift our focus to truly understanding Reddit’s business: its segments and products, its customers, its value proposition, the industry it is competing in, and other findings.

By the end of this post, you’ll have a clear understanding of what makes Reddit an exceptional company with both a strong business model and a management team primed for long-term success.

Here’s the table of contents of the series once again:

What this deep dive series covers:

• The five-part bull case (”Bam Bam Bam Bam Bam”)

• 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 business itself

• Unit economics analysis

• The customer

• Legal structure, cyclicality, and operating leverage

• 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

Before we start!

Before we start, I highly recommend reading part 1 first, in which the high-level hypothesis (five BAMs) is shared in around 15,000 words (packed with qualitative insights and critical thinking; arguably the most thorough analysis of Reddit’s business on the Internet).

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.

Understanding Reddit!

History

Before I go further into the business, it’s worth slowing down on what this company is and how it got here.

Reddit’s history is unusually instructive, because the thing that makes it valuable now – 20 years of accumulated human conversation – is the direct product of two decades of decisions, crises, and near-misses.

You don’t get the unique asset Reddit represents today without the history, without the ups and downs and the occasional hiccups. So let me walk through it.

Founding and Early "Exit": From 25 links to the front page of the internet

Reddit began in June 2005 as a project by two University of Virginia roommates, Steve Huffman and Alexis Ohanian, in the inaugural class of the startup accelerator Y Combinator.

The idea they pitched wasn’t Reddit at all. It was a mobile food-ordering service called MyMenu, and Paul Graham rejected it, steering the pair toward a link-aggregation site instead.

“Their idea was bad though. And since we thought then that we were funding ideas rather than founders, we rejected them. But we felt bad about it. Jessica was sad that we’d rejected the muffins. And it seemed wrong to me to turn down the people we’d been inspired to start YC to fund.

I don’t think the startup sense of the word “pivot” had been invented yet, but we wanted to fund Steve and Alexis, so if their idea was bad, they’d have to work on something else. And I knew what else. In those days there was a site called Delicious where you could save links. It had a page called del.icio.us/popular that listed the most-saved links, and people were using this page as a de facto Reddit. I knew because a lot of the traffic to my site was coming from it. There needed to be something like del.icio.us/popular, but designed for sharing links instead of being a byproduct of saving them.

So I called Steve and Alexis and said that we liked them, just not their idea, so we’d fund them if they’d work on something else. They were on the train home to Virginia at that point. They got off at the next station and got on the next train north, and by the end of the day were committed to working on what’s now called Reddit.“ - Paul Graham

What they built was a plain page of links they liked to call the front page of the internet. On August 13, 2005, real user posts filled the home page for the first time, a small milestone that mattered because it meant the thing had users.

“I think of August 13, 2005 as the day Reddit really came to life. We had been online for a couple of months, but until then there had never been enough posts from users on any day to fill the front page. That morning, to my surprise, I opened Reddit to discover the home page was overflowing with posts from real users for the first time.“ - Reddit Co-Founder in the S-1 Filing

Late that year Reddit merged with Aaron Swartz’s Infogami, folding Swartz’s Python framework into the core stack and adding his architectural fingerprints to the early product.

Then came a decision that has aged strangely. In October 2006, barely a year after launch, the founders sold Reddit to Condé Nast, parent Advance Publications, for somewhere between $10 and $20 million, and left soon after.

At the time it looked like a clean win for two young founders. In hindsight, it’s cited as one of the great corporate undervaluations in tech history. The Condé Nast years did serve a purpose, though. They gave a bandwidth-hungry site the capital to survive its own growth. And in 2008, Reddit made the single most important architectural choice of its life: it launched user-created subreddits, which decentralized the platform into interest-based communities and, almost as a side effect, shifted moderation from an engineering chore into the hands of volunteer community moderators.

The self-governing city that defines Reddit today was born in that one product decision. The Data API arrived the same year, a detail that becomes enormously important 15 years later.

“Reddit has become one of the internet’s largest open archives of human experiences and Reddit data can be utilized in many ways – to both improve our platform and for commercial application. Since introducing our Data API in 2008, we have seen thousands of applications built – tools, and utilities dedicated to improving the user experience. While we recognize that many of our users enjoy using third-party applications that contribute to Reddit in many important ways, we also concluded that we needed to better manage infrastructure and opportunity costs – especially with commercial entities that require large-scale data use from our API.“ - S1 filing

In 2011, Advance spun Reddit back out as an independent company while keeping majority equity, restoring operational autonomy to a business that had grown culturally huge and financially unprofitable.

Reddit General Manager Erik Martin said in an interview back then that Reddit was getting 700,000 page views a day (about 21 million views per month) when it was acquired in 2006, and by 2011 it was getting 1.6 billion page views a month on 21 million unique users.

A decade of governance crises

For most of its first ten years, Reddit ran on something close to free-speech absolutism, and that stance repeatedly collided with reality. The mid-2010s were genuinely chaotic. CEO Yishan Wong, who took over the CEO role only in 2012, resigned in 2014 over, of all things, an office real-estate dispute, handing the role to interim CEO Ellen Pao. Pao absorbed the community’s fury when she banned notoriously toxic subreddits and, separately, when the company fired popular employee Victoria Taylor – an episode that triggered a site-wide moderator blackout in 2014 and 2015.

It was the first time the community demonstrated, at scale, that it could turn off the lights. It would not be the last.

Then, Huffman came back as CEO in July 2015, and his return marked a strategic turn as much as a personnel one.

He replaced the wild-west ethos with formal content policies, systematically banning illegal, non-consensual, and explicit hate content, and he began the long, unglamorous work of modernizing infrastructure that had been neglected for years.

The political flashpoints kept coming. Subreddits like r/The_Donald became centers of platform manipulation and hate speech through the 2016 and 2020 election cycles, and in June 2020 Reddit permanently banned it, closing the book on its absolutist era.

That same month, Ohanian resigned from the board amid national unrest (at the height of the Black Lives Matter protests) and explicitly asked to be replaced by a Black director, following earlier allegations from Pao that the platform had long tolerated racism – a promise Reddit fulfilled shortly after by appointing Michael Seibel, former CEO of Y Combinator. These weren’t sideshows. They were the company slowly learning that a platform built on human speech has to decide what kind of speech it will host, and that every such decision costs it something with some part of its base.

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Building the money machine, and the revolt it provoked

The commercial Reddit really starts around 2016. The company had served ads since 2009, but serious monetization didn’t begin until it started investing heavily in proprietary ad technology later in the decade; arguably meaningful monetization efforts did not begin until 2018.

“We started selling advertisements on Reddit in 2006. We began more meaningfully investing in our own ad technology and foundation in 2018. We built our advertising business by focusing on top U.S.-based advertisers, and over time we have expanded our focus towards mid-sized and smaller advertisers as well as new geographies. We believe we have a significant opportunity to increase our revenues from existing customers, as well as attract more advertisers to Reddit by enabling more ways for customers to invest to grow their business on Reddit, and intend to continue to make technological investments in this area. […]

We believe we are in the early stages of monetizing our user base, and we plan to expand our monetization efforts in ways that build on the core values of our platform. We plan to drive growth in advertising revenue by focusing on initiatives to support advertising improvements, including increased use of artificial intelligence in our advertising solutions. We also intend to open additional monetization channels for Reddit by providing our users and creators with the requisite tools and incentives to drive continued creation, improvements, and commerce. […]“ - S-1

Reddit acquired the video platform Dubsmash in 2020 and contextual-ad firm Spiketrap in 2022, rebuilding its ad-bidding stack to go after the performance marketers who almost exclusively focus on Meta and Google.

Somewhere in this stretch, Reddit, somewhat quietly, won the war for online advice, outlasting Yahoo Answers and Quora to become the internet’s default forum for human recommendations – the very position that makes it indispensable to AI models today.

Two events in the early 2020s defined the modern company. The first was cultural proof of power: in January 2021, r/WallStreetBets drove the GameStop short squeeze, showing that Reddit could coordinate mass consumer behavior well enough to bloody actual hedge funds.

The second was the fight that set up everything we discussed in part 1 of this series quite extensively already. In mid-2023, Reddit announced paid API tiers at $0.24 per 1,000 requests, explicitly to stop AI companies from scraping its conversation data for free. The pricing was steep enough to kill high-profile third-party apps like Apollo, and the community erupted (which may be an understatement) – more than 8,000 subreddits went dark in protest.

This time Huffman refused to fold. He threatened to replace uncooperative moderators and asserted, bluntly, that the communities were corporate assets. It was an ugly, revealing moment. It was also, in cold commercial terms, the decision that made the data-licensing business possible. You can dislike how it was handled and still recognize that the API fight is why the “other revenue” line exists at all.

Reddit API Controversy Timeline

April 18, 2023: Reddit announces plans to start charging for access to its Data API (which had been free since 2008), primarily targeting tech companies using Reddit data to train large AI models.

May 31, 2023: Christian Selig, developer of the popular iOS client Apollo, reveals that Reddit’s proposed rates ($0.24 per 1,000 API calls) would cost his app roughly $20 million per year, making operation financially impossible.

June 5–8, 2023: Popular third-party applications – including Apollo, Reddit is Fun (RIF), Sync, and BaconReader – announce they will shut down permanently on June 30 rather than incur unmanageable debts.

June 9, 2023: CEO Steve Huffman (”spez”) hosts an Ask Me Anything (AMA) to address community backlash, but his refusal to walk back prices and allegations against developers further inflame anger.

June 12–14, 2023: Over 8,000 subreddits participate in a planned 48-hour “blackout” by making their boards private or restricted, pulling down massive chunks of the site and causing temporary global outages.

June 15, 2023: A leaked internal memo reveals Huffman telling staff that the blackout had “no significant revenue impact” and “will pass,” prompting hundreds of subreddits to extend their blackouts indefinitely.

June 16, 2023: Reddit leadership begins sending warnings to volunteer moderation teams, threatening to strip them of their privileges and replace them if they do not reopen their communities.

Late June 2023: Users adapt their tactics to avoid mod removal. Communities like r/pics and r/aww vote to post exclusively photos of comedian John Oliver, while others reclassify subreddits as NSFW to cut off Reddit’s advertising revenue.

June 30, 2023: Apollo and several other major third-party clients officially turn off their servers.

July 1, 2023: The new paid API terms officially take effect.

July 20–24, 2023: During the annual r/place digital canvas event, users coordinate mass pixel art depicting protest slogans directed at Huffman (”Fuck spez”).

The IPO and the pivot to seekers

Reddit reached the public markets on March 20, 2024, listing on the NYSE under RDDT at $34 a share, roughly a $6.4 billion valuation, raising around $748 million.

In a gesture that fit its history, it set aside a slice of IPO shares – about 8% – for its most active users and moderators through a directed share program, letting the citizens of the city become owners of it.

The commercial engine spun up fast from there. A multi-year Google data deal reportedly worth around $60 million a year gave Google real-time access to Reddit content for LLM training, and an OpenAI partnership wired Reddit data into ChatGPT, establishing the company as a core vendor to generative AI.

Revenue pushed past the $2 billion mark on the back of programmatic ads and high-margin licensing, net income turned positive for the first time in Q3 2024, and the balance sheet strengthened enough to authorize a $1 billion buyback.

Interestingly, Reddit recently evolved its mission statement to “empower communities and make their knowledge accessible to everyone.” Read that carefully as it signals a strategy shift… The old Reddit was built for its logged-in members. The new mission explicitly embraces the seekers arriving from search engines and AI models as a core audience rather than incidental traffic – the tourists from Bam #2 in part 1, promoted to first-class citizens.

So where does that leave Reddit in its life cycle?

The honest answer is: it’s still to be determined. And in fact, Reddit might be in two ages at once:

• As a platform, it’s 20 years old, celebrating that anniversary in 2026, mature in its culture and entrenched in its niche.

• As a monetized business, it’s barely a toddler – it only became profitable in late 2024 and is still switching on entire revenue streams it has never monetized. The company is posting start-up-like growth, and it remains to be seen how durable these growth rates will prove to be.

That’s the whole investment setup. An old, established asset in the early innings of learning how to make money from itself.

The history explains why the asset is so hard to replicate and took decades to build. The youth of the monetization engine is why there’s an investment hypothesis worth testing at all.

Product

Ask Reddit to describe itself, and you won’t hear the words “social network.” The company insists it’s a global digital city, a “community of communities,” and this framing is not just a marketing or branding move.

I recommend you watch this new TED Talk with CEO Steve Huffman (only uploaded one month ago), in which he expands on the “city” analogy; he also talks about what will make Reddit stand out in the upcoming AI era.

The platform is home to over 100,000 active subreddits, each functioning as a neighborhood where people talk to one another about a specific topic, from parenting to particle physics to a single television show.

Besides the subreddits, some of the key user-facing products (to be distinguished from Reddit’s core customers (advertisers)) include:

• Subreddits & Feeds: The platform is organized into over 100,000 active communities (subreddits) dedicated to specific interests. Users interact with these through a personalized “For You” feed or specific community pages.

• Conversational Tools: Users participate by creating posts (text, images, video, links) and engaging in comment threads, which are considered the “heart and soul” of the Reddit experience.

• Search & Reddit Answers: Reddit is a major search destination, handling millions of daily on-platform queries (~40+ million queries per day). The company is unifying traditional search with Reddit Answers, an AI-powered tool that summarizes community discussions to provide curated responses to subjective questions.

“Reddit Answers queries, I believe, were up from 1 million to […] 15 million, […] over the last year and then 60 million to 80 million overall search queries. So we're seeing nice growth there.“ - Call Transcript

“Search on the internet is evolving to become more social and shifting toward more interactive and personalized experiences as users seek authentic perspectives from real people We believe Reddit is well-positioned to capitalize on these changes with its unique advantages: a highly engaged user base, conversations with commercial intent, and the largest collection of authentic content on the internet In Q1, over 60 million WAUq used Reddit’s on-platform search, and query volume increased 10% sequentially, reaching nearly 50 million queries per day We launched our first search ML model that is driving more relevant search results, and we built modern search features, including auto-complete and auto-queries Reddit Answers, our AI-powered conversational search tool, is now available to all U.S. users and some international markets including the U.K., Canada, Australia, India, and others We are testing integrating Reddit Answers into existing surfaces where Redditors are searching on the platform, and we expect deeper integration will grow awareness, deliver more dynamic search results, and set a foundation for a differentiated search experience“

• The contributor program allows eligible users to earn real (fiat) money for their contributions based on the “Gold” and “Karma” they receive from others.

  

• Developer Platform: Enables users to build interactive apps and games (like Flappy Goose) directly into subreddit posts.

  

• Reddit Premium: A paid subscription offering an ad-free experience, access to an exclusive “members’ lounge,” and premium avatar customization.

  

• Video in Comments: A recently introduced feature allowing users to respond to threads with short video clips, enriching the conversational experience.

I also like how CEO Huffman framed the unique value proposition of Reddit (to users) at the Bank of America 2026 Global Technology Conference:

“… Reddit search, I think, is the best at questions with no answers. So you could try it right now, like what show should I watch tonight? I’d like this show, what show would you recommend? I need help with this video game. What’s the best headphone? All these things. […]

What is important for Reddit, and I think this is unique to Reddit, which is we have completely unique and differentiated content and people don’t want summaries on -- I was going to say, important questions, but sometimes it’s like what I call them questions with no answers. So let me give you an unimportant question with no answer. What should I watch tonight? People want to hear the conversation. What car should I buy? Like where should I go? What’s the best headphone? There isn’t an answer. How do I deal with XYZ issue with my kid? Like people want to hear from other parents. And so there’s plenty, I think, of commodity content on the Internet. And indeed, a few companies have been vaporized by AI, but not Reddit. And instead, I think Reddit actually becomes more and more valuable over time and people start to appreciate this, what Reddit does more and more. So we keep doubling and tripling down on our mission, communities, authenticity, Reddit being the most human place on the Internet and having confidence that however the ecosystem evolves, Reddit will be a destination.“

That value proposition, that uniqueness, that “communities within communities” structure is the whole product. Everything Reddit sells is, in one way or another, a way of monetizing the conversation those “neighborhoods” generate.

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• InPost ($INPST) - generated an IRR of >400% as an acquisition offer emerged 2-3 months post write-up

• DigitalOcean ($DOCN) - up 5x in less than a year post write-up release

Why I think this is worth it: Over almost two years, I’ve published 350+ posts: 65+ deep dives across ~50 companies, valuation templates, the AI tools I’ve built and shared, my Perception Change Framework, portfolio updates, and educational pieces on concepts like base rates. The deep dives get the attention, but just as much value sits in the process-oriented pieces I believe – plus the embedded thinking I reveal in every analysis.

On the commercial side, the revenue flows from four sources of very different sizes.

• The overwhelming majority – roughly 94-95% – is advertising, and this is the business you should think of as Reddit’s core. Reddit sells access to its high-intent audience through native ad formats that are placed inside the users’ experience (without being overly disruptive, as of today). The customer-facing products (read: tools for advertisers) include:

  • Native Ad Formats:

    • Promoted Posts: Ads that appear natively within the home and community feeds.

    • Conversation Ads: A flagship product that places ads directly within comment threads, reaching users at their point of highest engagement.

    • Shopping / Dynamic Product Ads (DPA): These automatically match an advertiser’s entire product catalog to high-intent conversations, often delivering a 2x higher ROAS than standard campaigns.

      

    • Shopping Listing Ads: A multi-advertiser format that matches relevant products to specific shopping-related conversations.

    • Takeover Products: High-impact, guaranteed reach placements (e.g., Front Page or Category Takeovers) where a brand “owns” the top of the feed for 24 hours.

    • Free-form Ads: Unique long-form ads that allow brands to share multimedia content and expertise in a way that feels native to Reddit.

    

  • Performance & Automation Tools:

    • Reddit Max: An end-to-end AI-powered automated campaign type that optimizes settings in real-time to drive better results with less manual effort.

    • Automated Bidding: Includes goals such as Maximize Clicks, Conversions, or Installs to help advertisers scale efficiently.

  Reddit runs an auction-based model where advertisers bid for sponsored posts, conversation ads, and shopping ads, with Reddit recognizing revenue when a user clicks (CPC), views an impression (CPM), or watches a video (CPV). Nothing exotic there – it’s the same fundamental mechanism Meta and Google run, just earlier in its optimization.

  • Insights & Organic Presence:

    • Reddit Pro: A free suite of tools helping businesses establish an official organic presence, listen to community trends, and manage Verified Profiles.

    • Reddit Insights: An AI-powered social listening tool providing real-time visibility into brand sentiment and competitor positioning.

    • Conversation Summary Add-ons: An ad feature that uses AI to surface positive Reddit comments directly within a brand’s ad, providing social proof.

  • Measurement & Brand Safety: Reddit offers tools like the Reddit Pixel, Conversion API (CAPI), and a “Community Allowlist” to ensure ads are effective and appear only in brand-suitable environments.

• The second source is data and content licensing, the archive-as-oil business I covered in Bam #1 in part 1 of this series, where Reddit licenses its 20-year, 26-billion-item corpus to AI developers and search engines for training and grounding. Small today, strategically outsized.

• Then there’s what Reddit calls the user economy – digital goods like Reddit Gold, plus a Contributor Program that lets users convert quality contributions into actual money.

• And finally subscriptions, through Reddit Premium, which strips out ads and adds perks like exclusive avatar gear and a members’ lounge for a monthly fee.

Four vectors, but make no mistake about the shape of it: this is an advertising company with three interesting side businesses, one of which happens to be growing very fast.

It’s worth pausing on what kind of “goods” these actually are, because the mix is unusual.

• Advertising is a consumable service in the purest sense. An impression exists to be viewed or clicked, and once it is, that unit of inventory is gone. Data licensing works the opposite way.

• The content already exists and isn’t used up by being licensed. It’s closer to a non-consumable access right, granted for a fixed or usage-based fee over the life of a contract, which is part of why the incremental margins are so extreme.

• And the digital goods in the user economy are non-consumable assets that the user owns outright.

So Reddit runs a consumable business and a non-consumable one side by side on top of the same underlying asset.

Next, I always wonder whether a firm’s “product” or core feature is differentiated or just another interchangeable one (here’s Reddit’s feed) competing on price and reach. Reddit is clearly the former, and the reason comes down to a structural difference in how the platform is organized. Meta and TikTok are built on a social graph – the product knows who you follow, who your friends are, and infers what you might want from that web of relationships. Reddit is built on an interest graph. Users self-sort into communities based on what they’re thinking about rather than who they know, which means the platform captures intent directly instead of guessing at it. That’s the same declared-intent advantage discussed in Bam #2, but it’s worth restating here as a product characteristic rather than an advertising one, because it’s the root of nearly everything that makes Reddit distinctive. Reddit is a destination for seekers arriving with a specific question, not only scrollers looking to kill time.

There’s a second axis of differentiation that has grown sharper as the web has changed, and it ties back to the AI thesis. As synthetic content floods the internet, Reddit’s positioning as the largest source of authentic human perspective and lived experience becomes a genuine product feature that only increases in value as AI arrives in mainstream media.

The upvote and downvote system reinforces this – content visibility is earned through community validation rather than handed out by an opaque algorithm optimizing for watch time. You can’t easily fake your way to the top of a subreddit that a few thousand knowledgeable people are watching. That quality-control mechanism, run for free by the community, is part of what makes the output trustworthy enough for both users and AI models to rely on.

High-tier audience, mid-tier monetization

If you’re trying to place Reddit in a product segment, the honest answer requires splitting the question in two, because the platform sits in different tiers depending on what you’re measuring.

On the quality of the asset, Reddit is high-tier. The audience is genuinely attractive – as of the date of the S-1 filing, 64% of U.S. users have a household income over $75,000 – and the intent is about as good as it gets online.

On monetization, though, Reddit is mid-tier at best, still in the early innings of its monetization efforts, with ARPU still a fraction of Meta’s – we discussed this at length in part 1 (and it’s arguably the most important pillar of the thesis).

I’d frame that gap as the entire opportunity rather than a knock on the product. A high-quality audience being monetized at low- to mid-tier rates is a catch-up story. A mid-quality audience already monetized to the hilt would be a very different, and far less interesting, investment. The tier mismatch is the point.

What’s coming next?

Reddit isn’t standing still on any of this, and the product roadmap tells you a lot about where management thinks the business is going.

One of the most strategically important items is Reddit Answers, an AI-powered conversational search tool that serves up curated summaries of community discussions – the on-platform search product that turns the 80 million weekly queries from an unmonetized cost into a potential destination in their own right.

“Together, they drove more search volume and queries per user with over 80 million people searching directly on Reddit every week in Q4, up from 60 million just a year ago.“

Around it sits a widening set of tools. Reddit Pro gives businesses and publishers an organic way to build a presence, read community sentiment, and manage their reputation.

“We have seen growing adoption of Reddit Pro since expanding access to all publishers, giving them self-serve tools through auto import articles receive AI-powered community recommendations on where to share them and measure the reach and engagement of their content on Reddit. Publishers ranging from global outlets to local press like Fortune Media to the SF Chronicle and Dallas Morning News and sports brands like Arsenal FC are now using Reddit Pro. Overall, there’s a lot to be excited about this year. And every day, we see more businesses coming to Reddit it to connect with their audience and grow their business. And as the pace of change in the market grows, Reddit’s fundamental assets and value proposition built on authenticity, trust and high intent keep us exceptionally well positioned. Thank you for joining us and for your continued support.“ - Q1 Call

Reddit Max uses AI to automate ad campaigns for the small and mid-sized businesses that can’t staff a marketing team, which matters because SMB budgets are how ad platforms broaden beyond big brands.

“We’re executing against 3 areas: scaling automation through our ads platform and Reddit Max, delivering advertiser value across the full funnel, expanding the Reddit for Business ecosystem. Starting with automation. Reddit Max launched private beta earlier this year, and we’re seeing strong adoption and performance for mid- and lower-funnel advertisers. The number of advertisers using Max grew over 60% from Q1, while Max revenue grew over 150% during the same period. We continue to add capabilities to the Max suite.

In Q2, we added the app install objective to Max campaigns and launched tailored creatives, which uses AI to identify relevant communities and audiences then designs variants on advertiser creative to improve ad relevance and performance. Max campaigns are proving to drive better performance for advertisers and high-LTV customers. For example, Lenovo achieved 40% higher purchase value with Max than with standard campaigns, demonstrating how AI-driven optimization can turn high-intent users into high-value customers. Looking ahead, we plan to expand Max to a broader range of advertisers and make it the primary onboarding experience for SMBs. We also plan to introduce new features that simplify activation and continue enhancing our models to drive stronger performance.“

There’s video in comments to enrich the conversational core, …

“Video views was our fastest-growing upper funnel objective, more than doubling revenue year-over-year. Our 6-second engaged video views goal, which became generally available in January, helps video-first advertisers optimize for longer, more meaningful views. In testing, the objective delivered over 130% lift in 6-second view-through rate, over a 70% increase in video completion rate and an 80% reduction in cost per 6-second video view with auto bidding.“ - Q2 Call

… and Reddit Lite, a stripped-down app being tested in international markets to improve access and speed where connectivity is weaker – a direct enabler of the global runway discussed in Bam #5. I couldn’t find any updates on this endeavour ever since it was pitched at an investment conference back in March 2025, though:

“Now that said, we are building another version of our app called Reddit Lite, which we'll be testing internationally. And so we're doing 2 things here. One, we're just building a lightweight version of the app to use internationally, which is a kind of tried and true practice. But also, we're going to be experimenting with pretty big changes to the UI, making Reddit, in my opinion, much easier on the eyes, much easier to use, making a home feed that better accommodates all the different content types we have.“

And further out, potentially creator monetization (as teased in 2024): plans for paywalled subreddits and exclusive community subscriptions that would let Reddit siphon business from the likes of Twitch and Patreon.

“Your question is if we start to include other incentives in there, like monetary incentives, does that change? In my experience on Reddit, whenever we add basically a new way of using Reddit, what happens is it expands Reddit, but we’ve not seen it cannibalize existing Reddit. And so I think the existing altruistic free version of Reddit will continue to exist and grow and thrive just the way it has. But now we will unlock the door for new use cases, new types of subreddits that can be built that may have exclusive content or private areas, things of that nature. A good example of this, for example, is at Reddit, we didn’t host images back in the past. It was all text and links, and images were linked. […] So I’d look at this as an opportunity of expansion as opposed to one that is going to cannibalize the existing Reddit, which as I said, is magical. It’s something that we think is truly precious.“ - Huffman

I’d read that roadmap with a mix of interest and caution. The through-line is coherent, which is encouraging – nearly every item pushes Reddit from a passive forum toward an end-to-end utility that captures more of the value it already creates. But it’s also a lot of surface area for a company that has only recently learned to make money, and each new product is a fresh place for execution to slip.

Reddit Answers in particular carries an odd internal tension – Ii’s the product most likely to unlock search monetization, and it’s also the product most likely to keep users from clicking through to the threads that feed the ad business.

Business Operations

Reddit reports as a single operating segment, which sounds like an accounting footnote but tells you something about how the company thinks I believe.

The CEO acts as the chief operating decision-maker and evaluates the business on a consolidated basis, so there’s no divisional carve-up to analyze.

What the company does disaggregate is revenue by source, and that split is where the story lives. There are two lines:

• Advertising, and

• Other Revenue

… the latter bundling data licensing, Reddit Premium, and the user economy together.

“Other Revenue: In our content licensing arrangements, we provide customers with the right to access content from our platform over the contractual period. The transaction price in content licensing arrangements is generally a fixed fee or usage-based fee. We recognize content licensing revenue as our content partners consume and benefit from their use of the licensed content, which is generally ratably over the license period. Revenue from products sold directly to users, including Reddit Premium and Reddit Gold, was not material for the periods presented.“

The proportions are lopsided in a way that’s important to internalize. On a trailing-twelve-month basis through Q2 2026, Reddit did roughly $2.78 billion in total revenue. Of that, advertising accounted for about $2.63 billion, or 94.5%, with Other Revenue contributing around $153.6 million, the remaining 5.5%.

So when I talk about Reddit’s economics, I’m mostly talking about an advertising business, and the data-licensing story that gets so much attention – rightly, for its strategic weight – is still a rounding-error slice of the top line today.

That’s not a criticism. It’s a reminder to keep the near-term and the long-term properly separated.

The ad business pays the bills now. Licensing is the option on the future. But even that requires a very nuanced discussion, which we covered in Bam #1 (first and foremost, the risk licensing Reddit’s data into AI Overviews poses to potentially cannibalizing Reddit’s own traffic, and thus, its advertising business).

The economics underneath both lines are what make this a genuinely unusual company. Revenue hit its eighth consecutive quarter of 60%-plus year-over-year growth as of Q2 2026, which is a remarkable streak for a business of this size.

And in 2026, revenue converts into real accounting AND cash profits.

Reddit crossed into consistent GAAP profitability in late 2024, incremental adjusted EBITDA margins have averaged around 55-60% over the last five quarters, …

and FCF is trending only in one direction, …

… all of this shows that revenue is outrunning costs by a wide and durable margin.

Growth that fast paired with flow-through that rich is the “one-of-one” claim in a nutshell, and it’s why the a good chunk of the analysis in part 1 was focussed on stress-testing whether and how long that kind of profitable growth can last.

The KPIs to focus on

Every industry has its scoreboard, and for social platforms the metrics are fairly standardized. Reddit (and its peers) watch four in particular.

1) DAUq (1a) US + 1b) International)

For Reddit, arguably the most important KPI is the Daily Active Unique, the DAUq. Get the direction of DAUq right and most of the rest follows, which is exactly why the mid-2026 sequential dip of 300,000 U.S. uniques spooked the market so badly.

The two north-star milestones management keeps pointing at are

• one billion global DAUq, and

• 100 million U.S. DAUq,

… the latter roughly double today’s domestic base.

Those are enormous numbers, and hitting them depends on the thing they say they’re focused on controlling – product quality, speed, and feed relevancy that drive direct, daily habit rather than drive-by search traffic. Which brings the whole KPI discussion back to where it started. The domestic user count is the number the market watches most nervously, the conversion of casual visitors into daily residents is the engine underneath it, and the recent sequential dip is exactly the kind of wobble that makes both harder to read. Watch DAUq. But watch how it’s composed, not just how big it is.

2) Engagement I (Logged-in vs. Logged out)

This is the unit to watch. But the headline number hides a distinction that, until recently, mattered enormously. Not all DAUqs are the same. Reddit has historically split them into logged-in and logged-out users, and those two cohorts behave nothing alike.

The logged-in user is the “resident.” They’re on the app, they’ve built up years of interest signals, and in the U.S. they spend something like 25 to 30 minutes a day on the platform, climbing past 45 minutes for accounts older than seven years.

The logged-out user is the “tourist,” usually arriving from a Google search with a single question, grabbing an answer, and leaving. They spend far less time on the site.

Unsurprisingly, the resident contributes a lot more to ARPU than the tourist does. What’s easy to get wrong, though, is why. The instinct is to assume logged-out users monetize poorly because their intent is weaker or their signal is thinner, and that’s not what management says at all. COO Jennifer Wong has been explicit that on an individual impression basis, the value of the two is effectively the same. Both see ads in the same surfaces, the feed and the conversation pages, and Reddit can target both using high-quality contextual signals.

The monetization gap is almost entirely a function of time spent, which is to say inventory volume, rather than any deficit of intent. The tourist is worth just as much per impression. They simply generate fewer impressions before they leave.

It’s also about converting tourists into residents – turning weekly visitors into daily ones, and logged-out drop-ins into logged-in regulars. Management thinks of this as moving people from “seeker” to “scroller,” from someone who came for one answer to someone who stays to browse their communities.

However, Reddit learned that forcing a login immediately just annoys people and doesn’t hold them, so instead the goal is to satisfy the seeker’s question first, make Reddit a genuine end-to-end search destination, and let the deeper engagement and the organic log-ins follow from a good experience rather than a nagging pop-up.

The app is the prize in this conversion, since app users are worth multiples more than search referral traffic and are far more engaged once they arrive.

“The direct users, the app users are worth multiples more than the search referral traffic. We're not building Reddit for that drive by traffic, we're building Reddit for direct usage. And that's where our business lives.“ - Call Transcript

One wrinkle worth flagging for anyone modeling this going forward: the logged-in/logged-out distinction is about to disappear from the reporting. Beginning with the quarter ending September 30, 2026, Reddit will stop disaggregating DAUq into the two categories, on the reasoning that product improvements like instant personalization and streamlined onboarding are blurring the line between the two states anyway. Management will primarily evaluate performance on total DAUq and geography from here.

I have mixed feelings about that. On one hand it genuinely reflects an evolved product where the two experiences are converging. On the other, it removes a lens investors could use to see exactly how the tourist-to-resident conversion was progressing, which is precisely the dynamic that determines whether ARPU can keep climbing. Less disclosure is rarely a gift to the outside analyst, even when the rationale is sound.

3) Engagement II (Frequency)

If DAUq is the number the market watches, the internal metrics management actually steers by tell a richer story, and one of them reframes the growth question entirely:

The “1 vs. 7” Phenomenon

When Reddit looks at how many days a week a user shows up, the distribution isn’t a smooth bell curve. It’s bimodal. The two biggest clusters are people who visit one day a week and people who visit all seven, with relatively little sitting in the middle.

Huffman describes the core product job in exactly those terms: convert the 1s into 7s. There’s a revealing implication buried in that shape. Once Reddit truly clicks for someone, they don’t drift into being a casual three-day-a-week user – they tend to become a daily habit. The platform either gets you or it doesn’t, and the product work is about pushing more people across that threshold rather than nudging everyone up a notch.

“So weeklies and dailies, themselves are both important measures of Reddit. But if we look at within our U.S. traffic, we have about 200 million U.S. weeklies and about 50 million U.S. dailies. And so when I think about that path to 100 million U.S. dailies, so roughly double from where we are today, I look at the potential of the 200 million weeklies we already have. And so if we think about the kind of 3 aspects of growth on Reddit. So reach is like the total scale.

So already in the U.S., we’re at 200 million weeklies, but how do we grow that to capture more of those as daily users. Frequency is the one that we’re really thinking about right now. So how often do users come to Reddit every week. And so if you were to look at a histogram of how many days active a user is on Reddit, the 2 biggest bars would be 7 days and then they come every single day, 7 days a week or 1 day. And so quite simply, our job is to convert those 1s into 7s.

In between, there’s actually not much. But that journey can be challenging. So really increasing the reach there.

And then depth, so this is how much time people are spending on Reddit. I think we’re actually a very healthy spot here. A U.S. logged-in user spends on average 30 minutes a day on Reddit. And the older their account is, the more time they spend on Reddit.

So a seasoned account spends more like 50 minutes a day on Reddit. And so again, this kind of tells the same story [indiscernible] once users get it, they actually go deeper and deeper over time. One of the ways Reddit is different than social media is our users don’t age out of Reddit. They age out of social media and then they age into Reddit. But because Reddit communities cover everything you’re doing or thinking about from something mundane, like what should I watch tonight, right, the never-ending problem of life to relationship challenges or kid challenges, our medical maladies, whatever it is, Reddit is there with you on your life’s journey.

So it’s really for us that -- that frequency question, excuse me, of taking that -- the potential energy we see in our weeklies and converting those into dailies.“

This is where the gap between weekly and daily users stops being a curiosity and becomes the growth story. In the U.S., Reddit has roughly 200 million weekly active users but only around 50 million daily ones.

Sit with that ratio for a second. Four times as many people touch Reddit in a given week as use it every day, which means the domestic audience that already finds Reddit useful enough to return weekly is vastly larger than the daily base the market frets about.

Management calls this potential energy, and I think that’s the right way to hold it. The nervous read of the recent DAUq dip assumes Reddit is bumping against a ceiling. The more optimistic read is that the ceiling is defined by that 200 million weekly figure, not the 50 million daily one, and the job is conversion rather than fresh acquisition. Converting an existing weekly user into a daily one is a very different, and far more controllable, task than winning someone who has never used the platform at all. It doesn’t guarantee the conversion happens. But it reframes what “saturated” would even mean.

I don’t want to oversell it, though, and there’s an honest ceiling on this particular strength. Reddit’s engagement is deep but not necessarily long in raw minutes, and analysts rightly point out that a text-based platform struggles to match the sheer screen time of video-centric rivals like Instagram or TikTok. Scrolling video compounds watch time in a way that reading and writing comments simply doesn’t.

Logged-out visitors arriving from search spend maybe 5 to 8 minutes a session, a fraction of the resident’s daily half hour. So Reddit wins on the quality and durability of attention rather than the volume of it, and in an ad model where inventory scales with time spent, that’s both a genuine strength and a real constraint. The vintage effect makes each resident more valuable over time. It does not turn Reddit into TikTok, and it shouldn’t be modeled as if it will.

New User Retention & Sessions Per Day

The public gets DAUq and WAUq. Internally, the team watches a more sophisticated set that gets at the quality of engagement rather than just its scale, and these are the leading indicators I’d want to track if Reddit disclosed them more fully. The one management calls the core measure of product quality is new-user retention, specifically whether someone comes back after 7, 30, and 90 days.

Alongside it sits sessions per day, a newer internal gauge of home-feed quality, and a metric Reddit calls “good visits” – a visit where the user spends more than 30 seconds actually consuming a post. Good visits jumped 30% in late 2023 after improvements to the home-feed ranking models, which is the kind of concrete before-and-after that tells you the machine-learning investment is generating good results.

And search shows up here again as a leading indicator, since users who perform any search have 30% higher week-one retention. Search volume, in other words, isn’t just an untapped ad surface. It’s an early warning system for whether new users will stick.

4) ARPU

On the revenue side, each unit is measured by ARPU, and the global figure as of Q2 2026 was $6.18.

That blended number hides the disparity that defines the investment, though. U.S. ARPU stood at $11.85 while international ARPU was just $2.26 – the same coiled-spring gap from Bam #5, now expressed at the level of the individual user.

A U.S. Redditor is worth roughly five times an international one.

About four metrics is a fine scoreboard – you could add the margin profile, but given the embedded operating leverage, I see only one direction for margins if the KPIs above develop favorably –, but the discipline Buffett and others push for is narrowing further – identifying the handful of variables that genuinely drive long-term value (i.e. more cash) and asking how predictable each one is.

For Reddit, I’d argue there are essentially four levers doing the real work, and I’ll be watching them above everything else.

• The first is ARPU expansion, the central bet of the whole investment: closing the roughly 10x gap between Reddit’s U.S. ARPU and Meta’s just a little bit, powered by the shift from brand advertising toward high-intent performance and search ads.

• The second is international conversion, translating the English archive into 35-plus languages to wake up under-penetrated markets like France, Germany, and Brazil.

• The third is headcount discipline, the unglamorous lever that determines whether incremental revenue keeps flowing through at those 95-to-99% gross margins or gets eaten by hiring.

• And the fourth is data licensing, which I’d characterize as an embedded call option – a high-margin, potentially recurring and scalable, and defensive, revenue stream whose value is mostly still ahead of it.

Finally, I also like the framework/formula presented in a recent write-up on Reddit’s advertising business – it reminds me very much of how I always thought about Meta’s ad business:

“Reddit’s business should be viewed through an ABCD framework, where:

Revenue = A × B × C × D

A — Daily Active Users (DAUs). How many people show up.

B — Engagement. How much they do while they’re there (sessions, time, surfaces touched), which determines how many impressions each user generates. Logged-in users typically spend an average of ~30 minutes a day on the app, while logged-out users spend ~5-8 minutes.

C — Ad load. How many of those impressions carry an ad. Currently about one ad per 6-8 posts.

D — CPM. What each ad impression clears at. This is ~$6.30 according to my estimates.

A and B produce impressions. C converts impressions into ad slots, and D prices them. ARPU (which Reddit reports) is the product of B x C x D. We will begin with lever D.”

And that’s of course how management also thinks about its growth levers:

“Revenue growth was driven by both pricing and impressions, demonstrating the increasing value we deliver to advertisers.“ - Call Transcript

And …

Spoiler:

We will use a similar framework to value Reddit and determine its growth trajectory range in part three of the series (valuation)

Costs on a Per-Unit-Basis

Reddit doesn’t publish a formal cost-per-user figure, but you can back into it. Adjusted cost of revenue – hosting, app/website support, direct delivery, payment processing – ran $70.1 million in Q2 2026 against 130.3 million DAUqs, which works out to a direct variable cost of roughly $0.54 per daily active unique for the quarter.

“Cost of revenue consists primarily of payments to third parties for the cost of hosting and supporting our mobile applications and website. In addition, cost of revenue includes expenses directly associated with the delivery of our advertising and other services, including advertising targeting and measurement services, credit card and other transaction processing fees, and payments to our content partners. Cost of revenue also consists of employee-related costs, including salaries, benefits, and stock-based compensation.“ - Q2 10Q

Set that against the revenue each unique throws off and the picture is stark. Reddit maintains an industry-leading gross margin around 90%, which is another way of saying that nearly every dollar an additional user generates flows straight past cost of revenue toward operating expenses and, increasingly, net income. When your marginal user costs you 54 cents to serve and generates multiples of that in revenue, growth isn’t just good for the top line. It’s compounding for the bottom one. That’s the engine behind the incremental margins I keep coming back to.

Where Reddit operates, and what could go wrong there

Geographically, Reddit is still very much a U.S. business wearing an international coat. The U.S. remains the mature market and contributed roughly 79% of total revenue in Q2 2026 – about $638 million of $805 million.

The rest of the world, meanwhile, accounts for 59% of the user base, 77.1 million of 130.3 million DAUqs, but only around 21% of revenue.

Hold those two facts next to each other and you’ve got the entire international thesis in a single sentence: most of the users are already abroad, and almost none of the money is yet.

Focus markets, in the near term at least, are the U.K., France, Spain, Germany, Brazil, and India.

Operating Risks

The operating risks cluster into three I believe:

• The first and largest is Google dependency – roughly half of Reddit’s traffic arrives via Google, which leaves the top of the funnel exposed to search-algorithm changes and AI cannibalization. This is the concern from the drawdown section, and it’s not paranoia; it’s a genuine structural reliance on a company that is also, awkwardly, both a customer and a competitor.

• The second is regulatory in nature. Reddit faces inquiries from bodies including the FTC and the Dutch Data Protection Authority over its content licensing and AI-training practices, and that scrutiny only grows as the licensing business does.

• The third is geopolitical and access-related: the platform isn’t directly accessible in China and runs into intermittent restrictions or censorship elsewhere, capping parts of the global map.

A value chain built by its own users

What ties the operations together is a value chain that barely resembles a normal media company’s, because the most expensive inputs are supplied for free. The raw material – the posts and comments – is generated by Redditors at no cost, and the policing of it is done by 60,000-plus volunteer moderators, which strips out the safety and infrastructure spend that weighs on peers.

Reddit itself supplies the middle of the chain, the gears: the apps and the website that host and organize all that human output into an interest graph of 100,000-plus subreddits.

Distribution is entirely digital, through the iOS and Android apps and Reddit.com for users, and through APIs for the AI partners who license the corpus.

Form, cyclicality, and the machinery of operating leverage

The legal shell is quickly dealt with: Reddit, Inc. was incorporated in Delaware in May 2011, the same year Advance spun it back out. Nothing unusual there, and nothing that changes the analysis.

The more interesting operational questions are about how this business behaves when the economy turns, and how much its margins expand as it grows.

On cyclicality, I want to be honest about the embedded risk, because this is a place where the bull case has to concede ground. Reddit is a cyclical business. Full stop. Around 94% of its revenue is digital advertising, and ad budgets are among the first things companies cut when the macro picture darkens.

Management says as much – global economic worry, higher rates, and geopolitical instability can all push advertisers to pause campaigns or trim spend.

There’s seasonality layered on top, with the fourth quarter running strongest on holiday ad dollars and the first quarter typically softer in sequence.

“Our ARPU reflects the seasonality of our advertising revenue, with the fourth quarter typically being the strongest quarter of each year, especially in the United States, our most developed geography. United States ARPU is higher primarily due to the relative size and maturity of the U.S. digital advertising market, a dynamic we expect will continue for the foreseeable future.“

So anyone modeling Reddit as some recession-proof utility is kidding themselves. When ad markets contract, Reddit’s top line will feel it.

Here’s the distinction that matters, though, and it’s worth borrowing Chris Mittleman’s framing, which I regularly come back to as I’ve internalized the idea, to make it. Mittleman’s point about cyclicals is that he’s willing to tolerate cyclicality, but he won’t invest in cyclicals that burn cash in the downturn. You can accept a dramatic drop in sales during a bad stretch as long as free cash flow can stay positive and the business doesn’t torch capital to survive. That’s the lens I’d apply to Reddit.

The company wasn’t public in 2008, arguably the last true major global economic shock, so we don’t have a clean recessionary track record, and its self-description as having “grown through hard times before” rests partly on the idea that the human need for connection persists in a downturn – true enough, but not a substitute for audited proof.

“Ever-shifting macro environments like these create both challenges and opportunities. We’ve grown through challenging times before—people need connection and information just as much in uncertain times, and we’re well-positioned to meet this moment.

Our unique advantage is that people come to Reddit with intent—they’re not just scrolling, they’re also seeking. They come to Reddit for real opinions from real people. When you ask a question online today— whether it’s about a product, decision, or life choice—you’re not looking for generic answers or sanitized summaries. You’re looking for lived experience and personal recommendations, which is why Reddit is the #1 platform for finding “possible solutions to people’s needs or situation,” and where half of all product conversations online take place.“ - 2025 Q1 letter

What we can say, however, I believe, is that the post-IPO cost structure has moved Reddit firmly out of cash-burn mode. The capital-light nature of the business and 90%-plus gross margins mean that even in a sequentially weaker quarter, the business has levers to stay cash-flow positive.

So a recession would likely hit Reddit’s growth hard while leaving its solvency untouched.

That’s the tolerable kind of cyclicality, not the dangerous kind – provided the cost discipline holds, which management is very vocal about, when it’s actually tested, which it hasn’t been yet, though.

The operating leverage is where this business earns its unusual reputation, and understanding it requires looking at the shape of the cost structure.

Generally speaking, operating leverage refers to the extent to which a company’s costs are fixed versus variable, impacting its profitability with growing sales.

• Companies with high operating leverage have higher fixed costs relative to variable costs, meaning their profits are more sensitive to changes in sales volume.

• Conversely, industries with low operating leverage have a higher proportion of variable costs, making their profits less sensitive to fluctuations in sales volume.

And broadly speaking, variable costs can mainly be found above a firm’s gross income on the income statement, while fixed costs can mostly be found below the gross income line.

For Reddit, too, above the gross-margin line sit the variable costs – cost of revenue – which for Reddit is mostly cloud hosting on AWS and Google Cloud plus some advertising-measurement fees. Because Reddit rents the GPUs rather than building data centers, these scale with usage but stay low, running around 9 to 10% of revenue.

Below the gross-margin line sit the fixed costs, the far larger bucket at more than 80% of adjusted costs, and they’re overwhelmingly headcount – R&D, sales and marketing, and G&A.

When revenue grows, the variable costs barely move as a percentage, and the fixed headcount costs grow far slower than the top line as long as management holds hiring discipline. The result is the revenue-to-cost ratio I covered in Bam #3 in part 1 of this analysis, where the North Star is to grow revenue twice as fast as costs and the early inflection phase ran at 5x.

Play that forward and the margin question gets interesting. Management has set a long-term adjusted EBITDA margin target of 50%, and by Q4 2025 Reddit was already at 45%, which suggests it’s approaching that goal well ahead of the implied schedule.

“The long-term goal is 50%. And so that's what we're focused on right now. And I think most of that will come from just leverage off of incremental revenues. There aren't huge pockets of costs that we're sort of staring at right now and say we could take that out. That would be my take on your question.“ - Call Transcript

I’d treat the 50% target as a floor on ambition rather than a ceiling on possibility. Against a mature comparable like Meta, Reddit’s leverage looks almost absurd, because it hits elite gross margins without any of the multi-billion-dollar infrastructure spend that weighs on companies who own their own data centers.

If you’re trying to picture margins five to ten years out (which I will get into in part 3 of this series - valuation), the honest range is wide and depends heavily on how the international and search build-outs consume investment along the way. But a business with 90%-plus gross margins, low CapEx requirements, and a mostly fixed cost base has every structural ingredient for margins that keep climbing even if the pace of expansion naturally slows.

The direction is clear. The timeline is debatable.

Customers

Reddit has an unique customer, because in a way it has two “customers” which ar eeasy to confuse:

• On one side are the users, a vast global base of consumers who supply the content and the attention.

• On the other are the advertisers and AI developers, the corporations who pay to reach that attention or license that content.

Reddit is (mostly) free to use. And as the say goes, …

If you aren't the customer, you are the product."

The users are the product being sold, and they’re also, in a sense, the “customers” being served.

I’ll spend Part I on the user, since without a loyal user there’s nothing to sell, and turn to the paying side and the economics in Part II.

Part I

Start with who the Reddit user is, because the demographics matter to the investment case more than they might first appear. In the U.S., this is a genuinely attractive audience for anyone with something to sell. As already highlighted, Reddits users, on average, tend to be decently affluent. Around 64% of users sit in households earning $75,000 a year or more.

The gender split runs close to balanced, roughly half male, which is worth noting because Reddit long carried a reputation as a male-skewed site and that’s less true than the stereotype suggests.

On age, the platform skews young but not adolescent, with something like 41% of users between 18 and 34 – old enough to have money, young enough to have decades of purchasing ahead of them.

“According to Comscore data about Redditors in the United States aged 18 and over, for the three months ended December 31, 2023, 41% were between the ages of 18 to 34, 50% were male, and 64% had a household annual income of $75,000 or more.” - S-1

What I also found noteworthy is that “many Redditors are not active on traditional social media platforms” (S-1 filing).

“… according to Comscore data for the three months ended December 31, 2023, of people who visited Reddit in the United States, 32% were not active on Facebook, 37% were not active on Instagram, 73% were not active on Snapchat, 41% were not active on TikTok, and 53% were not active on X.” - S-1

Furthermore, what holds these people on the platform isn’t who they follow. It’s what they care about. Reddit users have self-selected into an interest graph rather than a social graph, and the values underneath that choice tell you why they’re sticky. They often prize anonymity, which is rare among the major platforms and which frees them from the performance and self-display that define Instagram or TikTok.

“Because Reddit is interest-driven versus friends-and-follower driven, and because Redditors have control over their identity, they often seek information on topics important to them that are not visible to social media platforms. For example, a Redditor might privately explore how to cure their acne, but they are unlikely to share this with friends on other platforms publicly. As such, Reddit offers advertisers a chance to reach users that other platforms cannot in the most contextually relevant ways.“ - S-1

Now, I should be careful here, because the interest graph isn't Reddit's alone anymore. Instagram and TikTok have both drifted hard in the same direction – TikTok was arguably built on it, with a "For You" feed driven far more by what you engage with than by who you know, and Instagram has spent years pivoting its feed toward algorithmic recommendation over your actual friends. So the idea that a feed should serve you what you're interested in rather than what your social circle posted is no longer a differentiator on its own.

What still separates Reddit is the structure underneath the graph. On TikTok or Instagram the interest is inferred, reverse-engineered from your behavior by an algorithm guessing at what you'll linger on. On Reddit you declare it, explicitly, by choosing to join r/mechanicalkeyboards or r/personalfinance, and then you talk to other people who declared the same thing. It's an interest graph organized around communities and conversation rather than around a solo feed of content served to you in isolation.

That, plus the anonymity mentioned above, is the real distinction. Reddit prizes pseudonymity in a way that's rare among the major social media platforms, and it frees users from the performance and self-display that still define much of Instagram and TikTok. You're usually not building a personal brand in r/personalfinance. You're just asking a question and getting honest answers from strangers who have no reason to perform for you.

You’re not there to look perfect for people you know. You’re there to talk, candidly, about a thing you’re interested in, whether that’s a mundane hobby or something closer to an existential crisis, with strangers who happen to share the obsession. Reddit shows up in the pivotal moments – the parenting struggle at 2 a.m., the scary health question, the career pivot – where your friends and family simply don’t have the specialized knowledge and a subreddit full of people who’ve experienced exactly that situation does. It has become the default place to get a recommendation you can trust, precisely because the person answering has no obvious incentive to lie, in contrast to a paid influencer or an SEO-optimized review farm. Over 40% of internet users say Reddit recommendations are the single most influential factor in their purchasing decisions, which is a staggering figure when you sit with it.

“Over 40% of Internet users consider recommendations on Reddit the most influential factor in purchasing decisions, surpassing expert reviews, influencer endorsements, and aggregated star ratings. Reddit conversations are where interests meet intent, they inform purchase decisions and offer valuable spaces for brands to connect with people looking for trustworthy opinions.“ - Call Transcript

So if Reddit disappeared, users wouldn’t just lose a website. They’d lose one of the internet’s largest open archives of human knowledge and a space for honest conversation that genuinely doesn’t exist in the same form anywhere else. That’s the mark of a product with a deep hook rather than a shallow one.

Part II – The actual customer who actually pays Reddit

Everything up to here has been about the user, the person who supplies the content and the attention. But the user doesn’t pay Reddit a cent – some do for some perks, but it really doesn’t move the needle for the business.

The customer who writes the big checks is the advertiser, and understanding that base – how it’s structured, how concentrated it is, and how it’s changing – is of course important. Reddit works with thousands of advertisers spanning the full size range, from Fortune 500 giants down to small businesses running a few hundred dollars through the self-serve tool. Historically this was a heavily large-enterprise, heavily U.S. base, and the story of the last couple of years is Reddit deliberately widening it across sizes, industries, and geographies.

Reddit sorts these relationships into three tiers based on how much hand-holding they need, and the shape of that pyramid matters.

• At the top sits Large Customer Sales, the Fortune 500 and AdAge 200 names (in case you didn’t know, Ad Age's annually ranks the largest U.S. advertisers and most-advertised brands) that work through the big creative and media agencies and get a dedicated, consultative Reddit team organized around their vertical. As of late 2023 this group alone drove roughly 65% of direct ad revenue, which tells you how top-heavy the business was not long ago.

• In the middle is the mid-market and SMB tier, generally companies spending north of $10 million a year, running their own campaigns with light guidance from Reddit’s ops teams – its revenue was doubling year over year by mid-2026 (“We saw strength across our sales channels, including large customers and scaled. Our scaled channel revenue, which includes mid-market and SMBs, doubled year-over-year.”).

• And at the base is self-service, the smaller businesses using the automated Ads Manager with no salesperson involved at all. That bottom tier is the one I’d watch most closely for the health of the platform, because it’s the scaled, low-touch channel that lets an ad business broaden beyond a handful of whales.

The industry mix is still concentrated in the places you’d expect Reddit to work, the endemic verticals where its communities are “deep.” As of late 2023, more than half of ad revenue came from just four buckets:

• technology and communications,

• business and finance,

• electronics, and

• media and entertainment.

Recently, growth, encouragingly, is coming from newer territory – retail, travel, pharma, and automotive are all migrating budget onto the platform.

On concentration, the trend is genuinely reassuring even if the starting point wasn’t. Reddit’s advertiser count grew more than 70% year over year by mid-2026, and the reliance on the biggest players is steadily easing. The top 10 advertisers accounted for 21% of total revenue in 2025, down from 25% in 2024 and 26% in 2023. Management has noted that no single industry made up more than 15% of revenue as of late 2024, and no individual customer exceeded 10% in any of the last three years. That’s the direction you want.

I won’t leave this section without the risks, because the advertiser base carries some structural fragilities that are easy to overlook when the growth looks this good.

• The first is baked into the entire digital-ad industry: advertisers have no long-term commitments and can cut or cancel spend whenever they like, which is precisely why a recession hits a business like this so quickly.

• The second is agency dependency. A lot of those large customers buy through a handful of enormous agency holding companies, so a soured relationship with one of those intermediaries could dent revenue well out of proportion to any single client leaving.

• And the third loops straight back to the international thesis: only a small % of ad revenue came from outside the U.S., even though more than half the users are international. It’s the runway I described in the international pillar, but it’s also a reminder that today’s revenue rests heavily on one country’s ad market, with all the concentration risk that implies.

Arguably, there’s a third distinct end consumers: AI developers. While users provide the “raw material” and advertisers have historically been the primary source of revenue, management increasingly views data licensing partners as a fundamental pillar of Reddit’s future business model. The most prominent customers are Google and OpenAI, who use Reddit’s 20-year archive for training and grounding their Large Language Models (LLMs). Neither Anthropic nor Perplexity are commercial data-licensing customers of Reddit. In fact, Reddit has sued both companies over alleged unauthorized web scraping.

“In addition, we face competition from large language models (“LLMs”) and other AI models that retrieve and synthesize information, such as those built by Google, Meta, OpenAI, and Anthropic; Redditors may choose to find information using AI tools, which in some cases may have been trained using Reddit content, instead of visiting Reddit directly. While we have made, and expect to continue to make, significant investments to integrate AI, including generative AI, into our platform, AI technologies are rapidly evolving and there can be no guarantee that our products and services will remain competitive as new AI technologies are developed, adopted, and integrated.“ - 10-K

Companies like Sprinklr, Meltwater, and Cision license the Data API to help their corporate clients uncover brand insights and monitor global trends. A newer vertical includes the Intercontinental Exchange (ICE), which uses Reddit data to develop analytics products that help investors capture market sentiment from communities like r/wallstreetbets.

Do people love Reddit, or just use it?

There’s a difference between a product people tolerate and one they’re attached to. Reddit clears the bar for attachment, and it does so in a way I find very convincing. Users say “I love Reddit” unprompted. As already highlighted, usage deepens with tenure. A new logged-in user typically starts at around 20 minutes a day. Someone who’s been on the platform for more than seven years is spending 45-plus minutes a day.

For Reddit, loyalty seems to compound. The longer you stay, the more the place has wrapped itself around your specific interests, and the harder it becomes to leave.

Reddit covers every niche imaginable, which means it grows with you through each life stage. The subreddits you needed at 22 aren’t the ones you need at 37, but they all appear on the same platform, so the platform never ages out of relevance the way a single-purpose app does (you “grow out of” Snapchat as you transition from adolescence into adulthood, for instance).

Some users describe themselves, half-jokingly, as chronically online or addicted, and while I’d treat that language carefully, the underlying point holds: there are switching costs. They aren’t financial in nature. It’s rather the accumulated relevance of a feed and a set of communities that took years to assemble. And the loyalty runs deep enough that users and volunteer moderators feel genuine ownership over the platform, which is exactly why the company handed them a slice of the IPO.

On Retention

Management has said, and I think correctly, that new-user retention is the single best measurement of product quality. It’s a cleaner signal than raw user growth, because growth can be bought with marketing while retention can only be earned by the product actually being good. So the retention trajectory is where I’d look to falsify or confirm the “people love this” claim, and lately it’s been pointing the right way. In mid-2026, Reddit reported that new-app-user retention was up 50% year over year on a relative basis, which the company flagged as an important sign that product improvements are making the platform stickier.

Search turns out to be a retention lever, which connects a few threads from earlier. Users who perform any search on Reddit show 30% higher week-one retention. That’s not a coincidence – search is how a new user discovers that Reddit has something for their specific obsession, and once they find that first relevant community, the hook sets.

There’s a quality-of-user point layered on top: direct app users and logged-in users are worth multiples more than drive-by search traffic, because they see more impressions and engage more deeply.

Reddit’s user-marketing spend is conservative, typically a low-to-mid single-digit percentage of revenue, and management evaluates it with a straightforward cash model that targets a quick payback. Low acquisition spend paired with rising retention is the combination you want as an investor.

“This quarter, we're kind of low mid-single digits percent of revenue. To be honest with you, Tom, we don't have sort of a pinpoint number that we're going after. We're really, at this point, looking at that quality user. We're looking at the ROI and we're looking at the retention curves of people that we're bringing on to the platform. That's really what we're focused on.“ - Call Transcript

From a customer lifetime value framework POV, Reddit looks exceptional: Low CAC, high margin per user, high retention, and lengthening customer longevity. When acquisition is cheap and the customer stays longer and monetizes more every year they’re around, that’s a fantastic position to be in.

Simplicity & Industry Analysis

A pain point solved by a business only becomes incredibly valuable if it’s hard for someone else to solve, so it’s worth being clear-eyed about who Reddit competes with.

The honest answer is that it competes on two fronts at once:

• For information and recommendations, it’s up against Google, Wikipedia, and increasingly (!) the AI chatbots like ChatGPT and Gemini.

• For entertainment and time, it’s up against Meta, TikTok, and YouTube. That’s a fearsome set of competitors on paper and in practice. We all know how incredibly addictive (and likely socially harmful) their algorithms are. Beyond traditional social networks, Reddit also vies with X (formerly Twitter) for real-time commentary, Discord for niche community hangouts, and platforms like Twitch or Snap for mobile-first engagement. Ultimately, Reddit isn't just competing against other forums—it's fighting any app capable of capturing five minutes of idle human attention.

“We also compete to attract and retain Redditors’ attention on the basis of our content and Redditor experiences with our platform and face significant competition for prospective users, both domestically and internationally. We compete against many companies that provide content and communications services to online users, including Google (including YouTube, Search, Maps, and Shopping), Meta (including Facebook, Instagram, Threads, and WhatsApp), Wikipedia, Snap, X, Pinterest, TikTok, Roblox, Discord, and Twitch, and which offer a variety of internet- and mobile device-based products, services, and content. Many of these companies have greater financial resources and substantially larger user bases than Reddit. Our competitors may draw users towards their products or services and away from ours. This could decrease the growth, engagement, or retention of Redditors, which, in turn, would negatively affect our business. In addition, we face competition from large language models (“LLMs”) and other AI models that retrieve and synthesize information, such as those built by Google, Meta, OpenAI, and Anthropic; Redditors may choose to find information using AI tools, which in some cases may have been trained using Reddit content, instead of visiting Reddit directly. While we have made, and expect to continue to make, significant investments to integrate AI, including generative AI, into our platform, AI technologies are rapidly evolving and there can be no guarantee that our products and services will remain competitive as new AI technologies are developed, adopted, and integrated.” - 10-K

I don’t want to soft-pedal the competition, because it’s fierce and Reddit is not the gorilla. Arguably, Reddit is the challenger. Meta is the dominant force in the room, with deeper user data and best-in-class ad-targeting ROI that make it a far easier choice for most small and local businesses, who can lean on Meta’s measurable and granular geo-targeting in a way Reddit can’t yet match.

Google is the more complicated rival, because it’s simultaneously a major partner and an existential threat, since roughly half of Reddit’s traffic is search-dependent, which hands Google enormous leverage over Reddit’s top of funnel through nothing more than an algorithm tweak or the continued rise of AI Overviews.

And then there are the benchmark peers, Pinterest and Snap, less direct competitors than yardsticks the market uses to argue about Reddit’s ARPU ceiling and its multiple.

But the structure of Reddit’s product does make it genuinely awkward to replace. The entertainment platforms are mostly broadcast systems built on following – you watch what creators you follow put out, and the platform optimizes for self-display and passive consumption. Reddit optimizes for participation and belonging, which is a different psychological need and one that a follower-driven feed doesn’t scratch. You can’t easily bolt a Reddit onto Instagram, because the whole point of Reddit is that it isn’t Instagram.

And on the information side, the AI chatbots are, ironically, dependent on Reddit rather than a clean substitute for it, since they source a chunk of their most-cited answers from Reddit threads in the first place. There’s a real tension there, which I’ve flagged before and will keep flagging: those same chatbots could also intercept the user before they ever reach the thread. So I wouldn’t call the “moat” unbreachable. I’d call it structurally distinct in a way that has, so far, let Reddit outlast every direct forum competitor that came for it, from Yahoo Answers to Quora.

The graveyard of dead Q&A sites is itself a piece of evidence.

The market-share picture makes the challenge concrete. Google and Meta together hoover up somewhere between half and 70% of all digital ad spend, which leaves everyone else fighting over the remainder.

Reddit’s position within that remainder is improving, though, and one figure caught my eye: its median wallet share inside its own advertiser base roughly doubled to around 9% within twelve months. So the advertisers who are already on Reddit are handing it a bigger slice of their budgets, which is the pattern you’d want from a challenger that’s proving itself rather than plateauing. I’d file this as a crowded, highly competitive market that I’d normally prefer to avoid, softened by the fact that Reddit isn’t really competing head-to-head for the same inventory. It’s selling something the giants structurally can’t, which is why it survives in their shadow at all.

Is this a good industry, or a good business trapped in a hard one?

Reddit sits at the intersection of two industries. One is digital advertising, which is competitive, cyclical, and dominated by two giants; but at the same time of very high quality.

The other is data licensing for AI, which barely existed three years ago.

What I can say is that Reddit occupies a genuinely attractive niche inside an otherwise brutal industry. The evidence for the niche being attractive is in the margins and the pricing. Reddit runs gross margins north of 90%, hitting 91.5% in early 2026, which is a software-like profile that most advertising businesses never approach, never even dare to dream of, and it’s the thing Huffman means when he calls the financial model one-of-one.

There’s evident pricing power too, though it’s uneven in a telling way. Generic advertisers, the CPG crowd, are paying only about 3% more year over year, which is barely keeping pace. Financial-services advertisers, on the other hand, are bidding Reddit’s prices up 25% annually because the intent in those communities converts into measurable outcomes. Read those two numbers side by side: the pricing power is real, but it concentrates in the verticals where declared intent pays off.

The differentiation itself is structural, rooted in the interest graph rather than the social graph, and that is what lets Reddit capture users at the moment they’ve declared what they want.

The niche economics are excellent while the surrounding industry stays brutal, and any honest read of the business has to hold both of those at the same time.

A twenty-year-old activity dressed in changing technology

The technology layer Reddit operates on changes fast. It went from basic web links to mobile apps to, now, AI-integrated everything, and rapid change is exactly the thing that should scare patient investors, because businesses that start doing lots of new things have a way of doing them badly. I take that concern seriously here, and I won’t pretend the roadmap from the product section, with its half-dozen new initiatives, is the picture of a company sticking to its knitting.

Here’s the counterweight, though, and it’s the reason I’m not more worried than I am. The technology around Reddit keeps changing while the actual activity inside it has stayed almost eerily constant for two decades: people talking to other people, in communities, about things they care about.

That is what Reddit was in 2005 and what Reddit is in 2026.

What changed was the wrapper, the apps and the monetization, not the human behavior at the center.

When I ask myself whether I can state with near certainty that this business and its core product won’t be obsolete in ten or twenty years, I’d probably still say “no,” though – unfortunately.

At the same time, the odds of Reddit still being around, most likely in a different shape and form, aren’t too slim either. People wanted candid advice from strangers before the internet, they’ll want it after the next platform shift, and Reddit has already survived the arrival of smartphones, the entire social-media era, and a global pandemic without abandoning its forum roots.

Betting on Reddit is closer to betting on the continuation of past behavior than it looks at first glance, even if the wrapper keeps getting redesigned.

Which way do the structural winds blow?

Weighing the long-term forces, I think the tailwinds are stronger than the headwinds, but the biggest headwind is genuinely dangerous.

On the tailwind side, the flood of “AI slop” makes Reddit’s archive of authentic human conversation more valuable the more the rest of the web degrades. You can frame this through the dead internet theory, the idea that a growing share of online content is bot-generated noise, against which human ground truth becomes scarce and prized. Social search is a rising behavior, and Reddit is the single most-cited domain by AI models across the internet, which positions it well as discovery shifts away from the old blue links.

Those are powerful, durable forces pushing in Reddit’s favor.

The headwind is the mirror image of that same trend, which is what makes it so hard to dismiss. AI cannibalization is the central risk to the whole story. If users increasingly get their Reddit-sourced answers straight from a chatbot or an AI Overview without ever clicking through to Reddit, the company loses the referral traffic that feeds its logged-out tourist audience, and it loses it precisely because its own data made the AI answer good enough to end the search.

The same force that makes Reddit’s data valuable to license could hollow out the traffic that makes Reddit valuable to advertise on.

I don’t think that tension is resolved yet, in either direction, and how it resolves is arguably the single most important open question in this investment.

TL;DR

I'll use a TL;DR here, which I'm told is deeply ingrained in Reddit's own culture – the "too long; didn't read" summary that a kind stranger drops at the bottom of a wall of text for everyone scrolling past.

Fitting, given how much text this series has already asked of you.

So, if I had to explain this company and its business model to my parents over dinner, I'd put it like this:

Reddit is a 20-year-old digital “city” built on authentic human conversation, and that conversation has become essential raw material for the AI era while also drawing an unusually high-intent, affluent audience that advertisers increasingly want to reach. It's a rare business that pairs software-like gross margins above 90% with 60%-plus revenue growth, because it's only now starting to monetize an audience it spent two decades building. The bet is simply that Reddit closes the monetization gap with giants like Meta while remaining the internet's primary source of genuine human perspective – and the main thing that could break the bet is AI intercepting its users before they ever arrive.

And that, my friends … that's the business of Reddit.

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If you've made it through both parts (make sure to not miss part 1), you now have the same foundation I do: a 20-year-old platform sitting on an irreplaceable archive, a genuine inflection in profitability, an interest-and-intent model that advertisers are still learning to value properly, and a fistful of real risks – the U.S. user ceiling, the Google dependency, the AI-cannibalization tension – that I've tried not to wave away.

What I've deliberately held back so far is the part every investor actually wants to argue about.

Is it a buy?

I don't yet have an answer, and I've resisted pretending to have one, because a hypothesis this dependent on a handful of swing variables deserves to be modeled properly rather than eyeballed.

That's what the next part is for. In Part 3, I'll turn from the business (which is of exceptional quality as I concluded) to the investment, and I'll work through the things that decide whether the price makes sense: management's tenure, compensation, and whether they have real skin in the game, along with any insider buying worth noting; the balance sheet; and then the heart of it, valuation. I'll lay out the growth drivers explicitly – whether the ARPU gap can realistically close at something like a Pinterest – and take a view on where steady-state margins actually settle once the easy leverage is spent.

Crucially, I'll try to anchor my inside view to the outside one with a base-rate analysis, because it's dangerously easy to fall in love with a specific narrative and forget what usually happens to companies that looked like this. Then I'll show you my own model, assumptions exposed for you to disagree with. And I'll close with a more speculative thought I keep turning over, which is whether a certain company might end up wanting to own this thing outright.

That's the plan. See you in Part 3!

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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.

Following 13 years at Platinum Asset Management, Jamie launched Senjin Capital in 2024 with a clear mandate – buying quality, asset-rich Japanese small caps at 30 cents on the dollar and engaging constructively with management to unlock trapped balance sheet cash.

We take a deep dive into the real drivers behind Japan’s market evolution, looking past high-level headlines to explore:

• The $300M Sweet Spot: Why over 2,000 Japanese micro/small-cap companies lack meaningful analyst coverage, and how that structural neglect creates Senjin’s core edge.

• Setting up a Fund: Jamie detailed the operational challenges of setting up an activist fund in Japan, the process of identifying and engaging with target companies, and the cultural and financial literacy aspects of working with Japanese management teams.

• Governance Reform vs. Cosmetic Compliance: We discussed the progress of governance reforms in Japan, the differences between large and small caps, and the competitive landscape for activist investing. How to distinguish between genuine capital allocation shifts and superficial disclosures as the Tokyo Stock Exchange pushes for higher capital efficiency.

• Tactical Activism: What constructive, active engagement actually looks like in practice.

• Macro Dynamics & The Yen: Jamie’s take on central bank policy, unwinding cross-shareholdings, and why currency fluctuations play a distinct role depending on export versus domestic exposure. Jamie shared his views on the yen’s undervaluation, the impact of currency movements on different types of businesses, and briefly compared the situation in Japan to Korea.

Whether you are an institutional allocation specialist or looking to understand why global investors are re-evaluating Japanese equities, this conversation offers a pragmatic, ground-level blueprint for value investing in Japan today.

It carries the hypothesis, the business, the competitive position, the valuation, and the case against, laid out briefly so you can get a grasp of the key thesis, even on a day when you don’t have an hour or two for the full piece.

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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.

Say the name at a dinner party, and you'll get a knowing smirk, a GameStop joke, maybe a comment about the weird corners of the internet. Say it to a value investor and watch them wince at “high price.” Say it to a growth investor and they'll mutter something about Google killing the traffic.

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Everybody knows Reddit. Almost nobody has bothered to actually look under the hood, because the reputation does the thinking for them, and the reputation says meme stock, too expensive, too strange, move along.

Psychologists call this the availability heuristic – in investing, a mental shortcut where people judge a business based on whatever vivid stories, recent headlines, or cultural stereotypes easily come to mind, rather than doing the hard work of analyzing the actual data and qualitative insights.

It takes deliberate cognitive effort to look past the noisy, available anecdotes and evaluate a company on its cold, hard fundamentals, so most people simply take the path of least resistance and let the popular consensus do the thinking for them.

I was, at first, shrugging off Reddit too. Then I looked, and what I found was so far from the caricature that I plan to share my fingins and thoughts in a deep dive series on this fascinating company.

Let me show you what changed my mind, starting with the most recent quarter, because it captures the whole paradox in a single afternoon of trading.

Reddit reported earnings on July 30, 2026, and here’s what happened. Revenue grew 61% year over year to $805 million (beating the $730 million estimate), the eighth straight quarter above 60%.

Earnings per share came in at $1.25 against expectations closer to $0.95. Next quarter’s guidance sailed past what analysts were modeling. Net income more than doubled. Free cash flow landed at $261 million. By almost any measure, it was a blowout, the kind of print a growth investor daydreams about.

The stock fell 21%.

A company beat on revenue, beat on earnings, beat on guidance, doubled its profit, and the market took a fifth of its value off in a session.

What spooked everyone wasn’t the money. It was a single sequential number: U.S. daily active users ticked down from 53.5 million to 53.2 million, and management described its search referral traffic as choppy and hard to forecast, particularly late in the quarter.

That’s it.

A rounding-error dip in domestic users, blamed on volatility in how Google and AI Overviews funnel people to the site, was enough to erase a quarter that was otherwise close to flawless.

Pull back and the pattern is even starker. As I write this, Reddit sits more than 44% below its peak, and the drawdown chart looks less like a stock and more like a seismograph.

This is a name that has fallen 50-plus percent from a high, recovered, and done it again, more than once, inside two years of being public.

Again, as alluded to above, my honest starting point, and I suspect it’s yours too, was a shrug.

Reddit? The GameStop forum? The meme-stock poster child trading at some absurd multiple?

I’m a value-leaning investor by temperament, no great Reddit user myself, and every reflex I’ve built over the years told me to file this in the “too hard, too hot, too expensive” drawer and move on.

Die-hard value types laugh at the premium multiple. Growth investors have half-convinced themselves that Google has quietly put a lid on the whole story. It seems neither camp seems to actually want the stock.

And that, more than anything, is what made me look closer.

When a genuinely high-quality business gets orphaned by both tribes at once, and then hands you a 44% drawdown on top, my curiosity tends to override my reflexes.

Moreover, Advertising businesses, and digital ones especially, are supposed to be right up my alley. I owed it a proper look before dismissing it.

What I found is a business that is far, far better than its reputation, and a valuation story that is a lot more subtle than the headline multiples suggest.

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Because here’s the thing the “it trades at 35x earnings” crowd misses: Reddit only just switched the monetization on.

This is a 20-year-old platform that spent almost its entire life not really trying to make money, turned profitable for the first time in late 2024, and is now sitting on levers it has barely touched. It runs a 91% gross margin business.

91%!

It’s the seventh most visited website on earth, built almost entirely on content its users generate for free and moderated for free by tens of thousands of volunteers, which is the same reason its economics resemble YouTube’s more than any traditional media company’s.

Out of 300-plus public tech companies, it’s arguably the only one combining 60%-plus revenue growth, 90%-plus gross margins, and real free cash flow with essentially no capital intensity. Reddit itself hence refers to it as a one of a kind model.

Trailing multiples on a business whose earnings power is still mostly ahead of it will lie to you.

That’s one of the central puzzles this series is going to work through.

There’s another reason I got interested … Reddit has in a way become the internet’s repository of ground truth. Siyu Li, an investor I respect for his analytical rigor and the kind of names he gravitates toward, put it better than I could (see tweet below), and he too seems to have taken an interest around this drawdown. He described being at Lollapalooza in Chicago and wanting to know which sets people actually loved. Where do you go for that? Reddit!

Not a magazine, not an AI summary, not a Google blue link. A thread of real humans saying what they really thought, in real time. As Siyu put it, Reddit often holds the ground truth to people’s real-time opinion on sports, music, restaurants, everything, and increasingly everywhere globally, and there isn’t even a close second competitor.

He floated an analogy too: that this unique position could earn Reddit serious bargaining power, something like Airbnb’s relationship to Google, or WeChat’s to Apple. People predict the future by pattern-matching to the past, he noted, and in this case Reddit might just be the exception. That’s roughly where I’ve landed too. As the open web fills with synthetic AI slop, the one thing a language model can’t fake is what it’s actually like to have done the thing, and Reddit is where that lived experience is shared, expressed, and discussed.

It’s now the single most-cited domain by AI models across the entire internet.

“In fact, 80% of users in a recent survey [said] that they believe some questions can only be answered by humans as opposed to AI-generated summaries. For LLM and AI search engines, these conversations and the knowledge they create are essential for training. Platforms like Reddit where people discuss every aspect of life from the trivial to the transformative of a backbone of building AI that actually works. That's why Reddit is the #1 most cited domain for AI across all models per data collected by Profound. In an automated world that depends on human knowledge, we view Reddit as one of the most important and differentiated data sources.“ - Call Transcript

Management likes to say there’s no artificial intelligence without actual intelligence, and however self-serving that sounds, no major LLM has been built without training heavily on Reddit’s 26 billion posts and comments.

Every month, its communities generate the equivalent of all of Wikipedia in new material.

Enough for the intro. I will presumably split this analysis into four parts.

• First, the heart of the bull case, the five pillars of the investment hypothesis, delivered in the “Bam Bam Bam Bam Bam” style I borrow from Bill Miller (I’m aiming for about 5,000-8,000 words; call me out in the comments below this post if I failed; update: this piece ended up with 15,000 words of valuable insights (sorry 😉)).

• Second, a comprehensive walk-through of the business, how Reddit actually works and makes money, unit economics, etc., etc.

• Third, valuation, where I’ll try to make sense of those multiples and put a number on it.

• Fourth, the entire analysis distilled into a visual slide deck for those who’d rather see it than read it.

Let’s get into it; this will be fun, I promise.

What this deep dive series covers:

• The five-part bull case (”Bam Bam Bam Bam Bam”)

• 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 business itself

• Unit economics analysis

• The customer

• Legal structure, cyclicality, and operating leverage

• 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”-Hypothesis

As always, I will start with Bill Miller who once made a point about pitching stocks that has stuck with me ever since I first heard it, and it shapes how I approach every write-up on this blog. Portfolio managers, he explained, have ultra-short attention spans. Miller’s advice for what to say in that window was refreshingly blunt. You walk in and you say something like, “I want to talk to you about Homestore. It’s at $2.25. The 52-week range is $2 to $4 and the all-time high was $100 back in 2000. I think it’s a buy for five reasons: one, bam; two, bam; three, bam; four, bam; five, bam. The stock trades at $2 and change. I think it’s worth $6 or $8. Here’s why. And here are the risks.”

That’s the spirit I want to bring to Reddit.

For Reddit (Ticker: ), the pitch centers on a company that has spent 20 years building a singular “city” of human knowledge and is now, for the first time, turning on the monetization engines. Reddit sits at a historic inflection point in its business model, where two decades of accumulated human data is finally meeting a sophisticated ad-tech stack and a high-margin licensing market. You should care because Reddit is a “one-of-one” business. It pairs 60%-plus revenue growth with 90%-plus gross margins and inflecting free cash flow, and yet the market stays skeptical about whether its user base growth is durable over the long haul.

Right now the market treats Reddit as a risky social media play, or as a platform dangerously hooked on Google traffic that AI will eventually cannibalize. What that view misses is that Reddit is a utility for human perspective, and it becomes more scarce and more valuable precisely as the rest of the web fills up with synthetic AI slop.

If Reddit can fold its conversational data into its own search product while continuing to close the ARPU gap with its peers, it graduates from meme-stock territory into something closer to a foundational internet utility with defensive, recurring cash flows.

Also, I’m deliberately calling this an investment hypothesis rather than a thesis. As my regular readers will know, a thesis tends to be a statement of belief, and belief has a way of nudging investors toward information that validates the view they already hold. A hypothesis is different in that it’s more of a proposition you actively try to falsify. That’s the attitude I want to adopt throughout this piece.

Bam #1: Data is “oil” of the AI era & Reddit is sitting on the ultimate AI oil well

If you want to understand why Reddit may be interesting right now, start with what it actually owns: The company sits on the internet’s largest archive of authentic, human-to-human conversation, and that archive has become foundational raw material for training nearly every major large language model on earth.

Where most social platforms live off high-velocity scrolling (aka doomscrolling with the compulsive consumption of often negative or emotionally charged content) and interruptive ads – the precise ad load on Instagram of course varies by individual user, but across the main placements (Feed, Stories, and Reels) the average user sees one ad for every 3 to 5 organic posts (god, I hate this experience) –, Reddit spent two decades accumulating something different: a structured record of human experience that AI developers now can’t build without (“Reddit’s content is in demand, and it’s not commodity content“ - call comment).

And for the first time, Reddit is charging for access.

Let me start with scale, because the numbers here are genuinely hard to wrap your head around:

• As of early 2026, Reddit’s corpus runs to more than 26 billion posts and comments.

• Every month, Reddit’s 100,000+ active communities generate the equivalent of Wikipedia’s entire content library in new, human-written information.

That’s not a static dataset gathering dust. It’s a constantly regenerating feed of how people actually talk, argue, recommend, and reconsider.

LLM developers reach for that data at every layer of the AI stack.

• They use it in pre-training to build the initial world model.

• They use it in post-training to teach models how to speak like an ordinary human rather than a corporate press release.

• They use it for grounding, so that answers reflect what real people think and experience rather than what a model hallucinates.

• And they use it as a live search index, pulling up-to-the-minute information on sports, news, and fast-moving trends.

Four distinct jobs, one source.

“And so Reddit is used in pretraining, right, create the whole model. It’s used in post-training, like teach the model how to speak like a normal person. It’s used in grounding, like what do people actually think. And then on top of that, these models are running on a live search index of like what’s going on, on Reddit. So it’s essential for the entire stack.“ - Call Transcript

This is where management’s favorite line comes in, and I think it’s more than a slogan:

“There is no artificial intelligence without actual intelligence”

…, they argue, and the actual intelligence is sourced from Reddit.

The logic holds up when you look at where the open web is heading. As more of it fills with sanitized, synthesized, bot-generated filler – the stuff people have started calling “AI slop” – authentic human perspective grows more scarce and, by simple economics, more valuable.

Reddit is currently the single most cited domain on the entire internet across all AI models.

Think about that for a second! When an AI hands you a recommendation or a summary, it’s more likely to be drawing from a Reddit thread than from any other source on the web.

“I think one of the dynamics we’re seeing in the modern Internet is the more it becomes sanitized and summarized and optimized for attention by AI, the more that people crave the human, the human information that’s both AI that crave it and also the Internet consumer or people in general that crave it. And that’s our business … those human connection and conversations.“ - Call Transcript

There’s a reason for that. For a whole category of questions – which bike helmet should I buy, how do I deal with a difficult kid, is this movie worth watching in cinema – there is no clean objective answer. People want the messy, contradictory, honest spread of viewpoints, shared by actual humans, that you only get from a real discussion, and so, increasingly, do the models trained to answer on their behalf.

“So both AIs and Internet consumers love Reddit content. This is because that basically human verification of what AI is telling people is really important. At the end of the day, you can get a surface level answer from AI, but you need the context. For many questions, there isn’t an answer. There are multiple perspectives describing that answer and multiple reasons why different parts of that answer might be relevant to you or not. For example, take a simple question. What movie should I watch tonight?“ - Call Transcript

Recently, Reddit has flipped this asset from a free public API into a high-margin, recurring revenue business (contributing around 5-6% of revenue in recent quarters), reported inside the “other revenue” line. That line grew from $15.2 million in 2023 to $140 million in 2025 ($153.5 million over the LTM).

“Other Revenue: In our content licensing arrangements, we provide customers with the right to access content from our platform over the contractual period. The transaction price in content licensing arrangements is generally a fixed fee or usage-based fee. We recognize content licensing revenue as our content partners consume and benefit from their use of the licensed content, which is generally ratably over the license period. Revenue from products sold directly to users, including Reddit Premium and Reddit Gold, was not material for the periods presented.“ - 10-K

For context on the underlying scale, the licensed archive exceeds two billion posts and 22 billion comments, and importantly, it also refreshes constantly rather than aging out. The anchor partnerships are with Google and OpenAI, structured as deep, multi-year deals spanning model training, post-training, and search grounding.

Context on the deals:

• In February 2024, Reddit signed an AI licensing deal with Google worth approximately $60 million annually. The agreement grants Google real-time access to Reddit’s Data API, allowing it to train its Gemini AI models on vast streams of human-generated conversational data. Beyond AI training, the deal deepened their cloud infrastructure collaboration via Google’s Vertex AI and improved how Reddit content is organized and displayed directly within Google Search results.

• In May 2024, OpenAI struck a similar licensing and technology deal with Reddit, giving ChatGPT real-time access to Reddit posts and discussions via the Data API. This allows OpenAI to incorporate fresh user conversations into its models and directly showcase Reddit content to ChatGPT users. In return, OpenAI became a Reddit advertising partner and provided Reddit with access to its AI models to build enhanced user and moderator tools, such as automated thread summarization and moderation assistance.

Beyond the marquee names, Reddit has pushed into verticals. In 2024, it partnered with Intercontinental Exchange to build data products for the financial industry, mining real-time sentiment from communities like r/WallStreetBets to feed insights to traders.

It also runs agreements with social-listening and enterprise firms like Meltwater, Cision, and Sprinklr. The marketplace is broadening, not narrowing.

“We continue to address the data licensing opportunity and are in contact with potential partners In Q3, we entered into a new partnership with Meltwater, a media and social intelligence company Meltwater accesses Reddit’s content through our data API, which allows their customers to uncover brand insights, monitor industry trends, and tap into the discussions happening on the platform“ - 2024 Q3 letter to shareholders

What makes this a genuinely attractive business, rather than just a novel one, is the economics. The data already exists on the platform. Reddit isn’t manufacturing anything incremental to license it, so the marginal margin is close to pristine, and this line is a meaningful contributor to the company’s 90%-plus gross margins.

Then there’s the pricing, which is where it gets a little wild. According to expert-network interviews (I’ve read about this second-hand so best to treat this data point with some caution), standard API data might run around $0.24 per 1,000 calls, while Reddit’s licensing deals reportedly command a 50x to 500x markup. That premium isn’t really about the raw bytes. The argument is that Reddit isn’t only selling data – it’s selling legal immunity, an exclusive and litigation-friendly path to the world’s largest public archive of human conversation, organized and delivered through a clean API.

In a world where scraping is increasingly contested in court, a signed license has real value on its own.

The pricing model itself looks poised to evolve, and this is worth watching closely. Early deals leaned on flat fees (see added context on the OpenAI and Google deal above). Reddit is now signaling a shift toward usage-based, metered pricing, which would tie revenue to how much data models actually draw and add a variable kicker linked to how often Reddit content gets synthesized into products like Google’s AI Overviews.

• Google Deal: Reached its initial expiration/renegotiation window in mid-2026. Discussions around renewing or extending the terms are currently ongoing, with reports indicating Reddit executives are pushing for usage-based pricing models rather than flat annual fees.

• OpenAI Deal: Reaches its initial renewal window later in 2026. Because it was signed shortly after Google’s deal, renegotiations for its next multi-year phase follow a similar timeline.

If that transition materializes, revenue stops being a fixed high-margin annual check and starts scaling with the actual usage of Reddit’s intelligence across the AI ecosystem. Broadly speaking, that’s a better place to be in.

None of this comes without a fight, and the value of the asset is exactly what invites the trouble. Reddit has had to lean hard into what you might call API defense, blocking crawlers and search engines that won’t be transparent about how they use platform content, and it has commenced litigation against entities that built LLMs on Reddit data without a license.

“In terms of third-party search, the ecosystem is evolving with search, summarization, and training blending. We are seeking the right balance between openness and protecting our users and platform. Our partnerships with Google and OpenAI illustrate how commercial agreements aligned with our content policies can be mutually beneficial. They help people discover communities on Reddit while safeguarding our users’ information. We’ve restricted access where transparency is lacking in how Reddit content is utilized. The internet and search benefit from Reddit’s content, and we are open to finding solutions that serve our users, Reddit, and the broader internet community.“ - 2024 Q2 letter

There’s a regulatory dimension too. In March 2024, the FTC opened a non-public inquiry into Reddit’s sale and licensing of user-generated content for AI training – a reminder that this business operates on genuinely new legal terrain, where the rules are still being written.

“In addition, we are in the early stages of our content licensing efforts and are exploring content licensing opportunities where we believe the opportunity does not conflict with our values and the rights of Redditors. These programs may subject us to evolving approaches to the regulation of this data and implicate complex and developing data privacy and data protection, misappropriation, and intellectual property laws, rules, and regulations. Given the novel nature of these technologies and commercial arrangements, we have received and expect to continue to receive inquiries regarding our content licensing efforts from regulators. For example, in March 2024, we received a letter from the FTC advising us that the FTC’s staff is conducting a non-public inquiry focused on our sale, licensing, or sharing of user-generated content with third parties to train AI models. The Dutch data protection authority, the Autoriteit Persoonsgegevens, has also inquired about our content licensing efforts. Given the novel nature of these technologies and commercial arrangements, we are not surprised that regulators have expressed interest in this area. We do not believe that we have engaged in any unfair or deceptive trade practice, we expect to receive continued regulatory interest in our plans, and any regulatory engagement can be lengthy, unpredictable and may cause us to incur substantial costs. It is possible for any regulatory engagement to result in reputational harm or fines, cause us to discontinue or modify our products, services, features, or functionalities, require us to change our policies or practices, divert management and other resources from our business, or otherwise adversely impact our business, results of operations, financial condition, and prospects.“ - 2025 Q3 Results

Management, for its part, frames the partnerships as a flywheel rather than a pure cash grab, using partner resources and infrastructure to sharpen its own machine translation and search capabilities.

“And second, on data licensing, things other than dollars. But, obviously, it’s citations, it’s mind share. It’s just general partnership. Like these companies have the data centers, the foundational models. And so our partnerships with all of these companies are multifaceted.

And so there’s a lot we can do in terms of beyond just the dollars. It’s how can these relationships help Reddit achieve its mission. So bringing in new users, advancing our own AI technology. So things like the machine translation, the LLM powered onboarding, all of the safety things, all of these things are kind of part of what we get through these relationships, which is why they’re so meaningful to us beyond just the core dev relationship or the business relationship.“ - Call Transcript

So the same deals that generate revenue are meant to upgrade the product.

We’ll test that claim later.

How big could this line of business get?

Naturally, I was wondering how big this revenue stream could realistically get?

Start with what's contracted, because the base is smaller and less mysterious than the headlines imply. In January 2024 Reddit signed licensing deals worth an aggregate $203 million over two-to-three-year terms, and as of June 30, 2026 it still carried $92.1 million in remaining performance obligations, roughly $62 million of which lands in the back half of 2026. Strip away the "other revenue" fog and essentially the entire AI licensing business is two contracts – Google at around $60 million a year and OpenAI near $70 million – with Premium subscriptions and a fragmented long tail of social-listening buyers like Meltwater and Cision making up the residual. That last group is small and unglamorous, but it's recurring and far less counterparty-concentrated than the marquee AI deals, and I'd treat it as the more durable part of the line.

Now the upside, which is where it could get genuinely large, but admittedly also genuinely uncertain. The bull case rests on a pricing model change rather than more customers: Reddit is pushing to move off flat annual fees toward usage-based metered pricing, tied to API volume plus a variable kicker for how often its content gets synthesized into AI answers like Google's Overviews. If that shift lands, insider chatter has a renewed Google deal alone reaching $150–200 million a year, and a fully renegotiated book – Google, OpenAI, plus settlements with the likes of Anthropic and Perplexity – reaching $400–600 million annually, with Wells Fargo publicly modeling roughly $550 million on renegotiation.

I'd hold those numbers loosely, because they ask you to believe two Reddit contracts will dwarf the entire disclosed publisher-licensing market several times over (OpenAI's News Corp deal, the largest on record, runs about $50 million a year).

The way I'd actually frame the ceiling is as a share of AI-lab economics rather than a count of deals: labs pay essentially zero for content today while Spotify pays labels around 70% of revenue, and the whole question is whether that equilibrium settles nearer 0.5% or 3%. On a $200 billion lab-revenue pool by 2030, a 1% content take is $2 billion, of which the single most-cited source on the internet might capture 15–25%, so $300–500 million; at 3% the math runs past a billion.

Such a wide range is maybe the most honest forecast I can make here, and I want to be upfront that it's a legal and negotiating outcome, not something more diligence on Reddit itself will narrow.

What I can say with more confidence is the direction. This is a line that could plausibly grow multifold on renewal. It may still remain a rounding error on Reddit's total revenue, or become a defensive, high-margin annuity worth as much as a mid-sized ad business – and which of those it becomes will be decided in negotiating rooms over the next four quarters, not on a date you can pencil into a model.

PS: Besides the size and mechanisms of the new deals, Siyu flags another interesting set of considerations below:

Inversion

Now to the caveat I’d put front and center: How recurring is this revenue, actually going to prove to be? The current major deals are short- to medium-term, roughly two to three years, and a fair question is whether the fees endure or fade once the models move past the data-hungry training phase. If the industry’s center of gravity shifts from training toward inference – running models rather than building them – you could imagine a world where an LLM has already learned what it needs from Reddit’s back catalog and no longer pays up for another pass. That’s the bear case on the durability of this revenue stream, and I don’t want to wave it away.

"Also playing chicken re: a new data licensing agreement is probably not a great idea if that's what management is doing. The second LLMs become less dependent on Reddit they lose all leverage. And they are likely at peak leverage right now. Dependence on Reddit for training is declining rapidly while synthetic data and transfer learning is reducing the importance of Reddit's content even more.” - Adam Wilk on X

But I’d push back on it, at least partway, from my own experience as a user. The thing that reliably frustrates me about LLMs is stale knowledge. You ask a question, you get a confident answer, and you can feel that the training data stopped a couple of months before you sat down to type. The model doesn’t know what happened last week, and sometimes it doesn’t know what happened last quarter. That staleness is precisely the gap Reddit fills. Its archive isn’t a frozen textbook you learn once and set aside. It’s closer to a live feed of the most current human read on almost anything – which phone actually has battery problems, which policy just broke, which trend is real and which is hype. As long as the world keeps changing and users keep wanting up-to-date, ground-truth human perspective, there’s a structural reason for models to keep coming back rather than coasting on a two-year-old snapshot. So the training-to-inference shift is a genuine risk to the flat-fee version of this business, and it’s also the strongest argument for why usage-based pricing on live data could turn out to be the more durable model.

One more concern belongs here: Licensing Reddit’s data into AI Overviews may cannibalize Reddit’s own traffic. If users get their answer straight from the AI summary, they have less reason to click through to the thread itself. So the same deals that light up the “other revenue” line could, at the margin, erode the engagement that feeds the advertising business. That’s not a footnote. It’s a real strategic tension inside the company’s own strategy, and it should be considered when reading about my projections for how big this line of business could become.

This is where it gets interesting!

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• InPost ($INPST) - generated an IRR of >400% as an acquisition offer emerged 2-3 months post write-up

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One housekeeping point: I wrote this a little while back (about 12-14 days ago), so share prices and a few figures may have potentially moved slightly since. Grab in particular is up some 15% since and also reported its latest quarter this week – I thought the results were fantastic fwiw – so keep in mind that the numbers in that section predate the print.

With that, enjoy.

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Disclaimer:

As of the date of publication the author owns shares in Grab Holdings but not in the other two companies (Boston Omaha and CTS Eventim); 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.

Germany: CTS Eventim ($EVD.DE) – A Digital Tollbooth on Sale?

Let me start close to home. CTS Eventim is the undisputed heavyweight of European live entertainment and the second-largest ticketing provider on the planet, trailing only Live Nation.

Billionaire founder Klaus-Peter Schulenberg took the reins of a distressed 83-person Munich software firm back in 1996, relocated it to Bremen, and rebuilt it around a proprietary technology platform.

Since the IPO in February 2000, the stock has returned a staggering 2,350%, roughly 13% a year for more than two decades. And yet pull up the chart today and you meet a very different mood. The shares have been dead money for five years, and they sit around €56, down close to 50% from the peak they touched in May last year. So what happened to the tune?

How Eventim Makes Money

Eventim runs two segments that look like one entertainment powerhouse on paper but behave very differently underneath. The first, Ticketing, is the crown jewel. It contributes only about a third of group revenue yet throws off more than 77% of adjusted EBITDA and roughly 83% of operating profit.

Think of it as a digital tollbooth. For every ticket sold, the company collects a fee worth something like 10% to 15% of the face value, and because the infrastructure is already built, each additional transaction costs almost nothing to process.

The economics of a 100€ concert ticket could look roughly like this:

In 2025, that meant close to €9 billion in gross transaction value across nearly 178 million retail tickets, at an effective take-rate near 11%. Margins in this segment have topped 40% at the EBIT line for years.

The second segment, Live Entertainment, is the operational counterweight. Here Eventim acts as the principal risk-taker: through its Eventim Live network of nearly 40 promoters, it books artists, funds tours, and stages the shows.

This side carries much thinner margins and roughly 70% of group revenue, but it feeds the machine. The promoters route their high-profile tours exclusively through Eventim’s own software, self-sourcing the very inventory that the high-margin tollbooth then processes.

Add the physical venues the group manages or owns – the LANXESS Arena in Cologne, the Eventim Apollo in London, the new Unipol Dome in Milan – and you get a company that captures a margin at nearly every touchpoint, from promoter fee to venue rental to ticketing commission to the beer sold at the concession stand. Group revenue hit a record €3.1 billion in 2025.

Why It’s So Hard to Dislodge

Eventim’s grip on its core markets is the thing bears consistently underestimate. Estimates vary, but the company holds something like a 50% to 60%-plus share of primary ticketing across Germany, Italy, and Austria. In its home market that figure runs even higher; the German Federal Cartel Office itself established, in its 2017 abuse-of-dominance proceedings, that Eventim controlled 60% to 70% of ticketing system services for promoters. That dominance has only grown since. If you want to see a major touring act in Central Europe, you have virtually no route to your seat that doesn’t clear through Eventim’s portal.

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That moat rests on a few reinforcing pillars. There’s the vertically integrated flywheel I described above, where owning promoters and venues forces high-margin volume through proprietary channels.

“Being vertically integrated enables Eventim to produce more concerts, which in turn drives high-margin ticketing revenue. More revenue in the industry drives artists to tour more, which further feeds the flywheel. Eventim’s revenue has grown at a low-double digit rate for many years with attractive margins and returns on capital. The business is asset-light, has a net cash balance sheet, and generates a lot of free cash flow. We are pleased to be shareholders and to be able to own this outstanding business with a substantial margin of safety.“ - Vulcan Value Partners

There’s the technology: EVENTIM.Net can absorb more than a million concurrent users during a stadium on-sale for the likes of Taylor Swift or Ed Sheeran without buckling, a feat regional rivals can’t match, and building that industrial hardening in-house is cost-prohibitive for any single promoter.

There’s the data, over 260 million user profiles that let promoters target buyers with a precision smaller players can only envy. And there’s the demand itself, which is stubbornly price-inelastic. A live concert can’t be digitized, simulated, or streamed into the same thing. During the 2008–2009 financial crisis, while industrial sectors were being flattened, Eventim’s ticketing revenues actually rose 29%. Fans guard their concert budgets even when times are tight.

One more signal worth weighing. Schulenberg already controls roughly 38.8% of the company through his family vehicle, and as the stock cratered in early 2026 he deployed about €20 million of personal capital into two open-market purchases, at €54.37 and then €50.85. Insiders sell for all sorts of reasons; they generally buy for only one.

What Went Wrong

If the business is this good, why is the stock cut in half? A few anxieties are doing the work. The loudest is venue execution. When Eventim signed up to build the Milan arena for the 2026 Winter Olympics, the budget was pencilled in at €180 million. Global inflation, energy prices, supply-chain snarls, and design changes ballooned the final bill to nearly €400 million. Free cash flow took a visible hit, and the market began re-rating the company from an asset-light digital compounder into a lower-return, capital-heavy real estate operator. A new 20,000-seat arena committed in Vienna only sharpened that fear, though management insists venue ownership isn’t the primary objective and that it intends to keep only a minority stake in the property vehicle under a PropCo/OpCo structure.

Then came a cautious 2026 outlook in late March, guiding for roughly flat profit growth against analyst hopes for double digits, which knocked the stock down as much as 21% in a session. Part of that guidance reflected a structural change in the long-standing Stage Entertainment contract, which looks like Stage Entertainment insourcing its backend software. The relationship wasn’t lost entirely; the retail ticketing partnership was extended across four countries in April, protecting the high-margin point-of-sale volumes. There’s also a genuine margin-mix effect, since the lower-margin Live Entertainment segment has been growing faster than Ticketing, plus integration costs from the See Tickets and France Billet deals.

I won’t wave away the longer-term worries either. Regulation is a live risk: the Cartel Office already forced promoters to be able to distribute at least 20% of volume through third parties, and further fee interventions could follow. A well-argued short thesis frames the 2022–2023 boom as a post-COVID sugar high that should normalize. And Spotify, sitting on the music discovery funnel, could in theory disintermediate primary ticketing over time.

I happen to think Eventim’s vertical integration and the sheer localness of the business keep it defensible, and it’s telling that Q1 2026 came in strong – group revenue up 23%, EPS up 38%, like-for-like ticketing up 6% once you strip out the Stage accounting artifact. But these are the cracks worth pressure-testing.

What You’re Paying

Here’s where it gets interesting, and where you have to be careful. Most research terminals get Eventim’s valuation wrong, because they pull the total consolidated net result and ignore that a chunk of those profits belongs to minority partners in non-wholly-owned subsidiaries. Strip out that leakage and use the net result actually attributable to shareholders, and the picture sharpens. At the May 2025 peak, a €10.8 billion market cap put the business at a demanding 36.6x attributable earnings. After the drawdown, at a €5.7 billion market cap, that multiple has compressed to roughly 19x, up roughly ten to fifteen percent since I initially covered the company in June.

I don’t think the business is meaningfully over- or under-earning, and I treat the shift toward some venue ownership as structural rather than a one-off distortion. So 19x strikes me as a fair read of today’s setup. The question is what it’s worth. A monopoly-like franchise growing at solid rates arguably deserves something closer to 25x; one respected German fund noted it historically traded at 30 to 35x and treats a sub-20 multiple as an opportunity. Re-rate from 19x back to 25x over five years and the multiple alone adds about 5.6% a year. Layer high-single-digit earnings growth on top, and you’re underwriting slightly market-beating returns without heroic assumptions. My own five-year exit-multiple model that I ran in June (at a slightly lower price), across three scenarios, lands on a weighted expected IRR around 18%, and you collect a dividend near €1.44 (a payout of roughly 50%) while you wait.

The core question, then, is simple. Is the market right to re-value Eventim as a capital-heavy infrastructure play? Or is it handing patient investors a monopolistic, recession-resilient compounder at a discount to its own history because of a temporary construction bill and a conservative guide?

Full CTS Eventim deep dive

Singapore: Grab Holdings ($GRAB) – The Operating System for Daily Life in Southeast Asia

Now travel about 10,000 kilometres east.

Grab began in 2012 as a fix for one of the world’s least reliable taxi systems, dreamed up by two Harvard Business School classmates who wanted Malaysians to reach their destinations safely. Fourteen years on, it has become something closer to the operating system for daily life across Southeast Asia.

In several countries, the name is a verb: people say they’ll Grab to the mall or Grab some dinner without a second thought. The company outlasted Uber in the region, bought its rival’s local operations in 2018, and now serves more than 50 million monthly transacting users across eight countries. Earlier this year, Grab made two moves that most investors are (of course) aware of, but that might fly under the radar in terms of Grab’s valuation if you’re only glancing at headline numbers shared by the company (both the backward-looking numbers as well as the current guidance). The acquisitions of foodpanda Taiwan and Stash Financial were both announced in Q1 2026, but if you check the latest Q1 earnings, you won’t see these deals reflected anywhere in revenue yet.

Despite all these developments, the stock tells a bleaker story. It trades around $3.3, down roughly 48% over the last 12 months, and close to 80% below its 2021 debut.

Three Engines Under One Roof

Grab runs a superapp with four reporting segments, and the economics differ sharply beneath the surface.

• Deliveries is the revenue engine, home to GrabFood, GrabMart, and GrabExpress, and it generated about $1.8 billion in 2025.

• Mobility is the profit engine: ride-hailing across cars and, importantly, motorcycles, which account for roughly three-quarters of all trips in the region’s congested cities. That segment produced $1.22 billion in revenue and $690 million in adjusted EBITDA last year, a 56% margin that funds much of the rest.

• The third engine is the one I find most interesting. Financial Services – payments, lending, insurance, and three digital banks – grew 37% to $347 million in 2025 and still runs at a loss, but management expects it to hit EBITDA breakeven in the back half of 2026. Its loan book crossed $1 billion in 2025 and is on track to pass $2 billion by year-end 2026.

• The fourth segment, Others, is mostly GrabMaps, the proprietary mapping stack Grab built because global providers couldn’t handle Southeast Asia’s narrow alleys and motorcycle shortcuts, now licensed to the likes of Amazon and Microsoft.

Underneath all of it sits a toll-booth model. Grab takes a cut of each transaction, roughly 13% of order value in deliveries and about 15% in mobility, and layers on a fast-growing, high-margin advertising business.

GrabAds already runs at a $236 million annualized rate, up 45% year on year, at an estimated 60% EBITDA margin, and it has only penetrated about 1.7% of deliveries volume against a ceiling closer to 4%.

The headline milestone came in 2025, when Grab posted its first full year of net profit, $200 million, after 16 straight quarters of improving adjusted EBITDA.

Why the Flywheel Is Hard to Copy

The bear frame is that a car ride is a commodity and margins in this business are structurally capped.

There’s truth in that.

So the question that decides everything is whether the superapp can lift Grab above a commoditized utility, and the evidence, I believe, increasingly says it can. Start with scale: Grab holds a dominant 71% share of Southeast Asian mobility and 65% of deliveries, running three to three-and-a-half times the size of its next regional rival. That density lets it spread fixed technology and corporate costs across an enormous transaction base.

Then there’s the flywheel. Around two-thirds of users engage with more than one service, and here’s the number that matters most. A customer using a single service in 2021 had a one-year retention rate of 37%; a customer using three or more services retains at 88%.

The more of the ecosystem you touch, the less likely you are to leave for a fifty-cent discount elsewhere, especially once your money, your loan, and your loyalty points all live inside the app. Layer on the data loops – billions of trips feeding better routing and sharper credit underwriting – and you get advantages that compound quietly across verticals.

Two harder barriers deserve a mention. First, regulation cuts both ways here: Grab spent more than a decade and roughly $12 billion securing digital banking licenses in Singapore, Malaysia, and Indonesia, and those licenses are extremely difficult for a challenger to replicate. Second, the AI-driven cost structure. Grab doubled its revenue between 2022 and 2024 while holding headcount essentially flat, deploying over 1,000 proprietary models, with more than 90% of mobility rides now dispatched by AI. I’d also flag a scale-economies-shared instinct that I like: since 2021 average fares have fallen 16% while driver earnings per hour have risen 29%. Management seems to be widening the ecosystem rather than squeezing it, which tends to be the durable way to build a moat.

Some selected comments on the focus on affordability from earnings calls:

“… a powerful strategic roadmap, focused on affordability, ecosystem-led lifetime values and Gen AI efficiency.“

“Now that is going to translate into also absolute margin expansion and absolute margin dollar in the business. We are driving cost down so we can lower the cost of serving the business. That affordability that we’re working on so focused on is working, and we’re going to continue to extend that.“

“We’ll continue to do this because both ourselves and the government have aligned interest to develop a sustainable platform that operates reliably for our customers and affordably for our customers to enable us to continue to create and enhance livelihoods for driver partners and micro SMEs across Indonesia.“

“So despite the macroeconomic headwinds, we have driven affordability as a key part of our strategy. and the product-led strategy in Indonesia.“

“Affordability drives a lot better frequency“

“We still have work to do also in affordability. We’re not stopping on affordability. There’s still a lot of things that we want to do on the ride side of the house as well as on the Deliveries side that will continue to also fuel the momentum on the growth business of our On-Demand.“

“This increases our affordability and grows the overall user base, as you saw in our numbers, which is our key strength. Also, our focus on affordability is paying off. So this isn’t new. Our focus on affordability, which we began in 2023, with products like Saver delivery, Saver transport, that was explicitly designed for this purpose. These services are now essential for users, enabling them to manage their wallets effectively. So this makes us a must-have service not a nice to have, which protects us from a pullback in discretionary spending. Look, but the reality is we may not be immune to macro trends, but our strategy is designed to be resilient and even opportunistic in this landscape. So we continue to reinforce this by partnering with governments as well. For instance, in Indonesia, we’ve been running what we call the Kota Masa Depan, which is a future cities program in partnership with the Ministry of Micro, Small, and Medium Enterprises, where we have worked to support small businesses and digital upscaling across nearly 20 cities. And in Vietnam, our AV launch is really to design to drive better NPS and also lower partners costs. These on-site projects, they strengthen our ecosystem and create a more sustainable, profitable business for the long term. So we are confident in our strategy and our outlook.“

What Went Wrong

So why has the stock been such a disappointment?

A big part traces back to how Grab came public. It listed in December 2021 via a SPAC at a $40 billion valuation, right at the peak of the pandemic tech mania, which left a generation of early investors deep underwater as the market pivoted from growth-at-all-costs to profitability. For most of the prior decade, Grab was also viewed as a bottomless pit for venture capital, and that reputation as a loss-making juggernaut has been slow to fade even as the numbers turned.

The live worries are more concrete. Regulation and labor sit at the top: Indonesia has floated commission caps, and gig-worker reclassification proposals in several markets threaten the low-cost economics of a contractor-based model. Governance is a genuine knock too, since the dual-class structure hands founder Anthony Tan outsized voting power and limits minority-holder influence. Add a high and rising short interest through 2026, plus an $80 million settlement in 2025 over disclosures around the SPAC process, and you have a stock the market still prices mainly as a mobility-and-delivery outfit.

What that framing potentially overlooks is the high-margin optionality stacking up in advertising, digital banking, and eventually autonomous vehicles, none of which is close to fully reflected in long-term cash-flow expectations.

Those are the falsification points I keep testing: whether Indonesian regulation or a scaling loan book could derail the profitability inflection.

What You’re Paying

Here’s where the setup gets compelling. At a market cap near $14 billion, and against management’s guidance for more than $1.2 billion of free cash flow by 2028, Grab trades at roughly 11.5x that 2028 number. Strip out the balance sheet, though – as the company sits on an enormous cash pile; on a conservative read, net liquidity of about $5 billion puts enterprise value near $9 billion – and the EV-to-2028-FCF multiple drops to something like 7.5x. For a business growing revenue in the high teens with expanding margins, that’s an interesting number.

The path to get there rests on management’s North Star: a 20% revenue CAGR from 2025 to 2028, adjusted EBITDA tripling to $1.5 billion, and free-cash-flow conversion climbing from 58% to 80%. Those targets are backed by 16 consecutive quarters of margin improvement, so they read as ambitious rather than fanciful.

My own ten-year scenario work from May, starting from a $10 billion enterprise value and $200 million of net profit, spans revenue CAGRs from 12% to 24%. The base case, mid-teens to low-twenties growth with similar net margins and an 18–26x exit multiple, points to compounded returns somewhere in the 14% to 28% range, though I’d shave a few points off for dilution.

full Grab Holdings deep dive

United States: Boston Omaha ($BOC) – A Baby Berkshire Nobody Wants?

The last stop for today’s blog is the company that took me the longest to write up, since I effectively had to study three (!) businesses in one.

Boston Omaha began its current life in 2015, when Adam Peterson and Alex Rozek (Warren Buffett’s grandnephew, for the trivia fans) bought a tiny Houston shell company whose only asset was a building housing a sushi restaurant. They had a plan: build a holding company that compounds intrinsic value per share over decades. Roughly $480 million of capital raised and 50-plus transactions later, that’s what they’ve assembled. The comparisons to a young Berkshire write themselves, which is both the appeal and the burden (how many “mini-Berkshires” have actually delived shareholder value?).

The stock, meanwhile, has been miserable. It IPO’d at $13 in 2017, touched the high $20s in early 2022, and now trades in the low to mid teens.

A Holding Company and Its Locomotives

Management likes to describe Boston Omaha as a train pulled by four locomotives. The first is billboards, run through Link Media, now the sixth-largest outdoor advertising operator in the country with roughly 4,000 structures and 7,600 faces.

“From our first acquisition in 2015 to today, Link has grown to be the 6th largest owner of billboard faces in the country.“ - 2022 letter

This is the cash cow: about $45 million of revenue in 2024, margins around 45%, and, crucially, very little capital needed to keep it running once the structures are up.

The second is broadband, a fiber business across Utah, Arizona, and Nevada with about 46,900 customers. Its cleverest feature is the “protected build” model, where an HOA or developer signs a decade-plus contract and every home in the community pays a bulk fee whether or not the resident uses the service, which produces near-100% take rates and guaranteed cash flow.

The third had been (!) insurance: surety bonds written through General Indemnity Group, licensed in all 50 states, a niche where written premium grew from $9.3 million to $26.4 million while averaging a remarkably low 14.6% loss ratio. I say “had been” for a reason. In May 2026, Boston Omaha agreed to sell the entire surety unit, GIG together with its United Casualty & Surety carrier, the BOSS Bonds agency, and the SuretyBonds.Market platform, to CopperPoint Insurance for $84.3 million in cash – Boston Omaha’s market cap is $475 million as I write this –, a deal expected to close by year-end 2026. So the four-locomotive train is on its way to becoming a three-locomotive one, and I’ll come back to what that does to the math.

Sitting alongside those is Boston Omaha Asset Management, whoch enables BOC to be a holder of concentrated minority investments in companies Boston Omaha does not control but believes can compound value. The jewel there is a roughly 15% economic stake in Sky Harbour – about 46% of the publicly traded Class A shares – a company that builds and leases private-aviation hangars at capacity-constrained airports. As of the latest Schedule 13D/A filings (spring 2026), Boston Omaha directly holds about 8.67 million Sky Harbour Class A shares, plus another 2.67 million held inside its United Casualty & Surety subsidiary, so roughly 11.3 million shares in total, plus warrants on another 7.72 million. That's down modestly from the ~11.94 million shares cited in my January write-up, since they've been selling small tranches throughout 2025 and into 2026.

It’s yet another asset-heavy, regulation-shielded, slow-to-build infrastructure play, which tells you something about the house style.

What ties the whole thing together is capital allocation. Cash from the steady billboard business gets recycled into the higher-growth, hungrier segments, and the scoreboard management actually cares about is intrinsic value per share.

On my preferred proxy, revenue per share, the record is tangible: it compounded from $0.58 in September 2016 to $3.58 in September 2025, a 22.4% clip.

Toll Booths, Pipes, and Underwriting Desks

Let me be honest about the moat, because Boston Omaha isn’t a textbook wide-moat business and pretending otherwise would mislead you. What it owns is a set of narrower, segment-specific advantages that happen to be annoying and uneconomic for anyone else to replicate.

Billboards are the clearest case. You can’t simply erect new structures in prime locations however much capital you have, because zoning, permitting, and community resistance choke off new supply. That regulatory friction protects the incumbent, and Link earns a cash-flow return on tangible capital north of 30%. Pricing power is local and situational rather than absolute, but in strong locations rents can rise without losing tenants.

Broadband works on a different principle, closer to a railroad. Once you’ve laid fiber to a few thousand homes in a small town, a second provider rarely finds it worth the money to overbuild you, so the network becomes a local near-monopoly. Layer on the switching friction of installation and downtime, and you get durable retention.

Insurance was always the weakest of the three, and I’d say so to anyone. There’s no brand, switching costs are thin, and the whole industry is crowded with people who were “disciplined” right up until they weren’t. What made the surety niche defensible is that it’s small enough to be ignored by the big carriers and carries structurally low loss ratios, because a surety bond is designed to prevent a loss rather than pay one. It’s probably no accident that this is the leg management has now chosen to cash out.

The thread running through all of it is cultural: a patient, per-share-focused capital allocator in Peterson (I recommend reading all of his annual letter), who is also the company’s largest shareholder.

What Went Wrong

So why does a business with a 22% revenue-per-share CAGR trade down 74%? Because the market can see the costs and can’t yet see the payoff. Consolidated free cash flow has been meaningfully negative, yet, arguably that’s by choice: broadband soaked up nearly $30 million of capex in 2024 against just a couple million in billboards, on the theory that today’s build becomes tomorrow’s high-margin subscriber base. That’s a defensible trade, but it means reported numbers look ugly, and after a decade the company still shows no clean consolidated profit.

Book value per share, the metric a Berkshire-style vehicle is supposed to compound, has grown at only about 7% since 2016 – even though management clearly explains in their letters why due to certain accounting regulations, this has become a less useful metric (again, I encourage you to read the letters yourself)..

For a lot of investors, that’s the whole story, and they’ve walked away.

“On the eve of Valentine’s Day in 2015, present management fell hard for a small company in Houston whose only business was a single building that housed a sushi restaurant. Over the past six years, approximately $480mm in capital was raised and over $280mm has been deployed in operating businesses in over 50 transactions to build Boston Omaha into what it is today.“ - 2020 letter

Governance added fuel. When co-founder Rozek left in 2024, ending the co-CEO structure, the company repurchased his shares, including super-voting Class B stock, at prices far above the market, roughly a $19 million cash cost that landed as the stock was already depressed. An independent valuation firm blessed the price as fair to intrinsic value, and avoiding litigation over super-voting control probably was the lesser evil, but it stung and it dented trust.

Add a macro backdrop where higher rates punish any “invest now, earn later” story, and you get a stock that short-horizon and mandate-constrained investors simply can’t hold.

The bear case, which deserves respect, is that this is a serial reinvestment machine that keeps deferring the moment of truth, and that the inflection is always next year. My read is that these headwinds are temporary rather than terminal, but the burden of proof sits squarely with management to be fair.

What You’re Paying

This is where the complexity becomes the opportunity. Boston Omaha’s market cap is around $475 million. Strip out the roughly $115 million Sky Harbour stake and about $30 million of other minority investments, and you’re paying something like $330 million for the operating businesses. Against roughly $25 million of current underlying free cash flow, a figure management itself cited back in 2022 and that outside analysts corroborate, that’s about 13x, or a 7.5% yield. And that cash flow isn’t static. Next year points to about $28 million, and one analyst I respect projects roughly $35 million by 2027 as broadband matures, which would compress the multiple further.

The GIG sale sharpens the picture rather than muddying it. Insurance was throwing off only about $1 million of free cash flow, so losing it barely dents the ~$25 million, yet it converts that sleepy leg into $84.3 million of cash, the bulk of which flows to Boston Omaha to fund buybacks or redeployment. Fold that incoming cash into the sum-of-the-parts and the stub you’re paying for the billboard-and-broadband core looks cheaper still.

Management is effectively simplifying the story and handing itself dry powder at the exact moment the stock trades well below its own estimate of intrinsic value.

The downside is what makes it interesting, because you don’t need a fancy sum-of-the-parts model. The billboard business alone anchors a floor: on about $18 million of estimated segment free cash flow at a normal 10–12x takeout multiple for scarce outdoor inventory, Link is worth something like $180–216 million by itself. Value the 44,500 fiber passings at the $3,000–5,000 per passing that recent private deals imply, and broadband adds another $130–220 million, before you count the fixed-wireless customers or any of the minority stakes. In other words, the pieces you can value conservatively already cover most of today’s price, with the reinvestment upside thrown in for free. Management clearly agrees the stock is cheap; they authorized a $20 million buyback in 2024 and a fresh $30 million program in late 2025, which is decently accretive when you’re retiring equity at about 13x FCF, or a 7.5% yield; in Q1 2026, Boston Omaha actually repurchased 375,286 Class A shares for $4.8 million..

I’ll be straight with you: I haven’t bought this one yet and it’s no slightly more expensive than when I first wrote it up in January this year. Part of that is currency risk, since I invest from Europe and have my reservations about the dollar, and part is that I want to see broadband’s inflection show up in reported cash before I fully commit. But intellectually I’m optimistic the business is worth more than the market says, the downside looks well protected by the billboards alone, the insurance business sale make the story easier to decode for outside investors, and Peterson strikes me as a thoughtful allocator being punished for a build phase rather than for structural weakness.

This is the kind of setup that tends to feel exactly like this right before it works.

full Boston Omaha deep dive

Closing Thoughts

Please don’t read this as a buy list. It isn’t one. Each of these three carries risks I’ve tried to lay out honestly, and two of them I haven’t even bought myself yet.

What ties them together is a pattern I keep circling back to. All three are down heavily, each wearing a kind of temporary disguise that makes it awkward to own today: a doubled construction bill and a cautious guide at Eventim, a SPAC hangover and a gig-economy label at Grab, a decade of heavy reinvestment with little to show on the income statement at Boston Omaha. Look past the surface, though, and you find businesses shielded by something that took years to build, be it a regulation-protected tollbooth, a superapp flywheel, or scarce physical assets in industries that barely change from one decade to the next.

And importantly, in every case, the person steering capital has been doing it for a long time and has real money riding on the outcome (yes, I do have a very strong bias toward founder-led businesses!).

That mix – a durable edge, an aligned operator, and a share price the market has temporarily written off – is what I spend my days hunting for, wherever in the world it happens to live. Germany, Singapore, the US. It seldom turns up where everyone is already looking.

If this is your kind of investing, I’d love for you to come read more of it over at Compound with René.

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Three months ago, in May, I published a long deep dive on Nintendo in which I argued that the market was still pricing a growth inflection as a legacy hardware cycle. I framed it as a hypothesis rather than a thesis, precisely so that quarters like this one could do their job, which is to tell me where I am wrong.

Today, Nintendo reported its first quarter of the fiscal year ending March 2027, and I want to walk through what the print actually says, what it says about the seven pillars I laid out in May, and where my view has shifted. The full Q&A is not out yet, as I write this (I have to catch a plane in around three hours from now), so the comments are largely based on the results and slides shared and the added explanations.

Net sales came in at 517.8 billion yen, down 9.5% year on year. Operating profit went the other way, up 150.5% to 142.5 billion yen, which lifts the operating margin from 9.9% to 27.5%. Ordinary profit more than doubled to 206.1 billion yen (close to 40% margins) and net profit rose 53.5% to 147.4 billion yen.

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I think overall it’s an “okay” quarter; not more and not less.

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.

A 27.5% Margin That Is Really Closer to 18%

Two things flattered this print, and both are disclosed in plain sight. The first is roughly 300 million U.S. dollars booked as a reduction of cost of sales in connection with IEEPA tariff refunds.

“We recorded approximately 300 million U.S. dollars as a reduction of cost of sales in connection with refunds of IEEPA tariffs. The tariffs related to the refunds were primarily borne by the company rather than passed on to consumers through product prices.“

At the quarter’s average rate of 159.38 yen to the dollar that is about 47.8 billion yen, or a third of reported operating profit.

The second is currency, which added 39.0 billion yen to sales and about 22.2 billion yen to operating profit.

Strip out the refund and the operating margin lands near 18%. Strip out the currency help as well and you are in the mid-teens. Against 9.9% a year ago that is still a genuine improvement, and it is exactly the improvement the model predicts once hardware stops dominating the revenue mix. Hardware fell from 78.8% of platform sales to 55.3%.

First-party software climbed from 64.8% of software sales to 82.6%.

Digital reached 61.5%, up 2.2 points (but down from Q4; 67.2%), with digital sales up 90% to 132.7 billion yen.

On the refund itself: Nintendo booked it, and it intends to keep it. There is a class action in Washington arguing that the company should hand it back to the consumers who paid the tariff-inflated prices, and Nintendo’s lawyers filed a motion to dismiss in July, arguing that buyers “received exactly what they bargained and paid for.” I have no view on how a Washington court will rule. I do have a view on the accounting: this is a one-time item, it does not repeat, and anyone building a run-rate off Q1 needs to take it out.

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Why Switch 1 Software Grew Four Times Faster Than Switch 2 Software

One line in this release stood out: Nintendo Switch 2 software sell-in grew 9.2% year on year to 9.46 million units. Nintendo Switch software, the nine-year-old machine, grew 38.6% to 33.81 million units. The old console outgrew the new one by a factor of four in its second year.

At first glance, this looks alarming.

Think about it for two minutes and it makes sense. A couple of reasons why:

• Tomodachi Life: Living the Dream shipped 7.94 million units in the quarter and has now passed 8 million on a sell-through basis, and it is a Switch 1 title that runs beautifully on Switch 1 hardware.

• Meanwhile the prior-year comparison for Switch 2 software is the launch quarter, when Mario Kart World was going out of the door inside hardware bundles by the million. Roughly 12.6 million Switch 2 software units were bundled with hardware across FY26. That is a brutal comp to lap.

So the mix looks odd for good reasons. What I take from it is something I have believed since before the Switch 2 launched, which is that the depth of the Switch 1 catalogue is an asset rather than a drag. Nintendo is still monetizing an installed base of well over 100 million people while it builds the next one. Annual playing users came in at 130 million for the twelve months to June, holding the level from last year. The company earns money from those users whether they have upgraded or not.

Do Apple Investors Care Whether It Was a 16 or a 17?

Which brings me to something that has been bothering me about how this business gets analyzed, including by me. Analysts spend enormous energy splitting Switch 2 units from Switch 1 units, as though they were two companies. Switch 2 was 3.82 million of 4.48 million hardware units in the quarter, or 85% of the total.

Fine. That is roughly what anyone would have guessed. The split tells you almost nothing you did not already know.

Now look at the ecosystem as one thing, which is what it actually is. Total hardware sell-in fell 34% against a launch quarter, which is again, to be expected.

Total software sell-in rose 31%, from 33.07 million units to 43.27 million. That is the number I would put on the front page and place most emphasis on.

An ecosystem that moved 31% more software in its seasonally weakest quarter, in a year with no 3D Mario and no mainline Zelda, is not an ecosystem losing engagement.

Long-term Apple investors do not build their spreadsheets around iPhone 17 versus iPhone 16 versus iPhone 15 units. They look at total unit growth, installed base, and services attached to it. That’s what Nintendo investors should do too!

Nintendo is obviously not Apple, and the cadence is different, since we are five to seven years away from a Switch 3 rather than twelve months from the next iPhone model. But the direction of travel is the same, or at least similar.

Backward compatibility and Nintendo Accounts turned two generations into one continuous base, and over time users migrate as the Switch 2 exclusives pile up. There may even be an Apple-style forcing function at the far end of this, when Nintendo eventually stops supporting Switch 1 the way Apple retires an iOS version. That is a 2035 problem presumably, but it will be another incentive to migrate eventually.

The Pipeline Is Still My Biggest Complaint, and the Tie Ratio Proves It

I want to hold my own hypothesis to the fire here, because this is where the May piece looks most optimistic in hindsight. In the deep dive I quoted Ryan O’Connor’s analysis that the Switch 2’s implied twelve-month tie ratio of 3.74 essentially matched the original Switch’s 3.71. We now have thirteen months of actual data rather than an extrapolation. Life to date, Nintendo has sold 23.68 million Switch 2 units and 58.17 million Switch 2 software units. That is a tie ratio of 2.46. Take out the roughly 13 million bundled copies and you are at about 1.9.

The comparison to Switch 1’s first year is not perfectly clean, since bundling practices differ and the Switch 2 base is younger on average, which mechanically depresses the ratio. Even allowing generously for both, the extrapolation was too kind. Software per console is running below where the bull case had it.

I do not think this breaks the hypothesis. I think it dates it. The pillar I called the system-seller flywheel was explicitly premised on the idea that the flywheel had not started yet, and thirteen months later it still has not! (which is disappointing to say the least)

The titles that move the needle are Mario, Zelda, Mario Kart, Animal Crossing and Smash Bros. Since launch, the Switch 2 has had exactly one of those. Yoshi and the Mysterious Book in May, Star Fox in June, Splatoon Raiders in July. Perfectly decent games. None of them is a system seller.

The back half of the year looks materially better. Fire Emblem: Fortune’s Weave lands on 17 September, Nintendo Switch Sports Resort on 22 October, and The Legend of Zelda: Ocarina of Time is scheduled for sometime this year, which is the most interesting item on that list by a distance.

Pokémon Winds and Pokémon Waves arrive in 2027, as does Xenoblade Genesis.

Still no 3D Mario announced. No Nintendo home console has ever gone two holiday seasons without one, and October is where they have historically been placed, so I would treat the absence of an announcement as a timing question rather than a strategy question.

But it remains an open question, and the release cadence is the single sharpest criticism I have of this company right now. The hardware execution has been close to flawless. The first-party software cadence has been underwhelming, and my hypothesis still depends on them fixing it.

Nintendo Just Put a Number on the Memory Problem

In May I argued that the memory panic was overdone, mostly because software carries around 90% of operating profit and hardware margin compression is therefore a smaller lever than the market assumed. I still believe the second half of that. The first half deserves an update, because the input side got worse, not better. DRAM contract prices jumped roughly 60% quarter over quarter in Q2 of this year, and TrendForce expects a further 13% to 18% in Q3. Samsung and SK Hynix are both signalling that shortages persist into 2027 and possibly beyond. This is not a spike that reverses next quarter.

What has changed is that we now have Nintendo’s own number instead of a narrative. The FY27 guidance, unchanged from 8 May, has roughly 100 billion yen of higher component costs and tariff effects baked directly into cost of sales. That is a quantified, disclosed headwind of about 5% of forecast revenue, and Nintendo is still guiding operating profit up 2.7% to 370 billion yen despite absorbing it. That is the answer to the memory question, and it is a considerably more useful answer than any stress test.

Nintendo also did the thing the deep dive flagged as the obvious lever and raised prices. Japan went from 49,980 yen to 59,980 yen on 25 May, a 20% increase, with the United States moving from $449.99 to $499.99 on 1 September and Europe seeing a smaller bump. Nintendo Switch Online pricing went up too. Furukawa’s framing was that carrying the higher costs indefinitely would make the business unviable, which is about as blunt as this management team gets. And importantly, in the Q1 filing, the company reports that Japanese sell-through held up after the increase. That is a small data point and I would not over-read a single quarter of it, but pricing power in the one market that already absorbed a 20% hike is worth more to me than most of what was in this release.

There is a second-order effect worth planning for. The Western price rise takes effect on 1 September, which sits inside the July to September quarter. Expect some pull-forward of demand into Q2 as buyers move ahead of the deadline, and expect that to make Q2 hardware look better than the underlying trend, with a corresponding payback later.

121 Billion Yen of Concrete in Kyoto

Slightly buried at the back of the deck: Nintendo is building a Technology Development Center in Minami-ku, Kyoto, on land acquired from the city in 2022. Nine floors above ground, roughly 49,300 square metres, completion planned for March 2029, at a current estimated construction cost of 121 billion yen (about $660 million). That sits alongside a forecast R&D spend of 190 billion yen this fiscal year, up from 143.7 billion in FY25. R&D in the quarter alone was 49.1 billion yen, up 26%, while advertising fell 22.9%.

I like this a lot more than the market probably will. The most common criticism of Nintendo’s capital allocation, which I made myself in May, is that the cash pile sits there doing nothing while shareholders wait. Spending it on development capacity and headcount is the version of capital allocation I actually want from this company, given that the entire hypothesis rests on their ability to produce more AAA software more consistently. Whether it works is a 2029 question. The intent is the right one.

Where This Leaves the Hypothesis

Guidance is unchanged: 2,050 billion yen of net sales, down 11.4%, operating profit of 370 billion, up 2.7%, and a dividend cut from 219 to 162 yen, which is mechanical rather than a signal since the payout ratio is holding near 60% on a lower net profit forecast.

Run the pacing and that guidance looks conservative; as always for Nintendo. Q1 delivered 38.5% of the full-year operating profit target, and even stripping the tariff refund it delivered 25.6%, in the seasonally weakest quarter of the year. On units, roughly 42.8 million of the 165 million software target came in Q1, which is 26% of the year before the two strongest quarters have started and before any new AAA title was released or announced. Hardware is pacing at 24% of the 18.5 million target, and Switch 2 needs 12.68 million units over the remaining three quarters against 14.04 million in the equivalent stretch last year, with a holiday season, a price-hike deadline, and a better release slate in between. I would be surprised if Nintendo does not raise numbers at some point in the second half.

Was the quarter better or worse than what was priced in? The revenue decline was expected and everyone knew it was coming. The margin recovery holds up even after you strip the one-offs out. My honest read is that Q1 marks the trough of the year on almost every line, and the year-on-year comparisons get easier from here.

Nintendo’s stock is up 3% in Frankfurt trading as I type this.

The pillar I would now watch hardest is the one I already flagged as the core of the whole thing. Games sell hardware. Nintendo has 23.68 million Switch 2 owners waiting for a reason to buy their fourth and fifth game, and the company has not yet given them one. If Ocarina of Time and a 3D Mario land in the next twelve months, the tie ratio problem solves itself and this quarter looks like the bottom of a very ordinary trough. If they slip again into 2027, I will have to revisit whether the back-loading strategy is discipline or drift.

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.

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Articles & Letters:

• Thread on X with stock ideas

• Open letter by Bernard Arnault in reaction to "the investigation" by Le Monde (translation shared by European_DGI) – I can assure you you will enjoying reading this and laugh out multiple times!

  “First, I learned that my staff are very well dressed and none are overweight. I apologize to readers for this lack of body diversity, and I will contact the company restaurant on Monday. I also learned that visitors have their Hermès ties taken away. That is false: we let them keep them. We simply offer them a second, more discrete one for the elevator. It is a matter of politeness. I will add, as a secret, that I own several.“

• Horizon Kinetics June letter (“Under the Hood Revived (we just HAD to!): What’s in Your Index?“); topics covered:

  • Hyperscalers Are Sacrificing Their Free Cash Flow for Data Center Growth

  • Data Center Spending Means Tough Trade-Offs for Hyperscalers

  • Emerging Co-Dependence Risk

  • Here’s one chart from the letter:

    

    Reading Suggestion: Very much related to it is my own analysis from last week titled “8 Signs the AI Bubble Is Further Along Than You Think“

• Seeing What Others Miss: An Investor’s Guide to Insight by

• Albert Bridge Capital shared a FT article by Andrew Dickson (from 2021 I believe): “BAILLIE GIFFORD’S NEVER-SELL MANTRA IS A SONG FOR FOOLS“

  “In an after-the-fact diagnosis, Burns is implying that a biased sample of self-selected winners like Tesla and Alibaba suggest that it is a mistake to ever sell any shares in any companies that you think are “winners” either historically or prospectively. Yes, it is true, if you sold Tesla too early, you didn’t make as much money as those who didn’t. But what about those investments that weren’t Tesla? And what about former consensus winners like Eastman Kodak, or Cisco, or Nokia? Justifying his view, Burns cites research by professor Hendrik Bessembinder which suggests that a) a majority of stocks do not outperform 1 month US treasury bills b) 1 per cent of companies accounted for all global net wealth creation and c) 99% of companies were a “distraction to the task of managing money”. Burns suggests that Bessembinder’s research should “shake the foundations” of the investment industry and that we need a “vastly different mentality” to “focus on the possibility of extreme upside”. That sure would be nice, wouldn’t it? If we all could just sit back and take our money out of 99 percent of our investments and all plough it in the same 1 per cent that everyone else already knows about, and then expect to outperform. As preposterous as it sounds, the conclusions drawn from Bessembinder’s paper were also misinformed in the first place. It isn’t entirely Burns’ fault, Bessembinder himself presented his observations and conclusions in a sensational way.“

  • Two comments that are very related to this critique that I shared on X recently:

    • Here, I myself claimed that Bessembinder’s study is “The single most-referenced finding in equity research this decade [and] is misleading. Not wrong – misleading.“ – and explain why.

      “Here’s my problem with how that data point gets used: It assumes a forever holding period. That may be a clean theoretical construct – and even Buffett himself said “his favorite holding period is forever” – but it ignores one of the single most important skills in real-world investing: TIMING. Bessembinder is measuring lifetime, buy-at-IPO-hold-until-delisting/bankruptcy outcomes. Almost no one actually invests that way, including the man whose quote gets attached to the idea (see above).“

    • In this post, I argued that the single biggest weakness of some quality funds is their lack of timing skills.

      “They excel at security selection. They do not even try their hand at timing (another way of saying they are average at best), I don’t find them to be particularly valuation-disciplined. And they aren’t particularly differentiated with regard to position sizing.“

• An MIT study drawing on 52 executive interviews, surveys of 153 leaders and analysis of 300 public deployments found that roughly 95% of enterprise generative AI pilots delivered no measurable impact on profit and loss.

  “Zero return.”

• S&P Global found 42% of companies abandoned most of their AI projects during 2025.

  “The percentage of companies abandoning the majority of their AI initiatives before they reach production has surged from 17% to 42% year over year, with organizations on average reporting that 46% of projects are scrapped between proof of concept and broad adoption“

Podcasts & Videos:

• Intelligence Squared: What Everyone Gets Wrong About Iran, with Clarissa Ward and Lyse Doucet (Part One)

• Gavin Baker back on the Patrick O’Shaughnessy podcast (Invest Like the Best); topics covered:

  • AI Selloff vs. Fundamentals

  • Financing the AI Buildout

  • GPU Prices Keep Rising

  • Claude Moves Markets

  • What Could Break the Thesis

  • The Memory Supply War

  • Nvidia’s New Playbook

  • China and Open Source

  • Data Centers and Regulation

  • SpaceX and Orbital Compute

• New Mohnish Pabrai interview on the New Money YouTube channel; topics covered (embedded further below); table of contents:

  • 0:00 Market Overvaluation

  • 3:20 Berkshire's Future

  • 5:30 Berkshire's Cash Pile

  • 6:57 Buffett's Google Investment

  • 13:30 The Kaspi Play

  • 17:30 How Mohnish Finds Stocks

  • 24:00 Circle of Competence

  • 28:00 Adobe Stock

  • 31:00 The SpaceX IPO

  • 33:30 Elon Musk

  • 35:40 Buffett's "Too Hard" Pile

  • 36:40 Passive Investing Bubble

  • 39:05 Mohnish's Non Negotiables

  • 43:20 Focus

  • 44:05 If Mohnish Started Over...

  • 45:00 Holding Overvalued Compounders

  • 48:10 Private Credit

  • 48:50 Outro

Other:

• modest proposal shared this excerpt on X on changing market structures; I couldn’t find the original source (would love to take a look at the exhibit), so if anyone can help out?

  “There’s been a big change in who is setting prices in the U.S. equity market in the last 15 years, and retail investors and high-frequency quants, including traders employed by investment banks, now comprise the majority of the directional trading activity …“

  

• Barclays has Google’s CapEx at $500 billion in 2028

  

• Charts shared by Tobias Carlisle:

  “Mid and small caps are still valued at roughly a 20-30% discount to large caps, near the cheapest levels in the chart's ~27-year history. Historically such wide discounts have preceded periods of mean-reversion and small-cap outperformance (as happened after 2000). The recent uptick in blue/red lines (bottom-right of chart) suggests a modest recovery in small/mid-cap relative valuations is underway, worth watching if it continues. Second chart shows small-caps have outperformed large-caps by about 11% over the trailing year.“

I was on the podcast of this week, and somewhere in the middle host Siem asked me a question I hadn’t prepared for. Not about a company, or a macro theme, or a mental model. He asked what I actually want to accomplish with my content.

My answer was, more or less, nothing in particular.

No revenue target. No subscriber number. No plan to turn this into something. I first and foremost write because I like writing – and the same could be said about creating video content, sharing insights on X/Substack Notes/Threads, recording podcasts, etc. –, and because I like the work that has to happen before the writing: the reading of company filings, listening to earnings calls, thinking critically and, at times, creatively, doing research on a current them, picking the right valuation model for a company at hand, depending on its profile and maturity, the slow (or sometimes fast) process of a business becoming legible to me.

If I stopped publishing tomorrow, I would probably still do most of it. The publishing part just makes me do it properly. In fact, this is what I like Substack and writing written research notes much better than creating YouTube content. The audience on Substack’s platform allows me to go really deep on companies, the management team, the financials, risks, etc. YouTube rewards videos with mass appeal, with clickbaity titles and thumbnails, shallow analysis that doesn’t go too deep.

Substack is different.

But back to the podcast. I think that answer may sound evasive on the podcast. It isn’t. It’s the most useful thing I’ve figured out in the past six years of creating stock market-related content on various platforms.

Some takeaways and goals (seven in total):

#1 – Producing beats consuming

If I had to name one life-hack that has actually made me happier, it’s this: spend more of your day producing than consuming. Doing as opposed to just sitting around, staring at the wall or doomscrolling your TikTok feed.

Not because producing is virtuous, but because consuming leaves nothing behind. You finish a day of binge-watching a new Netflix series, and you have nothing you can point at. You finish a day of writing, drawing, taking photos, building a map for a video game, recording a tutorial for your university peers, WHATEVER (!), and there’s a thing that didn’t exist that morning, however small, however flawed.

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#2 – Focus on what you can control

The second part of the same idea: point your effort at the things you actually control.

I have no direct control over whether this newsletter reaches 10,000 subscribers. None. That number is a function of the algorithm, the market cycle, whether someone with a big audience happens to restack me on a Tuesday. Treating it as a goal to hit by deadline X is a way of making my mood a function of other people’s decisions.

What I do control is a) the cadence – whether a piece goes out when I said it would, how regularly I show up for my audience. And b) the quality – whether the analysis is deep enough that you couldn’t have gotten it somewhere else.

That’s it.

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 4,600 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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#3 – Attracting the right people

The nice thing about optimizing for quality rather than reach is that it selects your readers for you. I can see this in our WhatsApp community, and it’s the part of this whole “project” I’m most proud of. Nobody is posting rocket emojis. People show up with actual expertise from their actual jobs or their investing background and the research they have done. Everyone is friendly, curious, and useful. I didn’t engineer that. It’s what you get when the front door is a 6,000+-word deep dive rather than a hot take or a shallow analysis.

I like to think of this as a form of survivorship bias. Do you have the attention span to consume deeper critical analyses, or are you looking for easy fixes and answers?

#4 – 1,000 true fans?

A few weeks ago crossed 1,000 paid subscribers, and in the post about it, he referred to Kevin Kelly’s essay, 1,000 True Fans – at least indirectly.

First: what an accomplishment! Congrats to him. I exchanged a couple of DMs with him a few months ago, and he struck me as a genuinely nice person willing to help and support others.

Anyone who has tried to convince even one stranger on the internet to pay for written work knows what a thousand of them represents.

Second: the essay lodged itself in my head and hasn’t left.

Kelly published it on The Technium in March 2008, and a core pillar of the essay is the concept of the “Long Tail” in light of the creator economy. It was the fashionable idea back then and everyone was celebrating what it did for consumers.

“This new ability for the creator to retain the full price is revolutionary, but a second technological innovation amplifies that power further. A fundamental virtue of a peer-to-peer network (like the web) is that the most obscure node is only one click away from the most popular node. In other words the most obscure under-selling book, song, or idea, is only one click away from the best selling book, song or idea. Early in the rise of the web the large aggregators of content and products, such as eBay, Amazon, Netflix, etc, noticed that the total sales of *all* the lowest selling obscure items would equal or in some cases exceed the sales of the few best selling items. Chris Anderson (my successor at Wired) named this effect “The Long Tail,” for the visually graphed shape of the sales distribution curve: a low nearly interminable line of items selling only a few copies per year that form a long “tail” for the abrupt vertical beast of a few bestsellers. But the area of the tail was as big as the head. With that insight, the aggregators had great incentive to encourage audiences to click on the obscure items. They invented recommendation engines and other algorithms to channel attention to the rare creations in the long tail. Even web search companies like Google, Bing, Baidu found it in their interests to reward searchers with the obscure because they could sell ads in the long tail as well. The result was that the most obscure became less obscure.“

However, the “Long Tail” brought its own set of problems:

“The long tail is famously good news for two classes of people; a few lucky aggregators, such as Amazon and Netflix, and 6 billion consumers. Of those two, I think consumers earn the greater reward from the wealth hidden in infinite niches.

But the long tail is a decidedly mixed blessing for creators. Individual artists, producers, inventors and makers are overlooked in the equation. The long tail does not raise the sales of creators much, but it does add massive competition and endless downward pressure on prices. Unless artists become a large aggregator of other artist’s works, the long tail offers no path out of the quiet doldrums of minuscule sales.”

His way out was effectively the concept of “1,000 true fans.”

A creator... needs to acquire only 1,000 True Fans to make a living.

The arithmetic is almost insultingly simple. A “true fan,” according to Kelly, is someone who will buy anything you produce. Get $100 a year from each – Kelly frames it elsewhere in the essay as roughly one day’s wages, which I find an interesting way to think about it – keep the full amount because they pay you directly, and a thousand of them is $100,000. “A living for most folks,” he writes (remember that the piece was released in 2008). Not a fortune. A living.

What made the idea stick with a large audience is his reframing. Kelly’s point is that a thousand is a number a human being can hold in their head. “You might even be able to remember a thousand names. If you added one new true fan per day, it’d only take a few years to gain a thousand.”

5 – But Substack is plateauing and AI is coming for writers …

I’ve read several pieces recently arguing that Substack is plateauing. That writing is doomed as AI is broadly adopted. That the competition has become brutal. That big and small writers alike are struggling to grow at all.

And in the comments under one of my own posts, someone recently made the point that when this exuberant market finally turns – and it will eventually – the appetite for equity research specifically will dry up, and a lot of “us” will stop.

I think all of that is basically right, and none of it changes what I’m doing.

Here’s why:

Every one of those forces is a filter on the median, not on the work. AI has made competent writing easier, almost infinite, which means competent writing (grammar, style, vocabulary) is now worth roughly what it costs. What it has not done, and I don’t think will do anytime soon, is generate the thing that actually moves an investment view: outside-the-box thinking, a mental model built over decades of watching businesses succeed and fail applied to a new analysis, the creative leap of noticing that this company is really the same shape as that one from a different industry twenty years ago, identifying inflection points. Genuine insight. Valuable insight because it is not priced in by the market.

The bull market ending doesn’t destroy that – it just thins out the people who were just in this for a quick buck or the fame.

Over the very long term, anyone who delivers more value than they charge will find an audience. That is a timeless business mechanism.

#6 – The part I’m bad at

The uncomfortable corollary is that providing value and being found are two different problems.

wrote something in early July in an article that genuinely deflated me for an hour:

“Not every investment has an equal reward. This is equally true in business as it is in Substack. To date, all of my posts combined have brought me a total of 98 subscribers. My top performing (and first ever) note has also brought me exactly 98 subscribers. My posts have taken hundreds of hours of painstaking research, writing and editing. My note took me about 10 minutes to write.”

I know this feeling in my bones. I have published pieces that cost me three weekends and a fair chunk of my sanity and added, net, zero subscribers.

That is not a rare event. That is a normal Tuesday.

Want to see a current example? Below you see the stats of yesterday’s write-up “8 Signs the AI Bubble Is Further Along Than You Think“ that has genuinely done quite well in terms of likes received and comments shared. New subscribers added: 1.

Or my latest deep dive on Amadeus IT Group, which I spent hours and hours researching (+ building a valuation model, + creating a custom slide deck) while on holiday. One new free subscriber. Zero new paying subscribers.

I think this is another advantage I may have over some other investors who aren’t in this for the long run. I love studying businesses. So sure, there are brief moments of disappointment. But usually I just shrug for a moment and then move on. On to the next deep dive!

Kelly is blunt about this in the essay, too, and it’s the paragraph I keep skipping over and shouldn’t. Cultivating true fans is …

“time consuming, sometimes nerve racking, and not for everyone.”

Some creators, he says, “should just paint, or sew, or make music” and let somebody else handle the fans. That’s me. I would rather spend eleven hours reconstructing a segment’s true economics than eleven minutes writing a note about it.

#7 – Because the A in SMART stands for attainable

So why am I still writing down a number?

The old SMART framework is a corporate cliché at this point, but the A is what I had to think of regardless. Goals are supposed to be attainable – stretchy enough to pull you forward, plausible enough that your brain doesn’t file them under fantasy and stop trying.

A million readers is not attainable (for me at least) and, worse, it isn’t even meaningful as a target. Kelly says this directly: “Millions of paying fans is not a realistic goal to shoot for, especially when you are starting out. But a thousand fans is doable.”

And here’s the part that makes me think it isn’t arrogance to say it out loud: There are hundreds of millions of people investing globally. If one in a million of them wants what I specifically offer – global equity research for people who love businesses, obsessed with quality and disciplined valuation, no hype, deep analytical work for the patient minority – that’s still a large enough pool. Compared to some other nichés, the investing TAM is absolutely massive!

Kelly’s line: “any 1-in-a-million appeal can find 1,000 true fans. The trick is to practically find those fans, or more accurately, to have them find you.”

I’m confident in the work. As outlined, not yet in the marketing. But I will try to do better on that front too. And I’m learning from others too – both big (such as or ) and small (such as , , or )

And of course you can help me to by spreading the word, leaving a comment occasionally, restacking a write-up. You might want to start right now?

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Wrapping up

We’re closing in on 5,000 free subscribers. Eighteen months ago that number was one, and it was me. My YouTube audience gave me a 100 subscriber boost, but that was about it (generally, I’ve found that YouTube subscribers translate very poorly to blog subscribers).

I don’t take it for granted, and I’m aware of how much of it is timing, luck, and the generosity of people who restacked something when they didn’t have to.

A thousand true fans is a long way off. A very long way in fact. I might never get there. But one can dream big, right?

The market may turn, the appetite for this kind of work may thin out, and the honest answer is that most of that is outside my control anyway. But the target is doing something useful in the meantime: it keeps me pointed at depth instead of reach, at the hundred people who read every word instead of the ten thousand who opened one thing once.

Kelly calls it “a much saner destiny to hope for.” I’ll take that. And in the meantime, the only two things I actually control are showing up on schedule and doing work that’s worth your time.

That, I can promise.

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On the morning of July 30, a hedge fund sold its entire public equity portfolio in a single block trade before the opening bell. Longs and shorts together, the whole book, handed to Citadel in one transaction. Six trading days earlier, that same portfolio was sitting on a 439% net return for the year.

Ooops!

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The fund we’re talking about – you already know it – is Situational Awareness LP, run by Leopold Aschenbrenner, who is twenty-four years old and wrote what a lot of people consider the defining investment memo of the AGI era.

He had turned roughly $225 million of seed capital into a book worth tens of billions in under two years. Reports on the exact size vary quite a bit, somewhere between $20 billion and $45 billion depending on which outlet you read.

Apparently using 4x gross leverage, concentrated across the AI infrastructure stack:

• power generation,

• data centers,

• memory.

Then Korean semiconductors wobbled. Under a week later, it was finished.

I published a piece in early June called “Navigating the Froth: 6 Alternative Signs of a Market Top,“ where I laid out six alternative signs that we were somewhere late in this cycle.

• Chip workers in Seoul buying Ferraris with their bonuses.

• Jensen Huang being chased through a Taipei night market by food bloggers.

• Three private companies queuing up to go public at a trillion dollars each.

• Berkshire’s cash pile going vertical.

• And more.

Those six had something in common that I did not fully appreciate when I wrote them. You could see all of them from across the room.

There is a line on my Market Sentiment Cheat Sheet that has aged well: bottoms scream, tops whisper.

In the weeks since that piece, the whispers have moved somewhere considerably harder to look. Into special purpose vehicles. Into lease classifications. Into a single sentence about useful-life assumptions in an earnings call.

Before we start, let me deal with an objection I hear most often these days:

We cannot be in a bubble if this many people are calling it a bubble.

I don’t find that argument persuasive for a straightforward reason: you are not observing the market when you scroll your feed, you are observing an algorithm that has learned what keeps you engaged. Fintwit did not exist in 1999. It did not exist in 2007. The fact that your timeline is saturated with bubble talk tells you something about your timeline, your echo chamber, but very little about aggregate positioning.

And positioning is the thing. Saying you think the market is expensive costs nothing. What people are doing with their money looks quite different from what they are saying with their words. That’s one of the first principles I learned about Buffett - watch what he does, and not what he says.

In this piece, I want to discuss eight new signs that we may be approaching a market top and the end of the long-lasting bull run.

Here is the structure:

1. Systemic Leverage

2. When the Supplier Becomes the Customer’s Bank

3. The Cash Flow Machines Start Borrowing

4. Reading the Footnotes Instead of the Headline

5. Common Sense ROIIC Check – The Arithmetic Nobody Wants To Confront

6. The Electricity May Not Exist

7. The Customers Aren’t Getting Their Money’s Worth

8. Common Sense Test #2 – This Time: Valuation

9. Final Thoughts

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.

1. System Leverage – Aschenbrenner Is Just One Anecdote

Aschenbrenner’s thesis was arguably right. Power, data centers, and memory were precisely where the money went in 2025 and the first half of 2026. What ended him was the financing structure sitting on top of that thesis.

Run four times gross leverage and a 25% drawdown erases your equity. You lose the option of being right eventually. Your prime broker decides when the position closes, and makes that call during the worst week rather than the best one.

Note what did the damage. Korean semiconductors, specifically the pressure around SK Hynix’s US listing. In my June piece, I wrote about the KOSPI as a national index trading with the volatility of a micro cap, more than half its weight in two chip companies. Concentration of that sort is wonderful on the way up.

One fund blowing up may be an anecdote. I get that. But this isn’t a single incident. It is more systemic.

In mid-July, apparently, 1 in 30 (3.4%) adults got margin called.

FINRA margin debt, the total amount of money that investors borrow from their brokerage firms to buy stocks and other securities using their current investments as collateral, hit $1.502 trillion in June, an all-time high, up 51.5% year over year and still up 46.3% after inflation.

As I argued in June, this indicator on its own is a lousy timing tool. What it measures well is fragility, which tells you how violent the adjustment will be when things go south, without telling you when exactly.

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And the metric above may even understate how levered up investors are, possibly badly, because it captures margin lending at broker-dealers while missing the leverage embedded inside the products retail increasingly buys as default exposure.

Nobody holding those products will ever get a margin call, and that is the problem. When an individual buys a leveraged ETF (like a 3x S&P 500 fund), the leverage exists inside the fund's structure via total return swaps and futures contracts. A daily-reset fund must thus rebalance at the close to maintain its target multiple, so it mechanically sells into declines. The forced selling still happens, on schedule, inside the fund, without anyone experiencing the moment of panic that would normally make an investor reconsider what they own.

• When the market goes UP: The fund’s asset base grows faster than its debt/exposure ratio. To restore a 3x target for the next day, it must buy more exposure at higher prices.

• When the market goes DOWN: The fund’s assets shrink faster than its exposure. To bring its leverage ratio back down to 3x (and avoid being over-leveraged for the next day), it must sell exposure at lower prices.

Related to this, I guess, made an observation that stuck with me (read his thoughts here): watch how fast people dump enormous, established businesses on a single bad headline. Few built their position by understanding the firm well enough to hold through a bad quarter, so they use trailing stops, then buy back after the recovery. Li Lu once called rotation the rarest gift in investing. What we have instead is a market where much of the float is held by people who pre-committed to selling at a price rather than at a thesis, on record margin, in products that liquidate themselves on the way down.

A levered holder is not really a holder. They are a renter, and the margin clerk owns the building.

2. When the Supplier Becomes the Customer’s Bank

Nvidia is reportedly in talks to backstop as much as $250 billion so OpenAI can lease computing power from a ten-gigawatt project in Pike County, Ohio, with a separate arrangement to help finance OpenAI’s purchase of some $350 billion of chips. Bloomberg puts the total slate of fresh deals above $750 billion.

“Nvidia Corp. is working on AI infrastructure deals potentially worth more than $750 billion, including an artificial intelligence initiative with SK Hynix Inc.’s parent worth more than $500 billion.” - Bloomberg

Here is the number that made me put my coffee down (admittedly, I looked a little more shocked than in the image below) …

Nvidia’s own Q1 fiscal 2027 10-Q caps total lease-guarantee exposure at $3.5 billion.

A $250 billion commitment would run roughly seventy-one times the entire guarantee book it currently discloses.

How times can change.

The term “circular financing” gets thrown around frequently these days without much precision. A supplier provides capital, or a guarantee that unlocks someone else’s capital, to a customer, who then buys the supplier’s product. The supplier books revenue at shipment while the risk moves onto its balance sheet. Demand looks robust, growth looks organic, and the accounts record something economically closer to the supplier buying its own products with extra steps.

The bull response is that these arrangements are immaterial at Nvidia’s scale.

The writer behind Dirt Cheap Stocks gave the most economical rebuttal I have read in his piece from two months ago titled “Calling the Top“:

“if it’s immaterial, why would you engage in the behavior at all?”

We ran this experiment in 1999, when telecom equipment makers lent enormous sums to carriers so those carriers could buy equipment. Lucent alone committed $8.1 billion, and McKinsey later put nine suppliers’ combined exposure around $25.6 billion. The customers could never generate the revenue to repay, Lucent’s sales fell 69% from their peak, and it wrote off roughly $3.5 billion of customer loans.

The detail worth holding onto is what the vendors did as conditions deteriorated. When outside capital fled in early 2001, they accelerated financing rather than pulling back, because slowing down meant admitting the previous two years of revenue were partly manufactured. That entire nine-supplier complex committed about $47 billion in today’s money (accounting for ~80–85% cumulative inflation over the past 25 years).

In today’s instance, we are discussing one supplier contemplating $250 billion.

One other number in Nvidia’s filings stands out too: the share of its receivables tied to major customers has gone from an average of roughly 23.8% across fiscal 2020 to 2024 to about 64% in its latest quarter.

“Three direct customers accounted for 30%, 18%, and 16% of our accounts receivable balance as of April 26, 2026. Three direct customers accounted for 25%, 18%, and 13% of our accounts receivable balance as of January 25, 2026.”

Of course, during fiscal years 2020 through 2024, Nvidia’s business was far more balanced across PC gaming, professional visualization, and automotive clients, and as the generative AI boom accelerated through FY2025 and FY2026, Nvidia’s Data Center segment expanded to represent nearly 90% of total company revenue. Still, I find this a remarkable level of concentration.

Now, this heavy customer concentration is a direct structural byproduct of the hyper-consolidated AI infrastructure boom. Because training and deploying frontier AI systems requires tens of billions of dollars per quarter in capital expenditure, purchasing power is concentrated almost exclusively among a small circle of hyperscalers (widely identified by Wall Street as Microsoft, Meta, and Amazon) alongside key server integrators. Clearly, those are cash-flowing machines throwing of billions and billions in cash flow. But the required CapEx may be too much of a burden even for those players, which leads to signal number 3.

3. The Cash Flow Machines Start Borrowing

For fifteen years, the defining financial trait of big tech was that it did not need anyone’s money. Microsoft still carries a AAA rating, one of two left in America. That era has ended fast enough that most investors have not repriced what these companies now are.

Amazon, Alphabet, Meta and Oracle issued roughly $194 billion of bonds in 2026 through July 7 alone, according to Reuters' analysis, against about $108 billion in all of 2025. Meta’s October deal was $30 billion in one shot, the largest individual non-M&A high-grade bond sale on record. Oracle is the one to watch, sitting at BBB while participating in the same build-out as counterparties rated AAA. The marginal borrower always breaks first.

What concerns me more is largely invisible on the balance sheet. Meta’s Hyperion campus is financed through a vehicle called Beignet Investor LLC, which raised roughly $27 billion in private notes from Pimco, BlackRock and Apollo. Blue Owl holds 80%, Meta 20%. Because Meta is a minority partner, that $27 billion never appears as a liability in its accounts. It’s an off-balance sheet liability – another late-cycle symptom?

Meta also provides a residual value guarantee covering the first sixteen years. If the campus is worth less than an agreed threshold when a lease ends, Meta makes up the shortfall in cash. Read that again and ask who bears the asset risk. The debt moved. The risk did not. IFR (International Financing Review), about as sober a credit publication as exists, ran its analysis under the headline “off-balance-sheet gymnastics 24 years after Enron.”

“The contradiction at the heart of Meta’s Hyperion financing is between the bond ratings and Meta’s proposed accounting treatment. If you follow the cash, Beignet’s bond is almost pure Meta exposure. Meta funds the construction risk; Meta’s rent and Meta’s residual value guarantee service the debt; and Meta is the party that suffers if demand for AI computing disappoints.

If Meta ever walks away from the project, the RVG obliges it to write a cheque that, together with whatever the campus (or part thereof) can be sold for, makes bondholders whole. The RVG runs for 16 years and is triggered if Meta fails to renew a lease at expiry, terminates early or defaults under the lease. Any one of these leads to a payment of a “guaranteed minimum value” that is sized so the bond can be repaid, either from the underlying sale proceeds or directly by Meta. The final four years of the bond are not covered by the RVG but by a termination fee equal to the outstanding balance at that point.“ - IFR

Debt has been trending upward across all Big Tech names …

… and Meta stands out to me here as the quality of its balance sheet has deteriorated the most in terms of total debt recently.

One exchange from Meta’s latest call is also worth your attention. Youssef Squali asked Susan Li directly about the growing pile of off-balance-sheet obligations and whether Meta would consider issuing equity to fund some of this. She pointed him to the disclosures and said they would evaluate all financing options for 2027. She did not rule out equity. A CFO with a comfortable funding picture rules out equity, because doing so is free and reassuring.

The reason shows up in the cash flow forecasts. Alphabet just reported its first quarter of negative FCF in its history.

Meta’s is expected to turn negative in 2026 and reach around negative $24 billion in 2027. Amazon’s is projected to be negative this year.

Companies do not borrow at this scale because borrowing is cheap. They borrow because internal cash no longer covers the plan.

4. Reading the Footnotes Instead of the Headline

Microsoft reported in late July and one of the headlines that was picked up by the investing media was a CapEx reduction, with 2026 guidance falling from roughly $190 billion to around $175 billion.

The stock rose after hours and the next trading day. Microsoft added nearly $450 billion in market value on Thursday, the largest one-day gain on record for a company. To be fair, it was a great quarter overall. Some coverage treated the CapEx cut as the first evidence of spending discipline from a hyperscaler.

Nothing was a real cut.

Effective at the start of fiscal 2027, Microsoft is extending the estimated useful life of its data centers and office buildings from 15 years to 25. That lowers annual depreciation and lifts reported earnings on assets it was building anyway. It also changes lease classification, moving future data center leases from finance leases into operating leases, and finance leases count in reported capex while operating leases do not. The $15 billion came out of the line item rather than the budget.

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, who flagged this as one of the first in a Substack Note, asked the two questions I have yet to see answered.

• Why this?

• Why now?

Consider the same quarter’s other disclosures. CapEx including finance leases hit $41 billion, up roughly 70%.

There is sort of a control experiment available. Effective January 2025, Amazon shortened the useful life of a subset of its servers from six years to five, citing the increasing pace of AI development, and accepted a roughly $0.7 billion hit to operating income for it. Servers are not buildings, and I want to be fair about that. Maybe that useful life extension is entirely justified. But when assumptions get adjusted, they mostly get adjusted in the direction that flatters the company and the income statement, and usually when it most needs the “help.”

Hence the practical takeaway, which is the most useful thing in this piece if you own any of these businesses, might be that for hyperscalers, the income statement has become the less informative of the two documents, because accrual accounting hands management wide discretion over depreciation, lease classification and capitalization.

Work from the cash flow statement instead, consider the free cash flow the company actually produces, and then adjust by hand: add back growth investments (maybe also from the income statement; e.g. R&D) and form your own view on how much CapEx is actually maintenance dressed as growth CapEx by comments made by management.

5. Common Sense ROIIC Check – The Arithmetic Nobody Wants To Confront

The four big hyperscalers – Amazon, Microsoft, Alphabet, and Meta – will spend somewhere around $700 billion on capex in 2026. Estimates range from $630 billion to $750 billion depending on definitions (might even be higher after recent guidance updates).

Against that, here is what they earn.

• Alphabet made about $244 billion over the last twelve months

• Microsoft $133 billion,

• Amazon roughly $135 billion,

• Meta about $68 billion.

Call it $580 billion combined.

They are spending, in a single year, a little above 1.3x what all four of them earn.

Now run a back-of-the-envelope ROIIC calculation, which almost nobody in financial media seems willing to do out loud. A 15% return on incremental invested capital is a reasonable bar for businesses of this quality. On $700 billion, that requires about $105 billion of additional annual after-tax earnings in perpetuity, so combined profits would need to rise 18% and stay there, purely to justify one year of spending. And 2026 is not a one-off, with roughly $400 billion spent in 2025 and forecasts for 2027 higher still.

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Let me be precise about what that actually means, because it is easy to get that wrong. It is a permanent step up in the level of profits. The 2026 spend does not require earnings to compound at 15% a year. But it requires them to be $105 billion higher, forever.

The trouble is that the steps stack!

• The roughly $400 billion spent in 2025 needs $60 billion of permanent additional profit.

• The 2026 spend needs another $105 billion.

• And 2027 estimates from Evercore, Bank of America and Moody’s now sit above $1 trillion, which asks for a further $150 billion. Barclays has Google's 2028 CapEx alone at $500 billion.

Three years of building, about $2.1 trillion, therefore requires some $315 billion of extra annual profit held in perpetuity.

And that assumes the spending stops in 2027, which nobody expects. Goldman models $5.3 trillion of capex across these four companies from 2025 through 2030. At 15%, that needs roughly $795 billion of incremental annual profit, putting combined earnings around $1.4 trillion.

The entire S&P 500 currently earns something like $2.3 trillion, so four companies would have to generate about half the index’s present profit pool.

There is a cleaner way to see why this might not work as advertised. Sustainable growth equals return on capital multiplied by reinvestment rate. Capex against earnings runs above 100%. But you cannot reinvest more than you earn out of what you earn, and that gap is precisely the bond issuance and the special purpose vehicles you start to see (discussed in #3).

A second framing avoids hurdle rates entirely. Depreciate $2.1 trillion over five years (which is too strict, I admit that, because data centers have a longer useful life than the servers, but let’s run with it for illustrative purposes) and you generate about $420 billion of annual depreciation, which exceeds what all four companies earned in 2025.

Some of that replaces charges rolling off older assets, so treat the figure as directional. The direction is not comforting, though, and it is exactly why the useful-life assumptions in the previous section matter. Lengthening the schedule is the main lever for making the income statement look attractive.

It changes nothing about the cash flow dynamics, though.

Maybe it works. AI is a genuine technology with genuine applications and I have no interest in pretending otherwise. But the burden of proof on that capital is enormous today.

PS: John Huber shared some fantastic thoughts on this as well, adding some additional angles and perspectives to consider (check out his follow-up response in the comments as well):

PSS: I wrote about this before:

PSSS: An intelligent comment by :

6. The Electricity May Not Exist

All of the above assumes the build-out can actually be completed, which is not entirely clear if you look at the physical supply chain.

In Northern Virginia, Phoenix, and Dallas, where much of the announced capacity is being sited, waits for a grid connection now run four to seven years (and sometimes even extending up to 14 years).

Substation transformer, a large electrical device that changes voltage levels, transfers power between the grid and consumers, and maintains safe energy flow using electromagnetic induction, lead times have gone from about 140 weeks in 2023 to over 160 weeks today. Gas turbine backlogs at GE Vernova, Siemens Energy and Mitsubishi Power, who between them supply two-thirds of the gas plants under construction worldwide, now stretch as long as eight years. Grid operators are openly saying demand is growing faster than any historical trend they can model against.

Do you see the mismatch?

A GPU can be delivered in weeks. The electricity to run it takes years, and in the worst locations the better part of a decade.

“Artificial intelligence (AI) technology is advancing at an extraordinary pace. At the same time, the computing power used to train frontier AI models has been doubling every five to six months. Unlike the semiconductor scaling that defined previous technological eras, this growth is driven not by shrinking transistors but by deploying ever-larger chip clusters.

Combined with the scale of investment in data and computing infrastructure, this progress is already transforming entire industries. But the energy system must keep pace for progress to continue. This shift from silicon efficiency to physical scale is precisely why grid connectivity has become the binding constraint.“ - weforum

That GPU begins depreciating the day it is finished putting together, on a five or six year schedule, which is shorter (!) than the interconnection wait in three of the largest data center markets in America. Depreciation does not pause while you wait for a transformer.

The politics are turning too. The Economist has asked whether the data center backlash will derail the boom, reporting that opposition has made suitable sites genuinely hard to find, and the environmental argument got harder to wave away once Google and Microsoft both walked back carbon commitments to accommodate the build.

If you go back to sign #6, the hurdle to clear 15% ROIICs in light of these constraints may get harder.

In fairness, delayed is not cancelled, and hyperscalers have flexibility about where they build. Data centers in space are proposed, which are orbital facilities designed to handle energy-intensive computing and AI workloads using continuous solar power and radiative cooling, driven by companies like SpaceX and Blue Origin.

But there is the potential that the returns arrive later than underwritten, and where the asset depreciates whether or not it is plugged in, later is expensive.

7. The Customers Aren’t Getting Their Money’s Worth

Some of the signs above discussed so far concern the supply side.

But none of those concerns matter much if the demand is not genuinely there

So the question that decides this is whether enterprises buying AI services are actually getting a return. And it seems like there is more skepticism these days, in some organizations at least, compared to 12 to 24 months ago.

An MIT study drawing on 52 executive interviews, surveys of 153 leaders and analysis of 300 public deployments found that roughly 95% of enterprise generative AI pilots delivered no measurable impact on profit and loss.

“Zero return.”

S&P Global found 42% of companies abandoned most of their AI projects during 2025.

“The percentage of companies abandoning the majority of their AI initiatives before they reach production has surged from 17% to 42% year over year, with organizations on average reporting that 46% of projects are scrapped between proof of concept and broad adoption“

You can quibble with any single study, and you might want to take a look at the underlying methodology, but it seems like there is a growing, serious body of evidence – beyond anecdotes – pointing towards similar findings

The case study of Ford may be brought up here too, just because it might even make you laugh out loud …

WHAT WERE THEY THINKING?

The company pulled experienced staff off quality control and replaced them with AI, and has since been recalling those workers because the AI was less concerned about quality than the people were.

One anecdote, granted, though the kind that tends to appear at the front of a trend.

There is arguably a structural reason so much of this went ahead, and it has little to do with clear and visible ROIC thresholds being hit. Many large enterprises piled in partly because they believed their own investors expected to see it. Announcing an AI initiative, and declining to announce one was expensive from a reputational point of view or may negatively affect stock prices of publicly listed firms. That produces enormous spending never underwritten to a return, which is the first spending to go when budgets tighten.

Two more details worth highlighting:

• Some operators have started selling excess AI capacity into the secondary market, which is hard to square with demand exceeding supply by the margins implied in the capex plans.

  

• And the industry charges for usage rather than outcomes, so a clumsy implementation that burns tokens produces more revenue than an efficient one. A meaningful portion of AI revenue therefore measures how wastefully the technology is being applied, and compresses as customers improve.

8. Common Sense Test #2 – This Time: Valuation

The Shiller CAPE stands at an almost record high of 40.9x as I write this …

…, against an all-time record of 44.2x in December 1999 and a long-run median near 16 (16.1x).

Nvidia, Microsoft, Amazon, Meta, Broadcom, and Google – six names – alone represent almost 28% of the index.

According to Goldman, as of three months ago, “AI companies” make up 45% of the index (probably a rather broad definition to be fair).

Back to valuation … Again, there is one prior period in the history of the series at these levels: late 1999 into early 2000. Exactly one!

That is not a timing signal, as I outlined in my last piece referenced above (I’ll insert the lovely illustration again here), and I will keep saying so.

“… of |the] seven leading indicators studied, none have consistently predicted major market declines dating back to 1950. Even the most consistent indicators provided a warning signal for only about half of major declines. “ [note: A major decline in this study was defined as a decline of 10% or greater from the S&P 500’s most recent all-time high]

Anyone who went to cash on CAPE in 2015 – when it reached almsot 27x (way above the median) has been thoroughly punished.

I still believe, however, that starting valuation matters for the subsequent long-term returns. And I’ll admit that in the current environment you might have to shift your definition of “long-term” to 20 years+ because the high starting valuations from 2015 didn’t stop the S&P from performing incredibly well over the subsequent 10-11 years.

Of course, you could bring up some structural changes that justify higher multiples for US stocks – multiples are just a shorthand after all –, and I wrote about it in the piece linked below (different margin and growth profiles, outdated accounting standards, the composition of the index, global diversification, etc.); I recommend reading it to come to a balanced, well-informed view yourself.

Nonetheless, let me run a simple valuation exercise here, an exercise that Dirt Cheap Stocks used in his piece already, and one of the valuation approaches I favor myself.

You are currently buying the S&P at roughly 28.9x earnings with a dividend yield near 1%.

Want 10% a year for a decade? (roughly in line with the S&P’s long-term returns) Earnings have to compound at about 9%, and the multiple has to still be 28x times when you sell (a multiple well above the historical median; but as outlined in the write-up I linked above, that may be justified too). Long-run S&P earnings growth has been around 6% to 6.5%, so the bull case needs a permanent step-change in the earnings growth rate of the largest economy on earth while the most expensive multiple in twenty-six years does not compress at all.

To be fair, a 28x multiple translates into a 3.5% yield. Deduct 1% required to pay out the dividend (largely in line with the aggregate dividend payout ratio for the S&P 500 Index being approximately 30.5% right now), and that leaves you with 2.5% to buy back shares (that’s the absolute ceiling) and boost EPS. Historically, the 2-2.5% may be gross buybacks (before SBC effects), and only half of it is a net reduction in shares (1-1.25%).

But what if the multiple ever drops? If over a ten-year time frame (note: the longer your time horizon, the more negligible the impact of multiple changes), the multiple reverts back to the low 20s, earnings compound at 6%, an annual share reduction of around 1% (net) plus the dividend yield of 1%, and you end up with annual returns of about 5% compounded.

I’ll spare you the math for lower exit multiples.

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But hey, if AI keeps progressing at the current pace, we all will never have to work again, right?

Final Thoughts

I should be straightforward about my record. I have thought this market expensive for some time, and being expensive has not stopped it going up. I have no idea whether this turns in two months or two years or ten years. I would have been reasonably confident about multiple mean reversion over a 10-15 year time frame a few years ago. Today, I’m not anymore.

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Still, none of this changes how I invest. I prefer buying asset-light companies, trading at cheap normalized multiples, with clear growth drivers and structural tailwinds and a great deal of visibility in terms of ROIIC and reinvestment rates.

Also, look again at how this started. Aschenbrenner was substantially right about the direction of AI infrastructure, and being right did not save him, because he had built a position that required the market to agree with him on a schedule.

That thread runs through all eight signs: Circular financing, off-balance-sheet structures, stretched depreciation schedules, record margin balances, capital committed against a grid that cannot deliver, possibly for seven years or more. To me it seems like they too, in a way, shorten the time you have to be proven correct.

The “whispers” this time are in footnotes, lease classifications and interconnection queues, harder to hear than Ferraris in Seoul (reference to my initial piece; which you might want to read next).

What is visible gets priced immediately. What requires reading between the lines, connecting the dots, some intuition and common sense, may not.

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.

Consider that on July 23, 2026, just days before I’m writing this, the skies saw the busiest day for commercial air travel in history, with Flightradar24 tracking a staggering 153,359 commercial flights around the world.

A record share of those journeys touched Amadeus somewhere along the way. Every time you book a flight, check into a hotel, or watch your boarding pass load onto your phone, there’s a strong chance the transaction ran through a company most travelers couldn’t name if their connection depended on it.

The numbers behind that anonymity are hard to fathom. Amadeus processes more than two billion boarded passengers a year, handles up to 150,000 transactions per second at peak, and fields something like three billion search requests a day. That’s a data-processing load in the same neighborhood as Google Search, humming away inside an infrastructure business that trades on the Madrid exchange and rarely makes a headline outside the trade press.

If the system is down, the plane does not take off. When a streaming service goes dark, you’re annoyed. When Amadeus goes dark, aircraft stay on the ground and airports descend into chaos.

As I type this, American Airlines flights were stopped from departing after a brief IT outage led to a nationwide ground stop. A “technology issue briefly impacted connectivity” for some systems, the airline said in a statement. “Connectivity has been fully restored. We apologize to our customers for the inconvenience. We appreciate the efforts of our team to bring our systems back online so quickly and take care of our customers.” (shoutout to for sharing this with me today).

“Looks like AA uses a mix of Sabre and outsourced solutions to India. Not a good look and costs millions.“ -

It is the SAP of airlines, running check-in, luggage handling, and departure control with near-zero tolerance for error, which is why the company holds itself to a 99.99% uptime standard. Half a day of downtime would cascade into mass cancellations across the globe.

That is the definition of mission-critical, and it’s the kind of position most less-embedded software companies would trade a decade of growth to occupy.

So here is the puzzle that pulled me into this name. Over the last ten years, Amadeus grew. Revenue compounded at roughly 5% a year, EBIT at about the same, and earnings per share at close to 7%. The business got bigger, more profitable, and more entrenched.

As many stocks that attractive me or catch my attention, the stock did almost nothing. A shareholder who bought ten years ago has earned an annualized price return of around 2%, and the picture gets worse as you shorten the window: negative over five years, and worse still over three (-9.5% CAGR). As I write, the shares sit about 34% below their peak. A company that kept compounding, and a share price that went sideways for a decade. When those two lines diverge that far for that long, one of them is usually wrong, even if the starting valuation was clearly too high.

And once again, – and there are strong similarities to our Workiva analysis – it all comes down to a single word:

AI.

The prevailing fear is that agentic search and chatbots will disintermediate the distribution layer, letting airlines and travelers route around the middleman and cut Amadeus out of the flow. That anxiety has compressed the valuation from a historical norm in the mid-20s times earnings down to roughly 16x trailing and under 14x forward, with the stock changing hands at about 16x free cash flow (please note that the FCF multiple display below is off as it doesn’t account for “payments for intangible assets”).

The multiple did the damage here, not the fundamentals.

And I think the story behind it has the causation backwards. My reading, which I’ll spend this piece testing (rather than assuming), is that AI is less a threat to Amadeus than a customer of it. The large language models supply the brains for travel planning. They lack the plumbing to touch legacy airline systems, live pricing, and the deterministic record that makes a booking valid, legal, and operational. Amadeus is that plumbing, and it’s the neutral orchestrator airlines trust precisely because it isn’t Google.

There’s a new, a stranger chapter still. Amadeus is becoming an identity company. Through its acquisition of Idemia Public Security and the rollout of biometric corridors in places like Jakarta, it’s building a world of seamless travel where you clear borders and board planes without ever producing a document, verified on the move by facial recognition that has multiplied border-crossing capacity tenfold in early deployments. A future without passports, orchestrated by a former airline-booking consortium. Which is a fitting turn for a company that started life in 1987 when Lufthansa, Air France, Iberia, and SAS banded together to build a shared, neutral platform for an industry that couldn’t agree on much else. Nearly four decades later, that consortium has grown into what analysts affectionately call a friendly gorilla, a business with more than 50% market share that wins by being a channel friend to its customers rather than a toll they resent.

That’s the tension I want to work through in the pages that follow. A dominant, mission-critical, cash-generative business, priced by the market as if its best days are behind it.

And the timing is pointed, because Amadeus reports this Friday (as I type this, I’m not sure I will be able to release before the quarterly results. Please keep in mind that the analysis below was conducted pre-Q2 results). If you’ve never studied the name, this is the week to fix that, since a set of numbers landing against a beaten-down multiple is exactly the setup where a misunderstood business can move.

What this deep dive covers:

We cover the key thesis in about 10,000 words:

• The seven-part bull case (”Bam Bam Bam Bam Bam Bam Bam”)

• 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.

    

  • I do want to stress that this time I built the slide deck with Claude’s Opus 5 and the result blew me away! I think the deck is really really good!

If you then want to dig even deeper, we cover the business, the management team, detailed valuation work, etc. in the subsequent sections one more time:

• The origin story

• The business itself

• Unit economics analysis

• The customer

• Legal structure, cyclicality, and operating leverage

• 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 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.

“Bam Bam Bam Bam Bam”-Hypothesis

Why look at Amadeus now you may ask? Well, Amadeus may currently be severely mispriced, trading at a roughly 40% discount to its historical multiples due to overstated AI disintermediation fears that have overwhelmed its fundamental performance. What the market may be missing is that Amadeus is entering a “harvesting phase” where seven years of heavy R&D and cloud migration costs are shifting into a high-margin revenue driver, specifically through the “black box” of Nevio’s superior unit economics.

This may create a compelling entry point for a business that acts as the essential infrastructure layer AI agents require to operate reliably at scale.

As always, one deliberate choice in how I’ve framed this, and it isn’t pedantry. I intentionally call this an investment hypothesis rather than a “statement of belief” or a thesis. While a thesis often encourages a search for confirmatory data, this hypothesis remains unverified and is built to be actively stress-tested and falsified in the subsequent sections. My objective is not to find information that supports my view, but to attempt to falsify the claim that AI will disintermediate the distribution layer or that airlines can economically replace their mission-critical IT “nervous systems.” Keep that posture in mind as you read.

Bam #1: The Gorilla in the Plumbing

Amadeus’s oligopolistic dominance is the result of a decades-long compounding effect where scale, technological reinvestment, and network effects have created a nearly insurmountable lead over most of its peers. Industry insiders often call it the “gorilla of travel IT,” and the label fits.

“I think the best way of summarizing the business is as the gorilla of travel IT, but a friendly gorilla which is able to grow well ahead of a structurally growing market i.e. travel and importantly this is in a low risk way, given its diversification across geography and travel provider customer, and the inflation linked nature of how the revenue model works.“ - Business Breakdowns episode on Amadeus

Amadeus operates as the essential plumbing for the global travel industry, the nervous system that unobtrusively routes the signals every airline, agency, and traveler depends on without ever thinking about it.

In its core segments, Amadeus commands a position that is frequently a multiple the size of its nearest competitor.

On the IT side, it is the primary system of record for over 50% of the world’s airlines, processing roughly 2.2 billion passengers boarded each year. That’s about 46% of total global air traffic flowing through one company’s software. The dominance is most visible where it matters most commercially, at the top of the market: 50 of the top 50 airlines globally run Amadeus’s Passenger Service Systems, whether that’s the legacy Altea platform or New Skies.

• Amadeus Altéa: A comprehensive Passenger Service System (PSS) designed primarily for full-service, network, and legacy airlines to manage end-to-end flight reservations, seat inventory, and airport departure control.

• Navitaire New Skies (by Amadeus): A digital-first, ticketless PSS tailored for low-cost (LCC) and hybrid carriers, optimized for direct distribution, high-volume ancillary retailing, and web-centric bookings.

In the Global Distribution System market, Amadeus holds a 55% share, sitting well ahead of Sabre at around 35% and Travelport at roughly 10%.

This is where it gets interesting!

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Hi, we’re The Dutch Investors.

The three of us share one habit: an obsession with investing to the point it has bored our partners. But then, about 3 years ago, we met and were able to share our passions. We could (and still can) rant for hours.

We founded TDI because we wanted a place to discuss businesses, analyze stocks, learn together, and compound wealth together. Our goal is simple: to expand your investing universe.

This article aims to introduce you to three unusual and (hopefully) unknown Dutch businesses we think are run by competent management, have a sustainable competitive advantage, and are of high quality.

We tried to stay away from the Dutch companies you’re already familiar with. They’re not the usual suspects. We could have picked ASML, Heineken, Shell, Booking, Prosus, or Ahold Delhaize. Wonderful companies, all of them. But you already know them, and so does every other investor. There is no edge to be gained there. The three companies below are smaller, less known, and run by capable management.

Company Idea 1: Nedap N.V.

🏢 Company name: Nedap N.V.
⌛CAGR since IPO: 11.2%
✨ Market Cap: ~€650 million
📊 Revenue FY25: ~€296 million

If you are not Dutch, chances are small that you know Nedap. It is one of the reasons why this company might be even more exciting to you.

You probably know Amsterdam and The Hague, perhaps Rotterdam and Utrecht. Nedap is not located in any of these cities. The company has its headquarters located in Groenlo, a small village in the East of the Netherlands with around 10,000 inhabitants near the German border.

Former CEO Ruben Wegman studied computer science, joined Nedap in 1997, and has run the company since 2009. He left at the end of 2025. Under Wegman, Nedap has spent nearly two decades narrowing its focus from seven markets down to four.

We actually had the chance to talk to Wegman just weeks before he left. It’s freely available on all podcasting platforms.

The business model is straightforward but easy to underestimate.

The Business Model & Competitive Advantage

Nedap is transitioning from a hardware- to a software-driven company, focusing on superior software solutions tailored to customer needs. While hardware production is outsourced, Nedap retains control over key components, selling integrated hardware-software packages. Nedap is the market leader in these four key markets.

🐮Key market 1 - Livestock: Nedap started their livestock division in 1977. In this division, Nedap offers a combination of hardware and software to farmers. Currently, Nedap is only active in the cattle industry.

In livestock, Nedap is a global leader with over 40% market share, offering smart monitoring solutions with the goal of increasing productivity and improving the health management of cows. Think of it like a Fitbit but for cows. They have over 8 million connected cows, 25,000 farms, and operate in more than 50 countries.

🧑‍⚕️Key market 2 - Healthcare:

This is where Nedap has the strongest market position in our eyes. Moreover, it’s probably the most profitable in the future because it’s all software. Nedap’s market share in the elderly care market is 60%. In the disability care market, this percentage is around 50%.

In healthcare, its Ons (meaning ‘us’ in Dutch) platform simplifies administrative tasks for caregivers and health organizations, with a customer retention rate of 99% and a strong market position in elderly and disability care.

Think of Ons Nedap as an all-in-one platform where you can perform these activities:

• Electronic patient file management: health overview, medications, quality monitoring.

• Care logistics: calendar, scheduler, planning, capacity management.

• Administration: financial dashboard, billing, cross-health traffic (safely exchanging sensitive health information to and from other health organizations).

We asked someone who works with Ons about alternatives, and she said:

“If the organization would change the system, all caretakers would definitely disagree. We are used to this way of working and our clients’ information is in the system.”

🔐Key market 3 - Security:

In security, Nedap is mainly active in access management. Think about personnel access management solutions for employees of Amsterdam Schiphol Airport. Especially in Europe, Nedap has a strong market position with 36% of the top 250 European organizations as clients, including Airbus, Vodafone, Volkswagen, and Unilever.

🔐Key market 4 - Retail:

Do you know that bleeping sound when someone walks out of a store with unpaid products? For decades, Nedap has been known for the system that detects whether a product is paid for and alarms the shop owner when someone walks out of a shop with an unpaid product. Although it still sells those gates to customers, based on RF or RFID, it is not Nedap’s core focus within the retail area anymore.

In retail, it leads in RFID (Radio Frequency Identification)-based inventory solutions, significantly enhancing inventory accuracy for clients like Adidas and Decathlon, while also offering secure self-checkout technologies. A great thing is that Nedap is bigger than competitors 1, 2, and 3 combined with a total market share of 35% of retail RFID users.

Valuation & Ending Thoughts

Assuming 8% growth (CAGR), a 14% profit margin, and an 18-times exit multiple, including dividends, the IRR from today’s price of €99 should be around 14%.

We believe Nedap is one of the highest-quality, yet most overlooked, Dutch software companies. Because of its low-volume and small market capitalization, it is not (yet) included in many of the funds and investments that drive the majority of the volume.

There are numerous factors to consider and be aware of, and even a high-quality business can be a poor investment if the valuation is too high. Our entire deep dive is free for you to read and explore.

Read & Listen to entire Deep Dive

Company Idea 2: Ferrari Group

🏢 Company name: Ferrari Group PLC
⌛CAGR since IPO: 7.2%
✨ Market Cap: ~€700 million
📊 Revenue FY25: ~€359 million

To avoid any confusion, this company is not the luxury supercar manufacturer famous for its fast red cars. Apart from the name, which is just a coincidence, the companies don’t have a lot in common. This is about a high-security logistics company.

Founded in 1959 in Alessandria within Italy’s golden triangle of jewelry crafting, Ferrari Group originally served as a customs broker for regional goldsmiths. Today, it is domiciled in London and listed on Euronext Amsterdam. It remains a true family company: co-founder Miranda Ferrari’s stepsons, Marco and Corrado Deiana, serve as CEO and COO. The Deiana family retains ~71% ownership.

The Business Model & Competitive Advantage

The business is unglamorous, highly specialized, and split across four key operating divisions:

🚢 Key segment 1 - International Shipping:

Accounting for roughly 66% of total revenue, this is the core engine. Ferrari Group transports high-value goods across borders, managing logistics, high-security vaulting, and complex customs clearance.

🚚 Key segment 2 - Domestic Shipping:

Accounts for 17% of revenue. It handles point-to-point secure road transport within single national borders, bridging local boutique networks to major transport hubs.

✨ Key segment 3 - Special Services:

Accounts for 11% of revenue. They provide tailored security and logistics for high-profile trade shows, private VIP exhibitions, and events like Monaco’s Grand Prix de la Haute Joaillerie.

🏬 Key segment 4 - Warehousing:

With 6% of total revenue, it offers vaulting, inventory storage, and value-added tax/customs bond management for ultra-luxury brands.

Across these segments, Ferrari Group moves over €170 billion in luxury goods annually for 100+ brands across 64 countries. Client retention sits near 100%, driven by 3–5 year contracts and absolute operational trust.

Ferrari Group’s high entry barriers include custom-built security infrastructure, global regulatory compliance licenses, and deep integration into luxury supply chains. In addition to shipping boxes, they also handle all the risks that come with the process.

Valuation & Ending Thoughts

For the medium term, in this case five years, we think the 6-8% annual growth is doable. To be conservative, despite rising expectations for luxury logistics. Management expects bottom-line margins to improve, but again, to be conservative, we assume a free cash flow margin of 15% on average.

At the current price of around €8, one can expect an IRR of around 13.8%, including a 4% dividend.

Ferrari Group offers a sticky, high-margin moat in a niche that scale competitors rarely attempt to replicate. It remains a quiet compounder hiding behind one of the most famous names in the world.

The Dutch Investors' Blog

Company Idea 3: Basic-Fit

🏢 Company name: Basic-Fit N.V.
⌛CAGR since IPO: 8.2%
✨ Market Cap: ~€2.1 billion
📊 Revenue FY25: ~€1.42 billion

Basic-Fit, the largest budget gym chain in Europe with its headquarters in Hoofddorp, is almost certainly a name you’ve seen before. The origin story is almost accidental: founder René Moos started a tennis school in 1984, added a fitness corner when he had spare space, and eventually merged with a competitor in 2004 under the HealthCity brand. In 2010, the company split into a premium line (HealthCity) and a budget tier (Basic-Fit), took on private equity backing from 3i Group, and listed on Euronext Amsterdam in 2016 at €15 a share. Moos remains CEO and the largest individual shareholder.

The Business Model & Competitive Advantage

The model is simple: low-price, 24/7, largely unstaffed gyms with tiered monthly memberships (~€25 to €35/month). When Basic-Fit grows, they open multiple clubs at the same time in the same area to meet all of their customers’ needs before their competitors can respond. This is called a cluster strategy.

Basic-Fit ended 2025 with 1,660 owned clubs (excluding its recently acquired Clever Fit franchise network) and 4.82 million members. Average revenue per member is about €25. It’s a wonderfully simple, yet profitable model when executed well.

Basic-Fit’s unit economics and massive purchasing scale are its core drivers:

🏋️ Key driver 1 - High-ROIC Unit Economics:

Return on invested capital (ROIC) reached 31% at mature clubs in 2025, which was higher than the company’s own 30% goal. Even though core markets are getting older, this shows that the playbook still gives good results.

💥 Key driver 2 - Scale-Driven Purchasing Power:

When you add up all the costs, scale gives you an edge that standalone gyms can’t match. Basic-Fit gets bulk equipment prices from companies like Matrix and TechnoGym and handles software, app development, and national marketing for its millions of paying members.

🤝 Key driver 3 - High Member Retention:

Membership lasts an average of 23 months, which is almost twice as long as the fitness industry average of less than 12 months. This means that the business can count on steady income.

Valuation & Ending Thoughts

We know that the target is to open around 100 clubs per year for the coming years. That means Basic-Fit could have 2650 operating clubs in 2031. At least 80% of clubs will be mature at that time because the percentage of mature clubs will become higher as Basic-Fit grows. This means a total EBIT of €428 million can be expected from these mature clubs (2251 clubs times €190,000 in EBIT). Just imagine what happens if Basic-Fit were to stop expanding. Money would pour out, and an EBIT margin of 24.5% would be realistic.

Our baseline is to assume 100 extra clubs per year. One can expect about 11.8% IRR, including 2% dilution.

On the one hand, investing in Basic-Fit comes with risks. Think about debt levels, pace of maturity, and club openings. Furthermore, pandemics or other catastrophes could weaken the business. On the other hand, the valuation we used is pretty conservative.

💭 Closing Thoughts

None of these three are perfect, and we wouldn’t want you to read this as a buy list. It’s not.

What they have in common is that they’re run by people who’ve been doing this a long time, in businesses protected by something durable, whether it be switching costs, specialization, or scale earned the hard way.

The Dutch market, and Europe more broadly, is full of companies like this, and are easy to overlook if you only look where everyone else is already looking.

If you want more of this, we’d be happy to welcome you.

Subscribe to The Dutch Investors 🦁

This post was made in collaboration with René Sellmann.

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I could write a book about discounted cash flow analysis. The variations, the sequence of steps, how you arrive at each input and what each input actually means, why a margin of safety belongs in the process at all, why thinking in ranges beats thinking in points.

I realize that I sometimes struggle to keep my posts concise. There is always more I want to hand over than one post can carry, and the result tends to be bloated enough that nobody gets through it.

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So I am going to be narrow here. One problem. At least I will try.

A DCF is artificial by construction, and that artificiality is spread unevenly across the model. Some of it does no damage at all. Some of it costs you money without ever announcing itself, and the expensive part tends to be the part investors spend the least time on.

If you buy quality and hold for growth, as I do, this matters more to you than to almost anyone else, for reasons I will get to.

In yesterday’s write-up on Wise, I put it this way:

“Investors like straight lines. We build models in spreadsheets where each column is slightly larger than the one to its left, and something in the presentation of that arithmetic persuades us that reality will cooperate. It rarely does. You might forecast a topline CAGR of 13% over the next four years. A 1% margin expansion each year. The reality looks different. Maybe 18% next year, followed by 7% the year after. Real businesses sprint, stall, take a step backward, hit an obstacle nobody modelled, and then sprint again. What separates a temporary setback from a broken thesis is not the size of the stumble. It is whether the destination changed.”

I wrote that about a business, Wise, and not about a theoretical model. Yet, the same complaint applies to DCF models. Most DCF spreadsheets I’ve seen move in straight lines. Three growth stages. Constant Growth. Simple.

As a result, every DCF ever built describes a company that does not exist, growing in a manner no company has ever grown, before settling into a maturity no company has ever settled into on schedule.

That sounds like a devastating criticism. It mostly is not, and working out where the criticism stops being harmless and starts costing you money is the point of this piece.

Before I get there, we need to be clear about what a DCF does at the far end, because there is more than one way to finish one.

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Every model needs an ending …

A DCF says something simple. A business is worth the cash it will hand its owners over its life, discounted back to today at a rate reflecting what else you could do with the money and how uncertain the cash is.

Clean idea, right?

The trouble arrives because businesses do not have a known life, and neither you nor I can forecast a cash flow in year 47. So the model gets split in two. There is an explicit forecast period, where you determine the growth the company will grow at, and there is everything after that, compressed into a single figure called the terminal value.

In my own framework, the explicit period runs ten years, broken into two stages. Years one through five get one growth rate, years six through ten get a lower one. A high-quality business might get 14% in the first stage and 9% in the second. Then the model has to end, and here the conventions diverge.

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The first approach is the perpetuity growth model. You assume that after the explicit period the business grows at a constant rate forever, and you value that stream. Most investors settle somewhere between 2% and 3% for that growth rate, roughly in line with long-run inflation.

The second approach is the terminal multiple, or exit multiple. Rather than assuming perpetual growth, you take the final year’s earnings, EBITDA, or free cash flow and apply a multiple to it, generally drawn from where comparable businesses trade today or from what acquirers have recently paid.

Sell-side models lean on this heavily, and so does most private equity work, for the reasonable reason that those models are usually built around an eventual exit. If you intend to sell the asset in year ten, asking what a buyer will pay is the reasonable question to ask.

For someone buying a listed compounder with no intention of selling, that approach carries a problem baked into it. You are importing a relative valuation into an absolute one. The multiple comes from the market, so you have outsourced the most important assumption in your model to the same market whose pricing you were trying to assess independently. When the market is enthusiastic, your terminal value inflates. When it is miserable, your terminal value collapses, and your DCF obligingly tells you the business is worth less, which inverts what an intrinsic valuation is for.

There is a second, subtler flaw: The multiple you observe today attaches to a business at today’s stage of maturity. Some investors apply it to the same business ten years older, ten years further into its S-curve, with a growth rate that by their own model has already stepped down twice. A business growing 9% does not deserve the multiple of a business growing 20%, and yet analysts routinely lift the current multiple and drop it into year ten unchanged.

Problematic.

None of this makes exit multiples useless. It makes them a different tool answering a different question, and it makes the two methods most valuable when you run them against each other. This is the practical habit worth building, and it takes about ninety seconds.

Whatever perpetuity growth rate you chose, compare it to the value of a reasonable terminal multiple, and consider the multiple you have implicitly assigned to your terminal cash flow.

Then reverse it. Take whatever exit multiple you find defensible, and solve for the perpetual growth rate it implies. If your 3% terminal growth turns out to imply a 14 times free cash flow multiple on a business you have argued will still be earning premium returns in 2036, you have learned something.

If your 20 times exit multiple implies 5% perpetual growth, you have learned something too, something somewhat alarming, because you just asserted that this company outgrows the economy until the end of time.

Questionable.

Both methods embed a claim about forever. The perpetuity model states its claim openly and invites you to argue with it. The exit multiple hides the same claim inside a number that take a second to jot down in your spreadsheet.

Neither is more rigorous. One is more honest about what it is doing, which is why I use it.

It’s all fiction!

Of course, the used compounded growth rate - take the 14% for years one to five mentioned above - does not necessarily imply that the business grows at that rate every year. It claims where the business ends up after five years.

A company need not deliver 14% to the decimal in each of the first five years for a 14% first-stage assumption to describe its trajectory accurately.

A path of 13%, then 25%, then 4%, then 7%, then 23% compounds to 14.09% over five years, and that’s likely a more accurate description of how a business behaves. A strong year, an air pocket, a recovery, then a new product or a new market starts contributing.

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The spreadsheet column reading 14% five times in a row and the messy path arrive at the same place.

So what exactly is the complaint?

Every model is a simplification. The question worth asking is which simplifications cost you money, and this particular one costs you less than its obvious wrongness suggests.

Three flaws are worth highlighting:

• The first is arithmetic. Discounting cash flows cares about the order in which cash arrives – as future cash is less valuable in a DCF due to the time value of money –, so two paths with identical compound growth rates and identical ending cash flows are worth slightly different amounts today. Take a business generating $100 in free cash flow, a 10% discount rate, and two five-year paths. The front-loaded path grows 25%, 20%, 15%, 10%, 5%. The back-loaded path runs the same sequence in reverse. Both turn $100 in earnings power in year zero to $199 in year five, and both compound at an identical rate. Strictly speaking, the front-loaded path is worth more than the back-loaded one, though. It doesn’t make a major difference – somewhere in the vicinity of 3-4% – but it is something worth acknowledging, though, hardly worth agonising over.

  

• The second is that reinvestment does not follow a smooth line either. A business accelerating from 6% to 24% growth is most likely reinvesting (more) aggressively, funding working capital ahead of shipments, and often committing capital a year or two (or more) before the increased earnings power shows up. Its cash conversion in that sprint year will be worse than a smooth DCF model implies, sometimes considerably worse, and its conversion in the stall year afterwards will look better than it deserves. Your model shows a placid ramp, which you rarely encounter in the real world. I’m going to reference the example of Alphabet again, as it serves the purpose of illustration very well right now.

  

  The company lives through a sequence where the cash generated in 2026 bears little resemblance to the cash generated the year before. For a business with a strong internal cash generation and a strong balance sheet this is not that relevant. For a business funding growth externally, the sprint years are when often new equity gets issued.

• Thirdly, the straight line approach of DCFs may train your brain and thinking about your hypothesis in a suboptimal way. An inexperienced investor may look at a column of numbers rising by a consistent percentage, and may start to treat any deviation as evidence that something has broken. The company guides down for a quarter, the organic growth number prints 7% against your 13%, and the model in your head says the thesis is broken. However, in my view, and we discussed this in yesterday’s Wise piece, what separates a temporary setback from a broken thesis is whether the destination changed. A model built out of smooth increments has no room for a temporary stumble. It cannot represent one, so when a stumble arrives you have nothing in your framework to compare it against, and you improvise under pressure.

So the smooth line approach inside the explicit forecasting period is a fiction; theory vs. the real world of business. It’s not a big deal, but worth acknowledging.

However, something else is going on further down the model. The same criticism that lands gently in years one through ten lands hard at the point where the explicit period ends.

Artificial Cliffs

Look at what the illustrative example model above asserts. Years one through five, the business grows at 14%. Year six arrives and it grows at 9%, a step down of five percentage points occurring between two years for no obvious reason connected to the company.

Then year eleven arrives, growth falls to 3%, and stays there until the heat death of the universe.

My own template runs the terminal stage as a thousand years of cash flow, which I find useful to see written down (even though whether you opt for 1,000, 100 or 50 years makes little difference to the actual terminal value; again, the concept of time value of money applies here), because it makes explicit what the perpetuity formula is doing behind a tidy piece of algebra.

Both growth step-downs appear on a calendar boundary existing because I built the model in two stages of five years. Had I built it in three stages of four, the deceleration would have arrived at different moments – and be more gradual –, yet the business would have had no way of knowing the difference.

My point is, the timing and shape of the “fade” is one of the most consequential features of your forecast, and the architecture of the spreadsheet is setting it.

Now put that next to the evidence. McKinsey, in one of its research efforts, sorted companies into quintiles by revenue growth and followed each cohort forward. The pattern is no staircase as in your typical DCF model.

Rather, it is a curve, yet a steep one.

Businesses growing above 20% in year one are down to roughly 8% within three to four years. The 15% to 20% cohort halves inside five. By year ten, every cohort has converged to around 5%, roughly nominal GDP, because no group of companies can outrun the economy indefinitely without becoming the economy.

“Analysts have been persistently over-optimistic for the past 25 years, with ‘earnings’ estimates ranging from 10 to 12 percent a year, compared with actual earnings growth of 6 percent. |...] On average, analysts’ forecasts have been almost 100 percent too high.“

That cuts in an uncomfortable direction for anyone who thinks the standard structure is conservative. Assume 14% for five straight years and you are already claiming your business defies the median path by a wide margin, since the median 15% to 20% grower is nowhere near 14% by year four.

Most of investors’ “fantasy” (read: overconfidence or misjudgment) can be found in the first stage, and it does not feel like fantasy, because it is expressed as a single unremarkable number in a green cell.

A median is not a destiny, though, and this is where tension arises. A quintile is a crowd. Inside it sit the businesses that did compound at 12% or 15% for a decade and beyond, and if you own quality stocks, your proposition is that you can occasionally identify one business defying base rates in advance.

So the structure is too generous to the typical company and potentially too harsh on the exceptional one, and most investors correct for neither.

The textbook DCF model offers two stages and a terminal rate. Whatever you believe about durability has to be forced through those three cells.

More than the growth rate snaps into place at year eleven, too. Cross that boundary and the model asserts that margins have reached their permanent level, that reinvestment needs have normalised, that competitive intensity has settled, and that all of it happened at the same calendar moment.

Unlikely.

Businesses do not mature the way bonds mature. They mature in pieces, unevenly, some parts commoditizing while others are still expanding.

Here is why this artificiality can cost you. Take the illustration from my own framework: $557 of present value from the first stage, $581 from the second, $1,680 from the terminal stage.

That last figure is 59% of the total.

Ten years of judgment gets outvoted by one cell I filled in by convention, in about two seconds, using a number I have never thought more deeply about.

The terminal value dominates

Once you accept that most of the value sits in the terminal stage, it feels logical to conclude that years one through ten barely matter. Spend your effort on the terminal cell, wave through the rest. Right?

No!

It is wrong, because the terminal value inherits everything. Take a business earning $100 in FCF with a 10% cost of equity, assume our growth rates from above and hold terminal growth fixed at 3%. Our intrinsic value estimate was $2,820. The terminal value $1,681.

Now let’s only vary the five-year high growth period and move it up to 18% (from 14%). The terminal value, too, rises to $1,997.

The terminal growth never changed. The terminal value went up significantly.

Everything you assumed about growth, margins, and reinvestment across ten years flows into the base the formula is applied to, and the perpetuity equation faithfully multiplies your error into infinity.

How long does the moat last?

Value gets created only while a business earns more on capital than that capital costs. The moment the spread closes, growth stops mattering. So the durability question has a precise form: how many years does the spread stay positive, and how fast does it narrow?

Mauboussin and Paul Johnson named this in a 1997 paper and the concept has never had the attention it deserves. They called it the competitive advantage period and gave it a measure. The fade rate, f, is the exponential decay at which return on invested capital converges towards the cost of capital, and the competitive advantage period equals one divided by that fade rate. Across US stocks the range typically lands between ten and fifteen years, varying by industry and by company.

Here is what struck me. A ten-year explicit forecast followed by a terminal stage where returns have settled at the cost of capital is a statement that the competitive advantage period is ten years. You never typed that number anywhere. It emerged from a structure you chose because five plus five is tidy. For the median listed company, ten years is roughly right. For a business you selected specifically because you believed its advantages were unusually durable, you have applied the median assumption to a company you do not think is median, then congratulated yourself on being disciplined.

Three ways to express a longer runway, none of them clean. You can extend the explicit period to fifteen or twenty years, though forecasting revenue in year eighteen is a different order of fiction than year six, and if the true excess return period runs thirty years, extending the forecast to cover it defeats the purpose of having a terminal value at all. You have replaced one guess with fourteen more. You can fade gradually rather than stepping, letting growth and returns decay year by year at rates you have to justify, which describes the world far more faithfully but takes work per company and moves the answer less than you would hope. Or you keep the structure and let a positive spread persist into the terminal stage. That is Damodaran’s own practice, and he is explicit that it is discretionary: excess returns move towards zero in stable growth, but how far depends on the business, zero for firms lacking sustainable advantages, positive for firms that have them, negative for badly run companies with entrenched management. His reasoning is the one I landed on above. Excess returns outlive high growth by a wide margin, so the terminal assumption should reflect that asymmetry rather than flattening both to nothing on the same date.

I use the third route, and it does not become a licence to justify whatever price you were hoping to justify. Granting a permanent 15% return rather than a cost-of-capital return lifted that terminal value from 1,000 to 1,143. Granting 20%, heroic for eternity, gets you 1,214. Roughly a fifth of additional value for an assumption most people would call indefensible, set against the more than half that ten years of explicit assumptions moved. The dial carrying the durability argument is a gentle dial. I find that reassuring. It means the honest expression of “this is an exceptional business” adds ten to twenty percent, which matters when I am weighing 30 times against 34, and is useless if I am trying to talk myself into paying 60. If your quality argument needs more than that from the terminal stage, you are making it in the wrong place, and it probably belongs in the explicit period as higher growth or better margins, where reported numbers will check you within a few years.

What determines the fade rate is business analysis rather than modelling. Switching costs embedded in mission-critical workflows erode slowly, because the cost of ripping the system out rises with every year of accumulated data and habit. A brand supported by continuous marketing spend requires that spend forever, so the moat is rented rather than owned, showing up as a permanently higher reinvestment rate and a thinner spread than the headline margin suggests. Anything resting on one regulatory arrangement or one distribution partner has a fade rate that can go vertical without warning, and there I would not extend the spread at all.

One further consideration gets missed and it matters for the businesses I favour. A high return with nowhere left to deploy it is not a compounder stock. The competitive advantage period tells you how long the spread survives, not how much capital the company can push through it, and a business earning 25% on incremental capital while reinvesting only 10% of profits is a different proposition to one reinvesting 60% at 18%.

The second creates far more value over a decade despite the lower return.

The gap between your forecast and the base rate is something you have to earn

It takes one keystroke to type 20% growth for ten years into a model. Fewer than five percent of companies ever deliver it. That asymmetry between asserting something and achieving it is why base rates matter, and I have been turning it over for years without the tension resolving, which is why I keep coming back to it.

Mauboussin flags base rate neglect more than almost any other error. When you forecast growth you hold an inside view, your own judgment, built from work on one specific company. You have read the filings, listened to the calls, mapped the competition. That view feels authoritative because it was “expensive” to acquire.

It cannot stand alone.

You also need an outside view, an appropriate reference class, and the question of what actually happened to its members.

For Dino Polska the class would be grocery retailers at a comparable stage of maturity, and the question is what they delivered over the following five or ten years on the top line, on profit, on margins.

Base rate neglect is pushing that data aside and building a conclusion from conviction alone.

The data is unkind in a specific way. Mauboussin sorts companies by revenue base, since a business at two billion faces different arithmetic than one at forty, then reads across to the growth rate you are contemplating. Applied to Musk’s 2015 claim that Tesla would grow sales 50% annually for a decade from a six billion dollar base, the relevant decile produced no companies at all that had managed it.

Not few. None.

Buffett ran a version of the same test on profits, and my framework has carried it for years. Of the 200 companies with the highest net income in 1990, only 162 still existed by 2000. Fewer than nine percent of those grew net income at 15% or better across the decade. Not one of them repeated it in the ten years to 2009.

“We started by identifying the 200 companies with the highest net income in 1990. By 2000, only 162 of those companies were still around. Of those, less than 9% (14 of 162) grew net income at a rate of 15% or more from 1990-1999. None of those 14 companies grew at higher than a 15% rate for the decade ended in 2009.“

There is a methodological reason the outside view comes first rather than serving as a check afterwards. Sales growth shows very low year-over-year correlation, so last year tells you remarkably little about next year, which is why you start from the base rate and look for reasons to depart from it. Reverse the order and something predictable happens. You build from company-specific reasoning, arrive at 16%, then consult the reference class, at which point the base rate becomes a hurdle to argue around instead of a starting position.

This is where the exercise gets awkward for someone in my seat. If you buy quality and hold for growth, your proposition rests on the belief that this particular business is one of the rare ones, and the base rates are brutal on exactly that point.

They function as a direct statistical challenge to the thing I have built my process around, and there is no clean escape.

I do not think the discipline lies in choosing between conviction and the statistics of the reference class, and I am suspicious of anyone claiming to have resolved it. What is left is holding both at once. Genuine belief that you have found something exceptional, alongside clear-eyed acceptance that the odds say you probably have not.

Practically, the gap requires the defence rather than the forecast itself. If the class delivered 7% and you are underwriting 13%, six points of excess growth need a mechanism attached, specific enough to be wrong. New store formats at a defined pace with defined economics. Pricing power of a stated magnitude, supported by what happened the last three times prices went up. A category shifting online at an observable rate. When you cannot name the mechanism, you are likely blinded or biased; or both.

Justifying the gap properly, qualitatively takes real work, and often the work talks you down. That discomfort is the signal you are doing it correctly.

Base rate thinking applies to the terminal stage too, and almost nobody applies it there. Your terminal assumption contains a claim about how long an advantage survives, and there is a reference class for that as well, clustering between ten and fifteen years. Companies holding returns above their cost of capital for thirty years exist.

They are rare, identifiable and mostly famous.

If your model implies your business joins them, say so explicitly, because that assertion deserves the scrutiny you would give a 20% growth forecast and it usually receives none.

When EXACTLY does a great business become an average one?

Three percent is a defensible number and I am not about to question it per se. No company grows faster than the economy forever. Push the rate to five and you have asserted that this business eventually becomes the economy, which is simply an impossibility.

However, forever and from year eleven onwards (for a few more years) are different claims, though. A difference your textbook perpetuity growth DCF formula does not capture.

That is where the trouble starts for anyone who looks at “moaty” businesses.

Take a company with multiple structural advantages, enabling it to reinvest at high rates for longer than the outside view would suggest. Switching costs rising every year as the network grows. Or a brand name that has become synonymous with a product category. A cost position competitors cannot match.

Let’s just take Hermès as an example. Do I believe that business grows at 3% in year eleven? No. I think it probably grows at six or seven, then at five a few years later, drifting towards the economy sometime later, maybe in year 20.

The textbook model has nowhere to put that. Our example model above offers 9% through year ten and 3% after, so the entire question of how long the advantage keeps working gets compressed into one step change, on a date chosen because five plus five is tidy. Type 3% at year eleven and you have asserted that the competitive advantage period is exactly ten years. You never determined that number by thinking it through qualitatively. It arrived with the template. Which poses a problem.

For the median competitively advantaged listed company, ten years is maybe roughly right. But as McKinsey also showed, returns on invested capital can remain higher for longer. Put differently, structural advantages seem to persist (and only the ability to reinvest a lot of cash at these rates fades).

If you stick to the textbook DCF approach, for a business you selected specifically because you thought its advantages were unusually durable, you have applied the median assumption to a company you do not think is median, then congratulated yourself on being disciplined.

Again, look at the two McKinsey charts. Revenue growth converges across every cohort within a handful of years, fast growers and slow growers alike, funnelling towards 5%. Returns behave differently. The top ROIC quintile is still near 15% fifteen years after portfolio formation, having started around 28%, while the middle cohorts barely move.

Growth is fragile. Advantage is sticky.

If a business is still earning exceptional returns in year fifteen, something is still protecting it, and whatever that something is has not finished working by year eleven, and even if reinvestment opportunities fade, if you only reinvest 30% of your cash at 15% ROIIC, you still grow your topline at 4.5% (and not at 3%) – and maybe your business is inflation-hedged on top of this (take payment processing companies for instance).

So what do you do about it? Three options, none of them clean.

• You can stretch the second stage, running 9% through year twelve or fifteen for instance rather than year ten.

• You can fade gradually, stepping growth down a point or so a year towards 3% rather than dropping it in one move, which describes the world better and takes more work per company.

• Or you keep 3% at year eleven, accept that you are being conservative, and let your margin of safety do correspondingly less work at the other end, since applying both charges the same caution twice.

Nobody ever posts about a compounder they refused to buy

Everything so far pushes one way. Fade harder, respect the base rates, do not flatter your terminal assumptions. That is the conventional counsel and it is largely correct. I’m all for conservatism.

Applied without care, however, it is also a reliable method for missing every great business you will ever encounter.

Consider conservatism when it accumulates. You take 11% rather than the 15% your own work suggested. You fade to 7% in the second stage because the convergence curves say deceleration arrives faster than your inside view would suggest. Terminal growth at 3%, because “nothing outgrows the economy forever.” Then a 50% margin of safety on top.

Every one of those is defensible in isolation and I would sign off on each individually. Stacked, they produce a valuation so far below any plausible price for an ultra-competitively advantaged company that you will never own the business, even though it was maybe priced attractively enough at some point.

This kind of error, an error of omission, often stays invisible. Overpaying leaves a mark. It shows up in your returns, in your portfolio. Underwriting a compounder at half its worth and walking away leaves nothing behind. No entry in the P&L. Nothing to review. Nothing anyone can criticize, and a certain amount of unearned credit for discipline.

The investing world has produced an enormous literature on valuation-agnostic buying and almost nothing on the cost of habitual under-underwriting.

The arithmetic runs in the direction people find counterintuitive. A business earning 25% on incremental capital and reinvesting 60% of its profits grows earnings at 15% a year and funds that internally. Fifteen years turns $1 of earnings into roughly $8. A model built to be safe has the same business decelerating to 7% by year six and 3% by year eleven, arriving at a little over $3.

You have valued a different company.

The entry multiple matters less than it feels like it should for these compounders. Buy that compounder at 35 times, hold fifteen years, and even if the multiple compresses to 20 your annualized return comes to just under 11%.

This is the risk of underappreciating a runway vs. the risk of overpaying.

None of this argues for waving through a high multiple. The point is narrower: conservatism has a cost, too, and treating it as free is itself an analytical error. So I try to be deliberate about where it enters. I keep the forecast as honest as I can make it, neither optimistic nor defensively low, and hold the margin of safety separately as an explicit decision about how uncertain I am, so I can see what it is doing.

So what do I actually do?

I am not offering a superior model here. In fact, I rarely use a DCF these days.

The value of this entire discussion, and the value of attempting your hand at a DCF in the first place, lies in the questions it forces you to tackle rather than the figure it produces.

A DCF handing you a number and nothing else has failed at the only thing it is good for.

The sequence starts outside the company. Before I build anything, I want the reference class and what happened to it, which means finding businesses at a comparable stage in comparable industries and looking at what they delivered over the following decade on revenue, margins and returns on capital. That becomes my anchor, and everything afterwards is an argument for departing from it. The order is not cosmetic. Build the forecast first and the base rate becomes an obstacle you negotiate around, a completely different mental operation to starting from the data and having to justify every point of excess.

Then comes the exercise I find more valuable than anything else in my valuation work at the moment. If you take one practical thing from this piece, take this. Rather than typing a single growth rate into a cell, I decompose the top line into its drivers and assign a contribution range to each.

For a retailer, for instance, that might be new store openings contributing four to seven points, like-for-like growth at one to three, pricing at two to three, and a new category contributing nothing in the bear case and two points if it works. Sum the ranges, and you have a growth band rather than a point estimate, plus a picture of where the growth is supposed to come from.

The assumptions become auditable, and they generate questions I would not otherwise have asked. Assigning a band to new store contribution forces me to ask how many locations remain in the addressable market, what the recent cadence has been, whether new stores cannibalise existing ones, what the payback period looks like. When the company reports I am not checking whether revenue growth was 13%. I am checking whether openings ran at the pace I assumed and whether like-for-like held, which tells me which part of my thinking was wrong rather than merely that something was. By the time I have worked through every driver I understand the business considerably better, and the model is a by-product of that understanding rather than a substitute for it.

The same treatment applies at the far end, the terminal value, where most of the intrinsic value can be found.

• What am I claiming about the competitive advantage period?

• What generates the advantage and what is its natural decay rate?

• Can the company still deploy meaningful capital at that return, or is it a wide spread with nowhere to put the money?

• Are the reinvestment rate and the return I assumed consistent with the growth rate I typed in?

That last check takes thirty seconds and catches an embarrassing number of errors.

Everything gets expressed as a range, and I usually hold at least three scenarios rather than one valuation, so the output stops being a price and becomes a distribution, a range, and the decision becomes a judgment about the scenario distributions and assigned probabilities.

Then I invert the whole thing and ask what the market price already asserts. Solve for the growth rate the market is embedding, given a sensible discount rate and a reasonable view on returns and reinvestment.

A stock at 40 times might be asserting 18% growth for a decade, which the base rates say is a stretch bordering on fantasy. Or it might be asserting 9%, which for a business with a durable advantage is worth taking seriously.

What felt expensive on a multiple often looks different once you see what it requires, in both directions. I find that reframing more useful than any forward model I build, and it deserves its own piece rather than a paragraph here.

Is this as granular as sell-side modelling? Not remotely. Those models run to hundreds of line items, and building one teaches you the business in a way nothing else does. The failure mode is something other than imprecision. It is the man with a hammer, the conviction that four hundred rows make the output knowledge rather than a very elaborate opinion. Precision and accuracy have nothing to do with each other, and a forecast carried to the decimal place in year nine claims a resolution nobody possesses.

What I am describing is less granular and better calibrated to what can be known. Enough structure to catch inconsistencies and force the right questions, not so much that the apparatus starts manufacturing confidence. It is a long way from the alternative, the hasty assumption, which has a formal name. The hasty generalisation fallacy describes drawing a conclusion from a sample too small or unrepresentative to support it. Three years of strong growth extrapolated across a decade. One good quarter treated as a trend. A competitor’s stumble read as a permanent advantage.

I am not accusing you of it. I do it too, generally when I like a business and want the numbers to agree with me.

So where does this leave the DCF? Roughly where it should have been all along. It is a device for thinking, and its highest use is diagnostic. It tells you what you would have to believe. When my model implies a terminal spread putting a company among the two dozen most durable franchises in the world, I have learned something about my own reasoning rather than about the company. When the price embeds growth the base rates say almost nobody achieves, I have learned something about the price.

Neither insight arrives as a number, and both are worth more than the numerical output a DCF provides.

The artificiality never goes away. Growth stages stay arbitrary.

Knowing where your tools distort is what separates using a tool from being used by one.

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Wise can’t catch a break!

There are stretches in the life of a business where everything that can go wrong seems to arrive at once, and Wise is living through one of these moments it seems.

On the first of June, Belgian prosecutors confirmed they were investigating Wise Europe over roughly €500 million in suspicious transactions, drawn from hundreds of criminal files that had reached Brussels through European Investigation Orders from more than thirty countries.

The stock fell as much as twenty per cent that day before closing down eight.

Then came the chatter about a platform partner, NuBank, reconsidering its relationship, which I have not been able to verify anywhere and which I mention only because it circulated widely enough to shape sentiment.

And now this: On Thursday, the U.S. Office of the Comptroller of the Currency denied Wise’s application for a national trust bank charter, and by Friday morning in London the shares were down around ten percent at the open (as I type this, Wise’s LSE shares are down 7 percent).

Three blows inside two months, all of them landing on the same nerve.

The timing is what makes it sting. Wise moved its primary listing to Nasdaq in May, keeping London as a secondary venue, and the stated rationale was that the United States represented the biggest market opportunity in the world for its products.

You do not relocate your primary listing to a market and then get told by that market’s chief banking regulator that your management and board have demonstrated a persistent inability to manage money-laundering risk without the symbolism registering.

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Goldman Sachs, which is still Buy-rated with the stock on its Conviction List and a twelve-month target of 1,450p against a current price below 850p, put it plainly enough in its note on the denial: with the OCC decision layered on top of the Brussels investigation, they expect the shares to stay under pressure while the regulatory overhang persists. Sixty percent implied upside and an explicit warning that the stock may go nowhere for a while.

That is an unusual pair of statements to hold together, but it captures the situation and current sentiment reasonably well.

I want to do something more useful here than either panic or reassurance. Both are on offer elsewhere.

What I want to work through instead is a set of questions that I think matter more than the headline:

• What the OCC actually said as opposed to “what Wise said the OCC said,” and why the gap between those two accounts is the most important thing to understand about this event first.

• Then, why Wise wanted a charter in the first place, given that its founder spent years explaining why not being a bank was a deliberate choice rather than an accident.

• Why Circle applied two weeks after Wise, to the same regulator, for the same category of charter, and walked away with final approval fourteen days before Wise was rejected.

• What the reapplication path actually looks like once you account for a Federal Reserve policy process that has a stated end date, and for the fact that the American banking lobby has been filing formal letters against this charter since the summer of last year on grounds that have nothing to do with anti-money-laundering controls at all.

• And finally, what any of it does to a business that grew cross-border volume thirty-one per cent last year while deliberately cutting its own prices.

The uncomfortable part, and the part I think most of the commentary is skipping, is that the reason for the denial is more specific and more fixable than the “regulators are being difficult” story, and also more damning.

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Here’s everything I have ever written about Wise:

• 2026-07: Discussing Wise’s Q1 FY27 Results

• 2026-05: Deep Dive: Wise Plc. – Betting on the Unexpected?! - ($)

• 2026-05: Wise Plc. ($WISE) – 10 Critical New Insights! - ($)

• 2025-10: Revisiting Wise ($WISE) - ($)

• 2025-06: Wise ($WISE): Will Stablecoins Kill Wise, Visa, and Mastercard? - ($)

• 2025-06: Why Wise’s “Governance Problem” Might Be Its Greatest Strength

• 2025-06: Wise ($WISE) - ($)

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.

What the regulator said, and what Wise said the regulator said

The bare facts first. Wise US Inc. filed for a national trust bank charter on 16 June 2025, under the proposed name Wise National Trust.

A national trust bank charter is a specialised federal licence issued by the OCC. It does not permit deposit-taking in the ordinary sense, it does not come with FDIC insurance, and it does not allow commercial lending.

What it does allow, at least in the shape Wise wanted, is nationwide payment clearing, custody and settlement under a single federal supervisor rather than under fifty separate state regimes.

The application stated openly that the new entity would seek membership with the Federal Reserve Bank of Dallas in order to obtain a master account and, through it, a direct connection to the Federal Reserve payment systems. That was the point of the exercise.

On Thursday, the OCC denied it.

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Wise’s announcement to the market is a careful document and worth reading closely. It says the decision relates to an application submitted over a year ago, that the business and its compliance maturity have evolved significantly since then, and that the OCC’s letter refers to historical issues that Wise has been addressing.

It notes that the OCC cited a public multi-state consent order from July 2025, one month after the application went in. It says that the Federal Reserve’s May 2026 proposed change to master account access policy rendered the original approach non-viable, since the application was conditioned on obtaining a master account and the Fed has been pausing access for uninsured trust banks. It confirms that operations continue untouched across 48 states and four territories, alongside a portfolio of more than eighty licences globally. And it says Wise will submit a new application under a GENIUS Act framework in due course.

Read on its own, the announcement describes a company overtaken by a shifting regulatory landscape, judged on a stale snapshot of itself.

The OCC’s letter – which I believe has not been publicly published on the Office of the Comptroller of the Currency's official website yet, so I’m referencing second-hand resources – reads differently. Apparently, the regulator said the application …

• presented significant supervisory and compliance concerns (ouch!), and

• that Wise’s proposed management and board had demonstrated a persistent inability to manage money-laundering and terrorist-financing risks (ouch!).

That’s not the language of a technical mismatch between an old filing and a new framework. Persistent inability is a judgement about people and governance, not about paperwork. And the word choice was not accidental. The OCC published a policy statement in June clarifying that when it denies a filing it must notify the applicant in writing of the reasons, and that it intends to make denial decisions public precisely so the industry can see those reasons.

So these are the two accounts of the same event, and an investor’s first job here is to notice that they are not the same account. I do not think Wise is being dishonest. Everything in the RNS appears to be factually accurate, and the point about the Federal Reserve pausing master account access for uninsured trust banks is entirely true and genuinely material, as I will come to.

But there is a difference between a company saying the road was closed and a regulator saying it did not think you should be driving. Wise’s statement emphasises the first. The letter emphasises the second.

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When those two framings diverge, I generally place more weight on the regulator’s reasoning, because the regulator has no incentive to be harsh and every institutional reason to be measured, and because the OCC in 2026 has been anything but obstructive toward this category of applicant.

Which brings us to the consent order, because it is the hinge on which the whole disagreement turns. In July 2025, one month after Wise filed, the New York Department of Financial Services announced a coordinated action with regulators in Massachusetts, Texas, California, Minnesota and Nebraska, extracting a $4.2 million settlement from Wise US over inadequacies in its Bank Secrecy Act and anti-money-laundering programme.

Wise’s framing is that this is historical, that it responded by strengthening the U.S. programme, improving investigation and reporting processes, fixing the integrity of customer data and adding resources to local compliance.

All plausible, and probably all true.

The regulator’s framing, however, is that a firm which entered a six-state consent order for fundamental AML deficiencies thirty days after asking for a federal charter has not yet demonstrated it can be trusted with one.

Also plausible.

Then there is Belgium, which does not appear in Wise’s charter announcement at all and which the OCC would have been aware of. Wise Europe is based in Brussels and serves the rest of the European Economic Area through passporting, which means law-enforcement requests from across the bloc are routed to Belgium rather than handled nationally. Wise argues, with some justification, that this concentrates requests in a way that would not happen for a bank with branches in each country, and that receiving law-enforcement requests is a normal part of operating at scale rather than evidence of wrongdoing in itself. Fair. But the Brussels prosecutor is reportedly preparing a direct summons, which in Belgian procedure takes a case straight to criminal court without an investigating judge, and the investigation covers more than half a billion euros across fraud, corruption and drug trafficking. No charges have been filed and no findings have been shared with the company. Even so, this is now the third jurisdiction to question Wise’s controls (not to mention CEO Kristo Käärmann’s personal tax compliance troubles with HMRC), after the U.S. states and, going back to 2024, the National Bank of Belgium’s finding that Wise lacked proof of address for hundreds of thousands of customers.

Three separate regulators reaching for the same file is a pattern.

You can dispute what the pattern means. Denying that there is one is harder.

The market reaction, in that light, looks proportionate rather than panicked. Seven percent down, having touched ten at the open. It is the market pricing a longer wait, higher compliance spending, and a raised probability that something worse arrives from Brussels.

Wise is right that nothing operational changed on Thursday. It is also true that something informational did.

My latest deep dive:

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Why did Wise want a banking licence when it spent years explaining why it didn’t need one?

This is the part I found most interesting when I first sat down with the story, and it is where I think a lot of readers will get confused, because Wise’s own leadership has been unusually articulate about why the company deliberately chose not to be a bank. Here is Kristo on an earnings call in early 2025, and it is worth quoting at length because the reasoning is more careful than the summary versions suggest.

“Being a bank really only gives you mostly one thing, which is the ability to lend your business’ holdings to people on this side of the room. And none of our customers are really asking us for that. So you’re not calling and saying, hey, I have this money here, you’re paying interest, but I’d actually want you also to lend it to someone else. So that’s why banking as lending deposits is not really that relevant for us. Of course, because you would be taking, as a customer, huge amount of risk of holding your money with us if we were to lend your deposits. Therefore, this concept of deposit insurance is devised to give you comfort that you should do something as reckless as giving us your money and us lending it. Of course, if we’re not lending your money, you don’t need the deposit insurance.”

That is a genuinely good argument, and it holds up. Wise safeguards customer money rather than lending it. The holdings sit in government-issued or government-guaranteed assets, customers can switch on interest and receive something close to what a central bank pays, and the protection covers the entire balance rather than the £85,000 or €100,000 that a deposit guarantee scheme would cover. Kristo’s point is that a customer is better off, not worse off, for Wise not being a bank in the traditional sense. Read that alongside the charter application and it looks like a contradiction. It isn’t one, and unpicking why gets you to the heart of what this denial actually cost.

The thing to understand is that a bank charter bundles together two entirely separate privileges that have no logical reason to travel together. One is the right to take insured deposits and lend them out. The other is the right to plug directly into the national payment system. For most of modern financial history you could not have the second without accepting the first, and that historical accident is precisely what Kristo was complaining about on the H1 2025 call.

“It was a really weird regulatory setup, let’s say, 5, 10 years ago in the world, where you had to be lending customer deposits to access the payment system. So most regulators have now moved on from that, kind of recognizing that payment companies should have access to payment systems. It’s a relatively fresh change that nonbanks are able to connect. For example, in the U.K., we were the first nonbank to connect to the faster payments. In Japan we were last week the first nonbank to join Zengin as the payment system. So these regulatory limitations used to be in place. They’re now being lifted everywhere in the world, and that has kind of given us the opportunity to join.”

So there is no pivot. Wise has been consistent throughout. It does not want to lend your money and it never has. What it wants is the plumbing, and the trust bank charter was simply the vehicle available in the United States for getting the plumbing without the lending. That is why the application was for a national trust bank rather than a full-service FDIC-insured national bank, and why it was explicitly conditioned on obtaining a Federal Reserve master account. Strip away the word “bank” and the application was a request for a wire into the Fed.

Why does that wire matter so much? Because Wise has done this eight times already and the results are not subtle. It holds direct connections to domestic payment systems in the UK, Hungary, the euro area, Brazil, the Philippines, Singapore, Australia and Japan. Each one means an account with the relevant central bank and the ability to clear payments without a partner bank taking a cut and adding a delay. In Australia, the share of instant transfers went from 24 per cent to 83 per cent after direct integration. In Brazil, bank fees fell 40 per cent. In the UK, bank costs dropped roughly ninefold post-integration and customer contacts fell 75 per cent, which tells you the connections improve reliability as well as price. In Japan, 99 per cent of transfers now settle instantly. This is the single most tangible expression of what Wise means when it talks about a mission to move money cheaper and faster, and it is also, not coincidentally, the deepest part of its moat. Every direct connection is a piece of infrastructure a competitor would need years and a regulator’s blessing to replicate.

Now consider that the U.S. dollar sits on one leg of an enormous share of Wise’s volumes, that the United States is the market Wise itself calls the largest opportunity in the world, and that there are roughly four thousand banks there as potential Wise Platform partners. And then consider that this is the one major market where Wise still routes its dollar flows through correspondent banks, paying middleman clearing fees on volume it already controls end to end everywhere else. Estimates of what those fees represent circulate in the range of twelve to fifteen basis points of volume, which if accurate would be a meaningful share of net revenue, though I have not been able to verify that figure from a primary source and would treat it as an order-of-magnitude guess rather than a number to build a model on. The direction is what matters. Wise pays a toll in its most important market that it has already eliminated in eight others.

There is a second-order benefit that gets less attention and may end up mattering more. A federal charter would have replaced a patchwork of state money-transmitter licences with a single supervisor. Wise currently maintains licences across 48 states and four territories, each with its own renewals, examinations, reporting formats and interpretations. That is a permanent tax on management attention and a structural drag on how fast the company can ship new products in its largest market. Every state that has to be persuaded separately is a state that can say no separately. Consolidating that under one federal regulator would have simplified the operating model considerably, and for a business whose entire strategy rests on driving unit costs down toward zero, structural simplification compounds.

So the charter was never about becoming a bank. It was about removing the last major toll booth in the world’s most important currency corridor, and about trading fifty-two supervisory relationships for one. Both prizes are still there. They are just further away than they were on Wednesday.

Businesses don’t move in straight lines

Investors like straight lines. We build models in spreadsheets where each column is slightly larger than the one to its left, and something in the presentation of that arithmetic persuades us that reality will cooperate. It rarely does.

You might forecast a topline CAGR of 13% over the next four years. A 1% margin expansion each year. The reality looks different. Maybe 18% next year, followed by 7% the year after.

Real businesses sprint, stall, take a step backward, hit an obstacle nobody modelled, and then sprint again. What separates a temporary setback from a broken thesis is not the size of the stumble. It is whether the destination changed.

Example? Google’s FCF just went negative for the first time in history. Show me an analyst who had this in his 10-year model back in 2016!

The Power of Destination Analysis

The above framing owes something to Nick Sleep, whose destination analysis I keep returning to in my thinking.

Sleep’s idea was that most investors spend their energy forecasting the next few steps of a journey when the useful question is where the company ends up if it succeeds at what it is trying to do.

“It is an interesting psychological phenomenon to observe that if our annual results were reordered, we might feel differently about them. For example, place the results in descending order (+80%, +22%, +10%, +9%, +1%) and one is depressed by the decline; place them in ascending order (+1%...+80%), and we tend to think of them more favourably, even though the end result (the destination) is identical. Recent success feels better than distant success, as the brain perceives recent rewards more vividly. Psychologists call this the “availability heuristic” and it is this phenomenon that has sold a thousand mediocre mutual funds that appear, momentarily, to have a pulse! But that is not the way to invest.” - Nomad Partner 2005 Letter

Ask what Wise looks like in ten years if the mission works? Then ask whether Thursday’s news moved that endpoint?

The destination Wise is walking toward is one where it moves trillions rather than hundreds of billions, …

… at a take rate approaching zero, over infrastructure it owns directly in every major currency corridor, with a platform business embedded inside thousands of banks that have concluded it is cheaper to rent Wise’s rails than to maintain their own.

Nothing about a denied trust charter at a single point in time alters that endpoint I believe.

It alters the arrival time.

Sleep described this as well:

“Annual results will bounce around all over the place, and for Nomad more so than more diversified funds. But does that matter if the destination is secure? Indeed, if we could turn U$1 into U$16, does it matter if it takes 18 years or 22 years? There is a difference in the annual compound rate of appreciation (over 3% per annum, and I do not wish to make light of that), but securing the destination is also important. […]

To our way of thinking the question is, what good habits and techniques ensure that the destination is secure (even if the ride is bumpy), and that U$16 will be realised?“ - Nomad Partner 2005 Letter

So this is a no for now rather than a never, I believe.

That distinction is highly relevant, and iny my view it is not just a comforting phrase. The OCC did not rule that Wise’s business model is incompatible with a federal charter, and it did not close the door to a future application. It said this application, from this management team, with this compliance record, at this moment, does not clear the bar.

Every element in that sentence is a variable rather than a constant.

Impact on Wise’s Brand?

Having said that, I want to resist the temptation to wave this away, because there is something genuinely new here and it deserves to be named:

For most of its life Wise enjoyed a kind of regulatory halo. It was the good fintech, the one lowering prices and publishing its fees and beating banks at their own game, and regulators around the world responded by letting it through doors that had been closed to everyone else or at least many others.

First nonbank into UK Faster Payments. First nonbank into Zengin in Japan.

In 2026, that halo has dimmed. Three jurisdictions have now examined Wise’s controls and come away unimpressed, and you would fool yourself believing that these regulators do not talk to each other.

The OCC letter did not emerge from nowhere; it emerged from a file that includes a six-state consent order and, almost certainly, an awareness of what Brussels is doing. Wise now gets the hard look rather than the benefit of the doubt, and that is a change in operating conditions rather than a one-off event.

Time to roll up its sleeves and get to work! Time to do better.

Short-Term Costs

What does the hard look cost?

Start with precedent. Lookback reviews and remediation programmes of this kind are not rare, and the UK provides two useful comparisons in Starling and Monzo, both of which went through extended compliance remediation under regulatory pressure.

Broadly, one of our community members estimate the profit impact ran to something like ten to fifteen per cent for eighteen months to two years.

Now adjust for Wise’s specific situation, and the adjustments cut in both directions. Wise has far more transactions than either, which means the variable cost of additional human review scales unpleasantly. It also has far more profit, which means the denominator is much larger and the same absolute spend hurts proportionally less.

And the biggest single component, redesigning the compliance architecture itself, is largely a fixed cost that gets amortized across a volume base growing 20-30% percent a year.

The exact one-year impact does not really matter in my opinion. 5%, 8%, or 13%? Who cares? Call it a pause in profit growth for around a year, assuming Wise does not throttle customer acquisition to protect margins, which I do not think it will and would not want it to. I want Kristo to remain laser-focused on Wise’s destination. Invest aggressively in internal controls and whatever else is needed to make sure no regulator can derail you from your long-term destination.

Added Friction

There is a subtler cost that does not show up in that calculation. Wise’s cost advantage comes substantially from automation. Its whole architecture is built on doing at machine cost what banks do at human cost, and that applies to compliance as much as to payments.

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If remediation forces more human review into the onboarding and monitoring flow, it adds friction in precisely the place where friction is most expensive, both in unit economics and in customer experience (e.g. speed of transaction). Slower onboarding is lost customers. Slower transfers.

More frozen accounts (apologies for the size of the screenshot below; not a good look).

That is the version of this cost that would worry me if it persisted, and it is worth watching in the business-customer numbers over the next several quarters, since business onboarding is where Wise has previously paused growth to fix exactly this kind of problem.

Brussels might even demand Wise to slow customer onboarding to fix internal and AML/KYC controls first.

Scale Will Solve a Lot of the Concerns Discussed Above

Even so, I am not especially worried about the cost structure over any horizon that matters.

This is a business whose entire logic is scale economics shared, and scale solves cost problems if you let it run.

Wise grew cross-border volume at a very high clip last financial year to $243 billion, grew active customers to 19 million, and did that while deliberately cutting its own take rate to 52 basis points. It generated $2.5 billion of net revenue, up nineteen percent, and $660 million of income before tax at a 26.4 percent margin, above its own target range. It announced a buyback exceeding $500 million.

A company with those characteristics can absorb a three-year compliance programme without anyone needing to reach for the smelling salts.

I went through why I think the last set of results was substantially better than the market understood in my recent live stream …

,… and I laid out the broader case for the massive embedded operating leverage in Wise’s model as the company scales in the article below:

“Second, the consensus believes that Wise’s unique cost-plus pricing strategy naturally limits its ultimate profitability, but in this write-up, I argue that the business might reach a point where it will post long-term profit margins vastly superior to current market assumptions – potentially reaching 40% (or more!) as its massive operating leverage unlocks. Why should Wise not achieve 40% pre-tax margins once it captures a dominant share of the global money movement market? The consensus assumes that aggressive price cuts destroy terminal value, failing to recognize that lowering fees is actually a powerful customer acquisition tool that widens an unassailable structural moat.“

In light of today’s news, this sounds like a moonshot prediction, and I agree that that’s the absolute bull case, but I still think the logic I outlined in the piece is sound.

Here is the reframe I keep coming back to, and I recognize it is the optimist’s reading, so treat it accordingly: Read what’s shared about the OCC letter again. Persistent inability to manage financial crime risk, at a company processing 4.7 million transactions a day across 160 countries. If that assessment is even partially accurate, Wise needed to hear it. A firm on a mission to move trillions cannot get there with compliance infrastructure that three separate regulators have found wanting, and it is better to be forced to rebuild that at nineteen million customers than at ninety (indirect) million.

Painful, expensive, embarrassing in fact, and probably necessary.

Zoom out five to ten years and I suspect this period gets remembered as the one where Wise was made to grow up!

Base Rate Analysis: What usually happens to applications like this?

Before I offer an opinion on whether Wise gets its charter eventually, I want to do the thing that opinions are usually a substitute for, which is to look at what happened to everyone else who stood in the same queue.

Base rates are unglamorous work, but they are almost always more informative than any inside view. I did that work with the help of my Claude “AI superforecaster.”

So … here a brief summary (I shared the entire output in my community): applications by non-bank fintech, payments and crypto firms for an OCC national trust bank charter, 2020 to 2026, the modern wave of non-depository chartering. Nineteen named applicants, eleven with resolved first decisions, five still pending, three lapsed or withdrawn.

That is the tightest comparison set available to Wise, and it is worth noting up front how small it is (weight of evidence).

Of the eleven resolved cases, eight were approved outright. Anchorage, Circle, Ripple, BitGo, Fidelity, Bridge, Crypto.com and Sony Bank all cleared.

Two received conditional approval and then let it lapse without ever opening, Protego and Paxos, both having missed an eighteen-month build-out clock.

And one was denied outright. That one is Wise.

Oops.

Embarrassing.

Read that again, because it inverts the story most people are telling themselves this week. The modal outcome in this class is approval, at roughly seventy-three per cent, and the general reading that the OCC is hostile to fintechs seeking federal charters is simply wrong on the evidence.

Under Comptroller Gould the agency approved five national trust charters in a single day in December 2025 and ten inside eight months, a pace with no historical precedent. There are structural reasons for that. A national trust charter carries no deposit insurance, which keeps the FDIC out of the decision entirely, and the FDIC has historically been the harder veto point. The OCC’s own judgement is close to dispositive, and the OCC has signalled it wants more of these, not fewer.

Which means the comforting version of this story is unavailable. Wise is not a casualty of a closed door. Wise is the only outright denial in the entire modern wave. Every other non-approval in the class was a self-inflicted operational lapse rather than an adverse finding about the applicant.

That is a genuine tail, and it is worth pausing on what it implies about the regulator’s process.

The OCC had two softer off-ramps available and used neither. It could have negotiated toward a conditional approval with conditions attached. Or it could have let Wise withdraw quietly, which is the route problematic applicants normally take, as Figure Bank did under litigation pressure from state regulators.

Instead the agency issued a formal, public denial with a fitness finding attached. Regulators do not generally reach for the most confrontational instrument available when a gentler one would do the job.

There is a hole in that arithmetic, though, and it is worth digging into before anyone takes seventy-three per cent to the bank. We just hinted at it. Approval rates measure the applicants who stayed in the queue. They tell you nothing about the ones who were encouraged to leave it, and in federal chartering the encouraged exit is the normal way a weak application dies.

Monzo withdrew its U.S. national bank charter application in 2021 after the OCC signalled disapproval over governance structures and a limited Community Reinvestment Act footprint, and it never got back in, eventually exiting the U.S. market entirely.

Robinhood abandoned its application in 2019 amid regulatory pushback on risk management controls. Brex and Rakuten each withdrew industrial loan company applications with the FDIC after years of delay. Figure Technologies gave up its uninsured nonbank charter path under aggressive legal opposition from state bank regulators and pivoted back to a conventional FDIC-insured structure.

Five firms, five different flavours of no, and not a single formal denial among them.

Those cases sit outside the tightest comparison set, since Monzo and Robinhood wanted full deposit-insured national charters and Brex and Rakuten were dealing with the FDIC rather than the OCC.

The instruments differ, which is why they arguably do not belong in the tightest reference class. What they do establish is the mechanism, and the mechanism is what makes Wise’s outcome strange.

Regulators generally prefer the quiet exit. It spares the applicant a public record, spares the agency a written justification that can be litigated, and leaves the door open for a future conversation. The withdrawal is the polite door.

Wise was not shown that door, or was shown it and did not take it. If the OCC never offered the off-ramp, the agency wanted the finding on the public record. A formal denial is the loudest available outcome in a process that offers several quieter ones, and Wise received it while eight comparable applicants were being waved through.

To wrap up, again, if withdrawals under regulatory pressure are counted as failures rather than as absences, the real difficulty of the federal chartering gate is meaningfully higher than eight out of eleven suggests, and the modern trust-charter wave looks less like an open door and more like a door that opens for applicants with clean files.

Reapplication Base Rates

Now to another question that matters, which is what happens on reapplication. Here the data thins out to almost nothing. Two firms in this class reapplied after a first-attempt non-approval, Protego and Paxos, and both eventually succeeded.

Two out of two. A hundred per cent success rate on a sample of two, which is the kind of statistic that should make you nervous rather than reassured.

Protego took around three years. Paxos took around two and a half. So the timeline precedent for a successful second attempt is closer to thirty months than to the eighteen-to-twenty-four many commentators are throwing around today.

And there is a caveat here that must not get smoothed over. Both Protego and Paxos failed the first time by missing a build-out deadline. Neither was denied on management fitness or anti-money-laundering grounds. There is no precedent in this class for what happens after a denial of Wise’s specific type. Not a thin precedent. Zero. Any probability anyone attaches to Wise succeeding on reapplication, including the one I am about to give you, is a constructed judgement rather than a measured frequency, and it should be treated with corresponding suspicion.

With that caveat out of the way, my own directional estimate is that Wise probably does eventually get a federal charter of some kind within about three years, either as a national trust bank or under a GENIUS Act framework. Moderate confidence, driven by the strongly pro-charter posture of the current OCC and by the fact that the agency has approved almost everyone else who asked. Being denied again or stalling indefinitely is a meaningful possibility rather than the base case, driven by the fact that the underlying finding is about recurring cross-jurisdiction AML deficiencies that remain unresolved.

Three reasons this case might break the base rate

The first is the one I have already circled. A denial citing a persistent inability of management and board to manage financial crime risk is a fitness finding rather than a clock miss, and fitness is qualitatively harder to cure on a fixed timeline than operational readiness. You cannot schedule your way out of an assessment about judgement. What you can do is build a record, and there is an observable that tells you whether it is working: the state regulators’ two-year monitoring period under the July 2025 consent order runs through mid-2027, and whether that produces clean progress reports is the single most useful confirming or disconfirming signal available. Watch also whether any subsequent OCC statement frames the deficiency as remediable.

The second is the framework switch, and this is where I part company with the more relaxed readings of Wise’s announcement. Wise says it will reapply under a GENIUS Act framework. Every single approval in the comparison set, Circle, Sony Bank, Ripple and the rest, was granted under the pre-existing national trust bank statute, before the OCC’s GENIUS Act implementing rule was even finalized in February 2026. The GENIUS Act nonbank pathway has produced zero completed approvals to date. So Wise would be a first mover in an untested process with no timeline precedent whatsoever, having just been denied under the tested one. There is an argument that this is clever, that it sidesteps a statutory objection the banking lobby has been pressing, and I will come to that objection shortly. There is also an argument that it swaps a known process for an unknown one at precisely the moment when predictability has value. The observable to watch is the first completed GENIUS Act nonbank issuer decision from any applicant, whoever it is, because that sets the real clock.

The third is the one that should temper enthusiasm about a successful reapplication even if it arrives. An OCC charter is necessary but not sufficient. The Federal Reserve paused decisions on payment and master account access for Tier 3 institutions, meaning uninsured trust banks without a Fed-regulated holding company, which is precisely Wise’s category, through the end of December 2026 while it finalizes the payment account framework. Circle, Paxos, Anchorage and BitGo are all already OCC-chartered and all sitting in that same queue. Getting the charter does not get you the wire. Watch the Fed’s final payment account rule, comments on which closed on 27 July, and whether the Tier 3 pause lifts, extends, or hardens into something permanent.

Same kind, or different kind?

There is one more question a base rate cannot answer and that I think determines everything, which is whether Wise’s regulatory problems are a series of unrelated stumbles or one recurring problem wearing different hats.

• In 2021, the National Bank of Belgium forced Wise into a remediation plan after finding it lacked proof-of-address documentation for hundreds of thousands of customers.

• At some point before 2025, Abu Dhabi’s market regulator fined Wise $360,000 for gaps in its AML systems.

• In July 2025 six U.S. states fined it $4.2 million for AML and Bank Secrecy Act programme deficiencies covering an examination period from July 2022 to September 2023, specifically citing inadequate independent review frequency and deficient suspicious activity investigation and reporting.

• In June 2026 Brussels prosecutors confirmed a criminal AML investigation into roughly €500 million of transactions.

• In July 2026 the OCC denied the charter, citing persistent inability to manage AML risk.

Same kind. Every entry on that list is the identical underlying finding, deficient customer due diligence, transaction monitoring and suspicious activity detection, recurring across four regulators in four jurisdictions and across two legal postures, civil consent orders and now a criminal investigation, over five years. This is not a one-off that happened to land during a charter review. It is a documented pattern in the exact domain the denial is about.

Which brings me to what I think is the genuine misreading in this week’s coverage. The loud risk this week, the one in every headline and already in the share price, is the charter denial. Based on our base rate analysis, denial is the tail outcome and the class strongly favours eventual approval on some timeline.

The other risk is Belgium, and it is structurally worse. A criminal AML finding in the EU could produce standing supervisory constraints, transaction monitoring mandates, capital add-ons, growth caps, that throttle the compounding rate of Wise’s core European volume for years.

Belgium is where Wise Europe is licensed and it is the passport that lets Wise serve the entire EEA, which is a larger share of global transaction volume than the U.S. trust charter would ever have touched.

There is a rough analogy in MoneyGram, which settled a deferred prosecution agreement with the DOJ in 2012 over AML failures, only for deficiencies to persist and the agreement and monitorship to extend through 2018 with an additional $125 million penalty, years after the original headline had faded. I flag that as a directional analogy rather than a verified case study, since I have not gone back through the primary documents.

So if you are going to watch one thing over the next twelve months, watch Brussels rather than Washington. Any statement from the prosecutor’s office on charges, a settlement or a closure, and any parallel move by the National Bank of Belgium on Wise Europe’s licence conditions.

The charter is a slow-burn story about American growth optionality. Belgium is a live risk to the large revenue base Wise already has.

Wise remains still completely misunderstood

I have a private test for whether someone has actually done the work on Wise, and it takes about thirty seconds. Ask them who the competition is. If the answer comes back Revolut, or Remitly, or Nubank, the conversation is over, because those three comparisons each fail for a different reason and the fact that people reach for them tells you they are looking at the app rather than the business underneath it.

Revolut is a neobank assembling a full financial product suite for consumers, monetizing through interchange, subscriptions, trading and increasingly lending. Its charter application in March 2026 was for a de novo national bank with FDIC insurance, personal loans and credit cards, because that is what its model requires.

Remitly is a remittance business, serving a specific corridor pattern with a specific customer, competing largely on distribution and brand in the migrant-worker market.

Nubank is a Latin American consumer bank of enormous quality whose economics run on credit.

None of these is what Wise is. Wise is closer to infrastructure than to any of them, a company that has spent fifteen years building direct connections into national payment systems and is now renting that plumbing out to the banks it was once positioned against. UniCredit, Raiffeisen, MBSB and Capitec did not sign up because they liked the consumer-facing app.

The confusion gets worse when people look at the take rate. Wise cut its average take rate to 52 basis points last year, and management has told the market it intends to take out another one to two basis points per quarter through FY27, with one already gone in Q1. To a conventional Wall Street analyst, this reads as margin erosion under competitive pressure. It is the opposite, and the CFO volunteering the cadence unprompted on a call is the tell. Management teams in trouble do not pre-announce that they will compress their own pricing every quarter for the next year.

Only two kinds of company do that: the inept, and the ones executing so well that lower prices are a weapon rather than a concession. Wise invests in lower prices.

You could call this the Jensen paradox, after the pricing philosophy of deliberately giving away performance gains to expand the addressable market rather than harvesting them. Wise lowers its take rate, which makes it more attractive to customers, which brings volume, which lowers unit costs through scale and through the direct connections that volume justifies building, which funds the next price cut.

That flywheel is well understood by people who have studied Costco or Amazon and almost completely misunderstood when it appears in financial services, where the reflex is to treat every basis point of take rate as sacred.

The customers are not the only audience for those cuts, either. A bank evaluating whether to build its own cross-border capability or rent Wise’s is doing a cost comparison, and every basis point Wise removes from its own pricing moves that decision further in Wise’s favour.

Lower take rate is a customer acquisition tool for the platform business.

A VIC write-up put it well a while back, and it has stuck with me:

“Wise Platform is already established as a serious partner for retail FX, especially for challenger banks serving tech savvy and wealthier clients. But the commercial market is 20x bigger. Massive traction in the commercial market is the only way Wise has a chance to be a £100+ billion company. I think a lot of investors are skeptical that they can take significant share in the B2B space – in the quarter ending March 2024, Business volumes only grew 10% Y/Y. It was very ‘explainable’ – a pause in taking new business customers while they invested in better KYC/UBO onboarding. In the most recently reported quarter, that growth rate is back up to 20%, but a lot of doubts persist. With sub 1% market share, it seems like a world beating company could easily be posting 50% growth rates.”

That skepticism was reasonable when it was written. I think it has been answered. Business volumes have been the engine of the last several quarters, and the reacceleration is exactly what the bull case required.

Note also what caused the original slowdown: a deliberate pause in business onboarding while Wise rebuilt its KYC and beneficial-ownership processes. Which is to say, the same category of compliance investment that the OCC has now demanded, producing the same temporary optical damage, followed by faster growth on better infrastructure.

That is not proof the current episode resolves the same way. It is a precedent worth holding in mind, and it is one reason I am reasonably calm about the next eighteen months.

Then there is the question of what else gets built on top. Wise has been debit-only and low-margin by design, and the assumption that this is all it will ever be strikes me as a failure of imagination.

’s scuttlebutt work on Wise’s job boards is the most useful primary research I have seen on this, because hiring tells you where a company is spending energy months before it announces anything:

“One of my favorite research things I do is finding scuttlebutt and reading job boards for companies I’m researching. It’s a real-time snapshot of where they’re actually putting money and energy before they officially announce it to the public. Five things Wise is building:

Accepting card payments. Wise made its name on sending money abroad. Now they’re building the opposite. Letting businesses and online stores accept card and wallet payments through Wise in 17+ currencies. That’s Stripe and $ADYEN territory, and they think they can do it 30-50% cheaper.

Stablecoins (for real). Last year it was one crypto role. Now it’s a licensed stablecoin and digital-asset team in Dubai under VARA. They play crypto down in public. The hiring says otherwise.

A US bank charter. They’ve applied to charter ‘Wise National Trust’ to land a Federal Reserve master account and plug straight into US payment rails. Investing, coming to North America.

Wise Assets already holds ~$9B. They’re building the US broker-dealer and a Canadian investment dealer to bring it over. Fee income that doesn’t ride interest rates.

Auto-collecting subscriptions. A new product letting businesses pull recurring payments automatically, built on a direct-debit engine. Wise Business is becoming a full business bank account.”

Read that list and then reread the market’s reaction to the charter denial. Four of those five initiatives are entirely unaffected by Thursday. Card acquiring, stablecoin infrastructure, Wise Assets in North America and direct-debit collection all proceed regardless of what the OCC decided, and each is a higher-margin revenue line stacked on top of infrastructure that already exists and is already paid for to some extent.

There is also growing evidence Wise will offer credit cards, most likely as a program manager rather than an issuer, which would let it undercut banks on the FX rate while running the programme more profitably than the incumbents. High-margin revenue on top of cross-border rails. That is the shape of the next decade, and none of it requires a charter.

Downside Risk Thought Experiment

I want to close this section with a thought experiment rather than a valuation, because I find it more useful for thinking about downside than any multiple I could construct.

Ask what Wise’s infrastructure is worth to somebody else. Not what the equity is worth on the market today, but what a JPMorgan or a Citi or an HSBC, institutions moving trillions across borders for corporate clients over correspondent networks they know are expensive and slow, would pay to Wise’s network and growing list of platform partners?

My honest guess is a number that makes the current market capitalisation look silly.

Kristo controls the company and would never sell in my view – he loves building the company too much – so this will not happen and is not a thesis. But it is a floor of sorts, and floors are worth knowing about on days when the stock falls ten per cent on news that changed the timeline rather than the destination.

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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.

Imagine a software monopoly company that nearly quadrupled its revenue, from around $250 million to almost a billion dollars over the last nine years.

Yet, the stock itself rewarded its shareholders with precisely nothing. The stock is flat versus where it traded in July 2019. Seven years of really strong compounding growth, seven years of dead money.

In fact, more recently, it’s down 64% from its high as I write this (update: in fact, the stock ended yesterday’s trading session down 5%, bringing the total drawdown closer to 70% as of July 23, 2026).

Interesting setup!

On paper, that pairing shouldn’t be possible (or at the least not rational), and when a market hands you a monopoly business growing that fast – revenue compounded at nearly 20% over the last ten years and the PEG ratio sits below 1x – at a price that’s gone nowhere, the interesting question is whether the market knows something you don’t, or whether it is making a mistake and mispricing this equity.

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I think it might be the second one, and this post is my attempt to prove myself wrong before I let myself believe it.

What this deep dive covers:

We cover the key thesis in about 8,000 words:

• The five-part bull case (”Bam Bam Bam Bam Bam”)

• What went wrong

• The one event that I watch for that could create a generational buying opportunity

• 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.

If you then want to dig deeper, we cover the business, the management team, detailed valuation work, etc. in the subsequent sections (another 10,000 words).

• The origin story

• The business itself

• Unit economics analysis

• The customer

• Legal structure, cyclicality, and operating leverage

• The moat

• Is it a good business in a good industry

• Management and governance

• Growth drivers and forecasting

• Margins outlook

• Valuation (including two downloadable models)

• Other interesting findings

Let me set the scene with the problem this company solves. Not long ago, the largest corporations on earth assembled their most sensitive regulatory filings through a process best described as organized panic.

Fragmented Word documents labeled “Q3_10Q_Draft_v8_auditor_comments_FINAL.docx.” Spreadsheets (“Tax_Provision_2025_vFINAL_adj_check_tab.xlsx”) that didn’t reconcile. Someone checking printer proofs line by line last-minute, praying a wrong number hadn’t slipped through before the midnight deadline.

This company, Workiva, turned that chaos into something closer to a self-driving workflow, where changing a single figure at its source updates thousands of linked instances across every document in seconds.

Dull-sounding work. Mission-critical work.

And it now runs the plumbing for a shocking share of corporate America.

How shocking? The platform serves 95% of the Fortune 100, 89% of the S&P 500, and more than 85% of the Fortune 500.

It handles roughly half of all US filers, yet those filers represent something like 85% of total US market capitalization, which tells you the biggest and most complex companies are the ones that can’t live without it.

For instance, it just won SpaceX ahead of its IPO.

The AI standard-bearer, Anthropic (prediction markets point to a late 2026 IPO), is a multi-solution customer.

This is a hidden giant sitting underneath the disclosures of the global economy, and almost nobody outside its industry can name it.

So why is it potentially in the bargain bin? One word, and you already know it:

AI.

The dominant fear across software is that generative models and autonomous agents will make platforms like this one obsolete, and the multiple has compressed sharply, even as profitability hit an all-time high.

My hypothesis runs directly against that fear. In a zero-tolerance regulatory environment, an AI that hallucinates a number is a liability (!) rather than an assistant, and this company has spent fifteen years building the one thing those agents need to be trusted at all: structured, validated, auditable data with traceable lineage.

The technology the market thinks will kill it may be the technology that makes it even more indispensable.

That’s the case I’ll build and then attack across the rest of this piece – the near-monopoly, the moat, the management pivot, the balance sheet, the risks, and finally what I think the whole thing is worth (or what kind of returns the stock may generate from the current starting level).

If the hypothesis survives the beating, the disconnect between this company’s growing business and its stagnant stock starts to look like one of the more interesting setups in software right now.

High-Level Thesis: “Bam Bam Bam Bam Bam”-90 Second-Hypothesis

I always start with Bill Miller – and I won’t get tired of it – who once made an observation that every analyst should tattoo on the inside of their eyelids: portfolio managers have ultra-short attention spans, and almost none of them wants to sit through a pitch longer than 90 seconds. He liked to tell the story of Peter Lynch, who kept an egg timer on his desk. An analyst would walk in to pitch a stock, Lynch would flip the timer, and the poor soul had 90 seconds to make the case and get out. No preamble. No throat-clearing. Just the goods.

Miller’s own template was equally blunt. You name the company, you give the price and the 52-week range, and then you fire off the reasons in rapid succession.