Tag for finding my other articles on this stock: BN

Key takeaways

A slower growth quarter with acceleration expected through the year. Private credit worries are not systemic and Brookfield’s areas of exposure are fine. Momentum is accelerating in real estate. Merging BNT (insurance) back into BN gives the insurance operation a huge capital base. Both BN and BAM have bought back significant amounts of stock recently.

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Thesis and valuation update

No major change.

• Probably the single thing that stood out to me is that office construction costs have risen so significantly that the rents required to justify newbuilds are sometimes double current market rents, and demand is growing.

• 2026 will be a record year for fundraising.

• There is useful discussion of insurance capital and use of Bermuda reinsurers in the BN call.

• Most of Brookfield’s insurance business is life/annuity, but they have a small P&C insurer which they are increasingly talking about scaling.

• BEP have commented for several quarters now that battery costs have come down so much that they are economic for balancing grids an evening out renewable generation.

• I recommend reading letter too - good discussion about how little macro matters, and how they observe, test, and perfect businesses before scaling them.

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Notes (please note these are call summaries. I don’t dive into the detailed reporting every quarter).

BN

• DE $1.6bn, $6bn LTM, and will strengthen through the year. DEBR $0.59/share, up 7%, LTM $2.32/share.

  • Advanced $17bn of sales “substantially all” at or above marks.

  • Realised $157 of carry into income and have $11.8bn unrealised.

  • Think carry inflects in 2h as sales accelerate.

  • Partially monetised a tech investment at a gain. Growing relationships with tech companies are leading to interesting investment opportunities for the BN balance sheet and clients - they have $2bn in tech of which $1bn is SpaceX at its pre-IPO mark.

  • YTD have bought back $470m of BN shares plus $575m at BAM.

• Macro developments “often receive far, far more attention than their long-term impact warrants. Bottom line, we largely try to ignore them when building our business…Our role as investors is to capitalize on attractive entry points to acquire good businesses for value, operate them well and allow compounding to work over time…We take the time to watch an industry, learn how it works, invest in a measured way, refine a business model and only then scale a platform. This allows us to make small mistakes while avoiding large ones. In our experience, successful businesses are not built quickly. They are built deliberately.”

• Private credit: “there are issues that are grabbing a lot of headlines, but in the scale of the broader investment markets, their materiality is low [and] as it relates to Brookfield, these are very immaterial asset classes to us based on our deliberate posture…our credit portfolio is performing incredibly well.”

• Real estate.

  • Sentiment is now catching up with fundamentals. “Buyers looking for solid assets are moving back from software to real assets like these.”

  • In office, signed 2.6m ft2 of leases, 15% above the expiring levels.

  • Office replacement costs have risen significantly. Rents required to justify new construction are double current market rents in many markets. This makes new supply very difficult to deliver.

  • Manhattan West was started in 2020. It cost $1000/ft2; would be $2,500/ft2 now. Most recent lease was signed at nearly 3x the rent of the first lease, and is still not high enough to justify new construction. Recently refinanced this: $1.9bn 10-year nonrecourse mortgage, including $400m cash extracted, at 5.5% - a 107bp spread to treasury.

  • One Leadenhall was fully leased within 6 months of completion and achieved the highest rents ever in the city of London.

  • In retail, tenant consolidation into top-tier malls continues to drive demand. Commenced 1.6m ft2 of leases, 11% above prior levels.

• Brookfield Wealth Solutions

  • Insurance has $180bn in assets, $20bn of regulatory capital, and over $2bn of annualised earnings.

  • Origination

    • “Our priority is not maximizing volume but generating high-quality, durable earnings.” Goal is to compound equity capital at 15% with low risk and generate stable earnings.

    • Aging and the decline of defined benefit pensions creates a long runway for growth.

    • Annuity demand in the US is down 9-10% y/y but Brookfield has picked up 4pp of share.

    • Recently launched on 2 major bank platforms with more to come. Brookfield sell 1/3 of annuities through the bank channel vs. peers at 2/3.

    • Will write $25bn of new policies in 2026.

    • Outflows will be $10-12bn - average liability duration is 8-9 years.

    • Asia - early stages of building a presence in a very significant market, with growing interest from counterparties.

  • Spreads

    • LTM deployed $15bn into Brookfield strategies at an average total return exceeding 10%.

    • Spreads compressed slightly this q. Annuity rates peg to the back end of the curve but cash from newly sold annuities earns the short end until it can be deployed. When the yield curve steepens, therefore, spreads compress slightly. What matters in the long run, however, is the total return over the life of the annuity.

    • Brookfield are well positioned to invest globally for best total return. “We’re trying to build a business where at the top of the house, we can move our capital around to geographies and products, and we can do that without any conflicts or clients or other invested capital partners sitting in any parts of the business.”

  • Capital

    • Each policy-writing company is rated A or A- by the 3 major agencies, and 2 have received upgrades over the last few years.

    • Brookfield generally operate at about 4x the regulatory minimum capital requirement, not including the excess capital at BN.

    • UK is moving against use of Bermudan companies to reinsure pension risk transfer deals. No impact: Just doesn’t use Bermuda as a reinsurance jurisdiction, and anyway Bermudan capital rules align with the UK and Europe so repatriating reinsurance won’t affect competitors either. (My notes: the Bermuda regulatory regime is Solvency II equivalent and for US purposes Bermuda is a NAIC reciprocal jurisdiction. In 2024 Bermuda overhauled its rules to remain Solvency II equivalent, specifically targeting the life reinsurance and annuity block transfer markets where PE-backed reinsurers were taking advantage of Bermuda’s more lenient capital eligibility rules for private credit. Bermuda’s approach to assumed default and downgrade costs on private assets now reportedly results in higher costs than those applied to a reinsurer authorised by the UK PRA, so the competitive advantage of Bermuda domicile now rests primarily on the Pillar Two corporate tax rate of 15%).

    • The planned merger of BN and BWS creates a fully integrated insurance/investment operation and gives insurance a vast permanent capital base.

  • Closed acquisition of Just Group.

    • Leading pension risk transfer and individual annuity provider in the UK. Serves 700k UK pensioners, has $40m of assets. Going-in valuation gives a 10-12% return.

    • Brookfield can improve Just’s investing so that it can grow its £5bn of annual originations.

    • Just is very good at operating small pension schemes, where there is not much competition.

    • With BN’s capital and asset origination, they can also move into large deals, where there is also not much competition. (Competition is in the middle.)

  • Clearbrook (P&C) achieved a 99% CR. Important diversifier into specialist insurance. Have worked hard to exit some lines, derisk liabilities, and grow profitably. Expect opportunities to grow organically and via M&A as the P&C market softens.

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BAM

• FRE +11%, DE 7%.

  • FBC +12%.

  • LTM FRE 18%.

  • Sold $8bn, invested $34bn,

  • Will exceed long term growth targets in 2026.

  • Have bought back $800m over the last 7 months.

  • After the q, they issued $550m of 5y notes at 4.83% and $450m of 10y notes at 5.3%.

• 2026 will be a record fundraising year by a significant amount.

  • Including Just Group and flagship PE, YTD fundraising is $67bn, over half of total 2025 fundraising.

  • Each of Primary Wave, 17Capital and Pinegrove recently recently closed funds that were their largest ever and the largest of their kind.

• Oaktree closes in 2q. Benefits: easier to create customised solutions combining both companies’ products, and potential to optimise 2 balance sheets.

• “One of the clearest ways our platform is evolving is in how we engage with our largest clients.”

  • Investors are consolidating more of their business with fewer managers that can invest at scale across asset classes and geographies and up and down the capital structure.

  • Conversations are leading to broad strategic relationships and customized solutions using insights from across the Brookfield ecosystem.

• Real estate recovery is accelerating.

  • “What we’re seeing on the ground is far ahead of what you’re reading in the headlines”.

  • Significant increases in transaction activity and valuations. Primarily hospitality, logistics, housing, so far - less in office and retail but that will follow - “the fundamentals for office are absolutely flying…in Tier 1 markets, we’re seeing [rents] 50%, 70%, 80% higher than they were 5 years ago”.

• Credit

  • Spreads post-covid were excellent. That attracted capital and spreads compressed. They didn’t maximise growth in this period and “it’s important to separate the fundamentals of private credit from the excesses in select parts of direct lending.”

  • “We have always preferred areas where underwriting matters, where structure matters and where there is real downside protection, notably real asset credit, asset-backed finance and opportunistic credit”.

  • If there is a broader dislocation, Oaktree benefits.

    • “When liquidity becomes scarce and capital is repriced, that is when disciplined investors with flexible capital and deep experience have historically generated some of their best returns.”

    • “We are already tracking dozens of emerging opportunities in real time”.

    • Could deploy tens of billions in a proper credit dislocation but “today, we don’t see a broad-based macro condition that would result in meaningfully higher deployment patterns than what we’ve seen over the last 5 years. But we always see sector-specific distress. Today, we see distress in software, building products, chemicals, autos, packaging.”

• AI: “While there is a significant amount of capital flowing into the sector, the investment opportunity set is incredibly vast. And as a result of that, we can be incredibly selective. We can focus on the best assets in the best markets with the best revenue constructs and the best corporate credit counterparties.”

• Penetration of the individual wealth market is accelerating fast. With respect to 401ks, they are in advanced discussions with some of the largest target date fund providers to put real asset products into default portfolios.

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BIP

• FFOPU $0.90, up 10%.

  • Sold or agreed $1bn in sales.

  • Refinanced $1.5bn of nonrecourse debt.

  • Will exceed 10% FFOPU long term growth target this year.

• Assessing merging BIPC and BIP to form a single entity.

• New framework with a leading global OEM - exclusive long term leasing platform for industrial equipment, including for data centres, without residual value interest rate or refinancing risk. $375m (BIP share) over 24 months.

• Intel JV on schedule with first earnings in 3q26.

• Canadian midstream business seeing strong demand - completed $400m of growth projects over the last few months that are now ramping, and have $8bn of bite sized, straightforward, low-multiple growth projects ahead.

• Looking at an IPO for Csquare.

• Tremendous demand across datacentres, compute, fibre, grid stabilisation, behind-the-meter power.

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BBU

• Ebitda $582m, down on sales. LFL ebitda was up 5%. EFO $279m.

• Completed corporate simplification.

• Clarios is $15 per share in NAV at 9-10x ebitda and can 2x in 5y driven by advanced batteries (higher market share and higher margins), cash generation, and tax credits. Clarios received $1bn of tax credit cash this quarter, or $1.50 per share. Expect similar amounts annually through the decade.

• Sold 27% of La Trobe, an Australian asset manager and lender, at an implied 3x MM in 4y.

• Committed to lead a $500m investment ($150m BBU share) alongside OpenAI into the new OpenAI Deployment Company.

  • Primarily an advisory/services business which they know is needed from their own work.

  • Investment is a preferred with >15% upside CAGR but low downside.

  • Also gives the Brookfield ecosystem access to leading technology early.

• Sagen (Canadian residential mortgage insurer) has grown share, reduced expense ratio, and optimised capital efficiency under Brookfield.

  • ROE has gone from low double digits to over 20% and the business can distribute $400m per year over the cycle.

  • House prices are down 20% since early 2022.

  • 80% of the portfolio is fixed rate and most of the remainder have constant payments (so only the mix between interest and variable changes with rates).

  • Loans have full recourse, all insured borrowers in Canada are subject to a stress test that builds in a cushion for affordability in a rising rate environment, and insured borrowers facing financial hardship can extend amortizations.

  • Losses are therefore driven by unemployment (frequency) and home prices (severity). Both are manageable with resilient employment and significant homeowner equity.

  • Loss ratio has risen from 5% to 12% on severity, mainly on 2022/23 vintages with less equity. They price for long run loss ratios of 15-20%. Will be below that this year, but the last few years have been abnormal with strong employment and house price appreciation.

• BRK won a new concession in north east Brazil. Meaningful but will take time to ramp. Interest rates falling which may open an IPO window.

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BEP

• FFOPU +15% to $0.55. LTM FFOPU $2.08, up 12%.

  • Deployed or committed $2.2bn/$550m net.

  • Sold/agreed sale of $2.8bn/$800m net.

  • Closed $4bn of financing including CAD500m of 30-year notes at tightest spread ever.

  • Corporate level debt maturity now 14y.

  • Brought 1.8Gw online (LTM: 9Gw, up 2x in 2y) and contracted 1.7Gw from pipeline.

• Between strong demand and strong bids for mature assets, feel they can grow medium term FFOPU ahead of the 10% long term target.

  • Capital recycling is driven by value - if recycling mature assets generates more value than holding them, they sell. Bids are currently strong. Created Northview Energy in partnership with BCI, Norges Bank, and a Brookfield fund. BEP will sell mature, derisked renewables assets to Northview.

  • “Demand continues to go up. It is higher today than it was last quarter. It’s higher today than it was last year.”

• Good progress on the Westinghouse / US Govt deal including ordering long lead time items.

• Continue to see opportunities in the public markets where companies have projects but not capital. Bought Boralex in partnership with La Caisse. $6.5bn EV. Accretive on close, and can accelerate growth.

• Batteries

  • “Undoubtedly the fastest-growing technology across Brookfield Renewable today is batteries and energy storage. We are seeing that within all of our existing development platforms. We are increasingly looking at stand-alone energy storage opportunities. And the rationale for this is very simple. They remove grid congestion…and they are very quick to deploy.”

  • CapEx for batteries and energy storage has come down 65% over the last 2 years, “making these investments very economic”.

  • It is “absolutely, in no uncertain terms” economic to add batteries to existing renewables generation and offtakers are willing to pay a premium to firm up their power.

• Issued 2.8m BEPC shares to buy 2.8m BEP LP units for a net cash gain of $27m. Continue to explore whether a single structure is better.

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Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

Tag for finding my other articles on this stock: MRP

Key takeaways

Strong customer demand but no answer to fundamental questions around business model and returns. To really work this needs to trade above book value but there is no reason for it to do so. Current discount is 23%.

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Thesis and valuation update

No change to thesis. The risk is that this works until it doesn’t.

• Millrose clearly have strong customer demand but doing deals that are good for customers isn’t the same as doing deals that are good for shareholders.

• Housing demand isn’t great, so homebuilders are holding onto land they know they can sell relatively soon, and selling longer-dated land to Millrose with an option to buy it back. They pay Millrose 10.7% when they could finance it on their own balance sheet for 6% - they are either dumb or they think they are shifting significant risk to Millrose.

• Millrose pays out all of its option premium profits as dividends, and when it sells land it can only break even or lose money. It cannot retain profits but it does retain losses. Mathematically, I think book value has to fall over time.

• This is a problem, because Millrose is near its debt ceiling and can’t grow without either lifting the debt ceiling, issuing shares, or coming up with a funky new capital structure. They have said they will not issue shares below book value, but if book value can only shrink the shares are unlikely to trade at a premium. I would not be surprised to see Millrose lift its debt ceiling. This obviously increases risks.

• In fairness, a higher debt ceiling could also mean a higher dividend, a higher stock price, and accretive share issuance. That’s the bull case. But the fact is that Millrose’s flywheel only really works if the stock trades above 1x book. And if it does, Millrose will attract competition: their competitive advantages are replicable by any number of asset managers with access to capital.

• Finally: it would reduce risk if the housing market accelerates from here, because homebuilders will be more likely to exercise their options. But if it decelerates… ouch. And one day, it will decelerate.

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Notes

• Net income of $122.9 million, or $0.74 per share.

  • AFFO $126m, up 2.5% q/q adjusting for slightly fewer days.

  • 100% AFFO payout.

  • BVPS $35.26, down 2c.

  • Now 143k homesites across 904 communities in 30 states with 17 counterparties, up 2 q/q.

  • Assets now 69/31 Lennar/other. Non-Lennar deals average 10.7% vs an average cost of debt of roughly 6%. These options are typically floating subject to a fixed rate floor, currently around 10%. Millrose mainly fund these deals with floating debt.

  • Amended credit facility to unsecured and added $500m of capacity.

  • Debt/cap 29% vs 33% limit.

• Industry conditions:

  • Housing “demand is choppy, but not collapsing”.

  • Homebuilders are pulling back on starts; maintaining sales through incentives and inventory management; protecting balance sheets amid meaningful margin compression; preserving/growing land pipeline and community count; and restricting direct land ownership. The last two are mutually exclusive without a partner like Millrose.

  • “When builders are earning less on every home, the last thing they want is more capital tied up in land that won’t produce a closing for years, but they can’t afford to lose those future communities either.”

• Competitive advantages

  • “As a publicly traded company [with] a fully unsecured investment-grade…capital structure, Millrose offers counterparties a degree of capital certainty and transparency that private land banking alternatives are structurally unable to replicate.”

  • Scale = sophisticated underwriting, diversification of risks, and certainty of execution.

  • “The software and workflow complexity of managing nearly 144,000 homesites across 904 communities in real time is a barrier that cannot be replicated quickly or cheaply.”

  • Proprietary lot pricing dataset across 30 states “has become a genuine competitive advantage”.

  • Once they have a relationship with a homebuilder it tends to grow as they become operationally integrated with the land finance team and gain trust with the C-suite.

• Confusing commentary on growth

  • They have significant demand but they are close to debt ceiling and don’t have a plan to fund it.

  • They “haven’t yet turned our attention to alternative financing…structures” but they “spend a lot of time thinking…about what could next steps be”. Whatever that means.

  • Hope to trade at levels where they can “unlock the equity markets as a financing vehicle”.

  • “We’re not going to walk away from business, and we’re certainly not going to walk away from our existing clients”. They need capital.

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Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

What it does: enterprise software.

Elevator pitch: arguably one of the finest franchises ever built, with deep distribution advantages that let it deliver innovations cheaply to a huge customer base.

Mental model: moat (read about my mental models here).

Valuation and potential returns: 21x June 2027 EPS estimates and growing EPS 20% per year.

Exchange and ticker: Nasdaq, MSFT

Stock price and market cap: $422, $3.1t.

Do I own it? Yes.

IR website: here.

Tag for finding my other articles on this stock: MSFT

About this blog: I have been investing for 25 years, professionally and personally. I look for stocks that have a high probability of compounding at 15% for at least 5 years with limited downside. I write these stocks up on my blog. You can find more about me, my philosophy, my mental models, and my portfolio structure on my site.

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

Welcome to the final instalment in my Microsoft saga. The goal of this piece is to determine whether Microsoft can compete over the next 5-10 years. Part 1 introduced the layers of AI the AI stack and looked at two, silicon and infrastructure. Part 2 dived into two more, LLMs and the agentic stack. So far we have concluded that:

• In silicon, Microsoft is behind because it started late, but Maia 200 is promising and Microsoft will close the gap.

• Infrastructure will commoditise slowly, and a new utility compute industry will eventually allow hyperscalers to go (partway) back to being capital light.

• LLMs will commoditise behind the frontier, creating a rolling wave of commoditisation and increasingly cheap intelligence.

• Microsoft is well placed to 1) help enterprises develop and manage their own agents, and 2) develop proprietary agents that can be sold into large verticals. The agentic TAM is huge.

Part 3 starts with distribution and bundling, and then considers whether layers can be combined to create competitive advantage before drawing everything together in conclusion.

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Distribution and bundling

Distribution and bundling have been Microsoft’s deepest moat for years. Through Windows and Office alone, they are in virtually every enterprise IT department and on virtually every enterprise employee’s screen. When a competing product comes along, they clone it and bundle it into an existing suite of products. Suddenly it’s on every desktop, for nothing. It’s not as good as the standalone version, but it is there and it is free. Adoption skyrockets. Over time Microsoft improves the product and then monetises it by re-segmenting the bundle.

On top of that, Microsoft sells trust. They wrap the bundle in all the things IT departments love - permissioning structures, data security. But they don’t charge too much. They’re selling software, so the gross margin on the incremental sale is extremely high. They can afford to keep the price of the bundle well below the total price of all the standalone options you’d have to buy to replace it. (Years ago a colleague of mine looked at this. Everyone at the company lived in Microsoft products all day. Literally all day. And yet the company spent less with Microsoft than it did on milk for coffee and tea.)

The bundle has all the products you want, wrapped in all the compliance and security stuff you need; it requires managing one vendor relationship rather than 10; and it costs peanuts. What IT department wouldn’t use it? Code was never the moat. The cost to replicate the products has been falling for years and is tiny compared to the market opportunity. Distribution, bundling, trust, and price were the moat.

Does AI change this? I don’t think so, but there are wrinkles.

We saw in Part II that Microsoft is building 1) the cloud AI stack for enterprises to build bespoke agents, and 2) first party agents for big use cases. In the AI stack, distribution is a clear advantage but bundling isn’t. Microsoft has few peers when it comes to selling this kind of relationship to enterprise, although it is clear that Google, Amazon, Anthropic, and Open AI will compete. But the sales motion here is less about bundling and more about monolithic contracts, and the economics are about leveraging fixed costs. In proprietary agents, however, distribution and bundling may be a superpower. That is where I want to focus.

Bundling isn’t easy with frontier AI. When Slack launched, Microsoft cloned it, creating Teams. Whatever the cost of doing that was, it vanished into Microsoft’s overall R&D budget. By contrast frontier models cost tens if not hundreds of billions to train, and AI labs may only have a year or two to monetise them before their capabilities are commoditised. Microsoft has chosen not to develop frontier models itself, quite possibly because of that exact dynamic. The result is that it now distributes third party products, not its own. This creates a dependency that was not present before.

However, bundling commoditised AI might be very different. My thesis really hinges on one thing: for any given task, a given level of intelligence is required. That level of intelligence may be impossible one year, frontier the year after, and commoditised the year after that. As the frontier advances, the trailing edge commoditises, the cost of inference falls, and the pricing model switches to seat + consumption, Microsoft can bundle more and more intelligence at less and less cost. And that strikes me as an immensely (and increasingly) powerful proposition for both TAM and margins.

There are about 400m M365 Commercial seats worldwide. Of these, by March 2026, over 20m had adopted the paid M365 Copilot add-on, up 35% q/q. That is with Copilot’s capabilities today. In 5 years Copilot might still not be as good as the frontier models, but in absolute terms its capabilities will be incredible, it will be cheap, and it will be bundled into an enterprise’s existing financial and control arrangements. The chances of increased adoption (and maybe increased growth in M365 Commercial seats, too) are strong.

It’s obviously dangerous to extrapolate from one example, but this post on X captures what I am trying to describe. This user found that Excel in Agent mode can now update financial models from press releases. This might be child’s play for Claude, but that’s not the point. The point is that Copilot is improving and the user 1) I doesn’t care which LLM was used, just that it works; 2) prefers letting Microsoft choose the LLM over getting locked into one frontier lab; 3) might now use Excel more, not less, and for more productive things; and 4) would happily pay Microsoft extra for this capability. And as he says in the comments: why bother using the Claude Excel plugin if Excel Agent mode just works? I think that as commodity models advance, this thought process will play out across millions of use cases in thousands of enterprises.

If this is right it creates a couple of interesting dynamics:

1. Copilot may always be behind the frontier and may never have a great reputation as a result. But so long as it keeps getting better, that might not matter.

2. Frontier models may always dominate frontier workflows, but they will also have to charge frontier prices. As Copilot gets better, workflows developed on Claude might come back to Microsoft as commoditisation and bundling kicks in.

If this plays out as I think, Microsoft will become a critical distribution partner for commoditised LLMs. As such Microsoft can be an agent of model commoditisation, not just a beneficiary of it. It will also be an (unlikely!) ally of regulatory agencies seeking to prevent any potential winner-take-most dynamic in the LLM market.

The economics of bundling AI aren’t as clean as the economics of bundling software. The nth copy of a piece of software can be sold for virtually zero marginal cost, whereas intelligence costs money every time you use it. As discussed in Part II, Microsoft is moving towards a seat + consumption pricing model. This should both increase Microsoft’s revenues and improve Copilot’s performance. But can they make a margin?

• The bear case is that there isn’t a CTO on earth who hasn’t heard of Anthropic and OpenAI. Under pressure to adopt AI and aware that Copilot’s reputation is weak, they will test all options. They will not want to get locked into a single LLM provider, but if they somehow do (despite model commoditisation) then the frontier labs might generate cash flow in excess of the cost of training the next model. In this scenario the frontier labs both disrupt Microsoft’s cloud/productivity/agentic layer and build proprietary infrastructure to put pressure on the hyperscalers.

• The bull case is that with proprietary silicon, commoditised infrastructure, and commoditised trailing edge intelligence, Microsoft can deliver increasingly powerful intelligence cheaply through its unique distribution setup. Meanwhile frontier labs, desperate for cash to train their next model, will have to charge high prices for their older models, holding up a pricing umbrella for Microsoft.

There is clearly some validity to at least the first part of the bear argument. Open AI and Anthropic have bypassed Microsoft’s distribution advantage to some extent - otherwise their revenues would not be growing as fast as they are. Whether the second part of the argument holds - that these revenues are sticky - remains to be seen. It’s probably not binary - both arguments will be true to a degree. But on balance, I find the second argument far more compelling.

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Conclusion on distribution and bundling

As the rolling wave of LLM commoditisation advances and inference costs fall, Microsoft will be able to bundle more and more intelligence into its product suites at lower and lower costs. This plays neatly to Microsoft’s time-honoured strategy: be the second mover, clone and bundle the product, drive adoption, make it better, and then slice and dice the bundle to monetise it. If this works Microsoft will always look like it is behind the leading edge, and Copilot may always have a poor reputation compared to frontier models, but it will be good enough for a vast and growing range of uses, it will be cheap, and it will be delivered at strong margins.

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Combining layers

If anything renders Microsoft’s distribution moat obsolete it’s not the insurgency of OpenAI and Anthropic; it’s the full-stack advantage of Google.

In Part I I discussed the layers in the AI stack. Google owns all of them. It is producing its own silicon at scale. It is building infrastructure at pace. It owns its own frontier LLM, Gemini. It owns the full cloud stack needed to build and deploy agents. It owns distribution at vast scale to consumers. And it owns a huge search and advertising business that AI improves.

How does this full stack create advantage? Several ways:

1. Google can optimise margins across the whole stack, not individually for each layer. Said another way, it can use profits in one area to subsidise another while it builds scale and competitive advantage.

2. It can fully integrate and optimise its stack to deliver lower costs.

3. It can move fast, forcing cooperation across layers in ways hard to replicate when you don’t own every layer.

4. It can generate an immediate return on its LLM investments by deploying them to improve its existing businesses.

5. There will never be any question over whether Google has access to frontier intelligence (whereas Zuckerburg argues that OpenAI and Anthropic could claim “safety” reasons for not giving third parties access to their most advanced models).

I have not included the data flywheel here. Google has enormous amounts of proprietary data on which to train models. This data can be used to optimise models for improving Google’s existing businesses, like search. But I’m not convinced it is a huge advantage in enterprise, where Google is subject to the same restrictions as Microsoft (see Part II) and where Microsoft has more data.

The counterargument is that Microsoft also owns a lot of the stack. It doesn’t own a frontier model, but that might be a blessing in disguise given how unclear the ROI is in that layer. Instead, Microsoft owns the layers where ROI is clearer - silicon, infrastructure, cloud/agent stack, and distribution. If it can integrate these well, it should get sufficiently close to Google on cost, margin, and speed. Rather than locking clients into one LLM - which they will not want - it offers a marketplace of thousands of them. It absolutely owns enterprise distribution. Google does have enterprise distribution - over the last decade Google Cloud has become a formidable competitor to Microsoft’s Azure, and it provides an effective stack to customers wanting to build their own agents. But Google does not have an operating system and productivity apps already installed on the desktop of every user. That makes it more difficult to create proprietary agents and roll them out for free, without asking, and within existing security and permissioning arrangements. Finally, Microsoft is building cheap, optimised LLMs for specific, large use cases. In these cases, it will have genuine full stack economics. As cheap models get better and better, I expect Microsoft to address more and more use cases with this full-stack architecture.

I don’t mean to dismiss Google. It is certainly a formidable competitor. Gemini reasons better than Copilot, Google’s cloud business has built strong relationships across enterprise, and there is plenty of anecdotal data to suggest that Google is willing to discount heavily to encourage enterprise to switch. And there are advantages to the full stack. But Microsoft has advantages too. I am not sure Google’s full stack gives it a unique right to win in enterprise.

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Conclusion

Here is my Microsoft hypothesis per layer:

• Silicon: Microsoft is behind but catching up with Google and Amazon.

• Infrastructure: Likely to commoditise eventually, especially behind the frontier, creating a new utility compute industry and allowing hyperscalers to return to more capital-light ways.

• LLMs: A rolling wave of commoditisation, with frontier models never more than a year or two ahead of cheaper models. Microsoft will be the distributor of increasingly powerful commoditised AI.

• Agents: A goldmine, with a deep cloud stack allowing customers to develop, orchestrate, monitor, and control agents, plus extremely valuable horizontal and vertical proprietary agents. TAM is every process in every enterprise.

• Distribution: Microsoft’s deepest moat. Microsoft will bundle increasingly powerful intelligence into existing products, wrapping it in trust and pricing it cheaply. It will be hard for IT departments not to buy it.

AI is moving fast and the competitive dynamics are fluid. It is hard to develop confidence in where profits will eventually be made and who will make them. One strategy for dealing with this would be to reformulate investment theses whenever there is new news. I think this leads to high trading costs and chasing the latest hot stock. I prefer to form a 5-10 year high-level thesis based on an understanding of competitive dynamics and moat formation. That thesis can be assessed against short term newsflow, but it is important to give it time to play out. It is also important to diversify exposures.

Microsoft is well positioned to be the distributor of commoditised AI to enterprise. The TAM is huge and the right pricing models combined with Microsoft’s distribution advantages should ensure attractive margins. With revenue growth and operating leverage, I expect that Microsoft can compound earnings at 15-20% for many years despite rising depreciation costs. At 21x June 2027 earnings (less if you give credit for the Open AI equity stake), I think Microsoft is a compelling investment.

To end: as I said at the start, I have not addressed the ultimate bear case - that artificial general intelligence renders all competitive advantage obsolete and reduces returns across the entire tech industry to the cost of capital. I have three things to say on this:

1. I see this as a low-probability outcome for various reasons; in fact it’s equally likely that Microsoft ends up making good margins distributing commoditised AGI.

2. If it does come to pass, affordability and quality of life will improve dramatically regardless of how an investment in Microsoft works out.

3. This risk is easy to hedge. Plenty of assets will do well in a scenario in which humans have more discretionary spending power and more free time.

Links to previous Reviews

1. IRSA

2. Brookfield

3. Cheniere

4. Uber

5. Howard Hughes Holdings

6. Millrose Properties

7. Microsoft Part 1, Part 2.

8. My notes

Thanks for reading - if you enjoyed reading this please subscribe, like, and restack, and do get in touch if you have questions.

Pete

Tag for finding my other articles on this stock: MSFT

Key takeaways

EPS compounding high teens. 35% q/q growth in paid Copilot seats perhaps the most significant individual datapoint.

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Thesis and valuation update

No change to thesis. Intelligence is fragmenting and commoditising. Microsoft is well-placed to distribute commoditised intelligence to enterprise. TAM is vast. Stock trades at 21x June 2027 EPS.

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Notes

• Revenue +15% c/c, gross profit 13%, EBIT 16%, EPS 18% excluding OpenAI stake impact.

  • Infrastructure depreciation and agent usage decrease gross margins, offset by infrastructure efficiency gains at the operating level.

  • Cloud revenue +25% c/c at 66% gross margin.

  • Azure revenue +39% c/c, ahead on early delivery of capacity.

  • AI business $37bn ARR, +123%. Includes paid Copilot, Azure AI consumption revenue (OpenAI, Foundry, AI-driven compute/networking/storage, etc.), revenue attributed to AI features embedded in core products.

  • M365 Commercial seats +6%.

  • EBIT margin 46%.

  • Headcount down as they build fast, agile teams.

  • CFOPS +26%. Capex $31.9bn, 2/3rds on short-lived items (which is what correlates with revenue). FCF $15.8bn.

  • FY capex $190bn including $25bn for higher component prices. Demand exceeds supply at least through 2026.

• 2 mutually-supportive priorities as Agents drive TAM:

  • Building the world’s leading cloud and AI infrastructure for third party agents.

  • Building high-value first party agents across core domains like productivity, coding, and security.

• Infrastructure: optimising every layer - DC design, silicon, system software, model architecture.

  • Reducing time to deploy, increasing efficiency. More revenue, sooner, at lower cost.

  • Maia 200 now live in 2 DCs and offers 30% more tokens per dollar than the latest chips in their fleet.

  • 40% improvement in inference throughput for Copilot’s most-used models, on software and hardware optimization.

• Enterprise data and context: “across Fabric, Foundry, Microsoft 365 and our Security Graph, we are building a unified IQ layer for organizational intelligence…And as AI usage grows, so does the context layer, creating a flywheel that continuously improves the grounding, relevance and effectiveness of every agent”.

  • Cosmos DB revenue +50% y/y driven by AI.

  • Fabric has 35k paid customers, up 60% y/y.

  • Amount of data in OneLake (which underlies Fabric) grew 4x.

  • 15k customers use Foundry and Fabric, up 60% y/y, connecting agents to data.

• Third party agents.

  • AI Foundry offers 11,000 models. 10,000 customers have used more than 1. 5,000 have used open source models. Foundry has c.60k users but they vary in sophistication.

  • Agent 365 is the “control plane” - governance, identity, security and management frameworks for agents. “Tens of thousands of companies are already managing tens of millions of agents in Agent 365”.

• First party agents.

  • “Here we are in 2026 and the most exciting things are plug-ins in Word or Excel or CLIs in coding…that means we have a structural position in knowledge work, coding, security, which are the big TAMs”.

  • Copilot is evolving from a chat assistant to a coworker, executing long running tasks across key domains. Innovation is accelerating - M365 saw 625 updates over 12 months, up 50%. Includes intelligent auto-routing to the right model, and use of multiple models to improve responses.

  • Copilot adoption and engagement are exploding. M365 Copilot seat adds up 250% y/y. M365 Copilot paid seats up ~35% q/q to >20m and accelerating. MAUs of first party agents is up 6x ytd. Copilot queries per user are up 20% q/q. Copilot weekly engagement is now at the same level as Outlook (impressive but definition not clear - likely the percentage of licensed users who use it at least once a week).

  • WorkIQ now spans 17 exabytes of data, growing 35% y/y, with billions of e-mails, documents, chats, Teams meetings, and SharePoint sites added each day. “Copilot is uniquely valuable at work where nearly every task depends on organizational context. Work IQ grounds Copilot responses in the full context of an organization, including people, roles, documents and communications, all within the company’s security boundary….this is not some static database. It’s the most important database in any company that is constantly changing every second”. And as Copilot adoption grows, Copilot conversations and artifacts get added, making the data richer.

  • 1st-party models differentiate high-value Copilots and reduce COGS. New voice transcription and image generation models increase GPU efficiency by 67% and 260%, respectively.

  • Examples

    • LinkedIn Talent Solutions helps hirers automate sourcing, screening, and messaging - $450m ARR already.

    • Security Copilot customers up 2x y/y.

    • GitHub “is seeing unprecedented growth driven by proliferation of agentic coding”. Enterprise subscribers to Github Copilot up near 3x y/y, the majority using multiple models.

• Shifting to seats + consumption model (aka seat + agent).

  • Seats include some consumption. Long term consumption commitments will get discounts. Additional consumption charged on top.

  • Customer Service is at the forefront with 60% of customers now buying usage-based credits.

  • Github Copilot is moving to seat + usage too.

  • On a like-for-like basis this reduces bookings, since seats are booked up front and usage is real time, but not revenue.

  • As value-add rises, this accelerates revenue growth in M365 Commercial.

• Windows monthly active devices >1.6bn, “and over time, Windows value will extend to deliver unmetered intelligence at the Edge”. Bing MAUs topped 1bn.

• OpenAI agreement evolution maintains win-win dynamic. Still have royalty-free access to a frontier model through 2032.

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Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

Tag for finding my other articles on this stock: HHH

Key takeaways

Howard Hughes released a new set of metrics and valuation methodologies. These are useful, especially adjusted maintenance free cash flow for the Operating Assets segment. Management peg per share value at $104 today with potential for $211 by 2030 - their deck is linked below. Share price today is $63.

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Thesis and valuation update

No change to thesis. The real estate business shows momentum and is generating cash which will mainly be redeployed into Vantage, the new insurance subsidiary. That acquisition should close soon. Marc Grandisson, the ex-CEO of Arch, one of the best-performing insurance companies of the last 25 years, has joined the HHH board. This bodes well for Vantage.

The new valuation framework is similar to mine and produces a similar outcome. I’ll update mine for the new metrics and republish it in the next few weeks.

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Notes

• Operating summary

  • MPC EBT +33% on higher land sales. “The real estate engine did exactly what we needed to do. It grew cash, it provided pricing power and it converted more land into long-duration income.”

  • Operating Asset TTM same-store NOI +2%, driven by leasing and the burn-off of rate abatements in multifamily and office.

  • Strategic Developments: broke ground on The Launiu which is 70% pre-sold.

  • G&A high this quarter at $25.8m on $3.4m of Vantage acquisition costs.

• New metrics

  • MPCs: residual land value, undiscounted and uninflated.

  • Operating assets: Adjusted Maintenance Free Cash Flow. This is NOI - interest - amortisation of deferred leasing costs - depreciation of tenant improvements. It’s a good proxy for “cash we can take out”. It should grow high single digit organic (mid-single digit same store rental growth + 3-5% from operating leverage) plus 1-2% from building new assets. It is well diversified, with Office, Retail, and Multifamily making up about 30% each and Other the rest.

  • Strategic Developments: gross profit after tax of remaining condo sales from projects in development and advanced predevelopment.

• New valuation methodology

  • Detailed deck here.

  • Their 1q26 valuation is “basically a liquidation value”. NPV is higher if they keep rationing the supply of land, reinvesting in communities, and building the commercial land themselves so they keep the development profit.

• Balance sheet

  • $1bn debt raised at tightest credit spreads in HHH history. Half at 5.875% due 2032, half at 6.125% due 2034.

  • Repaid $750m of 5.375% notes due 2028.

  • $300m 5y mortgage at Downtown Summerlin raised at 5.52%.

  • $1.8bn in cash. Including the PSH Vantage preferred, all plans fully funded.

• General commentary

  • Summerlin land values have compounded at just under 15% over 5 years and the cost of capital should be a modest spread over treasuries given this is an established community and it is a virtual certainty the land will be sold.

  • Real estate overall will generate $2.5-3bn of excess cash by 2030. (This is after building out more Operating Assets. Unclear if it is pretax or after.)

  • Focus for the next few years will be on injecting additional equity into Vantage rather than buying additional operating companies, in the expectation that Vantage will do 15-20% ROE and be valued at 2x equity.

  • Beginning of a meaningful transition in the shareholder base.

  • Shifting from annual guidance to long term objectives per platform, “consistent with how we allocate capital and measure success internally”.

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Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

Tag for finding my other articles on this stock: IRSA

Key takeaways

The two segments that matter are malls and Ramblas del Plata. Malls is generating consistent ebitda. A positive here is international brands coming to Argentina. RdP is progressing well and will become a significant cashflow generator over the next 3-4 years.

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Thesis and valuation update

No change to thesis. Still priced to compound at +/- 20% in a bull case. I plan to publish a detailed valuation update in the next few weeks.

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Notes

Y/Y figures are in inflation-adjusted pesos. Because I did not publish 2q26 results, my notes for those are included at the bottom.

3q26:

• Malls

  • Occupancy 98%. EBITDA -1% y/y for the q and +2% for 9 months.

  • Tenant sales down 9% (9m/9m) on weak consumption and falling prices. However

    • 87% of IRSA revenues are fixed.

    • One reason is clothing inflation has exceeded inflation for several years - this is reversing as the economy reopens and imports compete.

    • No sign of tenant stress - number of transactions is stable, defaults are normal, rate of signing new leases is normal, fixed rents on new leases rising slightly higher than inflation.

  • International brands coming to Argentina as the economy opens. Positive for tenant mix and traffic.

• RdP

  • 2 more plots swapped for $11.3m - over 13,000 sellable m2, 3700 net to IRSA (implied % >27.4%).

  • Total now swapped or sold is 137k sellable m2 for $105m. The swaps account for 97k sellable m2, “nearly 25k” is net to IRSA, implying 25.5% IRSA share. This is inline with expectation that the initial plots would be at the low end of the 25-30% guide, and it is good to see IRSA’s share of the most recent swaps higher.

  • Expect over $300m of revenue from selling units received under swap agreements over the next 3-4 years.

  • 52% of the horizontal infrastructure for Phase 1 is complete and 23% of the total.

• Other

  • Offices fully occupied with small rent increases. Expanding one site with 72% already leased to Mercado Libre. Positive on office with strong demand and fewer new projects.

  • Hotels doing well on inbound tourism.

  • Net debt/ebitda 1.4x, LTV 11%. Will rise as they spend cash to accelerate developments.

  • Unlikely to enter the datacentre business but likely to build a significant logistics business over time.

2q26:

• Malls

  • Over time mall sales should rise with nominal GDP.

  • Recently traffic and volumes have been strong but prices weak, so tenant sales are down 9% y/y.

  • Ebitda +2% for the half though on inflation-linked fixed leases. Distrito

  • Diagonal mall on track for May 2027 opening - adds 22k GLA and first mall in La Plata city.

• Ramblas del Plata

  • Signed 2 more swaps for $12m. Total now 2 plots sold, 13 swapped, $93m, 124k sellable m2.

  • Expect sales prices of over $5000 per square metre for residential over the life of the project. Commercial, over $4000.

• Other

  • Launching coworking at the underutilised Philips building. Going well and will expand.

  • Issued another $180m of the 2035 bond at 8.25% (8% coupon).

  • ND/rental ebitda 1.6x, LTV 13%.

  • Now have enough cash on hand to finance all planned capex and acquisitions; debt ratio will rise as they spend the cash, then fall as they complete the projects.

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Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

Tag for finding my other articles on this stock: UBER

Key takeaways

Clear evidence of price elasticity - gross bookings is rising as insurance costs come down. This is critical for the long term thesis that Uber’s TAM will explode as AVs bring down costs.

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Thesis and valuation update

Thesis intact. Rapid growth, operating leverage, AV fragmentation, and positive commentary around their relationship with AI personal assistants which I see as the big competitive threat.

23x 2026 normalised EPS (per TIKR) and 16x trailing FCF. Lower if you adjust for equity stakes.

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Notes

• Gross bookings +21% (audience 17%, mobility 20%, delivery 23%). Revenue +10% (18% without move of driver payments from COGS to contra-revenue in the UK). Non-GAAP EBIT +42% on segment operating leverage offset by corporate investment in tech headcount. Non-GAAP NI +39% and non-GAAP EPS +44%.

  • TTM FCF $9.8bn.

  • $3bn buyback in the q (40m shares).

  • $8bn of equity stakes on the balance sheet, mostly public.

• Key operating stats/features

  • Insurance coming down, mostly passed through, strong elasticity helping bookings growth.

  • 50m Uber One members, up 50%; better retention, 3x spending, 50% of gross bookings are now members.

  • Cross-platform users growing 1.5x faster than overall users.

  • In mobility, barbell strategy: low cost products like Wait and Save drive 75% more frequency than core products while premium features drive 3.5x the profit. All drives higher lifetime value.

  • Adding selection in sparse/suburban markets is growing gross bookings in these markets at 2x overall rate and at higher margins. See higher % of reserve and Wait and Save in these markets too - improves reliability.

  • Uber for Business now does $5bn of high margin gross bookings and is growing 45%.Target $10bn by 2028.

  • Can now order eats to pick up on the way in a taxi, and delivery to room in hotels.

  • Can book hotels in-app via Expedia partnership. Long wondered whether they could evolve from on-demand to planned services. Uber Reserve answered this - hence hotels. Giving most of the economics of this deal to Uber One members.

  • Launched in Finland and straight to #1 in the App Store - there is a global halo/network effect, not just local.

  • Delivery in 35 countries now and targeting more. Within Delivery, Grocery and retail growing fast with added selection and growing awareness. AI shoppers help.

  • Freight gross bookings +6%. Nearly as many new enterprise customers added in 1q26 as in all of 2025. “Significant opportunity to more tightly integrate Freight with the broader Uber platform to create a cohesive end-to-end logistics ecosystem”.

  • Earners +21%. Various new features to boost driver experience - AI assistant, Hourly, Women Preferences.

• AI:

  • Bumping up FY AI budget already.

  • “It’s creating…employees with superpowers,” an accelerator for every company.

  • Will hire fewer people than planned this year due to AI.

  • Can now predict where you are going 3/4 of the time.

  • Turn a recipe, image, or prompt into a curated cart.

  • Can now personalise user interfaces. Different users interact in different ways. To date they have had to build for the majority. Now they can build for everyone. Key for adding new services, driving cross-platform usage, personalised upsell, etc.

• AV “is another $1tn TAM”.

  • Live in 8 cities, 15 by yearend, rides up 10x y/y.

  • No negative impact when Waymo launches in a city. In markets where Waymo has been operating for a while (SF, LA) Uber’s category share is higher than 6 months ago.

  • Bottleneck is cars on the road.

  • 30 autonomous partners. Success in signing partners is because they have demand. Also Uber Autonomous Solutions lets partners focus on building the driver while Uber does everything else.

  • Santander deal paves way to AV fleet financing. Difficulty is lack of established residual value, but their ability to offer predictable demand (and higher than 1P networks) underpins attractive financing.

  • Working with Marsh and Apollo on insurance.

  • Working with Hertz on fleet management and securing depots in regulation-ready markets. Builds on work they have done for some time as drivers have switched to EV.

  • Data offering for training models “has scaled quickly” - some of the earner fleet has robotax-grade sensors creating a differentiated dataset in combination with Uber’s proprietary data.

  • AV investments need to drive audience acquisition, frequency, or margin. Investing capital for now, but vehicle investments are transferrable to finance partners in time.

• Personal assistants vs interacting with apps

  • “Talking to many of these third-party agents. We have a great market position… [we] often dictate the terms of trade in those discussions”.

  • “I think we’ll continue to see that the majority of our transactions come direct.”

    • Building an indispensable service in mobility and delivery over 70 countries.

    • Engaged users / Uber One bring people to the app.

  • Assistants will interact with Uber’s agents.

  • Fears of metasearch in travel were unfounded. Most of the value stayed with Expedia, Booking, Airbnb.

  • Google Maps had comparison shopping between Uber and Lyft, and it wasn’t the same experience as coming direct to the app.

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Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

Tag for finding my other articles on this stock: LNG

Key takeaways

EBITDA and DCF guide increased; execution excellent as usual; buyback executed with real discipline, averaging $202 in a quarter that saw the stock range from $194 to $297.

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Thesis and valuation update

Minor increase in 5y cash flows likely but no substantive change.

At last closing price of $240 my (simple) DCF shows a 15% IRR through 2030. Caveat: this assumes buybacks are at the current share price.

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Notes

• Ebitda $2.3bn, DCF $1.7bn. Net income negative due to noncash charges related to the accounting mismatch on their IPM contracts.

  • Bought back 2.7m shares for $535m ($202). Opportunistic. Overage on DCF or delays in FIDs = more buybacks.

  • Paid down $250m of debt.

  • Issued $1bn of 2036 notes at 5.2% and $750m of 2056 notes at 6%, their inaugural 30-year issuance. Used some proceeds to prepay $550m facility.

• Increasing FY guide to $7.25-7.75bn ebitda (up $500m) and $4.75-5.25bn DCF (up $400m) on higher production, higher marketing margins, and optimisation efforts. Also locked in 1mt of 2027 CMI volumes at good margins.

• Project progress

  • CCL Stage 3 project 97% complete. Train 5 substantial completion achieved in March and T6&7 on track for summer and fall - each a few weeks ahead of the schedule assumed in the initial guidance. First LNG at T6 imminent.

  • T8/9 and debottlenecking project now 37% complete.

  • Phase 1 expansions at SP and CC on track - “the most compelling risk-adjusted infrastructure investment opportunities on the Gulf Coast or maybe all of North America”.

  • After Phase 1 expansions, CC probably the focus, advantaged by having 500 acres of unused land with access to water, next to their power plant, and only 40 miles from their Sinton station for gas supply. SP has land, but it’s wetlands.

• Hormuz/Qatar

  • Demonstrates the value of geopolitically stable supply and the role of flexible US volumes in balancing the market - most Qatari supply goes to Asia so US cargoes rerouted there. These benefits are reflected in current commercial negotiations.

  • 13mtpa of supply off the market for up to 5 years.

  • Also likely to see delays to new capacity planned for Qatar and UAE.

  • 2026 is much tighter than thought and 27 “more structurally constrained”.

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Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

What it does: enterprise software.

Elevator pitch: arguably one of the finest franchises ever built, with deep distribution advantages that let it deliver innovations cheaply to a huge customer base.

Mental model: moat (read about my mental models here).

Valuation and potential returns: 21x June 2027 EPS estimates and growing EPS 20% per year.

Exchange and ticker: Nasdaq; MSFT.

Stock price and market cap: $421, $3.1tn.

Do I own it? Yes

IR website: here.

Tag for finding my other articles on this stock: MSFT

About this blog: I have been investing for 25 years, professionally and personally. I look for stocks that have a high probability of compounding at 15% for at least 5 years with limited downside. I write these stocks up on my blog. You can find more about me, my philosophy, my mental models, and my portfolio structure on my site.

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

Part 1 of this review introduced the layers of AI and dived into two, silicon and infrastructure. It concluded that

1. Microsoft is behind in silicon because it started late, but Maia 200 is promising and Microsoft will close the gap.

2. Infrastructure will commoditise slowly, and a new utility compute industry will eventually allow hyperscalers to go (partway) back to being capital light.

Part 2 dives into the middle two layers: LLMs and Agents.

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LLMs

Large Language Models are the engines behind AI. Is this a winner-take-most market, or will LLMs be commoditised? If it’s winner-take-most Microsoft has a real problem. It doesn’t own a leading LLM, so it won’t be the winner; in order to sell AI to its customers, therefore, it will have to buy from the winner, who will have the whip hand in negotiations and might bypass Microsoft entirely to own the customer relationship directly.

Winner-take-most could come about in two ways:

1. One LLM lab reaches artificial general intelligence first, it could pull ahead of the others in performance terms. AGI isn’t well-defined, but in this context it means the LLM would improve itself faster and at lower cost than is possible with humans managing the process.

2. Several LLM labs run out of money.

I think it is vanishingly improbable that either of these things will happen, for a variety of reasons.

The first is that it is in literally nobody’s interests for one LLM to dominate the future. Here’s a short list of people who would absolutely hate this outcome:

• Every consumer.

• Every enterprise.

• Every voter.

• Every government.

AI is an incredibly potent technology. AGI will be terrifying. The idea that one company would be allowed to monopolise that sort of power is effectively impossible. Governments, customers, competitors, and regulators will work hard to ensure this doesn’t happen. And if it looks like it’s going to happen the company concerned will be broken up, so winner-take-most isn’t even really in the interests of the winner.

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The next reason is simply that I don’t think technology works this way. Technology seems to be inherently replicable. Like the 4-minute mile or the 2-hour marathon, once one person can do something, others follow. I can’t think of any major technologies that were cutting edge 5, 10, or 20 years ago that have not been replicated. I am not sure AI will be any different.

The evidence so far suggests that LLM advances are indeed replicable. There are perhaps 4-8 frontier labs. None has so far carved out a significant lead - on the contrary, models from these labs leapfrog each other in capability. Further, xAI is only 3 years old and Meta has stumbled, fallen behind, and is apparently catching up again. None of these datapoints argues for winner-take-most. On the contrary, the evidence suggests that hiring the right people and throwing money at them gets you a seat at the front of the race. And the number of “right people” will inevitably grow over time.

Equally important is the proliferation and performance of second-tier models. While the frontier models are breaking new ground at great cost, second-tier models are about a year behind and cost far less. This one-year gap varies by task and over time, but it doesn’t appear to be trending longer. This is critically important. A certain level of intelligence is required for any given task. Eventually, many models will be good enough for each task. Intelligence that is impossible this year might be frontier next year and commoditised the year after. In addition there is evidence that the software surrounding a model can be as important as the model itself: for example, Microsoft Critique uses multi-agent review to achieve better results than the underlying models alone, suggesting that combinations of commoditised models may become extremely capable.

I believe all of the above argues strongly for a rolling wave of commoditisation behind the ever-advancing frontier LLMs. Microsoft seems to agree: I think their strategy is to become the distributor of commoditised AI. This is a strategy shioft from the early days of AI in 2022/3. Back then they built everything on OpenAI models, arguing this drove utilisation and efficiency. Why has the strategy changed? A cynic might argue it’s because they don’t have a frontier model of their own and their relationship with OpenAI has become rather less cozy. But there might be a simpler answer: initially Microsoft didn’t have a choice, but 18 months later they did. ChatGPT kicked off the AI era in November, 2022. It took about a year for all the other frontier models to become available and months more for powerful open-weight models to proliferate. But proliferate the models did, and in May 2024 Microsoft publicly announced a model-agnostic architecture for the first time. Today there are an over 11,000 models available on Microsoft’s platform. That number alone is strong evidence that LLMs will commoditise.

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To distribute commoditised AI, Microsoft puts together several things. First, the models, available via API. Second, the harness in which the models run. Third, the reams of enterprise data stored in Microsoft’s systems. And fourth, the customers.

Who benefits? The commoditised LLM benefits from broad distribution. The customer benefits from access to cheap models and from not locking themselves into a frontier lab that might not be competitive in the future. And Microsoft benefits, because amongst other things:

• Inference explodes. Models are cheap to run. Labs don’t have to invest in distribution. Low costs drive AI adoption.

• Costs can be optimised by routing tasks to the optimal model.

• Performance can be optimised by using domain-specific architecture and/or more than one model.

• By building proprietary low-cost models and agents for specific use cases, Microsoft can build vertical niches with full-stack economics.

There are, of course, counterarguments to the commoditisation thesis. Perhaps the best is the most obvious: the independent frontier labs are growing revenue like weeds. Anthropic’s run-rate revenue reached $30bn in April. This is over 10% of the revenue run rate Microsoft has taken decades to build, and is up 3x in 4 months. OpenAI is reportedly on a similar trend. On the face of it, exploding revenues suggests these will be powerful companies in the future. But the more revenue the labs make the longer they stay alive, the more models there are, and the more likely commoditisation is. Also, I am not arguing that the frontier becomes commoditised. Indeed, the labs may be able to keep growing revenue by solving ever-more impressive problems at the frontier. But behind the frontier I predict rolling model commoditisation as domain-specific systems are built on second-tier models to solve problems that were frontier 12 months ago. That is what I think Microsoft is positioning for.

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Another counterargument is that models trained on data nobody else has access to are likely to outperform with regard to that dataset/use case. I don’t think this argues against commoditisation of models in general, but it is an argument in favour of companies like Meta and Google driving increasing performance out of their legacy businesses.

A third counterargument is that vertical integration might be key to optimising model economics. Complex queries are exponentially more expensive to run than simple ones, so a small fraction of super-users can dominate the cost of running a model. This means flat pricing does not work and even consumption-based pricing doesn’t perfectly solve the issue since inference pricing depends on datacentre utilisation: a complex task run at a slow time is cheaper than a complex task run at a busy time. Demand prediction is key and adding a distributor between the model and the customer obfuscates the data. I don’t think this kills a multi-model architecture. I find it very hard to believe that Microsoft can’t figure out a pricing model that produces stable average margins across its huge customer base. Indeed, they have already begun to introduce consumption-based pricing, which will help with this.

Finally, Mark Zuckerberg argues that for competitive and safety reasons, frontier AI won’t always be fully available via APIs. I can believe that. But I think second-tier models are likely to remain available via API, at least to grade-A distributors like Microsoft who can ensure safety and provide a route to market. In fact, as second-tier models get more powerful, I could imagine strict regulation of how they are distributed, which would benefit scale players like Microsoft.

The endgame may be commoditisation even in an AGI scenario. AGI should reduce the cost of developing frontier models. In addition, compute is only going to get cheaper. That argues for more and cheaper frontier models, not fewer and dearer. Cheaper frontier models would lead to a massive expansion in TAM for the industry, and probably excellent economics for the distributors.

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OpenAI

What does commoditisation mean for OpenAI? Microsoft’s contractual relationship with OpenAI keeps being weakened, so I don’t ascribe much value to it. However Microsoft does have a strategic interest in keeping multiple model providers alive, and it has an equity stake in OpenAI.

OpenAI’s frontier model performance is, broadly, matched by its main competitors. ChatGPT has a huge consumer user base (>800m) but engagement is low, there is no network effect, and switching costs for AI chat assistants are nil (I’ve personally gone from ChatGPT to Grok to Copilot to Claude and halfway back to Copilot). Unlike Meta and Google, OpenAI has no legacy business on which to unleash its LLMs to drive productivity and cash flow. OpenAI does have growing enterprise revenues but appears to be behind Anthropic, and anyway both have to compete with Google which can afford to subsidise its Gemini LLM aggressively, as it demonstrated when it reportedly undercut Anthropic when Apple was looking for a model to power Siri. OpenAI is burning cash fast as it invests to advance the frontier, and even on its own projections won’t achieve cash flow breakeven before 2030. Rolling commoditisation may prevent independent frontier labs like OpenAI and Anthropic from selling legacy models at prices that would support continued investment in their frontier models. If this is the case, they will have to generate a return on each frontier model in the year or two before its capabilities are commoditised.

None of this reads well. But big cash generative firms like Microsoft, Amazon, and Nividia have two good reasons to keep OpenAI alive: they benefit from advancing the AI frontier because this expands their TAM, and they benefit from preventing Google developing a vertically-integrated monopoly. Arguably, it is better that they share the costs than that each bears them alone. My base case is that they will keep OpenAI alive, at least for now.

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In the long run I see three possible outcomes:

1. There is a positive return on developing frontier LLMs, in which case OpenAI will survive and Microsoft’s equity will be worth something.

2. There is a negative return on developing frontier models, in which case OpenAI will die and Microsoft will buy it, shut down the frontier effort, and sell OpenAI’s legacy models to customers at strong margins.

3. Only Google and maybe Meta can earn a return on frontier models, by deploying them to improve their legacy businesses. I think this is unlikely - if there is a return on developing frontier models it will apply across the economy and thousands of companies will pay for it - but if it happens Google becomes an AI monopoly and gets broken up.

Conclusion on LLMs

While frontier models will remain an oligopoly with capital as a barrier to entry, trailing models will commoditise. As the frontier moves forward, more and more use cases will be addressable by commoditised models. This rolling wave of commoditisation will be wonderful for customers but also potentially very good for distributors. Microsoft will distribute these commoditised models by allowing customers to build bespoke apps and agents on them and by bundling cheap intelligence into existing services. Customers will choose Microsoft over independent labs to avoid getting locked into a single model vendor and to benefit from using the right model for each specific task. As commoditised models improve, Microsoft’s TAM will increase. Eventually every process in every enterprise will be addressable.

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Agents

This section is about everything Microsoft does to make agents possible, including its cloud platform, productivity suite, vast data lake, proprietary LLMs, and finally the agents themselves.

Why am I lumping all of these things together? Because while several of them are powerful standalone businesses in their own right, I think it will become increasingly clear that they all exist to support agents. In the AI era agents will drive productivity, agents will expand the TAM, and agents are where the money is.

Cheap models make powerful agents economically viable. As the AI frontier rolls forward agents will be able to do more and more complex tasks. In addition as silicon advances and datacentres become more efficient, cost per token will continue to fall. This combination - more powerful agents that cost less - will cause an explosion in use cases. To capture this opportunity, Microsoft has developed products to address every stage in the process of creating, deploying, using, and managing an agent:

• Azure is Microsoft’s cloud platform and the foundational software infrastructure layer. It provides the global cloud infrastructure, security, identity, and scalable compute on which every other product in the agentic stack runs.

• OneLake stores enterprise business and operational data, natively or via mirroring. Fabric ingests, transforms, analyses, and models this data to surface business-ready insights. Fabric IQ adds business semantics so te data has consistent meaning. Foundry IQ turns scattered enterprise content into usable data for agents. Work IQ uses Microsoft 365 emails, meetings, and documents to help agents understand a user’s role, relationships, work patterns, and how their organisation actually operates.

• Foundry lets developers build, deploy, and govern code-heavy agents. Copilot Studio lets users build low-code agents that live in Microsoft 365 apps. Agent 365 lets organizations register, manage, secure, and monitor agents from any source.

• Microsoft 365 Copilot embeds agents directly into Word, Excel, Outlook, Teams, and other productivity tools.

• Microsoft Agent Factory is a program (and procurement bundle) that brings Work IQ, Fabric IQ, and Foundry IQ together under a single metered plan, helping organizations move quickly from experimentation to deployment.

One important caveat: the customer, not Microsoft, owns the data in OneLake and Work IQ. Microsoft does not use it for training models or agents that it makes available to other customers. The data can only be used to train models and agents for that specific customer, with that customer’s permission. Nonetheless Microsoft’s agent stack is immensely powerful, combining infrastructure, data, data preparation and analytics, human and organisational insights, tools for building simple and complex agents, surfaces on which to deploy them, and tools to control and manage them.

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Microsoft is building two business models on this platform:

1. The platform, sold to customers to create their own agents.

2. Proprietary agents, sold to customers directly.

Customers building their own agents will be a huge business. As a matter of competitive necessity, every enterprise will apply agentic AI to every process to drive efficiency. Each enterprise has specific use cases and ways of working, so they will develop specific agents that suit their needs.

Building proprietary agents is potentially transformational. Microsoft has always been a horizontal software company. It builds software that can be used by all enterprises across all sectors. Outlook, Excel, security - all enterprises need these. The first thing proprietary agents can do is transform the capabilities of the existing horizontal productivity suite. By adding AI chat to Windows and agents into major applications like Excel, Microsoft increases the value-add and pricing power of its legacy products.

The second thing proprietary agents can do is help Microsoft go vertical. By building agents that automate sector-specific workflows, Microsoft can build large vertical software businesses. Microsoft Copilot inside Excel now does AI-powered DCF modeling and financial statement parsing. Copilot inside Word does contract review and case law research. Developing vertical software no longer requires domain engineers and years of development; it now requires an agent and a customer relationship. Microsoft has both.

To date Microsoft’s proprietary agents don’t have a great reputation. For example, Copilot chat has a reputation for hallucinating. I think this has caused analysts to underestimate the potential of this business. To date, Copilot has run on OpenAI’s GPT series of models. These are highly competitive but Copilot underperforms because Microsoft has limited its context window (presumably to control costs).

Three things will make Microsoft’s proprietary agents vastly better. The first is Microsoft’s move to a seat + consumption pricing model, which will allow Microsoft to charge more for users who need better performance. The second is cheaper inference. And the third is the rolling commoditisation of LLMs, which will be able to address exponentially more use cases over time.

As Satya Nadella said on the 3q26 earnings call: Agent Mode in Excel “sort of didn’t work until it started working” because the model got better. Many use cases will follow this pattern.

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Competition in agents

Microsoft is not the only company offering an agent platform or proprietary agents. At minimum, it will have to compete with the other hyperscalers plus Anthropic and OpenAI, and a host of single-product startups building agents for specific uses. I think Microsoft is well-equipped to compete, with advantages that include:

1. Distribution. Microsoft can bundle agents into existing subscriptions and products. More on this in Part III.

2. Trust. For decades, enterprise IT departments have been built around Microsoft’s data privacy, permissioning, and security architectures. This is not an unassailable moat, but it will take time for each competitor to build trust.

3. Data. With a customer’s permission, Microsoft can build agents that know who you are, what you have worked on, who you interact with, what permissions you have, and how your organisation works.

4. Scale. Microsoft can leverage the cost of developing and maintaining its agent platform and its proprietary agents across thousands of existing customers, globally.

5. Switching costs. Agents reduce these initially, by handling migration tasks that used to be a headache. But agents that handle workflows will become deeply embedded in how each organisation operates. Once large numbers of agents are working together to coordinate and execute complex tasks, switching costs will be significant. Customers know this, which is an incentive to work with Microsoft rather than getting locked into Anthropic and OpenAI (which may not stay solvent, let alone with the LLM race).

Despite this, customers will likely build agents on Microsoft’s platform and experiment with other vendors. Some of these new relationships might become sticky, or Microsoft might win these customers back as its proprietary models and agents improve. Either way, the market is big enough for several players.

Overall, I think that as the infrastructure and LLM layers commoditise, value will shift to “compound systems” like Microsoft’s agent platform.

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Economics

If that is right, then the economics are very attractive.

For starters, the market is huge. As agents do more of the work that humans can do, enterprises will devote more of their operating budget to tech spending. Agentic efficiency will also help them develop new products and services, growing revenue and boosting spending power. To get an idea of the scale, consider Microsoft 365 Copilot. Microsoft 365 has 450m customers. Over 20m of them pay for M365 Copilot. That number rose 35% in the last quarter. Paid M365 Copilot costs $30 per month. That makes it a $7bn product already. As it gets more powerful, I expect adoption and possibly pricing to rise. M365 Copilot alone could theoretically be a $50-100bn product. That’s just the general, horizontal Copilot. There are others for specific verticals, and that’s before you consider all the other agents being built on Microsoft’s platform.

If the competitive arguments above are right then margins should be strong. The platform itself has some of the economic characteristics of legacy software. Each new customer involves additional compute costs, which can be covered by consumption-based pricing. However there is no additional software development cost for each new customer. Like Windows and Office, the software component of Azure, Foundry etc. can be sold millions of times at near 100% gross margins. The cost of coding is falling fast, but that’s been true for decades; code has never been Microsoft’s competitive advantage. As long as there are some remaining advantages around distribution, trust, data, scale, and switching costs, margins should be attractive.

On the proprietary agent side, the same applies: the same advantages, and the same low marginal cost of the software component. Some of the more complex agents may be able to achieve outcome-based pricing, capturing a portion of the value they deliver rather than a fixed price. In addition, the cost to run agents will fall as models commoditise and compute gets cheaper. All of this suggests strong margins.

One concern is that Microsoft does not have a frontier LLM itself and therefore has to pay external providers for frontier intelligence. The benefit of this is that it doesn’t have to fund the essentially speculative development of frontier models. The downside is that once the OpenAI deal expires in 2032, Microsoft might have to pay market price for frontier intelligence and its gross margins might fall. But by then, I think Microsoft will have built an immense business distributing commoditised models. These will be hugely capable and cheap, allowing high gross margins for a distributor with a moat. In addition, Microsoft is building proprietary models optimised for specific large use cases. These are cheap to develop and efficient to run, and will give Microsoft full-stack economics in specific verticals.

Another concern is that for decades, Microsoft has sold its products on a per-seat basis. If one agent can do the work of several people, customers will need fewer “seats”. But if agents make humans more productive enterprises might employ more of them, not fewer (Jevons Paradox). Second, Microsoft is already migrating to a seat + consumption model, and agents will consume a lot.

On the 3q26 results call, Microsoft’s CFO Amy Hood said that AI margins are better now than they were at the same stage of the cloud transition. She implied that this isn’t widely understood, and that consumption-based pricing will improve margins. If she’s right, these statements have enormous importance.

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Conclusion on agents

Agents vastly expand Microsoft’s TAM. Microsoft offers a full stack for third parties to build their own agents without locking themselves into one model provider. It is also developing its proprietary agents which improve the value offered by its productivity suite and allow it to go much deeper into large verticals where it will own the full stack. As commoditised LLMs get more and more powerful, Microsoft will be able to offer better and better proprietary agents at strong margins.

Agents are Microsoft’s future. In Part III, we will examine Microsoft’s superpower: how it will distribute them. We will also look at the competitive advantages of combining different layers of the AI stack, and briefly discuss valuation.

Links to previous Reviews

1. IRSA

2. Brookfield

3. Cheniere

4. Uber

5. Howard Hughes Holdings

6. Millrose Properties

7. Microsoft Part 1

8. My notes

Thanks for reading - if you enjoyed reading this please subscribe, like, and restack, and do get in touch if you have questions.

Pete

This email is a summary of my activity this month.

Trades

• Sold a tracker in BMW3. Can’t get comfortable with Chinese competition and the commoditisation of AV vehicles.

• Bought a tracker in Goodwin $GDWN.LN after a massive spike and drawdown. Family run compounder in high-end steel foundry.

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Articles I wrote

• Can Microsoft Compete? Part 1 - revisiting a stock I have held since 2010.

• Millrose Properties. Don’t like the risk/reward one bit.

• Uber Freight. Counterpoint to the article linked below.

• Brookfield 4q call summaries. Done by hand, not by AI!

• Howard Hughes Holdings - shaping up to be a good compounder, if you can live with the fees.

What I found interesting this month

• on Millrose Properties - the bull case to my bear.

• on Howard Hughes, Progressive and Fairfax, and PE-backed life insurers.

• on the other side of the private credit coin.

• on offshore drillers.

• on Goodwin.

• on how dividends destroy shareholder value.

• on nuclear.

• on cheap Chinese cars - relevant to my Uber thesis.

• on how to think about volatility and the alt managers.

• on moats in luxury.

• on Uber’s logistics platform.

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Thanks for reading - and please get in touch if you have questions.

Pete

What it does: enterprise software.

Elevator pitch: arguably one of the finest franchises ever built, with deep distribution advantages that let it deliver innovations cheaply to a huge customer base.

Mental model: moat (read about my mental models here).

Valuation and potential returns: 21x June 2027 EPS estimates and growing EPS 20% per year.

Exchange and ticker: Nasdaq, MSFT

Stock price and market cap: $401, $3.2tn.

Do I own it? Yes.

IR website: here.

About this blog: I have been investing for 25 years, professionally and personally. I look for stocks that have a high probability of compounding at 15% for at least 5 years with limited downside. I write these stocks up on my blog. You can find more about me, my philosophy, my mental models, and my portfolio structure on my site.

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

Introduction

I have owned Microsoft since 2010. What gave me the confidence not to sell - even as the company transformed and the multiple expanded - was a deep conviction in Microsoft’s competitive moat. Not its technology. I don’t think technology ever constitutes a sustainable advantage in itself. The moat was distribution. Microsoft sells to enterprise. Enterprises move slowly. Microsoft is deeply embedded: enterprise IT departments are built on its products, and it has a huge reseller network reaching millions of SMEs. Microsoft leverages this difficult-to-replicate incumbency by copying innovations (it is the quintessential second-mover) and bundling them cheaply alongside existing products. This has been remarkably hard for standalone competitors to fight.

Distribution + time to react + cheap bundling = a moat full of crocodiles.

Does AI change this?

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Satya

Satya Nadella is the CEO of Microsoft and the chief architect of its renaissance over the last 15 years. Two things he has said over the years rattle round my brain:

1. The software industry - and by implication, Microsoft - has no franchise value.

2. With agentic AI, Microsoft’s TAM is every process in every organisation.

Both of these comments are mind-blowing. One is a stark warning. The other is exceptionally bullish. They appear contradictory, yet both are right. This makes analysing Microsoft a fascinating challenge.

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Why I wrote this

Microsoft is a largeish position for me, and I have a long term time horizon - 5 years at minimum, and ideally 10 years or more. However Microsoft’s business is changing rapidly as AI alters its competitive landscape. I needed a better framework for understanding how the industry is evolving. A vast amount has been written about this, although a lot of it is very short term (Azure only grew 39% in 2q26, not 40%!). This piece is an attempt to synthesise what I have read into a framework for interpreting newsflow over the next few years: what will be the signs that Microsoft’s competitive position is strengthening, or weakening?

I am a generalist, not a tech expert. This can make interpreting short term newsflow harder, but might make interpreting long term trends easier, because what will drive long term trends is not the latest tech advance but classic competitive dynamics. The key principle is simple: if too many companies can do a thing, pricing will fall until the return on capital equals the cost of capital. The main beneficiaries of innovation will be the customer, not the innovator.

This piece focuses on each layer of the AI tech stack and whether long term competitive advantage will be carved out in any of them (or by combining any of them). It does not address the idea that AI drives the value of everything to zero and software is dead. This is deliberate. I see limited evidence in favour of this theory so far. On the contrary, AI seems to be strengthening the classic tech competitive advantages of network effects and access to unique data. In addition I think it is almost impossible to analyse this thesis sensibly given the comprehensive advances in technology that would be necessary and the unpredictable ways incumbents might find to defend themselves. I do not dismiss the possibility, but rather than letting it scare me out of investing in the greatest productivity advance in human history I prefer to think through the wider impacts and find ways to hedge. But that’s a separate topic entirely.

This article will be published in 3 parts:

1. Introduction, layers, silicon, and infrastructure.

2. LLMs and agents.

3. Distribution, combining layers, and conclusion.

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Layers

There are multiple layers in the AI future:

We need to frame whether real competitive moats can be created within each layer or by combining layers. And to do that, we need to start at the bottom.

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Silicon

Having the cheapest compute is a clear advantage in the AI race. Evidence for this is already showing up in earnings releases. The undisputed champion of highly advanced general-purpose AI silicon is Nvidia and it does not look like this will change any time soon. All AI infrastructure builders will probably need buy Nvidia for a long time. This levels the playing field to some degree, because they’re all using the same chips for large parts of their workload.

That said, by designing silicon in-house hyperscalers like Microsoft can keep pressure on Nvidia pricing and maximise infrastructure efficiency by tightly integrating chip design with the hardware and software that comprises the rest of the system. One of the core themes of this article is that several layers of the AI stack will at least partly commoditise, and in commoditised industries efficiency is the key competitive battleground.

Amazon, Google, and Microsoft all have their own in-house silicon design programmes which are emerging as core competitive advantages and significant businesses in their own right. Microsoft’s programme is currently the laggard. It unveiled its first chip in late 2023, several years after Amazon and Google. It is therefore promising that Microsoft’s Maia 200 chip, released in January 2026, already appears to be competitive with Google and Amazon’s inference chips. However, the data comes from Microsoft’s internal testing, the exact parameters for these tests have not been released, and there is limited third party validation. In addition, Microsoft’s production volumes are much smaller than Google’s or Amazon’s.

In short: this is a weak point for Microsoft but they are addressing it. Given the importance of inference efficiency, what we know about Maia, and the Microsoft programme’s comparative immaturity, I think Microsoft is likely to close the competitive gap rather than slip further behind. I think all 3 companies will have highly competitive silicon, and this will be a competitive advantage against compute providers who don’t have in-house silicon. I am less certain that any of these 3 companies will develop a lasting silicon advantage over their peers.

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Infrastructure

The hundreds of billions being spent on AI infrastructure are the stuff of legend. Hyperscalers have little choice but to build today: the world is short compute, and if they don’t build it they can’t sell AI to their customers. That is death. Nonetheless, there are two big questions regarding this spend:

1. Will current spending produce a worthwhile return on investment?

2. Does owning infrastructure confer a lasting competitive advantage?

I think the answers are yes and maybe.

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Infrastructure question 1: ROI

Here’s how today’s capex could earn a poor ROI:

• Supply gets overbuilt.

• Demand collapses.

• Obsolescence.

The supply overbuild argument is predicated on the idea that rising capex multiplied by improving efficiency = explosive growth in compute capacity. Currently, all the evidence is that more capacity is needed: hyperscalers say they are capacity constrained, Microsoft has to choose between allocating capacity to internal uses and selling it to customers, and older generations of chips aren’t being retired, suggesting they can still be rented out for attractive prices even though better chips are available. So far, so good. But will this last?

Bears point to the huge overbuild of fibreoptic capacity in the dot-com bubble as an obvious analogy. The problem wasn’t just that capacity was overbuilt initially; two additional factors combined to make things worse. One was that the capacity bottleneck was the send-receive technology at either end of the cable. Rapid improvements in cheap send/receive technology therefore multiplied capacity for years after the cables were installed. The second factor was that fibreoptic cables last decades if they’re installed well. As a result, overcapacity never self-corrected even as internet traffic exploded.

The datacentre buildout looks very different to my eyes. This is partly because there are clear braking factors on capacity growth, notably power availability, chip supply, and the fear of overbuying one generation of chips before a more efficient one comes along. Also, when we break the capex into its component parts some important differences with the fibreoptic buildout emerge. Roughly:

• 15% goes on land and buildings. This is the component that looks most like fibreoptic cables: the compute capacity that goes in the buildings will keep getting better and the buildings will last decades. But even if a few too many get built, the loss on the excess capacity won’t be total: land and buildings can be repurposed and retain value.

• 25% goes on electrical and cooling equipment. In the event that capacity is overbuilt this will suffer significant impairment, although much of it can be repurposed/used for parts.

• 60% goes on the actual compute, including GPUs. This is where most of the capex is going and it is where the fibreoptic analogy really breaks down. Although software improvements can meaningfully improve the performance of installed chips, there is no bottleneck equivalent to send/receive in fibreoptic. Instead there is a hard ceiling set by the physical hardware, so capacity cannot multiply for years after installation. And the useful life of chips, while subject to much debate, is far shorter than that of fibreoptic cable. As a result, compute capacity degrades over time rather than compounding. Even if capacity gets overbuilt, this will bring supply and demand back into balance relatively quickly.

What about demand collapse? The bearish argument is that training frontier models has an unproven ROI, and if investors get tired of pumping cash into OpenAI and Anthropic (in particular) they will have to cut back on training their next generation models. However, I think the risk of demand collapse is diminishing:

1. Inference has grown from 1/3rd of compute usage in 2023 to 2/3rds in 2026. Inference is driven by adoption of AI, not training new models. In my opinion, adoption has barely begun. Even if training spend drops, inference will keep growing, and compute built for training can be retasked to run inference workloads (albeit less efficiently).

2. It is becoming increasingly clear that AI has vast real-world uses. OpenAI and Anthropic are growing revenues rapidly - Anthropic has grown annual recurring revenue 30x in 15 months and 3x in the last 4. This might be the fastest revenue ramp in technology history. These companies are nowhere near self-funding, but as revenues grow their dependency on investors falls and their attractiveness to investors rises.

Finally, obsolescence is the idea that if tomorrow’s data centre is vastly more cost-effective than yesterday’s, then tomorrow’s datacentre will set pricing and yesterday’s will struggle to earn a decent ROI. What great leaps forward will render today’s capacity obsolete? Two possibilities come to mind. The big one is the efficiency of leading-edge chips. These will inevitably obsolete older chips. That’s a problem if the step up from one generation to the next is huge, and if the generations come in rapid succession. The evidence so far is the opposite: chips remain competitive long enough to more than earn their cost of capital. My guess is this will continue, but of course it is linked to demand: the combination of a huge step up in chip efficiency and a significant slowdown in demand would render a generation of chips obsolete. That said, this would be a one-time event and would collapse the cost of compute, stimulating demand and raising margins in other parts of the business. It’s a risk, but not an existential one.

The other potential great leap forward is some paradigm shift, such as Elon Musk’s goal of putting datacentres in space to benefit from 24/7 solar power and infinite radiative cooling into deep space. While this is theoretically coherent, it is a wildly complex idea to deliver cheaply. To put it politely, I suspect we are in for a wait.

In conclusion: the risk of a short to medium term ROI collapse is likely overstated by the bears. Demand is growing ahead of supply and may do for years. Indeed, the real risk is not spending, not being able to sell AI, and losing customers that can’t be regained. Nonetheless, at some point supply and demand will meet. ROI will compress, but capacity degradation will correct this fairly quickly. Also, any reduction in ROI on infrastructure may be offset by margin improvements in the layers that use compute. More on this in Part II.

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Infrastructure question 2: does owning infrastructure confer a lasting competitive advantage?

Question 1 dealt with the short to medium term ROI on current capex. Question 2 is about long term ROI on infrastructure: does owning infrastructure confer competitive advantage such that ROI stays high, or does infrastructure commoditise?

There doesn’t seem to be much competitive advantage in owning the “bare metal” - the land, buildings, cooling systems, racks, and chips that make up a datacentre. But there is competitive advantage in integrating it all together. Running 100,000 GPUs as a coherent unit with optimised interconnect, utilisation, cooling, and so on is extraordinarily hard, and doing it better drives significant efficiency gains. Microsoft, Amazon, and Google have spent a decade learning how to do this. A new entrant cannot replicate this knowhow overnight even if they buy the same chips. But whether this edge is sustainable is another matter. We are in the early innings of a massive buildout. Multiple players are throwing capital at this and need to solve it if they are to survive. I think it is likely that the optimisation gap between the leaders and followers will narrow over time.

The other way to think about this is by workload. Infrastructure for frontier models and the most demanding large-scale inference needs to be optimised to perfection and there are genuine gaps between the leaders and the rest. On the other hand, infrastructure for standard inference done by midsize models is already commoditising. Competition is mainly on price and reliability. In addition, as small models improve and chips get more energy-efficient, inference will move to the edge driven by advantages in latency, security, and cost. (In other words, for simple tasks models will run on your computer or phone rather than in a datacentre.)

These two trends - the narrowing of the optimisation gap, and the relentless forward march of the frontier leaving ever more commoditised inference in its wake - suggest to me that over time, more and more infrastructure will become commoditised. If so, a new utility industry will emerge selling commoditised compute with a mix of long term contracts and instantly-available capacity at spot. There may be competitive advantage in owning frontier infrastructure, but as the industry matures hyperscalers like Microsoft will be able to choose what they own and outsource the rest.

This has implications for ROI and free cash flow. The market sees the hyperscalers ramping capex and worries that ROIC and FCF must fall. I think this framing might be wrong. What’s really happening is that the hyperscalers are incubating a second business. While AI is compute constrained, hyperscalers must own compute in order to guarantee supply and sell AI. But in the long term, the decision to own compute will be driven by ROI. If there is long term competitive advantage in owning compute, the ROI will stay high and the hyperscalers will retain ownership. If not, utility compute can be separated from the original capital light businesses, either by selling/spinning compute or simply by reducing capex and buying third party compute. My money is on at least partial commoditisation and separation.

What really matters, therefore, is that the original capital light business is still there, still profitable, and has a vastly expanded TAM. We will explore this in Part II.

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Links to previous Reviews

1. IRSA

2. Brookfield

3. Cheniere

4. Uber

5. Howard Hughes Holdings

6. Millrose Properties

7. My notes

Thanks for reading - if you enjoyed reading this please subscribe, like, and restack, and do get in touch if you have questions.

Pete

What it does: finances land banks for homebuilders

Elevator pitch: homebuilders want to go capital light. Millrose is happy to buy their land and sell it back to them when they need it, for a fee.

Mental model: n/a - I was hoping it would be value (read about my mental models here).

Valuation and potential returns: trades slightly below book value with a 10% yield. I think the upside is capped at 10% and the downside is significant.

Exchange and ticker: MRP, NYSE

Stock price and market cap: $31, $5.1bn

Do I own it? No.

IR website: here.

About this blog: I have been investing for 25 years, professionally and personally. I look for stocks that have a high probability of compounding at 15% for at least 5 years with limited downside. I write these stocks up on my blog. You can find more about me, my philosophy, my mental models, and my portfolio structure on my site.

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Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

I meant to write about Microsoft this week, but got distracted by this. I don’t plan to write about stocks I don’t own very often, but I enjoyed thinking through this business model and the risks.

What it does

Millrose finances land banks for homebuilders. Homebuilders find a property they want; Millrose buys it; the homebuilder pays a deposit and an option premium; Millrose funds the development of horizontal infrastructure (roads, utilities, landscaping etc.); the homebuilder can then build and sell homes; and then, finally, the homebuilder exercises its option to buy the property.

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How the finances work

Millrose’s P&L and balance sheet are almost completely separate (at least when things are going well - more on that later).

The P&L is quite simple. It looks like this: regular option premium payments, less management fees, less interest on debt, equals dividends. There is not much tax or retained earnings because Millrose is a REIT.

The balance sheet is also fairly simple: home sites on the asset side and equity + debt + deposits (in that order) on the liability side.

The cash flow statement is more interesting. Balance sheet activity creates massive inflows and outflows of cash. Millrose receives deposits, buys land, pays for horizontal infrastructure up to a pre-defined limit, and then sells the land at total cost. It looks like this:

In rough terms, the cost of the land and the cost of the basic infrastructure are about equal. I derive this from the fact that at year end Millrose had about $8bn of land on the balance sheet and will receive about $16bn if all options relating to that land are eventually exercised. The difference is the cost of developing basic infrastructure: another $8bn.

These asset cycling cash flows can be billions of dollars over a year. Because Millrose sells the land + infrastructure at cost, these transactions don’t usually touch the P&L. However, as we will see, there are real risks with this activity.

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Why Millrose exists

Millrose was spun out of Lennar. It buys land from or for Lennar and other homebuilders. This allows the homebuilders to control a land bank without carrying it on their balance sheet. The idea is that the stock market rewards capital light businesses with higher valuations. This is true, but the market is not stupid (most of the time). It understands that in capital-heavy businesses, there is a cost, financial or strategic, to going capital light. And homebuilding is a fundamentally capital-heavy business: you can’t build homes without land, and the land needs to be good.

To go capital-light, therefore, homebuilders need to get land off their balance sheet while keeping access to it, keeping the economic upside of ownership, and transferring most of the risk. And that is exactly what Millrose lets them do.

Landbanking is not new. What’s new is listing a landbanking vehicle. Most landbanks are funds. They raise capital, buy land, sell it, and return the capital to investors. Millrose, being listed, doesn’t return the capital. Instead it recycles it into the next land acquisition. The other difference is that Millrose, being a REIT, taps into a large market of yield-hungry investors, particularly (I suspect) retirees. This may reduce the sophistication of Millrose’s investor base, and its cost of capital.

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The bull case

Homebuilders are willing to pay 8-11% of the land value per year in option fees, which is sufficient for Millrose to pay a good dividend to its shareholders.

Millrose’s addressable market is theoretically huge. The value of the land and horizontal infrastructure underlying annual home starts in the US is $170bn. That’s all got to be on someone’s balance sheet, and why shouldn’t it be Millrose’s? The potential for growth seems huge. And indeed, according to management on results calls, homebuilders have been beating a path to Millrose’s door since the spin in early 2025.

A hard-asset company, trading at a discount to book value, yielding 10%, with a long runway for growth? What’s not to like?

Let’s find out.

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The problems, in no particular order

Millrose pays Kennedy Lewis a management fee worth 1.25% of tangible capital. Not net tangible capital, and not tangible capital per share - just tangible capital. This seems to create two gloriously perverse incentives:

1. to issue cheap shares and buy expensive assets. There is some protection for the first 18 months post-spin, because Lennar kept a right to be compensated with extra shares if Millrose issued new shares below Lennar’s in-price. But once that date is past, I imagine the stock certificate printer at Millrose will go brrrrrrr. This might make it hard for the stock to rerate.

2. to carry assets at inflated valuations. Note that Millrose has not obtained an independent appraisal as to the value of its land. In effect, we have to trust the value that Lennar put on the land when it span Millrose out. Future acquisitions will be carried at cost (until they’re not).

Homebuilders sell land to Millrose, or bring Millrose ideas for land to buy. I think we can safely assume that they keep their best land on their balance sheet. There is a clear risk that they will dump their weaker assets on Millrose, and Kennedy Lewis will buy them to boost fees. Worse, Kennedy Lewis run traditional landbanking funds which compete with Millrose for acquisitions, so it is not even clear that the manager’s best deals will go into Millrose.

Millrose will struggle to grow book value or dividends per share. REITS have pay out most of their profits, so they can’t retain capital to grow. However most REITS do at least benefit from inflation in land prices and rents. Millrose does not: when they sell land, they only recoup their cost. Any land price inflation during Millrose’s ownership accrues to the homebuilder. Inflation protection is one of the main reasons to own real estate of any kind, and Millrose doesn’t offer it. This is one of the reasons Millrose’s yield is higher than most REITS: most REIT yields are implicitly inflation-linked (because underlying rents are expected to rise with inflation over time) but Millrose’s is not.

Millrose only has two ways to grow on a per share basis, and both are limited:

1. It can take on debt, but this adds risk and Millrose cap themselves at 33% debt-to-capital. They’re already at 25%.

2. It can shift its business mix away from Lennar towards other homebuilders, who pay higher options yields. However, Lennar has the right to reserve a significant part of Millrose’s capital. The exact calculation is complex, but the impact is that Millrose can’t grow its business with other homebuilders very much without issuing new shares. Since issuance may well be below book value, the resulting dilution is likely to offset the mix shift benefit.

Homebuilders don’t have to exercise options. They don’t even have to build homes on the land. If a project is uneconomic homebuilders can simply walk away. If they do, they lose their deposit and pay a termination fee, but in a major market downturn or if there are extreme project-specific issues walking away might be the economic or even the only option. It is inevitable that some options will not be exercised. In these cases, Millrose keeps the land but almost certainly loses money. They may be forced to sell the land for less than they paid, or worse: when a homebuilder walks, Millrose is liable for all the costs related to the land, which might include claims from unhappy homebuyers, the cost to remove partially-completed construction, or environmental reclamation costs.

In theory Millrose is protected from homebuilders walking away from options because land parcels are pooled: if a homebuilder walks away from one option it loses all the deposits in the pool, and Millrose can terminate the other options in the pool. Diversification within pools is meant to ensure that the assets aren’t correlated. Pooling ought to incentivise homebuilders to exercise, not walk, but it is imperfect:

1. Millrose cannot refuse to sell assets to Lennar, even if Millrose dispute Lennar’s right to buy based on pooling cross-termination provisions. All Millrose can do is litigate to recover losses. There is no guarantee this will succeed, and doing it could wreck Millrose’s relationship with their major customer. In addition, Lennar’s payments per pool appear to be capped, which presumably limits the value of the pooling provisions to Millrose.

2. When Millrose was spun out of Lennar, it was Lennar that chose which assets went into which pool. It is prudent to assume that they designed the pools to their benefit. Pooling offers little protection if all the bad assets are in one pool.

3. The following language appears in the 10k: “Lennar retains substantial discretion in selecting pool properties and setting pool terms. We may have limited ability to negotiate pooling conditions with Lennar…and we may not be able to negotiate pooling terms at all with Other Counterparties”. While this is to some extent boilerplate wording, it’s also true: pooling is by definition done through negotiation with homebuilders, who are not stupid. They will not accept pool terms that significantly increase their risks.

There are two implications of the homebuilder right to walk. The first is that far from growing, Millrose’s per share metrics are likely to decline over time. Millrose does not make a profit when a homebuilder exercises their option to buy a homesite - it simply gets back what it spent. But when a homebuilder does not exercise their option, Millrose is highly likely to take a loss. Millrose cannot offset inevitable losses on bad projects with profits on good ones. It can replenish the lost capital by issuing shares, but there is no incentive to do this above book value. Between losses on projects and share issuance below book value, it seems highly likely that book value per share will erode over time. And if book value per share erodes, so eventually must dividends per share, since the dividends are derived from asset ownership.

The second implication of the homebuilder right to walk is that Millrose has a potential cash flow timing mismatch which could be quite serious if there is a downturn or dislocation in the housing market. If homebuilders stop exercising their options, the cash inflow from selling land + horizontal infrastructure stops. However Millrose does not control the timing of the cash outflow to build horizontal infrastructure: if the homebuilder wants it built, Millrose has to fund it. Millrose could therefore face a situation where billions of dollars flow out but not in.

Millrose’s dividend is exposed to both housing market conditions and interest rates, which are likely to be somewhat correlated. Under some market conditions Lennar can suspend monthly option payments or reduce them by 50%. Other homebuilders may simply stop paying their option premiums. In addition, Millrose competes with alternative sources of finance. If interest rates fall, option premium rates on new deals must fall to remain competitive with debt finance. Millrose’s P&L is operationally and financially levered, so any reduction in option premiums will drive an even greater reduction in the dividend. Millrose’s dividend might behave more like a levered floating rate bond coupon than an equity dividend.

Finally, Millrose’s share structure means the company will never be subject to shareholder activism or sold to the highest bidder. Millrose has two classes of stock. The A shares trade publicly and have 1 vote per share. The B shares are 99% owned by the Miller family, which founded, runs, and effectively controls Lennar. Currently the B’s have 10 votes per share and 43% of the total votes. No matter how many A shares are issued, the B’s will never drop below 35% of total votes. Any amendment to Millrose’s Charter requires a 2/3rds supermajority, meaning in effect that the B’s have a veto. The Charter forbids anyone from owning more than 9% of Millrose unless exempted by the board - and anyway the B shares have a collective veto over various things, including a sale of the company.

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Financial engineering

The comparison between the finance Millrose offers and the finance a lender offers is stark.

Option yields (premiums/land value) are 8-11%. Compared to debt, this seems like an expensive way to fund a land bank. However, the spread is significantly lower once you include Millrose’s significant investment in horizontal infrastructure, and it is arguably not adequate compensation for the additional risk Millrose takes compared to a lender.

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How it could go wrong:

1. Kennedy Lewis grow Millrose as fast as possible, levering up and issuing shares to buy every land bank a homebuilder offers them without sufficient concern for downside risk.

2. The economy turns down and interest rates follow.

3. Some homebuilders stop exercising option contracts but Millrose still has to fund horizontal developments at the projects that are moving ahead. Cash makes a giant sucking sound.

4. To fund itself, Millrose sells land for whatever it can get. The company doesn’t take impairments, but it becomes clear its assets aren’t worth their marks. With leverage, mark-to-market book value is seriously impaired.

5. Lennar reduces its options payments by half. Rates come down so new deals, if there are any, are done at low yields. Millrose’s management fee and debt interest are fixed, however, so net income basically evaporates. The dividend is cut to 0. Panicked retirees rush for an increasingly crowded exit.

6. The stock drops 90%. Lennar offer a 20% premium to buy their land bank back for a song. There’s no counterbid because the Class B shares would veto it. Desperate shareholders vote for the deal.

This isn’t a prediction. But it wouldn’t be the first time, either.

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Conclusion

Millrose yields 10%, but can’t grow value per share because it can’t retain profits. In fact, value per share is likely to decline in the long run because the manager has a strong incentive to issue shares below book value and because the company cannot offset the inevitable losses on some deals with gains on others. So the upside appears capped at +/- 10% per year, and that might be generous.

The potential downside, however, appears significant. There are protections in place such as pooling but the structure seems prone to a cashflow crisis, balance sheet impairments, and/or significant dividend reductions. I am not certain that any of these things will happen, but if they do, they may all happen at once.

On top of that, neither the manager nor the owner of supervoting shares seem well-aligned with Class A shareholders.

Contrast the risk/reward with Berkshire Hathaway, my go-to comparison stock. In my estimation Berkshire has a good chance of compounding intrinsic value at +/- 10% over time, so the upside is similar, but the chance of Berkshire becoming seriously impaired is vanishingly small. In fact, at just the sort of time when Millrose might become impaired, Berkshire is likely to be increasing its intrinsic value by buying assets on the cheap.

Also, a big part of investing is positioning yourself to make good decisions in tough times. With Berkshire, I know I won’t panic sell at the wrong time. With Millrose, I don’t.

There is only one way to find out whether this company will do well in a major downcycle: wait for one. I am happy not to own it while I do that.

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Links to previous Reviews

1. IRSA

2. Brookfield

3. Cheniere

4. Uber

5. Howard Hughes Holdings

6. My notes

Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

Uber Freight has two parts:

1. Digital freight brokerage was launched in 2017 and operates as a marketplace; shippers post loads and carriers accept them through the Uber Freight app. Uber earns the spread between what it charges shippers and what it pays carriers, so it is exposed to spot pricing cycles.

2. Managed transport is a SAAS+services business which manages the entire carrier network for large shippers. This is deeply embedded into sticky customers and is insulated from spot pricing cycles.

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Uber Freight’s right to win

Freight is a large and potentially attractive business, but it’s highly competitive with established scale players.

Uber’s 10k states: “We believe that Freight is revolutionizing the logistics industry. Freight powers a managed transportation and logistics network and connects Shippers and Carriers in a digital marketplace to move shipments while leveraging our proprietary technology, brand awareness, and experience revolutionizing industries. Freight provides an on-demand platform to automate and accelerate logistics transactions end-to-end while providing visibility and control of logistics networks. Freight connects Carriers with Shippers’ shipments available on our platform, and gives Carriers upfront, transparent pricing and the ability to book a shipment with the touch of a button. Freight serves Shippers ranging from small- and medium-sized businesses to global enterprises. By leveraging logistics solutions expertise and value-add solutions, Freight enables Shippers to create and tender shipments, secure capacity on demand with real-time pricing, and track those shipments from pickup to delivery. Freight operations are principally based in North America and Europe. We believe that all of these factors represent significant efficiency improvements over traditional transportation management and freight brokerage providers.”

“Revolutionising.”

“Significant efficiency improvements.”

This sounds good.

Is it reflected in the evidence?

Not really:

Now in fairness, freight is a cyclical industry. 2023 saw a post-covid boom in shipping rates that boosted revenue (but apparently not ebitda). 2023/4/5 saw a predictable hangover which may be masking progress in revenue growth and margins at Uber Freight. CH Robinson is a competitor in the brokerage industry and shows a similar cyclical trend:

Three things strike me from these figures:

1. Even allowing for the cycle, Uber Freight shows no obvious evidence of being a disruptive technology that’s “revolutionising” an industry.

2. Uber Freight appears to be subscale, at least compared to CH Robinson.

3. CH Robinson is far more profitable than Uber Freight, despite focussing on brokerage, supposedly the lower-quality part of the business.

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Going deeper

It is tempting to point to obvious inefficiencies in logistics and conclude that technology - and specifically, Uber’s technology - can solve them. However:

• Uber Freight is not uniquely positioned to address inefficiencies in logistics - as I discuss below, there are multiple large players with decades of data and plenty of capital who are building solutions, too.

• Some of the inefficiency is structural, creating the illusion of opportunity where in fact there is none. We will never get to the point where every truck is full all the time and no load ever has to wait. It is physically impossible.

Brokers match people who need something moved to people who have a truck. In theory there is a network effect here: the bigger the network, the easier it is for the broker to minimise inefficiencies such as half-empty runs and long journeys to collect loads. However there are no barriers to entry in freight brokerage, and there is no evidence to suggest that network effects are strong enough to drive winner-take-most dynamics. There are an estimated 16,000 brokers in the US. The top 10 firms control about a third of the market. Beyond that, brokerage is wildly fragmented. Even tiny players can build local networks strong enough to keep them alive. In addition there are “load boards”, neutral marketplaces where loads can be posted and accepted, which allow small brokers to widen their reach and also allow shippers and truckers to find each other without brokers at all.

The big brokers (CH Robinson, RXO, J.B.Hunt, etc.) are large, well-capitalised, and very capable of keeping up in the technology race. The same goes for the dominant load board (DAT One, owned by Roper Technologies). The digital native insurgents that tried to dislodge the leaders in the 2010s have died - Convoy was probably best in class and collapsed in 2023. It is not obvious to me why Uber would have transformationally better tech than any of the other big players. Uber might take share from the tail, but CH Robinson has been doing that for decades and still “only” has 17% share.

In managed transport, while I can accept that customers are sticky, the same argument applies: I see no reason why Uber will be transformationally better than the competition, so while it might keep its existing customers, I do not understand why it should take share or have real pricing power. In addition we have no idea whether Uber is profitable within this segment. If it is, then brokerage is losing money hand over fist, which suggests brokerage is a much worse business than its peer CH Robinson.

I accept that the industry is in a downturn and Uber Freight have spent several years integrating an acquisition and rebuilding their technology. The business may well perform better in the next cycle. But have they built a platform for dominance? I don’t see it.

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Where it gets interesting

There is one area where Uber Freight can genuinely do something different. By linking with Uber’s gig-economy driver network, Uber can add last-mile to its Freight offering. The long-run vision is a single platform that orchestrates first-mile, long-haul, and last-mile delivery across transport modes and geographies. This is virtually impossible for other freight brokers to replicate.

The problem is, I am not sure how many customers really need freight and last mile in the same package. Most users of freight are shipping from a factory to a warehouse or a retailer. And if they do need last-mile delivery direct to the customer, why would they choose Uber over or Amazon, which already offers consumer discovery, factory-to-doorstep logistics, trust, and returns all in one service?

That said, I do think there is a logic here. Direct to consumer is growing. By combining discovery and logistics, Uber can be a part of that trend. But a big, profitable part? Uber Freight has a lot to prove before we can conclude that.

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Conclusion

Uber Freight operates in a large market where others have built profitable, capital light businesses. It may well become one of those. But there is very little evidence that it is a disruptive force, able to deliver materially greater efficiencies than competitors and take market share.

As an Uber shareholder I would absolutely love to be wrong on this. Do you think I am? Persuade me!

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Links to previous work

1. IRSA

2. Brookfield

3. Cheniere

4. Uber

5. Howard Hughes Holdings

6. My notes

Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

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Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

BN

• FY25

  • DE $6bn, DEBR $5.4bn = $2.27/share, +11%. DEBR CAGR since 2021: 18%.

  • Raised $112bn, financed $175bn, sold $91bn, and deployed $126bn.

  • Insurance assets now $145bn.

  • Operating business DE $1.6bn.

  • $11.6bn unrealised carried interest. Will realise significant amounts in next 3 years.

  • Bought back over $1bn at $36 per share.

  • Issued CAD1bn of 7- and 30-year notes.

  • 17% increase in the dividend to 28c/year.

• “Splitting market capitalisations” across multiple securities doesn’t work in the age of indexing. Now streamlining. “Initial step” was merging Business Partners and Corp. Next they will merge the insurance entity into BN, which will allow insurance to fully benefit from BN’s capital base and grow. Will assess other subsidiaries in the future and they are already issuing Corp shares to buy LP units in both BIP and BEP.

• Long term stock returns: 19% 30y CAGR; $1m turned into $285m. Only works if you pick a good business, run it well, and don’t interrupt compounding, which requires excess capital and a flexible balance sheet.

• Business relationships are “increasingly with the best”: Google, NVIDIA, JP Morgan, Microsoft, the US government.

• Liquidity has returned in both debt and equity markets and interest rates are starting to come down, which “will do wonders” for the US economy.

• Real Estate: with limited new supply and growing demand, asset values are “set to rise substantially”.

  • Sold $24bn in 2025, invested $33bn, financed $42bn.

  • FFO catching up to NOI on higher rents, tighter financing spreads, and some deleverage. Also, 20-25% of the debt is floating so 25bps lower rates adds $35m FFO.

  • Signed 17msf of office leases in 2025 at 18% spreads in super core and core plus. Virtually no new office supply coming in gateway cities globally, several of which are seeing prime office rents 50% above pre-covid levels.

  • “Capital markets get stronger by the day. Those really involved in the business [are starting] to appreciate what’s going on in the office market...I think as that…broadens, you’re going to see transaction activity really pick up…[and] we will be poised to monetize a number of assets”.

  • Have derisked the NA resi business by selling MPCs; now more capital light.

• Wealth Solutions:

  • DE $1.7bn, up 24%. 2.25% spread, 15% ROE.

  • DE will exceed $2bn in 2026 on $20bn of capital.

  • Have worked hard to diversify the liability side across product types and geographies so they can allocate capital to wherever the cost of funding is lowest. Pricing can move fast.

  • In the UK, £500bn of pensions will come to the risk transfer market over the next 10 years.

  • Growing footprint in Asia where demographics make savings products key.

    • $3tn of life and savings insurance on Japanese insurer balance sheets alone. After 3 years of work they have strong relationships with half a dozen insurers and first deal done.

    • Asia Pac has broad trends towards investing in financial assets - building relationships.

  • P&C business delivers $8bn of float at “virtually no” cost, and should make underwriting profits in future. Will grow organically and buy other assets cheap in down markets, with a path to $20-25bn of float by the end of the decade. P&C is less competitive than annuities.

BAM

• FY:

  • Raised $112bn, invested $66bn, sold $50bn.

  • FBC +12%, FRE +22%, DE +14%. FRE up 28% in the q.

  • Issued $500m of 5 year notes at 4.65% and $400m of 10-year notes at 5.3%.

  • Dividend +15%.

• 2026 looks very strong

  • Oaktree, Just Group, and acquisitions in Q4 will alone add $200m to FRE.

  • Expect a “further step change” in fundraising and likely dealmaking.

  • Closed flagship RE and Transition funds, giving dry powder to deploy at a very attractive point in the RE cycle.

  • Launched or launching new infrastructure and PE flagships.

  • Operating leverage is driving margins up in each business but consolidated margins will fall on

    • Acquisition of Oaktree. Oaktree is structurally lower margin, and is at a (counter)cyclical low.

    • Breakout of partner manager economics. BAM will now report their revenues and costs, not just FRE, and they are currently subscale and low margin, but rising.

• By broadening the platform, “we have built a business that can raise capital more consistently and deliver an earnings profile that is more predictable, more resilient, and better positioned to grow across economic cycles”.

  • 90% of 2025 fundraising was non-flagship.

  • In 4q they raised $35bn across 50 strategies; in 2026 they will raise across 60 strategies compared to 4 10 years ago.

  • They have 2,500 institutional relationships, up 10x over 10 years, plus 70k clients in private wealth and 800k in insurance.

  • Wealth is “an absolutely amazing opportunity” in terms of potential scale across 3 channels: retail/HNW, insurance policy/annuity, and 401(k)/retiree benefit.

• “A step change in growth is emerging across our infrastructure and private equity platforms”.

  • Strong investor demand.

  • AI needs infrastructure.

  • PE needs change management to deal with AI. Operators will win not financial engineers. Half of Brookfield’s returns historically have been driven by operating improvements, “a real differentiator”.

  • Unlike many, they have returned $10bn of PE investor money over the last 2y.

• AI is a strong net positive for the business.

  • Very little exposure to things that might be disrupted (software), much exposure to things that might benefit (industrials), and ability to deploy capital against long term contracts with world class counterparties (datacentres).

  • Huge client appetite for AI - first fund has $5bn committed of $10bn target, likely >$20bn with co-invest.

  • “There is no question. The bottleneck to AI growth today is not capital. It is not demand. It is electricity supply.”

• Private credit demand remains very robust, driven by huge capital requirements to build out assets.

  • Demand outweighs supply in real asset and asset-backed credit.

  • Spreads are very tight in commoditised areas, but distress here is driving increased activity in opportunistic credit.

• Teskey becomes CEO, formalising a change 4 years in the works. Flatt remains Chairman, and BN CEO.

• Investments in partner managers are likely to slow but secondaries would be near the top of the list if something comes along.

BIP

• FFO $2.6bn, $3.32 per unit, up 10% lfl. Distribution up 6%, 17th year over 5%. Payout 66%.

• Sold $3.1bn, invested $2.2bn including $1.5bn inorganic, completed $16bn of financings.

• On the NYSE, BIP has delivered 14% total returns since inception; higher for BIPC and on the TSX.

• 3 D’s “are driving an infrastructure investment super cycle that is broadening in both scope and scale”.

• Backlog is $3.9bn for Intel and $5.3bn for everything else. Intel comes online late this year; the rest commissions at a rate of $1.5-2bn per year. Should support a return to 10%+ FFO growth.

• Step change in data business in 2025.

  • More to come in 2026, with significant take-or-pay contracts signed on existing capacity, high-return densification projects, and lease-up of their land bank for development.

  • Develop datacentres at 9-10% yield on cost, and sell for 5.5-6%. Development leverage is 70% so this translates to high teens RoEs, or in the 20’s when everything goes right.

• Agreed to sell 1 of their 4 Brazilian transmission concessions for $150m net to BIP, a 45% IRR, and an 8x MM. Will close 1q26.

• A more pro-market energy policy for Alberta could boost their Midstream business.

• Issuing equity in BPIC to buy back BIP 1-1.

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BBU

• FY LFL ebitda up 5% to $2.1bn. EFO $1.2bn.

  • Sold $2bn, repaid $1bn of corporate borrowing, bought 4 new investments for $700m, and repurchased $235m of stock at $26 per share, a 50% discount to their view of fair value.

  • $20bn of refinancings at a 50bp cost saving, with spreads very tight.

• Have always focused on improving businesses. Two things make that even more important now: deglobalisation requires capital and change management, and AI beneficiaries will be those who can implement it. “This is the environment we were built for.”

• Clarios: 30% of NAV. Ebitda is up 40% since they bought it, or $700m, can repeat this over the next 5 years with investment in advanced batteries, and enhanced recycling and critical mineral recovery. Will generate $5bn of FCF over that time before tax credits, more than the $4.5bn 2025 up-financing.

• Nielsen margins are up 350bps since acquisition on $800m of cost savings.

• Evaluating IPO’ing BRK - window seems to be opening and the business is derisked and growing strongly.

• New investments

  • Fosber: equipment for corrugated packaging industry, 2/3rds aftermarket with high cost of downtime, carve-out at 10x ebitda, clear opportunities to improve performance.

  • First National: Canadian resi mortgages, asset light, $160bn of mortgages under administration.

  • Chemelex, heat management equipment, aftermarket, carve out at 11x ebitda, opportunities to improve margins.

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BEP

• 4q FFOPU $0.51, +14%. Raising dividend 5%, 15th year in a row.

• FY FFOPU $2.01, +10%.

  • Deployed or committed $8.9bn ($1.9bn net), sold $4.5bn ($1.3bn net) for 2.4x invested capital and returns above target, financed $37bn.

  • Issued $450m of 10-year debt in March 2025.

  • Raised $650m of new equity in November.

  • Issued CAD500m of 30-year debt in Jan 2026 at 5.2% and their lowest spread ever.

• “It is now clear that power is a strategic priority around the world and is the bottleneck to growth for both governments and corporates”, driven by electrification, industrial growth, and AI, not just replacing fossil fuels as it was a few years ago.

• Capital is an increasingly important competitive advantage and the environment for acquiring development assets is very attractive. Listed assets, carve outs from utilities, and “lower quality” developers lacking capital and operating scale but with big pipelines are particularly attractive.

• Sales proceeds will become more programmatic/recurring as they scale. Have already agreed an $860m ($210m net) sale in 2026 and a framework for future asset sales up to $1.5bn to the same buyer. Expect to sign more of these frameworks soon. They derisk capital recycling and speed up the time from development completion to sale. “I will go out on a limb and say I think this is going to be a huge differentiator for our franchise”.

• By asset type

  • Solar and onshore wind are low-cost and fast to market. Scaling development capacity from 8Gw in 2025 to 10Gw in 2027. US permitting for solar is accelerating; for onshore wind it is slowing somewhat, but still happening.

  • Have not done much offshore wind but opportunities are growing in Europe. Might include end-of contract assets than can be bought assuming merchant economics and then re-contracted.

  • “The value of hydro is being recognized more than ever before.”

  • Westinghouse: US govt commitment “provides long-term demand certainty, helping unlock supply chain investment”.

  • Battery costs are down 95% since 2010 and 60% over 2 years. In addition, over the last 2-3 years revenue models have switched from merchant to take-or-pay. Batteries are the fastest growing part of BEP today. Neoen was the largest acquisition in BEP history and included a large battery pipeline.

• Will issue of $400m BEPC shares to repurchase BEP LP units for a net reduction.

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Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

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Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

Trades

Quite a lot of activity this month as my energy positions outperformed the rest and I recycled some capital. These were mostly small trades.

• Reduced Transocean, bought more Howard Hughes, bought more Pershing Square.

• Bought Saga Plc.

• Sold Noble.

• Bought more Ashmore.

• Sold Cheniere.

• Reduced Peyto.

• Bought more Blackstone, KKR, and Apollo.

• Bought more Ashmore.

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Articles

• Howard Hughes Holdings review.

• Brookfield investor day summaries.

• Uber review.

• Vail Resorts first look.

• Cheniere Energy review.

What I found interesting this month

• LongYield on Alibaba.

• Grow or Die on Uber.

• Cayucos Capital on Jardine Matheson.

• Future Cognitive Capital on Microsoft.

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Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

What it does: real estate company becoming a diversified holding company.

Elevator pitch: very long term real estate assets are starting to generate cash. One of this generation’s great investors is deploying it. This combination might make a unique compounding vehicle.

Mental model: moat, value (read about my mental models here).

Valuation and potential returns: potential 3x in 5 years.

Exchange and ticker: NYSE, HHH.

Stock price and market cap: $63, $3.8bn.

Do I own it? Yes.

IR website: here.

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

Introduction and: why now?

Howard Hughes stock has gone absolutely nowhere for 15 years. Why should the next 15 be any different? The answer is simple. The company is starting to generate quite a lot of cash, and will likely do so for decades, and they’ve come up with a very interesting way to reinvest it.

HHH’s core business is in real estate - specifically, Master Planned Communities (MPCs). These assets often take 50-60 years to build out. They consume cash initially but as revenues rise and investment falls they pass a cash flow tipping point. HHH’s MPC business is past the tipping point and is starting to generate significant amounts of cash: I estimate about 50% of the $5.6bn GAV (gross asset value) will be sold within 10 years and 80% within 20 years. The problem is, there are only a few good MPCs nationally, so reinvesting cash into new MPCs can only be done opportunistically - it’s not a strategy.

So what to do with the cash? The obvious answer would be opportunistic buybacks and dividends, with the balance between the two determined by how fully valued the stock is. And right now that would be a good answer, because management insists the stock is undervalued. But it’s not a great long term strategy: eventually the stock will be fully valued, and while dividends return value to shareholders, they don’t create it.

Enter Bill Ackman’s Pershing Square Capital Management. Pershing has been involved with HHH for years, and in 2025, HHH hired Pershing Square to build a diversified holding company. This is riskier than the buybacks and dividends strategy, but if done well will create more value, because it means HHH has a very long reinvestment runway. It can now invest its cash into:

1. Buying a portfolio of minority stakes in listed companies for value. This runway is not all that long if it is done on HHH’s balance sheet - eventually they’d be classified as an investment holding company, which would bring a regulatory burden they don’t want. However by buying an insurance company and putting the minority positions onto the insureco balance sheet, HHH can redeploy any amount of MPC profits into this portfolio.

2. Buying control positions in private businesses.

As part of the deal, PSCM injected $900m of new capital into HHH by purchasing common stock at $100 per share. This cash will help fund the acquisition of Vantage, an insurance company. The balance of the investment will be funded by Vantage preferred stock issued to Pershing Square Holdings (PSH). Vantage’s shareholder equity will be invested into a portfolio of common stocks similar to Pershing’s existing portfolios. Future MPC cash flows will be used to pay down the Vantage prefs, and once that is done they will be invested into either control positions in high-quality private businesses or into additional insurance company equity (and therefore listed stocks), depending on where the best opportunities are. The structure looks like this:

This strategy looks incredible on paper, and might actually work. Pershing Square’s investing credentials are clear. But it will not be easy: a lot comes down to Pershing Square’s execution, and whether they are worth their fat fee.

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Valuation

The table below shows my sum of the parts (SOTP) for today, which I think serves as a reasonable bear case, and a bull case for 2030. The column in-between shows cash flow for each segment, which builds up to the 2030 cash balance. Figures are in millions of dollars.

Let’s dive into the detail.

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Insurance

In December 2025, Howard Hughes announced the acquisition of an insurer named Vantage, which was founded in 2020 by Carlyle, Hellman & Friedman, and the founding management team.

Insurers make two types of profit (or loss). First, insurers try to charge more in premiums than they pay out in eventual claims. And second, in between collecting the premium and paying the claim, they invest their customers’ money - called float - and keep the returns.

There are two broad strategies in insurance. One is to underwrite programmatically, selling large volumes of less profitable insurance business. This results in high leverage (measured as premiums/equity and assets/equity) and as a result, regulators insist that the assets are invested conservatively. Weak insurance profits and conservative investing produce mediocre returns on assets, but the leverage helps turn this into an adequate return on equity.

The second strategy is to write less insurance, being pickier about the risks taken and the prices offered. This results in higher margins, and also in lower leverage, which has several advantages:

• It reduces the impact of investment volatility and adverse reserve developments on regulatory solvency.

• It gives flexibility to increase the volume of premiums written during periods of strong insurance pricing.

• It improves customer perception of counterparty risk. Customers want an insurer whose cheque always clears.

• It allows for optimised asset allocation.

It is this last point that can turn this type of insurer into a compounding machine. This second strategy was pioneered by a company you may have heard of: Berkshire Hathaway. The strategy lowers risks in two ways: it writes far less premium volume per dollar of equity than most insurers, and as a result has lower assets/equity; and it invests its float (i.e. its loss reserves) in cash and short-term Treasurys with little to no duration or credit risk. Because it takes so little risk, regulators allow it to invest its shareholder equity into a portfolio of common stocks. The combined returns from insurance margin, plus interest on float, plus returns on well-selected common stocks, achieved with low leverage and risk, have been the stuff of investing legend - and that is what HHH and Pershing want to replicate with Vantage.

Prior attempts to “replicate Berkshire” by hedge fund managers have not worked. Pershing argue that these were structured principally as financing vehicles, designed to boost funds under management for the fund managers. By contrast, Pershing will charge HHH a fee on its market cap, but they will not charge Vantage a fee for managing its investment portfolio. Their incentive is therefore to create value, not to write additional premiums to increase float and therefore fees for the investment manager, regardless of the insurance returns. Indeed, HHH have been explicit that Vantage will not have any top-down goals for premium volumes: premiums will only be written when the business is judged to be profitable. I think there is a second difference, too. Hedge funds run long/short books, where the longs are typically high turnover and the shorts have uncapped downside that can destroy a fund if they are wrong. There is no fundamental reason why hedge funds should compound - it is all down to the skill/luck of the manager. But Pershing is no longer really a hedge fund. They invest long-only and long term in some of the largest, fastest-growing, deepest-moat companies on earth. While Pershing have an exceptional record of outperforming broader markets, a lot of the compounding simply comes from the holdings themselves.

Because Vantage plans to run with low leverage, float invested in Treasurys, and equity invested in common stock, we can split the valuation into two parts:

1. The insurance part, which includes selling insurance, paying claims, and interest on float.

2. The investment part, which is the common stock portfolio.

This is not how most analysts would do it. Most would include the interest on float in the investment bucket, and would then calculate an ROE for the whole company. However, the interest on float is directly related to the amount of insurance written. It is a core part of insurance profits, whereas the returns from investing equity into common stocks is not. The advantage of doing it my way is that we can value the common stock portfolio at market prices and then value the insurance operation standalone.

Why market prices for the common stock portfolio? Because it is easily replicable. Pershing Square have said that Vantage’s common stock portfolio will be transparent and invested similarly to their existing portfolios, in liquid stocks of large companies. This means the portfolio is easy to replicate, and should not be valued higher than market prices even if the returns are spectacular. Pershing disagree with this logic, arguing that it is impossible to replicate the exact timing of their trades, the exact weights in their portfolio, or their occasional highly asymmetric hedges. This is true, but it is clear from the valuation of Pershing Square Holdings, which trades at a persistent discount to NAV, that the market does not see things this way. (Equally, the Vantage portfolio does not deserve to trade at a discount - the PSH discount is justified by fees, which Vantage does not pay.)

Valuing the standalone insurance operation is trickier. Vantage is currently making a 97% combined ratio. This is what most industries would call a 3% EBIT margin: it means that for every $100 Vantage collects in premiums, it pays out 97% in claims and operating costs. Believe it or not, this is actually pretty good: insurance is a commoditised industry and margins are thin.

HHH say that Vantage’s combined ratio will improve over time. They argue that while its loss ratio is good, its expense ratio is not. This is because it is a young business that has not yet achieved scale, so it is not yet fully leveraging its roughly $350m in fixed operating costs. As it grows, its combined (loss + expense) ratio should improve further.

Unfortunately, HHH have acquired Vantage at the end of a long insurance upcycle. Because insurance is commoditised, it is also cyclical. When profits are available, capital enters the market, pushing prices down. When losses are made, capital exits the market, pushing prices up. The key drivers of these cycles are catastrophe losses and interest rates. When (for example) a hurricane wipes out capital in the insurance industry, prices (at least in relevant lines of insurance) are likely to rise. And when interest rates rise (or fall), capital seeking the best risk-adjusted returns leaves (or enters) insurance.

The increase in interest rates after covid, combined with various catastrophe losses, drove a hard market (upcycle) in insurance pricing from roughly 2021-2025. That hard market is now softening. This makes it harder for insurers to write profitable insurance, and is likely to pressure both premium growth and combined ratios across the industry.

The following table shows two possible valuation scenarios for Vantage. Both assume $1.5bn in shareholder equity, 2x assets/equity, and $350m in operating expenses, which is roughly right for 2q26 according to the deal deck and commentary. The scenarios are:

1. Vantage writes fewer premiums at a higher loss ratio and achieves zero insurance profit.

2. Vantage writes more premiums at a lower loss ratio and achieves insurance net profit equal to 5% of shareholder’s equity.

This allows us to frame Vantage’s valuation quite simply.

If Vantage’s shareholder’s equity is invested in common stocks, and we are valuing this portfolio at market price, then we are going to pay 1x shareholder’s equity for the common stock portfolio.

In addition, we are going to pay 10x insurance earnings. 10x is a 10% earnings yield, and if you add inflation you get a low-teens total nominal return. That seems fair for a commoditised business.

For now, while I wait to see how the cycle unfolds and whether Vantage is a good underwriter, I will use Scenario 1 and assume insurance profits are $0. My SOTP today therefore only values Vantage at 1x equity for its common stock portfolio. However if Vantage proves its worth then the insurance operation could easily produce a return on equity of 5%. At 10x, that justifies another 0.5x equity for a total multiple of 1.5x, which is what I use for my 2030 SOTP.

The magic of this model is that it might well produce 20% or 25% compounded returns. Pershing Square say they aim for 20% returns on their common stock investments, and insurance could easily add 5%. This is why excellent insurer-investors like Berkshire Hathaway and Fairfax Financial have produced such exceptional compounded track records over time. Before acquiring Vantage, HHH produced this useful table showing how common stock returns and combined ratios drive compounding (the underlying assumptions about leverage and asset allocation are broadly similar to mine):

Four final thoughts on insurance:

• Remember: the common stock portfolio is replicable, so even if it does produce a 20% return, it should not be valued at more than 1x. That’s why I structure the valuation as 1x common stocks + 10x insurance ROE, rather than 10x total ROE.

• This valuation includes nothing for AdVantage, which deploys 3rd party capital into insurance policies underwritten by Vantage. This effectively allows Vantage to monetise its underwriting skills via a fee-stream, rather than just by writing policies backed by its own capital. This is very valuable in upcycles but less so in downcycles, and I don’t want to ascribe value to it until we have seen how it performs through cycles.

• The big risk not captured in my valuation is if Vantage have dramatically underestimated future claims. In this case shareholder’s equity will be overestimated, since it will be used to pay claims. What gives me some comfort here is that virtually all of Vantage’s book has been written during a hard market which offered good pricing. I can’t guarantee it, but there really shouldn’t be systemic problems in the insurance book.

• HHH have said that post-close, they will invest more primary equity into Vantage to de-lever the balance sheet and reduce the effective purchase price (since primary capital will go in at 1x p/bv). I don’t model this because I don’t know the amount, but it doesn’t really change my valuation - the cash merely moves from one of HHH’s pockets to another.

Master Planned Communities
These are large plots of land that are steadily sold to build new suburbs. Howard Hughes adds value by securing permits for long term development plans, building basic infrastructure, building commercial real estate, and controlling supply to maximise profits over time. As these communities mature, the price of land for homes rises dramatically. Development can take decades, with negative cash flow initially and very strong cash flow at the end, when the infrastructure is complete and land values are high.

I like this business. It makes intuitive sense to me that by investing early in a place people are likely to want to move to, investing to improve the area, curating a lovely place to live and work, and monopolising the supply of land with a long term value-maximisation mindset, it is possible to make good returns. Howard Hughes’ MPCs are in affordable areas with low taxes and excellent demographics, and land values are rising steadily:

75% of current MPC profits come from Summerlin (22,500 total gross acres along the western rim of the Las Vegas Valley) which opened in 1990, and another 22% from Bridgeland (11,500 total gross acres in Houston) which opened in 2010. The other MPCs are The Woodlands and Woodlands Hills (Houston) which are smaller but are scheduled to ramp profits over the next few years, and Teravalis (33,800 total gross acres in Greater Phoenix, Arizona), which only started in 2024 and is targeted for completion in 2086. In maturity terms Teravalis is the baby of the portfolio, but it is a very big baby.

HHH give us 3 ways to think about valuing the MPC business. The first two are earnings before tax (EBT), which is a P&L measure, and MPC Net Contribution, which is a cashflow measure. To get from EBT to Net Contribution, the big adjustments are that

1. Cost of sales is added back. This is what HHH paid to buy the land, so it is a noncash charge in the current period.

2. Proceeds from MUD and SID bond collections and sales are added back. These are bonds issued by municipalities to HHH to subsidise some of the development expenditures.

3. MPC development expenditures are deducted - this is the investment to make the land saleable (some of which earns MUD and SID bonds which can be collected or sold in future periods).

The following table shows EBT and Net Contribution. Net Contribution has lagged EBT by an average of $75m per year over the last 4 years due to MPC development expenditures. Eventually, Net Contribution will exceed EBT as communities mature and less development spend is needed. We are not there yet, but it is clear that profits and cash flows are growing and guidance is for that to continue, although 2025 was a bumper year on the sale of a particularly large plot in Summerlin so there is a step down in 2026:

I assume that MPC Net Contribution averages $400m per year over the next 5 years. For the purposes of my 2030 valuation, this means $2bn gets deducted from the MPC valuation and added to the holdco cash balance.

The third valuation measure is Gross Asset Value (GAV), which is a discounted cash flow. The table below shows % of GAV and planned sell out dates for each of the MPCs. By 2036, all of Bridgeland residential and The Woodlands, and Woodlands Hills will have been sold, along with perhaps half of Summerlin. That accounts for around 50% of today’s GAV. By 2046, Bridgeland commercial, Summerlin, and some Teravalis will have been sold, accounting for another ~35% of today’s GAV. By MPC standards, these timeframes are short: we are well into the monetisation phase. This data is from September 2024, which is the last breakdown of GAV that I can find:

The most recent GAV is $4.4bn, from 4q25. This excludes Teravalis because it is from a slide showing GAV growth excluding the acquisition of Teravalis in 2021. Teravalis (including Floreo) had a GAV of $944m 18 months ago. Given the high discount rates on these assets, their GAV is likely $1.2bn today, making a total YE25 GAV of $5.6bn. The segment also has a little over $400m in net cash, but this includes $400m of MUDs. HHH has a habit of selling MUDs at discounts of 20-25%, so I reduce segment net cash by $100m. MPC NAV is therefore $5.6bn + $0.3bn = $5.9bn today.

Should we trust a company-provided GAV? As you might expect, the key inputs to the DCF are aggressive, but defensible:

• Commercial land price growth rate 3.5%, fractionally above probable inflation as population density rises.

• Residential land price growth rate between 5% and 7% depending on the asset. This is in-line with historical data.

• Discount rates of 7-9% for the more mature assets, 15% for Floreo, and 20% for Teravalis. The weighted average in 2024 was 9.6% and this will rise slowly as Floreo and Teravalis grow in the mix.

• Cash margins between 75% and 97% - selling land you already own is a very cash generative business!

If I was going to question one assumption, it is the 7% residential price growth rate at Summerlin. This asset accounts for a large part of the overall GAV, and while 7% is in-line with historic performance, extrapolating it for the 17 years until sales are complete is not cautious. Offsetting this is the fact that Teravalis, a monster asset, is discounted at 20%; if it works out it will drive huge GAV upside. In fact, GAV is likely to rise despite accelerating land sales. At 20%, the Teravalis GAV will be $7.4bn in 10 years if everything goes to plan. That exceeds the GAV of all the MPCs today.

Overall I think the GAV HHH provide represents a full, but not crazy, valuation for the MPC segment.

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Strategic Developments

This segment develops high-rise condos for sale. The majority of what it is building is at Ward Village in Hawaii, but it is also building the Ritz Carlton Residences, an ultra-luxury condo development in The Woodlands, which might become a template for further developments in the MPCs.

Earnings from Strategic Developments are lumpy. It takes 3-4 years to sell a tower, and the profit is booked at the end; on top of that, a couple of the Ward Village towers are affordable homes sold at cost. That’s why HHH booked $282m of segment EBT in 2024, when it had a high-value tower to sell, and -$14m in 2025, when it had an affordable tower to sell.

Nevertheless, the economics of Strategic Developments are attractive. Most of the towers are pre-sold, which reduces risk. Between deposits and construction loans, HHH has to put up very little equity to get a tower built. They have a decent record of delivering towers on-budget. And they already own the land, so the cash margins are decent. HHH guide to a 25-30% gross profit on sales. After net interest, I estimate 15% pretax margins and 12% net. That’s in Hawaii, where construction costs are high, because labour is tight and materials have to be shipped.

HHH has already delivered 8 towers at Ward Village, 2 of them affordable. It has 2 more under construction and 3 in pre-development. These last 5 are 71% sold on average with $3.5bn in revenue already under contract, which implies $4.9bn in total eventual revenues. In practice revenues will probably be slightly higher, since the final units usually go for the highest price.

The Ritz Carlton Residences are 76% pre-sold with $37m in deposits taken and $380m of revenue under contract, implying total sales of $500m. Working through build cost and likely interest profile I think net margins are likely to be slightly higher here - I assume 15%.

All of these developments will be complete by 2030. $5bn in revenues at 12% and $500m at 15% implies $675m in net profit over 5 years. I discount this to $500m for today’s valuation.

For the 2030 valuation, two things are relevant. First, in early 2025, entitlement changes at Ward Village made another 2.5-3.5 million square feet of development possible after 2030. That’s at least equivalent to the 5 towers currently in development and pre-development. Second, the success of the Ritz Carlton Residences, which generated $250m in future sales in their first week of marketing, is something that HHH might be able to replicate as they build out their MPCs. I therefore assume Strategic Developments, having generated $675m of cash flow between 2026 and 2030, is still worth $500m at the end of 2030.

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Operating Assets

This segment owns commercial real estate that Howard Hughes has built in its MPCs. These assets generate rent, but they also make the communities better, which drives residential land price inflation - so while this segment should be valued on its rental profits alone, a significant part of the return on investment from building these assets turns up in MPC segment profits.

The key metric for this segment is net operating income (NOI). This is rental income less cash operating expenses - effectively ebitda for real estate. It’s worth noting that once interest and depreciation are deducted the segment produces slightly negative EBT. One way to think about this is that the value is effectively in the depreciation (which generates cash flow and shields the business from tax) and the underlying land, with an option on the true asset life being longer than that assumed for depreciation purposes.

Roughly half of the NOI is from office, and the other half is a mix of retail, commercial, and multi-family. There is obviously debate about what assets like this are worth, especially office. My view is these are advantaged assets because they are located in thriving, growing residential communities and because Howard Hughes controls nearly all the commercial real estate in their MPCs. They rarely sell, and nobody else can build without their permission, so there is little risk of speculative overbuild. The downside is that HHH cannot sell a controlling stake, at least not until the MPCs are complete, although they have speculated that they could sell a minority stake in Operating Assets which would set a valuation marker and produce cash for reinvestment.

HHH reported $276m of operating asset NOI in 2025, and the company says stabilised NOI for existing assets and those under development will be $361m, with the vast majority of the uplift coming from existing assets that are not yet mature. The company does not say when stabilised NOI will be achieved, but the asset-by-asset disclosures suggest that it should take 3-5 years. For today’s valuation I assume the $262m in 2025 NOI is capitalised at 8%, and for the 2030 valuation I capitalise the $361m in stabilised NOI at 7%, on the basis that more mature assets in more mature communities should be worth more.

Notably, neither valuation assumes any franchise value in Operating Assets - yet it is highly likely HHH will continue to create value by building new assets.

Roughly, segment NOI less depreciation and interest is zero. With no EBT, there should be no income tax to pay. I therefore assume segment free cash flow (FCF) is equal to depreciation - roughly $170m per year - and add 5x$170m in cash flow from Operating Assets to the 2030 cash balance, less $30m for additional equity needed to complete assets under construction. I do not grow FCF with NOI, which should be conservative. In addition, I model 2030 segment net debt at 62% LTV (the company guides to 60-65%). The increase in debt from $2.5bn today generates an additional $689m of cash for HHH.

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Holdco debt

HHH break out debt by segment in the 10k. There is $2.04bn of debt at the holdco level. The Vantage deal will cost $2.1bn, and HHH had $1.28bn of cash at the holdco level at YE25. I assume $1.2bn of this is spent, and therefore $0.9bn of Vantage prefs will be issued to PSH, for a total of $2.94bn in holdco debt and prefs by mid-2026.

Some notes:

• HHH claim the MPCs are unencumbered; I think this is wrong: both the Operating Assets and Strategic Developments carry as much debt as they can bear. The MPC segment has very little, but the holdco has quite a lot. In effect, the MPC debt is simply at the holdco level.

• The debt is well-structured: in terms of interest rates, 96% is fixed or swapped or capped, and after a $1bn bond issue in February 2026, ~60% is due after 2030.

• HHH has the option to buy back the Vantage pref at a price linked to the growth in Vantage shareholder’s equity. I assume these prefs are repaid in 3 equal annual instalments (consistent with guidance) and grow the balance by 15% per year because I assume Vantage shareholders’ equity grows at this rate for my 2030 valuation.

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Overheads

HHH guide to $82-92m in overheads in 2026. I assume $90m and capitalise this at 10x. I also assume overheads inflate at 3% per year, which feeds into my cash projection and my capitalised overheads figure for 2030.

Overheads includes the fixed component of the Pershing Square fee, which is $15m per year inflated by the Personal Consumption (PCE) index.

A couple of key items are not included in overheads:

• Deal fees, which could be significant if HHH pursues a lot of deals.

• Stock based comp. I prefer to think about this in terms of potential dilution rather than the Black Scholes based P&L measure. There are 59m shares outstanding. No options were issued in 2025 and at year end there were 68k options outstanding, so options don’t represent a big dilution risk. 300k RSU’s were issued in 2025 at an exercise price of $77. Assuming RSU issuance continues at this pace and all are exercised, shareholders will suffer 0.5% dilution per year. I can live with that, especially considering Pershing has an incentive to keep stock based comp within sensible bounds (see below).

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Performance fees - and Pershing Square’s alignment with minority shareholders

Overheads does not include the variable part of the Pershing fee, which is dependent on the share price. Specifically, Pershing gets 1.5% of the market cap over a threshold. The threshold is calculated by multiplying a fixed share count of 59.4m by a reference share price of $66.15, which inflates with the PCE index. In effect, Pershing can only increase its fee by increasing the share price above inflation. And notably, Pershing:

• cannot increase its fee by causing HHH to issue more shares.

• can increase its fee by causing HHH to buy back shares below intrinsic value, if doing so increases the share price.

I think HHH directors did an extremely poor job of negotiating the reference price. HHH has argued for years that their real estate business is worth over $100, but now HHH will pay a fee for any share price increases above $66. If the market merely comes to agree with HHH about the value of the real estate business, Pershing will collect a performance fee. That is not right. The reference share price should have been at least the $100 that Pershing themselves paid to inject new capital into HHH in 2025, and ideally $118, which was the NAV that HHH published in 2024 - and even this would have ignored NAV accretion in 2025.

However annoying this is, the fact is that the reference price is $66, and we must assess value on that basis. For me, the key is that there is strong alignment between Pershing and minority investors:

• the variable fee clearly incentivises Pershing to increase the share price significantly and sustainably ahead of inflation.

• the fixing of the reference share count incentivises Pershing to make (or influence the HHH board to make) shareholder-oriented decisions around share issuance, buybacks, and stock-based comp.

• PSH and PSCM between them own 47% of HHH. Ackman and his team own 90% of PSCM and 27% of PSH. Indirectly, they own a lot of HHH. They want the share price to compound.

• HHH is reputationally deeply significant for Ackman. He has often spoken of his admiration for Buffett and desire to build one of the great investment track records. To compound an insurance holding company for decades is to be compared to the Master. I doubt much motivates him more (except fees).

Pershing Square have several advantages over other fund managers. In particular, their assets under management is almost entirely permanent. Having managed both permanent and temporary capital, I can attest to the sad fact that capital duration affects manager psychology. It is much easier to focus on the long term when you have permanent capital. In addition, Pershing’s ability to attract talent is significant and their analyst tenure is impressive, which speaks to the culture at the firm. Finally, their performance is phenomenal - the chart below shows gross performance, which is relevant to Vantage, since it does not pay fees:

In short, while I think the HHH directors have done minorities a disservice with the reference price, I think Pershing Square is an excellent and aligned partner.

For the variable fee, my SOTP assumes:

• $0 today, since the share price is below the reference price.

• A $120 share price on average over the next 5 years, driving a total cash outflow of $225m.

• That in 2030, the share price equals the NAV, maximising the variable fee, and that the fee is capitalised at 10x.

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Tax

Within my NAV, insurance, MPCs, and strategic developments are valued net of tax, and the operating assets make no earnings before tax so they pay no tax. I therefore do not capitalise future tax into the NAVs.

I do, however, deduct tax from the cash flows as follows: $400m in MPC EBT, less approximately $225m in holdco costs and interest, gives $175m in taxable profits each year, at a 22% rate.

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Holdco cash

YE25 holdco cash was $1.28bn and I assume $1.2bn is used for the Vantage acquisition, so my starting holdco cash balance is $80m.

I exclude restricted cash. This is mostly condo deposits so including it risks double counting cash flow from Strategic Developments.

I then add the cash flows from each of the segments over the next 5 years to get to the 2030 cash balance. The striking possibility is that even after buying Vantage, HHH might have $1.7bn to deploy into new acquisitions over the next 5 years, before considering leverage.

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Conclusion

First, a confession. HHH is a complex beast, with 4 quite different businesses and an unusual partnership and fee stream to consider. In addition, while the company produces a lot of disclosure, it isn’t presented as clearly or as consistently as I would like. To research HHH is to make multiple choices about what matters, and what does not; what merits more time, and what does not. I may well have missed things, and I apologise if I did.

As I write HHH trades at $63 per share. Recall that HHH thought their NAV was $118 per share in 2024 and Pershing paid $100 per share in 2025. According to my maths:

1. The stock has 36% upside to my current SOTP.

2. The stock has ~200% upside of 204% to my 2030 SOTP, a CAGR of 25%.

Here’s a reminder of my SOTP:

And here is a summary of the assumptions:

I don’t expect the stock to rise 36% to its current NAV any time soon. It has traded at a discount for years. But I do think the 2030 NAV is realistic. Not conservative, perhaps, but realistic. I assume good performance from each of the assets, but not spectacular. Vantage shareholders’ equity could easily compound faster than 15%. MPC NAV might not beat my assumption, but with 50% of today’s GAV being sold in the next 10 years the duration of the cash flows will shorten considerably, reducing risk and helping the stock trade closer to intrinsic value. I assume operating assets reach their guided stabilised NOI, but not that any more assets are built. I assume future strategic developments achieve similar economics to current ones, not better, and that the Ritz Carlton Residences success can’t be replicated elsewhere in the MPCs. And I assume $1.7bn of accumulated cash sits on the balance sheet, undeployed.

My standard hurdle for investments is 15%, which compounded is a double in 5 years. Here we can buy a solid set of assets, trading at a discount to a relatively conservative current NAV, with realistic line of sight on making 3x our money over 5 years and compounding after that, because MPC GAV will continue to grow and because HHH now has a virtually infinite reinvestment runway.

Could things go wrong? Could the Vantage balance sheet be littered with huge unforeseen claims? Could the MPCs suddenly lose momentum, perhaps because of large unforeseen demographic shifts? Yes. Of course. But investing is about embracing uncertainty, deciding what risks you want to take, and ensuring you are being paid to take them. On that basis, I am happy owning HHH at $63 per share.

Links to previous work

1. IRSA

2. Brookfield

3. Cheniere

4. Uber

5. My notes

Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

Here are my summaries of the last Brookfield investor day transcripts. I hope they’re useful.

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

BN - real estate and Wealth Management are huge opportunities

• 19% CAGR over 30 years, or 27x.

• Plan value today is $180bn or $68 per share. This is 16x average annual earnings over the next 5y and 10x average annual DE.

  • “I’m quite confident we can sell all the businesses for probably premiums to those numbers.”

  • $82bn is public holdings.

  • $12bn is funds managed by BAM, compounding at 15%. Will realise net $5bn over 5 years.

  • $34bn is PV of carry, valued as net unrealised carry + annual targeted carry x10. (They also do a DCF which produces the same result at an 8.5% discount rate.) They’ll convert $6bn to cash over the next 3 years and $25bn over the next 10, net.

  • $26bn is real estate.

  • $26bn is BWS at 15x annualised DE.

  • Expect 25% DE and 16% plan value CAGR for next 5 years.

  • 5y DEPS target $6.95.

• Will generate $53bn of cash flow over the next 5 years, I think including asset sales. $28bn will go to dividends and to grow BWS, $25bn is free to be reinvested.

• Generating 15% returns is easier than it was due to scale and capabilities.

• Nimble within two guiderails: value investing, and driving returns through operating capabilities.

• “Once we understand an industry, we move fast and we deploy at scale. We’re not early, but once we understand it, we move fast and we deploy at scale.”

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• Real estate

  • Sold $5bn of balance sheet assets over the last year and refinanced $16bn.

  • Plan value $26bn and DE $730bn. Will sell $24bn over the next 5 years, reinvest $10bn, and generate $3bn in annual dividends, leaving 2030 plan value $15bn and DE $640m.

  • In the last year, balance sheet investments have signed 15msf of leases at 11% rental spreads. This will drive NOI over the next 2 years as leases roll. 5y NOI LFL CAGR should be 4%.

  • Now splitting assets into 3:

    • Super-core is 60% of invested equity. 34 irreplaceable and complex assets that they can keep reinvesting in and will own forever (but may sell stakes). 90% of this is office and retail with 95% occupancy and 47% LTV. 10% is resi and mixed use.

    • Core-plus is 25% of invested equity. 57 assets of equal quality to supercore, but with business plans that are complete or being completed and which will be sold. The performance metrics are almost identical to supercore: 27 office assets have 44% LTV and 94% occupancy.

    • Value add is 15% of invested equity. 95 assets generally in secondary markets where the plan is to reposition and sell.

  • Office: 2 years ago only 5% of companies required employees to be in the office all the time. Now it’s over 50%. 2 years ago the average work requirement was 2.5 days per week. Now it is almost 4 days. But nothing has been built for years, and existing supply is being converted to other uses. Very little space is available for new leases, so the premium for new office space averages 60% globally. In NYC it is over 100%.

  • Retail is driven by consumer spending. US retail spending is 140% of 2019 levels but there is virtually no retail construction - since 2015, US retail construction has focused on convenience and not shopping destinations. “This directly impacts retailers who are starved for more space.”

    • Alderwood Mall in Washington is 99% occupied with NOI up 50% since 2021. They’ve just refinanced at 5.9%, having recently redeveloped an old Sears box into 76ksf of retail space plus 328 apartments. The new retail space is 100% leased and generates $4m of NOI, while the apartments are 96% leased and have just been sold at a 4.7% cap rate.

    • Fashion Place in Salt Lake City is 100% leased and generates $1000psf in sales. Replacing underperforming brands has driven sales up 20% since 2021 and they have just refinanced at 5.4%.

  • Flatt: “I’ve seen [this cycle] 5 times before. The psyche got hurt more this time, but the fundamentals are actually way, way better as we come out of the bottom of the market”.

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• Brookfield Wealth Solutions

  • $135bn of assets, $14bn of equity, $1.7bn of DE ($2.1bn next year).

    • 3 big recent transactions have been at an average of 1.8x book, which implies $26bn of value or $20 per share of BN.

    • Also generates $300m of fees to BAM on $30bn of assets invested in funds.

    • Including the UK acquisition they will have $180bn of assets, $30-35bn of inflows, $10bn of outflows, and $20-25bn of net inflows. Add some M&A and they can reach $350bn of assets and $5.5bn of DE in 5 years, reaching a 17% ROE and valued at 12-15x.

  • “Investment-led insurance” - by investing in high-yielding private assets, you can have low leverage and lots of cash. This combination is great for risk, returns, and regulators. Most insurers operate at 10-20x leverage. Brookfield operate at 7-8x and they have $50bn of assets in cash or cash equivalents. All their businesses have A ratings and 2 have had upgrades under Brookfield ownership due to retained capital.

  • “We think we can build a business that can compound capital for many decades to come” driven by aging and Brookfield’s ability to invest at scale.

    • Today 1 in 6 Americans are over 65. By 2050, it’s 1 in 4. Same all over the developed world. This plus the lack of DB pensions drives a $7tn retirement deficit.

    • Aging drives demand for wealth products.

      • Pensions and Sovereigns is a $22tn market.

      • Today US retirement accounts have $40tn (401ks, IRAs, and employer DC accounts). By 2040 this will be $100tn.

      • 20 years ago 7% was in annuities; now 10%, and likely going to 15%.

      • Trump’s recent Executive Order opens retirement accounts to private assets.

    • Brookfield can offer high return private investments in the accumulation phase, and then competitive annuities for the decumulation phase.

  • Initially thought they would do this as a reinsurer and then realised the value of distribution. American National and American Equity previously did $5bn of annual annuity origination combined. Now they do $25bn with more to come - but they scale back when rates aren’t right.

  • Regulation is “an incredible moat”. They work hard with regulators “to make sure our disclosure is at the top end of their expectations and to default to overcommunication…the more we work with regulators, the more that moat widens and gives us protection and creates scarcity value”.

  • Massive value created by buying insurers at or below book, selling noncore lines for 1.6x, and then selling all their long dated bonds just before inflation took off.

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BAM

• FRE: $2.7bn today → 17% CAGR to $3.59/share by 2030.

  • DE: 18% CAGR. Base case 2x in 5 on $1.2tn FRE-bearing capital, “inherent operating leverage”, rapidly scaling complementary products.

  • Additional levers get to >20% DE growth.

  • Exceeded last 5-year plan: FRE-bearing capital $563bn vs $510bn target; FRE $2.7bn vs $2.6bn.

  • Carry drives growth after 2030.

  • 87% of fee-bearing capital is long-term or permanent in nature, growing to 92% by 2030 — structural earnings visibility most peers can’t match.

• Past 12 months: raised $97bn, deployed $135bn, monetised $75bn, returned $50bn - record monetisations despite low M&A volumes.

• Competitive position.

  • Owner-operator model, co-investment alignment, and boots-on-ground operational expertise are the core differentiators.

  • Scale creates a self-reinforcing loop — platform attracts capital, capital enables better deals, deals build the track record.

  • Brookfield capital goes in first, clients come alongside.

  • Cross-platform information advantage: Westinghouse underwritten because of renewables expertise; Canadian housing underwritten because of real estate presence; Chemelex surfaced because of infrastructure knowledge.

  • Compounding expertise from repetition - hundreds of renewables deals, deep infra experience.

• Growth levers

  • Products: >70% of fee revenue from strategies launched in the last decade. Lots more to come following the pattern flagship → complementary → retail.

  • Institutional share of wallet; although BAM is in 39 of the world’s top 50 investors, they only have 2% of their alts portfolio.

  • Partnerships: $40bn of go-forward deployment from bilateral partnerships announced in 2025 alone. Barclays partnership seeding financial infrastructure fund; sovereign AI partnerships seeding AI infrastructure fund. Partnerships are multi-dimensional — tenants, offtakers, pension managers, co-investors.

  • Individuals: private wealth raising $10bn this year, up 50% y/y. 60,000 private wealth clients vs zero 5 years ago. 401(k)/retirement markets are “early, early, early innings” this opening is not in their base case.

  • Europe institutional: expect to raise 3x 2024 levels in 2025 — “infancy.”

  • Family capital also barely started.

• Outlook by business segment

  • Infrastructure: massive multi-year investment need. Spinning out dedicated AI infrastructure fund, which is differentiated because half is yielding, not greenfield, with sovereign and hyperscaler counterparties on 20yr+ contracts. US data centre vacancy <2.5%; 10GW of lease capacity added in US this year alone.

  • Renewables & Transition franchise now generates >$400m annual revenue, built in <5 years from zero. Largest transition strategy globally.

  • Real Estate: — fundamentals strong, supply near-zero, capital structures normalising, transaction activity recovering and rate cuts will accelerate this. Sold $3.7bn, deployed $6bn in last 12 months. “Rents going through the roof” in next 5 years. Buying multifamily at 5.7% caps (vs historically selling at 3.7%), with pathway to >7%. 20‑yr opportunistic track record: 21% gross / 17% net on $44bn equity.

  • Private Equity: 26% average gross IRR over 25 years across 6 vintages — “best performing PE track record in the market.” Wealth, structured equity, and financial infrastructure products on the way.

  • Credit & Castlelake: $250bn FBC today vs $100bn 5 years ago. Private credit is still very early and asset-backed finance is “taking off.” Capital markets business growing — 2-3 years to materiality but credit growth could accelerate that significantly.

• AI and productivity

  • “Robotics and AI can soon change a lot of processes… margins will expand dramatically over time.”

  • “We are possibly in one of the greatest investment booms in history… leading to some of the greatest productivity advances we will ever see.”

• M&A: 7 meaningful additions in 5 years (Oaktree, LCM, 17Capital, Primary Wave, Pinegrove, Castlelake, Angel Oak). Options allow buying ~$250m of incremental FRE over time.

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BIP

• L5y FFO/unit CAGR 10%

  • L5y understated true performance: FX headwind cost ~2% annually; rate headwind cost 2-3%. Adjusted for both, underlying growth was ~14%.

  • Targeting return to 14%+ long-term rate over next 5 years.

  • Distributions: target higher end of 5-9% target range, without increasing payout ratio (currently 67%, down from 78%).

• 2025 to date: deployed $2.1bn ($700m organic, $1.4bn new investments); recycled $2.8bn at 20% IRR / 4x MOIC - annual record and “exceptional” given these were regulated/contracted assets. Already at $3bn recycling target. Private market transactions achieved 15x EV/EBITDA — 3-4 turns above where BIP trades publicly.

• Competitive position

  • Full-cycle strategy: deploy at 12-15% hurdle, crystallise value through recycling, maintain liquidity to go on offence in dislocations. COVID, rate shock, and the trade war produced some of BIP’s best acquisitions.

  • Cross-sector learning:

    • Intel semiconductor deal assembled from data centre contracting + LNG project finance + corporate partnership governance knowhow.

    • Hotwire identified as two businesses (development platform + stabilised portfolio) at signing - value not recognised by sellers.

  • 100% of new investments funded internally over last 3-4 years - recycling makes BIP self-funding.

  • Private market buyers paying 10-11% cost of equity for BIP’s mature assets; BIP redeploying into 15-17% returning opportunities - spread is core compounding engine.

• Growth levers

  • Organic backlog 4x larger than 5 years ago - highest-returning capital deployment.

  • Recycling program 5x larger, now $2-3bn annual run rate going forward.

  • AI infrastructure: $500m annual BIP deployment targeted.

  • Macro turning: rates stable/falling and USD softening for first time in years.

• AI buildout

  • 1-2% of US GDP, larger than the fiber build-out, approaching railroad-era scale, analogous to electric grid build-out in duration and necessity.

  • Power density per rack is 10x non-AI and forecast to rise 5-10x within 10y.

  • Data centre inventory sold out.

  • AI factories are DCs plus $30m/MW of chips - 4x the capital intensity of standard cloud.

• Recent acquisitions

  • Colonial Pipeline: largest US refined products system, 50% of East Coast demand, 5,500 miles Houston-NY, 9x EBITDA with FERC-regulated inflation-linked tariffs and 90%+ utilisation. Bought during trade war noise with limited competition. Upside from operational improvement.

  • Hotwire: bulk fibre to HOAs, immediately recycled stabilised assets to lower-cost capital. Growth via homebuilder partnerships and Brookfield ecosystem.

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BBU

• Adjusted EBITDA $2.7bn, 5y CAGR 16%.

  • EBITDA margins doubled from 12% to 24%.

  • Adjusted EFO/unit: $3.65 → $6.90.

  • NAV: $28 in 2020 → $54 today.

  • Capital recycling: $2bn target for 24 months achieved in 12; confident of another $2bn over next 24. The sale of 3 partial interests at an 8.6% discount to Brookfield’s evergreen fund, if reinvested in buybacks at market prices, adds $2.50 in NAV/unit.

• Long term record

  • 26% gross / 20% net IRR over 25 years, driven by margin expansion, not multiple expansion or financial engineering.

  • Since IPO: 25 investments monetised, $8bn of proceeds at BBU share, in line with carrying NAV and above target returns.

• Brookfield ecosystem ($1.1tn AUM, 400 companies, 30 countries) is the information advantage

  • Cross-portfolio best practices identified and deployed at scale.

  • AI use cases now live across 200+ applications; best practice in one company rolled to all 400.

  • AI value creation office: 30 dedicated people sharing lessons.

  • Buying industrial companies that benefit from AI as a productivity tool.

    • Clarios: custom ML algorithm on 30yr-old facility saved 60% more than expected, now rolling across all Clarios plants and comparable BBU businesses.

    • Sagen: ML models on 25 years of proprietary data — mortgage underwriting automation up 1.5x, better house price prediction, improved fraud detection.

• Financial infrastructure is a new priority vertical.

  • $4tn market opportunity.

  • Strategy: buy asset-light software and services businesses (not banks), unshackle them from conglomerate parent constraints, digitise/automate, and deploy operational expertise.

  • Target characteristics: scale, distribution, technology-enabled, regulatory moat.

  • Network + Magnati combined into #1 payments provider in Middle East/Africa, processing >60% of regional payments.

  • Barclays payments carve-out: building “the largest startup you can imagine” — 3,000 people, every process being rebuilt from scratch. Target: $200m EBITDA uplift.

  • Now have leading payment infrastructure in 60+ countries.

  • Ranjan: “we can quadruple the EBITDA of these businesses soon after buying them.”

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BEP

• FFO/unit: 10% organic annual growth. Building blocks:

  • inflation escalation (~2%, $150m incremental FFO over 5 years)

  • re-contracting at higher prices ($100m)

  • asset optimisation (1-2%)

  • development pipeline execution ($385m, ~5%).

• Competitive position

  • Only platform combining large-scale low-cost wind/solar with irreplaceable baseload — hydro, nuclear (Westinghouse), and now batteries (Neoen).

  • Hyperscalers need 99.999% availability; BEP can deliver both cheapest power and reliability, most peers can only do one.

  • Hydro: largest private portfolio globally. More strategic than ever - dispatchable, 24/7, scarce. Selectively recycling non-core assets (First Hydro UK, Maine portfolio) while reinvesting in core (increased Isagen stake). Google framework locks in long term contracted cash flows and enables up-financing; it is also is a “hunting licence” for US hydro M&A.

  • Nuclear: Westinghouse serves ~2/3 of world’s nuclear fleet, supplies ~half of all reactors globally = global scale + deep US expertise = ideal positioning for new builds, life extensions, and accelerating global investment. Still “very early stages of a long sustained investment cycle.”

  • Discipline as an edge: deliberately avoided offshore wind (subsidy-dependent, construction risk), residential solar (unproven economics), and highly leveraged structures.

  • “Clean portfolio, track record and balance sheet” entering the upswing. Highest credit rating in sector and financing terms improving - 10-year notes in March at lowest coupon in 5y, tightest spread in 20y.

• Growth drivers

  • Data centres alone drive 8-10% annual US power demand growth through 2050.

  • Deployment: $9-10bn over next 5 years across development and M&A - step up from prior targets.

  • Half is now proprietary organic development.

  • Target adding 10GW annually by 2027, sustained from there.

  • Capital recycling now a core, recurring part of the model. Each portfolio company now recycles assets as they mature. Target >$2bn of asset sales annually.

  • M&A: pipeline >$100bn enterprise value. BEP wins on certainty of capital and execution speed, not price. Renewables regulatory uncertainty in US market is creating attractive entry points. $25bn of partner capital available alongside BEP’s own $4.7bn - total equity firepower ~$30bn.

  • Batteries: costs down 90% since 2010, further declines expected. Neoen acquisition makes BEP global leader - 1.5GW operating, ~50GW development pipeline. Fastest-growing segment within BEP. Firms up intermittent renewables to meet reliability demands, particularly for datacenters.

  • Wind and solar development are nearly the entire pipeline in key data centre markets. Contracting activity with hyperscalers up ~100% in last 2 years. Microsoft and Google partnerships - only two such framework agreements in the industry.

  • Opportunity to consolidate distributed generation: smaller renewable assets, typically solar, sited close to or at a commercial or industrial customer’s premises, with the power contracted directly to that offtaker. These ease grid constraints and deliver cheap power.

• Capital recycling

  • Platforms: Saeta Yield, India platform, Luminace majority - 26% IRR, 2.6x MOIC.

  • Individual assets: First Hydro, Shepherd’s Flat, Maine hydros - 18% IRR, 3x MOIC.

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Links to previous work

1. IRSA

2. Brookfield

3. Cheniere

4. Uber

5. My notes

Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

What it does: Orchestrates mobility.

Elevator pitch: Uber is a dominant 3-sided network that allows customers to order transport and hamburgers.

Mental model: Scaler, moat, asymmetric payoff.

Valuation and potential returns: 30x non-GAAP net income, but potential to compound in the teens for 20 years.

Exchange and ticker: NYSE, UBER

Stock price and market cap: $78, $154bn.

Do I own it? Yes.

IR website: here.

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

Tl;dr

This is a thought piece about Uber’s TAM and competitive position in 10 and 20 years. The underlying product should become far cheaper and therefore the market far larger. Autonomous vehicle (AV) supply is likely to fragment, meaning many providers will need Uber to scale and compete. AI personal assistants might come to dominate demand, creating a risk of disintermediation, but there are strong practical and regulatory reasons why assistants will not bypass Uber. Uber should probably engineer its take rate down to help grow the market and reduce the risk of disintermediation, but even so there should be plenty of space for revenue growth and operating leverage. The resulting skew between more bearish and more bullish investor outcomes is attractive.

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Introduction

Investing requires a balance between attention to detail now and a broader, more general understanding of how the long term future might unfold. This piece attempts to imagine how Uber’s competitive moat might evolve over 10-20 years in the face of two interrelated threats: the growth of AV platforms, and disintermediation by AI.

For a more traditional introduction to Uber, packed with details on current market shares and financials, I recommend this by :

Hated Moats

Uber Technologies: Deep Dive Analysis

Overview & Positioning…

Read more

5 months ago · 43 likes · 5 comments

For long term investors in Uber, I think there are 5 things that really matter:

1. Potentially explosive growth in the total addressable market (TAM).

2. Whether the autonomous vehicle systems market fragments or is winner-take-all.

3. Whether AI can disintermediate Uber.

4. What happens with take rates.

5. The upside/downside skew.

Let’s ride.

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TAM explosion

AVs will massively expand Uber’s TAM, because they will massively reduce the cost of transport.

Why?

1. AV drivers will be much cheaper than human drivers. This reduces the cost per mile.

2. AV technology enables a wholesale shift from personal use toward rideshare. This will dramatically increase utilisation of the global car fleet: personal cars get used about 5% of the time, whereas cars on Uber achieve 3-4x that, and without driver fatigue AVs will achieve more. Since depreciation is a significant part of total cost and is fixed, higher utilisation of the global fleet further reduces cost per mile.

3. AVs can be owned in fleets. Part of the cost of individually-owned cars is personalising them. Colour, trim, and specification choices all add complexity and cost. Fleet-owned cars can be mass-produced to exactly the same design, further reducing cost per mile.

4. AVs will be safer than cars driven by humans and as discussed, the cars will cost less. This brings down the cost of insurance. In addition, AVs will eventually bring down the cost of regulatory compliance, broadly defined. No more sexual assaults or risk of drivers being classified as employees. All these things further reduce cost per mile.

5. Electric vehicles are more expensive to buy than infernal combustion vehicles, but less expensive to run and maintain because they have 1/10th the number of moving parts. As utilisation rises the fleet will naturally shift towards EVs, further reducing cost per mile.

6. Large numbers of autonomous electric vehicles (AEV) solve one of the world’s great problems today: renewable electricity is cheap on a levelised cost basis but intermittent, and when you include the cost of storage or backup it’s expensive. EVs are batteries on wheels. An AEV can constantly compute the highest-value use between charging, discharging, and mobility. This will require significant investments in local grids, but the societal benefit is compelling. AEVs will get paid for balancing grids, further reducing cost per mile.

7. AEVs will have AI inference chips on board. These chips will be idle when the car is not driving. This idle time will represent a large distributed compute capacity. It won’t be the most efficient compute, but the marginal cost will be tiny, so it’ll get used. AEVs will get paid for distributed compute, further reducing cost per mile.

Uber’s user base is relatively small today. Its annual active user count is roughly half Spotify’s monthly active user count, despite the fact that Spotify arguably has more competition (Apple, YouTube, and Amazon are all huge in music streaming). Why? Because Spotify is free. Uber’s user base is fundamentally limited by the high marginal cost not of its service, but of the product it distributes. Most people can’t afford to use taxis and food delivery very often, and many not at all. The scope for TAM growth is absolutely massive: taxis and ridehailing likely account for less than <1% of distance travelled by humans on land, whereas personal cars likely account for >70%. As cost per mile comes down, I would expect total distance travelled to rise and ridehailing to gain share. For many people, I expect ridehailing to replace car ownership entirely, eventually. The potential for TAM expansion is enormous: if I am right the user base will explode and frequency will rise.

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The above focuses on mobility, but the same applies in delivery. The human driver represents about half the cost of last-mile delivery. Robotics will transform this. Uber has partnerships with Nuro, Lucid, and Serve to introduce AVs and robots for delivery. The impact on total cost will not be as significant as it might be for mobility, because the underlying cost of the hamburger being delivered won’t change, but reducing the cost of delivery itself will expand the market.

These changes have a number of broad societal benefits, too. Driving becomes safer. Cities become more liveable: without personally-owned cars, inner-city parking can be eliminated and roads can be re-designed with larger walkways and cycleways. Carbon intensity is reduced. I think it is likely that, in time, AV will receive both regulatory and popular support.

Pushbacks:

1. “I want to keep my car. I like driving”. Do you, though? Really? I get that taking a Ferrari round Silverstone or going off-roading in a Land Rover is fun. But driving to work? Driving with your kids screaming in the back? These things are not fun. Given the choice most people would far rather sit in the back, do some work, make a call, watch a film, play with the kids, or just stare out of the window.

2. Specific use cases. You might use fleet AEVs on Uber for your commute, but not for heading out of town at the weekends, and definitely not for your annual half term ski holiday drive from London to the Alps. But I think that as cost per mile falls, as fleet AEVs become ubiquitous, and as Uber innovates around specific use cases and availability in less-dense areas, you’ll book AEVs to do exactly those things. That half term ski trip? You’ll book 2 AEVs 6 months in advance for the whole week, and it’ll still be cheaper than owning a car.

I am not arguing any of this will happen soon. This is a multi-decade, high-level prediction. But I think the logic is compelling, and that the change will accelerate as the cost benefits become clearer.

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AVs - fragmentation vs dominance

Uber will benefit from TAM expansion if it is the demand aggregator for multiple AV types and fleets. It will not benefit if two or three AV manufacturers dominate the market and build their own demand platforms.

In this, I feel pretty confident. I think fragmentation is likely for a variety of reasons:

1. The market is huge. Huge markets attract competition.

2. None of the up-and-coming AV manufacturers has a pre-existing advantage: a product that is miles ahead, ownership of all the data or all the customers, or vast amounts of sunk capital that others have to match to catch up.

3. There’s no real barrier to entry in car manufacturing, a famously commoditised industry.

4. There’s no real barrier to entry in support infrastructure (charging, etc.).

5. There’s no real barrier to entry in developing AV systems. This is more controversial, but it is already clear that multiple players are developing AV datasets and/or the ability to train AV models in virtual worlds. Also, the challenge does not lend itself to having one winner: in the long run it’s not about being the best, but about being good enough. I think many AV systems will eventually meet that hurdle.

6. Several powerful entities are highly motivated to ensure no one AV system dominates, including Uber, NVIDIA, regulators (for competitive reasons), and governments (for security reasons). NVIDIA’s full stack AV offering and Uber’s Autonomous Solutions are great examples of how these two companies, at least, can be agents of fragmentation - not just beneficiaries of it.

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Assuming the market does fragment, Uber is a huge beneficiary. Utilisation will be the holy grail of AV economics and it will not be possible for every player to develop a demand platform - they will need an aggregator. Uber is positioning itself as a plug-and-play monetisation platform for AV. It offers instant utilisation, dispatch, operating and finance partnerships, customer support, and localised compliance. As a result it has a rapidly growing array of partnerships with AV developers and legacy car manufacturers, all aimed at launching AV fleets in multiple cities worldwide over the next few years. These solutions may not be the best or cheapest initially, but Uber lets them monetise quickly and reinvest to improve. For details on Uber’s partnerships (and links to some interesting models), I recommend this by :

Platform Aeronaut

Uber Is Quietly Winning the AV Rideshare Setup

If 2025 was the proof point that consumers will actually take autonomous rides at scale, 2026 is starting to look like the year the strategic map gets redrawn. For the last few years the AV debate has mostly been framed around who has the best self-driving technology. That still matters of course. But increasingly that is the wrong question for investor…

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2 months ago · 27 likes · 1 comment · Thomas Reiner

Uber takes a lower percentage of gross bookings for AVs (the target appears to be around 20%) than it does for human drivers (around 30%). However, it also has lower driver incentive and insurance costs. In the article below, estimates that Uber’s “real net revenue” might be as much as 65% higher with an AV driver than it is with a human one. I would add that if sales, marketing, R&D, G&A, and D&A costs remain the same, all of that drops to the EBIT line. Applying this assumption to 2025 financials implies that shifting to AV could nearly double EBIT (assuming only mobility benefits - if the other segments do, too, EBIT could triple).

Fundamentally Sound

On Uber: AVs, Take Rates, and Fragmentation

One of the primary arguments against Uber as an investment can be summarized in two words: AV disruption…

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5 months ago · 152 likes · 4 comments · Manu Invests

Uber’s economics also work for AV fleet operators. Uber takes 20% of their revenue. In return, it delivers higher revenue and lower costs than they can generate on their own:

1. With Uber, fleets don’t need to acquire customers. My guess is that most startups would need to invest >>100% of revenues for years to match the utilisation that Uber can provide on day 1 - something investors simply will not support in a market with so many players and no evidence of winner-take-all characteristics.

2. Uber estimates it generates 30% higher utilisation than standalone AV operators are achieving, and believes that the gap will grow from here because the standalone operators are currently running small fleets in very high-demand areas, with free publicity and novelty value on their side. These ideal utilisation conditions fade as fleets grow and AV expands into less dense areas.

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Nevertheless, some players will go it alone and build their own demand platforms. Successful standalone players will have two key things in common: deep pockets, and cheap customer acquisition costs as a result of existing brand awareness and legacy apps. In the west, Tesla’s Robotaxi and Google’s Waymo are the obvious candidates. For these players, going it alone may be a rational choice: saving 20% of revenue in the long run justifies the investment to acquire customers today. But even in these cases, selling spare capacity on Uber to maximise utilisation will probably make sense. And even advantaged standalone players do face two challenges:

1. They will grow city by city, and it will take years to match Uber’s coverage. Uber is using that time to become the demand aggregator for dozens of other AV fleets.

2. Users simply don’t want too many ridehailing apps. My home in London is in a ridehailing blackspot. I often have to search on 3 apps to get a ride, and I absolutely hate it. It is stressful and often expensive, because if I get distracted I can easily end up with two rides and a cancellation fee. I recognise that competition is necessary, but I would far rather consolidate my usage onto one app.

My guess is the vast majority of demand will settle onto a maximum of 3 apps per area. The network effects in this business are primarily local, so not everywhere will have the same winners, but Uber is very well positioned. Certainly if Waymo and Tesla came to London at scale, I’d stop using FreeNow and Gett instantly - but not Uber.

For these reasons, as long as consumers use apps to hail rides, I am pretty confident Uber will be a dominant player. And therein lies the problem. What if consumers don’t use apps?

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Can AI disintermediate Uber?

recently wrote an excellent article on how hard it was for Uber to build its network, and therefore how hard it would be to disrupt.

The Dutch Investors

Why Uber is close to being undisruptable

Last month, we analyzed Uber for our premium members. That meant speaking to former employees, reading Super Pumped, and reading its annual reports. During this process, we found some interesting facts that we wanted to share with you…

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3 months ago · 32 likes · The Dutch Investors

As an Uber shareholder, reading this felt like slipping into a warm bath of confirmation bias after a long day. But unfortunately, I can imagine how it might be wrong.

Uber’s network connects millions of drivers with hundreds of millions of consumers. The marketplace is incredibly fragmented. That’s why the network was difficult to build. But even in a fragmented AV world, supply will consolidate down to a few AV fleets. And if AI personal assistants (AIPA’s) get better - which they certainly will - the demand side could consolidate too.

In other words, if the future of ridehailing is AV and “Hey, Siri”, there might only be a few dozen major fleet providers on one side of the network and 3-4 AIPA’s on the other. That makes the network much easier to replicate. If the AIPA’s develop direct links to the fleets, they could bypass Uber entirely. This worries me much more than the AV transition because fewer people seem to be focused on it.

Notably, Uber cannot counter this threat with “hey Uber”. The operating system providers do not allow the creation of always-on wake words at the OS level, partly because they gain a huge advantage by keeping this functionality to themselves, and partly because there are data security implications of always-on listening so they can’t let everyone do it. There is a workaround in Android, but it requires running a foreground service with persistent notifications, isn’t optimal for battery performance, and is rarely used. So in practice “hey Uber” is only usable when the app is already open, which won’t beat “hey Siri” in terms of user experience.

Nonetheless, I think Uber has a number of potential defences.

The first is that the AIPA’s might route demand through Uber rather than bypass it, and indeed they already do - you can access Uber’s services through Siri, Alexa, and Google Assistant today. There are two very good reasons for AIPA’s to do this:

1. To reach their full potential AIPA’s will need to offer great services across a wide range of activities, not just mobility. The best way to do this is probably not to take everything in house, but to have specialist providers who excel in each area.

2. If AIPA’s start disintermediating the orchestration layers in major industries, they will become dominant consumer gateways with extraordinary power across large areas of the consumer economy. I highly doubt that competition regulators will allow this.

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The second defence is that to disintermediate Uber, AIPA’s would have to orchestrate mobility themselves, dynamically predicting demand, optimising routes, booking rides, negotiating prices, and supporting customers. They would have to do this well enough to offer better economics to fleets than Uber, despite the fact that the fleets would have to take the lead on building support infrastructure partnerships and navigating complex and varied local regulations, things Uber currently helps with. Uber’s vast datasets, deep experience, and emerging partnerships in these areas represent a deep moat. For more on what Uber does under the hood, I recommend this by :

Future Cognitive Capital

[$UBER] Why Almost Everyone Still Misunderstands Uber

Why Almost Everyone Still Misunderstands Uber…

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4 months ago · 43 likes · 7 comments · Hidden Market Gems

A third defence is that Uber is actually a 3-sided marketplace. While supply and demand for mobility might get consolidated, it’s harder to imagine the same happening to delivery. AIPAs might be able to replicate a significant part of delivery by connecting to major chains, but a large part of delivery will always be fragmented amongst thousands of mom & pop restaurants and shops. Replicating these relationships would be costly.

The fourth defence is time. Consolidation down to a few players on either side of the network is going to take years. Major braking factors are the ramp-up of AV vehicle production, the optimisation of AV designs to bring down costs, the slow creep of regulatory acceptance, and the expansion of AV outside of major city centres. In the meantime, mobility is clearly going to be a hybrid of AV and human, which is much harder for the AIPA’s to replicate.

This combination of defences gives Uber a deep moat, full of crocodiles. Is it unbreachable? Theoretically, no - very few moats are unbreachable in the fact of a deep-pocketed and determined competitor. But it is a huge deterrent. It seems very likely that the easiest thing for AIPA’s will be to route demand through Uber, and that Uber has time to adapt, deepening its relationships with AIPA’s, ensuring it is the default API for mobility, and - perhaps - reconsidering its take rate strategy.

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Take rates

As cost per mile falls and TAM expands, there are three possible paths for take rates.

1. Uber’s take rate could stay the same in absolute dollars. Markets might celebrate this in the short term but it would be a disaster in the long: eventually Uber would represent the majority of the cost of a ride, and network participants will be motivated to bypass Uber.

2. Uber’s take rate could stay the same in percentage terms. This would be very good for Uber’s profits, since we expect the TAM to expand explosively and many of Uber’s operating costs are somewhat fixed.

3. Uber’s take rate could come down in percentage terms. This would be less good for profit growth but phenomenal for Uber’s competitive sustainability.

This might not be a popular view, but I will be very bullish if Uber finds intelligent ways to manage its take rate down as gross bookings inflect upwards. Of course, I will not be bullish if this happens chaotically under intense competitive pressure. But win-win solutions, in which (for example) Uber offers lower take rates to fleets that dramatically expand low-cost supply in strategic areas, would be a very good outcome. If it does this, Uber will combine three of my favourite competitive moats:

• Network effects, which Uber already has.

• Scale economies shared, in which economies of scale are shared with customers in the form of lower prices, which drives more demand and more economies of scale which are also shared, creating a powerful flywheel.

• The cheap critical component, in which some critical component is so cheap that nobody even thinks to replace it or compete with it, but it is still priced to give excellent returns to its provider.

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Valuation and skew

I think investing is about embracing uncertainty. Many investment writeups predict what will happen. My view - especially at a time of rapid and accelerating technological change - is that we simply don’t know, and we need to be comfortable with that. What we can do, however, is frame different long term futures and assess risk-reward skew.

This table shows what would happen to Uber’s 20 year revenue CAGR under very different gross billing and take rate scenarios:

The next table takes the revenue CAGR range in yellow in the table above, and shows the resulting 20-year non-GAAP net income CAGR under different margin assumptions:

Some thoughts on the inputs:

1. As discussed above, I would like to see take rates trend down over time.

2. Gross billings grew 19% in 2025 without any real help from falling cost per mile. Over the next 20 years I would expect cost per mile to fall hard in real terms; as a result total distance travelled will grow ridehailing will take a much larger share. I can only guess at the impact, but I think gross billings could easily grow +/-10x under those conditions. I don’t have a strong view on whether mobility outgrows delivery, so I apply the growth to consolidated gross billings.

3. Net margins. In 2025, Uber reported a 10% non-GAAP net margin. There are 4 reasons to expect this to increase: 1) as discussed above, AV economics may drive up to 2-3x greater EBIT for the same level of gross billings; 2) Uber has significant fixed costs, creating strong operating leverage as revenue grows; 3) AI should enable productivity increases, and 4) freight is currently almost 10% of revenue but lossmaking - this will presumably either scale to profitability or be closed.

This is obviously not a sophisticated analysis - indeed, I imagine it gives the detail monkeys among my readership the yips - but I find it useful for framing skew.

In the lower scenario, with 5% revenue CAGR and 15% margins, net income compounds at 7%. Uber currently trades at 30x non-GAAP net income, so the multiple would almost certainly fall in this scenario, but the deployment of free cash flow into buybacks and dividends would help. Investor outcomes would be poor, but not terrible.

In the middling scenarios, with 5-10x growth in gross bookings, 10-15% take rates, and 20-25% non-GAAP net income margins, net income compounds in the low teens for 20 years. In this scenario, I would expect FCF deployment to more than offset any multiple compression.

In the more optimistic scenarios, 11% revenue growth and 30% net margins generates 17% non-GAAP net income CAGR. With buybacks and dividends the compounded returns could be spectacular.

In short: I like the skew.

None of these scenarios represents the absolute worst or absolute best possible outcomes. In the worst case, Uber might fail completely, in which case investors will lose their money. On the other hand, the top table suggests revenue could grow faster than 11%, driving non-GAAP net income compounding at over 20% before FCF deployment, in which case investors could make 40-80x their money. This is the beauty of equity investing: the downside is capped, but the upside is not. I don’t plan on either of these last two scenarios, but if I had to pick, I’d say the second is more likely than the first.

Again: I like the skew.

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Links to previous work

1. IRSA

2. Brookfield

3. Cheniere

4. My notes

Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

Ticker: MTN

IR site.

What it does

Vail operates 42 ski resorts globally. It generally leases the land and owns the resorts themselves - the ski infrastructure and associated lodging, dining, and retail real estate.

These could reasonably be described as irreplaceable assets, but the irreplaceable bit is the location, not the resort, so one long term question I have is whether leases can be renewed on good terms.

Summary figures for the last full year:

• $860m of ebitda, $300m of net income, $320m of FCF.

• $3bn of net debt and operating leases.

• Negative tangible asset value.

Profitability for the current full year is guided lower on poor snow conditions.

The vast majority of ebitda comes from Mountain operations, which break down like this:

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Outlook

After several years of acquiring assets and then covid, Vail needs a reset to deliver visitor growth.

The CEO has been in place since May 2025, but had previously been CEO for 14 years, so he knows the business well. He discussed his views on the 4q25 call. According to him Vail has:

• Been over-reliant on email marketing and has not sufficiently developed other channels.

• Been over-reliant on call to action marketing at the expense of building an emotional connection to the brand and specific resorts.

• Lost focus on Lift sales as they have grown Pass sales - they can grow both.

• Failed to capitalise on strong engagement with their app, which doesn’t have checkout functionality, so conversion is low.

• Not optimised the price/benefit relationship across thousands of products.

All of these problems feel solvable over a multi-year timespan.

Notably, a lot of people enter and exit the industry each year - skiing for more or fewer days, or skipping a year or two. This means there is a large opportunity to increase utilisation within the ski demographic, not just by attracting new skiers.

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Valuation at a share price of $134, using last full year data

• 16x P/E.

• 9x ev/ebitda.

• 6.7% free cash flow yield.

I’d describe this as reasonable rather than cheap, but it would get cheap quickly if the company can grow revenue at high incremental margins.

Areas for more work

• Lease renewals.

• Deeper dive into financials, especially incremental margins and returns on capex.

• Get more comfortable with capital allocation. The company is paying a large dividend and buying back stock; I worry it should be reducing leverage.

Conclusion

I thought I would be intrigued enough to buy a tracking position. On reflection I am not. I think these are fantastic assets and I can imagine a future in which rising disposable income and management efforts drive significant revenue growth at high incremental margins. But given the debt and the risk around lease renewals, I need to do a lot more work before I risk capital.

What do you think?

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Links to previous work

1. IRSA

2. Brookfield

3. Cheniere

4. My notes

Thanks for reading - if you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

What it does: liquefies natural gas for export.

Elevator pitch: well-managed and cash generative infrastructure company with contracted cash flows, strong growth at high incremental returns on capital, and a large buyback programme.

Mental model: value.

Valuation and potential returns: DCF suggests 13% IRR to 2030 with relatively low risk.

Exchange: NYSE, ticker LNG

Stock price and market cap: $246, $52bn.

Type of holding: this is one of my trades, at a 1-2% position.

IR website: LNG IR

Disclaimer: This post is for informational and educational purposes only. Building Arks is not licensed or regulated to provide any financial advisory service and nothing published by Building Arks should be taken as a recommendation to buy or sell securities, relied upon as financial advice, or treated as individual investment advice designed to meet your personal financial needs. You are advised to discuss your personal investment needs and options with qualified financial advisers. Building Arks uses information sources believed to be reliable, but does not guarantee the accuracy of the information in this post. The opinions expressed in this post are those of the publisher and are subject to change without notice. The publisher may or may not hold positions in the securities discussed in this post and may purchase or sell such positions without notice.

Introduction

Cheniere owns two LNG liquefaction assets in Louisiana and Texas. These complex, multi-billion assets cool natural gas into liquid form so it can be shipped worldwide.

I have owned Cheniere continuously for 10 years and have got the sizing more right than wrong over time. I first bought the stock in the mid $30s in 2016, and then sold quite a bit in the mid $60s in 2018. After a lot of progress in the business I added a little in the high $50s in late 2019, and then I made it a 10% position in the low $30s when markets collapsed in 2020. At that point the stock was trading for 3x distributable cash flow if you looked 18 months forward. I sold most of my stock in 2022 at $120-150, 4-5x the price I’d paid 2 years earlier, making it one of my most personally significant investments ever. I largely missed out on the rally from $150 to $250 in 2024/25, but the big percentage gains had been made by then. Finally, I added at $190 in December 2025, and that position is up 30% in 2.5 months.

My early gains were not without risk. The company was developing two new, highly complex, multibillion LNG facilities, and the potential for cost overruns or other problems was significant. It was also highly levered, so the potential downside was great. However, Cheniere is superbly managed. They have consistently under-promised and over-delivered. Today, Cheniere is a materially de-risked company: it is investment grade, with copious cash flows, strong growth at high returns on incremental capital, and significant buybacks.

Let’s dive in.

Why do we need LNG?

Oil is liquid. This makes it easy to move around. As a result, global oil prices are pretty efficient - once you adjust for quality and transport costs, there is basically one global price of oil.

Natural gas is different. It is, well, a gas. This makes it very hard to ship. You can’t put it on a truck or a ship in its natural state. You can put it down a pipe, but pipes are a bitch. They’re expensive, unpopular, and vulnerable, and there aren’t enough of them. As a result, gas prices vary wildly from place to place. Where there is local oversupply, prices are very low or even negative (where gas is a by-product of drilling for oil and there is no local demand). Where there is local undersupply, prices are much higher. This creates incredible arbitrage potential and has incentivised the development of the LNG market. By cooling gas into its liquid state, you can ship large volumes over long distances fairly efficiently.

Fracking transformed the US from being short gas to being very, very long gas. Gas prices plummeted as a result, creating a huge incentive to export gas. LNG is the only way to do this at scale.

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Cheniere’s journey and reinvestment economics

Through the 1990s and the 2000s it was more or less consensus that the US would need to import gas in the future. Cheniere was originally conceived as an LNG import terminal. Once it became clear that fracking was a paradigm shift, Cheniere pivoted to producing LNG for export. Thankfully the sites it owned were perfect, and some of the equipment could be repurposed, but liquefaction plants are huge projects and it took over a decade to achieve production at scale. It was an extremely impressive decade: from scratch, Cheniere built two of the biggest LNG complexes on earth, and they delivered each piece ahead of time and within budget. That’s an incredible achievement and evidences one of the key planks of the investment case: management is exceptional.

Cheniere produces 50-53mtpa today, with projects under construction to get it to 60-63mtpa, projects in advanced planning to get to 71-75mtpa, and potential beyond that to get to 100mtpa. Cheniere has two great advantages when it comes to return on incremental capital deployed:

1. It is building brownfield, which reduces costs. By expanding current facilities Cheniere can leverage current assets and contractor workforces, and deliver additional capacity at a construction cost to ebitda ratio of 6-7x. By my maths this translates into a 20% free cash flow yield to equity, which for assets that will likely run for 60 years is superb.

2. Cheniere has been shipping LNG for 10 years and has developed an enviable reputation for reliability. Some customers are prepared to pay a premium for this. Cheniere discussed this on the 4q25 earnings call: they are signing 25-year contracts with world class counterparties with a tolling fee of more than $2.75/mmbtu, when they estimate the market rate is below $2.50. If the spread is 30c, Cheniere are getting 12% more ebitda per $1 of capex than the average.

Cheniere’s business model and commodity sensitivity

Cheniere aims to sell 95% of its production under long term contracts, making its cash flows highly predictable. These contracts are priced to provide Cheniere with a return on its investment. They do not have exposure to commodity prices and tend to be with investment grade counterparties, so I think it is reasonable to view the profits from these contracts as low risk.

The other 5% of production is sold by Cheniere’s marketing arm, CMI, which captures the spread between whatever it can buy gas for in the US and whatever it can sell LNG for overseas. These profits are therefore “at risk”, but the risk skews to the upside because Cheniere doesn’t have to produce these volumes if the spread isn’t attractive. As long as CMI locks in its purchase and sales prices at the same time it can’t lose money, but when global LNG prices spike it can make lots.

One of the counterintuitive outputs of this business model is that in the long term, Cheniere might benefit more from low LNG prices than high ones. Although CMI will makes less money at low LNG prices, Cheniere is primarily in the business of deploying capital into brownfield growth under 20-year contracts at 20% FCF yields on equity. To do more of this, it needs more demand for LNG. And for that, it needs low prices.

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LNG market outlook

The LNG market has had an “interesting” few years. The late 2010s saw a rapid expansion of global supply and rapid demand growth out of Asia as a result. A dearth of projects in the early 2020’s meant less new supply, and there were projections for a tighter market. Then Russia embarked on its appalling invasion of the Ukraine. In response, Europe switched rapidly from buying Russian gas to buying LNG, tightening the market rapidly and pushing global LNG benchmark prices to very unusual levels. In effect, Europe outbid Asia for volume: Asian buyers tend to be price sensitive, so Asian LNG demand has barely grown since 2021.

Over the last couple of years the outlook has shifted again. European demand has become the new normal, and the market has largely adapted to it. A wave of LNG liquefaction projects over the next few years will add significantly to supply. And Asia has continued to invest in regasification and gas distribution capacity, which stands waiting to absorb new supply at lower prices.

To a great degree, this doesn’t affect Cheniere, which has 95% of its production through 2035 already contracted. But it’s worth knowing, because there will be headlines about an LNG supply glut. The tl;dr is: yes there is a lot of supply coming, but it is likely to stimulate Asian demand. Says Cheniere: “we’ve always been of the view that moderate prices are good for this industry.”

Growth projects

The following projects take Cheniere to 60-63mtpa of production in 2028, and 71-75mtpa in 2030, and 100mtpa thereafter:

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Legal & capital structure

Cheniere owns its Corpus Christi asset outright but it owns its Sabine Pass asset through a partnership which is separately listed (CQP). As a result

1. Cash flow growth is not linearly correlated to production growth - if the growth is at Sabine Pass, Cheniere only owns 51% of it.

2. You have to adjust for minority interests when calculating an ev/ebitda ratio. The lazy way to do this is to add the part of CQP’s market cap that Cheniere does not own to the EV. This doesn’t help you distinguish between the valuations of Cheniere and CQP, but it is good enough for a sense-check.

As it happens, the majority of Cheniere’s growth is at Corpus. Corpus has 21mtpa of capacity now, with 9mtpa under construction, and potential for 24 beyond that, giving a total of 54mtpa and 33mtpa of growth. Sabine Pass has 30mtpa now, with none under construction and potential for 20mtpa, giving a total of 50mtpa and 20mtpa of growth. This doesn’t affect the economics, but Cheniere owns a higher percentage of the growth at Corpus than at Sabine.

On the capital side, like most infrastructure companies, Cheniere is levered. On a consolidated basis it finished 2025 at 3.3x net debt/ebitda, including operating leases but excluding restricted cash. The debt structure can be seen at page 19 here. The debt is well-laddered, and has been coming down in both absolute and relative (to ebitda and asset) terms. Growth is funded 50/50 equity/debt, which is a very effective way to de-lever in relative terms. Cheniere had 5 ratings upgrades in 2025 and has had many more over the preceding years.

Management

Key to the investment case is the management team. It is incredibly hard to create a business like this from scratch, and to build multiple multibillion-dollar assets ahead of time and underbudget, but this team has done so consistently. They have also communicated with the market consistently and clearly, and they have implemented a highly rational capital allocation plan that has allowed them to:

• Grow the business from 0 to 50 mtpa.

• De-lever the business, both by paying down debt and by funding ebitda growth with equity, and achieve investment grade.

• Reduce the share count from 257m at the peak in 2018 to 210m now, per TIKR.

Management have also had some luck, of the sort nobody wants. Over the last few years Cheniere has grown production fast and ahead of schedule. As a result, the company has had more cargoes to sell at spot than planned, just when spot prices were high because of the war in Ukraine. This has generated excess cash flow which Cheniere has used to de-lever and buy back shares. I hope they do not get that kind of luck again, although as I type LNG prices have spiked on the Iran war.

Risks

Russian gas might come back. I regard this as a low risk; Russian gas production has mostly been redirected to Asia rather than curtailed. If the political situation changes dramatically Europe might start importing more Russian gas, but they have already built LNG regas infrastructure and will remain an opportunistic LNG customer. And in the end, lower prices serve to grow the gas market.

Long term margins. Cheniere aim to sign contracts (and market spot gas) at margins of $2.50-3 per mcf. This has increased from $2-2.50 when they started out, which implies that they have been able to increase margins as the cost of building assets has risen. However, if LNG liquefaction capacity gets overbuilt in the future, margins will come down when contracts begin to roll off. In the worst case, LNG liquefaction might end up like oil refining, which is highly commoditised and done on a spot basis with no long term contracts. I think this is possible, but not soon: as long as buyers need to incentivise new capacity, long term contracts will be needed. I see this as a 2050 risk.

Feedgas. Cheniere is basically built on the shale revolution. That’s what supplies the gas that Cheniere cools and sells. It is clear that the rapid growth phase of North American shale is over. That in itself is not a huge problem: there is plenty of gas and it remains cheap by global standards. However, some analysts such as Goehring & Rozencwajg argue that gas production will now enter a long decline. That might well make Cheniere’s product uncompetitive, pressuring margins once contracts start to roll off. I think G&R get a lot right, but I think their argument is more compelling at $50 oil and $2 gas than it is at $65 oil and $3.50 gas. Said another way, I don’t think it takes a huge uplift in the gas price to incentivise more drilling, and I don’t think the shales are so exhausted that drilling won’t work.

Hurricanes. Cheniere’s assets are on the Louisiana and Texas coasts, potentially in the direct path of a hurricane. However management have known this since day 1. The assets are built to withstand hurricanes, and procedures are in place.

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Impact of the Iran war

If the war escalates and Qatari LNG exports are impaired in any serious way, LNG prices could stay high. This benefits Cheniere but not transformatively since most of its volumes are contracted (and most of what isn’t contracted has already been forward sold for 2026).

Equally, if the war ends tomorrow, Cheniere might immediately trade back to the low $230s, where it was prewar.

In short, I don’t think the war is hugely relevant to Cheniere unless it escalates and lasts for a long time. I very much hope that is not the case but if it is, Cheniere will benefit from being a reliable supplier well away from the war zone.

Valuation

These are long lived assets. LNG facilities can easily run for 50 years and I think well maintained ones with consistent feed gas in a mature market can likely last significantly longer.

Cheniere uses a bespoke metric called distributable cash flow, or DCF. This is basically ebitda less maintenance capex, interest, and cash tax. It overstates long term owner earnings in 2 ways: first, these are new assets so maintenance capex is fairly low; second, Cheniere is still investing hard which creates tax allowances. However DCF is an accurate measure of the cash the company will produce over the next 5-10 years, so I think it is a reasonable valuation tool. Cheniere’s latest DCF guidance is laid out on page 13 here.

Once projects currently under construction are completed in 2028, the company will produce 60-63mtpa and $21 of DCFPS assuming the middle of the DCF guidance range and no further buybacks. However, management consistently beats guidance and they are buying back shares. Assuming the top end of the guidance range and a share count of 200m, 2028 run rate DCFPS reaches $23.5.

Once the company has completed its $10bn authorised buyback and the CC and SPL Expansion projects, all due by 2030, DCFPS guidance increases to $30. I think they will beat this. Again, guidance uses the middle of the range for DCF but tend to beat guidance, so I think we can use the top end. Also, I don’t think they have accounted for all of their FCF. On the 2q25 call the company guided to $25bn of DCF from 2h25 to 2030, and $7.5bn of equity investment to get to 71-75mtpa of production in 2030. Of this, $2.4bn of DCF was to be produced and $1.4bn of capex was invested in 2h25, leaving $22.6bn of DCF and $6.1bn of capex for 2026-2030. This nets to $16.5bn of FCF over those 5 years. The dividend will consume ~$2.5bn leaving $14bn. Guidance assumes a $10bn buyback, leaving $4bn unaccounted for. Either the buyback will be bigger than guided, or the company will keep growing production.

Finally, the 2030 guidance assumes $10bn of buybacks at $285 per share. This is well above the current share price, which is a sensible assumption for a management team issuing guidance. However as an investor I’m equally interested in how many shares the company could buy back at the current price. If all FCF (after dividends) is used to buy back shares at the current price the 2030 share count will be 157m, not the 175m that management assume. With that share count, and using the top end of the DCF range, we get nearly $36 in DCFPS.

To summarise:

The implied multiples seem reasonable to me for a long-lived, highly contracted, cash-generative asset. I also run a simple DCF which assumes that all FCF after dividends is used for buybacks at the current price, and at the end of 2030 the stock is valued at 12x 2031 DCFPS, which seems fair given they will still have a runway for 33% growth (75mtpa to 100mtpa) at advantaged economics.

With a DCF built this way, the IRR is doubly sensitive to the share price because it affects both the starting point and the buyback. The alternative is to guess what price the buyback will average. I like my method because it tells me the IRR if the shares remain at the current price, but it is a matter of preference.

My DCF puts the 5-year IRR at today’s share price of $246 at 13%. At $230, the IRR is 15%; at $290 it is 8%. For me, it is a comfortable hold at the current price.

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Links to previous work

1. IRSA

2. Brookfield

3. My notes

If you enjoyed reading this please like and restack, and do get in touch if you have questions.

Pete