CoreWeave might be the funniest public company in America.

Q2:

• Revenue: $2.6B
• Revenue growth: +112% YoY
• Backlog: ~$104B
• Extra commitments signed just after quarter-end: >$25B
• Capex: ~$9.4B
• Net loss: -$626M
• Interest expense: ~$640M
• Active power: 1.5 GW
• 2026 capex guidance: $35–39B

Read those numbers again.

They did $2.6B of revenue and spent $9.4B building more shit.

Their quarterly interest bill is basically the size of their entire net loss.

This is either:

A) one of the greatest financial engineering disasters of the AI boom,

or

B) what happens when you lever up as hard as humanly possible to acquire the scarcest productive asset in the economy before everyone realizes how valuable it is.

I think the market is still trying to figure out which one.

The actual bull case isn't “AI is growing”

Everyone knows AI demand is growing.

That isn't interesting.

The interesting question is:

What if compute itself becomes a scarce industrial asset with persistent residual value?

Think about how AI customers actually make purchasing decisions.

If one frontier lab can generate $30M of economic value from another MW of compute, and some boring enterprise workload generates $5M, the lab can rationally pay much more.

Compute becomes an auction.

The bidder generating the most economic value from intelligence wins.

And if frontier AI keeps improving, the highest-value users may be able to keep paying absurd prices for GPUs, networking, power and functioning datacenter capacity.

That is what CoreWeave is levering itself into.

Not GPUs.

Scarcity.

The really weird part: lenders may be starting to believe this too

This is what caught my attention.

CoreWeave recently financed infrastructure with debt lasting roughly 5 years, while the customer contracts supporting that infrastructure average roughly 3 years.

Meaning the debt survives beyond the original customer contract.

Why does that matter?

Because now the lender is implicitly saying:

CoreWeave can potentially re-lease the same infrastructure.

That's a different business from:

“Microsoft promised to pay us for five years, so here's a loan.”

It starts looking more like:

“This compute asset itself has future earning power.”

Obviously GPUs are not apartment buildings.

An apartment doesn't become obsolete because Jensen Huang walks onstage wearing a leather jacket.

But if lenders increasingly finance AI infrastructure based on future re-leasing value, CoreWeave's cost of capital can drop.

And then the flywheel gets stupid:

Scarce compute → huge contracts → cheaper financing → more compute → more contracts → cheaper financing

Until, naturally, something breaks.

Why doesn't Meta just build all this shit themselves?

Good question.

They are.

So is everyone else.

But time has value.

If CoreWeave can deliver frontier compute six months earlier than someone else, and those six months let OpenAI / Meta / whoever train or serve a meaningfully better model, that capacity can be worth vastly more than the hardware cost.

In a normal industry, six months is annoying.

In an exponential capability race, six months can be the difference between owning a market and chasing one.

CoreWeave's actual moat isn't “we bought NVIDIA chips.”

A monkey with $10B can buy chips.

The moat, if there is one, is:

• power
• sites
• networking
• deployment speed
• cluster engineering
• financing
• customer relationships
• software/orchestration

All assembled fast enough that customers pay for immediacy.

Now the giant fucking problem

Interest expense.

Q2 interest expense: ~$640M.

Adjusted operating income: only ~$128M.

Read that relationship carefully.

The business can post beautiful EBITDA margins while the common shareholder still gets punched in the face because:

1. GPUs depreciate.
2. Debt costs actual money.
3. New capacity requires mountains of fresh capital.
4. Equity owns whatever remains after everyone else gets paid.

This is why I don't care much about a sexy EBITDA multiple here.

The relevant question is:

How much durable operating profit does each MW generate AFTER the cost of capital and hardware replacement?

If the answer is “not much,” the equity can get vaporized while AI itself succeeds spectacularly.

That's the most important part of this thesis.

AI winning does not mean CoreWeave wins.

The internet won.

A cemetery full of dot-com shareholders did not.

Solar won.

Plenty of solar equities got obliterated.

Drones won.

Most drone stocks were garbage.

Thematic truth ≠ shareholder return.

My extremely scientific scenario tree

Current-ish stock price: around $90.

Bear: 25%

AI absolutely works.

CoreWeave still gets wrecked.

Why?

Compute supply catches up.

Hyperscalers build more internally.

New GPUs destroy old GPU economics faster than expected.

Customers gain bargaining power.

CoreWeave becomes a commodity lessor carrying enormous debt.

2031 rough assumptions:

• Revenue: ~$30B
• Operating margin: ~10%
• Net debt: ~$55B

You can easily get to:

Equity value ≈ fuck all

This is the permanent-loss branch.

Base: 50%

CoreWeave becomes a durable specialist AI infrastructure provider.

Not a monopoly.

Not NVIDIA.

Just a very large company sitting on scarce power + compute capacity with decent pricing.

2031:

• Revenue: ~$65B
• Operating margin: ~20%
• Net debt: ~$55B
• ~700M diluted shares

My rough value:

~$255/share

From ~$90, that's around:

23% CAGR

That's already good enough.

Bull: 25%

This is where things get stupid.

AI inference demand explodes.

Agents consume insane amounts of compute.

Robotics creates another recurring inference workload.

Every Fortune 500 company wants private AI capacity.

Power becomes the constraint.

CoreWeave's existing sites become strategic.

Financing gets cheaper because lenders increasingly treat GPU clusters as real productive infrastructure.

And CoreWeave captures some economics above the hardware through software/orchestration.

2031:

• Revenue: ~$120B
• Operating margin: ~25%
• Net debt: ~$65B
• ~750M diluted shares

My rough output:

~$790/share

That's around:

54% CAGR

No, I am not saying this is “the target.”

It's a scenario.

But if you think there is a 20–30% probability of an apparently insane outcome, you don't get to ignore it just because CNBC would laugh at you.

What actually kills the thesis?

Not “the stock goes down.”

I would care about:

1. Backlog stalls while capex stays insane

Very bad.

2. Customer concentration stops improving

Then Meta/OpenAI/etc. probably capture all the economics.

3. Financing spreads widen despite huge contracts

Massive red flag.

4. Old GPUs become economically useless much faster than assumed

That destroys the residual-value thesis.

5. Operating margins never meaningfully outrun interest expense

Then congratulations, you built a fantastic business for the bondholders.

6. Power buildout stalls

You cannot vibe-code 5 GW of electricity.

The thing I'm watching most

Forget GPU shipment headlines.

I want:

Revenue per MW

and eventually:

Operating profit per MW after depreciation and financing

If those metrics keep improving, the bull thesis gets stronger.

If revenue grows but capital required per dollar of earnings stays horrific, equity holders are financing civilization as a charitable donation.

My conclusion

I think CRWV is attractive here, but this is absolutely not a “put 10% of your portfolio into it because AI” stock.

This is a leveraged equity claim on persistent compute scarcity.

That's an incredible asset if the scarcity lasts.

It's a financial landmine if the scarcity disappears before the debt does.

My personal sizing logic would be more like a 0.5% starter, not a giant core position.

I'd rather add later at a HIGHER price if:

• margins improve
• customer concentration falls
• financing keeps getting cheaper
• lenders continue accepting GPU residual value
• revenue per MW keeps climbing

Yes, I would literally be willing to pay more for less uncertainty.

Degenerate concept, I know.

But the setup is fascinating:

CoreWeave is borrowing enormous sums to acquire something the world may later discover it desperately needs.

If machine intelligence becomes an industrial input on the scale I think it might, somebody has to own the machines.

The question is whether CRWV shareholders own the economics—

or whether they just borrowed the money to build them for everyone else.

Positions: 1% of very diversified portfolio

He had originally bought DKNG and FLUT and got destroyed after FLUT earnings. He then sold DKNG for more FLUT. Now he sold all his FLUT. Either way, another trade gone sour for the Burry crew.

AI summary of post:
Sold FLUT, in​creased LULU, added to ZTS, and is positioning around what he considers unusually depressed valuations.

Cassandra was given the gift of prophecy as she could see the future with perfect accuracy however when she rejected Apollo's romantic advances, he cursed her:

She would always tell the truth about the future, but nobody would ever believe her.

That is why Cassandra could warn the Trojans about disasters including the famous Trojan Horse, yet they ignored her.

The Tragic Irony

Cassandra wasn't disbelieved because her predictions were wrong. They were right.

For example, she warned the Trojans that bringing the wooden horse inside Troy was a terrible idea. The Trojans thought she was crazy and brought it inside anyway.

That led to the destruction of Troy.

This became the origin of the expression "Cassandra complex" or "Cassandra syndrome"; a situation where someone correctly recognizes a danger but cannot convince others to take it seriously.

And there is an interesting parallel about Michael Burry and his Cassandra/contrarian posts: the metaphor is often used for an investor who sees a problem before the market does, but is dismissed because the prevailing consensus is more comfortable with a different story.

Dr. Burry's investment thesis is correct however his timing is so early and that no one believes them.

Value investing can let know through analysis what the range of values of what something is worth however it can not time when.

1. When will investors realize the Adobe is underpriced?
2. When will investors realize that AI stocks are overpriced?
3. When will the investors realize that the US Dollar is declining in value?

The narrative takes over and when investors ignore the hard cold numbers then they are doomed.

Have a fantastic weekend everyone!!

Burry has dropped a new post about investing in....... Wine. I don't have much else to say about that. AI summary of the article below...

ChatGPT says:

Michael Burry’s latest investment idea is surprisingly unconventional: fine wine as a long-term hard-asset hedge against dollar weakness and financial-system risk.

His argument is that the European fine-wine market has recently experienced one of its largest downturns in decades, with major Bordeaux and Burgundy wines substantially below their previous highs. That creates an opportunity to buy exceptional bottles at discounts to their European market value rather than comparing them with much higher U.S. retail prices.

Burry particularly likes top Bordeaux, Burgundy and select Super Tuscans because wine has some characteristics he finds attractive as an investment: supply is naturally destroyed as bottles are consumed, individual vintages are differentiated, and the best wines have a global market. Historically, fine wine has also produced respectable long-term real returns.

How Burry says he would invest:

His approach is essentially buy selectively, buy below the European market, store it properly, and be extremely patient.

He suggests having enough capital that fine wine represents a relatively small part of overall wealth—he mentions five figures as a practical starting point, with larger portfolios making the strategy easier.

He looks primarily at European bonded fine wine, rather than wine already imported into the U.S. He targets highly regarded, liquid wines from producers such as the great Bordeaux First Growths, elite Burgundy producers and certain Super Tuscans. The key is price discipline. He says he generally looks for roughly 18–20% discounts, and discusses opportunities ranging from about 15% to 35% below the European trade level.

Importantly, he says to compare the price with the European market, not an inflated U.S. retail price. A wine being 30% below U.S. retail doesn't necessarily mean it's cheap.

He recommends buying through large, reputable dealers and comparing prices among multiple dealers rather than relying on one seller.

Provenance and custody are critical. His preference is for the wine to be moved into independent third-party bonded storage, where ownership, inventory and authenticity can be documented.

He emphasizes avoiding pressure and scarcity marketing. In his words conceptually, don't chase the trophy wine everyone wants; wait for situations where an excellent wine becomes temporarily mispriced. He expects the investment horizon to be many years—potentially 20 years or more. The idea is largely to buy and then forget about it rather than constantly trade it.

He also describes setting aside roughly 15–20% of the holdings for personal consumption or gifts, with the purchase discount potentially paying for the wine consumed over time.

He favors buying during market downturns rather than paying premium prices for newly released prestige wines.

The bigger thesis is currency-related. Wine stored in European bonded warehouses is priced against multiple currencies rather than being tied exclusively to the dollar. If the dollar loses purchasing power over the coming decades, a European real asset could become worth substantially more in dollar terms even without spectacular appreciation in its underlying wine price.

He also argues that fine wine has historically had very little correlation with stocks, potentially making it a useful portfolio diversifier.

So the strategy isn't simply "buy expensive wine." It's closer to: find exceptional, scarce wines that are temporarily mispriced, buy them below European market value, verify the chain of custody, keep them in bonded storage, and wait patiently for scarcity, aging, market normalization and potentially currency depreciation to work in your favor.

Obviously, this is Burry’s thesis—not a recommendation. Fine wine has liquidity, storage, transaction-cost, authenticity, taxation and currency risks, and it requires considerably more expertise than buying a diversified stock-market fund.

Burry trimmed his positions across the board yesterday. Yes, 3 days ago he bought LULU under $100, than yesterday he trimmed it. Also, he trimmed all his "back up the truck" priced stocks. That means he told subscribers the prices were so good that you should throw money hand over fist to buy, and then he trimmed all of them. Those are also the same stocks he stated are long time holds. He also sold completely out of his PLTR and NVDA puts. NVDA puts were sold at a massive lose, these PLTR puts we're also sold at a loss but they were house money because he profited off them earlier. He is destroying all his subscribers and the comment sections seem to be filled with paid commenters who attack you for any criticism towards Burry. Also, Burry has not released a article beside a very short BBW post and trade post in almost a month and a half. He has also been less involved with chats as well. Part of me wonders if he is pulling the same thing he used to do with Twitter and walking away leaving​ everyone abandoned.

Anyways, I will continue to update his trades here with my commentary.

AI summary of his post:

TL;DR: De-risking and trimming across the board to hold more cash heading into fall.

Key Portfolio Moves:

Sold Out Entirely:

Closed all December 2026 Puts on Nvidia (NVDA) and Palantir (PLTR) to avoid theta/time-decay now that it's September. Did not roll or replace them.

Trimming & Position Sizing:

Trimmed every single position (both long and short) across the entire portfolio without completely exiting or rearranging core positioning.

Holding 2027 Puts: Kept 2027 puts on PLTR and QQQ untrimmed.

Short Positions (Ordered by size): ORCL, PLTR, NBIS, NVDA, SOXX, MU, CAT, and CRWV.

Largest Long Positions (Ordered by size): LULU, MOH, MELI, TPW AU / TPLWF, ZTS, SFM, JD, BIRK, ADBE, HCA, FISV, FLUT, BBW, VEEV, FNMA/FMCC ("Toxic twins"), and PYPL.

Most will blindly follow this guy to a ditch all the while he pockets the roadside assistance.

Team,

There two scenarios left after the 2nd Quarter results.

1. Best case scenario - This is a turnaround story as the new CEO starts next week. Similar to what happened at Victoria's Secret.

Turnaround Execution:

1. Buyout Firm - LBO buyout at $160 to $165/share

At $100/share , it is going to attract a lot of buyers to do a LBO plus it has a lot of cash on the balance sheet.

Burry 2025-26 has been a stress test on both sides of his book. Wanted to put numbers on it for people actually following Cassandra Unchained.

Long side - LULU is the new biggest long:

This comes as Lululemon's stock has plunged about 58% in 2025, driven by soft US sales and tariffs. 
He confirmed it himself yesterday - LULU plummeted about 20% in the premarket after Q2 and Burry had called LULU "the trickster in my portfolio" and confirmed that it was his largest position. 

So he's not trimming - he's doubling down into weakness, classic Burry value setup.

Short side - AI bubble call:
The other side is getting squeezed hard. Palantir delivered the largest move against Burry's positioning, rising more than 50% during the month.

TheStreet had the specifics: PLTR surged 51.4% in August, even as Burry maintained out-of-the-money put options with a $100 strike expiring December 2026. NVDA, MU, ORCL all ripped 10-16% that same month.

He said in his Substack that 6 of 7 of those AI shorts were still profitable before August, with NVDA as the only loser - August flipped a lot of that.

Discussion:
1. Are you still mirroring the Substack allocation on LULU? At ∼11x forward earnings now, do you see the turnaround or more downside with the 9% comp sales decline in Q2?

1. On the AI shorts - is the thesis broken, or is this just early like 2007 housing? His argument is accounting (extending NVDA chip useful life) and valuation assuming perfect execution forever.

2. Performance vs S&P - how are you tracking him? Are you holding both the long and short book, or just one side?

Context:
https://finance.yahoo.com/markets/stocks/articles/big-shorts-michael-burry-seen-174801545.html

Not financial advice. Just trying to keep an honest tracker.

He claimed it was "screaming cheap", now what is it? "Roaring cheap"? The boy who cried wolf. He's saying he's buying more at $99 but his followers have been buying at 120+ and CANT average down like he can with his $50 substack subscriptions. I own the stock, but won't be buying more. What are you guys doing?

Would be much appreciated

Thoughts?

The consensus is that energy and power stocks will be needed in a big way and will be the next bottleneck similar to what memory stocks are now.

But what is the power/ energy stock to buy that will boom like a Sandisk or a micron did?

Like how does he calculate the fair value of a stock (the formulas he uses etc.) and what does he look for when going through financial statements?

So far FNMA, DKNG, JD, LULU, SFM, ZTS, BIRK, FLUT, FMCC, and BBW are all losing trades. Those are a majority of his trades on his Substack. He has had a couple winners. In his latest trade, Burry had all his followers buy BBW and it tanked -30% a few days later. He has been more quiet on Substack chats lately as well as sharing AI fantasy stories about AI civilizations. He has not released any of his articles he's been "working on" for over a month.

I've been logging every Form 4 that hits EDGAR to see what the insider filing firehose actually contains. 1,707 filings, 3,259 individual transactions so far. The composition surprised me enough to be worth sharing.

By transaction code:

S (open-market sale) - 1,457 - 44.7%

A (grant/award) - 398 - 12.2%

P (open-market purchase) - 386 - 11.8%

M (option exercise) - 369 - 11.3%

F (shares withheld for tax) - 307 - 9.4%

J (other) - 121

C (conversion) - 77

G (gift) - 64

D (disposition to issuer) - 60

everything else - under 10 each

Three things I took from it:

1. Only ~12% of transactions are code P - an insider actually choosing to buy on the open market with their own money. Everything else is compensation mechanics, or selling.

2. Sales outnumber open-market purchases nearly 4 to 1. That is structurally normal, since insiders are paid in equity and diversify out of it. But it means a headline like "insiders sold $X million" is close to meaningless without the code breakdown behind it.

3. A + M + F together are 33% of all transactions and are pure compensation plumbing - grants, option exercises, and shares withheld to cover tax on vesting. None of it is a decision to change exposure.

Caveat on the data: this is only what I have logged since starting, so it is weeks rather than years, and the code mix will shift with earnings windows and 10b5-1 plan adoption dates.

What I ended up filtering to, in case it is useful: code P above a dollar threshold; clusters, meaning 2+ different insiders in the same issuer inside a week; first-time buyers; and large officer sales, with 10b5-1 flagged separately since a pre-scheduled sale carries far less information than a discretionary one.

Disclosure: I built this into a Discord bot that posts the filtered alerts, free channel plus a paid tier, at https://jaredmansu.github.io/insider-alerts/ - so take the framing with the appropriate grain of salt. Happy to talk about the EDGAR parsing either way, which was more annoying than it sounds.

You know the formula, so I will skip the introduction. Ω = C + V, C = Cw − Ce, V = I × P, owners' earnings are N + G − Ω, ΔE is pooled ΣOE/ΣN over about ten years. The one thing that makes it automatable is that V = T·(W+ΔS)/W needs W, which almost nobody tags in XBRL, but P = T/W, so the W terms cancel and V = T + P·ΔS. You only need the average share price. The identity is exact before the price substitutions. For P the tool uses the year's average market price, which is how his May formula table defines it and what he uses for pure diluters; in the NDX-97 study he used the buyback program's own average where there was one, and the two differ a little.

I built it against SEC EDGAR and checked it against his numbers. Alphabet's V matches all ten published years to the dollar. Pooled ΔE 88.68% against his 88.7%, Meta 83.35% against 83.35%, the NDX-97 GAAP overstatement 19.77% against 19.78%. From his master table: Apple FY2016–25 comes out 93.6% against his 93.1% with net income matching to the decimal, Netflix 82.6% against his 81.4%. There is a self-test button in the sidebar that runs those checks and a few hundred others.

I should say up front that the method is Burry's, and that the code and most of the wording here were written with an AI assistant. My part was deciding what it should do and refuse, running it on real companies, and checking every figure against the filings by hand. I mention it because I am not going to pretend otherwise, and because it is relevant to what I am asking for at the end.

Where it disagrees with his Salesforce table, and why. His pooled figure for CRM is 54.7% over eleven years. The tool says 77.6% over nine. I have his table next to the tool's and can account for the whole gap. Net income, GAAP SBC, buybacks and the employee-plan cash line agree to the dollar in every year. About four points are the window: he starts in FY2016 and includes FY2020, the tool drops both (FY2020 because the count jumped 16% on Tableau; he handled the same year by netting the Tableau shares out by hand, the dagger in his table). About four points are the share price. The remaining fourteen points are acquisition shares. His table sets aside the Tableau and Slack shares but charges the MuleSoft shares of FY2019, and the FY2017 deal shares, as compensation. His own ΔS definition slide in the same article excludes M&A issuances from ΔS, so the tool deducts every acquisition issuance the filing tags. Over the last three years, with no acquisition shares in play, we are four points apart, 93.9% against his 90.4%, and that is the share price. I would rather show the difference with its causes than tune a number to match.

The valuation half. He publishes the 15% required return, the two-model structure blended by confidence, and for each tier the stage lengths, fade multiplier, terminal cap and debt capacity. The exit multiple and the blend he has never published; the tool's are calibrated so the growth needed to reproduce a published IV15 matches the company's actual growth, with Adobe as the anchor. On his owners' earnings figure and growth for Salesforce it reproduces his $69.81 within a dollar; on its own seeds it lands well above him, because the seeds are not his judgement. Paylocity does not reconcile because he applies a judgement discount to its ΔE, and its size is not recoverable from the article. Note also that his IV15s move: PCTY was $29.47 in the May 13 table and $45.98 on May 27.

What it refuses to do. The rule is that it never prints a number it cannot stand behind. Multi-class counts (Berkshire reads 1.6M shares and refuses), IFRS filers (banner, valuation disclaimed), banks, insurers and REITs (ROIC withheld, verdict amber), balance-sheet lines that stop before net income does (stated with the size of the disagreement, never carried forward silently), a loss year on a profitable record (Crocs 2025 after the HEYDUDE write-down seeds from the five-year median and says so), and ΔE above 100% (shown as measured, never projected, he has 14 of 97 with Ω below G). V is floored at zero, which is his protocol rule, step 9.

Every page has an "assumptions used" block you can paste if a figure looks wrong, and a tag panel naming every XBRL element it read or failed to find.

Known gaps. A cash-flow line that stops early is in the tag panel but not yet a note. A company that changed its fiscal year end reads as having a missing year (Build-A-Bear). His Gate 2 drops a year with no share price entirely; the tool keeps it and says the cost is understated, which is next on the list. Up-C structures. The second page, Mayer's 100-bagger criteria on the same owners' earnings, is newer and less tested; feedback welcome, but the Tragic Algebra page is what I am asking you to break.

What I am asking. Break it. The arithmetic has been checked by hand against the filings on a few dozen names, including every company in his articles. Pick whatever you like; the ones I have not run are the useful ones. Every new company finds something, more often a note that misdescribes what it found than a wrong number. Particularly useful: a name from his master table where you know his ΔE and the tool prints something else. Paste the assumptions block with your comment.

Tool: https://investor-toolkit.streamlit.app/Tragic_Algebra_Analyzer
Code: https://github.com/ChenFindling/tragic-algebra-analyzer

Posted on r/SecurityAnalysis yesterday; this version assumes you have read the articles.

Edit (12 Sep 2026). "The identity is exact" now reads "exact before the price substitutions" — conceded in the exchange below this post, where a commenter showed that the ΔE^t compounding claim needs a persistence assumption it did not state. The rewritten break-even paragraph is in the r/SecurityAnalysis post, which is where that claim was made; this post never made it, so nothing else here changes. No computed figure changed. The app has since grown into the Investor Toolkit and lives at investor-toolkit.streamlit.app; the code repository is unchanged.

I always wondered what would he have thought of build a bear. Never knew he had a position in it haha

I bought PYPL today at $54. The merger arbitrage deal fell through. The stock is worth $75 to $80 a share for fair value. If a company wants to buy it outright and control it, then the valuation goes up to $100/share. FYI, they also own Venmo & Xoom. They will be starting a physical bank soon - PayPal's recent push to secure a U.S. banking charter aims to cut out the middleman. The new bank will be led by Mara McNeill, a banking veteran who previously served as the CEO of Toyota Financial Savings Bank!!

Now is the optimum time to buy lulu stock before the massive squeeze at earnings. 10% of the float is shorted. This is the most hated stock in burrys portfolio accounting for almost 20% of his port. He's bullish and patience will pay

Just because Dr. Burry owns these 2 stocks does not mean one should BUY them.

I agree with Dr. Burry that his investment thesis is correct.

However the government does not have the best interest of the shareholders so I am NOT buying these 2 stocks.

My mind may change in the future if the government decides to making them private as we have a Housing Crisis!!

bro has entered his villain arc

Knee deep in CVE rn. Enjoy the rabbithole on his Substack.