Let’s start with an anecdote before we move on to more structural things I’m seeing.
On the morning of July 30, a hedge fund sold its entire public equity portfolio in a single block trade before the opening bell. Longs and shorts together, the whole book, handed to Citadel in one transaction. Six trading days earlier, that same portfolio was sitting on a 439% net return for the year.
Ooops!
The fund we’re talking about – you already know it – is Situational Awareness LP, run by Leopold Aschenbrenner, who is twenty-four years old and wrote what a lot of people consider the defining investment memo of the AGI era.
He had turned roughly $225 million of seed capital into a book worth tens of billions in under two years. Reports on the exact size vary quite a bit, somewhere between $20 billion and $45 billion depending on which outlet you read.
Apparently using 4x gross leverage, concentrated across the AI infrastructure stack:
power generation,
data centers,
memory.
Then Korean semiconductors wobbled. Under a week later, it was finished.
I published a piece in early June called “Navigating the Froth: 6 Alternative Signs of a Market Top,“ where I laid out six alternative signs that we were somewhere late in this cycle.
Chip workers in Seoul buying Ferraris with their bonuses.
Jensen Huang being chased through a Taipei night market by food bloggers.
Three private companies queuing up to go public at a trillion dollars each.
Berkshire’s cash pile going vertical.
And more.
Those six had something in common that I did not fully appreciate when I wrote them. You could see all of them from across the room.
There is a line on my Market Sentiment Cheat Sheet that has aged well: bottoms scream, tops whisper.
In the weeks since that piece, the whispers have moved somewhere considerably harder to look. Into special purpose vehicles. Into lease classifications. Into a single sentence about useful-life assumptions in an earnings call.
Before we start, let me deal with an objection I hear most often these days:
We cannot be in a bubble if this many people are calling it a bubble.
I don’t find that argument persuasive for a straightforward reason: you are not observing the market when you scroll your feed, you are observing an algorithm that has learned what keeps you engaged. Fintwit did not exist in 1999. It did not exist in 2007. The fact that your timeline is saturated with bubble talk tells you something about your timeline, your echo chamber, but very little about aggregate positioning.
And positioning is the thing. Saying you think the market is expensive costs nothing. What people are doing with their money looks quite different from what they are saying with their words. That’s one of the first principles I learned about Buffett - watch what he does, and not what he says.
In this piece, I want to discuss eight new signs that we may be approaching a market top and the end of the long-lasting bull run.
Here is the structure:
Systemic Leverage
When the Supplier Becomes the Customer’s Bank
The Cash Flow Machines Start Borrowing
Reading the Footnotes Instead of the Headline
Common Sense ROIIC Check – The Arithmetic Nobody Wants To Confront
The Electricity May Not Exist
The Customers Aren’t Getting Their Money’s Worth
Common Sense Test #2 – This Time: Valuation
Final Thoughts
Disclaimer: The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.
1. System Leverage – Aschenbrenner Is Just One Anecdote
Aschenbrenner’s thesis was arguably right. Power, data centers, and memory were precisely where the money went in 2025 and the first half of 2026. What ended him was the financing structure sitting on top of that thesis.
Run four times gross leverage and a 25% drawdown erases your equity. You lose the option of being right eventually. Your prime broker decides when the position closes, and makes that call during the worst week rather than the best one.
Note what did the damage. Korean semiconductors, specifically the pressure around SK Hynix’s US listing. In my June piece, I wrote about the KOSPI as a national index trading with the volatility of a micro cap, more than half its weight in two chip companies. Concentration of that sort is wonderful on the way up.
One fund blowing up may be an anecdote. I get that. But this isn’t a single incident. It is more systemic.
In mid-July, apparently, 1 in 30 (3.4%) adults got margin called.
FINRA margin debt, the total amount of money that investors borrow from their brokerage firms to buy stocks and other securities using their current investments as collateral, hit $1.502 trillion in June, an all-time high, up 51.5% year over year and still up 46.3% after inflation.
As I argued in June, this indicator on its own is a lousy timing tool. What it measures well is fragility, which tells you how violent the adjustment will be when things go south, without telling you when exactly.
And the metric above may even understate how levered up investors are, possibly badly, because it captures margin lending at broker-dealers while missing the leverage embedded inside the products retail increasingly buys as default exposure.
Nobody holding those products will ever get a margin call, and that is the problem. When an individual buys a leveraged ETF (like a 3x S&P 500 fund), the leverage exists inside the fund's structure via total return swaps and futures contracts. A daily-reset fund must thus rebalance at the close to maintain its target multiple, so it mechanically sells into declines. The forced selling still happens, on schedule, inside the fund, without anyone experiencing the moment of panic that would normally make an investor reconsider what they own.
When the market goes UP: The fund’s asset base grows faster than its debt/exposure ratio. To restore a 3x target for the next day, it must buy more exposure at higher prices.
When the market goes DOWN: The fund’s assets shrink faster than its exposure. To bring its leverage ratio back down to 3x (and avoid being over-leveraged for the next day), it must sell exposure at lower prices.
Related to this, I guess, Arne Ulland made an observation that stuck with me (read his thoughts here): watch how fast people dump enormous, established businesses on a single bad headline. Few built their position by understanding the firm well enough to hold through a bad quarter, so they use trailing stops, then buy back after the recovery. Li Lu once called rotation the rarest gift in investing. What we have instead is a market where much of the float is held by people who pre-committed to selling at a price rather than at a thesis, on record margin, in products that liquidate themselves on the way down.
A levered holder is not really a holder. They are a renter, and the margin clerk owns the building.
2. When the Supplier Becomes the Customer’s Bank
Nvidia is reportedly in talks to backstop as much as $250 billion so OpenAI can lease computing power from a ten-gigawatt project in Pike County, Ohio, with a separate arrangement to help finance OpenAI’s purchase of some $350 billion of chips. Bloomberg puts the total slate of fresh deals above $750 billion.
“Nvidia Corp. is working on AI infrastructure deals potentially worth more than $750 billion, including an artificial intelligence initiative with SK Hynix Inc.’s parent worth more than $500 billion.” - Bloomberg
Here is the number that made me put my coffee down (admittedly, I looked a little more shocked than in the image below) …
Nvidia’s own Q1 fiscal 2027 10-Q caps total lease-guarantee exposure at $3.5 billion.
A $250 billion commitment would run roughly seventy-one times the entire guarantee book it currently discloses.
How times can change.
The term “circular financing” gets thrown around frequently these days without much precision. A supplier provides capital, or a guarantee that unlocks someone else’s capital, to a customer, who then buys the supplier’s product. The supplier books revenue at shipment while the risk moves onto its balance sheet. Demand looks robust, growth looks organic, and the accounts record something economically closer to the supplier buying its own products with extra steps.
The bull response is that these arrangements are immaterial at Nvidia’s scale.
The writer behind Dirt Cheap Stocks gave the most economical rebuttal I have read in his piece from two months ago titled “Calling the Top“:
“if it’s immaterial, why would you engage in the behavior at all?”
We ran this experiment in 1999, when telecom equipment makers lent enormous sums to carriers so those carriers could buy equipment. Lucent alone committed $8.1 billion, and McKinsey later put nine suppliers’ combined exposure around $25.6 billion. The customers could never generate the revenue to repay, Lucent’s sales fell 69% from their peak, and it wrote off roughly $3.5 billion of customer loans.
The detail worth holding onto is what the vendors did as conditions deteriorated. When outside capital fled in early 2001, they accelerated financing rather than pulling back, because slowing down meant admitting the previous two years of revenue were partly manufactured. That entire nine-supplier complex committed about $47 billion in today’s money (accounting for ~80–85% cumulative inflation over the past 25 years).
In today’s instance, we are discussing one supplier contemplating $250 billion.
One other number in Nvidia’s filings stands out too: the share of its receivables tied to major customers has gone from an average of roughly 23.8% across fiscal 2020 to 2024 to about 64% in its latest quarter.
“Three direct customers accounted for 30%, 18%, and 16% of our accounts receivable balance as of April 26, 2026. Three direct customers accounted for 25%, 18%, and 13% of our accounts receivable balance as of January 25, 2026.”
Of course, during fiscal years 2020 through 2024, Nvidia’s business was far more balanced across PC gaming, professional visualization, and automotive clients, and as the generative AI boom accelerated through FY2025 and FY2026, Nvidia’s Data Center segment expanded to represent nearly 90% of total company revenue. Still, I find this a remarkable level of concentration.
Now, this heavy customer concentration is a direct structural byproduct of the hyper-consolidated AI infrastructure boom. Because training and deploying frontier AI systems requires tens of billions of dollars per quarter in capital expenditure, purchasing power is concentrated almost exclusively among a small circle of hyperscalers (widely identified by Wall Street as Microsoft, Meta, and Amazon) alongside key server integrators. Clearly, those are cash-flowing machines throwing of billions and billions in cash flow. But the required CapEx may be too much of a burden even for those players, which leads to signal number 3.
3. The Cash Flow Machines Start Borrowing
For fifteen years, the defining financial trait of big tech was that it did not need anyone’s money. Microsoft still carries a AAA rating, one of two left in America. That era has ended fast enough that most investors have not repriced what these companies now are.
Amazon, Alphabet, Meta and Oracle issued roughly $194 billion of bonds in 2026 through July 7 alone, according to Reuters' analysis, against about $108 billion in all of 2025. Meta’s October deal was $30 billion in one shot, the largest individual non-M&A high-grade bond sale on record. Oracle is the one to watch, sitting at BBB while participating in the same build-out as counterparties rated AAA. The marginal borrower always breaks first.
What concerns me more is largely invisible on the balance sheet. Meta’s Hyperion campus is financed through a vehicle called Beignet Investor LLC, which raised roughly $27 billion in private notes from Pimco, BlackRock and Apollo. Blue Owl holds 80%, Meta 20%. Because Meta is a minority partner, that $27 billion never appears as a liability in its accounts. It’s an off-balance sheet liability – another late-cycle symptom?
Meta also provides a residual value guarantee covering the first sixteen years. If the campus is worth less than an agreed threshold when a lease ends, Meta makes up the shortfall in cash. Read that again and ask who bears the asset risk. The debt moved. The risk did not. IFR (International Financing Review), about as sober a credit publication as exists, ran its analysis under the headline “off-balance-sheet gymnastics 24 years after Enron.”
“The contradiction at the heart of Meta’s Hyperion financing is between the bond ratings and Meta’s proposed accounting treatment. If you follow the cash, Beignet’s bond is almost pure Meta exposure. Meta funds the construction risk; Meta’s rent and Meta’s residual value guarantee service the debt; and Meta is the party that suffers if demand for AI computing disappoints.
If Meta ever walks away from the project, the RVG obliges it to write a cheque that, together with whatever the campus (or part thereof) can be sold for, makes bondholders whole. The RVG runs for 16 years and is triggered if Meta fails to renew a lease at expiry, terminates early or defaults under the lease. Any one of these leads to a payment of a “guaranteed minimum value” that is sized so the bond can be repaid, either from the underlying sale proceeds or directly by Meta. The final four years of the bond are not covered by the RVG but by a termination fee equal to the outstanding balance at that point.“ - IFR
Debt has been trending upward across all Big Tech names …
… and Meta stands out to me here as the quality of its balance sheet has deteriorated the most in terms of total debt recently.
One exchange from Meta’s latest call is also worth your attention. Youssef Squali asked Susan Li directly about the growing pile of off-balance-sheet obligations and whether Meta would consider issuing equity to fund some of this. She pointed him to the disclosures and said they would evaluate all financing options for 2027. She did not rule out equity. A CFO with a comfortable funding picture rules out equity, because doing so is free and reassuring.
The reason shows up in the cash flow forecasts. Alphabet just reported its first quarter of negative FCF in its history.
Meta’s is expected to turn negative in 2026 and reach around negative $24 billion in 2027. Amazon’s is projected to be negative this year.
Companies do not borrow at this scale because borrowing is cheap. They borrow because internal cash no longer covers the plan.
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