Burry Being Burry……
“Fundamentally, I am moving timelines up.”
That’s Michael Burry talking about the AI bubble.
And apparently, something he found over the weekend changed his mind about when it could burst.
By Monday, he had covered every common-stock short in his portfolio.
But he wasn’t backing away from the bet.
He was adding leverage to it.
Burry replaced nearly all of those shorts with put options, saying his latest research convinced him the AI bubble could burst “sooner than later.”
That’s a fairly meaningful portfolio change from someone who was already positioned for AI stocks to fall.
So, what did Burry find over the weekend?
Let’s dug into it. ⇩
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Short Story, Long Puts……
Burry’s Monday portfolio update was extensive.
He covered his common-stock shorts in Micron, Nebius, Caterpillar, SOXX, CoreWeave, Nvidia, Palantir and Oracle.
Then he rebuilt almost the entire bearish book with put options:
→ Micron MU ( ▲ 0.0% ) : June puts, around the $500 strike
→ Nebius NBIS ( ▼ 0.62% ) : June puts, double-digit strikes
→ Caterpillar CAT ( ▼ 1.92% ) : December 2027 puts, around $400
→ SOXX SOXX ( ▲ 0.21% ) : September 2027 puts, low $400s
→ Palantir PLTR ( ▲ 0.04% ) : enlarged September 2027 put position, low $100s
→ Nvidia NVDA ( ▲ 0.52% ): September 2027 puts, mid-$100s
→ Oracle ORCL ( ▼ 0.36% ) : December 2027 puts, mid-double-digit strikes
CoreWeave was the exception. Burry covered the short but said he hadn’t found puts at a price he liked.
He also rolled his existing QQQ puts into a larger Nasdaq-100 put position and opened a new bearish position in MetLife, using longer-dated puts.
Why make the switch?
Leverage.
Put options allow Burry to express a larger bearish position with less upfront capital, while limiting his maximum loss on the options to the premium paid.↓
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Why Puts Change the Bet?
Shorting a stock and buying a put can express the same opinion.
The stock goes down. You make money.
But the math is very different.
A traditional short requires substantial capital to support the position, and the payoff generally moves with the stock.
Puts can provide similar market exposure for a fraction of the upfront capital.
That means Burry can use the same amount of money to make a much larger bearish bet, while his maximum loss on the option itself is limited to the premium paid.
There’s a catch: puts expire.
If the decline comes too late, even the right thesis can lose money.
Which helps explain Burry’s change of strategy.
He now believes the AI unwind could happen “sooner than later.”
A shorter timeline makes the expiration clock less intimidating — and the extra leverage, in Burry’s words, “more palatable.”
✱ Same bearish thesis. Much less room for being early.
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Déjà Vu…
So, what changed Burry’s mind?
Start with 2.07%.
That’s net capital investment across the S&P 500 as a share of U.S. GDP as of June 30, according to Burry’s research.
✱ In plain English, net investment is what companies are spending on new assets after subtracting depreciation on the assets they already own.
And 2.07% is unusually high.
Burry says only one period in nearly four decades went higher:
→ The aftermath of the March 2000 dot-com peak.
What happened next wasn’t pretty.
As the dot-com infrastructure boom unwound, depreciation and write-downs eventually overtook new investment. Burry says S&P 500 net investment stayed negative for 12 consecutive quarters, from mid-2003 through mid-2006.
→ That’s the pattern he’s watching today.
AI spending is still climbing, and Burry expects that to continue for another few quarters.
But in his framework, the bill for all that investment tends to arrive later — when companies discover that some of the assets they’ve spent heavily on aren’t worth as much as expected.
His earlier estimate put that reckoning around 2028 or 2029.
After this weekend’s research, he’s now telling investors he’s “moving timelines up.”
Exactly how far? He hasn’t said.
The Commitments Add Up…
Burry’s concern isn’t just how much Big Tech is spending today.
He’s looking at how much has already been committed for tomorrow.
By his calculations:
→ Microsoft MSFT ( ▲ 0.77% ): more than $300 billion in uncommenced leases, nearly triple the previous level.
→ Amazon AMZN ( ▲ 1.01% ) : roughly $267 billion in leases and purchase commitments, up 81% in nine months.
→ Meta META ( ▼ 1.84% ) : roughly $700 billion in off-balance-sheet commitments.
→ Alphabet GOOG ( ▲ 1.01% ) : nearly $900 billion in commitments and other exposures, including AI-related deals Burry describes as circular.
Amazon’s long-term debt also doubled to $128.9 billion over the same period, by his count.
Those figures aren’t directly comparable accounting line items, but Burry’s argument is simple:
Big Tech is making enormous AI commitments while the useful life of today’s hardware remains uncertain.
Longer depreciation schedules and greater use of leases can spread those costs over time.
Burry believes that makes the AI buildout look less capital-intensive on paper than the commitments suggest.
And among the companies he’s been studying, one stands out.
Oracle ORCL ( ▼ 0.36% )↓
Eyes on Oracle?
Oracle has $664 billion in contracted future revenue and, according to the data Burry cites, carries debt equal to roughly 4.3× EBITDA — well above the other major tech companies in his comparison.
But Burry is focused on something more specific:
$11.4 billion in customer prepayments.
Some of those contracts contain what Oracle calls a “significant financing component.”
Under accounting rule ASC 606, that means part of the upfront payment is treated like financing from the customer. Oracle records interest on it, then recognizes a larger amount of revenue over the life of the contract.
Burry estimates the structure could increase the future cloud revenue recognized from those contracts by nearly 20%.
Meanwhile, the associated financing cost appears in interest expense, rather than operating expenses.
Why does he care?
Because operating margin is one of the metrics Oracle emphasizes when discussing the economics of its cloud business.
So Burry’s argument is what investors should make of the resulting numbers.
And Oracle has an answer for the broader concern.
✱ Its GPUs, the company says, may be holding their value considerably better than skeptics expect.
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