The most verifiable part of the “Burry short basket” story is simpler than the internet version: his last mandatory 13F for Scion explicitly lists very large put bets against Palantir and NVIDIA. The difficult part is Oracle: Oracle is not shown in the same Sep. 30, 2025 13F holdings table, so any “NVDA+PLTR+ORCL” basket framing must be pinned to other communications or other filings—not this one document.
What the filing actually discloses
Burry’s Sep. 30, 2025 13F is a two-name AI software/compute de-risking bet—on puts, not short stock
Reported put exposure (notional value)
$912.1M
Reported in Scion Asset Management 13F-HR for period ended Sep. 30, 2025 (filed Nov. 3, 2025): Palantir — Put, 5,000,000 share-equivalent
Reported put exposure (notional value)
$186.6M
Reported in Scion Asset Management 13F-HR for period ended Sep. 30, 2025 (filed Nov. 3, 2025): NVIDIA — Put, 1,000,000 share-equivalent
Oracle presence in the same table
Not found
In the same Sep. 30, 2025 13F-HR holdings table, Oracle is not listed as an option position
How to interpret the options disclosure
A 13F showing puts is not the same as a stock short—but it still targets valuation downside
13F-HR holdings tables record option positions in “value” and “share-equivalent” terms. The investor economics are straightforward: put holders benefit when the underlying price declines. For an “AI basket” thesis, the practical market read is that the investor was willing to pay for downside exposure in the consensus winners—especially where valuation and expectations have expanded.
What this changes versus a 1999/2000-style “macro bubble only” call is the selectivity: it isn’t just “tech is expensive.” The document ties risk to specific names—NVIDIA (compute bottleneck expectations) and Palantir (enterprise AI/government-software rerating). That combination behaves like a bet on multiple compression across the AI stack rather than a single-industry slowdown story.
Fundamentals check: did the financial profile justify “over-valuation risk”?
The companies aren’t in trouble—so the risk Burry targeted likely sits in multiple and durability assumptions
| Company | FY2023 revenue | FY2024 revenue | FY2025 revenue |
|---|---|---|---|
| NVIDIA | $26.97B | $60.92B | $130.50B |
| Palantir | $2.23B | $2.87B | $4.48B |
| Oracle | Not used in analysis | Not used in analysis | Not used in analysis |
Non-obvious mechanism
Why the “AI consensus basket” can de-rate even when revenue keeps rising
- Marginal compute demand can slow (still positive, just less explosive), shrinking incremental growth that high multiples price in.
- Enterprise AI adoption can lag even as models improve—driving “revenue timing” risk more than “revenue existence” risk.
- Cloud and customer capex cycles can reposition allocations, making bookings/contract ramps less smooth across the stack.
This is where the pair trade logic matters. NVIDIA sits at the hardware/accelerator chokepoint; Palantir is closer to software outcomes in enterprise/government. Buying puts on both simultaneously is consistent with a scenario where both the capex curve and the value-realization curve misalign—even if each company still reports earnings.
Supply-chain aware view
The bet is really on downstream capacity utilization and upstream pricing power assumptions
A full-stack AI drawdown typically propagates like this: semiconductor demand (accelerators) affects OEM and board-level pricing; hyperscalers and enterprises then govern the pace of training/inference deployments; software layers (platforms and decision tooling) rely on “effective usage” to convert spend into renewal and expansion.
So even though a 13F lists two names, the economic channel you should map is broader: accelerator utilization and networked deployments drive the software spend narrative. That’s why consensus “AI leaders” are often vulnerable together: when expectations reset, multiples compress across multiple tiers.
Horizons: what moves first vs. what changes later
In the short run, the hedge would react to guidance/ordering pace; in the long run, it would hinge on durability of AI monetization
- Short-term (weeks to a quarter): ordering cadence and margin commentary are the first “headline levers” that move AI-multiple stocks.
- Short-term: customer deployment timing (pilot-to-production conversion) can swing software sentiment faster than revenue totals.
- Long-term (1–3 years): AI spend’s share of enterprise budgets determines whether upside catches up to the valuation reset—or not.
- Long-term: ecosystem switching costs decide if software re-rates stick after a macro pullback.
Investor implication
How to use this: separate “what Burry actually filed” from “what traders say the basket is”
Listed stocks this “consensus AI de-rating” lens touches (and why)
- Put exposure targets a valuation reset, not a revenue collapse—FY2025 revenue rose to $130.5B, yet the hedge implies downside skew
- Multiple sensitivity is visible in earnings power: FY2025 net income reached $72.9B, so downside hinges on what’s assumed after this run-up
- Near-term catalysts likely center on guidance and demand cadence, because those drive expectations for the next growth leg
- Reported put exposure is the largest single AI-name bet in the filing at $912.1M notional value
- Strong fundamentals don’t remove expectation risk: FY2025 revenue was $4.48B with net income $1.63B, so the hedge is about durability/expansion assumptions
- Short-term movement likely tracks customer conversion narratives, which can change faster than annual revenue totals
- Oracle inclusion is not proven by the Sep. 30, 2025 13F table, so any “basket” claim needs a separate primary disclosure
- Because Oracle monetizes cloud/enterprise spend, de-ratings can occur via capex timing, but the filing evidence is absent for that specific period
- Watch for a verified linkage—e.g., a later 13F period explicitly listing ORCL option positions
