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Table of Contents
🔥 Here’s What’s Happening Now
The bears tried to sell the market off early, but failed. NVDAs deal with Open AI (more below) was the major news. Lots of Fed speakers this week, and except for Miran yesterday, the others were hawkish. TLT continued it’s drop…..
As I’ve said before, if the bond guys are bearish and the stock guys are bullish, I’d side with the bond guys. One also has to wonder why Gold is behaving like an AI stock, it’s up again pre market also….
Those of your familiar with my version of the Permanent Portfolio know I think you should have a fixed allocation, and a rather large one, to precious metals. If you aren’t in gold now though I’d wait for some sort of pullback.
I also think you need a fixed crypto allocation. Bitcoin is still struggling below it’s 50 day, I’d look for some signs of a bottom before buying the dip. Perhaps $110k or $108K….
Ethereum is also below the 50 day. I’d look for a potential undercut and rally in the 4,060 area…..
Remember, it’s not crypto OR precious metals, it’s crypto AND precious metals…
I’d either be putting money in all….
Or buying dips when you get them.
I’ve said before that Argentina was my best trade last year, this year it has sucked. Possibly a bottom here though…..
🧠 Nvidia–OpenAI “circularity”: smart vendor financing or a bubble fuse?
The NVDA Open AI deal was the big story yesterday. Got a call from a hedge fund manager last night wondering how this wasn’t a Ponzi scheme. I suppose it isn’t as I go into detail below, but definitely feels strange.
As I’ve often said, I believe this market is being held up by AI capex spending, but with nobody really making money on AI you have to wonder if the industry has it’s “where’s the beef?” moment and the spending slows.
Things like this have to be in the back of your mind, which is why I think it’s imperative to always have hedges and design your trades for asymmetric returns…..
Do I think you should decide this is the top and go short or get out? No, you will only know the top in hindsight. Trade based on what you see, not what you think. What you see is a bull market. If you always have hedges in place then you can sleep at night. You should have a systematic way to add hedges and reduce equity exposure (more on that in my webinar next week: register below) when the market starts to turn down.
Now to the deal…..
What happened
Nvidia will invest up to $100B in OpenAI and similar, cash-constrained AI players. For every $10B NVDA invests, OpenAI will spend ~$35B on Nvidia chips—at lower margins to OpenAI (i.e., effectively a discount) but with demand “pre-funded” and credit risk reduced. NewStreet calls this demand backstopping.
OpenAI’s model is still loss-making (management guided to ~$44B cumulative losses through 2029 before first profit) and has layered in enormous multiyear chip and data-center commitments (e.g., Oracle, Broadcom). Financing these without help was expensive—~15% debt on projects linked to startup credit risk vs 6–9% when backed by Microsoft-grade counterparties.
Nvidia is doing this broadly: 7% of CoreWeave, a $6.3B “buy-back unused capacity” pact, $5B into Intel to co-develop parts and expand attach, plus strategic investments in xAI and others. The market rewarded it—+$160B to NVDA’s market cap on the OpenAI news alone. (All per the WSJ summary you shared.)
Is this a Ponzi? My expert take
No—but it is vendor financing at a massive scale, and we’ve seen that movie before. Telecom gear in 1999–2001, solar yieldcos in 2014–15, even some SaaS channel financing: the leader lends/backs the customer to pull forward demand and establish platform dominance. It works—until end-market cash flows fail to show up.
Why it’s rational for NVDA:
Secures multi-year share of the scarce bottleneck (state-of-the-art GPUs + networking).
Lowers customers’ cost of capital → larger clusters → faster platform effects for Nvidia software (CUDA, networking, SDKs).
Even with discounts, the lifetime value of the ecosystem (chips, systems, software, services) can dwarf the margin give-up.
Why it’s risky:
If AI unit economics (training → inference → enterprise value) don’t improve, customers can’t self-fund.
Capex reflexivity: NVDA equity strength funds demand, which supports NVDA equity. If growth wobbles, the loop works in reverse.
Concentration risk: Moody’s already flagged Oracle’s OpenAI exposure. If OpenAI delays or scales back, second-order providers (clouds, colos) feel it quickly.
History rhymes: Telecom vendor financing blew up when traffic/revenue lagged; stocks repriced brutally 2000–2002.
Bottom line: Not a Ponzi—strategic vendor financing in a capacity-constrained market. But execution risk now sits at the “AI application” layer: if monetization lags and capex growth slows, long-duration AI infrastructure equities will de-rate.
What breaks the loop (or validates it)
Green lights (bull):
Enterprise inference revenue ramps (agents, copilots, RAG on proprietary data) with measurable ROI.
Cloud AI revenues and RPO→billings→revenue cadence march higher; utilization stays >80%.
Power constraints are solved (nuclear PPAs, long-dated contracts), keeping cost per token trending down.
Red lights (bear):
Utilization slippage at “neo-clouds” and startup tenants; capex deferrals; cancellations/renegotiations.
Enterprise AI pilots stall at POCs; CFOs push back on budgets; pricing compresses for inference APIs.
Credit risk creeps up—more “negative outlook” warnings like Oracle’s OpenAI exposure; funding rates rise.
Could we see a 2000–2002-style event?
A full dot-com bust requires broad earnings misses + credit tightening + overbuild. I’d not base-case that for Nvidia itself—training remains a real bottleneck and NVDA still has product cadence + software moat. But a mini-2000 is absolutely possible in the periphery if capex growth slows:
Vulnerable: neo-clouds, second-tier data-center builders, overvalued AI software with thin gross margins, and equipment names levered to one hyperscaler/customer.
Resilient: core bottlenecks (NVDA; HBM memory leaders; high-end optics; best-in-class semicap), and power/fuel cycle (utilities with nuclear baseload, enrichment).
Winners / Losers — ranked (12–24 mo)
🏆 First order (core bottlenecks)
NVIDIA (NVDA) — 9/10: Still the scarce input; backstops demand, expands attach (networks, software). Watch gross margin (discounts), utilization, product cadence.
HBM memory: SK Hynix / Micron (MU) — 8–8.5/10: Every GPU cluster is HBM-intensive; margins far better than legacy DRAM.
High-speed networking & optics: Broadcom (AVGO), Arista (ANET), Credo (CRDO) — 8–8.5/10: AI fabrics scale with cluster size.
Semicap tools: AMAT/LRCX/KLAC — 8–8.5/10: Foundry/packaging capex remains elevated to feed AI chips.
⚙️ Second order (capacity → compute → power)
Hyperscalers: MSFT/GOOGL/META/ORCL — 8–8.5/10: If RPO converts and PPAs secure cheap power, they keep winning share; ORCL most sensitive to OpenAI execution.
Power & nuclear: CEG/NEE — 8/10: AI PPAs + subsidy floors = durable CF.
Fuel cycle: LEU/CCJ — 8–9/10: Enrichment and uranium are the new chokepoints if nuclear scales.
🧪 Third order (applications & services)
Data/ops platforms: SNOW/NOW/DDOG — 7.5–8/10: If AI moves from sizzle to workflows, they monetize consumption + price/mix.
IT services/integrators: ACN/EPAM/GLOB — 7.5/10: Agentic AI + multi-model reality favors expert services.
❌ At risk / “show me”
Cash-hungry AI startups / neo-clouds reliant on vendor financing — 5–6/10: Funding and utilization sensitive; could get hit if capex slows.
Generic DC REITs without high-density liquid cooling — 5.5–6/10.
On-prem server vendors (low AI attach) — 5–6/10: The spend is in hyperscale.
ARM-centric PC AI hopes if NVDA–INTC synergy gains traction — watch this space.
Positioning
Own cyber (PANW/CRWD/ZS/CYBR) and nuclear power (CEG/NEE) against the top two real-world constraints: data/security and energy.
Stay overweight NVDA / HBM memory / networking / semicap — the bottlenecks; use pullbacks to add.
A barbell — core infra + selective application platforms that show net-revenue retention uplift from AI (not just PRs).
Track RPO→billings at clouds, utilization at DCs, NVDA gross margin (discounts), and credit spreads on AI-linked DC debt. Those will call the next move.
Nvidia’s OpenAI deal isn’t a Ponzi—it’s vendor financing on steroids. It can extend the boom if AI applications start paying their own way; if capex growth slows before ROIs show up, the periphery (neo-clouds, second-tier infra) gets hit first. Stick with the bottlenecks (NVDA/HBM/optics/semicap) and the power stack; trade the rest with a strong BS detector.
The Investment Strategy Wall Street Hopes You Never Discover
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-Why the 60/40 strategy is dead and what to do instead
- How to use AI to uncover today and tomorrow's hottest themes
- 4 unknown edges that still exist in today's market
- How to set up your portfolio for asymmetrical returns
- Little-known asset class that has limited risk and potentially unlimited returns
- 4 ways to hedge your portfolio that don't include bonds
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📈 Stock Corner
Today’s stock is CoreWeave (CRWV)……
Full disclosure, we have the 2x (CRWU). Stock made an undercut and rally at the 10 and 50 day and is getting a few brokerage firm upgrades.
🤝 Before You Go Some Ways I Can Help
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Inside HEAT: Our Monthly Live Call on What Wall Street Doesn’t Want You To Know
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Tuttle Wealth Management: Your Wealth Unshackled
Advanced HEAT Insights: Matt’s Inner Circle, Your Financial Edge
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