Jordi Visser / VisserLabs
Running Hot Into Scarcity: Why Bottlenecks Are the Risk to the AI “Bubbleâ€
TL;DR
- The market is undergoing a regime shift driven by inflation and severe physical bottlenecks, moving from an era of abundance to one defined by scarcity.
- AI's explosive demand for compute (requiring up to 1,000x more power than generative AI) is creating critical supply chain constraints in energy, chips, and raw materials.
- The current parabolic growth phase shows signs of exhaustion, demanding a shift from high-risk tech exposure toward assets with scarcity value like Silver and Bitcoin.
Summary
YouTube: https://www.youtube.com/watch?v=F3VFYNLFcLQ | Duration: 51 min | Pipeline: GPT-5.4 (v2.1 anchor-first)
â—† Search for the alpha
Visser’s core claim is not that the AI trade is fake or about to collapse like 2000. It is that scarcity is replacing abundance, and that this changes the risk phase of the whole cycle. He anchors that view with hard observations: he says he has already sold two-thirds of Micron and is now effectively out of all of it; he is instead accumulating silver and Bitcoin; CPI printed 0.6% month-on-month, taking year-over-year CPI to 3.8%; global yields are rising while inflation pressure broadens; the Strait of Hormuz has remained effectively shut since April; the Supreme Court issued a unanimous freight-broker ruling that he says could threaten 30% to 50% of freight brokers; the U.S. is facing its worst spring drought since 1895; and the Dodge Momentum Index is up 14.1% year-over-year, but commercial momentum falls from 37.2% to only 5.8% ex-data centers. The thesis derived from those anchors is that AI demand is real and secular, but the market is underpricing the friction: hoarding, logistics, energy stress, packaging constraints, and delivery delays can create speed crashes long before they kill the bigger trend.
- Portfolio action matters: he is not talking abstractly. He has de-risked Micron after a huge run and is rotating into silver and Bitcoin because they are not at 52-week highs and do not show the same bubble signs.
- Counter-consensus framing: this is not “dot-com 2.0.†He says the danger is not lack of financing but bottlenecks — a physical-world cap on a $90 trillion buildout.
- Macro regime shift: inflation, oil, and rising yields are moving together. AI strength has masked that pressure, but it has not removed it.
- Crowding and forced buying: sovereign wealth funds and asset managers have been “stopped into†the tape as buyers since May, chasing AI winners because they were structurally underweight.
- Semis warning signal: DRAM pricing momentum has already rolled negative while semiconductor relative performance is still rising — historically a setup that makes the semi trade more fragile.
- Korea as early-warning system: KOSPI machinery and construction, previously correlated to SK Hynix and the hot AI buildout, have started breaking down.
- The trade hierarchy is changing: sellers of AI inputs have cash flow today; hyperscalers are spending heavily now and only realize the payoff later, which means multiple compression can hit spenders even if the long-term thesis stays intact.
- Defensive AI rotation: if momentum breaks, he would rather reduce beta into names like power producers than keep pressing the hottest parabolas.
| Anchor | What Visser says | Why it matters |
|---|---|---|
| Micron position | He had already taken off 2/3 and is now effectively out of all of it | He is de-risking into strength, not calling the secular AI thesis dead |
| Rotation target | Accumulating silver and Bitcoin | Rolling bubbles: move toward scarcity assets without fresh bubble signs |
| CPI | 0.6% print; 3.8% YoY | Inflation is re-accelerating into an AI capex boom |
| Hormuz | Shutdown is an April event and still unresolved | Energy + shipping bottleneck is now structural, not headline noise |
| Freight ruling | Unanimous Supreme Court decision; potential extinction event for 30-50% of brokers | Supply-chain fragility can worsen even outside semis themselves |
| Drought | Worst U.S. spring drought since 1895 | Another non-oil inflation vector feeding scarcity |
| Dodge Momentum Index | +14.1% YoY; commercial +37.2%, but only +5.8% ex-data centers | Data centers are carrying the buildout almost by themselves |
| Exhaustion model | Extreme exhaustion bucket averaged about -4.1% on the Tuesday move | His momentum heat map is already flagging unwind risk in the hottest names |
| DRAM vs SOX/NDX | Negative DRAM rate-of-change now contrasts with still-rising semi relative performance | Historically a warning that semis become vulnerable to bad news |
| Valuation rebuttal | Since start of 2026 S&P up 8%, forward estimates up 13% | Multiples fell rather than expanded — not classic bubble math |
â–º Chapter summaries
Running hot into scarcity: the next AI risk phase is not a collapse of the theme, but a collision between parabolic demand and hard physical limits. (0:00)
Visser opens by saying this is a different video because several threads from the prior three weeks are starting to converge: inflation, pressure on the Fed, the possibility of higher yields, and what he sees as the next phase of parabolic moves. He reminds viewers that last year’s big parabolas included Palantir, gold, and silver — gold roughly doubling in a year and silver becoming a four- to five-bagger in his framing. He says those have since consolidated while new parabolic behavior has shifted into other parts of the market. The key personal disclosure comes early: he has been scaling out, had already taken off two-thirds of Micron, and is now effectively out of the whole position. Importantly, he frames that not as a bearish call on AI, and not as a desire to short it, but as a response to where the bubble signs are now most visible. He would rather accumulate silver and Bitcoin, which are not at 52-week highs and do not show the same exhaustion. The phrase “running hot into scarcity†becomes the lens for the whole video: a trade that was long scarcity and short abundance has massively outperformed, but now scarcity itself brings bottlenecks, shortages, and eventually changes in earnings.
Inflation is broadening, not fading: CPI, PPI, import prices, and negative real yields all point to a different regime than the post-ChatGPT disinflation window. (3:12)
He walks through the inflation data with a clear point: the issue is not just one hot print, but the regime shift behind it. CPI came in at 0.6% month-on-month, which pushes year-over-year CPI to 3.8%, and he notes that outside the COVID distortion this is one of the biggest prints since 2012. PPI came in even hotter. He overlays input costs, import prices, and CPI and argues that the setup is not merely an oil story; it is the combination of scarcity, hoarding, and the dramatic shift in AI compute demand. He also notes that since ChatGPT was democratized, rates had mostly stayed above CPI, but now CPI is breaking above short rates, producing negative yields. He widens the lens to global 30-year U.S. bonds, JGBs, German bonds, and gilts, saying the pressure is global, not just American. In his framing, the market’s traditional response to this kind of inflation and yield pressure should be negative, but AI earnings growth and momentum chasing have temporarily overwhelmed the macro drag.
Hormuz, freight, drought, and weather: scarcity is not one bottleneck but a stack of them, each adding friction to an already overheated system. (7:00)
Visser broadens scarcity beyond semiconductors. He argues that the unresolved Strait of Hormuz closure is now too important to ignore because the longer it remains shut, the more inflation pressure it exports into oil, shipping, and central-bank decisions. He then highlights a unanimous Supreme Court ruling on freight-broker liability, saying major industry players had warned this could become an extinction event for 30% to 50% of freight brokers and create large transport inefficiencies. He layers on the worst U.S. spring drought since 1895 and the crop report, plus the weather effects of El Niño, to show that scarcity is not a single-node problem. The point is not that all these factors hit the AI trade directly on the same day. It is that they all feed an economy already running hot, already hoarding inventory, and already trying to accelerate a giant capex cycle at once. That is the kind of backdrop where “small†supply shocks compound into larger market fragility.
Peak Q1 earnings may have pulled demand forward: the agentic AI shock, bonus depreciation, and competitive hoarding all hit together. (12:00)
This section is one of the most important in the video. Visser argues that Q1 was extraordinary because several catalysts arrived at the same time: the faster-than-expected rise of agentic AI, a sudden realization of demand, a strategic race for chips and infrastructure, and the “one big beautiful bill†with bonus capex depreciation that encouraged front-loading. In his reading, agentic demand made the need for chips, cooling, tubing, and optical infrastructure go parabolic. That then triggered competitive ordering, higher pricing pressure, and likely hoarding and over-ordering. Once Hormuz stayed shut in April, the bottleneck became more real. He is careful to say this is not a bearish thesis in the usual sense. It is a warning that in parabolic markets, when everyone is forced to buy and the inputs themselves become scarce, you should expect speed crashes and rising volatility even inside a still-valid secular theme.
Momentum exhaustion is no longer theoretical: South Korea, exhaustion buckets, and oil-sensitive correlations are already flashing warning signs. (14:00)
Visser references a special midweek video he made to flag a growing set of warning signals. The main point is that weakness is no longer isolated, and some of the first signs of contagion are showing up in South Korea, which he treats as one of the hottest and most informative AI markets in the world. He also describes an exhaustion model he updates weekly for subscribers, classifying names into extreme, elevated, somewhat exhausted, and low exhaustion buckets. When he tested the Tuesday move, the extreme exhaustion group showed an average move of around negative 4.1%, which he treats as confirmation that the heat map is working. He then points to KOSPI machinery and construction beginning to break relative to SK Hynix and other oil-sensitive, AI-linked names. For him, that is the sort of subtle correlation break that often matters more than a loud headline.
Parabolic subthemes are multiplying: power semis, sovereign-wealth-fund chasing, and benchmark arbitrage are all signs that the market is now overcrowded in the same trade. (18:00)
He turns next to a basket of power semiconductors he had recommended earlier and says the move in those names over less than a month has bothered him precisely because the demand has not even fully arrived yet. Much of the re-rating has simply been people front-running the future. He ties that to what he saw from Goldman’s trading desk: sovereign wealth funds and asset managers had been forced into the tape as buyers since the calendar flipped to May, in a highly concentrated AI momentum chase. This links back to his Institutional Investor article, “Your CapEx is My Opportunity: The Benchmark Arbitrage of the AI Buildout.†In plain English: many institutions were underweight the parts of the market that worked, and had to sell losers and buy winners to catch up. That benchmark arbitrage can last for years, but it also creates exactly the kind of crowded tape that becomes fragile once the rate of change slows.
DRAM is the canary: if memory pricing momentum is rolling over while semis still outperform, the trade becomes much more sensitive to bad news. (24:00)
Visser gives a more technical warning here. He overlays DRAM prices with the SOX relative to the NDX and says they have tracked each other well since 2017 using z-scores. Historically, when the six-month rate of change in DRAM prices rolls over, SOX relative performance versus the Nasdaq tends to roll over around the same time. In the current setup, DRAM pricing momentum has already turned negative while semiconductors are still rising relative to the broader tech complex. That is a dangerous mismatch because it means the semi trade can no longer rely on accelerating memory prices to keep sentiment and estimates moving in the same direction. Once that cushion is gone, any bad news — a supply-chain disruption, a policy headline, a geopolitical shock — can hit much harder. He also mentions Korea’s AI windfall-tax debate to show how crowded and politically visible the trade has become.
Micron and the five-year scorecard: this really has been the dominant trade, which is exactly why speed crashes become more likely after giant gains. (30:00)
Visser uses his own Micron chart to make the point concrete. He says he was fortunate to buy through a wide lower range and that in life, if you ever get a five- to eight-bagger, you should respect it. Even if Micron keeps going higher and he never gets another chance to buy it, he is comfortable being out. He then zooms out to compare Micron against the Mag 7 ex-Nvidia and notes that the name went from worst performer in early 2025 to by far the best. He also shows a five-year leaderboard where nearly every major winner has been an AI name. His point is not to deny the move. It is the opposite: because the move has been so real and so huge, people who missed it are now emotionally and structurally pressured to chase, which is exactly what creates the conditions for violent momentum reversals.
This is not bubble math in the classic sense: estimates have risen faster than prices, but supply-chain disruption could still hit earnings if production cannot keep up. (36:00)
One of Visser’s strongest rebuttals to the “everything is a bubble†crowd comes here. He notes that since the start of 2026 the S&P has risen by 8%, while consensus forward estimates have risen by 13%, which implies the multiple has actually gone down. In classic bubbles, multiples expand. That matters because it means current prices are being supported by real earnings revisions. But he immediately pivots to the risk: if Hormuz-related disruption feeds into semiconductor production, and if one part of the stack cannot be built, then the rest of the system cannot realize revenue on time either. Data-center demand is real, but if the shelf is empty, you cannot keep selling what is not there. That is why he keeps returning to the distinction between prices and throughput. High prices and high demand do not guarantee deliverable volume.
Hyperscalers versus suppliers: the market’s new leaders get cash flow today, while spenders risk multiple compression until capex turns into recognized revenue. (42:00)
In the final stretch he separates the AI ecosystem into two camps. The sellers — chipmakers, equipment names, memory, and related suppliers — are receiving cash flow today. The hyperscalers — Amazon, Microsoft, Meta, Google — are the spenders. Their earnings have not broken because capex can be depreciated and because the RPO pipeline is enormous, but that does not mean their multiples escape compression. He points out that Microsoft capex has reached 37% of revenue, and while there may be hundreds of billions in future revenue visibility, bottlenecks can delay realization. He also notes that the broader market would not have held up without the hyperscalers bouncing, yet those same hyperscalers remain down year-to-date relative to the S&P. That relative chart is one of the key things he is watching. His implication is subtle but important: even if AI remains the long-term winner, leadership inside the trade can keep rotating away from the spenders and toward those monetizing the capex immediately.
The practical takeaway: respect the secular trend, but trade it like a market built on parabolas, bottlenecks, and speed crashes. (49:00)
Visser closes by effectively telling investors to stop thinking in old business-cycle terms. This is not a normal consumer-versus-manufacturing cycle. It is an AI buildout that can still run for years, but it will do so through rolling bubbles, periodic unwind phases, and heavy dependence on physical-world inputs. Breadth in consumer-facing sectors is weak, the 1970s-style inflation comparison remains in his mind, and capex-heavy spenders are likely to face continued multiple compression. The correct posture, in his view, is neither denial nor maximalism. It is to stay with the secular trend while accepting that the next leg will be messier, more supply-constrained, and more violent than the market was pricing a few months ago.
Generated with algorithm v2.1-anchor-first · model openai-codex/gpt-5.4 · 2026-06-01T01:00:35Z
Transcript
Back from Florida and getting ready to head up to Maine for at least a week, maybe longer, and preparing for the move up there for the summer.
This will be a different video.
I really do believe that the combination of some of the things we've been talking about for the last three weeks is getting us ready for the next regime shift, which would be about inflation and the pressure it would put on the Fed, with yields possibly moving higher.
At the same time, everyone has now been forced in, and we clearly have the next phase of parabolas. I want to remind people, because I'm writing a paper on this, that last year the main parabolas of the year were Palantir, gold, and silver. Palantir had a similar move to what Micron has had over the last 18 months. Gold doubled in a year. Silver was a four- or five-bagger.
Those things have been consolidating, and in a world of bubbles, parabolas, and speed crashes, these things shift quickly.
There is absolutely no doubt that between the leverage ETFs and breadth breaking down, the market is now in a different position.
For me personally, I've been scaling out of things. I mentioned that I had taken two-thirds of Micron off. I am now, effectively, out of everything, definitely out of all of Micron.
That is not a negative view, and it is not me wanting to short this stuff. I will be looking to accumulate things, as I have been doing in silver and in Bitcoin. Those things are not at 52-week highs and do not have any bubble signs right now.
You're going to have rolling bubbles, but the agenda for today is hoarding, bottlenecks, and the next risk phase.
We're running hot into scarcity.
I wrote a paper this week on that exact subject. The government wanted to run the economy hot, but they are running it into scarcity. At the beginning of the year, my trade was short abundance and long scarcity. That has worked very well. It is not just the thematic portfolio that is up significantly this year. The other side was being short software. If you combine the two, you're talking about massive outperformance.
Now, five months into the year, the scarcity trade is becoming the dominant part, but scarcity brings bottlenecks, shortages, and changes in earnings. That's what I think is going to happen.
Let's go through the inflation data.
CPI came in in line, a 0.6 print, but it takes year-over-year CPI up to 3.8%, and it continues the trend. The important part is not just that it was 0.6. Outside of COVID, it is one of the largest prints since 2012.
PPI came in even hotter. This is not just an oil story. This is scarcity and hoarding tied to the dramatic shift in AI compute demand.
I've talked about shortages and model changes. I have moved almost completely to ChatGPT at this point. 5.5 is by far the best model. Codex has replaced Claude Code for me. I moved all of my OpenClaw-related work over to Codex 5.5 and saw amazing capability, especially while I was in Florida.
At this point, the compute shortage, the hoarding, the leapfrogging, and everything required to keep up with the first quarter's demand add up to a dramatic shift. OpenAI 4.5 and the move into the agentic world came much faster than anyone expected. It happened at the same time the one big beautiful bill and bonus capex depreciation were in place.
So hoarding is going on. Leapfrogging is going on. Revenues went higher. We have RPOs all over the place.
A lot of things are built into the market that can be delayed simply by not being able to build out data centers fast enough or get everything plugged in. That is where I think we are.
It is not a negative story, but you have to get used to AI cycles versus traditional consumer and manufacturing business cycles. AI cycles are part of a 90-trillion-dollar buildout that is going to happen, but we do not have enough supply for it. That means you're going to run into situations where something breaks.
Import price inflation is significantly higher. These numbers were already tracking high even before the war. That is important.
We are going in at levels that are much higher than what could have been expected. PPI, the input-cost side, overlaid with year-over-year CPI, makes the same point. I don't see how this avoids feeding into headline inflation unless it proves to be a temporary spike, and I don't think it is just temporary.
We are now back in a different regime.
Since ChatGPT was democratized and launched, rates had been above CPI. Now CPI is breaking above rates and three-month bills, so we have negative yields.
Around the globe, 30-year U.S. yields, 30-year JGBs, German yields, and gilts are all following the inflation situation. This is not just a U.S. thing.
There was no solution to Iran, so the Strait of Hormuz is still shut. That is the major issue. We are well past the point of ignoring the impact this is going to have.
It has obviously affected oil prices, but the longer it sits here, the more inflation pressure builds and the more pressure there is on central banks to respond and potentially raise rates.
Traditionally, that would be very negative for the market. But there have been two positives that have overwhelmed it. First, earnings growth dominated by the AI sectors has been far better than expected. Second, there has been a momentum chase, and I think we are close to the end of the biggest phase of that chase.
Supply-chain stress that peaked in COVID is moving higher again. The global supply-chain pressure index and the World Bank's supply-chain stress data are both reflecting new strain. You can see it in PPI, supplier delivery times, and everything else.
There was also a very important unanimous Supreme Court ruling this week that may not have reached most people's news feeds. The ruling shields freight brokers less than before and makes them potentially liable if they hire unsafe trucking companies. This could be an extinction event for 30% to 50% of freight brokers.
The issue is that it could create major supply inefficiencies and destroy hundreds of thousands of transport companies. The fact that it was unanimous means it is not likely to be reversed.
We also had the worst U.S. spring drought on record since 1895.
We got the crop report. Conditions are poor. These are all bad situations. El Niño is another thing you are going to hear more about this year. You can try to solve Hormuz. You cannot solve weather. This can become an issue for many countries around the globe, usually through dryness and fires.
I bring it up because when you combine Hormuz staying shut with weather-driven stress, inflation pressure broadens even further.
The bonus depreciation and front-loaded incentives allow companies to elevate earnings for now. The question is what happens when that rate of change shifts.
I put together a framework around peak Q1 earnings because people need to understand what happened. We had insatiable demand. The rise of agentic AI was not expected. The speed of adoption was not expected. Once agentic AI showed up, all of a sudden demand turned parabolic.
Parabolic demand means more chips, more cooling, more tubing, more optical fiber — everything. That sets off the strategic AI race. It coincides with the one big beautiful bill. Massive amounts of dollars start flowing through. RPOs build up. Companies are forced to compete with each other. That leads to all sorts of components being ordered.
The problem is there has almost certainly been over-ordering and hoarding. Even if it did not start that way, every week that goes by with the message that if you want it you need to buy it now pushes pricing pressure higher.
Then you add the Strait of Hormuz being shut down — an April event that is still real.
This is a big mistake for people to ignore now. There is risk here, and this is not a bearish thing in the normal sense. It is more that you have to be ready for speed crashes when you're in parabolas.
I did a special video this week to go through a growing set of warning signals suggesting the AI leaders may be entering their next phase of rising volatility or consolidation. What stands out is that weakness is no longer isolated. Signs of contagion are showing up in the hottest market in the world, South Korea.
I walked through the possibility of a momentum unwind. Last week I also highlighted the exhaustion model I upload every week for subscribers. It breaks things down into extreme exhaustion, elevated exhaustion, somewhat exhausted, and low exhaustion.
To test how it worked on Tuesday, I had OpenClaw calculate the average and median moves for each category. For the extreme exhaustion bucket, the average move was about negative 4.1. That told me the exhaustion model is working.
We've also seen oil-sensitive things that had been very correlated to SK Hynix start to break. SK Hynix is one of the key lines I watch. The KOSPI machinery index peaked and started to break down. Construction has also weakened. When I see that, it tells me not everything is benefiting anymore, and oil is part of the reason.
Another chart that bothered me was power semis.
I highlighted power semis back in late March. This is a basket of six names I recommended. In less than a month, they had enormous moves, and they have not even fully seen the demand yet. A lot of that move was simply because they were cheap.
The power-semi side is going to be driven partly by edge devices and partly by the DC conversion side, especially around Nvidia's 800V DC architecture. A lot of those things are still on the come.
When prices start moving that fast ahead of reality, that becomes a classic momentum trend. For people who made money on it, that's fantastic. But when you're trading parabolas, you have to be ready for the turn, and I think the probability of that turn is increasing.
Goldman Sachs' desk also bothered me. They said they had seen sovereign wealth funds and asset managers being stopped into the tape as buyers since the calendar flipped to May. A clear momentum chase, highly concentrated in AI.
This is the rotation I wrote about in Institutional Investor in my article, Your CapEx Is My Opportunity: The Benchmark Arbitrage of the AI Buildout. Institutions were underweight the things that were working and overweight the things that were not, so they had to chase. That benchmark arbitrage is what I have been trying to get RIAs and advisors to focus on. It will be a permanent part of the next decade, even though there will be temporary disruptions.
The thematic portfolio finished the week down 46 basis points. I don't show that because I think it was a good week. I show it because it had just had an enormous run. Everything related to capital goods is through the roof. The earnings are justified in terms of the rotation.
When I look at semis versus the Nasdaq, especially SOX over NDX, a big part of that is justified. The semis are winning relative to software and the hyperscaler spenders. If anyone says this is a bubble, the bubble is in the spending and the race to catch up.
There are two ways bubbles end. One is the dot-com version, which I do not think is the case. The other is that we run into bottlenecks. That is what I think this is.
I overlaid DRAM prices with SOX relative to NDX and found that going back to 2017, they track pretty well in z-score terms. Historically, when DRAM prices start to roll over in second derivative terms, SOX over NDX also tends to roll over.
Now, DRAM pricing momentum has turned negative. I would be very wary of that in semiconductors.
The risk is that once DRAM momentum rolls over, the semi trade becomes more sensitive to bad news because the market can no longer rely on accelerating memory prices to drive the story.
That is why the bottleneck matters so much. At this point, any kind of bad news becomes more dangerous because everyone is already in the trade. We are going to get episodic moves.
There was also an AI windfall-tax debate in Korea. Whether it happens or not, it shows how politically concentrated and visible this trade has become.
Momentum itself has become isolated to the AI trade. People have been trying to call the top of SMH versus software for some time, but it kept going higher. Now, after a two-and-a-half-bagger in a short amount of time, you need to respect the possibility of speed crashes.
The reason I am out of Micron is simple. I bought lower. I had a huge gain. If you get a five- to eight-bagger in your life, you should respect it. I may miss more upside. It may keep going. I may never get another chance to buy it. That would not surprise me. But I am still fine being out here.
When I compare Micron with the Mag 7 ex-Nvidia, Micron went from being the worst performer as of Q1 2025 to by far the best. That tells you how violent this rotation has been.
If you look at the winners over the last five years, nearly every top performer is an AI name. If you avoided this "bubble" for five years, you've missed a huge move. Some names are up 37 times. The move is real.
The question now is what it looks like a year from now.
I also showed data on the number of days with plus or minus 1.5% moves in the U.S. momentum index. Since the end of 2020, the trend is clearly higher. In the old QE world, this was not the norm. Now we are living in a period with much more frequent violent momentum shifts both up and down. This is what I mean by speed crashes and unwinds.
Estimate revisions are still massively positive. That is why it is hard to have a sustainable down move in the market without the red bars suddenly appearing or peaking. What I worry about more is a peak in revisions that then starts to move lower.
Because if the market had a parabolic move and revisions start to roll over, that is what causes the fall.
I also think Hormuz could create supply disruptions that feed into semiconductors and affect the ability to produce. Remember, when you are selling something, it is not only about high prices and strong demand. It is whether you can actually make the necessary volume. At some point, you may have sold everything off the shelf, and then there is nothing left to sell. If production cannot keep up, that is the issue.
The whole data-center stack is interconnected. One piece not getting built makes it difficult for the rest to get done. That creates real supply-chain correlation risk.
And again, I am talking about changing risk-reward because prices moved higher, earnings moved higher, and supply disruption remains unresolved. Hormuz has not been fixed. That means there could be a shift.
The estimate revision factor for the S&P still justifies the index moving higher. But if revisions start to move lower, that is where the issue begins.
Another reason not to listen too much to people screaming bubble is this: since the start of 2026, the S&P is up 8%, but consensus forward estimates are up 13%, which means the multiple has actually gone down. In bubbles, multiples go higher.
On the turbulent side, nothing has shown up yet, because this has all been one trade. Rates had not moved until Friday. Oil had moved higher, and that mattered, but the macro framework had not yet broken the trade.
Where we are seeing warning signs is in the divergence between the S&P and the VIX. The S&P is far above prior highs, but the VIX is also much higher than it was back then. That is a warning.
If you look at household durables, only four of twenty-six names are up on the year. In restaurants and retail, there are huge drawdowns. Breadth can be bad for a long time.
I still think we are in something like the 1970s, meaning up, down, up, down, up, down. Over the next decade, because of AI disruption, I think it will be very difficult for the capex spenders to avoid multiple compression.
Code2's reports make this point well. The fight right now is between the sellers of AI inputs and the hyperscaler buyers. The sellers are the new leaders because they have cash flow today, not sometime in the future. The hyperscalers are spending heavily now.
Their earnings are not being hurt yet because they get to depreciate capex, so they still get an earnings boom. They still have significant pricing power and all-time high margins. But if you look at free cash flow relative to capex, they are being penalized. Their multiples are coming down gradually.
That is the tradeoff. Some of these supplier names have doubled, and they are doing it at the expense of the hyperscalers.
Microsoft now has capex equal to 37% of revenue. Yes, there is a huge RPO backlog and future revenue visibility, but if bottlenecks last too long, they will not be able to realize those revenues on schedule.
The market would not have gone higher without the hyperscalers bouncing. The semis would not have worked without that bounce. Retail would not have joined to this degree without that bounce. But even so, the hyperscalers remain the chart I am watching, because year to date they are still down relative to the S&P.
So the practical takeaway is this:
The secular AI trend is real.
The scarcity trade is real.
The earnings have justified much of the move.
But the next phase is about bottlenecks, hoarding, logistics, weather, freight, energy, and speed crashes.
That is the risk phase we are entering, and it is one investors need to understand without confusing it for the end of the AI story itself.