B. Funk (@B_Funk_) header
B. Funk (@B_Funk_) profile picture

stocks, options (none of it is advice), I’m an expert at knowing experts are rarely right. However, I stayed at a Holiday Inn Express last night

Joined August 2020
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Buying $AAPL thinking they are winning by not spending a dime on AI, while selling $META $GOOGL $MSFT $AMZN $SPCX because they are spending a ton on AI, will be looked back as being one of the worst investing decisions/market narratives in history.
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Five years from now young investors will look back at this market and realize what an extraordinary opportunity fear created. And that opportunity could get even bigger in the days and weeks ahead. Nothing creates greater price misallocations than fear and greed. We’re living through one of those moments right now. And with fear creating opportunities in some of the world’s strongest businesses there’s little reason to take on the added risk of speculative companies.
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That was a great quarter by $AMZN and the AWS guide for ‘27 & ‘28 of 40% plus is extraordinary. $META $AMZN $SPCX the best to own over the next few years. They all control their own destinies, don’t have any businesses that are being cannibalized, or any real competition for its Core Business(es). If they spend appropriately and innovate, they will be huge winners and the best risk/reward.
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I have no skin in the $TWLO game, but down 13% after those numbers and guide? Weird
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Companies sell when they are forced to, or when they think things can’t get any better. $LITE selling, $ORCL guiding to a CAPEX peak in ‘28.
$MRVL is down over 10% following reports it's looking to acquire $LITE and combine its chip business with one of AI networking's leading optical suppliers.. But with Lumentum's laser capacity reportedly sold out through 2029 why would it even consider selling now?
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Maybe Zuck is right when he says $META hasn’t found any upward limit for its compute needs. This is great for $META & $SPCX
$GOOGL Alphabet CFO: "With respect to cloud margins, given the supply constraint environment, we started utilizing third-party compute capacity at the end of Q3, and will ramp usage in Q4. We expect margin headwinds in the near term as we utilize this capacity."
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Just own $SPCX & $META. It will make things a lot easier over the next few years. Currently 50% of my growth portfolio and I will add lower. Both Q’s look even more amazing tonight.
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The $META quarter just became even more impressive.
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$AAOI now trading 1x July’27 forecast ARR. What are these, iron ore companies?
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Hey @NBA you’re league is a joke.
GIANNIS JUST “PASSED TO HIMSELF” IN TRANSITION, TOOK ABOUT 47 STEPS, AND THEY CALLED IT A BUCKET… You literally cannot pass the ball to yourself in the NBA. That’s a travel every single time at every level… But superstar privilege is alive and well. Refs let him Euro-step from half court like it’s nothing… This is why casual fans tune out. Same rules don’t apply to everyone… How many more of these “missed” calls are we supposed to ignore this season?
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The world’s most accomplished tech founders and business leaders are betting hundreds of billions on AI with extraordinary conviction. Meanwhile much of the investing world thinks they’re making a massive mistake. The irony is hard to ignore. An investment industry where very few have historically managed to beat a passive index is now questioning the judgment of the people building the technology and running the businesses that will put it to work. Maybe the investors are right. Maybe the builders are. But I can’t remember a time when the stakes were this high and the two sides saw the future so differently.
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Just another year of the nba being trash. Unwatchable.
It’s now a foul on the defender if he doesn’t touch Shai Gilgeous-Alexander. To be fair, Harper did make contact with SGA’s shoulder…when Shai threw it into Harper’s chest 😂😂
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$META sell-off is comical. They are growing their CORE business 20% plus and introducing new revenue streams with insane take-up that will also become multi-billion income streams…and doing it all at less than 1x PEG, and below a market multiple. And they have over 50% of the entire world 16 years and older as a built in user base. Thanks for the shares back in the 600’s. You have all lost your minds.
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Elon & $SPCX just single- handedly put the AI compute bear case to bed. Low valuations, terrible sentiment, mid-term election year, earnings acceleration, top in rates, top in oil, with the next 8 months historically being the most favorable period for stocks. A lot of people who’ve sold in the past couple of weeks are going to regret it next year.
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Been obsessed with the stock market since I was a teenager. Have traded through the dotcom bubble, the financial crisis and just about every market mania since. But I’ve never seen anything like the skepticism surrounding AI. Not even close. Every time one bubble narrative falls apart a new one takes its place. Rumors become headlines. Misleading data goes viral. Claims that could be debunked with 5 minutes of research get repeated by major media outlets, influential investors and Wall Street analysts. It’s relentless and honestly pretty fascinating to watch. Of course there will be spectacular failures and massive wealth destruction along the way. That’s what happens during technological revolutions. But I’ve never witnessed this much effort to convince the world that something so transformative is actually one giant speculative bubble destined to take the entire economy down with it. I understand why AI scares people. What I find harder to understand is why so many investors seem to be rooting for it to fail.
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$SPCX Q1 ‘27 revenue guidance $33-$37b Analysts at $22.1b
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Well, on to College Basketball.
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Now that I have successfully rage baited what feels like every AI bear on X, let's systematically break down the most common counterarguments because they are very off the mark. #1. The AI trade is the same as the dotcom bubble or the 2008 crisis This is the most frequent rebuttal, and it is a lazy comparison. When you look under the hood, the numbers do not support it. Looking at the S&P 500 top 10 at each peak: March 2000: 53.6x trailing earnings, 9.1% net margin October 2007: 16.4x trailing earnings, 13.3% net margin Today: 26.5x trailing, 20.9x forward, 33% net margin Unlike the dotcom bubble, today's leaders have the earnings to support their build out. In the three years before the 2000 peak, the tech leaders' stocks rose 7.4x on 2.1x earnings growth, and the rest of the market was priced even higher: the Nasdaq traded at about 175x earnings. Today's AI leaders rose 2.9x on 3.1x earnings growth, and on average they pay about a fifth of the 2000 price per unit of growth. PEG on trailing three year growth: 2000: 1.6 to 5.7 Now: 0.2 to 1.6 2007 was never a valuation problem. It was a leverage problem, which I cover in #4. Yes, today's concentration at the top of the index is real, and it is higher than in 2000, but this time it is backed by profits. Today the top 10 are 40.6% of the S&P 500's value and 36.1% of its earnings. In March 2000 they were 27% of the value and only about 15% of the earnings. Put today's earnings at 2000's prices and the gap is massive: Nvidia at Cisco's peak multiple (178x) would be about $1,210 a share, a $29T company, 5.7 times today's price. Today's top 10 at the 2000 top 10's 53.6x would be worth $43T even on earnings excluding gains, against $28T today. The S&P 500 at 2000's forward P/E of 25.2x would be about 10,160, against 7,659. (See Chart 1) #2. Nvidia is the next Cisco, or the next Enron. From January 1998 to the March 2000 peak, Cisco's stock rose 7.6x while its trailing earnings rose 1.7x, ending at 178x pro forma earnings. Over the last 26 months, the same length of time, Nvidia's stock rose 1.8x and its trailing earnings 3.3x. It trades at 31x. Enron is an even worse comparison. In 2000 it reported $100.8B of revenue, much of it gross trading volume, and kept $979M of it, a 1% margin, while its stock traded at about 74x earnings. Its profits leaned on mark to market accounting and debt kept off its balance sheet, and it filed for bankruptcy in December 2001, then the largest in US history. Over the last 12 months Nvidia turned $303B of revenue into $193B of net income and $134B of operating cash flow, paid in cash by the largest companies in the world. #3. Today's companies aren't profitable These are some of the most profitable companies in history. Over the last 12 months Nvidia earned $166B excluding investment gains, more than Saudi Aramco's $161B in 2022, the largest annual profit any company had ever reported. Until 2024 only Aramco had earned more than $100B in a year. Nvidia, Apple, Microsoft and Alphabet now each do, even excluding gains. The suppliers are the same. Micron earned $85B at a 64% margin and TSMC $78B at 50%. SK hynix made $85B of operating profit, and Samsung made $80B of operating profit in the third quarter alone, a quarter only Aramco has ever topped. The ten largest tech companies of March 2000 earned $37B combined, at a 15% margin. Cisco kept 17 cents of each revenue dollar and Lucent 9. Nvidia keeps 55 cents and Micron 64. To be fair, memory is cyclical. These are shortage profits, and Micron's previous record year was $14B in fiscal 2018. (See Chart 2) #4. The AI trade is built on debt and is not sustainable The dotcom buildout ran on borrowed money. Debt owed by US telecom carriers rose from $158B in 1996 to $380B in 2000, and the junk rated carriers had negative operating cash flow as a group. The seven pure network builders (Global Crossing, Level 3, Williams, XO, 360networks, McLeodUSA, Winstar) owed $31.8B plus $6.5B of preferred stock, and six of the seven did not cover their interest bill even on their own EBITDA numbers. Telecom made up 55% of US junk bond defaults in 2001, and 23 telecoms went bankrupt by mid 2002. In 2000 WorldCom needed 3.2 years of cash flow to repay its debt, Global Crossing 8, and XO's cash flow was negative. Today Alphabet, Microsoft, Amazon and Meta owe $351B, hold $533B of cash, and could repay it all with about six months of cash flow. In the last year the 10 largest US tech companies generated $1.10T of operating cash flow and had $523B left after $574B of capex. At the 2000 peak, the top 10 tech names had about $34B of free cash flow, $66B in today's dollars, and traded at about 57x cash flow. Today it is 24x. 2008 was leverage inside the financial system. In 2007 financial sector debt was 144% of GDP, broker dealers ran 46x assets to equity, and Citigroup ran 18.6x and Bank of America 11.4x, both top 10 companies at the time. Today financial sector debt is 85% of GDP, broker dealers run 17x, and the S&P 500 top 10 run 1.8x. The debt that does exist sits at the edges, with names like Oracle. The four largest spenders are paying for this out of cash flow. (See Chart 3) #5. Demand is inflated, and they are overbuilding capacity like the dotcom bubble. AI provides no long term value and adoption is overstated. In 2000, WorldCom said internet traffic doubled every 100 days. In reality it doubled about once a year, and US backbone networks ran at about 10 to 15% of capacity. The carriers built for demand that did not exist yet, in the hope that it would show up. Yes, AI spend is larger now, but it sits against $2.3T of signed backlog at AWS, Google Cloud, Microsoft and Oracle. Demand is running ahead of supply: TSMC says demand is still far above its ability to supply, Micron says it has no line of sight to when supply and demand balance, and Nvidia's CFO expects supply to remain a bottleneck at least through fiscal 2028. Rental prices for the H100, a chip that shipped in 2022, are up 17% over the past year after halving from their 2024 peak. Hardware normally gets cheaper as it ages; over the past year we have seen the opposite, because demand is outrunning supply. The suppliers see this demand first. They would be the canary in the coal mine here, and they just reported record quarters: TSMC, ASML and Micron each posted the highest quarterly revenue in their history. TSMC raised its 2026 growth guidance at every update, to about 44%. ASML lifted its 2026 sales guide from €34 to 39B to €44 to 45B, says 2027 is close to fully covered with orders for its standard EUV machines, and has customers asking to order for 2029 and 2030. By press estimates a High NA machine costs about $380M and a standard EUV machine about $180M. Nobody books those years ahead on a whim. Memory makers are seeing the same and are signing take or pay agreements years out. Micron has 26 of them, some running to 2031, covering over 35% of its revenue through 2030, and over 75% of its 2027 output is already committed. Samsung's agreements run at least five years, and SanDisk has $93.9B of minimum contracted revenue. For comparison, in 2000 Lucent had committed $8.1B of financing to its own customers. Now the money runs the other way: Micron holds $12.7B of customer cash deposits, and ASML's long term customer down payments rose from €3.6B to €9.3B last quarter. These commitments are funded by the cash flow of the largest companies in the world. Generative AI reached 55% of US adults aged 18 to 64 within three years of launch. The internet was at 30% at the same point, and the PC at 20%. About 2B people use AI worldwide, 55.9% of US businesses on Ramp pay for AI tools, and Census data shows 23.8% of US businesses used AI in the past two weeks. Consumers spend about $40B a year on it, roughly $20 per user, so monetization has barely started. Physical AI is earlier still. Waymo runs about 500,000 paid rides a week, up from 50,000 in May 2024, and Nvidia's physical AI revenue passed $9B over the last 12 months. Each robot or autonomous vehicle needs far more compute and memory than a phone: Micron says an L4 vehicle typically carries over 200 GB of DRAM, about 24 times a phone, and expects humanoids to need as much. Counterpoint expects humanoid memory demand to grow 20x from 2026 to 2030. Volumes are still small; this layer of demand has barely started. (See Chart 4) #6. Today's tech leaders aren't smart This is the most insane one for me. The idea that random people on X can question the intelligence of the people running these companies is nuts. ASML's EUV machines fire a laser at a drop of molten tin twice, 50,000 times a second, creating a plasma hotter than the surface of the sun to print chips. TSMC is mass producing chips at 2nm. These companies turn science fiction into reality on a regular basis. The leadership is also nothing like 2000. Executives at Enron and WorldCom were convicted of fraud, and Congress passed Sarbanes Oxley in 2002 because of them. Since then every public company CEO and CFO has had to personally certify their company's financial statements. For people to throw stones at the intelligence of these leaders is just loony. In summary, I am very optimistic about the transformative nature of AI for our lives and our economy. So as I originally stated, I will continue to be long my picks and shovels favorites like TSMC, ASML, GEV and others. We are still in the early innings; don't let lazy fear mongering tell you otherwise. I am not saying "it is not the same" out of hope or cope. The math and data support me.
If you’re short or anti the AI trade, your thesis is literally to bet against some of the smartest people ever who are running the largest and most profitable companies to ever exist. Yeah… I think I’ll stay long.
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just got the weekly status report from the team
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On my way to the office this morning, I passed a group of young people protesting, a Palestinian flag draped over their shoulders. And I asked myself a question I can't shake: why does this generation always fall into the same trap? No matter the history. No matter the context. Even the ones from wealthy families, who went to the best schools, who were dealt every good card. Always the same trap. I don't think it's stupidity. I think it's a mechanism. And a mechanism can be taken apart, piece by piece. A. The observation: everything the state touches becomes unaffordable. Look at economist Mark Perry's famous chart, the one people call "the chart of the century." It tracks US prices since 2000. At the top, what explodes: hospital services, college tuition, textbooks, childcare, housing. Increases of +100%, +150%, up to +250%, far above general inflation. At the bottom, what collapses: TVs, software, phones, toys, clothing. A TV today costs a fraction of what it did in 2000, for an infinitely better product. Look at what separates the two groups. It isn't technology. It isn't complexity. It's one variable: how much the state is involved. At the top, sectors that are subsidized, regulated, shielded from competition, where the state funds demand and blocks supply. At the bottom, sectors where companies fight every single morning to serve you better and cheaper. B. The mechanism: why it's systematic. When the state subsidizes demand without freeing supply, prices rise. Every time. Guaranteed student loans, and universities raise tuition. Housing aid plus blocked building permits, and rents skyrocket. Administered healthcare, and bureaucracy eats the budget before it ever reaches the patient. In France it's even more vicious, because the price doesn't disappear: it hides. You never see the hospital bill, you pay it through payroll contributions. You never see the cost of school, you pay it through taxes. Public spending at 57% of GDP, one of the heaviest tax burdens in the world, more than €3.4 trillion in debt. And the result? Overflowing ERs, falling PISA scores, young people who can't afford to live in the city where they work. The market didn't fail in these sectors. It was never allowed in. C. Suffering demands a culprit. A 22-year-old lives all of this in their bones. They can't find a place to live. Their degree either buries them in debt or opens no doors. The future feels blocked. That suffering is real, and I don't deny it for a second. But human beings can't stand suffering without a culprit. They need a face. A scapegoat. And this is where everything is decided: who taught them how to read the world? D. Whoever tells the story picks the villain. Schools are public. Universities are public. Culture runs on grants. Film goes through funding committees. Public broadcasting shapes the narratives. The people handing down the interpretive framework are, overwhelmingly, paid by the very system that creates the problem. Do you really think that system is going to name itself as the culprit? No. It names the capitalist. The boss. The landlord. "The rich." The multinational. The commercial West. Same role, same casting, every time. E. One lens, a thousand causes. And this brings me back to that flag. A generation taught to read every situation through a single lens, oppressor on one side, rich, Western, capitalist, oppressed on the other, will apply that lens everywhere. To housing. To climate. To conflicts on the other side of the world. The cause changes, the lens stays. That's why the trap is always the same: it's not the cause that draws them in, it's the way of thinking that was installed in them. F. The perfect inversion. Here's the irony. Capitalism is the force that drove down the price of almost everything it touched. The state is the force that blew up the price of almost everything it captured. And young people blame the first for the crimes of the second. It's like blaming the firefighter for the fire because you saw him at the scene. G. The ballot box confirms it. In the US, a few weeks out from the midterms, a large share of urban young voters is getting ready to vote Democrat for more state, more spending, more regulation. New York elected a self-described socialist mayor, carried by young voters, on promises of rent freezes and city-run grocery stores. Rent freezes, the policy that has made housing scarcer everywhere it's been tried. The cure that worsens the disease. In France, it's the same play in two acts. Part of the youth votes for the radical left, which promises more state. Another part votes for the center, which promises to "manage" the state well, and has dug the debt deeper than ever. Two different ballots, one shared assumption: the problem is the market, the solution is the state. H. The way out. These young people aren't stupid. They're right to be angry. They're just aiming at the wrong target. The day they understand that their rent, their tuition and their hospital are expensive precisely because the state runs them, their anger will change direction. They'll stop protesting against those who create. They'll start protesting against those who capture. That day, the greatest intellectual scam of our time will be over.
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