Static (This is the Generational Top in Equities)

We are in the grand finale of the 15 year passive bubble. Every bearish macro event for the past decade has been shrugged off by equity markets because the passive bid was always there. Things are changing. The young generation, being less trusting of the system than ever before and less optimistic about their own financial future, is continually shifting towards independent work and independent investment decisions. Hyperspeculation has taken hold of the youth and will not let go anytime soon. Over time that weakens the passive bid that has held this market up for so long. These factors, combined with an aging boomer population holding the majority of wealth in equities, will finally lead to the passive bid being overwhelmed. This bubble will top on the same liquidity dynamics that started it. Right before the bubble tops, the same mechanics that started it go into overdrive and lead to excess and capitulation. Things like the levered etf’s and the greatest passive bagholding event of all time in spacex are getting us very, very close. However, in the short term it has become far too consensus to expect the market to top on the day of the IPO. The pattern won’t play out that simply. I have never had more conviction in an idea than this: - Do not be long passive for the next decade. It will be chop, pain, and underperformance. - Gone are the days of your guaranteed 10-12% per year for doing nothing. These final thrusts with no pullbacks are the las gasps of the infinite bid. - Hyperspeculation will continue to drive insane moves in small pockets of single name stocks, crypto, alt assets, etc. - Skilled operators will make fortunes actively trading, unskilled operators will be wiped out, and passive will end up with a decade of time wasted with nothing to show for it. - AI slop and midcurve quants using chatgpt to code trading algos will create lucrative and exploitable new inefficiencies in markets.

What Everyone Missed In Leo’s Blow-Up👇 Leopold Aschenbrenner lost $30 billion (~67%) in a month. The consensus post-mortem, from the Wall Street Journal to the replies on X, is that a young man used 4-to-1 leverage on concentrated positions and got carried out. While that is true, it does not convey any useful information. Leverage is certainly the reason Leopold lost so much, so quickly. But it is not the reason he lost. Leverage is merely a magnifying glass. It doesn’t pass judgement. The reason the reason his fund was doomed was because he’s wrong. And no one, anywhere, has explained why. On the morning of Thursday, July 30, before the opening bell, Situational Awareness LP sold its entire public stock portfolio — the long side and the short side together, roughly $16 billion of it — to Citadel in a single block trade. Millennium Management and Jane Street bid for the assets. Ken Griffin and Citadel won. That night, Aschenbrenner wrote to his limited partners. Net performance for the month, unaudited: down 67%. Net performance for the year: still up 80%. "We let you down this month," he wrote. "We came closer to permanent capital impairment than is acceptable to us." Six days earlier, on July 24, he had written a different letter. That one reported a 439% net return for the first half of 2026, described the selloff in artificial intelligence stocks as one of the best buying opportunities since early 2025, and invited his investors to wire more money starting August 1. It closed with a postscript: "At times we call out opportunities that seem like a particularly good time to add funds, if you have been waiting for one." Assets that stood near $45 billion at the start of July finished the month around $10 billion, and roughly half of what remains is a single illiquid private stake in Anthropic. Leopold is 25 years old. He graduated from Columbia at 19, as valedictorian. He worked at the FTX Future Fund from February to November of 2022, then joined OpenAI's Superalignment team, then was fired in April 2024. Two months after the firing he published a 165-page essay called "Situational Awareness: The Decade Ahead," raised $225 million from Patrick and John Collison, Nat Friedman and Daniel Gross, and started a hedge fund. He had never managed money before. Situational Awareness was constructed to express only two ideas. The first conviction: the physical build-out of artificial intelligence — the chips, the memory, the power, the data centers, the neoclouds — was the trade of the decade. The fund's disclosed long positions read like an inventory of the second derivative of the AI boom. Bloom Energy Corporation (NYSE: BE), fuel cells for data centers. Sandisk Corporation (NASDAQ: SNDK) and Micron Technology, Inc. (NASDAQ: MU), memory. CoreWeave, Inc. (NASDAQ: CRWV) and Nebius Group N.V. (NASDAQ: NBIS), rented compute. IREN Limited, Core Scientific, Applied Digital, Riot Platforms, CleanSpark, Bitfarms, Bitdeer — bitcoin miners converting their substations into AI compute. The second conviction: application software was going to be destroyed by A.I. Not disrupted. Obliterated. Leo explained why on Dwarkesh Patel's podcast, in June 2024: "I'm so bearish on the wrapper companies because they're betting on stagnation. They're betting that you have these intermediate models and it takes so much schlep to integrate them. I'm really bearish because we're just going to sonic boom you. We're going to get the unhobblings. We're going to get the drop-in remote worker. Your stuff is not going to matter." That was the whole thesis. Buy the compute. Short the stuff that runs on the compute. By CNBC's reporting, the short leg included Adobe Inc. (NASDAQ: ADBE). A 13F does not disclose short stock. It does not disclose swaps. We only know about Adobe because reporters were told… but you can look at the tape and, when you do, it’s clear that Leo was short software in a major way. Between the June 30 close and the July 29 close — the last session before the block trade cleared his shorts — the two sides of his portfolio did this. The longs: · Sandisk: down 55.32% · Nebius: down 46.33% · Bloom Energy: down 45.90% · CoreWeave: down 38.90% · Micron: down 35.98% · IREN: down 35.91% The shorts, over the same 20 sessions: · Workday, Inc. (NASDAQ: WDAY): up 37.24% · Adobe: up 28.49% · Intuit Inc. (NASDAQ: INTU): up 27.64% · Salesforce, Inc. (NYSE: CRM): up 20.25% · Veeva Systems Inc. (NYSE: VEEV): up 17.15% Over that same window the Invesco QQQ Trust fell 10.14% and the SPDR S&P 500 ETF Trust fell 2.32%. Nvidia — the supposed epicenter of the AI trade — fell 5.04%, and finished the full month of July up 0.33%. This was not an AI crash. The S&P 500 stayed near its record throughout. This was a violent rotation out of the leveraged, capital-hungry, second-derivative end of the AI complex and into the profitable, cash-generating, asset-light end of it. Which is to say: the market rotated out of exactly what he owned and into exactly what he was short. Then there is Microsoft. Microsoft Corporation (NASDAQ: MSFT) closed at $390.54 on Wednesday, July 29. It closed at $451.10 on Thursday, July 30. That is a gain of 15.51% in a single session on 110.2 million shares, against a July average of 37.1 million. Yes, Microsoft reported its fiscal fourth quarter after the close on July 29. But the results were nothing out of the ordinary. Revenue came in at $90.007 billion against a $87.62 billion consensus. That is a 2.7% beat. Earnings were $4.74 per share against $4.21. It was a good quarter. Not a historic one. A 2.7% revenue beat does not add roughly $450 billion of market value to the most widely owned company on earth in six and a half hours. Something else was in that tape. And the answer is extremely important. Leo blew up quickly because of leverage. But he failed because he is simply wrong. Aschenbrenner's software thesis rests on a single premise: that a company selling enterprise software is selling the work the software performs. If a model can perform that work, the company is worth nothing. That premise is what a very smart 25-year-old engineer believes. It is not what anyone who has ever run a business believes. Nobody buys Microsoft because Microsoft writes the best code. They buy Microsoft because Microsoft is the rail everything else runs on. Active Directory is where your employee identities live. Excel is where your board deck's numbers come from. Teams is where the compliance-recorded conversation happened. Azure holds a FedRAMP High authorization and Department of Defense Impact Level 5 clearance, which means a defense contractor cannot casually swap it out for something cheaper without re-clearing the entire stack with the government. Veeva runs the customer relationship management and regulatory document systems of the pharmaceutical industry. Nineteen of the top 20 biopharmaceutical companies use Veeva's regulatory information management platform. Those systems are validated under GxP — the good-practice quality regulations that govern anything touching a drug — and 21 CFR Part 11, the Food and Drug Administration's rule for electronic records and signatures. Every major release is formally qualified. When an FDA inspector arrives, the audit trail in that system is the company's defense. You cannot replace that with a model that is very good at writing code. You would have to re-validate a decade of regulated records, in front of a regulator, on a system with no track record, to save a fee that rounds to nothing in terms of the cost of building a new drug. How small a fee? Veeva's licensing runs somewhere between roughly $1,800 and $6,600 per sales representative per year. A fully loaded pharmaceutical sales rep costs the employer between $134,000 and $219,000 a year. The software is 1% to 5% of the cost of the person using it. Microsoft raised the price of a Microsoft 365 E3 seat from $36 to $39 per user per month on July 1 of this year, and E5 from $57 to $60. Add Copilot at $30 and a fully loaded E5 seat costs $1,080 a year. Against a knowledge worker costing $75,000 to $120,000 all-in, that is roughly 1% of the employee. This is the part the compute maximalists cannot see. These companies are not selling labor. They are selling the rails on which labor runs, at a price so far below the value created that the buyer never bothers to negotiate hard, and with switching costs so high that the buyer could not leave even if he wanted to. Do people try to leave? Constantly. And they almost always fail. (Ask me how I know!) Panorama Consulting Group's tracked studies of enterprise resource planning replacements put average cost overruns at 189% across industries. Gartner projects that by 2027, more than 70% of recently implemented ERP initiatives will fail to fully meet their original business goals. Ripping out a core enterprise system is one of the most reliably disastrous things a large company can attempt, and it was true before anyone had heard of a transformer model. The incumbents are not being disintermediated by artificial intelligence. They are selling it! Microsoft passed 30 million paid Copilot seats in the June quarter, up from 15 million in January. Tech wizards like Leo hate copilot. Just like they hated Windows ’97. And everything else Microsoft has ever built. So what? Accenture alone bought 740,000 of them. Bayer, Johnson & Johnson, Mercedes-Benz and Roche have each deployed more than 90,000. Microsoft's commercial remaining performance obligation — contracted revenue not yet recognized, which is the closest thing software has to a railroad's signed freight contracts — stands at $678 billion, up 84% year over year! Adobe's AI-first annual recurring revenue passed $500 million in the quarter ended May 2026 and tripled year over year. Salesforce's Agentforce went from $800 million of annual recurring revenue in the January quarter to $1.2 billion by April, up 205%. Veeva is giving its AI agents away free inside Vault CRM through 2030, which is the single most revealing data point in the set: Veeva does not need to monetize AI, because Veeva's moat is the validated record, not the intelligence applied to it. Aschenbrenner thought AI would eat the applications. Instead the applications are selling AI as an upsell on top of a subscription the customer cannot afford to cancel – because it costs nothing compared to the value it delivers. These software companies are computing toll booths: they’re what enterprises pay to implement compute. And, as compute gets cheaper, they will generate vastly more revenue, not less. The proof is sitting there in their earnings and cash flows: they’re riding on lower and lower cost of compute, which makes their business more and more efficient. · Adobe: 36.6% operating margin, 35.6% return on invested capital, capital expenditure of $179 million on $23.8 billion of revenue — 0.75% — and $9.85 billion of free cash flow. · Veeva: 28.7% operating margin, 68.5% return on invested capital, a 44.3% free cash flow margin, and effectively no capital expenditure at all. · Salesforce: $41.5 billion of revenue, roughly $14.4 billion of free cash flow, capital expenditure of about 1.4% of revenue, and $72.4 billion of contracted backlog. · Intuit: $18.8 billion of revenue, roughly $6.1 billion of free cash flow, $124 million of capital expenditure. Veeva earns 68 cents a year on the dollar. And invests nothing it growing its business. Adobe currently trades at about 11 times trailing earnings. Salesforce at about 13. Intuit at about 14. These are the multiples of a dying industry, applied to businesses converting a third to nearly half of every revenue dollar into free cash. This enormous mispricing was manufactured by people who like Aschenbrenner, believed these businesses were doomed. But they aren’t. And that’s not all. Aschenbrenner assumed that because a technology is transformative, the capital that builds it will earn its cost. There is no relationship between those two things. In fact, it’s more likely not to be true. Leo’s own essay contains the tell: "Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans." He wrote that as a bull case. But it isn’t. That is a recipe for a financial disaster. Amazon.com, Inc. (NASDAQ: AMZN) spent $131.8 billion of capital expenditure in 2025 against $139.5 billion of operating cash flow. That is 94.5% of everything the business generated, poured back into the ground, in a single year. Its 2026 cap ex guidance is $220 billion. Alphabet Inc. (NASDAQ: GOOGL) spent $91.4 billion in 2025, 55.5% of operating cash flow, and guides to $195 billion to $205 billion this year. Meta Platforms, Inc. (NASDAQ: META) spent $72.2 billion, 62.4% of operating cash flow, and guides to $125 billion to $145 billion. Microsoft spent $115.9 billion in the fiscal year that just ended, against $182.9 billion of operating cash flow. Capital expenditure was 34.9% of revenue, up from 18.1% two years earlier. Free cash flow fell to $67.0 billion from $74.1 billion in fiscal 2024, on revenue that grew by more than a third over the same span. Microsoft is running harder and generating less cash. That is what a huge capital cycle does even to the best business in the world. Moody's projects hyperscaler capital expenditure of $785 billion in 2026 and close to $1 trillion in 2027, funded in part by roughly $175 billion of debt issuance this year. Where will the money come from…? Oracle: fiscal 2026 capital expenditure of $55.7 billion, free cash flow of negative $23.7 billion, capital expenditure at 82.6% of revenue, long-term debt up from $76.3 billion to $124.7 billion, and $248 billion of future data-center lease obligations not yet on the balance sheet. CoreWeave: $5.13 billion of 2025 revenue, $14.9 billion of capital expenditure, negative $7.25 billion of free cash flow, net debt at 8.1 times EBITDA, term loans at 11% to 15%, a weighted-average short-term borrowing rate of 12.3%, and a $1 billion private placement in April 2026 at 9.75%. Meta's Hyperion campus in Louisiana is financed through a special purpose vehicle in which Blue Owl Capital holds 80% and Meta holds 20%, funded by $27.294 billion of senior secured notes at a 6.581% coupon maturing in 2049. The noteholders have no pledge on the physical data center. Their credit is Meta's promise to pay rent starting in 2029, plus a residual value guarantee. Twenty-seven billion dollars of debt, secured by a lease, sitting off the balance sheet. And… like the EU’s finance minister explained two decades ago… “when it gets serious, you have to lie.” Microsoft extended server useful lives from three years to four, then to six, adding about $3.7 billion to fiscal 2023 operating income. Alphabet did the same, adding about $3.0 billion. Amazon added about $2.5 billion in 2024. Meta added $2.59 billion in 2025. Oracle added $573 million. Every one of those is a non-cash increase in reported profit produced by an assumption about how long a chip stays useful. It’s a lie. But not everyone is lying. Effective January 1, 2025, Amazon shortened the useful life of a subset of its servers and networking equipment from six years back to five, citing, in its own 10-K, "the increased pace of technology development, particularly in the area of artificial intelligence and machine learning." That cost it $1.4 billion of additional depreciation and $1.0 billion of net income. Amazon is the operator with the longest and hardest-won experience running data centers at scale, and Amazon is the one telling you the hardware wears out faster than the schedules assume. How could all of this spending possibly pay off? Bain & Company's global technology report puts it at roughly $2 trillion of annual artificial intelligence revenue by 2030, and calculates that even if every dollar of on-premise IT budget shifted to the cloud and every dollar of AI productivity savings were reinvested, the industry would still be about $800 billion short. Sequoia Capital's David Cahn, who has been running the same arithmetic since 2023, has escalated his estimate from $200 billion to $600 billion to roughly $840 billion. Against that: OpenAI's audited 2025 revenue was $13.07 billion, with an operating loss of $20.92 billion. Anthropic's 2025 revenue was $10 billion. Combined, $23 billion. And of every dollar spent on Nvidia systems, roughly 72 to 75 cents is Nvidia's gross profit. Data center is now 88% of Nvidia's revenue. The margin is not in the build-out. The margin is in selling to the build-out. What’s about to happen is obvious, because it has happened before. Between 1865 and 1873 the United States built the most consequential physical network in its history and destroyed an enormous amount of capital doing it. Track mileage went from 35,085 miles in 1865 to 52,922 in 1870 to 74,096 by 1875. Construction peaked at 7,439 miles laid in 1872. Railroad capital reached roughly $4.5 billion at a time when the entire banking system's capital was $720 million and the federal debt was $2.3 billion. In January 1870, of 896,596 shares traded on the New York Stock Exchange, 781,340 — 87% — were railroad shares. From 1870 to 1874, roughly 70% of all railroad securities issued in London were American. American rail bonds paid 6.5% when British consols paid far less, and European capital came for the yield. Every argument you hear today was made then, too. The railroads will transform the country. Yep, they did compress distance and cost of transportation in a way that seemed impossible only a few years earlier. And it didn’t make any difference. On September 18, 1873, Jay Cooke & Co. failed. Cooke had contracted to place $100 million of Northern Pacific 7.3% gold bonds, but sold less than $20 million. He ended up effectively owning 75% of the railroad he was supposed to be financing. And it failed. The New York Stock Exchange closed for ten days — the first closure in its history. By 1876, 134 railroads were in default on $500 million of bonds out of roughly $2 billion outstanding. By 1877, 20% of American railroad track mileage was in receivership. European investors are estimated to have lost around $600 million between 1873 and 1879. A very large fraction of the capital that built the American rail network was lost. And where the roads survived, competition took the returns. Revenue per ton-mile fell from 1.88 cents in 1870 to 0.73 cents in 1900, a decline of about 61%. Rate wars on the New York-to-Chicago corridor drove the through rate from $1.88 down to 25 cents, then 20 cents, and no pooling agreement stabilized the worst of it until late 1885. Every additional mile of track made the network more valuable to America and less valuable to the men who had paid for it. The AI build-out will have the same problem – but it will be much, much worse. Compute will be a pure commodity. Nobody disputes that the models are transformative. The problem is, that’s true of all of them. Which of the second-derivative names Aschenbrenner owned has route control, like a monopoly railroad? Bitcoin miners with retrofitted substations? Rented compute resold at a spread? Memory, an industry that has never once earned its cost of capital through a full cycle? Those are not toll booths. Those are the Northern Pacific just before bankruptcy. The railroads made a fortune – but not for their investors. Adams Express Company was incorporated in 1854 with $1.2 million of capital. It did not own a single mile of track. It bought space on other men's trains and moved parcels, money and valuables on them. By 1866 its capital was $10 million and it was paying an 8% dividend quarterly. By 1875 its capital was $12 million. It paid an unbroken $8 per share annual dividend from 1869 forward — straight through the depression that put a fifth of American rail mileage into receivership, and straight through the next one in the 1890s. American Express Company (NYSE: AXP) declared a $6 dividend in 1869, cut it to $3 in the depression year of 1877, restored it to $6 by late 1881, and held it there for the rest of the century. An 1888 board report showed ten-year net earnings of $26.24 million. By 1890, the express companies were handling more than 115 million packages a year over 174,535 miles of railroad and steamship routes. And they didn’t own a single locomotive or a single boat. Pullman's Palace Car Company was organized in 1867 with $1 million of capital. It did not own track either. It owned the sleeping cars and leased them to the railroads. Capital grew to $36 million by the early 1890s with nearly $25 million of accumulated surplus. Dividends ran 9.5% to 12% from 1867 to 1871 and 8% annually for decades after. In 1879, with 464 cars out on lease, it earned gross revenue of $2.2 million and net profit of almost $1 million. Pullman put out $1 million of equity and earned $1 million a year on a network that cost other people billions and bankrupted a third of them. Adams Express converted itself into a closed-end investment fund in 1929 and is still listed today as Adams Diversified Equity Fund (NYSE: ADX). The company that rented space on the railroads outlived almost all of them. I’d bet a lot of money that Leo had never heard of any of these businesses. But for people who are experienced in putting capital at risk, the pattern is not subtle or hard to understand. When an economy builds an expensive new network, the capital that builds the network earns a poor return because competition, obsolescence and overbuild strip it away. The businesses that ride on the network at near-zero incremental capital cost, and that own the customer relationship, the data or the standard, keep the profit. I’ve seen this entire act before, during my career. In the five years after the Telecommunications Act of 1996, carriers poured more than $500 billion into fiber, switches and wireless networks. By the early 2000s no more than 2% of North American long-haul capacity was in use. Global Crossing raised roughly $20 billion, built 100,000 miles of undersea fiber, filed for bankruptcy in January 2002, and saw its assets change hands for about $250 million — roughly 1.25 cents on the dollar of invested capital. WorldCom filed six months later, at the time the largest bankruptcy in American history. Who got the value? Google, Amazon and Netflix, which built businesses on top of bandwidth that had become nearly free because somebody else had already gone bankrupt providing it. By 2018 and 2019, Google and Facebook were funding roughly four of every five dollars of new transatlantic cable investment — buying the rails only once the rails were cheap and only once they owned the applications that made the rails worth owning. Leopold Aschenbrenner is not stupid. He is the opposite of stupid, which is part of the problem. He is a brilliant technologist who has never had to make a payroll, never had to explain to an auditor why the electronic records changed, never had to decide whether to spend eighteen months and $40 million ripping out a working system to save $200,000 a year in license fees. He looked at enterprise software and saw code. A businessman looks at enterprise software and sees the thing his company cannot operate without for a single day, priced at 1% of the employee who uses it, backed by a validated audit trail he would have to rebuild from scratch in front of a regulator, and running on a contract he signed for three years. An investor who has read a balance sheet from 1874 sees $220 billion of annual capital expenditure, an 8-times-levered reseller of rented compute borrowing at 12%, $27 billion of data-center debt hidden in a special purpose vehicle, and useful-life assumptions that the most experienced operator in the business is quietly walking back. The kid believed the technology determines the return. But it never has. It’s the capital structure that determines the returns: who controls the standards, who controls the customer, and who owns the data? Yes, the A.I. models will change everything. But that does not mean the people building the machines will be paid for it. The money will be made where it was made in 1874 and again in 2004: by the toll booths riding on top of somebody else's ruinous capital expenditure.

@JaredKubin @firstadopter The public book was fully novated to Citadel to satisfy the margin debt, leaving the LPs with a zero in the public equities book. The +80% comes from blending the Anthropic stake at +620% YTD (25% of NAV), while the public book was -100% (75% of NAV) = 80% YTD.

you wouldnt understand since you also work for a scammer, but ya, people frown upon him being engaged to the woman who is chief of staff and sister to the ceo of one of the biggest ai hardware buyers in the market and they frown upon him apparently having exclusive access to top openai and anthropic staff and obtaining information that the rest of the world isnt privy to.

@TheSpeculator0 Im assuming that knowing he was insider trading was part of the appeal to investors. If you want max ai upside you pick the guy with insider info who can be the scapegoat if the SEC ever decides to care.

So this guy obviously insider trades, runs his public book into the ground and because he happens to own Anthropic is still up decent, and people are defending him / want to give him more capital? Just wire Ken Griffin your money, it's a lot easier. He also does cooler things with it than the EA cult.

@financialjuice They’re just making shit up at this point to prompt more govt involvement which ends with them getting a govt investment

OpenAI investigators find evidence that other AI agents escaped containment - Sources.

@JG_Nuke @edzitron @MacrostrategyP @gnoble79 Great listen

I had the pleasure of sitting down with @edzitron @MacrostrategyP and @gnoble79 today to talk about the current state of the AI Bubble and the inevitable result of it.

R.I.P. Credit Suisse, you guys would’ve somehow lost a billion dollars here

@Ross__Hendricks What’s even worse is he was insider trading the entire time (wife high up at anthropic) and this still happened. Every cycle there’s guys like this

From hedge fund hero to requiring an investor cash infusion to meet margin calls 2026’s version of “mistaking leverage for genius”

@Remzztrades Shhhh let them keep buying every dip in every name

You guys want my honest brutal opinion? A lot of these names that are down 40-60% will never see their 52-week highs again. And if they do, it could take years. Every market cycle creates new leaders. A handful keep leading, while the majority of high-beta names never reclaim their former glory. It’s an expensive lesson, but it’s one you’ll only have to learn once.

@Ross__Hendricks It was months and months of young kids making fun of one the best traders of our generation, calling him washed, saying he only ever had one good trade. He was always going to be right.

Burry comin in from the top ropes ... all the haters that got bagged on this momo unwind awfully quiet all of a sudden

@TheShortBear Lmao. Amazes me people were ever fooled by him. He had insider information on AI the entire time (wife works high up at Anthropic) and he is still taking enormous drawdowns.

Custom ETF representing 80%+ of Leopolds AI portfolio. Officially down 50% from highs and retracing the full post MOU (war) gains.

@danikissel8 @jukan05 Korea just had its version of the 2000 dotcom bubble, and it has popped.

@Staticether @jukan05 So you’re staying away for now?

Finally, some welcome news. In a report published today, JPMorgan said that most leveraged ETFs in the Korean stock market have been liquidated and estimated that hedge funds’ deleveraging is also about 90% complete.

In case it isn’t already incredibly obvious , Trump cannot save this market with anything to do with Iran. It is all tech and AI. Amazing seeing some of the boomers on here are giving sp500 commentary using Iran as their main narrative driver. You should not trust a thing someone like that says. Knowing the biggest narrative the market cares about is the most basic analysis a macro trader can do. If people are not able to identify what matters at this point in the cycle, yikes.

Never seen the timeline like this before. People have been absolutely annihilated. There’s an entire generation of traders who only know how to buy every dip and think every bullish catalyst sends a stock straight up immediately. They have no idea what is coming. They have no idea that stocks can trade with terrible price action for YEARS even with bullish catalysts. The Korea/memory bubble is popping as predicted. And yet, the US indices really haven’t moved much. But they will. Imagine the destruction when the Nasdaq touches 20,000. The next decade is going to destroy retirement accounts. It will not be a tariff style panic flush. It will be a steady destruction of this excess in indices and then 5-10 years of chop. $SPX -> 5800 $NDX -> 19,000

@theblazetrends So close to a bottom

BREAKING: Legendary economist Lacy Hunt has completely liquidated his firm's 30-year U.S. Treasury holdings, ending a 44-year bullish bet on bonds.

@ConnorJBates_ Don’t forget Jensen’s leather jacket selling for $1 million at an auction. Pump and dump scammer serenity becoming one of the most subscribed to accounts on all of X before losing 50% in a month.

Every single cycle there are always signs. Hindsight is clearly 20/20 but always fun to look back. 1. Leopold being peddled as a celebrity, and every stock he mentioned or bought got bid up 2. Jensen calling $MRVL the "next trillion-dollar company," sending the stock up 32% in a single day 3. The Pattern Day Trader (PDT) rule getting removed. Since it was scrapped on June 4th, that practically marked the top on $MEME, down ~44% since 4. An anonymous "bottleneck" investor focusing on key chokepoints goes to nearly 1 million followers on X, pumping random foreign stocks hundreds of percent 5. Terry Smith capitulating on his strategy and incorporating "momentum" 6. Record use of margin and leverage by the Koreans. Total casino over there 7. Margin debt as % of M2 at its 2nd highest level in history, just behind the dot-com bubble 8. Newly minted "memory experts" finding $SNDK and turning bullish after a +2,000%+ 1-year run 9. $SPCX IPO 10. Elon Musk becoming the world's first trillionaire on June 12, 2026 11. 5 sigma deviation for momentum stocks vs. low volatility 12. $SOXX $SMH "June 2026 marked the largest aggregate month of inflows into semiconductor ETFs, exceeding $19 billion." Sentiment is fascinating to me. So much value in being aware of the narratives, what's going on beneath the surface, etc. Always fun to go back and see how obvious it looks in hindsight, but not in the moment. Purely for fun compiling this, but every cycle you start to sniff the froth out a little better. What am I missing? Anyone got signs to add?

@QQQ275Soon @iamKidMixAlot It’s not the middle of the bull market

@iamKidMixAlot No idea high beta names would have their worst month ever in the middle of a bull market.

I’ve genuinely been a bad father and husband during this sell off. My moods have been terrible, I’ve yelled more than a few times, and it has taken a toll on the family for sure. Losing 60% of net worth in less than 2 months was never in the plans. Looking forward to some sort of relief, whether it’s a market bounce or going to $0.

@RealNickMugalli “The smartest people on the planet” LMAO

The smartest ppl on the planet cannot all be stupid, right? There has to be a return on an investment soon. There’s a lot to AI than meets the eye. They cannot all be spending money like drunk sailors with no ROI…we’ll see