transcript.txt and here (The Daily Dirtnap, Warsh, Torsten Slok, Paul Volcker, Lehman, Bear Stearns, the Sahm rule / Claudia Sahm, Barron's, Absci, Rogaine/minoxidil, Anthropic, OpenAI, palladium, Situational Awareness). (2) The bond call carries no ticker. He is long the 30-year and the 10-year outright and names no ETF or fund, so it is captured in the talking points and the macro themes, not as a table row — no TLT row has been invented. (3) Same for the metals: gold, silver, platinum, palladium and copper are commodity views with no vehicle named. (4) Two companies are deliberately not tabled because they are never named: the high-dose-minoxidil stock ("the ticker is m—") and "another company begins with a C… a European company." (5) ABSI and the Vanda Research positioning data are Jack Farley's contributions, not Dillian's — the attribution is stated in each row. (6) Bear Stearns, Lehman, Bloomberg, Time and Barron's appear only as historical or sentiment furniture and carry no investment view, so they are not rows.Remarks of 2026-SEP-03 on The Monetary Matters Network with Jack Farley. Stance reflects how each name was framed in this conversation (not a price rating) — most of the equity work here is chart-reading, so several rows are technical reads rather than fundamental calls. Research: QT Qualtrim · SA Seeking Alpha · STK Stock Analysis.
| Ticker | Name | Research | View | What he said | At |
|---|---|---|---|---|---|
| INTC | Intel | QT · SA · STK · FA | Positive | One of only two names he calls out individually and unconditionally as basing in the chart sweep: "Intel looks like it's bottoming." Notable because it sits inside the semiconductor complex he reads as topping at the sector level — the base is the exception, not the trend. | 9:18 |
| ORCL | Oracle | QT · SA · STK · FA | Positive | The other unconditional base in the sweep: "Oracle looks like it's bottoming." Immediately qualified at the index level — "but I'm seeing a lot more charts that are rolling over than charts that are basing." | 9:18 |
| NVDA | NVIDIA | QT · SA · STK · FA | Neutral | Genuinely two-sided. The chart is in his bottoming group ("Nvidia, AMD, couple of other semi names — I'm seeing some charts that are bottoming"), but he is explicitly waiting for the top signal and it is not fundamental: "I don't really think of things in terms of fundamentals… the leather jacket guy said they were growing at 70% and the stock ripped… what I've been waiting for for the last six months is for that second derivative of growth to change… you see the growth rate start to come down to 60 or 50%. And that's when the stocks are going to top." Ownership is the other flag — a student's entire portfolio is "50% Nvidia and 50% Broadcom," which he suspects is typical of US retail, and "they're probably not going to sell at the highs." | 10:58 |
| AMD | Advanced Micro Devices | QT · SA · STK · FA | Neutral | Named in the same bottoming cluster as Nvidia — "also Nvidia, AMD, couple of other semi names — I'm seeing some charts that are bottoming interestingly enough" — with no separate thesis, and offset by the sector-level call that "semis, healthcare and financials are topping right now." | 8:49 |
| AVGO | Broadcom | QT · SA · STK · FA | Neutral | Appears purely as a concentration exhibit, not a call: "I have a student who showed me his portfolio. It's 50% Nvidia and 50% Broadcom and that was his entire portfolio. And my suspicion is that's the case with a lot of retail investors in the US." The point is the holder, not the company — "they were the darling stocks for a long time. Everybody piled into them." | 10:07 |
| GOOGL | Alphabet (Google) | QT · SA · STK · FA | Neutral | The exhibit for the whole debt-financed-AI argument rather than an equity view: "when Google comes to market with a $40 billion bond issue, that puts a lot of pressure on the market," and it is the concrete case of the thing he has never seen before — "in my lifetime, this is the first time I've seen tech being financed with debt… usually you finance tech with equity, right? Because the asset has a very short lifespan." The cost is the punchline: "I don't know what the spread of Google paper is over treasuries… but they're essentially paying a 6% coupon on this debt. It's a lot." | 5:17 |
| NFLX | Netflix | QT · SA · STK · FA | Neutral | His one-line rebuttal to the "tech is deflationary" claim, with no view on the stock: "so many people in tech… always say that tech is so deflationary. It's like I don't know. Have you paid your Netflix bill? It's not that deflationary." | 7:07 |
| LLY | Eli Lilly | QT · SA · STK · FA | Neutral | A track-record reference, not a live call — Farley volunteers the name ("you do. Eli Lilly") when Dillian says he has "a history of finding" these, and Dillian confirms the trade without restating a view: "a few years ago I was early on the GLP-1s trade… I made you made a bunch of money for subscribers." It is offered as evidence for the method (invest then investigate), not as a recommendation today. | 21:53 |
| ABSI | Absci Corporation | QT · SA · STK · FA | Neutral | Farley's mention, not Dillian's — the host had been screening the baldness-drug names himself after Dillian flagged the theme in the newsletter: "there's one Absci Corporation that is — it says it's AI powered drug discovery. So I get a little skeptical there." Dillian's own position is that he knows nothing about the theme yet: "I don't know anything about it. Literally I just saw a tweet and I put it in the newsletter." | 22:43 |
| Kite Pharma | Kite Pharmaceuticals (acquired) | — | Neutral | His 2016 immunotherapy winner, cited to establish the pattern behind "invest then investigate": "I did a lot of research on immunotherapy… and bought something called Kite Pharmaceuticals, which was an immunotherapy biotech. And basically it was a three-bagger. Got taken out I think by Bristol Meyers." The acquirer is his own hedge and is left as spoken — no view is expressed on the buyer. | 21:30 |
| Situational Awareness | Situational Awareness (hedge fund, liquidated) | — | Neutral | The July blow-up, read as a bottom signal but explicitly not the end of it: "anytime you have a leverage player that goes t.u., that usually marks a bottom." His caveat is the whole point of the segment — Bear Stearns in March 2008 was followed by a 17% S&P rally and then Lehman, so "the most leverage player gets taken out first, but there's still so much leverage in the system… my guess is there's another Situational Awareness coming in the months down the line." | 14:58 |
| Citadel | Citadel (private) | — | Neutral | Named only as the buyer that cleared the overhang, with no view on the firm: "Citadel got the cleanup print on that and now they're pretty much out of that trade at this point." Farley fills in the mechanics — the block trades were announced July 27th or 28th, and Citadel had sold the bulk of the positions by late August. | 13:32 |
| OpenAI | OpenAI (private) | — | Neutral | The named exception to his one bullish concession about this cycle versus 1999: "there are a lot of analogies to the dot-com bubble 25 years ago… but the one thing that's different is there are profits. I mean, except for maybe in OpenAI and Anthropic, but there are profits." Farley pushes back that the labs' revenue growth has been "among the best ever for history of companies," and Dillian defers — "you know more than me on that." | 31:31 |
| Anthropic | Anthropic (private) | — | Neutral | Paired with OpenAI in the same clause as the profitless corner of an otherwise profitable market — "except for maybe in OpenAI and Anthropic, but there are profits." No company-level view; the mention is doing valuation work, not stock-picking work. | 31:31 |
| Vanda Research | Vanda Research (positioning data, private) | — | Neutral | Farley's source, not Dillian's — cited to complicate the crowded-semis story: "I actually have some data from a company called Vanda Research… top of the line positioning data on retail. And they actually say that retail positioning in semiconductors is among the lowest it's been over the past two years," with the late-July hedge fund unwind "the biggest since 2020." Dillian accepts it — "I like it. I can go with that" — and shifts the crowding to institutions. | 11:25 |
| JPM | JPMorgan Chase | QT · SA · STK · FA | Negative | The one explicit short in the episode, already published to his podcast audience: "on the Macro Dirt podcast that I do with Tony Greer, I talked about financials topping a couple weeks ago. I talked about how JP Morgan was a pretty good short." Financials are also one of the three sectors his 50-chart sweep flags as topping, and one of the groups that rallied to fill the gap left by the semis sell-off. | 8:49 |
| GS | Goldman Sachs | QT · SA · STK · FA | Negative | Singled out with Morgan Stanley as the worst of the topping financials: "especially the broker dealers. Goldman Sachs and Morgan Stanley have very scary charts." Also on the first pass of the sweep — "Goldman Sachs, Morgan Stanley, Wells Fargo all look like they're topping." | 17:11 |
| MS | Morgan Stanley | QT · SA · STK · FA | Negative | Named twice in the same breath as Goldman: topping in the chart sweep, then "especially the broker dealers. Goldman Sachs and Morgan Stanley have very scary charts." The broker-dealers are the sharpest expression of his financials-are-rolling call. | 17:11 |
| WFC | Wells Fargo | QT · SA · STK · FA | Negative | Third name on the topping-financials list: "Goldman Sachs, Morgan Stanley, Wells Fargo all look like they're topping." Banks are also part of what has been rallying to fill the semis gap — which in his reading is precisely why the group is late, not early. | 8:49 |
| JNJ | Johnson & Johnson | QT · SA · STK · FA | Negative | The healthcare name he pulls out of the topping bucket: "it looks to me like semis, healthcare and financials are topping right now… Healthcare, Johnson and Johnson." Farley's framing supports the timing read — healthcare "had been a laggard but has been recently catching a bid," and the recent bid is one of the flows filling the hole the semiconductor sell-off left. | 8:49 |
"View" is Dillian's framing in this conversation (Positive / Neutral / Negative), not a price rating. Most single names here come out of one manual exercise — a sweep of the top 50 S&P charts — so the two Positives (INTC, ORCL) are technical bases and the five Negatives (JPM, GS, MS, WFC, JNJ) are topping patterns in the two sectors that rallied while semis fell. The largest position of the episode is not in this table at all: long 30-year and 10-year Treasuries, a huge portion of his own money, held three to five years, with no ticker named. Research: QT Qualtrim · SA Seeking Alpha · STK Stock Analysis.
What each name is doing in his argument, in everyday language. The biggest position of the episode — long 30-year and 10-year Treasuries — has no ticker and therefore no block here; it lives in the talking points and the macro themes.
Intel designs and manufactures computer chips, and has spent years losing ground to competitors while trying to rebuild itself as a contract manufacturer for other companies' designs.
Dillian is not making a business argument here at all. His method for this segment was to sit down and look at price charts one by one — a habit from his Lehman Brothers trading days — and sort them into "topping" (a long rise that is rolling over) and "bottoming" (a long decline that is flattening out and forming a base). Intel came out of that sweep in the second bucket: "Intel looks like it's bottoming."
What makes it interesting is the contradiction. He reads the semiconductor sector as a whole as topping, yet two chip-adjacent names look like they are turning up. A bottoming chart in a topping sector is usually a stock that already had its crash and has run out of sellers — which is the opposite risk profile to a crowded winner.
Oracle sells database software and, increasingly, rents out cloud computing capacity to companies training and running AI models.
Like Intel, it appears purely as a chart read: "Oracle looks like it's bottoming." No revenue, backlog or margin argument is offered — the entire claim is that the price pattern has stopped falling and started to base.
He caps it immediately with the count that matters more than either name: "I'm seeing a lot more charts that are rolling over than charts that are basing." In other words, treat these as individual exceptions, not as evidence that the market has turned.
Nvidia makes the chips that nearly all AI training and inference runs on, and has been the single largest beneficiary of the AI build-out.
Dillian's view is genuinely split, which is why it is graded Neutral rather than forced either way. The chart is in his bottoming group. But he is explicit that he does not value the company on fundamentals — "the leather jacket guy said they were growing at 70% and the stock ripped" — and that what he is watching for is a specific, mechanical signal: the second derivative of growth. That means the rate at which growth itself is changing. Revenue growing 70% is fine; revenue growth decelerating from 70% to 60% to 50% is the tell. "That's when the stocks are going to top."
The second half of his caution is about who owns it. A student of his holds a portfolio that is 50% Nvidia and 50% Broadcom and nothing else, and he suspects that is common across US retail. Crowded ownership does not make a company worse, but it changes what happens on the way down — "they're probably not going to sell at the highs."
AMD is Nvidia's main competitor in high-end processors, including the accelerator chips used for AI workloads.
It is named once, inside the same sentence as Nvidia, as one of the semiconductor charts that "are bottoming interestingly enough." There is no separate argument for it, and it inherits the same offsetting problem: the sector it sits in is one of the three he reads as topping.
Treat it as a technical observation with a short shelf life, not a position.
Broadcom makes networking and custom chips, and designs the bespoke AI accelerators that large cloud companies use as an alternative to buying everything from Nvidia.
Here it is not a company at all — it is the other half of a story about crowding. A college student showed Dillian a portfolio that was 50% Nvidia and 50% Broadcom, with nothing else in it, and Dillian's read is that this is roughly what a lot of American retail investors now own.
He is careful not to sneer at it: "I hesitate to use the word dumb money because they've been right." The concern is behavioural rather than analytical — concentrated holders who bought a long move are the least likely group to sell near the top, which is what turns an ordinary drawdown into a disorderly one.
Alphabet is Google's parent — search, YouTube, Android, and one of the handful of companies spending enormous sums building AI data centres.
In this conversation Alphabet is not a stock idea; it is the evidence for Dillian's bubble diagnosis. Its $40 billion bond sale is his example of something he says he has never seen before in his career: technology being financed with borrowed money rather than shares. His objection is a matching problem — an AI data centre is obsolete in a few years, so funding it with ten- or thirty-year debt commits you to payments long after the asset has stopped earning. Equity has no such schedule; debt does.
The price of that debt is the second half. Google's bonds yield only modestly more than Treasuries, but because Treasury yields are so high, "they're essentially paying a 6% coupon on this debt" against roughly 2% in 2021. And because these issues are enormous, they compete with the government for the same pool of savings — the crowding-out effect Volcker described in the late 1970s, now running in reverse with corporates doing the crowding.
Netflix is the streaming service — and here it is standing in for an entire argument about inflation.
The claim Dillian is attacking is that technology is inherently deflationary, so an AI boom should push prices and therefore bond yields down. His rebuttal is a household bill: "Have you paid your Netflix bill? It's not that deflationary." Tech companies that win a market raise prices like anyone else; the falling-cost story describes the inputs, not what consumers actually pay.
The broader point is a race between two forces — the demand for capital to fund AI capital spending, which pushes borrowing costs and prices up, versus productivity gains, which push them down. He thinks the first is the bigger force, and he doubts the second is even measured honestly.
Eli Lilly is the pharmaceutical company behind the GLP-1 weight-loss and diabetes drugs that reshaped the sector.
It appears as a credential rather than a call. Farley supplies the name when Dillian says he has "a history of finding" ideas like this, and Dillian confirms he "was early on the GLP-1s trade" and made money for subscribers. No current view on the stock is expressed.
What it is really illustrating is his idea-flow rule — get in first, do the homework second — which is the actual transferable content of that segment.
Absci is a small biotechnology company that uses AI models to design candidate drugs, including work in the hair-loss area that came up here.
Important attribution: this is Jack Farley's mention, not Dillian's. Farley had gone looking at the baldness-drug names himself after Dillian flagged the theme in his newsletter, and his reaction to the AI framing was wary — "it says it's AI powered drug discovery. So I get a little skeptical there."
Dillian's own position is a blank: "I don't know anything about it. Literally I just saw a tweet and I put it in the newsletter." He is passing on an unresearched idea deliberately, which is the whole point of the segment, not endorsing a company.
Kite Pharmaceuticals was a biotech working on immunotherapy — treatments that turn the body's own immune system against cancer cells it would otherwise ignore. It no longer trades independently; it was acquired.
Dillian raises it as the origin story for his method. In 2016 he researched immunotherapy, bought Kite, and the position roughly tripled before the company was taken over ("I think by Bristol Meyers" — his own hedge, left as spoken).
The lesson he draws is not about biotech. It is that unfamiliar, slightly ridiculous-sounding themes are exactly where the large moves are, because most investors postpone the research until the move is over.
Situational Awareness was a large hedge fund that was heavily long semiconductors and was forced to liquidate in late July, selling its publicly traded positions in block trades to Citadel.
Dillian's general rule is that a forced seller marks a low: when a leveraged fund is wound up, its positions move from an owner who had to sell to owners who chose to buy, and the overhang disappears. Farley puts it well — "the owners go from weaker hands to less weak hands."
But he then attaches the caveat that makes this the most useful part of the segment. In 2008, Bear Stearns collapsing in March looked like the capitulation, and the market rallied 17% over the next three months — before Lehman, the real event. The first blow-up is simply the most leveraged player, not the last one: "there's still so much leverage in the system… my guess is there's another Situational Awareness coming in the months down the line."
Citadel is one of the largest multi-strategy hedge funds, and here it plays a single role: the buyer of last resort.
When Situational Awareness was liquidated, Citadel bought the book in block trades — "Citadel got the cleanup print on that" — and had sold most of it back into the market by late August. That round trip is what converted a forced sale into a clean transfer of ownership.
No view is expressed on Citadel itself; it is there to show that the liquidation was absorbed rather than dumped.
OpenAI is the private company behind ChatGPT, and one of the two large AI labs named in the episode.
It appears in the closing valuation argument. Dillian's one concession that this cycle is not 1999 is that today's leaders actually earn money — "the one thing that's different is there are profits. I mean, except for maybe in OpenAI and Anthropic." So the labs are the exception that proves the pattern, not a company he has an opinion on.
Farley pushes back that their revenue growth has been "among the best ever for history of companies," and Dillian concedes the ground rather than arguing: "you know more than me on that."
Anthropic is the other large private AI lab named, paired with OpenAI in the same sentence.
Its role is identical: the profitless corner of a market Dillian otherwise credits with real earnings. That distinction matters to his argument because a bubble in profitable companies breaks differently — and usually less catastrophically — than one in companies with no earnings at all.
There is no company-level view here; the mention is doing arithmetic, not stock-picking.
JPMorgan is the largest US bank, and the only name in the episode Dillian describes outright as a short.
The call came out of his manual chart sweep and he had already published it: "on the Macro Dirt podcast that I do with Tony Greer, I talked about financials topping a couple weeks ago. I talked about how JP Morgan was a pretty good short." A "topping" pattern means a long advance that is flattening and beginning to roll over — the mirror image of the bases he sees in Intel and Oracle.
There is a flow argument behind it too. Banks were one of the groups that rallied while semiconductors were being sold, so money rotated into financials as the crowd left tech. In his framework, being the destination of a rotation is a late-cycle condition, not a bullish one.
Goldman Sachs is the investment bank and trading house — a "broker dealer" in the language he uses.
It gets the sharpest phrasing of the episode: "especially the broker dealers. Goldman Sachs and Morgan Stanley have very scary charts." That is a technical judgment, not a fundamental one — no comment is made on earnings, trading revenue or the deal pipeline.
The reason he singles out the broker dealers within financials is that their businesses are the most sensitive to markets themselves. If his broader view is right — deleveraging still to come, another fund blow-up ahead, a market that has been rallying on rotation rather than breadth — the firms whose revenues rise and fall with trading and issuance volumes are where the topping pattern should show up first.
Morgan Stanley is the other broker dealer named alongside Goldman, and it carries the identical read.
It appears twice: once in the first pass of the chart sweep ("Goldman Sachs, Morgan Stanley, Wells Fargo all look like they're topping") and once in the emphasis at the end ("very scary charts").
As with Goldman, this is pattern recognition rather than analysis of the business — but the repetition tells you it is the part of the financial sector he feels most strongly about.
Wells Fargo is a large US commercial bank — deposits, mortgages, consumer and business lending.
It is the third name on the topping-financials list and receives no separate commentary. It is included because the sector call is the point: he sees financials as a group rolling over, and Wells Fargo is one of the charts that produced that conclusion.
The same rotation logic applies. Banks caught a bid while semiconductors were sold off, and in his reading that inflow is what has stretched the group rather than what supports it.
Johnson & Johnson is the large pharmaceutical and medical-device company, and it stands here for healthcare as a whole.
Healthcare is the second of his three topping sectors, and Johnson & Johnson is the name he pulls out of it. Farley's framing explains why the timing matters: healthcare "had been a laggard but has been recently catching a bid" — that is, it has just finished a period of outperformance after a long stretch of underperformance.
That is precisely the shape Dillian distrusts. A defensive sector that suddenly starts working while the market's leadership is being sold is usually absorbing rotation money, and rotation destinations are where his chart sweep keeps finding tops rather than beginnings.
Summary & timestamps derived from the public Monetary Matters episode on YouTube (auto-transcript, cleaned, in transcript.txt) for personal study. Not investment advice. © The Monetary Matters Network / Jared Dillian for source material.