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It's easy to say, oh, the market's not trading on fundamentals. It's, it's, you know, you know, retail idiots or crypto Bros. Or whatever people want to say on the institutional side when they're underperforming. But the truth is it might be trading on fundamentals. It might be trading on a distribution of outcomes of 2030 fundamentals or 2031 or something in the future. Valuation doesn't work to pick stocks. I mean, I don't know how many times you have to, how many years you need to know that. Like, I mean, I, I actually have kind of changed my view on that to the point of, like, I just almost think it's arrogant now. If you say I buy a stock because it's cheap. We think only 9%, 262 out of the top 3,000 public US equities are currently generating any meaningful AI revenue.
C
Adam, thanks for joining us and welcome back to Excess Returns.
B
Thanks for having me.
C
So much for selling May and go away Gus.
B
I always think those things are a little rough. I mean, we, we actually did some analysis on that point and you need like a few hundred more years to prove it statistically significant. So it's, it's one of those things where like, you know, you just could have had some spurious things that happen and then people think it's a, a trade. But yeah, I, I don't, I'm not a big believer in that. I think we studied, it's the third worst month out of the 12 in the last 100 years, but it's nowhere near statistically significant. So I, I'm not a huge believer in those. That's a little astrological.
C
Yeah, well, I kind of said it tongue in cheek because I know that, you know, trivariant, where you're focused on is analysis over antidotes, combining quant and judgment. And I think understanding, you know, what is different between sort of cyclical and structural in the markets. And one of the things that you said recently, I don't know if it was from that great Barons article Or it might have been some other piece of research that you guys put out. But one of the things that you've said is a stock market leads the economy, not the other way around and that you'd rather be wrong based on your inputs rather than listening to some economist forecasts. So I just thought that might be practically a good place to start in sort of articulating how you kind of think about the markets and build your view.
B
I'm not, I didn't mean to insult anyone with that. I mean the idea like when you work at a big firm, I used to work at Morgan Stanley and you know, the big firms have these year ahead and quarterly outlooks, right. And, and you just have to imagine, you know, whether it's Goldman or JP Morgan or UBS or whatever, you have a lot of really smart people that they have disparate jobs around the world, right? Interest rate strategy, economics, fixed income equity strategy, currency, whatever. And so the idea of having some firm wide outlook, the way it worked at Morgan Stanley and I assume it's similar everywhere else is there's some meeting and it's a couple hours and when I was at Morgan STANLEY There was 44 economists and they would tell you in their outlook for the economy and then like a few days later the industry and currency and, and credit guys would tell you, okay, given the economic assumptions, here's what we assume will happen to the currencies and the rates or whatever. And then the last meeting, maybe two weeks after the original one was the equity strategists were supposed to tell you what you thought of the US equity market. But you know, ostensibly you were supposed to use as inputs the economic view and the currency and everything else. So like every one of those meetings, almost like a broken record. I always thought we could definitely all be wrong, but there's no chance we're all right, you know what I mean? Like, yeah, and so I just, yeah, I totally just thought I should just cope with my view because you know, it's. Some of these things are really hard to forecast like currency and interest rates for sure and oil and other things. So we might as well just use our judgment and, and I think we've said it's definitely demonstratory true, which is the stock market leads the economic data, not the other way around. Anyway, so they economists. The economist meeting should be after the equity meeting.
C
Do it in reverse, I guess.
B
Yeah, totally. What, and also like economic skill, which I think when we were younger, I'm, I'm older than you guys, but what when I was younger it was considered like a good degree, like you know, scientific, you know, but now like, I don't really think there's a lot of skill to that degree because like the, you know, Gemini or, or Klon or whatever, like you can get all the economic data immediately, the forecasts. Like one of my criticisms of economists is I don't think economists even, even know what already happened because the data gets revised or the definitions aren't exact what people think. And so we feel like it makes more sense to, you know, just use the information in stock price action to predict what's going to happen.
C
What do you think of the idea? I think one of the things that investors are trying to figure out now is whether or not we are in sort of a stock market bubble. I think a lot of investors are looking back to like the late 90s and 2000s and trying to draw corollaries between today's market and back then. What do you think of the question around whether or not the market is in a bottle or not?
B
I don't love that phrase. You know, I think it's really hard to time when the top is. What I would tell people is like, look, a lot of the smartest people with the best access to information and the most high powered computers are spending all day long trying to make this call. And so the idea that you're going to sort of sell exactly at the top of your memory exposure or your semi exposure, I mean, I'm not God. Like that's, that's a tough call, right? So I would rather try to figure out how to neutralize that exposure. Find other AI revenue diversified stuff from, you know, so. But I don't think it's a bubble in terms of price action. There are some things that remind me or rhyme. So I'll give you a couple thoughts. One is I feel like every time there's been a top, two things have been in place, hubris and debt. And so if you look at like say Sam Altman at OpenAI, Lots of arrogance, tons of debt, little bit worrisome, right? I could see somebody saying these kind of giga cap or whatever they're called, IPOs that are coming are a little kind of toppy, right? The total dollars in capital spending from the hyperscale or like the capital spending dollar growth, that's definitely kind of copy. But in terms of the price action, like we could still have a huge move from here to get it anywhere near where we were on, on valuations and, and even return moves versus the, the TMT crisis that peaked in March 2000. So I don't know. I don't even know what I would do with that information anyway because I don't think I can time the peak. And I feel like I'd rather be a couple weeks late and ride it over the edge than miss out on the continued upside.
C
And do you think that that is sort of what the market is sniffing out here? I mean it's been very resilient in the face of the war. Higher oil prices, I guess, you know, consumer sentiment is in the, is in the tank here. You know, what is the market? Is it, is it sort of seeing the earnings and the sort of the fundamentals through all that?
A
I guess.
C
Is that why the market's sort of
B
marching higher kind of. 2 thoughts on that? I mean it's easy to say oh, the market's not trading on fundamentals. It's, it's, you know, you know, retail idiots or crypto bros or whatever people want to say on the institutional side when they're underperforming. But the truth is it might be trading at fundamentals. It might be trading on a distribution of outcomes of 2030 fundamentals or 2031 or something in the future. And so and by the way, just actually interestingly, and this is maybe just coincidental, but the stock market S and P is up around 9% or so year to date. As we're recording this, the bottom up estimates for this year are about 8% higher today than they were at the beginning of the year. If you look at the sector level, the sectors where the estimates are up the most year to date are tech and energy. They're also the two best performing sectors. The sector from the estimates are down the most are consumer discretionary financials and healthcare. They're also the three worst performing sectors. So like there are some things where the fundamentals have tied to performance but I get the concept of the stocks are ahead of the fundamentals for the AI kind of data center build out. I mean there's no doubt about that. And so I think people are just trying to say maybe unknowingly, hey, I'm the man. I'm going to call that top before everyone else. I'm going to get it right. I think that's tough, tough, tough call. I mean every day you'll read some doomsday thing saying this is the top or whatever, but the market's up 100% since the first time I read one of those.
C
Do you have any thoughts on when the market is going to start? Demanding or wanting to see returns on this capex build out.
B
Yeah, I mean look, we did some really detailed work recently, Justin. I mean I think that's like a whole hero question. We think only 9%, 262 out of the top 3,000 public US equities are currently generating any meaningful AI revenue. Around 16% of companies are saying on the cost side that they are doing something or will be benefiting from it. So part of the answer to your question is, and this is like a bit of the innocent until proven guilty mode the equity market's been in is this is all still in front of us, man. So like getting bearish early could be the challenge. You know, maybe it's going to come at 27, 28 et cetera. You know, the earnings estimates this year bottom up are low 20s. People think it's mid teens again next year. So you're starting to see some of it on the revenue and cost side. But let's, let's, let's unpack your question a little bit more. I mean what could, what could derail the rally would be some implementation issues, right? Like what if a big company says we have to run things in parallel or maybe we, maybe there's a whole host of new. I had a hedge fund guy told me last week they have to hire an agentic safety officer, right? So you could start seeing like less productivity in terms of like revenue per employee or something that people thought because other jobs surface. I mean, I think that's possible and so there could be some sort of implementation delay. But I think the answer is in the next, I guess, short answer, your question is in the next year, man, we better see some, some, some serious productivity from the companies.
C
To your point about that, you know, hiring that, that new person, Bezos was on, interviewed on CNBC and he was actually making the argument that AI is going to create more jobs, you know, which is totally non consensus.
B
I didn't, I didn't know that. But man, I'll take it whenever somebody like that and I can, I can accidentally stumble on the same thing, something like that saying, oh I agree. In fact I wrote about that in my most recent piece that I think there's a weird consensus view that's the opposite of history. So history would show every new technology creates a whole host of new jobs. Some get displaced and others get built. But somehow everyone thinks the opposite. You know, everyone, everyone's worried their kids are going to be, you know, unable to get, be employed because AI is going to take all the jobs But I'm not sure. I mean I actually wrote, I wrote this in my Sunday note. You know, I didn't take, you know, brain, brain science or whatever to do, you know, brain science. I just literally typed into Gemini, you know, can you suggest for me jobs that might be formed, you know, because of AI? And a whole bunch of stuff came up in finance and law and healthcare and startups and marketing and corporate, I mean all kinds of jobs. And I started thinking, well, maybe, maybe this will be, you know, kind of more of a hiring boom, both corporate wise and economically than people think.
A
Do you think? I've been working on this thesis myself. Like I think maybe this is going to be maybe the most transformative technology we've ever seen. So to your point, there's going to be tons of jobs we can't even think of. But also because it's so transformative, like we might have a little more short term pain than we have with other technologies as well. So like maybe a little bit more in the short term, but more long term benefit. Do you think that's fair?
B
It's always possible. You know, I think the current data, if you look at like new hires for undergrads and master's degree, do support peer review. There's definitely a slowdown a little bit now, so that's possible. But I'm just starting to hear about, think through and see more AI related jobs forming and so, you know, and, and people with no skills, these areas can get up to speed pretty quickly, right? You can watch a one hour kind of Claude coding thing on X for free and get, get your skills up. So I'm optimistic that you know, there'll be a lot of opportunities even in areas that people think will be obsolete, like the law. I think there's going to be more legal issues around AI, not less.
A
You mentioned the IPOs and that are coming and I just want to ask you before I forget about it, like, do you have any thoughts like at a market wide level if that matters? Like a lot of people are talking right now about the fact that we're going to have, you know, Multiple trillion dollar IPOs coming and know where does that money come from and like all that, do you, do you think that matters to the market Overall that these IPOs are coming?
B
So it's tricky. I don't, I don't know if I have, I get asked this question a lot. I think it's a good question. I'll just give a couple of thoughts and then let you react and then let's let's, let's sandpaper our block. Okay?
A
All right.
B
So I, for most of my career I've been hamstrung by compliance issues on trading larger cap US equities. So periodically I've trafficked in the illiquid small micro caps. So there's been a time where I, I bought $10,000 worth of a 50 million market cap company and that trade moved the market cap to 70 million. So my $10,000 turned into the 20 million. That's thought one, thought two is when I worked at Morgan Stanley they were their, their call on interest rates were wrong every single year I worked there. And one of the main issue, one of the main reasons is because they would always say there's a lot of supply coming online. All these bonds are going to be issued, it won't be met by demand and so therefore bond yields will back up. And we probably all know interest rate people who have called 0 of the last 50, you know, bond breaking, breaking the financial system calls. Right. So what happens is, is when people afraid they buy the 10 year yield anyway and so you don't get pro rat and the same amount of volume and updates in this down day. Right. I'm just, I'm just, I'm just giving a couple random thoughts. So like I'm not sure, I think what possible mistake people are making in their head is like oh there's going to be a tree and a half at the IPO of SpaceX, you know and so that three and a half is just going to come straight out of the other mag7 and they're all going to go down like that's not the correct moth I can assure you. But I do think there will be some pro rata selling because a lot of passive or tight tracking error. Long only have to can't be underweight something this big. And as you know, at least with SpaceX it looks like it's going to be in the S and P pretty much right away. And so it's going to be an index problem for long only guy. So let's say they do 75B at one and a half trillion. Is that what it is? So long only. I mean Musk is choosing basically who get the shares right. So no big long always going to get the pro rata amount. Let's say that's one and a half is what 3% weight in the S and P. So like I think there's going to be a lot of forced buying for a really long time and I wouldn't be shocked if this thing went to two and a half trillion or three trillion, just almost independent of price, just because people have to buy some to catch up and not much has floated. I think it'll be different with OpenAI anthropic just because they're not going to be in the index day one and so it'll be more time. But I don't think that necessarily means the money pro rata comes out of like the other Max 7. I think it probably smooths across multiple other names and, or some new capital gets allocated to it. And then the other thought, I guess is a lot of institutional investors, you know, one of the things we do for a living is people send us their portfolios to do custom risk work. And I think a lot of institutional investors I analyze their portfolios for are actively underweight. Tesla. I think there's a general view that, oh, maybe it'll come from Tesla in particular in some sort of musk allocation. And I worry about that. Like, I feel like that could be dangerous. I, I, I feel like I want to be close to market weight Tesla, not underweight because I could see some combination, you know, what if, what if SpaceX buys like something could happen that could really screw you if you're underweight. So anyway, those are my thoughts, but let me pause again.
A
Yeah, well, a lot of, first of all, a lot of people do think those companies are going to combine. Like a lot of people in the tech community think that's, that's sort of the inevitability at some point.
B
Yeah. So, but you know, I, I don't know how to answer that. But you know, I think if you're strictly long only and really have low tracking error, you're going to have to be in your 100 allocated. You'll probably just pro rata so a little bit of everything to buy some, buy some up, you know.
A
Yeah, yeah, to your point, I mean I think it's impossible to know what's going to happen, but it's, I think the mechanics is just so interesting because this is just the largest IPO ever. And so you think both on the passive side, I mean the passive funds are kind of falling all over each other right now to make sure they get this thing in as quickly as possible. And then you're also going to have like on the active side, you've got some funds that hold it now that are going to be like in violation of their mandates because they're going to hold too much once it becomes public. So I'm just thinking about like the dynamics and all the. It's just interesting. I think, I don't think there's really much of a takeaway from it. It's just interesting to think about everything that's going to have to happen mechanically once this comes out.
B
I agree. And I'm not sure. I don't know. I don't know. All I know is that people who get paid a lot of money to do this stuff for a living in other examples that I pointed to are consistently wrong at it.
A
That's right. Hey, that's true. A lot of things in investing, right?
B
Yeah, but like I know, I don't know. So I'm honest about it.
C
Which is the best.
A
It's the best way to be. Yeah.
B
I mean, look, I think that the big, that the biggest issue is they're just floating very little. And the people who need to kind of get big chunks, 3, 4% positions, like if you're these big, you know, 10 trillion club kind of asset managers, like you're going to own 3%, your bench weight or whatever it is. So like you have to own and you're not going to get any shares at the IPO or these guys aren't Right. So they're going to be buying this thing almost like with no instruction until they can get a lot of it.
A
I want to pivot to talk about software, but first I want to talk a little bit about factors because I'm kind of a quant nerd myself. And I think it was the Barron's piece I was reading that you talked about. Gross margin expansion is probably one of the most powerful factors you use. So can you explain why that is?
B
Well, there's a couple reasons. One, I think the more down the income statement you go, the more BS there's in there. So I remember years ago called United Technologies, which was run by a guy named George David. He was the CEO. And this is before they had the Raytheon transaction had spun off Carrier and Otis. But when he resigned, he said or retired, he said, I'm proud that we beat earnings 59 consecutive quarters. And I thought to myself, you know, WTF? Like, how do you beat 59? Like are they handle us uniquely stupid in this sector? No. Right. So it just. Are there cyclical businesses you're in? Of course they're in helicopters, air conditioners, like, you know, elevators. So it only just proves that there's all these levers you can pull the farther down the income statement to beat the numbers. Right, like that. Sure, I'm sure economically there were some Quarters where they just beat it and they operated well. I'm not saying there wasn't a lot of that, but you can't beat 59 consecutive quarters, which is basically 15 years without having a lot of wiggle room. So answer one is you want to be toward the top of the income statement, not the bottom. Okay. Answer two is more than any other margin level. The change in gross margin and the change in multiples, even forecasted sales or press variations are highly correlated. So businesses that have higher gross margin traded higher EV to forecasted sales. It's not necessarily true at the earnings level because of, you know, perception about over under earning or other stuff. So I think it's that combination. I think as an analyst also you can spend meaningful time getting a disparate view versus consensus on gross margin. Right. Because if you think about gross margin, there's the revenue. The best thing to get higher gross margins is raise pricing without any commitment or loss in unit demand. Right. If I just charge more, if I charge more per widget and, and still sell the same number of widgets, that's really high incremental margin. Right. So we do a ton of work on this. But you know, and there's all, all kinds of other things to input costs on the cost side as well. You know, depreciation, labor material. So I think it's because on it's more predictable for analyzable and the change is correlated to the multiples.
A
I want to ask that because software has been basically the poster child for high gross margins for a long time. And now we have a lot of questions. It's changed, not level, if that makes sense. Yeah, yeah. Though they, I guess they've consistently had improve.
B
Right, right, right.
A
Yeah. But I know you're not, you're not positive on software right now and it's such an interesting thing to think about because they've been such really good businesses, like a lot of quality funds have them. But you've got this thing out in the future that's leading everybody to question the terminal value of these businesses. And so I was wondering if you could, you had said in, I think it was the Baron's piece where you said our my highest conviction call right now is not being sucked into any rally in software. So I'm wondering if you could talk that through it.
B
Yeah, I mean, so we've had this view for a couple of years. We called it our North Star to like semis over software software. And semis currently have the lowest correlation they've had since AI started. So at the very moment recording this, I think there's some notion that software is actually going to be defensive, almost like a consumer staple relative to semis. And there could be some truth to that because the near term P and L volatility is going to be lower, right? You sign up ServiceNow, you're not getting rid of the contract this year, et cetera, et cetera. But to take the tenor of your question, why have I been negative on software? Well, when I see this much multiple contraction like we've seen, the probability earnings miss is high and ultimately eventually the sales miss. So here's why. I think median software company will underperform by a lot from here. When you look at the analyst estimates, they're for 80% gross margin and pretty high net margin every year going forward with modest, very modest revenue deceleration, 20, 19, 18, that kind of stuff. So somebody could say, well these are really high growing businesses, they're high margin, what the hell, it's oversold SaaS apocalypse, all that crap. But the software companies usually work when the revenue is accelerating. So in order to get revenue acceleration, how am I going to have the same gross margin and net margin every year going forward? I'm probably going to have to invest money on AI tools, opex and capex, etc. And so I feel like phase one is they're going to have to invest to make sure they retain the business. Phase two is the big C, the big customers, the chief technology officers from J.P. morgan and Morgan Stanley Goldman. They're going to push back on pricing because they know that their position relative to the software companies are strengthened. So that's why I think they miss on earnings maybe in the next five or six quarters, not immediately. And then eventually they're going to miss on sales because companies are going to be able to in some cases attach their own internal tools or other stuff. What the analysts do is they call the CTOs, they all have a few contacts. One of the biggest BS phrases on Wall street is channel checking by the way. But what they'll do is all I did my channel checking. They have like one friend who's a CTO and that guy tells them, oh, we're never getting rid of ServiceNow or Intuit or whatever. And then they call the IR guy from the company and they cry in their beer together about how it's oversold. But that doesn't tell you anything about the 2030 distribution of outcomes. So that's kind of my general thesis. I'll just caveat it by saying look, there's going to be some software, some companies at work that you can't get rid of. And I think they're going to be the ones, and I have high conviction on this, that are more expensive and growing faster. The last thing I want to do is buy a cheap software company that doesn't grow and try to play it for its cash flow like the market's right on average to make the ones that are cheaper, cheaper because they're more likely to be made obsolete. The ones that are more expensive software like in security and other areas which we pointed out, CrowdStrike, Palo Alto, others which have been pretty good stocks recently. The reason is because you're just going to continue to pay them. Like Justin, if you worked at Big bank and you were like, hey, I cloud coded security and it's just as good as Palo Alto. Let's save the money. Let's say there's a breach two years from now, not only are you fired, the CEOs fired for being a dipshit for listening to in the first place. So they're just going to pay the software companies in certain areas as if they're consulting firms just to kind of, you know, CYA almost. And so I think there'll be some soft float window. Like they're not going to have the same pricing power and they're not going to have same margin profile five years.
A
So it's interesting because everybody, when you see something like getting killed like this, there's always the tendency like everybody wants to buy. Like that's just like kind of a natural reaction. But I thought what was good about your, what you're talking about is like a lot of times when you get these big declines of things, there is like some sort of major like structural impairment information. Yeah, yeah, yeah. I mean, something, right?
B
Yeah. I mean if you go back to The NASDAQ know, March 2000 to October 2002, 77.4% decline. There were still 10 rallies of 15% or more during that two and a half year decline. So like you can get some pretty powerful countertrend rallies and people will say, oh, the IGV is oversold. And, but like I'm, I'm just trying to get the, the 77% direction right. I'm not going to be smart enough to get these little kind of powerful countertrend moves. So if you want to buy software because you think it's defensive against an AI semi trade, buy the expensive ones that are growing faster. Okay. And so you're going to own a few Software companies in an S and P index fund. But I'm. My North Star is still semis over software for sure. So you, so you're still a believer?
A
I mean we've had, we've had quite a run up in semis here. You still think they're, they're pretty attractive.
B
I mean my current view is sort of like market weight, semis, underweight software. But I like that relevant relative trade. I mean, I think in semis it's trickier because you know, when you take that AI revenue sort of story I told you a minute ago, where 9% of the companies seem to be having some AI revenue exposure, there's six, we think there's about six different categories, right, like there's memory and semi cap, there's vertical and edge, there's infrastructure, there's power. Like there's different buckets there. So you're gonna start transitioning, you know, where you think they're over or under earning more, where more the acceleration is in front of you than behind you, you know.
A
And I don't know if you agree. I was listening. Did you listen to that Gavin Baker interview with Patrick o' Shaughnessy recently?
B
I, I've known Gavin for a really long time from when I used to be a semiconductor analyst. So I've listened to him. He's a very compelling communicator.
A
Yeah, he's very good and, but he was just making the argument that like the semi cab equipment stuff is very, very expensive relative to like the DRAM stuff. Like kind of both situations can't be true right now. Like there might be some relative pricing issues within that. I don't know if you agree with that.
B
Yeah, I mean, no, I like that logic. I mean, in fact what inspired me to do this AI revenue note I talked about was actually not was Micron and Caterpillar. So Micron at the time I wrote the note was trading at 7 times earnings. Next year's earnings I think maybe 6 times buy side expectations and cat was trading at 30 times. And I sort of feel like they both can't be true. Like if you're saying one's massively over earnings because of a data center build out inevitability and the other one is not over earning, those seem incongruous. I will say that there are people now I know that are trying hard to find cheaper drams and so to say, well I don't need to buy the expensive ones if I'm not using them. So like there's going to slowly be a convergence between demand and supply growth. So it makes sense to me. Cats more expensive than Micron in absolute terms. I think the debate is just is the chasm too wide? And it's hard to sell stuff when it's got this much momentum and pricing is going up and whatever. I mean the mic, the, the memory stuff's really interesting. I mean if you look back like and even down chain with SanDisk and other stuff like you know there may be people who are forced to buy the shares just because they're too underweight. Right. Like the risk management point you made about, we were talking about with SpaceX a minute ago. So I, I kind of feel like on when momentum's this good and fundamentals is good and a lot of people are underweight, you may still see the shares act better than people think. Where is Daredevil a minor? Don't miss the return of Marvel Television's Daredevil Born Again.
A
So what's next?
B
I feel liberated. We're gonna take this city back over medicated in an all new season. Now streaming only on Disney plus.
A
They're hunting us. It's time we started hunting them.
B
I can work with them.
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This should be tons of fun.
B
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A
I wanted to taking girls margins and like carrying them to the market overall. I'm wondering, you talked about how you think gross margins might be coming down across like the median company. Yeah. And that make you. I think I made you a little bit cautious. Can you just talk about that?
B
Yeah, I mean I was just making this point of like two things can be true at the same time. Like we could have the most high margin market cap ever. Like I think over 40% of the S&P 500 has higher market cap has more than 60% margin. But we could also have issues where the median companies margins aren't going up and part of that was just because of input costs with you know, commodities and oil and other stuff and less pricing power which you've seen across multiple consumer areas where businesses are bumping up into pricing issues where they just can't pass it on at the rate they were, you know. So the median company, you know, take the top 500. So the 250th biggest company, their gross margins are actually about 150bps lower than they were 18 months ago. So you've seen that trend where it's been harder for the average company to take pricing. But if you take the total dollars in the market, gross profit dollars and Divide it by the total. And that's because of Nvidia and, and Micron and other businesses that are currently, you know, generating a ton of high margin business. I mean, 45% of the entire S&P 500 earnings growth year over year in Q1 was from Micron. Nvidia.
A
Yeah. This actually gets into a question I was gonna ask you later, but I'll ask you now, which is this idea that, you know, early this year we had all the stuff that was like not working. It started working like the, the median company was outperforming value international stocks. Like it was all going crazy. And then we had this war and like a complete reversal in all of that. We're, we're right back to where we started. Like I'm wondering, did you have any thoughts on that? Like if there's, if this is kind of we're back to this is the way we're going to be now?
B
Well, they're just growing fast. Right? I mean, I think one of the thoughts was like, it's funny I said it to you earlier, like, well, it's change, not level, but it's funny like two months ago. And actually this was just kind of well timed and lucky. Right. Right in towards the end of March, I wrote a note saying, well, maybe level does matter. Just like the level is high enough if earning. If tech earnings go 45% or whatever they were expected to do at that time for this year and another 25 next year, it's not like tech's going to be 60% cheaper in a year. It's just going to go up. Right. And that's kind of what's happened. Like the level was so high, the growth was so powerful that it could handle multiple contractions. So the market could still be okay even if the media company has gross margin because the actual growth's okay. So, you know, we think growth grows low teens this year, maybe 10% next year. So, you know, market can trend higher even if there's a little bit of multiple contraction. And that's kind of been, that's kind of been, been my view. But you know, generally level change is better than level. Like something improving is better than buying a stock where margins go from 1 to 5 is better than buying one where they go from 80 to 76 or whatever. Yeah, yeah.
A
One of the things you've been ahead of and like when we talked about this in our last interview with you is you've been avoiding like these common value metrics everybody's using in terms of like thinking like all these things are cheap based on these standard valuation metrics.
B
Yeah, Valuation doesn't work to pick stocks. I mean, I don't know how many times you have to. How many years you need to know that. Like, I mean, I, I actually have kind of changed my view on that to the point of like, I just almost think it's arrogant now. If you say I buy a stock because it's cheap, you're just saying you think the optical valuation has information in it. You see it's cheap, but no one else with all the computer power in the world and all the people that are looking at think it's cheap. The hell are you talking about? Like box that are cheap are cheap for a reason. On average, all you. The reason you want to buy a stock that's low is if the estimates are too low, not if the price, if the price to earnings is low. Like, Right.
A
It's about like expectations versus reality. Right? Yeah. Like a lot of those stocks are cheap because expectations are close to reality, which is bad.
B
Buy low, sell high means buy where the estimates are too low and sell the estimates are too high, not the price to earnings
A
on that estimates point. That's another thing you mentioned is this idea that the penalty for like, for missing.
B
Yeah.
A
Has become very, very severe recently relative to the reward for beating. And I think you also mentioned that in the cheap companies, that's even worse. Those companies are getting killed. Right? Is that right?
B
Yeah. So maybe not everyone knows this, but about 70% of companies beat estimates. So you gotta like unanchor your head from it being 50 50. And that's either because of that thing I mentioned earlier where there's wiggle room on the P and L, or they guide conservatively or the estimates, the analysts aren't what they believe or whatever it is. Right. But like 70% beat. So what's really interesting is stocks that just got more expensive over the last quarter, they have a higher probability of beating estimates. Stocks that just got cheaper have a higher probability of missing. So there's information in the change in multiple. Right. And then the probability you beat a second time given you beat the first time is higher than the unconditional probability. So all of a sudden it's not just momentum why the stock's up, there's information in it. Like the market's on average correctly predicting that the company's going to beat estimates. And so we're in this regime right now. Like you mentioned, the penalty for missing is way harsher than the reward for beating. But the market's up because more companies beat than miss. And so like, the wise acre advice I give to some of my clients is just don't own stuff that misses. You know what I mean? But it used to be you could say, hey, I know current conditions are kind of weak for this business, but I feel like the stock's cheap enough and it's, it's down a lot. So it's kind of discounting a recession. And I believe it'll be in better shape in two years and I'll buy it here. Like, that was a completely reasonable thing to say in the 1990s and even first half of this millennium. But like now the market is crushing the companies that are cheap that miss because it's saying, hey, there's a serial correlation there. The probability they miss again is higher than the unconditional than the unconditional probability. So I think that's changed. Like the market's gotten increasingly anticipatory and, and right on average.
A
Is that something that's, is that something like regime specific or is that something that's just continued to change over time? Like more and more companies get penalized over time as, you know, as, as we learn more about this and the market gets smarter about it?
B
Yeah, I, I always struggle a little bit with that question, like to, to give a confident answer because like, how long do I need to see this before I conclude it's not spurious? But it's, it's not just regime recycle. You know, we wrote a note last week actually on like 10 things I used to believe that I don't believe anymore. And they were like, things that really have changed since COVID so more like five or six years, which I think is long enough to say it's not spurious. And I think, I can't prove this, but I think the way money's being run now, where so much money went to passive or super low fee and so much money went to multi strats that are running factor neutral with high turnover that I could see this being more structural and mechanically on how, how the market behaves. So things like valuation not working, or high quality not working, or other things probably are more structural.
A
That's one of the things that you said that early in the interview too. And I think it's such an important lesson for investors. This idea of like the N is very important in these variables. Like you'll see on X all the time, someone will be like, every time this happens, the market goes up X percent or something. And you're like, what's your sample size like 5 times or something like that. Like it's so important to remember that. That's such an important, I don't, I
B
don't know this guy, but I want to. There's a website called Tyler Vigan. I get no financial benefit from mentioning this T, Y L E R V I G E N. And I bought his book also and it's called, it's, it's a little too far for me to reach without putting my midsection into the camera here, which nobody wants. But it's Tyler Vigan.com and it's a spurious correlation website. And it's just got all these awesome things of like, you know, it just shows, you know, like a small sample size, like 9 or 10 data points, annual data points. And it'll be like a curve and it'll be like number of rainy days in Maine and you know, a number of times, you know, it just completely ridiculous spurious correlations. And they look perfect. And it's sort of always these good examples to realize like you could be concluding something that's preposterous with a small sample size. So I, I, I, I like that. I like, I agree with what you said there. The only challenge is like does this get spread around enough on X where it becomes like a self fulfilling prophecy and like that we don't know. And it could be right. Like like the May comment you made Justin made at the beginning. Like maybe, you know, people just start thinking that September is always a crap month and then you get a couple first bad days the beginning and it's like self fulfilling, you know, and then you see it posted on X by a thousand bots and you know, do.
A
It's funny because like in the quant world that made me think of esg because ESG is something you should not get a premium for over time, like doing something good. But like at the point that everybody started adopting esg, like ESG went crazy. Like again this is the idea is once everybody starts believing ESG is going to get them extra returns, like it kind of went nuts. It might be a bad example, but I just thought about that when you were talking about that.
B
Yeah, I mean that one's a tricky one because it's confounded so much by size and quality. Right. Like bigger businesses just can afford to have a lot more ESG frameworks or whatever. Like, you know, I've actually spent a lot of time on that topic. I wrote a note I think in 2021 called we analyzed the ESG ETFs that were out there at the time and think the note was called 49% S&P, 49% NASDAQ, 2% ESG. Because that's basically what the, the stocks in the, in the ETFs were. So it's trickier. I mean, I think we can all agree that G matters, like just the governments and for sure. But it's, it's harder to measure some of that S and E stuff, you know, like, it is, you know, is your. Are you guys. E. I don't know, like, you're. Whatever. I mean, you know, like, it's hard to measure. Like. What do you mean?
A
Yeah, yeah, no, definitely.
B
Yeah.
A
And obviously that's, I mean that's kind of died down anyway. Like that was, that was all over everything for a long time and now like you don't even ever hear about it anymore. Ye.
B
In Europe you do. You know, I'm on the board of a European company, public company, and it's definitely bigger in, in Europe and Scandinavia. And I think also, like some allocators want that. And so obviously if you're trying to gather assets, you. You may have to show that you are. But, but I think in the end, like, your, your point up front is right. Like you want to. It should be meritocratic. Like whoever generates excess returns, to use your phrase, like should, you know, command the premium.
A
Just one more, one more thing on estimates. You had this thing I saw in one of the interviews. You're talking about this, this idea of estimate achievability. And, and I know that goes beyond like a lot of people are like, is it going to beat or is it going to miss on this quarter? And that goes beyond that. So can you just explain that?
B
Yeah, I mean, I guess tying into the thought of like the penalty for missing is harsh and the reward for be part for beating. Like, how do I tighten things up? One thing I like to look at this is going to be on the nerdier side of what we've talked about so far, which we like worrisome to
A
somebody nerdy is great for our audience.
B
Okay. But I do a regression for every stock between change in sales and change in income. So that regression, if you do like year over year scatter plot is the incremental margin. So let me just make sure we're all on the same page. Let's say I'm a 30% gross margin business, right? So I. My gross profit's 30 cents on a dollar. The question is, what's my gross profit going to be on every new dollar of revenue above today's level. Right. So I do $0.30 on my first dollar, but maybe I do $0.40 on my second dollar. So if I get $2 in revenue right now, I'm going to have $0.70 in gross profit or 35% gross margin. Right. So we spent a lot of time thinking about what are embedded in the consensus estimates for incremental gross margin. And if the incremental gross margin expectations are in line with the business model average, that might increase the probability of achievability. If they're way above what the business usually does, that something has to fundamentally tie. Did they just move all their employees to a low cost jurisdiction? Did they have a big drawdown on depreciation roll off? Did they have big price increase that, that everyone's excited about the new product? Like there's me something that you can explain to me why the expectations for incremental margin are way above what they normally do. Because analysts are decent at. Actually their analysts are not very good at anything, but they're pretty good at knowing fixed and variable costs from the businesses. And so you should have a decent idea about SM achievability by looking at incremental margin. So I, I like, I think about that. A decent amount actually.
A
Yeah, it's interesting, that's an interesting point because the, the idea is as, as it scales, you know, those margins are going to change. So a lot of people are kind of looking at where it is now. But, but looking at it as it, as it scales, how it changes is probably a far. Going back to what we talked about before is far more important to talk, to think about.
B
Yeah. When I used to do semis, it was like the classic way to look at it is what are the incremental gross margins? And I'm guilty of applying semiconductor logic to a lot of sectors. But like, you know, look, we think about it in our own business too, right? Like you, you, when you, when you're scaling, you have, you know, costs that come in the door, but your incremental margin should be pretty high.
C
I just saw that Micron just crossed $1 trillion market cap. It's up 16% today.
B
Yeah, you never would have guessed that based on 25 years ago the business they were in. So yeah, they're whatever they are the 15th or 4th, 13th biggest company now, whatever the heck they are. It's crazy. Yeah.
C
What are your thoughts on sort of the mags?
B
I had a financial advisor tell me last week that they got 10 new clients that are like 10 million or above Micron shareholders that were just like regular employees that now have 10 million bucks.
C
Oh geez.
B
Micron stock. So it's been a boon for the financial advisor industry.
C
There's going to be a lot of new SpaceX millionaires out there too pretty soon. So yeah, financial advisor is going to be busy. I wanted just to get your thoughts on the Mag 7 here. I mean you have most of these companies, Microsoft, Meta, Google, Amazon, you know, they're all spending ridiculous amounts on this AI infrastructure build out. But then you have, you know, Apple basically the lone wolf that is basically doing it through partnerships and not necessarily a big cap expense. So I just, I wanted to get your thoughts on how you're thinking of positioning the Mag 7 and anything, you know, company specific that you're paying attention to.
B
Yeah, so our general advice has been to tell institutional investors to keep market weight. The bolus of the eight names and we count Broadcom in there too. The idea being that one, they're pretty macro stocks, meaning you know, they don't have a lot of company specific risk. Market goes up, growth beats value, large beats small. You can kind of tell how they did that day. Two, they're the most well covered securities in the world. So I always think it's funny where somebody thinks they have a non consensus view on one of these names that's pretty hard to have and then you know, three, like it's a really concentrated market. So I don't think people should have their highest conviction views on one of these names. They're better off being close to market weight the group and then having higher conviction in other things that are a little bit easier to have an edge on. So most institutional investors have big active weights there or they're underweight. The retail side's been a little bit more overweight and that's how the weights the weight. So I don't know. I feel like the answer is keep close to market weight to group. But if you put a gun to my head, like I kind of like Nvidia still. Just as I feel like the hyperscaler spending is not going to wane anytime soon and their position with Cuda and all the money they lost for years, it's going to be hard to do any complex modeling without that platform. So I don't love how the stock acts when they blow out the quarters, but I just don't see how they're not going to grow so fast for the next couple of years.
C
Adam, we always love having you on with these conversations and we could talk about, you know, for a lot longer about a lot of different things, but I wanted just to sort of close out on some of the work and the findings that you've done, which I find this very interesting in regards to spinoffs. And I think your research shows that the average spinoff, you know, tends to meaning meaningfully outperform its industry or peer group for a couple of years, while oftentimes the parent of that spin off lags. So could you just sort of explain that sort of data that you're seeing in spin offs?
B
Yeah, I mean, I agree with that. I think spincos have unlocked a lot of value. You know, it's complicated, Justin, because oftentimes the Remain Co is getting a tax benefit and that's the catalyst for doing it. But I could see a regime here in the next few years where AI, AI productivity, smaller companies being able to compete with bigger ones creates a wave of spinoffs, actually. And I could tell you it's somewhat popular at the law firm clients we have and on board discussions to consider SpinCo. So I'm, you know, I think it's a pretty good way to unlock value, particularly when the spin is in a slightly different sub industry than the Remain Co, where maybe there's not as many synergies, etc. So it'll be interesting to see if that's the new wave because M and A generally hasn't been that effective. The acquirer underperforms. So I think, you know, there's always you, you could make an argument that we got so many big companies now that you need to sort of make them smaller again. And maybe that'll be cyclically the next wave that happens over the next five or ten years.
C
Before we let you go, what is the highest conviction out of consensus idea that you and the firm has right now?
B
I mean, out of consensus and wrong are really correlated. And so for me it's been the healthcare sector that I think will work. And I just think the whole point of AI, or a big point of it is we live longer and we're more productive while we're alive. And so we have this aging demographic where people demand services, tools, diagnostics, drugs, et cetera. These businesses tend to be low margin, probably can benefit from incremental efficiency, can benefit from predicting their customer employee behavior. And so I feel like the market's telling me the government isn't going to pay for stuff at a rate that I think is wrong. I think the government, there's no political will on either side to cut the spending. The Amount that's in some of these names. And so I tend to like the drug distributors, the managed care, the Quest and LabCorp like the tools like all those kind of businesses that I just think will end up growing above GDP and have margin expansion but that has been out of consensus slash wrong as an aggregate call. Like the drug distributors were great stocks but then they get sold off harshly and managed care works and like we haven't seen things work at the same time and I think they should. So you know I like healthcare a lot. It's, it's, you know, it's uncorrelated to the tech bet which we're making is the most number of transactions in any sector. You know, top three on pipes and IPOs and follow ons and all, you know, all that stuff. And then you know, and, and you know, so I think portfolio construction wise it works too. But you know, it's been out of consensus slash wrong though by the way,
A
if there's something you want to be really optimistic about with AI like healthcare is a place like we may see some incredible breakthroughs like in the next decade or so.
B
Look, I, I, I spent a lot of time in this area. I took an AI for healthcare course at MIT a couple years ago and I got sort of mesmerized by the potential. Do you guys have wearables? Any or aura or any of those things?
C
Jackie? Yeah, yeah.
B
Poop or whatever. Okay, so yeah, it, I think what's going to happen in a few years is every house that's built is going to have a giant box that's like a wearable by your bed that's going to be tracking the electric and magnetic waves and everything and it's going to send you an email saying hey Justin, we made you appointment. We noticed you're drinking too much Gatorade during your. No, I'm kidding. But it's going to, it's going to know like everything that's wrong with you and really like the efficiency, like the healthcare tech convergence is going to be massive. Think it's underappreciated but that's been wrong. That's the most out of consensus call we have. And I, and I feel like what the market's telling me 0% chance healthcare is the best performing sector in the market over the next five years and I think it's 30 or 40% or whatever. I'm just trying to play that arm.
C
Thank you Adam. We really appreciate you coming back on and joining us. It's a day after Memorial Day hit in the morning with a nice conversation,
A
so we appreciate it. Yeah, thanks.
B
Thanks for having me. Great to see you guys.
C
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A
should be construed as investment advice. Securities discussed in the podcast may be holdings of the firms of the hosts or their clients.
Episode: Cheap Is a Warning, Not a Thesis | Adam Parker on What This Market Is Really Pricing
Date: May 28, 2026
Guests: Adam Parker
Hosts: Jack Forehand, Justin Carbonneau, Matt Zeigler
This episode features Adam Parker of Trivariate Research joining the Excess Returns team to dissect what today’s market is “really pricing.” The conversation debunks the notion that “cheap” valuations equate to opportunity, explores the limits of commonly used market analogies (“bubble,” “sell in May”), and dives into the realities behind AI adoption, capital spending, factor investing, software vs semis, and the behavioral shifts driving valuations. The episode is loaded with sharp takes on the dangers of simplistic value metrics, the quirks of index mechanics amid mega IPOs, and why healthcare is a misunderstood outcast despite immense potential.
“It might be trading on a distribution of outcomes of 2030 fundamentals or 2031 or something in the future.”
— Adam Parker (00:30, 07:47)
"The sectors where the estimates are up the most year to date are tech and energy. ... the three worst performing sectors are consumer discretionary, financials, and healthcare.”
— Adam Parker (07:47)
"The stock market leads the economic data, not the other way around...The economist meeting should be after the equity meeting."
— Adam Parker (03:33, 04:21)
"Only 9%, 262 out of the top 3,000 public US equities are currently generating any meaningful AI revenue."
— Adam Parker (00:30, 09:25)
"In the next year, man, we better see some, some, some serious productivity."
— Adam Parker (10:54)
"Maybe this will be, you know, kind of more of a hiring boom, both corporate wise and economically than people think."
— Adam Parker (11:04)
"I wouldn’t be shocked if this thing went to two and a half trillion or three trillion, just almost independent of price, just because people have to buy some to catch up and not much has floated."
— Adam Parker (14:02)
“The biggest issue is they’re just floating very little. So the people who need to get big chunks, 3%, 4% positions... are going to be buying this thing almost like with no instruction until they can get a lot of it.”
— Adam Parker (18:57)
"The more down the income statement you go, the more BS there's in there... More than any other margin level, the change in gross margin and the change in multiples... are highly correlated."
— Adam Parker (19:42)
"My highest conviction call right now is not being sucked into any rally in software."
— Adam Parker (22:31)
"...the last thing I want to do is buy a cheap software company that doesn’t grow and try to play it for its cash flow like the market’s right on average to make the ones that are cheaper, cheaper because they're more likely to be made obsolete.”
— Adam Parker (22:31–26:07)
"My North Star is still semis over software for sure."
— Adam Parker (27:09)
“Valuation doesn’t work to pick stocks... It’s almost arrogant now. If you say I buy a stock because it’s cheap, you’re just saying you think the optical valuation has information in it. You see it’s cheap, but no one else... thinks it’s cheap. ... Stocks that are cheap are cheap for a reason.”
— Adam Parker (33:04)
“The penalty for missing is way harsher than the reward for beating. ... The probability they miss again is higher than the unconditional probability.”
— Adam Parker (34:11)
"We spent a lot of time thinking about what are embedded in the consensus estimates for incremental gross margin. ... If they’re way above what the business usually does, something has to fundamentally tie."
— Adam Parker (40:52)
“I don’t think it’s a bubble in terms of price action... I’d rather be a couple weeks late and ride it over the edge than miss out on the continued upside.”
— Adam Parker (05:34)
"You need a few hundred more years to prove it statistically significant... That’s a little astrological."
— Adam Parker (01:24)
“You could be concluding something that’s preposterous with a small sample size.”
— Adam Parker (37:13)
"Our general advice has been to tell institutional investors to keep market weight [in] the group."
— Adam Parker (44:06)
“If you put a gun to my head, like I kind of like Nvidia still... their position with Cuda and all the money they lost for years, it’s going to be hard to do any complex modeling without that platform.”
— Adam Parker (44:06)
"Spincos have unlocked a lot of value... I could see a regime here in the next few years where AI, AI productivity, smaller companies being able to compete with bigger ones creates a wave of spinoffs."
— Adam Parker (46:11)
“For me, it’s been the healthcare sector that I think will work. ... I like healthcare a lot. It’s, you know, it’s uncorrelated to the tech bet which we’re making... I think the healthcare tech convergence is going to be massive. Think it’s underappreciated but that’s been wrong. That’s the most out of consensus call we have.”
— Adam Parker (47:18, 49:04)
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