The Bulls Are Trapped with Alex Altmann

Speaker A: I sort of always like the east side better than the west side. Just personally

Speaker B: depends what for. See, I think the west side doesn't skip a beat on the water, right? Because you got,

Speaker A: oh, like Hudson Yards,

Speaker B: but just the whole strip, Right. So you obviously have Battery Park, Tribeca. Uh, then you got soho, Meatpacking,

Speaker A: West Village. We're not going to go that far from the train stations,

Speaker B: you know what I mean? Like, and then soon, and you got Chelsea, Hudson Yards. Even Hell's Kitchen's kind of fun, uh, on the, you know, the right environment. And then you've got Upper West, Lincoln Square, and then Upper west, which is where I am. And like, the whole stretch is just beautiful.

Speaker A: I love the Upper west side.

Speaker B: See, I mean, that's the only. I lived in Tribeca when I was single. Is this recording?

Speaker C: Yeah. Also Alex,

Speaker B: it is. Okay,

Speaker C: when we start,

Speaker B: I'll just stop there.

Speaker C: When the show starts properly, you could drop the Halloween British accent and talk normally.

Speaker B: Yeah, exactly. Yeah.

Speaker A: Uh, you like on Riverside or.

Speaker B: Yeah, I'm on Riverside

Speaker A: Boulevard, one of my favorite neighborhoods.

Speaker B: Oh, yeah. I

Speaker A: love

Speaker B: it. You know it.

Speaker A: I love my best friend after college. Uh, so I was Upper east, he was all the way there. So it's a pain in the ass to go see him. But like,

Speaker B: I

Speaker A: love that neighborhood.

Speaker B: It's changed completely. So they built the park all the way south to 59th Street. Now all on the water. So

Speaker A: you could run all the way down,

Speaker B: all the way down. And you've got obviously the. Be

Speaker C: great for you.

Speaker A: Where's the boat basin?

Speaker B: Oh, it's up on 90 something.

Speaker A: Okay. Cause that's a whole thing also in the summers.

Speaker B: Yeah. I've got a friend who owns, ah, one of those.

Speaker A: Have you been

Speaker B: there?

Speaker C: No,

Speaker B: it's like a restaurant, boat thing.

Speaker A: I think the Upper west side's beautiful. Uh, I also, I like Hudson Yards. I would work there,

Speaker B: Hudson Yards. But the office is expensive there. It's like

Speaker A: it's $250 a square foot to touch anything on a decently high floor.

Speaker B: Yeah. Forget it.

Speaker A: I don't. It doesn't make sense for us. We're not in the 2 and 20 world. So, um.

Speaker B: You and me both, mate.

Speaker A: Yeah. So I think we'll figure it out. But, uh, I'm delaying that project as long as possible because it's a big decision. You gotta sign 10 year leases in Manhattan.

Speaker B: Listen, a lot could happen in the next 18 months. We'll talk a bit about it on this pod, I guess. But like, you know, you could see I mean, it's very plausible that we see a recession before the next election and you might actually get a decent opportunity to scoop some commercial real estate at, uh, like, attractive prices. If a bunch of businesses go pop,

Speaker A: oh, the whole city, God

Speaker C: willing,

Speaker A: literally anything, anything could happen.

Speaker C: Anything for a good deal. All right, let's go.

Speaker A: Yeah. Boys, how we doing? Ready? All right.

Speaker D: It's the compound episode.

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Speaker A: Thank you, thing one. We appreciate it. Mr. Cole in Halloween regalia. Ladies and gentlemen, welcome to the best investing podcast in the world. Four out of five dentists say the compound and friends is where they get all their financial news. We appreciate that. We have a new guest. I'm so excited. I've been looking forward to this conversation since we booked it. Uh, I'm really pumped for this. Our guest today is Alex Altman. People call you Alti, I've been told. Is that a thing?

Speaker B: There's a story to that, but yeah, sure.

Speaker A: All right, you'll get into that in one second. Alex is managing director and global head of equities tactical strategies at, uh, Barclays, where he generates thematic ideas and market content for the bank's equities and global global markets clients. The Barclays Equity Tactical Strategies, or Bets team generates tactical ideas from the trading desk and turns them into research for clients. Before Barclays, Alex was a macro portfolio manager at Millennium and spent a decade running equity trading strategy at Citi. So he's seen the markets from both the buy side and the sell side. Alex, thank you for being here. We really appreciate it.

Speaker B: Thank you for having me. Chris,

Speaker A: the crowd is going wild. Can you hear that it's unbelievable. It's run perception, uh, for the benefit of the audience. How do you define the term tactical and what is different about the work you do at Barclays versus other tactical trading desks or research groups that refer to themselves as tactical?

Speaker B: Sure. Okay, well again, thanks for having me guys. I mean tactical is a really easy answer. It just means it's camouflaged and you know, has, has weapons involved. Right,

Speaker A: Many. A lot of pockets.

Speaker B: Yeah, exactly. Just unnecessary pockets. No, I mean like tactical in the traditional sense of Wall street will mean that rather than thinking about your typical research outfit that will look at 6:12, even longer time horizon, 6:12 months, uh, we're trafficking in the shorter time horizon, more suited, but not exclusively to the fast money community. So we're thinking one week, two week, four week, maybe eight weeks ahead. Not really much beyond that. We have thematic views, we have views that have sort of been prevailing for months, if not years in some cases on some structural opinions. But we're generally trying to think four to eight weeks out and say, all right, how are we going to make money? What are markets are going to want to do? Where's the best asymmetry? And then the other aspect about the tactical consideration is we traffic a lot in verticals of the market that your traditional research outfits tend to not cover. So we'll think about positioning, derivatives, quant, what a hedge fund's up to. Um, and these are really important verticals or pillars of the investment process that uh, quite frankly all of the buy side are doing. But a lot of the sell side still kind of don't cover from a traditional research perspective. So we try to basically match the desk investment process to what the buy side or the guys that we typically talk to what they're doing. And that way we can have a pretty sort of like pari passu, head to head conversation.

Speaker A: The hedge funds want to know what other hedge funds are up to.

Speaker B: Yeah, they do.

Speaker A: And not purely like from a gossipy sense. Well, that too. They want to probably, but they want to know. So positioning has become something really important in the market. Michael and I joke about it. Anytime there's something going on in the market and we can't explain it, we go

Speaker C: positioning.

Speaker A: It's positioning

Speaker C: and it is,

Speaker A: but it's. But people want to know. People that are managing money professionally want to know what their peers are doing. And I think they recognize the limitations of like a traditional portfolio manager survey which sort of just comes out like groupthink. Um, so I guess you guys become a repository for well, here's what your peers are, here are the trades that people are putting on and why

Speaker B: that's one aspect of it. And then there's other aspects about positioning. Okay, so positioning can be instructive because obviously flow tends to dictate price. Right. And price dictates narrative. So in theory you can carve up. And uh, quite frankly I do follow this mantra, which is if, you know, if there's a positioning asymmetry that has been built in the market, does it have the propensity to change price in a very asymmetric way and in doing so can shift the market's perception of a narrative?

Speaker C: And situational awareness was a perfect example of that.

Speaker B: Perfect example of it. Right. And you get that periodically throughout any given year. You just need to have a framework in place that allows you to kind of monitor, uh, a lot of things simultaneously. So are we monitoring single stock positioning? I mean, we can, is the short answer, but we don't because generally if you aggregate up to like theme, sector, quant style.

Speaker C: Good enough,

Speaker B: good enough. And of course like aggregate market. So you want to know how a hedge funds position? How are mutual funds Positioned? How are CTAs positioned? How are volume control and QIS strategies positioned? How is risk parity positioned? If you kind of get that right. Oh, how is retail positioned? That would be probably the biggest

Speaker A: is the idea that's. So that's an opportunity to go the other way. Or not necessarily betting against an over, uh, an asymmetric positioning, but maybe just as like intelligence, like where is the money right now?

Speaker B: Correct. And so sometimes it will actually provide an informed conclusion about taking a contrarian bet. Other times that's not necessarily the case. And that applies pretty much universally. So what we tend to do is back test a lot of these positioning reports that we run against what the forward returns of whatever asset we're interested in. And then in some cases it can actually validate the view and reinforce it. So that is, this position's crowded, but actually based upon all of our backtesting, the crowding means nothing. And actually the forward returns are really good. And other times it will say the opposite. Where you want to take a contrarian bet and sort of say something controversial.

Speaker C: I feel like there is a school of thought that short term predictions are a total fool's errand. And I would say for most, for the casual investor, of course it is. Right. Trying to predict the market in the short term for most people is a total waste of their time. Do something else. But the idea that you have clarity. A, uh, year out in today's investing world sounds so insane, given how fast things are moving, that if you are going to make some sort of market call, tactical call. Yes. Zero to 30 days probably is reasonable.

Speaker B: Yes. And so I'll give you a couple of stats that, uh, can sort of help clarify that a bit. Right. So if I told you that if you were to buy the S, let's just use the S and P, it's easy, right? So if you were to buy the S and P on any given random day and you were to hold that position for 42 trading days is equate to about two months. The odds of you making money, right. Uh, is about 73%. And your average return will be around about just shy of 200 basis points. 190 basis points. That's pretty good right now. That's better, way better odds than going to a casino and playing any game. So if you consider that your baseline, you're effectively trying to either outperform that or underperform that. And I think that's where the randomness comes in. Because if you're going to just sort of buy the S and P and hold it and just sort of take a kind of a passive view on it, then the odds are you're gonna be right more time than not. So really, what you're ever trying to do, if you're gonna consider the tactical considerations, is you're trying to basically say, okay, are the odds materially deviating from that 73%. And we have a framework, which is actually pretty good. Is it perfect? No. Cause if it was, I wouldn't be sitting here telling you about it, uh, or talking to our customers about it.

Speaker A: You just run it internally and keep your mouth shut.

Speaker B: I'll keep my mouth shut from a beach.

Speaker C: But you have the data. So the way that a lot of gamblers lose, just a casual gambler, there's, uh, whatever, 20 games over the weekend, and they'll bet on 11 of them. And there's obviously no edge. You don't have to swing at every pitch, you don't have to bet every game. But when there is reason, when the data says, hey, uh, whatever, 80% of the time, do nothing. Right. Mostly noise. But 20% of the time, we have a 54% chance of making contact, and we'll swing when it makes sense to do so.

Speaker B: Yeah. And so in our case, obviously, we'll work on kind of the opposite, where we're generally looking for the 80 to 85 90s in some cases, hit rates, where we'll look at, uh, kind of the forward return profiles, whether it's on the S and P, whether it's on a, uh, particular style factor or whether it's even on a sector. And the hit rates look really attractive based upon pretty robust, not just back tests, but just very long sort of out of sample and in sample periods. So. Good case in point. Right. So our main framework that helps guide whether we want to be bullish or bearish, it's called Betty. It's Barclays Equity timing indicator. We were originally going to call it betting, but then kind of compliance. Had a bit of an issue with that,

Speaker A: uh,

Speaker B: unsurprisingly. And it's of. All it is is that you say we have all the data, everyone has access to data. If I told you what all of these inputs were, you could build it yourself. It's. There's no secret source. It's just a case of aggregating a bunch of stuff that's already available in the market and knowing that when a significant or a sufficient number of them are flashing either positively or negatively, you know, in your head and on paper, statistically, what the forward returns of the S and P are more likely than not going to do. And we have the whole, the whole thing laid out. And that's really our guiding light from a quantitative framework. And then the qualitative framework is the positioning. It is talking to customers. It's knowing what the organized narrative is in the market. And hopefully this is where it becomes more of an art than a science. You've got the science bit right. The art bit is pulling it all together. This is the bit that AI hasn't figured out yet is like pulling it all together in a way that you can say, okay, all the ducks are in a row. I think we got, you know, now we, um, to use your parlance, we have to take a swing.

Speaker A: Can you go back to what you said about the order? How, how you get to narrative? It start like. It starts with. It starts with what? Because I agree with the premise. Uh, I just. I sort of think like, um, whatever Price is doing that becomes the story that everybody accepts. It just takes a little while for that to be transmitted around the street. And then it's, uh, funny, like you hear people saying something on Thursday, like five people will say the same thing, and they arrive there because of whatever Price just told them. It almost never works the other way, where somebody is going against Price and people accept that narrative. Does that make sense? Like what I'm trying to Ask you.

Speaker B: It does. And that's. I would mostly, for the most part, I, uh, think of that as noise, is because people will use price to justify narrative or they'll explain something ex post. Because a price moved a certain way rather than necessarily providing real intelligence behind it and go actually, uh, challenging the view. Does that make actual sense? Right. And so again, that's not always the case, but there's often times in the market where things just move because maybe there's a big print, someone had to put through a certain trade and it was done in a sloppy fashion. Moves price. Everyone said, oh, what just happened? That's particularly, uh, prone, like in the oil market at the moment, you know, oil will move around by a dollar or two and then everyone jumps to a conclusion that some random headline from someone you've never heard of,

Speaker A: that's the reason.

Speaker B: Yeah, that's the reason. It's like, okay, maybe there was an algo that responds to a certain headline. That's obviously the world we live in. But more often than not, it's just noise.

Speaker C: Do you take every qualitative signal or quantitative signal? And the reason I ask is if you say it's just data and everybody has the data, then there's gotta be something else. You need some sort of, I don't know, situational awareness, for lack of a better phrase here. Um, so for example, the analytics in football might say, go front and fourth and one every time. But there could be. Well, it's like, yeah, but we have the momentum, our defense is strong, this offense sucks. Just punt it away and live to see another day. So how much of the qualitative overlay dictates it? Or do you just. It's just 100% quantitative, 82% chance we go no matter what.

Speaker B: No, no, no. The qualitative aspect is really important. That's what I was referring to before. And where there's art rather than just science, There are plenty of strategies in the marketplace that are just literally, you know, inputs, uh, and outputs. And if it's good quality inputs, you get good quality outputs and vice versa. But I'm a big believer that the discretionary overlay is really powerful. It's really important. And, you know, I kind of experienced that firsthand when I was running money as well in so far that if you just rely on a quantitative process and you inside your own bubble, I think it can work. Clearly, there's guys who have had phenomenally successful careers running those kind of strategies, but for me personally, I believe there's real power in Talking to the community and getting a really good qualitative assessment of what the zeitgeist is and then building the quantitative framework alongside that to see if they match up or if there's a discord. Right. And if there's some kind of dissonance between the two, then that to me is usually where there's a real opportunity. Because I'm a big believer personally that and today in this environment is a perfect example of that where you've got this so called prevailing narrative that suddenly everyone is bearish on AI, right. Because of what happened in the financing space or whatever it may be. And I conduct surveys. We just sent out a survey just today which uh, we conducted yesterday. We had 200 investors that came, which is a pretty good sample size from the Wall street community. And it's a high quality survey. And the feedback was overwhelmingly not bearish on, on AI. Right. Only 60% of people that responded thought that we had a financing problem. I'm like, how can that be? We have a financing problem because we've just gone through one over the past two weeks. So that number should have been 100%.

Speaker C: So what does that tell you?

Speaker B: Well, it tells me so that that's the start of a story, right, because you've got dissonance now. You've already got, okay, customer feedback is everyone's bearish. AI survey says you're wrong. Okay, let's check the positioning data. So traditional hedge fund PB positioning data from some of my competitors will say hedge fund nets are super low, therefore everyone's bearish and they've all sold tech. What they may not necessarily tell you, and this is in no way me sort of like pooh, poohing the quality of work from competitors. But what that data probably doesn't show necessarily or people overlook is that the range of net exposure changes by hedge funds is minimal. It will go from 48% to, to 55% back to 48%, right?

Speaker A: Yeah. Uh,

Speaker B: why of course? Because a lot of these guys are RV pod shops and so they're just running market neutral strategies. So in reality that they have no or little market sensitivity beyond their betas within the portfolio. So I don't care what they're up to. And we can, we've run stats around this. So the point being is, is that we'll use the positioning data where we think it's valid. So what are retail positioned in huge vertical? I mean the largest owner of stocks is the retail community. Next largest owner M mutual funds and levered ETFs what are they up to? So these are the verticals. What are volume control funds are up to? Those guys have significant equity length, QIS strategies. Ditto cta. Ditto. So you build up a quantitative picture across your framework and you say, okay, what does the positioning metrics actually look like? Now let's compare that to what the prevailing narrative is. And now let's compare it to what our customers are saying.

Speaker C: What do you see in retail? Is it dumb money as people say, or have they been. I feel like they've been pretty damn right the past this cycle with buying dips,

Speaker B: vast majority of retail portfolios would have outperformed institutional portfolios.

Speaker C: What does that tell you?

Speaker B: Tells us a few things. First and foremost is they have more holding power. Right. So a lot of the hedge fund community are operating on much tighter drawdown limits because their mandate. Um,

Speaker A: they're being observed.

Speaker B: Correct. The

Speaker A: retail account is not being observed by anyone other than the holder and the holder's wife.

Speaker B: Yes. And, and, and, and, uh, and it's something they want to brag about to their, their friends at a dinner party. I

Speaker C: bought the debt

Speaker B: I bought. But they're

Speaker A: not answering to a committee about why they're, uh, overweight semiconductors. They're just overweight semiconductors because they want to

Speaker C: and why they draw down 400 basis points.

Speaker A: Right,

Speaker B: Right. And the only thing that will basically cause them to stop out is either their brokerage account basically margin calls them or they lose their job. That's it.

Speaker A: Yeah.

Speaker B: Right. It really is all about. People always ask me, oh, what gets retail to sell? I'm like, lose your job or when your neighbor loses their job.

Speaker C: So there's been, there's been times where retail has dumped stocks. Like, obviously. Is that, is that a buying opportunity or. Not necessarily.

Speaker B: It depends on the starting point and how long it's been going on for. So what if I told you we've got data on retail back to around about 1995, like good quality data. Data. And what we do. Is

Speaker C: that relevant still in today's world?

Speaker B: Absolutely.

Speaker C: Hmm.

Speaker B: It's more relevant today than I think it's ever been.

Speaker C: Wow, that's surprising. Why do you say that?

Speaker B: Well, because, you know, the devices. Okay. I guess we have to kind of go back into history a little bit. 2019 was a real demarcation for retail trading. Not 2020. 2019. Uh, people don't really talk about it. And that's because in October of that year, it's when zero commission trading was introduced. Right. And it just so happened to coincide with the launch of Robin Hood. And some of the, you know, the more gamified this is when

Speaker A: Schwab said zero, Fidelity said zero and zero became the standard

Speaker B: zero. Exactly. Yeah, right. I remember. So there was very, very low frictions trading. Then what happened Covid. Right. And then what happened?

Speaker C: Everyone trades.

Speaker B: Bunch of stimulus checks. People sitting at uh,

Speaker A: home. 40 million new brokerage accounts open in 18 months.

Speaker B: Exactly. Yeah. So but really, I mean would non 00 commission trading have changed it? Probably not. But I do think it's important because you know it effectively lowered your transaction friction to, to, to nothing. And then you've got a bunch of people with stimulus checks and nothing to do and they're basically, you know, let's face it, we're all degenerate gamblers. So a lot of people basically got involved in that and, and that obviously coincided with a significant short term correction in equities. They

Speaker C: didn't leave. They never left after the bear market. They're still here.

Speaker B: They're still. Oh no, no, they, they. That's not true. They did. So there was a degree of selling by retail the retail community in 2022 and that was a deliberate financial tightening exercise by the Fed. Right.

Speaker C: But it was, but it was short lived. Like if you look at the percentage of overall volume it's still pretty. It's still high. Is it 25%

Speaker A: the retail share of trading is still where it was.

Speaker B: Oh in terms of the share. Yeah. But what we tend to track is the evolution of both cash balances and margin balances as a percentage versus the natural drift of the

Speaker A: retail got blown out of spacs and all that shit just like everybody else did.

Speaker C: Nvidia felt 75% and so did Meta in 2022. I mean that was terrible.

Speaker B: It was. Yeah. It was a bad time for retail invest and retail genuinely lost money. But they didn't. They did sell but they didn't

Speaker C: leave.

Speaker B: They didn't completely get out of Dodge. Yeah. And then ever since then 23, 24, 25, 26. Regardless of whether we've had those economic wobbles or not, they've just kind of been pretty.

Speaker C: So how is the data from the 90s relev to today?

Speaker B: So in terms of the comparable. Yeah, so we've blown through everything we saw in the 90s. The ownership of uh, the US household ownership of stocks. Today you've got approximately 2/3 of all American homes that own stocks. That's way higher than dot com. And the other stat which I sort of love to throw around Is that the next highest? 35%. Yeah. 35% of US household net worth is now in equities, the highest ever. The next highest wealth channel is unsurprisingly, um, home equity. But the gap between stocks and home equity in terms of your wealth percentage

Speaker C: closing

Speaker B: is the widest it's ever been in history. Going back to the 1960s. We've only

Speaker A: got. But isn't it obvious why, like homes have appreciated 0% over three years thanks to interest rates. The stock market has doubled. Like, of course,

Speaker B: of course

Speaker A: it's not causal. It's the reverse.

Speaker B: There's a whole bunch of, uh, other stuff. I mean, think about over the past really since 2022, mortgages have been completely unaffordable. New homes and existing home sales have plummeted. The housing market's basically been dead or zombie.

Speaker A: It's a housing market recession

Speaker B: for all intents and purposes, with housing really not doing much right in terms of prices. Um, so you've got a bunch of, you know, gen Y gen zers with money m that they savings that they've accumulated where they're going to put it. They're not putting it into a new home anymore. They're putting into the stock market.

Speaker A: Yeah,

Speaker B: right. So you've had that constant inflow that we estimate. If you think about where like typical new mortgage origination from home equity down down payments, 2 to $300 billion a year plus you got the 401k money that comes in every year. That's between 8 and $900 billion on our estimation. Right. So between that you've got over a trillion dollars. Then you've got a trillion dollars of buybacks. Even if you haircut that a little bit for the executions being low, you're still talking about 750 billion.

Speaker A: This is guaranteed, this is almost guaranteed buying like 401k money.

Speaker B: 401k is guaranteed.

Speaker A: It's like the weather. Like it's coming in,

Speaker B: it's coming in as long as people have jobs

Speaker A: and it's valuation insensitive and it's just, it's, it's automated.

Speaker B: Yeah. Because it's effectively like, you know, life plan, you know, retire at Target. Life target, whatever it is, you know, 65. So it's sold. You

Speaker A: had that at 900 billion a year.

Speaker B: Yeah.

Speaker A: Okay,

Speaker B: so the way I worked it out was number, um, of, uh, homes in America. And then we sort of haircut that number to assume that not every home can contribute to a 401, whether, you know, for whatever reason. Then we assume 12% contribution, uh, of your paycheck, um, and your median household income is $88,000. So we kind of, you sort of solve for that math and you haircut a little bit more. You get between 8 and 900 billion.

Speaker A: Yeah. So I wrote something about that 11 or 12 years ago on my original blog and I called it the relentless bid. And I basically said there's like three things driving this. Because the question back then in 2014 the market had just made an all time high in 13 and there was still a lot of bad news and euro zone stuff and people I don't understand why does this market ever sell off? Right? Like it just crashed spectacularly. Uh, every time there's bad news it wobbles and then it goes right back to highs. And people were struggling with that. And I basically said it's the combination of buybacks shrinking the float wasn't even at a trillion a year yet it was on the way. Um, this 401k money which I felt had been underappreciated. And then a third factor that I don't think anybody was talking about, the business model transition from stockbrokers to financial planners and wealth management. Transitioning from my broker trades stocks for me to my broker allocates the ETFs. And uh, that was trillions of dollars. If you look at Morgan Stanley going from predominantly trading commissions to predominantly fee based, what does that do to the way the market behaves? I argued it's a volatility dampener. There's more guaranteed money into the same 500 stocks every time people allocate to their wealth accounts. So we've been living in that world now for over a decade. Oh,

Speaker B: uh, yeah,

Speaker A: yeah. Uh, and I think it's like, I think it's a big reason for why the VIX so quickly evaporates every time it gets going. Like it just, you've got, all right, two weeks go by, the 401k money comes in. Um, the financial advisors who used to trade stocks, now they're just rebalancing ETFs. You could almost set your watch by it.

Speaker B: Yeah. And then now on top of that you've got the lever, you've uh, got the call overwriting ETFs. You've got kind of very deliberate volume selling products that are further suppressing or supplying gamma and vega, not to use these Greek terms, but like uh, you know, supplying volatility to the market as well on top of that. But you know, to answer the original question, you know, retail are uh, kind of all in on stocks. Part of it's involuntary because they've kind of lost faith in the home. The home ownership slice and also just the fractional nature of stocks is very appealing to younger individuals. Right. I don't need to cough up, you know, if your median home price in the US I don't know the number of. To my head, I'm guessing it's between 3 and $400,000. You know, you don't have to cough up $60,000, $50,000 for a deposit. I can go and buy a share of Nvidia or a share of the S of SPY or whatever and just forget about it. It unfortunately does create vulnerabilities in our economy. You know, and people ask me all the time and I know we're going to be tangential here, but what keeps you awake at night? Is it like Levitt ETFs or is it Iran or is it AI? I'm like, no, it's retail. It's. Retail is the scary one in the sense that because we've got such a financialized economy, right? Like even last year during the tariffs, when the S And P fell 20%, there was a visible drop in consumption. Over the subsequent two months,

Speaker A: negative wealth effect,

Speaker B: huge. And because it's real time, unlike.com, where you. But

Speaker C: that also scared people, there's massive uncertainty in terms of what the economy was going to do. I don't think it was just the stock market falling.

Speaker B: You're right, it wasn't just the stock market falling, but the average individual really had no concept about what the implication of tariffs was going to be in that moment. Right. They

Speaker C: were scared.

Speaker B: I think they were scared. But more importantly, in 2000 when we had even. It wasn't comparable today, but it was reasonably comparable in terms of the amount of equity ownership in households. You had to wait either for a monthly or quarterly brokerage report. Right. Most people did well. You know, they were looking

Speaker A: alerts, uh, into your hand 27

Speaker C: times a day.

Speaker B: You are seeing your real time wealth adjustment. Right? And that's very powerful on both the way up and the way down. You know, I kind of had this running joke that the stock market is the economy. Now, the old adage was stock market is not the economy. No, it is the economy. Now.

Speaker A: I agree with that.

Speaker B: Right.

Speaker A: I say it all the time and people get pissed off about it. But I really think it's more than ever.

Speaker C: I agree.

Speaker A: The centricity of the stock market, it used to be like an avatar, loosely speaking, for how companies are doing and then people would say, all right, but what does IBM and Coca Cola have to do with Main street like now? I think it's basically, um, we've built retirement around the stock market. Everybody's all in. Every household with high income also has a large 401k. Now we've tied compensation to the stock market. You think about all the young up and coming millionaire households. They all work for companies that are about to go public, just went public, have stock prices like, um, this is it. You can't have a prolonged two year bear market without a recession. It's impossible because everybody's wealth effect and everyone's mentality is based on how much money their accounts are worth. And so I totally agree with you.

Speaker B: Yeah. And the messed up thing is, is that I would challenge any economist on the planet no matter how good they are. And there are some phenomenal economists that I work with at Barclays, but I don't think any of them actually have a cell in their econometric model that measures S and P. Right. So they're monitoring everything.

Speaker A: Who does? The Fed does.

Speaker B: Well, the fed had their FCI

Speaker A: process looking at the 10 month moving average, looking at the stock market. I think they know when they've overstepped. I watched that play out in 2018. It was the most obvious thing in the world. It come out early December. We're nowhere near, uh, neutral neutral. And then on Christmas Eve of all times of year, we're in a 21% statistical bear market, like just past that 20% threshold. That doesn't really mean anything. But in the media bear market, they reversed themselves on Christmas Eve.

Speaker B: Yeah, I remember.

Speaker A: And a month later, not only are we perfectly near neutral, actually we're gonna start cutting rates again. That's literally what happened. How could it not be the 10 month moving average or the, or the 200 day or whatever?

Speaker B: You know what's amazing about that period in 2018?

Speaker A: Yeah.

Speaker B: It was also a midterm year and it was also a new Fed chair.

Speaker C: And Mnuchin was very chatty, remember that? He came out out of nowhere and said, don't worry, there's ample liquidity. Everybody was like, what the,

Speaker A: in the, in the great financial crisis, um, 10 years before, there was one Bloomberg terminal at the Fed in Washington.

Speaker B: Yeah.

Speaker A: There's one person in there looking at the markets. You want to bet there's 1,000 now?

Speaker B: Oh no. But I know that both the Treasury Department have Bloomberg terminals because they ping me

Speaker A: and

Speaker B: then so does the New York Fed. Well,

Speaker A: there's a Hedge fund manager running it. So I'm just saying like everything is the stock market.

Speaker B: Yeah.

Speaker C: Can I show you a stock market chart? I want to get your thoughts on this. So this has been an interesting year, um, for a million different reasons. And even though there is the relentless bid, um, AI has caused a lot of on off days. Same with software, same with energy. There are a lot of days where the stock market does X and the average stock goes the other way. So this is weird negative beta effect. Um, Soc Gen has a Great chart. Chart 15 Daniel, that shows the. They say there are 124,750 possible pairs of companies within the S and P. And at present 40% are negatively correlated. So they show the average stock correlation within the s and P500 and they compare that today. So the red line is the average and the black line is today. Mhm. 40% of days we've seen stocks going different directions in the overall index. It is a very funky time within the stock market.

Speaker A: Yeah, it's a lot less like 20, uh, 17. Every stock went up together. There was no volatility,

Speaker B: zero.

Speaker C: Matter of fact, today's a perfect example. So the last couple of weeks we've been talking about the same thing. Breath sucks, breath sucks, breath sucks. And we've been saying all right, but that's a feature of a bull market. You want the biggest stocks doing the heavy lifting. Usually when breadth is leading. Not usually, um, the average stock does better in a bear market. Just think about 2000 is a perfect example of this right after the dot com bubble bust. So today you have the equal weight up 98 basis points. The S&P is down 53.

Speaker B: Mhm.

Speaker C: And it seems to be that this is happening more with more and more and more frequency. So There's a bad Mag7 report, Google today for example. And the rest of the market catches a bit.

Speaker B: Yep. And you're asking?

Speaker C: Just, just, we're just talking.

Speaker B: We're just talking. Okay. So I can actually give you there's a pretty good answer for why this is happening.

Speaker C: Oh yeah. I don't think it's a mystery.

Speaker B: Uh oh, I'm curious.

Speaker A: I don't know. The answer was what's the, what's the reason?

Speaker C: Well, I think earlier in the year it was energy. It was a lot of energy stocks going up when the market went down. And that was this weird negative beta effect.

Speaker B: Yeah.

Speaker C: And then it was interest rates. Right. Interest rates went up. Consumer staples got killed, Reits got killed, utilities got killed. Max 7 was especially Apple completely undeterred and Apple's the biggest stock in the world. And then it was the software, uh, AI days on, off, on off, on off. I think it's been those three things. What else am I missing?

Speaker B: So there's like a unified, um, narrative that basically puts all those together. Um, and it goes back to our friends at, uh, RV Strategies. Relative value. Right. So if you think about, um, multi manager Aum in 2018, 2019, uh, before COVID was around about $300 billion. And today it's like a trillion.

Speaker A: Yeah.

Speaker B: So it's basically tripled since COVID And

Speaker C: so who are you talking about? Like Citadel and Millennium and those type of companies.

Speaker B: Well, name names.

Speaker C: Right,

Speaker B: but, but, uh, you know, multi managers pods, you know, basically guys where effectively their job is to isolate idiosyncratic alpha as opposed to be taking large directional bets. Right. So they'll encourage their managers to run high gross, low net exposure. And it makes sense, right? Why, why has there been explosion at AUM since COVID Well, because. Well, really since 2022 when interest rates went up. And it's because in a high interest rate environment, RV strategies are absolute no brainers. Right. Because I deploy a load of gross on my long side, load of gross on my short side. I actually haven't really deployed a dollar unit, so to speak. I've got plenty of risk, but I take my actual capital M haircut for collateral from my PB requirements. And

Speaker A: then you're earning a spread. Uh, you're earning an interest rate on the rest.

Speaker B: Correct? Right. So whatever your collateral commitments are, let's say that 15% aside or whatever, but you're taking the 70% and you're earning that, you're earning that 5%. You probably even get more than that in relatively safe.

Speaker A: That's the low net part. You're offsetting with your longs and your shorts. And then you're collecting, uh, an interest rate on whatever you don't have to allocate.

Speaker B: Correct. And because these businesses are run so, they're run so efficiently. That's why you're given very strict mandates on what your net exposures can be. Right. Because it's not you breaching some horrible limit. It's actually just because as an organization, they want to sort of manage effectively. There's a Treasury function, essentially.

Speaker A: Yeah.

Speaker B: And it's a very good business model. It's, you know, and all you're doing is you're trying to isolate that idiosyncratic alpha. Now here's the catch. If everyone's doing it right, it's not just a handful of funds. Everyone's doing it. Everyone has access to the same risk parameter metrics. So they're neutralizing their value and their quality and their size and their growth and all the rest of it. They're also obviously neutralizing their sector exposures and they're neutralizing their market exposure. But the number of stocks you can trade has shrunk. We talked about this equitization already. Right. So

Speaker A: like 3,000 stocks basically.

Speaker B: Right. And that number has gone down over time, not up. Right. It's

Speaker A: started in the business with like 10,000

Speaker B: and it's net negative issuance in the sense that we're having few. We've had fewer IPOs and more buybacks. So by definition there's less available stock to trade. Right. So with those combination of factors, plus the ballooning of aum, plus leverage from PBS on top, you end up with this crowding out effect. And everyone will say, oh okay, hang on a second, it doesn't matter because I've neutralized everything. No, all you've done is push the crowding into other aspects of your portfolio that you are either aware of or unaware of. Right. And this really matters because when you've ballooned the size of the number of strategies, so to speak, you're creating more of these vicious uh, or the propensity for these vicious unwinds.

Speaker A: So everyone unwinds one aspect of a portfolio at once. It hits the stocks three times harder than it otherwise would have.

Speaker B: Correct. Which is why you're seeing very little index volume and an absolute ton of factor volume

Speaker A: and

Speaker B: negative correlation. And

Speaker C: you see the stocks that are like obviously Spotify and Netflix are related. Ish. But for a year it was the exact same chart, like identical. And there's a million different stocks like that, that trade, that just trade. They're just in the same basket of stocks that people are buying and selling.

Speaker B: Correct. And by the way, a lot of those people are uh, actually ah, just computers. Right. So you've got obviously very sophisticated quant funds that are running sort of real time stat op strategies that are looking for the one day or even intraday, you know, price differential. They can play mean reversion. So there's those playing the super short term stuff. You've got the discretionary alpha guys which are looking for time horizons im, which is called, let's call it three to six week. And that's generally on single stock pairs as well mean reversion around earnings. That's why on earnings day the majority of a single stock Flow is coming from discretionary. And then on non earnings day, the vast majority is coming from quant and retail.

Speaker A: And then in the media, people are looking at the preponderance of all of this data and they're coming up with the story that explains it to non market participants who don't appreciate the degree to which. This is computers. Trading with computers.

Speaker B: Yeah.

Speaker A: And it sort of reminds. I taught. I taught my. My daughter. My daughter had a unit. I remember in elementary school they were learning about Greek mythology. So she's like sitting, reading this book. She's like, she can't make heads. Heads. Why are they giving us fairy tales to read? I said, you don't understand. This was science. Like, why does the sun rise in the east and set in the west? Oh, uh, it's because Apollo on his chariot is being pulled across the sky and he's glowing and so that's the sun. Uh, why is there an earthquake? The gods are mad you did this. Why is there a volcano? Like, this is what humans do. Even if it's absurd, they have to explain it. So in the media, they're looking at the net result of all this stat arb and everything that's happening. That's not a satisfying explanation. Did the market change its mind about AI Today is. Yes. And because. And then they find the headline that explains why it changed its mind.

Speaker B: I mean, this is the shameless plug to like the team, you know, like, the whole point of why we exist is to kind of we the bets team at Barclays. Like,

Speaker A: how many of you are there

Speaker B: globally now? We're 11.

Speaker A: Okay.

Speaker B: Uh, so we've got three in New York. We've got three in, um, in London, and we've just hired additionally in Asia. So we've now got five,

Speaker A: 11 people on the bets team.

Speaker B: For now, yeah.

Speaker A: Now, is it true you guys are allowed to kill?

Speaker B: We. We are. We are kill only. Yeah.

Speaker A: Only,

Speaker B: yeah. Kill, yeah. We're not. We're not in the capture business.

Speaker A: Okay.

Speaker C: What do you do about earnings season? So, like, for example, today, ServiceNow is down 27%. Is there like a blackout period where you're like, all right, we're just. What we do on the tactical side does not work when there are these major announcements.

Speaker B: It's a really good question. So, um, this is why maybe one day bets will be 12 or 13, because we want to get more involved in a single stock business. I mean, Barclays has phenomenal spec sales that cover specific sectors and so on and so forth. That's their business. And we partner with them but from a kind of macro thematic perspective we tend to stay out of the way. So for me earning season is an environment where

Speaker A: it's landmines

Speaker B: there, that was the word I was trying.

Speaker A: There's almost no

Speaker B: tactical,

Speaker A: there's no structure to it until you put one on it. Like you can't. The traditional way of thinking about how stocks are trading, then a company comes out and a random comment in a conference call could take a stock from being up 10% to down 10%.

Speaker B: You

Speaker A: can model that.

Speaker B: The only time where we really get involved in any season is the fact that uh, equities, to the benefit of my career, equities have become more macro. Right. AI is a macro theme. Right. Hyperscalers are no longer just institutional securities for the, you know, for moms and pops. They are, they are, they have eyeballs on them from every single corner of the investment community. Whether you're a credit guy, macro guy, retail, whatever. Right. So those businesses during earnings season I will, I will scrutinize just as much as uh, the next man. I'll listen to the conference calls, we will put them through natural language processing. We'll talk to obviously our spec sales and we'll talk to research, we'll talk to all the great teams that we can within Barclays to be as informed as an equity investor. We are equity investors but be informed at a micro level. Luckily for me, I started my career as a single stock Analyst uh, in 2004 at JP Morgan. So my DNA is kind of there already and I pivoted to Macro in 2012. So I've got kind of like a bit of that legacy, um, muscle memory to be able to sort of go into that during earning season if we need to. And we kind of need to now because you know the Google results were all about that, Microsoft results uh, were all about that. We're obviously going to get, I think we're getting Amazon tonight. Right. So you know, these do matter and whilst AI is the theme and you know, we can talk about that, whether it's going to be a theme for the future,

Speaker A: what's driving like two thirds of the economic growth or coming from some CapEx related spending that has to do with AI.

Speaker B: You want to know Wildstat?

Speaker A: Yeah.

Speaker B: Yeah. So next year, next year, 2027 consensus S&P earnings, 75% of that is expected to come from semiconductors and hyperscalers.

Speaker C: Great. Love it.

Speaker B: Right.

Speaker A: God, let's hope there's not a financing problem, uh, problem that extends into next year.

Speaker B: Like it's, it's wild. So I mean I took, I mean we kind of joke around it. It's like the S and P has just become the Cosby. Right? Yeah,

Speaker A: yeah.

Speaker C: Meta is spending 70% of their top line on CapEx, of their top line of their revenue, just on CapEx. It's unbelievable. Dan, you could throw up chart eight. So I'm curious to get your take, Alex, on how much the equity issuance is impacting the stock market. So we're looking at Microsoft cloud revenue growth.

Speaker A: I think it needs like 10 minutes to digest everything.

Speaker C: So the chart on the right, the chart on the right is year over year revenue growth and as you could see, it's accelerating. Okay. Obviously because of the AI trade, cloud is the beneficiary. So it's growing at 30%. It hasn't grown at this rapid of a rate since the third quarter of 2022.

Speaker B: Mhm.

Speaker C: At that time it was doing $23 billion in revenue. The fact that it is accelerating when it is literally almost three times the size is unmodelable, unfathomable,

Speaker A: um, unpredictable.

Speaker C: Unprecedented. And yet today the $25 billion debt offering and the stock is down. I mean they cannot have done, they cannot be doing any better, cannot have had a better quarter. Stock is down.

Speaker B: Yeah. So shouldn't we just be asking the question of if you're spending that much money and right now. Yeah. You've got phenomenal revenue growth, what's it going to come at the cost of? Right. Last time I checked, I think Microsoft's still operating cash flow positive right now.

Speaker C: It is,

Speaker B: I think it's the only one.

Speaker C: Also, the stock had a monster run. All right. So it's at an all time high, basically. Um, but the bar is high.

Speaker A: Just the shock that we were in a 15 year period of um, massive buybacks and now that's gone into reverse. Now we're looking at stock issuance from not every company, but from these gigantic companies that are super meaningful to the index.

Speaker B: Yeah, yeah,

Speaker A: it's a different environment.

Speaker B: We talked about that. So yeah, we did a lot of work around this and it was. Okay. So you can't just look at equities in isolation. That's the first thing. Right. So you're right. So 2026 on our modeling numbers will be a positive net issuance year.

Speaker A: Yeah.

Speaker B: Which is basically going to be, from what we can tell, essentially the barely.

Speaker C: Okay,

Speaker B: but goes back to that discussion earlier when, if you're, if you typically were retiring, net negative issuance of 4, 5 $600 billion a year and now you've had a multi hundred billion dollar swing.

Speaker C: It's different.

Speaker B: It's different. Right. And then the second thing is the competition for capital. Right. Because 2026 net IG and high yield issuance is going to be $1.2 trillion. Right. And then obviously the government needs to go cap in hand as well.

Speaker C: But it's all being absorbed still.

Speaker B: It is for

Speaker C: the most part.

Speaker B: But risk premia has widened as a function of it. Right,

Speaker A: let's put some of his charts up and uh, let's do chart 11. Daniel. So tell us what's going on here.

Speaker B: Okay, so this is just simply looking at the uh, it's just an equal weighted index of the spread of a bunch of data center bonds against uh, the equivalent benchmark, uh, which I think the average duration is about 17 years. So we just took the 20 year um, uh, treasury and you can see that that's sort of steadily widened and now it's sort of not steadily widening. And like. So yes, you're right, it is being absorbed, but at a price. Right. And so the prevailing market narrative right at the moment, when we talk about narratives, is that there is no price, that this AI trade doesn't make sense. Nvidia will tell you that. Meta to a degree will tell you that. Microsoft probably tell you that based upon their revenue growth numbers. Right. But the reality is a little bit different. There is a price. Right. And I think what the market is doing right now is trying to get to the point where that price is. It's trying to work out is there a price where you guys won't want to pay.

Speaker A: Put up a, uh, chart 12. So you are saying this

Speaker B: is my favorite shot.

Speaker A: The first time there has been real competition for capital in a higher interest rate environment. What are we looking at?

Speaker B: Right, so this goes back to the point that you're not, you're not just issuing in a vacuum in equities. You're issuing at a time when the government's trying to get money and they're running a significant deficit. The debt market, whether it's hyperscaler issuance or otherwise, just other corporate financing needs, are issuing, As I said, $1.2 trillion in net issuance.

Speaker A: The competition.

Speaker B: Yes.

Speaker A: Right.

Speaker B: And then equities is now you've completely offset or mitigated the buyback effect. Right. And so you take each market in any given year and you work out how much issuance was as a percentage of that market size. And then you get a percent, obviously you add up those three percentage numbers and then you basically put it on that as a dot and you compare it to where two year yields were in that year.

Speaker A: So why is this such an anomaly this particular year? Uh,

Speaker B: good, uh, question. So effectively this chart is just telling you that, you know, Corporate Finance and Econ101 holds true over a very long period of time. And this goes back to I think 1995 if I'm not mistaken.

Speaker C: Meaning higher cost of capital, less issuance.

Speaker B: Correct.

Speaker C: Uh, kind

Speaker B: of makes sense, but apparently

Speaker A: not today

Speaker B: we've decided, and this is like the AI narrative, AI can ignore that. Right. And the chart before the ig, uh, chart of data centers debt is telling you you can't ignore it because spreads are widening and they're going to continue widening to the point where it's effectively going to either test or break the market. And we're seeing cracks already. That's what coreweave is about. That's what Neo Cloud's more holistically about. It's about the fact that actually AI financing does have limitations. It may not apply today to hyperscalers who still are cash volcanoes, but it is certainly applying to levered, uh, plays on forward compute.

Speaker A: Well, so the market efficiently is uh, I guess like the way to think, the way I would think about this is it's rationality in the market.

Speaker B: Yes. It

Speaker A: got to core weave before it got to Alphabet, which is the way it should work. Yes. Okay, give me Ah, 13 guys. What um, you're saying equities are also finally catching up to the moves in credit by way of a bid to quality. And this is your balance sheet efficiency, I guess explain to the viewers what they're looking at and why this is meaningful to you.

Speaker B: Yeah, sure. So look, obviously what we try to do, uh, as a team is try to take relatively complex concepts in the market that may or be produced by other parts of the bank or by us and present them in ways that kind of make sense. Right,

Speaker A: right.

Speaker B: And so equity markets are amazingly efficient below the surface. Right. A lot of people just look at the S and P and go, it just goes up or you know, whatever. And yeah. And as we know recently, there's these tons of rotations and those rotations, some of them make sense, some of them may not. But this is a classic example of like one of the visualizations of that rotation. Right. And it's hard because this is a slightly longer time series, but essentially what it's telling you, the orange line is the behavior of

Speaker C: those are stocks.

Speaker B: Those are, this is A basket of stocks on the long side versus a basket of stocks on the short side. So it's an RV trade just like the triple C versus double P spread is also.

Speaker C: So this is intuitive. If you need to borrow money, money's expensive, you're in much bigger trouble than the companies that have a stronger balance sheet.

Speaker B: Exactly. It's actually a very straightforward concept which is the market is efficiently starting to basically tell you that if you're a lower quality balance sheet business. Yeah, the equity is going to start getting hurt uh, because the chances are you might need to tap that equity channel to start raising money because the debt channel is not available.

Speaker A: Is there a world where the neoclouds that seem to be uh, challenged to continue raising money at the rate that they have. Is there a world where they flame out and this never ends up touching the traditional hyperscaler stocks and they sort of just sail past it? Is there a world in which this is actually a new comparative uh, advantage for the traditional hyperscalers and it actually helps their stocks for there be chaos amongst uh, the nebbyuses of the world. Like how do you think about that?

Speaker B: So you know what I call that? I call that the trade after the trade. Yeah. So

Speaker A: I call it that too. But let's explain to Michael what we mean

Speaker B: in the sense that ah,

Speaker A: trade after the trade. Like just like. I mean I could explain it but I want to hear

Speaker C: Corvette's only $33 billion market cap. When is it like could Nvidia, if it goes low enough, would Nvidia just buy it and just put this to bed?

Speaker B: So if I listen. I don't know exactly what Jensen's thinking in his head. Obviously last week he told basically in corporate parlance told, uh, core weave to kind of go pound sand. Right. He basically said I have no interest in helping you guys out at all. Why would he. It's trading above the IPO price. So that move lower needs to be a lot lower before I think you'd even consider uh, from an equity perspective. But why would you even do that? He

Speaker A: doesn't want the equity, he wants the assets.

Speaker C: So you

Speaker B: buy the bonds.

Speaker C: But is there a Jensen put, like if things get bad enough he could just say one thing and chill everybody out. Maybe it's much lower. But

Speaker B: my suspicion is given how central Nvidia have become to the entire ecosystem and we've all seen some version of that chart with the

Speaker A: codependency.

Speaker C: Yeah,

Speaker B: yeah, it's

Speaker A: like your Greek

Speaker B: mythology analogy. And um, so I don't want to sort of speak and say, yes, there would definitely be a point where, where Jensen would do something like that, but it would be logical that he would, if there was a proper shakeout that someone like him who's already got vested interest would, would look to sort of hoover up assets. But also you've got to remember that could come at the expense of his own share price too. Right. So everyone assumes that the hyperscalers are completely immune from this. And the way I think about it is, and it's not the right analogy, but it's the only one I can think of is subprime and G sibs. Right, right. The just because you assume that these businesses have got fantastic operating cash flow that they're going to be completely immune from any AI unwind. And I think that's a very unrealistic proposition.

Speaker C: Um,

Speaker A: they basically went to zero. You talk about like Fannie Freddie.

Speaker B: Right. But again, I don't want to draw too strong a parallel to the gfc. I just mean in terms of, you m know there were guys who uh, really saw the subprime thing coming and they're like, I'm going to short the equity tranche, I'm going to go along the AAAs. And they both went to zero. Right. I'm not saying that hyperscalers can do zero. What I am saying is that the AI is touching everything. We've uh, talked about factors in this conversation. There is no way to correctly map the AI factor from what I am aware. I've tried, my team has tried and we can't do it. It keeps moving too quickly, the betas keep changing. Right. So you're either long AI or you're short AI Goes without saying the hyperscale is a long AI. So if there is a prolonged or protracted unwind of the AI trademark or the AI factor,

Speaker A: nothing is immune.

Speaker B: Nothing's immune.

Speaker C: But until then I

Speaker A: agree with

Speaker C: you. But of course. But immune is very strong of a word. But they have shown to be resistant, resilient, whatever you want to call it. Daniel, chart 14. So similar concept as what you were just showing the spread between uh, this is from the daily chart book. The spread between B and triple C credit has reached nearly 8%. Something seen only four other times since 1996. And on every other occasion the S&P 500 was already at least down at least uh, 12% below its 52 week high. And of course we're right near all time highs right now. It's just an unusual environment and they have proven to be Resistant.

Speaker B: Yeah, they really have because they've got this phenomenal earnings delivery. And you showed that Microsoft chart as an illustration of that

Speaker C: helps.

Speaker B: It helps enormously. But what we have seen is the market derated spectacularly, including those hyperscalers themselves. Right. And a lot of that is driven by memory stocks. When

Speaker C: you say derated, do you mean on, uh, the forward multiple? Do you mean on the.

Speaker B: Yeah, on the forward multiple.

Speaker C: Nvidia's 15 times. Nobody wants it.

Speaker B: I mean, I think there's also holding constraints, as in too big. It's 8% or 9% of the S and P now. So yeah, like a lot of these mutual funds, they can only buy up to 5% of their portfolio in it. Right.

Speaker C: But it's a size problem.

Speaker B: I think part of it's a size problem. Part of it is also that sort of codependency in terms of the whole AI ecosystem. There's that problem.

Speaker C: Thank God they're not trading at 40 times forward earnings. It'd be 13 trillion doll.

Speaker B: Well, the S and P would be at probably 12,000. So that would be a high quality problem. Certainly from an American wealth effect perspective.

Speaker A: I want to double click on, uh, the net issuance because I really think that that is game changing just in terms of changing the mentality of the market. I really think that people just felt like no matter how bad a company's results, S&P 100 company, you know, they're buying back stock and I can just ride it out and now that's no longer the case. Um, chart 16, guys, you're showing us net US equity issuance. Um, I guess, uh, you've got four colors here. So give us the story of the markets because this is a lot of years of this 30 years of data and this is a really big change now.

Speaker B: Yeah.

Speaker A: Versus the environment that most of us have grown up in. So tell us what you think is what's going on here. What's the implications?

Speaker B: So we did, we produced this chart a few months ago. Um, and I'm quite happy to say that it's a lot of it was based upon predicted or estimated for 2026. And for the most part we've been pretty accurate on this. So uh, and the easy bit is ignore. We know really what gross issuance. Sorry. Um, this is just in equity. So we know broadly what the M and A slice is going to be because a lot of most announced M and A is kind of completing in the year. So that, that sort of.

Speaker A: So the deals that were announced in 20, the deals that are announced in 1H26.

Speaker B: Yeah,

Speaker A: you have a reasonable amount of certainty. Like most of them will go through and they'll happen in 2H26.

Speaker B: Exactly. So how much stock is getting issued, how much stock has been retired from the M and A. Um, and then obviously from the actual, the issuance perspective, we also have at the money offerings from hyperscalers, we have converts, we have any other um, additional equity raises that need to be done. Um, and then obviously we have IPOs. Right. So IPOs is probably the bigger moving target. That and the, at the money offering. And obviously we had one large IPO this year.

Speaker A: We'll have the two biggest of all time inside of six months.

Speaker B: Uh, well, I mean, who knows?

Speaker A: SpaceX and then Anthropic, if it works.

Speaker B: SpaceX and Anthropic and obviously OpenAI got punted into 2027 we think. But obviously this is just a 26 forecast. So the idea being, um, the one thing that we didn't solve for, we solved for, we guessed is that the buybacks, you'll see that the red line or the red bar is basically flat year on year. So what we did was uh, executions and buybacks are always going to be less than announcements. Everyone like loves to highlight, oh, $1.2 trillion of announced buybacks. I'm like, yeah, but if you

Speaker A: authorized but not completed.

Speaker B: Correct. And the execution rate is typically somewhere between 60 and 70% of the authorization. They never, they never complete all of it. And so we basically said, all right, we'll keep it static year on year. Which I actually think is quite a generous number because of, you know, let's face it, all these businesses that are doing buybacks historically are now doing uh, massive capex program. So I don't even know if we're going to reach that kind of buyback number. But give the benefit of the doubt to say yes, they'll do approximately the same number as last year. You can clearly see that the gross issuance has exploded. A lot of that's because of IPOs. And consequently you haven't increased your buyback.

Speaker A: The blue bar is along the top.

Speaker B: Exactly.

Speaker A: It is now double the size of last year. Ish. Like just eyeballing the issuance, the new stock, I mean, is there a theoretical limit where it has to stop?

Speaker B: Well, there isn't a theoretical limit, but if you sort of hark back to the dot com period, you can obviously see in 99, 2000 you were dealing with sort of similar explosion in the numbers. I know they look small by today's comparison, but at the time they were massive. And ultimately, if you remember what broke the equity market back in dot com, we had a prolonged period of, of negative equity risk premium. But that persisted for years. It was the fact that we were just bringing too much paper to the market and the economics of those deals just didn't make any sense.

Speaker A: Yeah,

Speaker B: right.

Speaker C: We got, uh, some interesting news in the after hours.

Speaker B: Oh yeah, Amazon

Speaker C: intel down 25%.

Speaker A: Is that bullish?

Speaker C: Amazon Guys, Amazon down 12.

Speaker B: Is intel the one the government owns?

Speaker C: Sandis

Speaker A: own a nice chunk.

Speaker C: Don't worry, Sandisk is down 9.

Speaker B: Oh,

Speaker A: Amazon's down 12.

Speaker C: Right off the bat, um, semis were down 4%. So. All right, tomorrow's gonna be a day.

Speaker B: There we go. Did I mention I'm bearish

Speaker A: positioning? Um, what is your outlook between now and the end of the year? That seems to be your time frame.

Speaker B: Couldn't we have led with that? Because now I look like, oh, I'm bearish. No,

Speaker A: no, no. I read all your stuff. I know that you've been, I wouldn't say getting more risk off, but most of your notes are, uh, cautioning.

Speaker C: No, we know you've been wrong all year. Until

Speaker A: then, what do you tell. What do you. What is the message from the bets Research just about the environment, let's say between now and year end.

Speaker B: Okay, so, um, backdrop is. I, uh, mentioned Betty, our sort of quantitative framework. So that basically had been signaling various degrees of risk off ever since the end of May. So we were like mega bullish through the Iran thing. And then end of May we were like, okay, this is, this is, our model is just telling us to get out, like really to reduce risk. And then we had that big momentum unwind in the summer. Right. At the end of August, we changed our fundamental assessment. We were still cautious on the market, but it was like, okay, we have no idea where these AI revenues are going to come from. You know, we need a trillion dollars of revenues basically by the end of 2028 to pay for all of this CapEx,

Speaker A: all the commitments and CapEx.

Speaker B: Yeah. And right now our run rate for then is going to be somewhere around about 400. Right.

Speaker A: Okay.

Speaker B: It's just we're not there. We need to plug that gap. And so, you know, we went out to Asia. We really just went to the lion's den, spoke to a bunch of investors out there and we're like, hey, this is our whole roadmap. This is basically where the capex is. The capex number can't go any higher. 1.2 trillion for next year, 1.4 for the year after. Like maybe it moves by 100 billion here and there, but we're kind of at terminal point now. Um, I just don't see where the revenue is going to come from. S and p, top line, $17 trillion. It's about five and a half trillion dollars of profits. And we will say all of a sudden we're going to magic a trillion dollars. The cumulative revenue of Apple and Microsoft, two of the most successful tech companies in history since 1990 to today has been $9.8 trillion, inflation adjusted, not even 10 trillion. Meanwhile, SpaceX are telling you that their TAM's 30. Right. So the TAM of the universe,

Speaker A: in fairness, their TAM is every dollar ever spent on human capital

Speaker B: in the universe. Right. It's not

Speaker A: ever again.

Speaker B: Not just on Earth. So it's the GDP of America have

Speaker A: to adjust for Pluto, Neptune.

Speaker B: That's right,

Speaker A: yeah.

Speaker B: Uranus.

Speaker A: Okay, so

Speaker B: you know that joke.

Speaker A: So is the mark, so is the. So is the market now going through the throes of this realization that there's just not enough revenue to make any of this make sense until all the prices adjust. Is that what we're living through?

Speaker B: I think we're living through a, uh, reassessment about on the ROI debate, which by the way has not. It's not the first time we had. We had that debate in 2024 too. And it came with a capex hickey in the summer at the same time with the BIJ and a weak NFP and the S&P took like a 12 14% dent then as well. And we had one in 2025, although it was commingled with whatever thing was going on with tariffs. So to have these AI summers and winters is not uncommon. And so the end of August was sort of our demarcation to say, all right, I'm ready to lean into a much more bearish view on AI because of that revenue aspect. And then we also had sort of separately but related talked about this sort of competition for capital narrative back in the summer as well. And then we sort of just merged those two stories together. And that's kind of where we sit today. So our quant model is still telling us be very bearish tactically. Right. Camouflage. And then, uh, and then the AI bit and the financing bit. So people say like, oh, what's the catalyst for the market to go down? I'm like, at this point I don't really need a catalyst. Right. I'm kind of like you've got all the ingredients, they're already there. The financing bits kind of already catalyzing the revenue bit. I just don't think there is a specific catalyst that we can really lean into. The capex commitments are kind of already there. So those numbers aren't changing at the very earliest until probably the full year results in January. Right. So I'm like. And then our quant model is kind of telling you that real rates are high, spot volume correlation is high, that CTA's volume control, less CTA is more volume control and QA strategies are extremely long. Equity risk right now retail is extremely long. So the

Speaker A: bull, so the bulls might be trapped at least for the time being until expectations change or prices change.

Speaker B: Yeah. So people say, like what would get you more bullish? Well, you know, again, uh, our quant framework would be helpful for that. But really just for me, the clearing price of risk being lower just would be quite frankly very healthy for this market. Even if it comes with some near term damage,

Speaker C: we could use a little bit of a slap on the wrist. It's been a minute.

Speaker B: It has been a minute. It's

Speaker C: been below 20 forever and ever.

Speaker B: And the largest pullback we had so far in 2026 around Iran I think was 8 and a half percent.

Speaker C: Not enough.

Speaker B: It wasn't a lot. So in my head I've got between 71 and 7200 which is around the 200 day moving average. Right. That gets us down to about 17 and a half times forward. NTMPE

Speaker A: take a lot of risk out along the way to get like at that level you're just repricing everything basically.

Speaker B: You reprice everything and then I think we can go again. You know, I think there's probably another round of chip financing. There's probably another interesting, more

Speaker A: innovations that people get excited about.

Speaker B: Yeah. Like I mean do you remember when the iPhone came out? The most exciting bit of technology at the time was when you had that app, uh, that you could like drink a beer. You know, it had the gyroscope in it. Yeah. Like clearly that was not peak iPhone. Right. So I don't think we've yet even discovered or even imagined what peak AI is going to look like years from now. So I'm being a very, I'm trying to be very open minded about the bullish aspect of AI too. Everyone's like, oh, you're just a bear. I'm like, first of all, I haven't been a bear all year. And secondly like,

Speaker A: and it's Tactical. What you're saying is tactical. We've

Speaker C: spoken to bears. This is not, this is.

Speaker A: No, because then you get into Q1 and some, uh, biotech company says, we just got through a phase three trial 30% faster than we would have without AI uh, or the robots start showing up in workplaces. It's just like, there'll be more to it. But I do agree with you, like, all right, now we're getting these tech earnings and the reaction is negative.

Speaker B: Yeah.

Speaker A: Where do we go from here? If not a repricing of.

Speaker C: You're right, the capex spend, as we're seeing, as we're learning with these earnings announcements, it's exhausted. People are just not buying up, buying it anymore. The stock price,

Speaker A: people don't want to hear it anymore.

Speaker B: And you know who the first were to, to really sort of cry wolf about that? It was Uber. No, it was the Asian investor investment community. Because even at the. When was this? Right at the beginning of September, that's when I was out there in Hong Kong and Singapore and I came out there with like my big, oh, I don't know where the AI revenue is going to come from. I'm being really smart about this. And I went out there and every single meeting, every single meeting I had pushback. Being there would be like, what do you mean? Like, but semis are trading so cheap and this and that. And I would give them my whole rationale as to why I was sort of cautious. And at the end of the conversation, 90% of them would go, yeah, we agree with you.

Speaker A: Oh, my God, look at you. Look at you.

Speaker B: Love that. And

Speaker A: then. And so that's. So the realization for you is, okay, there's this facade of everybody wants to seem M positive, but everybody has that same reservation or that same concern deep down.

Speaker B: Yeah, I mean, look, look at the poll, poll I sent around today. Uh, the vast majority of investors still want to be bullish. Right. They want to buy semis because they're cheap. Right. They want to be in the AI trade because they use it. And they, I

Speaker A: think they want to be seen as they get. It is another big component to this

Speaker B: mass very much on the west coast, that,

Speaker A: yeah, people don't want to be the anti AI guy. You look like a crazy person or a loser.

Speaker B: Well, also, chances are if you've been anti AI any period for the past three years, you

Speaker A: look like an idiot.

Speaker B: Or you've been. Or you've lost your job,

Speaker A: you've lost your. Okay, I agree with that.

Speaker C: Supplies for the urine. But we're not super bearish. Just a little bit bearish.

Speaker B: No, I'm like as I said, I mean

Speaker A: tactically bearish due to positioning.

Speaker C: There we go. Perfect.

Speaker A: Is that fair? I

Speaker B: think that's pretty fair.

Speaker A: Why do they call you Alti?

Speaker B: Why do they call me Alti? Uh, so when I, when I started in high school,

Speaker A: I have a better nickname for you but I'm not going to say it until you, you say why.

Speaker B: Oh, I thought you say it off the air.

Speaker A: No, I want to hear like where did the nickname come from?

Speaker B: Okay, so when I gone to high school there were five Alex's in my class. Five Alex's, two Alistairs, one Alec and one Ali. Right. So everyone got last name. Everyone got. I went to this sort of like fancy school in London.

Speaker A: I can't believe it.

Speaker B: That's where the accent's real though. Uh, and so everyone got called by their last name. Right?

Speaker A: Oh okay.

Speaker B: And it kind of annoyed me. It's very like teacher pupil thing in the UK. And so when I got into the workplace I just didn't want to be called by my last name. And there were obviously Alex is a pretty common name. So I was just like all right, let's just find something else that you can call me that isn't going to offend me. Like I feel like I'm being talked to by my like teacher.

Speaker A: Oh. So when you hear Altman, it sounds like the headmaster has called you down to his office a

Speaker B: little bit. I got it. Not anymore. Now I don't care. But like it kind of. So that started in like 07 and then it kind of stuck with my team and then it kind of spread out from there.

Speaker A: So you said call me Alti and then that it stuck.

Speaker B: Yeah.

Speaker A: Okay. I would call you Liquid all. That's. I like it.

Speaker B: The other one's, the other one's Control Altman. Delete.

Speaker A: Control Alt. Oh, uh, I like that too. Do you have fun on the show today?

Speaker B: I had a great time.

Speaker A: So we're going to take like a two hour recess for supper. You can go to the gym and then we're going to come back and do another two hours. Okay,

Speaker B: great. Sounds

Speaker A: good guys. Alex Altman, I want. So where do people you guys are talking to institutions? Hedge funds primarily. Um, so if they're customers of Barclays bank they could subscribe to your uh, desks research. You guys doing anything public facing or beyond?

Speaker B: We're doing this.

Speaker A: Okay. So that's good.

Speaker B: Hey,

Speaker C: sand this. Flip screen. What do you say now

Speaker A: sand this green.

Speaker C: It's green.

Speaker B: There you go.

Speaker A: All right, delete everything we just said. Let's start

Speaker B: again.

Speaker A: Uh, Alex, this has been so much fun for us. We really appreciate all the insights and we hope you'll come back sometime.

Speaker B: I'd love to. Thanks so

Speaker A: much. Are you busy tomorrow?

Speaker B: Oh yeah. Come on, let's do it. Let's make it weekly,

Speaker A: guys. Alex Altman, Shout out to Barclays and the bets team. Much appreciated. Thanks for listening. Thanks for watching. We will see mhm you soon.

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