00:00:03 Speaker 1: Bloomberg Audio Studios. 00:00:05 Speaker 2: Podcasts. Radio. News. 00:00:09 Speaker 3: Hello and welcome to another episode of the OddLots Podcast. 00:00:21 Speaker 1: I'm Tracy Alloway. 00:00:22 Speaker 2: And I'm Joe Wiesenthal. 00:00:23 Speaker 1: Joe, I heard with all the market volatility recently. 00:00:27 Speaker 2: Yeah. 00:00:28 Speaker 1: I heard a pod is blowing up. 00:00:30 Speaker 2: You heard a rumor. 00:00:31 Speaker 1: I heard a rumor. 00:00:32 Speaker 2: Is that something being said? Anyone here? Anyone hearing talk of a pod blowing up? 00:00:36 Speaker 1: Somewhere a pod is always blowing up. No, but I think actually the past week or so for a lot of hedge funds has been kind of historic. 00:00:44 Speaker 2: So I would say October, just from the numbers that we've already got in, awful. And I would say it was this drip. There's been weakness in a lot of the popular AI adjacent names really since the middle of the summer. But it's building and building. Already getting kind of ugly. And then maybe with the midterms or something, you get this huge washout. And yeah, big numbers, big losses. 00:01:06 Speaker 3: Right. 00:01:06 Speaker 1: So we're recording this on November 10th. And I say the past week because that's when we got all the headlines about October performance for a lot of these funds. But for multi-strats in particular, I mean, we've done a lot of episodes on these. These were the hot new funds. They were supposed to be able to manage money in up and down markets instead of relying on like, one star investor or one centralized team. You had all these little pods that were supposed to be making bets independent of each other, uncorrelated. Correlation, as I always say, is one of the trickiest concepts on Wall Street to actually model. And so it looks like there are some questions about the business model. Did everyone basically pile into the same trade? 00:01:49 Speaker 2: Implicitly. So this is, I think, the number one question, which is that Could you have made a lot of money in the last 12 or 24 months without implicitly being long AI? 00:02:02 Speaker 1: Was there some other- And probably leveraged on long AI. 00:02:04 Speaker 2: And leveraged long AI. But this is the question. You can dress up the AI trade in a million ways, right? So you could do it through chips. You could even theoretically create exposure to AI through rates, whatever. But at the end of the day, if you were making money over the last year up until recently- were you doing it by implicitly being long AI? And did your boss, the risk manager at your firm, understand that the way you were making money was implicitly long AI, if in fact that's what you were doing? 00:02:34 Speaker 4: Yeah. 00:02:35 Speaker 1: Basically, we're multi-strats, just momentum dressed up in, I don't know, diversified sheep's clothing. I'm just drawing that metaphor. But I think that is the question. And I'm glad to say we have two very special, perfect guests. We're going to be discussing the hedge fund performance specifically with Nishant Kumar. He is the chief correspondent for hedge funds over at Bloomberg News. And then we're going to have on Michael Ball, who's a macro strategist at Bloomberg News, to talk generally about what's going on in markets, because there's a lot right now. So why don't we go ahead and get started? Nishant, thank you so much for coming on OddLots. 00:03:07 Speaker 5: Thank you for having me. 00:03:08 Speaker 1: Why don't we start with a basic question? You've been pretty busy in recent days. I think you've written dozens of stories at this point. But how bad was October slash early November for a lot of these funds? 00:03:21 Speaker 5: Well, how busy I was in the last 16 years of covering hedge funds, I never saw a day like last week. 00:03:29 Speaker 2: Wow. 00:03:29 Speaker 5: I just took a screenshot of all my stories and posted on Twitter and it got like 750,000 views. So that tells you how busy it was. But in terms of hedge fund performance, look, it was pretty bad. The interesting bit wasn't just that hedge funds lost money. It was that lots of different strategies got hit at the same time. So coming back to your main point that how correlated some of these strategies have become. Take, for example, Millennium, Ballyasney, 0.72, Exodus Point. These are all the mainstream pot shops that you, although, you know, pots sound like an insult to many of the people in the industry, but that's what they are. And they all lost money together. So these are the hedge funds who have the biggest concentration of assets, biggest concentration of talent, the most sought after hedge funds from investors because they have a track record of making money when the downturn hits. And they all failed together and they lost money last month. Millennium was down 2.3%. Now, on its own, this may not sound like a huge loss, but in their own context, they annualize at around 14%. And when they lose 2.3% in a month, that's a lot for a steady vehicle like Millennium. Same story at Ballyasney, same story at Exodus Point, 0.72. So yeah, I would say it was really bad. Normally, you might see equities had a bad month, but macro did well. or credit go ahead or stock pickers were fine. But this was like a perfect storm. Everyone failed together. 00:05:22 Speaker 2: Wait, can you explain to me why down 2.3% is that bad? I mean, it's bad. 00:05:27 Speaker 1: Well, for a start, it was worse than the S & P 500, right? In October. 00:05:31 Speaker 2: Yeah, sure. No, yeah, I get that. But like, explain to the listener, and by the listener, I mean me, why 2.3%, which doesn't sound like the end of the world, is, wow, this is one of the craziest months you've ever experienced as a reporter. 00:05:49 Speaker 5: So as I said, that again, 2.3 in isolation is not bad. 00:05:55 Speaker 1: Yeah. 00:05:56 Speaker 5: But you have a specific purpose in a portfolio. 00:05:59 Speaker 4: Okay. 00:06:00 Speaker 5: The value of a hedge fund in a pension fund portfolio or a sovereign wealth portfolio, and we are talking about this tens of billions of dollars worth of portfolios. Your role in a portfolio is to soften the blow from any market turmoil. That's the purpose. And you are not expected to match S & P 500 returns when S & P 500 is surging. That's not what is expected from a hedge fund. But when it goes down, when there is a turmoil, investors look at you to protect you. And that's where the problem is. 00:06:38 Speaker 1: Did anyone, to be fair, it was bad for pretty much every hedge fund out there, but there was at least one I saw that produced positive returns for October, and that was, I think, Citadel. What did they do differently to others? Or what do we think they did differently? 00:06:55 Speaker 5: Well, we don't know how, but yes, there were some exceptional winners on the multistrat side. Citadel was one. 00:07:03 Speaker 1: D.U. 00:07:04 Speaker 5: Shaw was another. And there were some odd quant funds that did well. But overall, the picture is still down. Maybe some quants worked out well if someone was shorting heavily. Maybe they were positioned right for last month. But yeah, we don't have portfolio-level details to explain what went right or even what went too wrong at certain hedge funds. 00:07:31 Speaker 1: What's your working, I guess, hypothesis for why everything went wrong for the vast majority of funds? 00:07:39 Speaker 5: It was a complete mayhem last month. You had AI stocks crashing. You had a surprise election in Brazil. And you have this huge sell-off in the high bond market. And they all combined to create this perfect storm for a lot of different hedge fund industry. You had the French issues and French bonds going down as well. 00:08:04 Speaker 4: So.... 00:08:06 Speaker 5: There were so many different trades that they were crowded trades and all these hedge funds had piled into them. And one after another, they started to go down. Take, for example, just the AI stocks. We don't know about situational awareness yet, but there is another fund called Alvara. 00:08:25 Speaker 1: There was a rumor that they were piling back into the market, right? Yeah. 00:08:29 Speaker 2: Yeah, tell us about this VARA company or this VARA fund. I hadn't heard of it until someone said it was like a situational awareness clone. 00:08:37 Speaker 5: So it was, and we wrote a story that how much of a portfolio overlap there was between VARA and situational awareness. So VARA, for example, lost 33% in October. That's like losing a third of your portfolio. But here's a killer statistic. They are still up for the year. So that's how much money they had made before losing. They had a tough month earlier this year as well. So that's the kind of destruction we are seeing in AI stock. If you are crowded and largely concentrated in a few AI stocks, you take Whale Rock, again, an equity fund down 12%. So there were these highly concentrated single strategies, maybe single market funds, which lost a lot of money. But then if you look at macro hedge funds, they also lost money. Kirkus World, which has like billions and billions of dollars, and they're a macro hedge fund, they lost 6.4%. That was their biggest down month since they started trading. Chris Rokos, another legendary macro hedge fund manager, we just reported today, he lost almost 5% last month. So there was really nowhere to hide in this market. last month. 00:10:17 Speaker 2: Earlier this year, We did a live show of Odd Lots. And Torsen Slok from Apollo, we had him deliver his slides. His favorite charts of the time. 00:10:27 Speaker 1: The king of charts. 00:10:27 Speaker 2: The king of charts, Torsen Slok from Apollo. And his basic thesis is that the market has emerged... into there's the AI factor and then there's the anti-AI factor. And maybe you can't hide because everything is implicitly this trade one way or another. When you look at the results, do you come to the same conclusion that whether you're talking about a macro fund, whether you're talking about a sort of traditional long short, whether you're talking about a single manager, whether you're talking about a strategic one, that at the end of the day, if you had been making money in this market, prior to October or maybe prior to June or whatever, that you had been making money implicitly via long AI? 00:11:13 Speaker 5: Well, if that is the measure, then I don't know who is anti-AI because I don't see many winners here for the whole. 00:11:24 Speaker 2: Industry as a whole. 00:11:25 Speaker 5: There might be some exceptions, but it doesn't seem to be an equal split or even maybe it 25, 75. It looks like the entire industry has piled into this AI theme, maybe not directly through stocks, but maybe they have exposure to credit that has exposure to AI, or maybe AI has started to impact macro. started to impact interest rates. 00:11:52 Speaker 2: Yeah, I was just going to say short treasuries could be an AI trade or a long AI trade, right? Yeah. 00:11:59 Speaker 1: Well, actually, on this note, we did get a really interesting report. We do have some analysis that we can look at to get clues of what these funds were actually doing. So Pivotal Path put out this report last week saying that hedge funds were basically all crowding into the same names, which again, for multistrats at least, was exactly what you were supposed to not see. They were supposed to be diversified and making all these independent bets. Talk to us about what Pivotal Path actually found. 00:12:29 Speaker 5: So mainly they were arguing for crowded trades. That was my reading. And I will separate it from momentum and everything. You can like have 10 very sophisticated hedge funds independently deciding they like the same stock, perhaps because they're liquid or maybe the earnings are strong or Maybe it fits in their risk framework. That doesn't make them momentum traders, but it does create this problem that if they all change their mind at the same time, which seems to have what has happened maybe last month, then it's a big problem. So Pivotal Path says the 10 largest firms it studied control about $ 2. 2 trillion, including borrowed money. That is a massive amount of money. And the capital backing that trade was something like $ 300 and $ 350 billion. That gives you a sense of how much leverage is in the system. So the report itself doesn't predict stress. But if you look at another report, which is from Goldman, The broader work they have done shows that correlations between multi-strategy funds themselves have strayed roughly 0.2, 0.3 band for years. So that doesn't point to maybe too much correlation, but crowding has become a big issue and it's backed by huge amounts of leveraged. And then it's concentrated in this tiny little world or maybe not tiny after anthropic IPO. tiny world of AI stocks. So when one thing's cracked, it leads to like the flood of problems for hedge funds. And that's what happened last month. 00:14:19 Speaker 1: So just on the leverage point, when a fund's positions start to go down, and I'm particularly interested in multi-strats here, but we can talk about funds in general too. When positions start to go down, What happens next? Is it like the portfolio manager decides to start cutting risk, or the centralized risk management team says you have to cut back on risk, or you have a volatility model that says you need to trim down exposure, or in some famous cases recently, does the prime broker start asking for more collateral and so you're forced to start liquidating positions? 00:14:55 Speaker 5: Yes, so let's look at this multi-strat model. In a way, they are the real hedge fund industry right now. Everything connects to them. The way I think about Multistrat is they are like a hedge fund supermarket. Instead of one star manager making all the decisions, you have these hundreds of individual portfolio managers or what we call pods. Trading different things. So one team may be trading U.S. stocks, another macro, another trading credit commodities, and so on and so forth. And sitting above all of that is a very powerful risk management machine. At most of the, at all the hedge funds, like this is the key. The firm decides how much capital each PM gets, how much they can lose, how much leverage they can use. how much risk the whole platform wants. If a PM loses money, risk gets cut. So for example, if you have $ 100 to manage and if you lose 5% of that, so $ 5, at many of the firms, your capital will be cut into half. If you lose another 2.5%, so total loss becoming 7.5%, you are closed out. You can be liquidated and you can get fired immediately. And that's why this is a very ruthless risk management arrangement that multi-strats have. And that's what makes them wonderful in a way. This ruthlessness makes the machine work really well because they don't allow you to lose so much that you become a problem for the whole hedge fund. If the losses continue, the allocation can disappear and obviously eventually the portfolio manager. The theory here really is that lots of relatively small uncorrelated return streams are more robust than like one gigantic star portfolio manager putting on a bet. So you are avoiding the key man risk. Like a star manager can make you really, really insanely rich. But if he gets it wrong, he has the ability to also destroy your machine altogether. 00:17:17 Speaker 2: So as you said, They're very, okay, there's this AI trade, but there's various flavors of how you can express bullishness on AI. And so let's say I'm the risk manager at one of these and Tracy is sort of long chips or maybe long memory. 00:17:34 Speaker 1: I would never, go on. 00:17:37 Speaker 2: And Nishant, you're like short treasuries because you think there's gonna be a lot of CapEx and that's gonna drive inflation, et cetera. Isn't it my job to say like, yes, they're actually making the same trade. This is not diversification. And so it's like, yeah, maybe I'll fire both of you. But isn't it for having a bad month because treasuries have rallied a lot over the last few weeks. But isn't it my fault for not having identified the fact that you are not giving me diversification. You are all making the same trade in different skins. 00:18:12 Speaker 5: Well, have you seen any risk manager fire him? 00:18:15 Speaker 2: I don't know. Do you ever hear, is that a thing? But shouldn't, if I have a lot of PMs making correlated bets, isn't it my fault? 00:18:25 Speaker 5: Well, the beauty of correlation is that it's not visible all the time. It goes up and down. And in moments like last month, it really goes up. So that interconnectedness, the impact of leveraging the system, how everyone is positioned, it's a very complex mathematics, I think. And it's a complex job. Plus, you can't rule it out. If you see, you know, Mac 7 and all these tech stops going so much. And if you, as a risk manager, come in and say that, okay, let's cut it out. And if you underperform, that's a very hard decision to make. And that's where some of these multistrat, I mean, to be precise, I mean, they are great at it. They do care about correlation and they do manage it. But eventually, if everything falls together, and it's not that everything fell together. It was first, it was AI. Then you sort of kind of rebalance your portfolio that the bonds go down. Then the problem in the credit market is, than Brazil. So it happened week after week after week. So that's where I think all the problems started to emerge. 00:19:44 Speaker 1: Well, I still remember we did that episode with Krishna Kumar about multi-strats. This was one of the first episodes. we ever did about multi-strats. And his characterization of the funds was that they're not maximizing for long-term returns, they're maximizing for short-term returns. So like every macro event that happens or every move, they react to it very quickly, right? And so when you have a succession of all these idiosyncratic things happening, You could see them sort of cutting positions. I think they cut AI exposure going into the midterms, but then the market started rallying on Wednesday. And so they went back in and then it falls on like Friday. 00:20:22 Speaker 2: And Thursday was the day they got a really. 00:20:24 Speaker 4: Yeah. 00:20:24 Speaker 1: And so they're just like reacting very strongly to each new day, which I think has posed a problem, certainly in recent weeks. So on that note, what do we need to see? To know that the multistrats are like piling back into the market or that leverage limits or exposure limits are starting to go up and they're able to take on risk again. 00:20:44 Speaker 5: Well, there are many statistics in the market and banks are in the best position to see that. But this week, things have already recovered a lot, it seems. There is already mean reversion. There is buying the dip, it seems. But the problem is we are in November and 10 days are gone and a lot of these portfolios are bleeding. On top of that, talking to people, the anecdotal evidence I see is that dozens and dozens of portfolio managers, big risk takers in equity space, in macro space, in credit space, they have been fired or they have been poached by others or they are spending their long non-competes on the beach. So there are a lot of people who are not in the market and we are in November, just 40 more days left for this year. Do they have courage to get into this market and take risk and make the most out of the next one and a half months? That is the question. And at the same time, not so many people are out of this market. So, Next two months is going to be very, very, very difficult. You know, what will it take traders to take risk now? And if they are wrong, you know, already bad performance can become so worse that they will lose their job anyways. 00:22:11 Speaker 1: Joe, I just had a great idea for Odd Thoughts merch. Yeah. You know, those like religious devotional candles. Oh, yeah. 00:22:18 Speaker 2: Devoted candles. 00:22:19 Speaker 1: With like pictures of Jesus or whoever. We need to do one that's like mean reversion. You light a candle and pray to the god of mean reversion to come save you. 00:22:28 Speaker 2: That would be good. I think that would be really popular. I really like that idea. Nishan, I just have one last question. Setting aside the performance of October, and this is an industry-related question, but setting aside the performance of October, you've just been hearing a lot about sort of like how many more multi-strats or variations on a theme are really necessary for How many more launches can we have that roughly either try to replicate the Citadel model or the Millennium model or whatever it is? Where do we stand with this? Like, in your view, is this just sort of saturated, especially when you consider the cost of, say, acquiring new talent? So, again, in my imaginary world, I want to launch a new Multistrat. I'm going to have to pay up to higher season traders that know what they're doing. Like, where do we see the sort of, what inning is this industry in? 00:23:32 Speaker 5: So we have already seen the problems in the multistrat industry in terms of starting a new multistrat. We saw at Jane Global, we saw at Walleye cutting parts of their equities trading. We have seen Eisler shutting down. So that's one side of the story. But in terms of demand for these strategies? Why do we need another multi-strategy hedge fund? Or why do anyone try to launch a new multi-strategy hedge fund? Because investors really want this strategy. 00:24:06 Speaker 1: It lets you run more money, right? Like the more pods you add, the more money you get to run. 00:24:12 Speaker 5: You can, you can, but there is a limit to that. Like how many ways, if you already have like dozens and dozens of equity portfolio managers, How much an incremental or additional five more equity fund management will diversify your strategy? So I think there is a cap on that as well. So investors want it. They can't deploy enough capital to these multi-strategy hedge funds. If you look at the top players, all of them are close to new money. One example which shows you how hot these hedge funds are Millennium wanted to raise about $ 20 billion in new capital earlier this year. They got demand for more than $ 30 billion. They took in $ 22 billion. I don't think more than 2% of the hedge fund industry, or even 1% of the hedge fund industry by number, managed $ 20 billion. So that's the kind of demand that these hedge funds have. At the same time, many of these large players are returning capital. Between D, Shaw, Point72, and Citadel, almost $ 35- 40 billion have been returned to investors. Now those investors need to find a new home for this capital. Where do they put in? This is a $ 40 billion problem for investors. So capacity is a real issue. If someone can genuinely build a multistrat and create decent capacity, with reasonable returns, there is demand for another multistrat. The question whether someone can build it or not is very tough to answer. We have seen many failed attempts. And that is the problem. Whether a new hedge fund, multistrategy hedge fund, has the right and resources to sort of employ another or poach another trader and hire the best people, that is the big question. I don't think they can. 00:26:16 Speaker 1: Yeah, I think the obvious takeaway from this is that more teams, more pods, more money does not necessarily translate into more adjusted returns, basically. All right, Nishant, thank you so much for coming on All Thoughts. Really appreciate it. We'll let you get back to reporting because there's probably eight stories that you need to write today. 00:26:35 Speaker 4: Thank you. All right. 00:26:52 Speaker 2: Well, that was our conversation, Nishant Kumar. And now let's talk a little bit more about the markets. We have here Michael Ball, macro strategist at Bloomberg News. He's going to explain to us all these big moves. Michael, thanks for coming on the pod. First time, I think, right? 00:27:06 Speaker 4: First time. Thanks for having me. Big honor. 00:27:08 Speaker 2: I don't even know where to start. Crazy markets. But you told me that the first 30 minutes of trading last Thursday, right? So two days after the election was like, the biggest puke for retail investors since COVID? 00:27:25 Speaker 4: Well, it was the biggest selling of single stock. So again, that is going to be mostly retail from the way we viewed it, because we know there's been a decent amount of de-grossing, de-netting from the hedge fund community. But look, everyone was involved. So I guess guys that were still holding on one way or another, whether they're retail or they're institutional to some of these single stock names, specifically in growth and tech, really just kind of, without really a major macro catalyst, dumped at that open Thursday. And it was a sucker punch because Wednesday, you saw people rebuilding positions. You saw vol falling. And it really made it really kind of even more curious to why all of a sudden Thursday morning this happened. 00:27:59 Speaker 5: Yeah. 00:27:59 Speaker 1: So this is the big question, right? So people expected a strong fall. turnout for the Dems in the midterm elections. 00:28:06 Speaker 5: Right. 00:28:07 Speaker 1: I don't think a lot of people expected necessarily the blue tsunami, but it was leaning Dem for sure. And then on Wednesday, the market reaction was pretty muted. We saw, you know, stocks actually go up. And then Thursday, everyone seemed to just like wake up and decide that was entirely wrong. What happened? What were people thinking? 00:28:26 Speaker 4: Wednesday was interesting too because the hyperscalers got a bid because the thought was that more regulation from this blue wave, and we saw all these things on the ballot for the AI initiatives, would force basically them to pull back on CapEx. It would be better free cash flow, and hence their core businesses would do better. And here we go. The thing that had been driving their earnings growth was now a negative, and the things that were kind of more tangential were just on the side. So it was a super interesting setup Wednesday into Thursday. And again, Thursday, we didn't have a necessary catalyst. We had our standard micro stories with some AI headwinds. Semis and sort of AI trade on Wednesday had been weak. They had been underperforming. The rotation was back in. We saw equal weight outperforming. We saw value doing well. But then lo and behold, Thursday happened. And what happened was once we started breaking levels on the SPX, and this is the NASDAQ was already sort of in correction territory. We'd already had a big negative gamma backdrop, something I can talk about more, which was basically people were positioned defensively. But SPX was still hanging in there and we were above this sort of 7,700 level, 7,600 level, a range we'd been in for several months. This rotation that had occurred over the last few months had buffered the weakness we'd seen sort of in the AI trade in October. And subsequently that all sort of fell apart as levels broke and feeding became self-feeding, actually started, the weakness became self-feeding. 00:29:38 Speaker 1: This is where the sort of like automatic mechanics of markets come into play. So the idea that like dealers have to cut positions just because they're breaking key levels, just because they need to maintain like a certain volatility weight and things like that. 00:29:51 Speaker 4: So maybe just as a quick background, we already knew in the summer we had a massive loss of momentum from the AI trade. August, we saw a rebuild in that. So what happened here is that basically Legacy Eye calls some of these auto callables, some of these exotic products that you guys have actually talked about. 00:30:06 Speaker 2: Which we've talked about on the podcast. 00:30:07 Speaker 1: This is why we've been talking. You know, people keep asking us, like, why are you doing episodes on structured products? It's because it, like, impacts the entire market. 00:30:14 Speaker 4: Yeah. So there was, like, a clearing event basically in July. And August was a rebuild. And what all this meant was that RealizeVol got sort of suppressed because the way volatility works is it's supply and demand as well. Obviously, you want to think about buying and selling, driving it. But it's a little more complicated because on the other side, there's a backdrop in option markets, which supplies basically delta and gamma into the market, which is a fancy way of saying vol suppression or vol acceleration. So when people talk about gamma, what they often mean is where the dealers are holding option positioning. Are they long or short options? And effectively, if they're long options, they suppress volatility. And if they're short options, they accelerate the move. So I want to buy a put. I want downside protection. The dealer is short that put. So that Delta hedge that as the market goes down, they are selling into the market, which exacerbates that move, which is exactly what happened Thursday. On top of all these other kind of, you know, cross currents, we had obviously some hedge fund news that they were blowing up. People were getting taps on the shoulder. We had sort of leveraged ETFs accelerating that because that's a big market and that has to exacerbate the move as well. That's a negative convexity product. And then all of a sudden the vol control community and some of these systematic guys who are always the boogeyman that get blamed, but were actually quite active on Thursday. had to jump in because if volatility picks up, they have to de-gross. And even with sort of the CTAs being more neutral, that's another kind of buzzword that's often thrown around when we see these big market moves. So they chase trends. They too, although they were somewhat less long, were also very active in selling. And that was a perfect storm Thursday that got us basically to break all the ranges we'd been in for months and test new lows. 00:31:42 Speaker 1: To my shame, Joe, we have never actually done a CTA episode. We've done levered ETFs. We've done vol funds. We've done structured products, all of that stuff. But we should do a CTA episode. 00:31:51 Speaker 4: We should do a CTA. 00:31:52 Speaker 2: The other thing is- Something about CTAs feels very like 2010s. I know. 00:31:56 Speaker 1: Well, yeah, people used to talk a lot about them in like the mid 2010s. 00:32:00 Speaker 2: Yeah, I feel like they're a little less. 00:32:02 Speaker 1: But now we can talk about them again. 00:32:03 Speaker 4: They're kind of like the boogeyman. Like you always hear them on these volatile days. Like, oh, it's the CTAs again. 00:32:07 Speaker 2: Ruining the day. 00:32:08 Speaker 1: CTAs stands for Commodity Trading Advisory. 00:32:11 Speaker 2: But they're basically hedge fund or systematic ways of trading futures. 00:32:16 Speaker 4: Active in most future markets. 00:32:18 Speaker 1: People always blame them for gold moves as well. That's the funniest. 00:32:21 Speaker 2: Okay, so we get this huge sell off on the Thursday after the election. 00:32:24 Speaker 1: Mm-hmm. 00:32:26 Speaker 2: I'm curious if it's like, yeah, you can kind of maybe tie it to the election. But so like two weeks ago or a week and a half ago, we were talking to Alexander Altman over at Barclays. And one of the questions was like, we were already nervous. And it was like, well, why hadn't VIX, why had the VIX been so low, et cetera? But there were like jitters long before Tuesday, building and building and building. So talk to us, like, let's set aside the election and all that. What was this like sort of like building anxiety, I guess, starting in the middle of the summer and sort of accelerating into October all about? 00:33:00 Speaker 1: Yeah. 00:33:00 Speaker 4: So I guess October really saw that shift in the CapEx narrative where all of a sudden it wasn't a growth engine anymore. And it was about financing, about free cash flow. And again, about this nimbyism and electricity problems, right? The actual execution of the CapEx. And we saw that in yields, right? Because all of a sudden we saw kind of a reversal on how yields were going with oil. Oil was still creeping up because we weren't obviously getting anywhere with Iran. But all of a sudden, we had growth concerns because AI CapEx next year was going to crater. And then we were going to basically have no growth because that's been the primary driver as the narrative goes. And we saw sort of the 10-year and the curve flatten and basically everyone get more worried about growth. What ended up happening is like the NASDAQ became much more negative. People were buying production on it, not just in single stock names and AI, but now as an index hedge. 00:33:44 Speaker 2: But just to be clear, was there like the whiplash from talking about chip shortage to chip glut? felt like it happened overnight. And I'm sort of curious, like gamma and all that stuff aside, was there some reason that you could put, was there some earnings call? Was there some event where it's like, Suddenly investors started flipping their perspective on the compute capacity question. 00:34:08 Speaker 4: You guys have been doing this as long as me. You know how narratives can spinely like enough needles on the camel's back. I don't really have one in mind to your point. I think the supply and the credit markets finally caught up to everything. The supply of actually equity paper, whether it was from Anthropic or from all these secondary issuances. 00:34:23 Speaker 1: To me, the moment that sticks out in my mind is the CoreWeave guy's interview in the FT where he basically talked about raising all the capital in the world. 00:34:31 Speaker 4: Yeah. 00:34:32 Speaker 1: You hear that from a senior executive at one of the most like prominent neoclouds out there. That to me is like the big flashing warning sign. 00:34:40 Speaker 4: Elon said something to his SpaceX, maybe like $ 3 to $ 13 trillion ultimately of capital raises. So it became this sort of bifurcated story where everyone was comfortable going into healthcare, into quality, into sort of even staples and then basically hiding out in there, which was holding up the index while just selling and degrossing in sort of tech. 00:34:58 Speaker 2: Elon had a tweet about like- Just one, just one tweet. Just one tweet. It was something about like questions about hyper, or sorry, about NeoCloud. And I'm curious whether it's like, is his view like create some FUD around non-megascale players and their ability to deliver? 00:35:17 Speaker 4: I mean, I don't know. I think, I don't want to like sidetrack, but I think one of the bigger stories was also the micro compute story where people would have it at their desktop level. So you wouldn't need the hyperscalers and the data centers because that, But I don't, yeah, I don't know about the answer. 00:35:34 Speaker 2: Nothing changed on that. 00:35:35 Speaker 1: Yeah. 00:35:35 Speaker 4: I don't really know what to your point. Like there's, there was a multitudes of headwinds all at once. And then again, the credit markets were basically saying enough. 00:35:43 Speaker 1: Well, actually on this note, again, we're recording November 10th. Should I say the time? Is it one of those days. 00:35:49 Speaker 4: Where it's 10 o'clock? 00:35:50 Speaker 2: No, it's actually, the market's kind of mild today. 00:35:52 Speaker 4: All right. 00:35:52 Speaker 1: We just had the CPI data out, and we also had Waller doing a lot of forward guidance, much to Warsh's chagrin, I guess, in talking about maybe even a 50 basis point rate hike in December. If you look at the neoclouds right now, these are companies that are borrowing a lot of money and are sort of like getting very leveraged. 00:36:13 Speaker 5: Surely. 00:36:14 Speaker 1: a lot of the stocks are up this morning, surely rate hikes, higher interest rates would be bad for that business model. 00:36:19 Speaker 4: Yeah, I heard you. I wrote about them yesterday because IRIN came out last week and said basically the prepayments from customers was quite good. So the free cash flow is looking better for that particular name. 00:36:29 Speaker 2: Interesting, yeah. 00:36:29 Speaker 4: And their borrowing needs may need to go down. Thankfully, everyone's waiting for CoreWeave, which has a little bit of a different leverage profile and a little more in the hole there. And then I guess we get Nebius too, which is more like IRIN. So- There seems to be also like a little bit of maybe differentiation now, even in that neoclass kind of sub world, because if people are prepaying quicker, then obviously it's not as much borrowing. We know, you know, that's that simple. Let's see what CoreWeave does. Also, again, they're massively oversold. That index is down 70%. These are all sitting very negative positioning as well. And that positioning is very expensive to hold if volatility collapses or if the skew starts to change against you. So basically, if you didn't get out now and you're waiting for the next catalyst, maybe that's CoreWeave after the bell. But you just need constant negative news for this sort of negative gamma dynamic to hold or you get bled out effectively out of the option positions. The premium is just decay. 00:37:19 Speaker 2: Wait, Corweave is reporting today? 00:37:21 Speaker 4: Yeah, after the bell. 00:37:21 Speaker 2: Okay. So by the time listeners hear it, it'll be out. 00:37:24 Speaker 1: I'm glad we did say that. 00:37:25 Speaker 4: I mean, I think that's a bigger risk event in some ways than CPI. Obviously, Waller coming out, upping the odds into the CPI was kind of not helpful. And you're seeing the two-year kind of sell off pretty notably and react to that. But overall, I think the AI story really needs to stabilize. And we may not get that until we get through some of this regulatory nimbyism worries. And that may take many months. But the actual position needs to stabilize. We need to see some rebuilding there because, quite frankly, everyone's almost flat to short. And there's a lot of room now for kind of new guys to step in. 00:37:53 Speaker 2: Iron actually literally November 2025 is a $ 77 stock. Today it's a $ 21 stock. Wow. But this is one of the ones that was like a Bitcoin miner. We have some access to the electricity grid. Maybe there's something more valuable we could be doing. 00:38:07 Speaker 1: People were into it like six months ago. 00:38:08 Speaker 2: Maybe there's something we could be doing with it that's different. 00:38:11 Speaker 4: The numbers were impressive. I'm digging as much as I can into the actual earnings calls of not only sort of the hyperscalers, but the neoclouds and also the pick and shovel guys at the industrial level. Everyone's backlog is pretty impressive. Iron's compute demand was very impressive, the growth there. Sure. Obviously, lots of leverage, lots of headwinds there and very rate sensitive in a lot of ways. But overall, like I still feel like the story was overdone when you see these 70% drawdowns. Now I don't, you know, I'm like ball, the macro strategy at Bloomberg. So other heads can weigh in, but it does seem like there's been a notable drawdown and now the position is cleaned up. 00:38:42 Speaker 2: There are questions with some of these new clouds. There are lots of questions, but also about like tenant quality. 00:38:48 Speaker 4: Right. 00:38:49 Speaker 2: So like I could be a customer of iron and I'm like, yeah, I'm going to, I'm going to spend with you over this, but like, That's not guaranteed, right? Like the quality, I'm not saying any, I don't know like who their clients are, but these are all concerns that start to creep in about like how good are your, I mean, I do think of them as real estate. How good are your tenants? 00:39:11 Speaker 4: A hundred percent. I think that's why the question now isn't necessarily 27, which looks more secure for a lot of these guys, as far as the backlogs, the prepayments and the sort of confidence we have in the earnings, it's 28. Like the whole story on 28 after the blue wave changed because projects in kind of under already being done aren't really at risk of being canceled in Texas. Now we got to hear from Ohio and Georgia. Obviously we have New Mexico, Arizona. There's many states that will have many varying things, but like the worry isn't necessarily the things that are already on the ground being worked on. The worry is new projects. And that means 28 earnings. And that obviously affects the neoclouds in that sense, because how much does then their costs equate to compute costs? 00:39:46 Speaker 1: Well, also on the compute tenants, like just going back to the conversation we had with Nishant about multi-strategy hedge funds, diversification would seem to be an issue too, right? If all of your tenants are in one way or another exposed to AI, which I'm guessing they probably are, right? 00:40:02 Speaker 4: Yeah, well, I ran and got hit because Microsoft. Microsoft wanted them to upgrade their chips apparently, which was a setback for a project because now the chips are moving faster than the projects can get done. Yeah. So there's a lot of, like, again, you guys have been covering this well, super complicated and very hard to get one narrative story, but it's all operational risk now. 00:40:20 Speaker 2: Just curious, were you a little bit surprised that, and we're going to record an episode on this ASAP, but the Jensen scandal did not have ripples outside of NVIDIA? I mean, there's two, there's actually three pertinent things. NVIDIA was not down that much. NVIDIA had been down, it's having a bad year. It's way off its highs like many of these other names. The news is not totally new. Bloomberg, a lot of this was basically out there. It all just sort of became top of mind at once. But are you a little surprised at this point that here's the crown jewel of the AI infrastructure story and we really don't know much about How it's going to be managed in a few months from now? 00:41:01 Speaker 4: I go back and forth on this. And this has been obviously the debate we've all been having for 24 hours now or since it broke this weekend. And literally, I think the AI trade now has become bigger than the Anthropix and NVIDIA. And I get that NVIDIA is seen as central for the financing. But I also push back that that's going to change if the CEO changes. Maybe the growth trajectory as far as the advancements of new chips and where they take kind of M & A and like how they expand in that sense will change if Jensen leaves. But overall, as the cornerstone, I'm not yet seeing anything that would make me think that's shaky. And again, yesterday was really the pain trade of everyone getting squeezed out of shorts and covering puts. So like the fact that everything else went up in the semis and sort of AI picking was more mechanical again. That's sort of what the main point should be. The last sort of three or four days since Wednesday literally have been just mechanical versus sort of AI narrative shifting a lot in my opinion. That's just my opinion. 00:41:49 Speaker 1: I guess we should talk about the Anthropic IPO as well, which is the other, I guess, event risk that's sort of coming up on the horizon. So they released, I guess, their preliminary valuation, $ 1. 4 trillion that they're aiming for, which is down from what a lot of people were expecting just even a few weeks ago. 00:42:06 Speaker 4: Two, yeah. Yeah. 00:42:07 Speaker 1: When you have all this new equity supply, I guess, coming into the market, would you expect to see that have an impact on other AI stocks? 00:42:14 Speaker 4: Yeah, I think so. And I think obviously people have to sort of rebalance. I think, too, there's two broader things. One, this year has been one of the first years where actual broader equity supply is no longer shrinking. Buybacks, as we know, were primarily being driven by hyperscovers, which free cash flow now has shrunk enough that that buyback pulse, at least for 27, is totally under question. And it's come off this year. And when you take employee compensation, it's even less. You know, we had three years there since basically 24 where equity supply was actually shrinking. So that was very good as you still had massive passive flow. coming from even outside the corporate buybacks. Now, to your point, like, yeah, it's going to crowd out. But with that said, like, it's $ 80 billion. It looks like that's kind of the number they're throwing around. I mean, SpaceX was absorbed well, and I'd say that was a more risky proposition in some ways, although we can debate that as well, and probably a higher valuation. 00:43:02 Speaker 1: We don't need to debate that. 00:43:03 Speaker 3: Yeah. 00:43:04 Speaker 4: But I guess, look, these are big numbers in theory, but the market's pretty big and it can absorb this as long as the story behind it is compelling, which I think it is. And the valuations have come off now. Like if it was at $ 2 trillion, I probably would be more worried. So almost like let's get through the risk event and then let's move on to the next part of the story. And that's kind of where I'm at as far as clearing event. 00:43:22 Speaker 2: Can we talk about the hyperscalers themselves? I was thinking about this. Like if I think of a company like Alphabet. And meta, these are the two examples. I feel like I could bucket them into three distinct businesses. And here's what, tell me if this is crazy. There is a legacy business that prints money. Let's just say we're talking about Alphabet. There's a legacy business that prints money, and that is Search. And it is still a huge moneymaker. There is a capital intensive business, but is also quite profitable in unit economics, and that is building clouds, either for themselves or for others. And then there is maybe like a call option, which is, will Gemini itself become a really valuable AI model in itself, the way other models, or is it just going to be sort of in the pack? I'm curious how the street thinks of the hyperscalers right now, because it feels like There are a few different economics embedded within each one. 00:44:22 Speaker 4: I think it's a great question. I think also, for your example, you can say, are the TPUs going to meaningfully. 00:44:26 Speaker 2: Yeah, and that could also be sort of a call option. Especially, like, With Nvidia, it's like maybe, yeah. 00:44:32 Speaker 4: That certainly prices the multiples you want to assign in the different business segments. I think the interesting thing was the hyperscalers didn't do very well because the traditional businesses struggle. And I think they struggle for reasons outside. Like Amazon had some issues. Microsoft had some issues. Google had some issues. Actually, Microsoft did quite well, to be clear. But Google had some issues with search, which makes perfect sense because search weakness... I'm using Claude more than I'm using Google probably to the detriment of token usage. And I shouldn't be, but we're all learning how to kind of adjust to this new tech. And that's probably going to be a little bit of a jitters for traditional businesses like search. So it does make sense, but I think the cloud business and the growth and the monetization of the cloud business is the cornerstone getting back to kind of your question of everything of the story. 00:45:10 Speaker 2: For investors, the number one question. 00:45:12 Speaker 4: Compute Pi has to keep growing and it's actually growing quite impressively still. And that's why we all get kind of lost in the narratives like token prices. or financing, or even competition and nimbyism. But as long as compute's growing, they can probably power their way through this. And that's what we're hearing. And when I look to some of the experts on the street, like the Gavin Bakers and these guys who put out quite a lot, it's really about watching that metric. And so far, there really isn't any flinch. We're still in a decent part of the S-curve there. 00:45:38 Speaker 1: Okay, I feel compelled to ask this, even though I don't know. 00:45:41 Speaker 2: If- We've been talking about AI the whole time. 00:45:42 Speaker 1: I know, like it feels like this isn't really in the zeitgeist of the market anymore, but it is at the same time driving a lot of market moves. So I don't know how to square that, but oil, right? So we've seen oil. Some of the pressure come off recently. People are speculating that maybe we're going to see an end to the Iran conflict. How much of a factor is oil at the moment? 00:46:01 Speaker 4: Yeah, it's big. And I mean, it's decoupled from rates again, which was nice. I mean, yesterday was interesting. That's Monday. effectively equities were ripping, yields were sort of rising because all of a sudden the growth picture was getting better and that traditional kind of balance between rates and equity had kind of resumed, but oil had fallen massively. And usually oil would drag down sort of yields and treasuries and we didn't get that. So people were again, re-changing sort of the calibration correlations across asset. But as far as oil, like the backdrop's actually positive if we can sort of end this kind of overhang of geopolitical risk premium. Barrels are getting out. I think JP Morgan upped their surplus for even this year to 1.5 million barrels. And the product market's actually loose and nice. So crack spreads and all that have come off. And even in Europe, like the Dutch gas market has come off nicely and that's helped European stocks. So the energy pulse, as we just saw in CPI today, had been materially starting to come into core, changing our Fed calculations. So anything now with oil falling down, and I don't know where the range is because there'll be a higher premium and there's still a lot of inventory to be rebuilt. And there's still obviously a lot of things lurking with not only the Gulf, but Ukraine and Russia, which could change some of that. But the price will be higher, but it looks like now the skew is funny enough lower, although it'll be a bumpy path because again, now we're a little bit oversold. We just moved about $ 10, $ 15 in a short amount of period. Our size are oversold. Option position, funny enough, yesterday picked up. People were buying calls again. You could see $ 100. Dollar Brent being kind of a point where people thought we'd get back to. 00:47:23 Speaker 2: I hadn't realized how much cracks had come down. 00:47:25 Speaker 1: Yeah. 00:47:25 Speaker 2: They were at 70 in October. 00:47:26 Speaker 1: It's pretty surprising, actually. 00:47:28 Speaker 4: Yeah, the price of the pump, as we all know, is lagging that, but it should follow it fully. 00:47:33 Speaker 2: I don't think it would have saved the Republicans this time around. 00:47:36 Speaker 4: He promised oil would fall after the election. 00:47:38 Speaker 1: You think they should have campaigned on lower crack spreads? 00:47:42 Speaker 2: Trust me. The crack spreads are coming down. We promise it will trickle through to the pump, too. Michael Ball. 00:47:49 Speaker 4: Thanks for coming on Outlaws. 00:47:50 Speaker 2: Thanks so much, Michael. 00:47:52 Speaker 1: Thank you. Well, Joe, I thought that was a really good overview of what's been going on. To me, last week was sort of the mechanics of markets on full display. Again, the reason we've been doing so many episodes on things like structured products, multi-strats, levered ETFs is because you do have them, it seems, adding to volatility or adding to the selling pressure when we start to get a down market, which I think is what we saw last week. And again, When it comes to multistrats, I think this puts a pretty big question mark around a lot of the business model and the defining feature of multistrats, which is the focus on short-term returns. And so, again, when you have an environment where things are flipping basically on a daily basis and they're trying to chase those trends, it feels like, or react to them, it, again, adds to the force of the selling or the buying. 00:48:55 Speaker 2: Yeah. 00:48:56 Speaker 1: Yeah. 00:48:56 Speaker 2: Completely agree. And yes, listeners, listen to our technical episodes. 00:49:00 Speaker 1: Sorry, am I being too ham-fisted in promoting previous coverage? 00:49:03 Speaker 2: No, no, not at all. I think that's right. And I think what Nishant said about like, okay, why is a down 2.3 month. 00:49:10 Speaker 4: Bad, right? 00:49:11 Speaker 2: All right, no one likes to lose 2% of their money, period. Every hedge fund will have down months like in down quarters. That's everyone has always had it. But if you think about like an institution, start from the level of the endowment or the pension or whatever, if you have a lot, you're inherently long risk assets. You have to be. 00:49:32 Speaker 1: You're paying for the hedge. 00:49:33 Speaker 2: It's in the name. You're inherently long risk assets. Most of your money isn't going to be things going up over time. So then when you have an allocation of the hedge and it doesn't serve as a hedge in a terrible month or in a really brutal month, you can see why a bunch of people get their hair on fire and get fired and stuff like that. It's not the losing money per se. It's not even the losing money. Besides, it's the fact that it did not serve its purpose. in that particular month from the perspective of the broader portfolio. 00:50:06 Speaker 1: They paid for the hedge. They didn't get the hedge, right? It's that simple. But actually, that reminds me, I want to know what Citadel did in October. 00:50:14 Speaker 2: Yeah, I do too. 00:50:15 Speaker 1: To eke out a positive return. So open invitation to Citadel if they want to come on the show and I guess, you know, lord it up over everyone else. 00:50:22 Speaker 2: Tell us every one of your positions. Tell us all of the skews of all of your... That's right. Tell us all of your Q-sips and all your equity holdings. 00:50:28 Speaker 1: Hey, that was October. It's November now. 00:50:30 Speaker 2: Yeah, just tell us. 00:50:31 Speaker 4: Why not? 00:50:32 Speaker 1: Shall we leave it there? 00:50:32 Speaker 2: Let's leave it there. 00:50:33 Speaker 1: This has been another episode of the All Thoughts Podcast. I'm Traci Allaway. You can follow me at Traci Allaway. 00:50:39 Speaker 2: And I'm Jill Wiesenthal. You can follow me at The Stalwart. Follow our producers, Carmen Rodriguez at Carmen Armand, Dashiell Bennett at Dashbot, Cale Brooks at Cale Brooks, and Kevin Lozano at Kevin Lloyd Lozano. And of course, you can chat about all these topics 24-7 in our Discord, discord.gg slash oddlots. And for more Oddlots content, check out our daily newsletter, which you can find at bloomberg.com slash oddlots. 00:51:02 Speaker 1: And if you enjoyed this conversation, if you like it when we do these market checkups, then please leave us a positive review on your favorite podcast platform. And if you're watching on video, then please like or leave a comment, or better yet, subscribe. 00:51:15 Speaker 2: And remember, if you're a Bloomberg subscriber, you can listen to all of our episodes absolutely ad-free. All you need to do is find the Bloomberg channel on Apple Podcasts and follow the instructions there. 00:51:25 Speaker 1: Thanks for joining. 00:51:26 Speaker 3: Thank you. 00:51:43 Speaker 2: Thank you.