00:00:02
Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.

00:00:18
Speaker 2: Hello and welcome to another episode of the AULTS podcast. I'm Tracy Allaway and I'm Joe.

00:00:22
Speaker 3: Why isn't thal Joe?

00:00:24
Speaker 2: When I think about the big market events this week? This week ninth, July ninth, macro doesn't feel like it matters that much anymore. So. We had renewed hostilities between Iran and the US markets at least as of Thursday morning, don't seem to care too much. You know, we've had some fed minutes. They don't really change things that much. The big stories this week, unusually for the US market, have all stemmed from Korea.

00:00:54
Speaker 3: Yeah, no, it's true. I mean, look, the Chips trade, which then becomes the Korea trade and all of these things is like the big thing in the entire world. And I agree, I do not think people are going to focus on much of this other stuff as long as this thing is so crazy. And you know, the Korean market, like we've just come to get used to this major, you know, pretty big market in the grand scheme of thing five percent a day, and we've suddenly all become sort of normalized to it. Yeah, this is the big thing.

00:01:27
Speaker 2: Yeah, So the two big Korea events this week. We had Samsung earnings already and then today, which means we're recording this podcast either at the best or the worst time, because we don't know how things are going to shake out. But we have a US listing from sk Heinex. And the reason Korean stocks are so interesting right now is it's not just that the US market is kind of like playing off with them as well, but it's because you have all these new products in the Korean market, all these things called single stock levered ETFs, which seem to be having an impact on the overall movement of the underlying shares.

00:02:03
Speaker 3: It's so funny to me. You look at again the performance of some of these chip companies, some of them up.

00:02:10
Speaker 2: Like ten is not enough we need exactly you know what, I.

00:02:14
Speaker 3: Look at this chart.

00:02:15
Speaker 4: You know what.

00:02:15
Speaker 3: The one thing I'm missing is some leverage here. This is always also funny to me when people were like trading crypto on leverage, just like what you're not getting enough you need like twenty exit but people love it and so yeah.

00:02:26
Speaker 2: But even here's the thing, even if you personally don't love leverage, leverage has an impact on you totally if you're in that market.

00:02:33
Speaker 3: You may not be interested in leverage, but leverage is interested in you exactly. One of those guys said, all.

00:02:39
Speaker 2: Right, so we should talk about all these products. You know, I can't resist a product tail wagging underlying share price dogs. So we really do have the perfect guest. We're going to be speaking with Alex Altman aka alt. He is, of course, the global head of Equities Tactical Strategies over at Barkley's so Alty Alex, so much for coming on.

00:03:00
Speaker 4: Thank you very much for having me.

00:03:02
Speaker 2: So I believe in one note I read from you, and the reason I wanted to get you on is you specifically use the word terrifying to describe the amount of notional exposure coming from levered ETFs. Can you give us a little bit of context about how big this market actually is now?

00:03:20
Speaker 4: I think that the look. I'll give you the numbers straight away, and as you highlighted, markets are moving really quickly, so these numbers change a lot every day. And I think at the time when we wrote about that, it was the local highs of the AUM and it was globally around about two hundred and fifty two hundred and seventy billion dollars. The number itself is actually not enormously terrifying at all. I would just say the the asymptotic growth of the AUM over the past few months has been somewhat sensational or just it's just meteoric. So just to put some numbers behind that, Yeah, if we look at say the Carean market, which you guys highlighted, at the beginning of the year, apac AUM so Asia Pacific AUM was somewhere around about twelve or thirteen billion, that's now around about fifty.

00:04:10
Speaker 3: Sorry, just sorry. And within these loverty.

00:04:13
Speaker 4: Livery products in Asia there they are now around about fifty to fifty five billion dollars, so talking about a threefold increase or plus over a relatively short period of time. And here in the US, if you take the beginning of April, beginning of April, which was of course the local lows for the market, we were talking around about one hundred and twenty odd billion here in the US, and that's now increased. I think at its peak it was just north of two hundred billion. So these numbers can move extremely quickly. And what's really interesting is that if you look at the US market it's not like you've actually seen significant inflows and share creation in that space. Most of it, of that AUM growth has been because of price performance. Oh interesting, whereas in Korea you've actually seen the opposite, not the opposite, but you've seen huge share creation on top of meteoric rises in the share prices.

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Speaker 3: Well that's super interesting.

00:05:07
Speaker 2: But just to be clear, for the Korean products, as the underlying share price goes up, the AUM also tends to go up, right, So that and then when the underlying goes down, it collapses. And so that's why you get these big spikes in AUM.

00:05:21
Speaker 4: Yes, so I think it's worth just like expanding all the mechanics of it just for a second. So I think that's really important to debunk and why they've become such a relevant product in the market. So if you just take we just actually put some numbers behind this. Let's say you had one underlier whatever it was, and it was an AUM of call it thirty billion dollars, just to make the numbers simple, and let's say it was triple levered. So now they're going to basically go out and get a load of exposure for another sixty billion dollars. That exposure is typically done through swap agreements, right, so they can actually sort of have the synthetic exposure through prime brokerages and so on and so forth. And so now you've got ninety billion dollars exposure. Now, let's say the stock goes down ten percent, so ninety billion dollars ten percent drop, so that's going to be nine billion dollar drop. So you're down to an eighty one billion dollar of exposure now, but you've lost nine billion dollars of your AUM, which was only member thirty billion, So the thirty goes down to twenty one. And then if you multiply that back by three to maintain your triple level exposure, you're going to be at sixty three, but you've got eighty one. So you need to reduce down your exposure mechanically by over ten billion dollars in order to sort of maintain what you've kind of put in your prospectors as of you know, your your triple leverage against that underlier. And that's what's creating these mechanical adjustments on a daily basis, whether it's down obviously on down days and then up on updates, so effectively you're creating a new short gamma dimension in the market that was relatively small only a couple of years ago. And I think really importantly is that there's a lot of dynamics that are moving non discretionary flows in the market. So obviously in the ETF world, you've got a lot of overwriting ETFs that are doing the opposite. They're effectively selling volunt in the market, which is creating a long gamma process and that would typically have netted off against a lot of these levit ETFs. But because these levit ETFs have become so large and they're rebalancing that now net gamma profile is effectively becoming more.

00:07:29
Speaker 2: Negative a bigger role in the market.

00:07:32
Speaker 4: Yes, exactly.

00:07:33
Speaker 3: Can you actually just maybe take a step backward? Can you just walk us through the basic I don't know if it's like the business or the simple mechanics of setting up a LEVERTYTF. So I have a company, I want to Okay, I'm an upstart ETF provider.

00:07:50
Speaker 2: I want now do the odd lots three times, Yeah.

00:07:52
Speaker 3: The odd oddlarge three times micron ETF whatever it is. So it's like, who'sing the leverage? Just talk to us about how this product, you know, it was originally conceived them, setting aside market impact and all that stuff for now, sure, how the product works.

00:08:08
Speaker 4: The product, I mean, the product is very straightforward. It's really no different to any other fund provider in the ETF space. So effectively, if you're creating an ETF and you typically go and get some kind of anchor investor or some kind of co sponsor who's effectively going to create the initial amount of AUM for you. And then obviously because you need critical mass. Yeah, there are as I'm sure you guys have talked about, there's more ETFs in the world than there are single securities here in the US. So creating the ETF and the fund is not complicated. It all obviously has to go through SEC regulation, and I think that's an important point to highlight when it comes to all of these levit ETFs is whatever your opinion on them may be, the fact is is that the SEC, the regulator, has approved all of these. So in the same way, these funds will then get approved. And from there, of course, the question is where do you get the leverage? So typically the leverage will come from a banking partner, so through a prime channel that they will effectively seek to get that exposure synthetically through the bank, and that in turn obviously will effectively create the balance of their notional exposure. Now from a bank's perspective, that goes through the prime balance. And the interesting thing about that is is that some of market participants have been talking about an increase in financing rates that has been driven by these levitytfs. I think we need to debunk that for a hot second, because I know I've a little bit off topic, but it is still very much from me. Now.

00:09:38
Speaker 3: I actually had a request recently someone wanted us to talk about equity finance and cars, So I'm glad.

00:09:44
Speaker 4: You brought that up. So it is perhaps a contributor. You have to acknowledge the fact that if you've got north of two hundred billion dollars of AUM that has materialized in relatively short order or grown exponentially recently, and you're obviously putting over two times leverage on that, you're creating an additional four hundred billion plus of stuff that's been brought and put on balance sheets in swap format. It's going to create a degree of tightness within bank balance sheets. That's not in isolation true. The fact of the matter is is that bank balance sheets have become tighter because my primary reason is markets have gone up, and as market's gone up, the price of stuff has gone up, and so that has been without a doubt, the biggest reason for financing rates rocketing is the fact that spot levels are higher. This has been a contributing factor. But we shouldn't overlook the fact that if you just look at the biggest driver of AUM growth within the hedge fund community, it's the multi manager platform we're talking about. Those guys are effectively are trillion dollars of AUM. Now that's potentially tripled since COVID, and obviously those guys have deployed a huge amount of risk on a long and a short side. So again that's using balance sheet as well. So it's not really so much just the levity ETFs that are going out and asking the banks for balance sheet that's causing financing rates to squeeze higher. It's a it's one of many.

00:11:06
Speaker 3: But balance capacity is scarce.

00:11:07
Speaker 4: Balance sheet's capacity is scarce, and it will remain scarce so long as SMP trading at seventy five seventy six hundred year.

00:11:15
Speaker 2: Well, just on a related note, okay, balance sheet is scarce from the dealers, and it is true that like if a lever in ETF comes to you and says I have two times leverage and now I need like forty billion dollars worth of exposure, You're not going to want to extend like that much credit to a single counterparty if you're a dealer. And so one of the things I've heard in the market is that maybe some of the levered ETF start going out and sourcing leverage not just through swaps with dealers, but through the options market.

00:11:43
Speaker 4: Have you heard this so that that was documented I believe in the press as well, and I believe that that was specific to one particular fund out in Asia rather than specifically anything that's happened here in the US. So I think that you can open a bit of a can of worms when you start talking about the availability of this leverage and to certain counterparties. And I don't think that's specific necessarily even just to just to the levity ETF market. I think you can really open that up in any counterparty risk when you think about does a bank really want to have so what you know, bank would be very careful in Barclays, so I would say, are pretty conservative and extremely diligent about how they choose their counterparties, who they want to who they want to partner with, and so as a general rule of thumb, you have to always keep that in mind. Just we're in the when the we're in the business of risk management at the end of the day, and so yes, this is sort of a I wouldn't even say a new tool is not a new shiny part of the market, but it's we would treat it exactly the same way as we would any other counterparty.

00:13:04
Speaker 3: As you mentioned in the beginning, that there's leverage single stock ETFs in Korea. There's leverage single stock ETFs in the US. The difference is that in Korea, so much more of the AUM growth has come in through new money rather than the underlying asset values going up. So one thing I think about the Korean market. People talk about incredible retail interest that probably dwarfs the US as some sort of per capita basis. How does that matter? Does that have implications in terms of the tail wagging the dog, the spillover effect, This fact that there is just a lot of interest in these products beyond just the products going.

00:13:43
Speaker 4: Up I think that the retail channel in general is one of the most important dynamics for global equities in the world today. Right, could we make the case that Korea in particular is kind of ground zero for that that retail cohort probably, you know, So for example, ninety three percent of levet ETFs in Korea are owned by the retail investor, whereas that number is lower in the US. It's approximately seventy five percent. Still still high, but not as high, right, And some may say, well, only seventy five percent of why is it not high? And also I think we should probably just be very clear, like levet ETFs have made retail an awful lot of money, right, So you know, there are plenty of guys driving around McLaren's because of their returns that they've generated in LEVITYTF. So you know, I think we sort of need to balance out sort of.

00:14:40
Speaker 3: No judgment here, We're just trying to We're just trying to learn how it works. But I don't judge anyone from making money on.

00:14:46
Speaker 4: Balance a lot of money has actually got asked this morning, you know, have you actually calculated how much money has been made? And I said no, But on balance a lot of it, Yeah, quite a bit. So going back to the point on retail. Take the US for example, the US, it's a phenomenon our lifetimes. Thirty four percent of US household wealth is now in equities, right, It's the highest on record. It's higher than dot Com. I think what's even more amazing about that stat is if you take the next largest component of household wealth in the US is real estate, and that is around about twenty six percent. So the eight percentage point difference between those two sort of assets, so to speak, is also the widest on record. We as a society have never been this over index or overexposed to equities, and so I think that what you've seen within, say the Levet ETF space is really just another small part of that broader ecosystem that has contributed to this enormous wealth creation. And one of the things that we think about a lot as a team. People ask us what keeps you awake at night? It's not levity ETFs that keep me awake at night. What keeps you awaken night is that you have a structural impairment to equities that effectively no economist on the planet has a cell in an econometric model that says twenty percent inpairment to the SMP it basically destroys let's just call it around about sixteen trillion dollars of wealth. So let's just say that's half of US GDP, right, and that is an instant impairment to US consumption. It's your recession straight out the gate. I don't want to get all sort of bearish or anything, but I think it's just important to highlight within the broader context that that retail investors have a huge amount of exposure and therefore, in turn, the US government has a huge amount of incentive to try and not do anything too disorderly that could completely derail I mean, my big stat is is that people used to say the economy is not the stock market or stop market is not the economy.

00:16:41
Speaker 2: I just haven't said many times on the podcast.

00:16:43
Speaker 4: Yeah, I just think the stock market is the economy now, not in the traditional sense of like, oh, the stock market is going up, therefore the economy is doing great. But yeah, a twenty percent inpairment to the stock market is kind of I think it will trigger a meaningful downturn in US consumption.

00:16:56
Speaker 2: The thing that worries me now is it's not just the stock market is the economy. It's like AI is the stock market, and therefore AI is the economy as well. Like we know it's been driving not just macro growth, but if it's also driving stocks and we're getting a wealth effect and it's also driving consumption, then I don't know, it's like an AI impact squared right.

00:17:15
Speaker 4: And look again, just to talk about facts, the bulk of levit etf AUM has grown within that cohort as well. The largest AUMs are all within either nasdact rated products or semis conductors or single names, most of which are I mean the largest the largest single name levit TF in the US is is Micron, right, so that kind of tells you the largest largest single name levi DTF in the world is Heinex. So these dynamics do play an important role, and especially when you start thinking about the tail wagging the dog, and price dictates narrative, right, So people see prices going up, that gives them a confirmation bias about oh, that means we maybe we can spend more money on capex, or that means that the AI story is alive and well. And that's not necessarily not true, But how much of that is getting distorted by these sort of these non discretionary flows that are pushing prices up, or indeed they're.

00:18:07
Speaker 2: Just general momentum, right, like momentum attracting more flows.

00:18:10
Speaker 4: Correct. I mean, let's face it, momentum is the everything. It's the most successful factor strategy in history, right. You know, SMP goes up seventy eight percent of the time. Therefore, by definition, investors generally want to be long momentum. They want to be long stuff that goes up, and they want to be short the stuff that goes down if they do indeed short.

00:18:29
Speaker 3: The MUU the Triple Averid I think it's triple Averid whatever it is that was trading at twenty three a year ago and it recently had a peak of over twelve hundred. So that'll get you a lot of McLarens on it.

00:18:41
Speaker 4: Yeah. I mean again, this is the thing for as a team. It's X, it's a it's a two xctif that's okay, But.

00:18:49
Speaker 3: Actually, can I ask a question about this? So you mentioned that all of these products, like they go through the regulatory process, and you know, we have the SEC. I don't know what career's equivalent is but I assume they have some sort of similar body. What is like the SEC's bar?

00:19:06
Speaker 1: Is it just yeah?

00:19:08
Speaker 4: Like what is like?

00:19:08
Speaker 2: What?

00:19:09
Speaker 4: No?

00:19:09
Speaker 3: Seriously or like you know ten x?

00:19:11
Speaker 4: Like what is the point?

00:19:12
Speaker 3: Is it just like Okay, this checks a certain set of boxes? Because clearly it's not about like doubt it should be you know, it's like is this product good or bad?

00:19:21
Speaker 4: Right?

00:19:21
Speaker 3: That's not really the question. Does this product meet a criteria? Or does it? What is the criteria? Why don't we have ten XCTF?

00:19:28
Speaker 4: So there's actually an anecdote. There was a time, if I'm not mistaken, relatively recently during the government shutdown, where there was an attempt to try and list and shelf some I don't think it was ten x, but there was I believe some five X levit ETFs, and effectively the regulator I believe at that point just kind of made it abundantly clear that that there are limitations to to leverage just from a to your beginning point. You know, you may not be interested in leverage. Yeah, leverage is probably interested in you. And again I'm not privy to those conversations in any way, shape or form, but I do know and understand that there are limitations to what a regulator would deem acceptable. Okay from a leverage perspective, quite quite reasonably as sure.

00:20:16
Speaker 2: Just going back to the momentum trade more broadly, so, Barklay's you have this index product. I can't remember the exact name, but it's like the market timing product.

00:20:26
Speaker 4: Betty Betty Betty, Barclay's equity timing indicator.

00:20:29
Speaker 2: Yeah, and that has been like in I don't know if if you use the specific term overbought, but like it's basically been in sort of bubblish speculative territory for some time now, like a record amount of time.

00:20:42
Speaker 4: Right, yep, that's right.

00:20:43
Speaker 2: Yeah, Okay, what should investors do with this information? Sure, because I feel like all the surveys right now show everyone's super bolish. Everyone thinks stocks are overvalued, and it's like, so what if the trade is momentum then you just keep going Yeah.

00:20:56
Speaker 4: So so Betty, Yeah, we love Betty. So this index was created shortly after I joined Barclays, but it was the first iteration was created back in twenty eighteen. So there's a reasonable amount of out of sample data around this framework. It's got nineteen inputs. None of those inputs. We have a mant on my team. I tell everyone this in my team every week, which is, if you can't quantify, you don't have the right to talk about it. And using the word feels and seams a band. If you use the word fields and seems, you're fired.

00:21:23
Speaker 2: I think we'd be in trouble.

00:21:24
Speaker 3: Jill, Yeah, but it's a good rule.

00:21:27
Speaker 4: But the idea is, it's a very simple rule, which is we just want to try and really deep root the team in quantifiable data, right, you know. And just to take a step back, when Scott and Ronnie who run the equity business, when they sort of effectively were hired into Barclays as kind of really revamp as an ascendant equity business, one of their main priorities was like, we need content at the center of the mind shared in order to sort of like really partner and hold hands with our clients. And so that's when they brought me in. And because we wanted to focus on quantifiable content as opposed to it. So that's the backstory as to why Betty was created. Because we wanted to have a market timing model that removed fields and seems and so it's got nineteen inputs. It's got everything ranging from real yields to spot Volk correlation to looking at discretionary flows, like what a mutual fund beat is, what a hedge fund beat is, what are CTA is doing, what a vult control doing, what elever TTF doing. So everything from the discretion in, the non discretionary vertical, from the vole vertical, from positioning. We just the only thing we didn't include was sentiment indicators. We weren't interested in feels and seams, so there's no AAI bullbear index or anything like that. And so your question was it's been in this record sort of warning territory. Now, yes, it has been in record warning territory, and effectively that's been driven by primarily momentum crowding. Now, as you know at the time of recording, we had a big momentum pullback over the past couple of weeks, so that's actually sort of been a relatively healthy and reselling that real yields problematic if you're competing for can capital at the same time as between the equity market. Obviously, record year for issuance, possibly this year government going to be record year of issuance IG record year of issuance.

00:23:10
Speaker 2: Yeah, this is the other big market story. Is like a blockbuster summer for IG bond issuance.

00:23:15
Speaker 4: Absolutely, So if you think about what real yiods effectively represent that dynamic of that competition of capital versus equities, if you just generally look at where real yields are today in say a post GFC environment or a post COVID environment and benchmarket against where equity multiples are, equity multiples shouldn't be this high, right, so we can get into a bigger debate about oh, dot Com real yolds were very high and in equity multiple skyrocketing. I'm like, yeah, but the government wasn't asking you cap in hand for tons of money, so they didn't endgrate. Yes, but but the hell of a ride it was in the build up to that. But so better effectively is taking all of these inputs and what is it telling you right now? It's just telling you that the forward return profile of the S and P from an asymmetry perspective a tactical two month time horizon, it's just not great. Right now. We're looking at if you were to pick a random day in time and say all right, I'm gonna buy the SMP, and I hold it for two months forty two trading days, the average return would be around about one hundred and ninety bibs. Not bad, right, and your hit rate of making money is about seventy three percent, so betty, when it is in this kind of territory, So six seven it was high as sort of ten or eleven. It was telling you that you only had a round about a thirty five percent chance or even lower of making money in the S ANDP over that same time horizon, and your average return was basically negative. So it's not so much necessarily that it's telling you, oh my gosh, the market's going to crater. It's really just an illustration of a bunch of quantitative inputs that are telling you, actually, the asymmetry is not great. And that's exactly what we've seen. The model first flashed as a warning signal late May. SMP's kind of gone done nothing since then, and so maybe in anticipation of some big correction in the equity market isn't forthcoming, And that's okay. I still take a lot of validation in the model that is kind of telling you that to just sort of pump the brakes a bit, let some of this froth and the equity market come out and actually get a reset, which then actually sets us up better. I mean, ultimately, earnings are still good. Right, We're still driving AI in the economy, and we can get into a debate about whether that's sustainable or not. And then we've also got to work off the assumption we're still running a massive fiscal deficit. And whilst that environment is happening, it's quite hard to create any kind of fundamental economic downtown too.

00:25:47
Speaker 3: Setting aside market timing and what's going to happen in the next two or three months, et cetera, just under sort of like bigger question the combination of market valuations. You want to measure them all the classical ratios that people like versus the increase in real yields, Like how historically expensive is this market right now?

00:26:10
Speaker 4: All right, So if we take the post GFC environment, the challenge is always going to be that SMP margins were much lower for a long period after the GFC than where they are today, and we have to acknowledge that higher margins should map into higher multiples. So but we'll do the full comparison, so post GFC, because there's not that many periods where real yilds of this high. Real yilds today on a ten year basis are running about the ninety fifth percentile, and they're around about I think two thirty give or take. So with that being said, if you take what the average SMP multiple when real yields were this high or higher, it's a scary low number. The S and P multiple would be around about fourteen to fifteen times, and we're currently trading on around about twenty point two to twenty point three. If you take the post COVID environment, which I think is probably a better representation of what S and P operating margins look like today, we're still low. It's around about eighteen and a half times, So you're still talking about basically a ten percent multiple contraction versus where the Hey.

00:27:17
Speaker 3: It's just a very simple question. Why are margins a more important factor here than expected growth or expected earnings growth? I mean, like, in my mind, I would pay higher multiples because I think that the earnings are going to have a faster growth rate than they used to have. That seems intuitive to me. Why is margins the lever here? That we're looking at.

00:27:37
Speaker 4: It's a good question. Well, it's not exclusively just margins. You can sort of measure it as row as well. There's different ways you can do it. But effectively, businesses are becoming more profitable. If it's a more profitable business, it's going to be working off the assumption to a degree it may not so be accurate, but that they're effectively that has a bigger moat. It's more it's a more high quality business, and therefore you'll put that on a higher godes, so to speak.

00:28:03
Speaker 2: Can I ask a slightly personal question, which is I used to joke that I wanted to be reincarnated as an equity derivative strategist because then I could just find a number to justify anything that's happening in markets. But does it feel like people taking more seriously now versus say twenty years ago, when people were still talking about like fundamentals and stocks. Now you have this environment where flows are super important, You have all these mechanical things happening, You have the multi strats, as you pointed out, Vaull targeting, CTAs, all this stuff is getting bigger. Does it feel like equity derivatives are more important.

00:28:39
Speaker 4: Now, Oh, I thought you were going to say, but it's my British accent that makes well that too serious because I'm.

00:28:46
Speaker 2: I will say, we get higher listenership on episodes when our guests.

00:28:50
Speaker 3: It's crazy because like everyone knows how much Americans love a British accent. But what's annoying is the bridge to know it too and exploit that. I just like you, like know, like you know what you're doing.

00:29:01
Speaker 4: That's a reason why I stayed in ten years married an American, you know, living living in the American dream. Sorry, do you know what you're doing? I'll get back to the actual question at hand. So is there increased validation from having a more quantifiable world that we operate in. Yes, But on a person, if you're asking a person quert, I don't thk ask a personal question if I was to give a personal answer. My career wasn't always like that. I started my career as a fundamental single stock analyst, and I actually saw in my career actually as a generalist sales at at JP Morgan in two thousand and four. But I then became a generalist analyst, so to speak, on the by side, and I did that within the avenger of the world for several years, and then when I went to the back to the cell side, I had to pivot. I had to change my investment approach because of the fact that the industry was becoming increasingly specialized, and as a generalist, I was struggling to make an impact on clients that were becoming much more sophisticated in the weeds on their particular sectors and areas of granularity that I just couldn't compete with. And so at the time I was working at City and City has a very good had a very good quant business, and I was like, what's all this quantum factor stuff? What is all that? And I genuinely didn't know, And this is twenty twelve, to be clear, twenty thirteen, and so I took it on a personal crusade to understand the post mortem of my portfolio management experience prior understanding why was my P and L doing certain things which I didn't understand at the time. And as it turned out, I was just a value investor. But the concept of being a value investor other than sort of the Ben Graham or Warren Buffett model was a bit as in value from a factor perspective. Now it's ubiquitous sort of fourteen years ago, But back then it was really novel that you were going to customers, discretionary customers, generalists or just long short guys who weren't quant guys and explain to them is quant phenomenon in layman parlance basically, And that was the start of a pivot into a much more sort of quny derivative y knowledge experiment and it just ballooned from there.

00:31:13
Speaker 2: Yeah, this is kind of what I'm getting at right, Like it has become more important in the market. I remember speaking of twenty twelve, do you remember show the headlines where like people would talk about CTA flows or something. Yeah, of course, and it would be like a mysterious force in markets. Now everyone knows.

00:31:29
Speaker 3: Now that's what it has become. Yeah, and it's interesting to think too, Like if if I just think in my mind about one of these platform shops, multi strategy whatever, the understanding of the comp of you know, the company, is that that pod invests in like theyst on the buyside, must be orders of magnitude greater than it was in the sort of heyday of like the cell side analysts who would like, Oh, we're going to issue a by rating on GeV or Nova or whatever like that, those investors no g company insanely.

00:32:02
Speaker 4: Well totally and look to put some anecdote around that. Barclays as a bank, as an equity business, as a research house again ascend an equity business. We've been working really hard over the past three years to sort of hold our client's hands and make them aware that we are a really prime and tier one equity franchise. A lot of that is about corporate access, right, so actually having more research coverage and having more access to more companies, which in turn we can road show and actually give our customers access to those companies because it is that important to them. To your point exactly, Joe, like, they have so much granularity and detail in their forensic modeling now that if you're a generalist, it's very, very hard to compete on such a granular level. So yes, I pivoted away completely and focused on different mantra. Was if you think about the verticals of equity investment, the way I see it is that you've got fundamentals, which is obviously what we talked about. You've got economics, you've got cross assets, slash macro. You've got quant which I would include factors, You've got derivatives, you've got positioning right, and then you've probably got some other stuff as well. But my view is the way that I run the tactical Strategies teams is that we don't need to be a ten out of ten in all of these. I'd love to be, but it's just I just don't think it's possible in a world of AI. We can obviously augment some of our game in certain verticals, but the aim of our game is if we can be like a seven or an eight in all of these, and some of them will be less and some of them will be more, some of them will be in nines or tens and others will be like fives or six is it basically means that what we can do is we can go into any customer, any client, any investor, and say, hey, there's something about the market that I'm sure I can help you on that you're not as aware of. And that's where I think that the evolution of that kind of education, investor education has come to now, rather than just focusing.

00:33:58
Speaker 2: On just one Yeah, I don't mean to get all media naval gazy here, but I think we are seeing a similar story in media where like the niche subject matter experts are becoming much more important, much more popular, versus the sort of generalized news platforms. I think they don't have to comment on that.

00:34:17
Speaker 4: By the way, No, but it does polly back into the world of finance and the world of AI, because in the world of AI, everyone can have an army of quants in their pockets now of questionable accuracy. But the point is you can crunch orders of magnitude more data. So where's the real value. I'm a big believer that the value I see it kind of think about it as knowledge and wisdom. Right, everyone can now have access infinite knowledge, but it doesn't necessarily mean that they've got wisdom. And the old saying is is that knowledge is knowing that tomato is a fruit, But wisdom is knowing that you know.

00:34:53
Speaker 3: Another episode And by the way, Tracy, I just want to say I meant to send you this. I saw someone with one of these viral froyo places that are like they put little cherry tomatoes.

00:35:04
Speaker 2: Actually that could be good.

00:35:05
Speaker 3: Yeah, that's I'm saying tomato is a fruit in the not.

00:35:09
Speaker 2: To get wildly off topic, but my tomatoes so far this year are freaking amazing, and come later this month in August, you're gonna have.

00:35:18
Speaker 4: Like, No, this is my take.

00:35:19
Speaker 3: Ex I love the same knowledge, wisdom tomatoes, et cetera, but I actually think some tomatoes actually to make a different sale. This is my only point. But I understand, I understand the point.

00:35:31
Speaker 4: Yeah, and so I think it's the same when it comes to sort of data and the world to find. You can be incredibly grindar and specialized, but sometimes you're going to miss the forest for the trees.

00:35:40
Speaker 3: Can I just ask not to turn this into just another AI conversation, but you must actually have some insight on the question on some of these things. Let's say, like you want to construct an index or some new thing, like how good are the models right now at like really reliably being able to do quantitative work. I know it's like you can get a lot of the way there, and even someone like me can like hag together something, but like to the standards that you have, like how much do they still like? No, this isn't that nowhere near something that I would like then be ready to turn into a chart and send to a client.

00:36:17
Speaker 4: Yeah, I think that's a great question, because we're doing that all the time. So, you know, we'll have a customer come in and let's say they've got a particular security there's a single name item. They want to hedge that item, and they want to hedge in with a basket. Right, That's that's one of our most common kind of business problems that we face off with, and so we need to build a universe of securities that effectively replicates that particular instrument without using that instrument, of course, And as a consequence of that, we're effectively running a what is essentially a giant pairwise correlation model, and then we've got to optimize the inputs depending on what individual correlations against that underlying instrument are. It's relatively straightforward if you've got a really cool optimizer if you ask AI to do it. What it's okay at is selecting what instruments you should. So let's say you're like, I need, all right, this is a household consumer product. Actually know what, Let's do it in AI. Let's make it more new economy. So we've got all right, we've got a particular AI vertical. Let's say it's a neocloud, all right, we need to hedge that neo cloud with something else, all right. So AI is quite good at selecting. Let's go and get all the other neoclouds that are listed, and then let's find a whole bunch of other companies that most of which you'll be aware of, maybe some of you're not aware of, that actually have a reasonably high correlation to that instrument that you're trying to hedge. That's kind of where it ends. It's not very good at telling you, all right, what about the liquidity consideration, but it.

00:37:45
Speaker 3: Can roughly sort of determine the first step the ingredients, right like you're making Emmanuel Derman in his book talked about like the job of the trailers to make if we were going back to the fruit saling question. But you have a bunch of wholesale and then you're sliced it up in a certain way. It could it can identify the ingredients, and then it's your job to figure out the optimal Like you can't do the proper slicing and allocation exactly.

00:38:09
Speaker 4: So it's it's, yeah, it's pretty good at it's pretty good at identifying what my universe is meant to look like because I get the.

00:38:16
Speaker 3: Sometimes I see these notes and I have never tried this, but like from I don't know, somehow I get I got on like JP Morgans like trading desk thing, and they're like, oh, by that, we figured it's time to go along this basket of you know, energy related companies in short, this basket of like whatever it is. And I've been curious. I've never tried it. It's like, could I get a model to like back out what these ingredients? Sorry? If I gave the model line.

00:38:40
Speaker 4: And the theme, yeah, so again I would I mean get this real credit to the to Barclays just in terms of we've been pretty leading edge in experimenting and adopting as much AI as we can, and so we have co pilot, we've got CLAWD licenses, we are we're working with other other partners sort of build in house staff either using external models or own internal models. But the point being is is that we've had plenty of time to operate in the sandbox now and I'd say where AI's without a doubt most powerful is when you're giving it very identifiable data parameters. Okay, right, So whether it's structured or unstructured data and say, hey, I need to try and figure out whatever my parameters are. That's the data. Where it's still less good is if you're basically giving it unstructured parameters to say just can you think about an ethereal topic and sort of come back to me with an answer, And it will come back with a pretty comprehensive answer, but most of the time it needs to be fact checked and or annotated or just tested to scrutinize it.

00:39:48
Speaker 2: Joe, you've successfully turned this into another AI conversation.

00:39:51
Speaker 3: Well, how can you talk about quantitative identify? You know, how can you talk about those Yeah.

00:39:56
Speaker 2: We were doing pretty good for forty minutes, So all right, Alex, thank you so much for coming on all lots really appreciate it. Truly the perfect guest.

00:40:03
Speaker 4: Thank you so much.

00:40:04
Speaker 2: Asking So, Joe, that was a fantastic conversation. A couple things stand out. So, first of all, it does seem like with the growth of all these products, the explosion, especially in Asia, that we have products who are sort of like more important marginal buyers and sellers in the market at a minimum. The other thing I was thinking about is like Okay, a regulator isn't necessarily going to approve a five times levered product or one hundred times levered product. But is there a point at which, like the aggregate number of all these products actually becomes more of a concern totally.

00:40:54
Speaker 3: I mean there's two things. One you have to take seriously, like where we are in terms of balance sheet and how much balance sheet is being allocated to this leverage and what happens to bank balance sheets in the event like some major downturn. And then I thought, like the just the idea of like I had not realized how big that gap has grown between household equity exposure and household real estate exposure. I still feel like that's probably like a pretty at least to me, like a pretty eye opening stand because they're just I know, there's a lot of equity exposure. It's become important and no one needs to like argue with me. It's like the stock market is the economy. But in my mind, I'm like, oh, it's still like real estate is the core of like people's holdings, And not only is it not the core, at least the aggregate I'm sure the media and household is still way more exposed to their house than the stock market, but in overall it's pretty staggering. And then you start lot being geared to the stock market, geared to.

00:41:53
Speaker 2: The stock market. How much of the stock market is now geared towards leverage and then how much of it is also geared towards AI. It's yeah, it's a lot.

00:42:00
Speaker 3: No, it's a lot. And he really spelled it out.

00:42:03
Speaker 2: Well, yeah, we have to have them back on definitely. Shall we leave it there for now?

00:42:06
Speaker 3: Yeah, let's leave it there.

00:42:07
Speaker 2: This has been another episode of the aud Thoughts podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway.

00:42:12
Speaker 3: And I'm Joe Wisenthal. You can follow me at the Stalwart. Follow our producers Carmen Rodriguez at Carmen Arman, Dashel Bennett at Dashbot, Kilbrooks at Kilbrooks, and Kevin Lozano at Kevin Lloyd Lozano and from our Odd Lots content. Go to Bloomberg dot com slash odd Lots for a daily newsletter and all of our episodes, and you could chat about all of these topics twenty four to seven in our discord Discord dot gg slash onlines and.

00:42:36
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00:43:01
Speaker 4: In