They said one of the features of the cat-hacks, booms, is that they actually produce profits. Because if someone invests and the other person, the buyer doesn't actually immediately to appreciate what they've acquired, then aggregate profits rise. They have no trouble investing tons of money during these technology transitions. But they do have a trouble spotting the winners. So that question is, can you get a investment in a tangible, as in any other type of physical investment? The city of the city obviously is. Hi everyone, welcome to the Intangible Economy. Our guest today is Edward Chancellor, who is a financial historian, journalist, and investment strategist. He is the best-selling author of Devil Take the High Most, a history of financial speculation, one of the classic books on investment bubbles. At least in my opinion, he's also the world's foremost authority on capital cycles, having written two books on this topic. In addition, he's the author of The Price of Time, the real story of interest, and most recently helped our former boss, Jeremy Grantham, write his autobiography. Ed, welcome to the show. I see you, Kai. What you did mention is that you came to GMOs, my analyst back in 2008. We came back to the financial crisis together, didn't we? Yeah, and the other piece being that to add to your many accomplishments, helping advise me on my economics thesis on credit cycles and bubbles at Harvard. And if I'm allowed to play our trumpet together, you remember how we were working in early 2009, and I got you to do a piece of research to show that quality stocks, GMOs, heavily invested in at the time, had tended to deliver author or I performed during boom period, but your bust periods, simply because they had a low beta to the market, in which case the arts was that when you wanted to get out of, when you thought the bust was coming to an end, you wanted to get out of quality as quickly as possible, which was actually, we delivered that research in February 9, just in a couple of weeks for the market turned. It, that was, and I credit you because you actually redefined quality in the various markets that we looked at historically as volatility or low-volts stocks, because we didn't have data for, you know, through quality back then. Still that. And when I think of sort of good pieces of research that I'd been involved in in my life, I'd say that was definitely one of the top five pieces. Yeah, very timely, and yeah, I was definitely a pleasure working with you at GMO. And that's why I'm so excited to have you on this podcast today to go through some of your research and your work. Okay, let's, let's, let's be read. Let's start. Okay, so the topic I wanted to start with is, I guess, the topic of the day. US big tech companies are investing trillions of dollars into AI data centers in what is set to perhaps be the largest investment infrastructure boom of history. Setting aside any of you on the technology itself, what does the history of capital cycles from the real Roy Mania to the Japan bubble to the dot com boom in the late 90s teach us about how the current cycle may play out. Um, well, it's, it's hard to leave, it'll leave out the efficacy of the technologies. It will have to get back to that in a minute. But the general, the general principle, I'm looking at past technology booms. And as you know, I wrote a paper of generally grant them on this in February this year, which is available on the GMO website. But the general pitch is is a new technology arrives. People get very excited about the impact of that new technology. Sometimes the new technology doesn't attract too much attention in its early years. I'm thinking for instance of, you know, when the railways came to Britain in the 1820s, um, 1825 was the launch of the first passenger railway in the UK, which is called Stockton and Darlington. And that the first few railway companies had a, um, had dominant positions, their competitions. They were pretty profitable and that technology was proven. And then we had two successive waves or, or, of investment, one decade later, sort of 8035, 36, uh, that led to boom stock market, a bit of a building came down, but it wasn't too much damage. The real problem, or mania came in, um, sort of 1843 to 1845. And that is really the, um, a period in which, uh, there was a massive, um, there were a lot of many, many railway schemes across Britain and the, um, in terms of capital employ, or capital projected capital expenditure. I think it was running to about 10% of, of UK GDP, certainly not much higher than AI today. And there, there were too many, um, as a result, not all the schemes got, um, actually went ahead, but, but the upshot was far too much duplicative, um, investment. And you're famously, as I say, it's three railway lines between, uh, London and Pete Proge, at least Anglia, three railway lines between leads and, and Manchester. And obviously, if you have three lines running between, um, two places, um, that, that could be less profitable than if you have one line. And the upshot of that is that, I am, the railway index, I think lost about 60% of its value. Um, and ironically, I just looked at this the other day, you know, canals, stops, canals with most obvious losers, uh, from the railway mania. And they did lose the end, but actually you did better investing in canals stocks to 1845 and 1850, but you did in railways because, uh, canals stocks, uh, you've been beaten down a bit with railways still have plenty to fall. Now, look, in the very long run, in, you know, very long run that's saying, 20, 30 years, that, that investment was pretty benign for the economy. And, you know, although the railways were never quite as profitable as they'd been in that early years, um, it, it did, it didn't, it, it, it was good for the economy. And, and what, if you got into railway stocks in 1851, Spubble, it burst, it was perfectly buying. Now, then, you know, we have, we have other sort of new technologies that attack much more competition. I mean, you just think, you know, um, motor cars in the late, um, 19th century, I think the US has something like 2000 motor car companies. Um, and the upshows that was, you know, we, we, general motors, which was a winner. And I had to be recapitized twice. And, um, and actually GM was really a sort of roll up of failing, um, car companies. And, and Henry Ford, I think he only, it is, was a Ford motor company wasn't listed, but Ford only succeeded on his third attempt. It was usually over, um, you know, over investors. aircraft was much the same. Um, I think, I mean, what, what a buffet police had. There were actually three aircraft companies in, in, um, in Nebraska. Uh, I believe it all in, in Omaha, Nebraska. Uh, that, that, you know, again, far too many aircraft companies founded, um, huge, huge, um, you know, very lost making. And that, you know, that person has really continued, you know, obviously into the dot com era, um, where, you know, again, massive cat, massive cat bags. And what's interesting about what we use to call "the TMT Bowers" is technology-mediate and telecommunications.
interesting is the capital is largely done by telecoms companies and they did the heavy spending but they really want the winners and so one of the points they made in a recent column of mine was actually markets are really they have no trouble investing tons of money during these technology transitions but they they do have a trouble spotting the the winners and then the end in the kit and then you know as you know after after the dot com bubble bus you know Nasdaq uses 85% 95 you know he sorry 78 79% of its value Amazon goes down more than 90% so even even though Amazon emerges as as an eventual winner there is a massive you massive loss and and it's not it it's dangerous to say in hindsight that you can spot Amazon as the winner and get its go you know because they could be near the other businesses around web madness and that you know that the might of might have actually taken the prime place so anyhow so that's the general picture the general picture is a new technology everyone gets very excited about it a huge amount of investment and investors tend to anticipate the profits flowing more quickly than they can then they actually tonight be the case and there you know there is there has always been I think there's always been a shake out I possibly though the one exception is the is is the arrival of the telephone another's a revolutionary technology where the the bell telephone systems began to insert itself and got a pretty early monopoly telegraph also moved to a bit early and moved to the monopoly very quickly so you know you could you could say that if you've got a revolutionary new new new technology and for reasons of inherent monopolistic what do you want to call it so environment there is case that the new technology can arrive without you know without a huge evolutionary investment but if the barriers to entry are relatively low and therefore you can have more than one dominant path then you're likely historic you're likely to get you historically you have had over investment and that's all we know we know we can't say that the you know the future will resemble the path but it should sort of guide our judgments at least and then you know then we can then we'll concess current circumstances as they need to what it's intended is this time different or not right so if I'm hearing you correctly you are saying that you know over the course of history there have been many successive waves of capital cycles which generally start due to the advent of a new technology which accords attracts investment capital in a few cases such as the telephone the industry has consolidated into monopoly pretty early and has been relatively stable but the vast majority of instances end up with an influx of capital and a fragmented market structure whereby profits are competed away to zero and that leaves investors in these companies with you know pretty pretty rough outcome and so then I'll add something you remember one of the key precepts of the capital cycle theory is that it draws on the person as dilemma being the radical problem which is that you know in the business dilemma you've got two prisoners and the questions you need to do they do they keep quiet and both serve as sort of moderate sentence or do they both rat on each other and get very long sentences in other words it's suboptimal to rat but the way the game you know the business dilemma game structured is there's an inducement for both to rat it doesn't it doesn't work by not you don't benefit by not ratting and and and I think it's the same you know the capital cycle during investment and you investment through this you see other people going into this into the new area and if you didn't go in there's a possibility that they might come out you know dominant monopoly and crush you and so you go in but if you go in you may come for you know the end result may be suboptimal for that's the investment what is all it may actually you may actually hang on in that it's not necessarily there may be a sort of agency problem it's not necessarily irrational for the individual and I think that you know with AI there's one narrative I don't know I mean I don't know whether you wanted to you know how robust it's but one narrative is that when when open AI came out with his was you know chat GBT in in November 22 Microsoft saw this as a way to team up with open AI to break open the Google search monopoly and then you know Google and started you know how to get to get you know respond and then of course you know then everyone else by standing by the way so I'd say you know this is a great technology we want to bid us the action to so of course of course we're going to get a huge capital. Yeah I mean it's interesting to think about how the different big tech companies have responded differently to the to the game theory right because we have Apple of course is a famous example of a company that has largely abstained from the arms race and it's kind of waiting to see how things shake out whereas amongst the hyperscalers you see ever increasing investment and quotes from CEO is being like I'd rather go bankrupt and lose this race right so there's a clearly a you know this this dynamic is clearly happening amongst at least some subset and maybe your point is just you you only need a few players to be bought into the idea in order to drive the entire cycle. Yeah and and you may have been pulling this case more cases than I am but you know it's not just the way you know the the top you know the largest hack US tech companies being able to there's a whole load of of other competition you got that what does it keep seeking China you would have I mean they are listed a few Chinese AI companies recently and then you've got you know what you know vast amount of you know a VC capital going into the same space so the the the tech you know the big tech catags into AI gets most of the most coverage I I'm spazin in in in absolute terms and relatively it's it's the largest section but there's a lot of other investment going on at the same time right so I guess the quick question then is so we know that there's a lot of supply coming online a lot of investment coming into the AI sector I guess the question goes it is ultimately will there be enough demand right will there be enough demand to meet supply and how should we think about this side of the equation. So it is often the case or it has been the case in in these tech groups that people overestimate demand and I think in back the railways in the in in an 1845 the catapex spending at that time would require you know within a specialist if someone's got a crunch to the numbers that would have required a passenger rail traffic to increase by threefold over the next five years and given that that you know that there were fair number railways already by that time in the K wasn't going to have them during the during the dot com bubble I there was this sort of urban urban legend going round that the data traffic was doubling every every two months where in fact it was any doubling every six months and you know that this little factoid you mean it actually originated in there with some company that was at late taken over by WorldCom which they do at bus and it was side-backsy everywhere you know or in media sale or all the brokers pitched up even the news US government pitched up said one believed it but in fact we actually am data this is guy I know good Andrew of the leak who was at the time that Bell laughs and in in in 2000 so just right rather time
and the ten poppers were eking. He put out a paper second, giving you the tree and the mullend growth. And no one said that the actual, accurate data was available in real time and never be attention to it. The upshot was well called when bus and host of those other single alternative telecoms carries. Old nets went bust and there was an massive over capacity in fiber optic cable and all the telecoms equipment supplies like Norton, Ericsson and Lucen, took big hits and actually there was a massive decline in profitability. I said one of the features of the caphex booms is that they actually produce profits because if someone invests and the other person, the buyer doesn't actually meet it to appreciate what they've acquired, then aggregate profits rise and say, well you see in the late 1990s going into 2000, massive search and reported profitability and then because that capital turns out to be misallocated, then you have, then new caphex isn't immediately curtailed and then you have to depreciate past caphex and so you have a collapse in profitability. And we're seeing something very similar today and as you know, the depreciation schedules for these AI chips, GPUs has been extended and I think you probably may better know but I think from roughly an average of three to three and a half years to six and a half years. And I understand that because if you buy a GPU and you keep it in a warehouse because you haven't actually built your data center yet, you didn't actually start depreciating the GPU until it's actually in the warehouse but there is a sort of technological depreciation that is going along, going on, even before you actually start using the chip. So, we'll see but you know, the market is being driven as far as I see and by strong economy on the back of a lot of caphex and very strong earnings growth but there's a contingent on the investment turning out to be possible and the demand being there. Now, the criticism going back to on the demand question and by all means, it's constantly if you have different view is there is this view put out that you know that AI is where on the we're on the cusp of official general intelligence, even singularity and that this, you know, the AI whatever that might be is just, you know, it will be able to do you know, almost every sort of conceivable human function apart from you know, physical, physical plumbing. And, you know, I'm very, very skeptical of that view because I don't, I mean, when I, if I was talking about AI as a large language models, large language models work through sort of inference, through probabilities of, you know, what is the most likely next taken to the idea. I can't see how that can need to regenerate the original thinking or activity and then be as you know that it's, it's, you know, sometimes can make you the wrong selection. And then for all you get the hallucinations and I think the hallucinations because these machines aren't sort of genuine reasoning models. There's a are inherent to the, to the large language model technology. And if that's case, if that's the case, you know, I really don't think that the demand that is mooted, apparently, it's going to be there. And I, I don't know if you picked this up. Do you see that last week or so a story about some company that provided software for car rental businesses? Do you see this? I don't know. They used everyone's wanting the Claude, the new, Claude vibe, vibe coding. They used Claude to be an update their software. And it wiped out their entire customer database. And it did not necessarily work. You think, you see, stayed up the whole business, crashed and the companies that we're using as far as Einstein, the company, the car rental companies were using the software, was suddenly frozen. And a couple of months ago, the winner of the, of the Royal Society's Faraday prize, the top scientific prize, I call Michael Woodridge, gave, gave the Faraday lecture, which I think is worth listening to. He's making his sort of points that I'd made. And I was at a station, like Wood's from head. And he then thinks it might be what he calls that a Hindenburg moment. When the Hindenburg moment was, I didn't know when it was in 1937, one of these, the Zeplet, everyone was excited by these Zeplets and, and the Hindenburg, that can, you know, blew up somewhere over some US airfields. Everyone had second thoughts about the technology. So I, I, I, I, I may have this one, but I, as far as I can understand, the hairpacks into large language models is not, you know, about simply improving search and helping with research, but actually is posted on, you know, a great, and a great through in an, and into a, a genetic AI. And, as I said, well, we see, I mean, it's not, you know, it's not uncommon for investors to, or, or, you know, I mean, investors, in companies and in markets to, to imagine that technology is more advanced than it actually is. You may think that a lot of those, you know, go back to the dot com bubbles. So those businesses would have been viable. Had we had the, um, faster internet connection, but the time people were on by large working on sort of incredibly slow dialogue connections that the businesses that would have been viable 10 years later were not viable then said, yeah, I didn't know what's going to happen to, you know, AI development, maybe someone fix, you know, much is a, you know, the large entry model technology with it. Um, I think you know, these are the reinforcement learning technology model. And then maybe they can harmonize and get something much better, but at the moment, they can't seem to be quite that. So Ed, so you believe that the, you believe that they're, that these models can be error-prone and that will limit the total addressable market of these models. I guess where I would, I think an interesting analogy would be that of like solid driving cars, right? So we know, for example, that Waymo was not perfect, but that and its error is not, is not zero percent. But so, so too are keeping drivers imperfect, right? And so one of the interesting phenomenon we've seen is that for whatever reason, politicians and, and drivers have a, a bias against AI whereby, you know, the, the tolerance threshold so much lower that if there's one big, um, you know, kind of headline about a bad Waymo accident suddenly, you know, the, the interest in, in the technology, you know, go, what wanes significantly? And so what, with your Hindenburg moment, is that kind of what you're saying here that we all know that AI is not perfect. We all know it's a, it's a nascent technology. Um, the AI bulls will say it's going to be getting better over time. This is the worst it'll ever be. I mean, it's kind of hard to argue with that. How much better it will become? We don't know. But you're saying that that the, the, there is a kind of tail risk for the AI thesis around if just one really bad thing happens that could potentially put a pause on AI development. No, I'm, I've been, I'm being a bit more adamant. They know that if given, um, the problems of hallucinations and, and, and I, you know, if there are these people who test models for hallucinations, you know, I know, you know, I'm not, you know,
looked to one report from October of last year and finally the best performance, two percent hallucinations and I think 20th performer was out of it. I think there might have been 20 cents, but I think it seems to say 20. You're not going to, there are certain activities where you cannot tolerate that degree of error and you, you, you, you, you call it. Yeah, I say, I'm, that, well, you, you, you, you knew what I mean. There are certain areas where you can tolerate certain amount of error, right? You, you know, yeah. So I think, I think what that means is that certain things you would not want to give AI. Like, you don't want to make AI in charge of the, the, the nuclear weapons, right? But in the case of say doing R&D and doing research into a completely green field technology where it's like, you know, the alternative is to do nothing. Then I think the bar is much lower, right? So then the question becomes what percentage of economic activity falls to the category one versus category two because that, you know, as I said, will constrain the total addressable market of a technology like this. And what, you know, I guess this is being implied is that, you know, when, when the demand forecasts are being written by AI companies, in, to an extent, baking in both categories and you're saying maybe only one category is actually available in which case the potential demand curve is a little bit less enticing than is currently being pressed by the market. Yeah, or, or put it simply the, the ruling principle of Manlade Park is fake it till you make it. And, um, the, the amount of hype in that, you know, or need, need to say by definition, all these technology maintenance have large doses of hype. And, you know, that's not in many cases have hype over the long run is, you know, it's factored, but there's never really never, ever, ever been as much hype. Um, as we see around AI and Frank, Frank, if you take, you know, you take the, um, efficacy of the amount of hype relative to the proven efficacy of the technology, the, the ratio is just more extreme than anything before. And I think the, the Thomas Edison, um, he, he, um, he, he, he hoped to know the, uh, uh, it can't just above technology before he'd read, fix the problem and it worked out in the end, but, uh, but, you know, and, and, you know, I think what, I think what people, what's happened is, is that in these, you know, speculative markets, we've lived through in recent years, you, the, the, um, we, reality distortion field that, that, that, that Steve Jobs, um, Pope's rising, and then, you know, must take it into the public markets, who Tesla, who almost just, you know, get to do something or bad to achieve something when you, you happen to achieve that, and that in itself can become some extent itself for filling posts in, in most cases, because it gives you the capital to then make the development. But you need everyone is doing it and that, and the theories and the, and this is a huge amount of, uh, of, of great competition. And I, I think that, you know, that just increases the, close back toe of, of, um, of it coming out and that. So I want to like, um, kind of take a flip side of this. So it sounds like on the, you can feel for the interject if you disagree, but it sounds like on the, um, kind of AI investment, um, boom, you are, you know, negative that you kind of see a, a repeat of history, these historical, um, booms and busts, um, in, in the making and, you know, that would generally make you bearish on, you know, I would assume all the companies in the, um, in the investment, um, supply, uh, value chain or, or the particular pockets, um, you know, with that you find to be, you know, areas where you think that the, um, for us, that would be less dim. Um, look, I mean, as to, you know, we all have our own sort of specialities. So no, um, me, it perhaps, it's some people look at markets where the investors or strategists can cover many different bases. I'm not saying I'm solely a capital cycle investor, but if you are a capital cycle investor, you, you, you, you're, you're sort of, it's your principal bank, just that step back whenever you see a surge of investment, um, across many companies. You, you, you capital cycle investor, can, if you, they could rationalize investing in a company that is itself investing a huge amount, providing the, um, industry or sector that they're operating in, uh, it is not investing massively too. But when a whole sector, uh, is plunging in, then, you know, the campus cycle investor, it prefers to step back and, and I, you know, yes, you know, the moment you've all, you've got, got a lot of, uh, the picks and shovels, makers of the, um, or, or, or, or, or, or, or, or, or, been void out, you know, the, for crap, you know, the grand companies and the, corning, you know, lot of the same companies that, um, actually were involved in the, in the TMT boom of now come back. Um, and I, I, I, for, I'm, I own some, you know, copper stock and, and copper, copper is, as you know, all set up benefit, she's, I'm sort of unwitting, I'm at benefit ship, but the reason I invested in that, copper stuff was not because I anticipate the eye thing, but because I thought that, um, like, that, that, that've been under investment in, in copper and, and, so you never watch, this is one of those, you know, very big investment things where everyone really, you know, gets pulled up in it where they like it or not. Right. So you actually wrote a piece, um, recently for, uh, Reuters, um, where you said markets have poor scorecards for spouting AI losers. This is the piece on the anti-bubbles, right? Um, and, and, so maybe you could walk me through this because I think, you know, you talked in this piece about, some cases where obviously the market got ahead of itself, saying, hey, this, they're going to be the long-term winners and they were not, but there are also cases of the market pockets of the market perhaps today, even that, um, or trading kind of at disparate, depressed multiples on this idea that maybe they'll be disrupted by AI. So maybe walk me through this argument, which I think is pretty interesting. Okay. Well, um, first of all, as you may, we used to have discussions about this at GMA that, you know, problems of shorting bubbles, yeah, because you can, you can, even if you're accurate, uh, you can have massive drawdowns, um, and this is probably not worth shorting a bubble, even if you have perfect foresight. Uh, then, and I hadn't, I think at a sort of, um, from a sort of top-down level, I think there is this, I think bubbles do have a sort of crowding out effect. The capital gets drawn into one sector and it gets pulled out of other parts, or other parts of the markets. And we saw that in the, um, in the, again, during the TNT bubble, uh, with what we'll call the old economy stocks, um, the companies that were deemed to be, um, you know, were deemed not be, um, affected by, um, negatively affected by the, uh, arrive of the internet. They were, um, they said, sorry, I'd rephrase that. The old economy stocks were businesses that were deemed not to partake in the, uh, in the new internet economy that were, old economy that was soon back replaced. Now, those old economy stocks, uh, pulled off, and, um, that offered me very good, you know, very good companies were selling cheap multiples, even while the market itself was on a high, uh, all-time, uh, all-time high. Now, and then you know, as you know, value stocks, uh, uh, as a fact, uh, were very depressed, small-cap was very depressed, emerging was very depressed. So, you know, there were, there were a whole load of anti-bubbles in, um, by 2000. And those, those were areas where they offered, you know, really great investments. So, you could make money in the anti-bubbles. And while the Merst Act was losing, in the 80% of its value. And then, I like, in that drew attention, you know, I'm a two, in that same piece to the, um, the excitement over the, you know, energy transition. And if you remember, this, the SPAC boom of 2020-21 was largely around, you know, stuff relating to electric vehicles. And, you know, general, all those sort of LIDAR companies and EVs and, um, and so forth. Um, and, um, but, you know, in, in, in, in 2021, you know, the, the traditional energy stocks, uh, were very beaten up. I think they, you know, they, uh,
energy set to a down to about 2% of the SB 500 from its average level of the range, sort of 8%, 10% waiting and Tesla was worth more than the entire listed North American energy universe. And to me, it didn't take huge amount of analysis to see that the oil companies were going to disappear overnight, that their investments weren't going to be sort of so-called stranded assets, and that EV growth was largely driven by subsidies and that so on. And Ed said that was a really nice anti-bubble, you didn't have to short the spags, but you created a wonderful investment opportunity. I mean, friends, friend of mine, Jonathan Teppo, runs company called Brebet Capital. He was pointing out that there was this company called Garrett Motion that provides the turbos that goes on to internal combustion engines that had a 40% market share, 60% of incremental market share, selling on 7 times PE. I mean, it's in the stock's up 150% over the last year or so. That's an anti-bubble, yeah. And where are the anti-bubbles today? I mean, Teppo shares the same skepticism about agentic AI, thinks that he has stocks, like some car auction business or online travel. He doesn't believe that these online businesses, whether in real estate market or travel, or whether they're going to be disrupted. And he also mentioned the London Stock Exchange Group that not only does, it provides the market for the stock exchange, but also a lot of other financial data that whatever. He doesn't believe that their notes are interrupted or faithfully compromised. And the market, I think market has revised its opinions somewhat, but definitely it took three months ago in the market was, I think sort of overplay, but selling everything, there was a sort of massive, overblown set off. The only company I saw that really has been impacted, a genuinely impacted, was one of the California educational technology companies that provided essay notes for lazy students. And the stock, AI's generally replaced that business stocks down in 95%. I've got no argument with that straightforward. That AI may make one or two errors in a student's essay. But that, we all make mistakes. It's not going to be the end of the world if it does. But you want AI to be booking your ticket to London and then find that it's flying you to Timbuktu, that is a real problem. And unraveling that problem is going to be very costly for a travel company that went down that route. Got it. So you and Tepper believe that a lot of what sounds like software companies or other companies that are selling down 50 plus percent on this idea that they will be disrupted by AI, that those are interesting places to at least look to the extent that you don't want a shorter bubble because as we know that can be quite challenging. So where areas where your investment has been crowded out, I mean, you're saying potentially the perceived losers of the AI disruption, which as you write in your article very well, historically the market has a pretty bad scorecard when it comes to identifying who will actually in the long term the losers, not always the folks who initially sell off. And I mean, it requires a bit of analysis because what people who hold that view and also point out that software as a service companies were trading with a tremendous bubble three or four years ago. And part of their selling off is really just to do with getting back to what was their value. And the other issue is that they have, you know, they love stock options. They pay out most of their earnings to their employees. So there's a business that everything else being equal. You want to be pretty cool. When I last looked, some of those companies were really not, you know, they may have, they may hold off a lot, but they weren't, they weren't, we weren't optically cheap. And I think once you take into base, into account the stock base compensation, they were probably worthy of avoiding. So yeah, I think, you know, look for the anti bubble, but, you know, but, but the stupid time in the analysis. Right. Of course, because there will always, in these cases, also be companies that are truly being disrupted by technology. And those will be zeros, right? You don't want to, you know, but be buying blockbuster into its downfall. Okay. So let's switch gears now from technology to other capital cycles. You know, when we were working together at GMO, I know you were spending a lot of time on, this was in the early 2010s, spending a lot of time on China. So I think this is a really interesting example of a case where, you know, I think the capital cycle did a good, a good job explaining what ultimately happened with China in terms of the fact that, you know, shareholders have not received a good return on their investment in Chinese stocks, despite a pretty robust economic growth. So maybe walk me through that episode and kind of, and then also bring me to the present and where we are now in terms of the capital cycle with China and other emerging markets if you can. I wouldn't say you say investors and, well, despite robust economic growth. I'd say because, because of the growth, because the growth was faster than I knew was, was higher than the returns on, on capital. And then actually the company's the growth had to issue, had to raise more capital. So in fact, actually, if your returns are low and your growth in an environment that a growth is growing, quote, quote, it's actually particularly negative. I think my lesson from China was this, the lesson from China, so I'm, so this is, is, you don't want to, when you're looking at markets, you don't want to look at valuation alone, you want to look at valuation and, you know, returns on capital and the capital cycle. And China had, you know, was the largest investor, you know, went through the greatest investment to ever. And, and they, and, and, and so just, as you say, you know, had to relatively strong economic craved tailed off a bit, you know, over the last few years, still raised strong growth and absolutely miserable returns and, and, and the shareholders were, they're huge, they're partly because China is having tendency to, to add companies to the index at a very high valuation. And then, and then people who bought it at the high valuations, and the index gets diluted by these new issuances and, and, and, and, there's a poor return. I think the capital cycle, you know, has been, the capital cycle, NASA is very well, vindicated there. And as you remember, we did a lot of work on the real estate. And I, you know, while we've indicated it, yeah. I mean, yes and no. And, you know, the, I saw the other day a chart showing real, real Chinese house prices below where they were in, in 2010, and, you know, a lot of those big, you know, we used to be sure some of those Chinese, real estate companies like Evergrande, you know, they, they were gone. They, many of them have gone bust. And it took, it took longer to play out than I expected. But as you know, however long, we've been in this business. You know, you, you might make a sort of fundamentally signed observation and then be, you know, raised by how long it's taken to play out. So, yeah, I, I, I, I'm not for a China-Suggest, they, I knew some people think that, I mean, I do some works, you know, with the marathon asset management. And they, you know, they had machine markets, people think that some of the Chinese real estate developers now, you know, particularly in the, you tear one, two cities are in a relatively good state. And I, I'm not following the Chinese story test not to tell you where we are now. I just from, from 15 years ago, I'd say that our position has largely been indicated. Got it. So here's another fun one.
So this is one of one of your broiders columns entitled "Big Booze" can sweat off its multi-year hangover. I'll let you tell the story, but basically in the COVID boom, people were stuck at home drinking booze. These stocks did well and then following the 2022 unwind, they have since collapsed and price and evaluations have fallen as well. But you and your article from July last year argue that these companies are Lindy. So what does that mean and how are you thinking about these stocks today? So the Lindy effect is a sort of joke. It's interesting. It was a notion that urban legend has derived from a Broadway cafe. And you were someone at the bar saying, "How long do you think this show is going to run for?" And the best is that the show is going to run for as long as the show has run. In other words, the show has been going for two weeks. You know, the show has been going for one night. It will go for one more night than it will place. If it's been going for five years, it'll run another five years. And then it turns out that that's the sort of rule of thumb that was actually turned out to be, "We can be at crit." And what I was just is, it's probably the case for the Spirits companies. I think particularly Spirits because the companies that would beat and up our companies, like Pané, Rico, Campari, De Adjo, Remi, Quantre, and Brandy Sales. Really took off to the pandemic. Because people were drinking and they were speculating. And they said, "When they went hand in hand." And they were starting. And apparently they laid it up that Kringes cabinet. So by the end of the pandemic, there was the space in the Kringes cabinet. They'd been clearly drinking off the Spirits and it says, "You could say that was a stock problem." And then the other issue is the GLP-1s came along with weight loss drugs. And they apparently put people off alcohol. And then there might be an issue that younger generation is taking cash them in rather than Kringes. I did it. But my guess is that these brandy companies and Spirits companies, they've been around for a couple of hundred years and you've got, you know, countries like Endergetting Rich. I didn't really like to play the sort of emerging consumer demand story because it's often what the breakers do. But I just. I think it's all just a single hard one. And one can find the exception. But I think it's a sort of good principle. It was. And where they are now, again, not following it particularly, I saw that the ad show recently stopped picked up because it had been expected results whereas Empire is still a little tired. I like. I particularly like the story of a red remy country where you could. where the company was valued less than the market value of the brandy and its faults. And that sort of reminded me of. there was a story in Germany, German hyperinflation when the Daimler Benz company was worth less than the cars and the factory lots. And I thought that was a good story. I wouldn't surprise me at the GLP ones, you know, if that sort of. it wouldn't surprise me at that. That diminishes somewhat over which years and eventually people will drink down there without gold. And they'll give back to the bottle. That's my. anyhow, that's what I sort of. There's another antibiotic. Well, I guess one thing is that the AGI crowd, they don't like to drink. So maybe that's two sides at the same coin. And maybe it is the anti-bubble. Yeah, I see. So that's probably. Well, if AGI were really to take over, there'll be a lot of idle ads. So they might actually start drinking it, who is? Right, so maybe it's a head against AGI. We have nothing better to do. Since the machines are doing all our work. Okay, so one question I had that's kind of more personal based on my own curiosity is, as you know, my area focuses often on intangible investments, such as an R&D software advertising human capital. As you know, in the US, for example, in 1995, intangible, intangible investment, or a bullet about 12% of GDP. Since then, intangible investment has increased to about 16% of GDP, while intangible investment has fallen to 10%. Over the past couple of decades. So capital cycle theory, of course, have originated many years ago, tends to be more focused on investment in physical capital. And so you talk to it at the energy cycle, emerging markets, AGI data centers. So my question is, is it fair to assume that the capital cycle also applies to intangible capital? And if so, we're some notable examples that we can point to either in the past or today, where we may have seen capital cycles in, you know, mostly or purely intangible assets. Well, I mean capital is capital, isn't it? So I don't think, you know, if we believe in the concept of intangible capital, which I think we probably should do because the reason, you know, is real, is really due with the counting convention. So I mean, if I'm largely to do with my inventions that we don't put, you know, that we tend to expense R and D and we don't tend to put brand values or, we brand values on the book. And unless there has been an acquisition, is that correct? Yeah. And then, yes. So then the question is, can you get a investment in intangible as in, as in any other type of physical, you know, investment? City odds pretty obviously, yes. And probably it, and you might be able to give me some better examples. But I remember that back in the early 1990s, huge excitement when Blacks, 18 and now Blacks, they Smith Klein, and had, you know, this great blockbuster, else drug called Zantac, that encouraged huge amount of investment in, by Big Farmer in R and D, that the cost of, you know, of blockbuster drug development, stored, and over that period, until the blockbuster drugs that they came out with were, you know, not, not, you know, didn't want to live in a decent tunnel on equity. So, you know, I think that's, you know, that's one that comes to mind. I think, can you, can you name it? If you think of other intangible, I mean, I was, as I said, I thought, anything really, anything really, what we're seeing today, in the AI space we've been talking about, you've got, and you've got obviously huge physical capex in the data centers, and then a huge valuation placed on the, on the AI scientists, you know, metting out and, you know, I didn't know how many people for, and my, right, you know, 100 million subscribers, is it there like, well, there's nothing. And, and, you know, that would look to be a case. I mean, there are the AI companies here, the Merrim Morati, when she had, from a chief technology company, or, of Open AI, chief technology officer of Open AI. She left, what a couple of years ago, for my own company, and they raised it, raised my evaluation of 12 billion dollars, even they, she had 30, wasn't going to tell, invest as well, they're going to put that, what the company was going to do. So that, that seems like an intangible, capital boom. I frankly, and then you know, yeah, kind, they get, they get brand valuations. This, this is not so much CapEx, but just brands getting over. I germ, bow in, in the late 1990s, new Buffett, you know, me, he talks a lot of sets. I've got a bit carried away with the lights, Cologne, and Gillette. We started calling them the Inervator Pulse, and they, I do think that, either Cologne or Gillette, so we're attracted to you from out of CapEx, but they definitely,
or CapEx competition, but they definitely, you know, went, you know, their intangibles or brands were definitely overvalued at that time and the likes of, you know, you know, Gillette was eventually swallowed up by Proct and Campbell, but you know, Kukai, Kukai, I mean, had a very poor decade after that. Yeah, I think that's right. You know, obviously, and assets and asset, capital capital, whether it takes the form of a factory or, you know, the IP embedded in an Nvidia GPU, which is, you know, this half the value of the actual data centers. I agree. It's embedded in the value added of the semiconductor supply. Hi, Kai, we've been talking about this software of the service, which might as well draw it at. I mean, I did write a piece back in 2022 about, you know, how these software as a service business, we were, you know, at certain valuations attracting capital in the slaves and civil. I remember one of the capital cycle metrics is when, you know, you know, you're really in favor because someone creates an index and then update the index to prove how well it's historically performed and then you can pretty much guess that from the main deception, the new index, it's going to do poorly. See, I think, yeah, this, you know, the SaaS bubble of 20/20, choose another very good example of an intangible bubble. Another interesting kind of related topic is if you go follow human capital, just talent, where's, you know, the Harvard MBA indicator? Where are all the best and brightest going? Right, it was a big tech in the past cycle. Before that, if you remember, it was, you know, Goldman Sachsett and Finance, right? So in the bubble that kind of peak, you know, 708, everyone wanted to go work for Wall Street until they didn't. And then it was tech. So, you know, maybe there's an interesting element here where it's, you know, the capital cycle has both kind of human capital elements as well as the actual physical accounting capital. Well, well, Harvard, I mean, it's just the, I mean, not just HBS, but the undergraduate, you know, the graduating body, then very, very reliable contrarian indicator. Well, I graduated from Harvard undergrad and went into, to work as a value investor in 2009. So I think, you know, invest at the bottom of the capital cycle. So the good idea of value investing at the time. We've done my part. All right, I got a couple more questions for you Ed. So here's one that I like. So there's this idea in Silicon Valley that's popular today that bubbles may actually be productive, that it may actually be good for the economy long run. There's a book that's been making the rounds called Boom Bubbles and the End of Stagnation by Hobart and Heuber. So the idea is that even if these bubbles form and they eventually end in tears for investors, they're ultimately productive to the extent that they accelerate the development of a genuinely transformative technology. So in the sense, the argument will go even if AI ends up being a bubble, not that everyone there's conceding it, but to the extent it were, it would have still been a good thing to have happened. Do you find this argument at all compelling? We depend on what perspective one's looking at it from. I tend, you know, and I think you do too. We tend to view the wealth from the perspective of an investor, you know, who's trying to maximize his gains, minimize his risk. And I know, you know, from the perspective of society, yeah, if you can bring forward the technology, whether it's in rare ways or cars or aircraft or internet telecommunications, or EVs or batteries or AI, that's all well and good. Sometimes, you know, sometimes it might not get the whole technology might be a sort of dead end, but perhaps not the end of the world. But yes, I think we talked to you. I mentioned the railroads earlier. They've succeeded to come in searches of CapEx, Bafin in the US and UK as properly, I think probably good thing in the end to Bafan columnist. But really just, really disastrous for the investors who partook in them. And so I think that's, you know, you have to bear that in mind. We're under no compulsion to make a loss-making investment for the benefit of society. The other issue is, and as I've already mentioned, investment, blooms tend to lead to a misalocation of capital and over investment. And that tends to slow rather than increase economic growth. And even if the dot-com bubble, because of that fiber optic cable that was laid, mainly you could get Netflix up and running and all of you video comprensing whatever that's all well and good. But actually remember that the downside of the dot-com bust within the market gave down what was the S&P down 40%, so I remember. You know, it required the we didn't require it as a response. The federal reserve slashed interest rates to 1% to fend off deflation and then we got a housing boom, we got a bus. In fact, the upshot, the way I see it is the upshot of the dot-com bust was the cable financial crisis, upshot to the global financial crisis. With low interest rates and so on and so forth, is it collapsed in productivity growth? So we've got the new technology and that's all very well for companies that end up as winners and so on. But actually the very long tail of these bus can be in your big quite sphere. And so I think it's sort of irresponsible to argue that the bubbles are good for snacks. It's very tip, one of the things you see during bubble periods is a sort of light headiness. Hey, you know, my portfolio is up 50% but what does it matter if there's a downside? But of course people don't feel like that when they're nursing sort of 90% loss on losses on yesterday's high-flowers. So this is a big, it's what's going on in the AI space, this big cat-ex boom, as you know, taking place with very weak consumer confidence, they call K-shaped economy and problems happening elsewhere in the financial system, private credit and private equity and really a lot of legacy VC stuff that was badly invested. The temporary here too much about so the whole sort of private and you know, private alternative investment world is pretty, so it's pretty bad place. So I would have thought that if and when this AI boom ends and turns to bus, a whole load of problems will emerge. And the value, I'm as the valuations come down and people just simply won't be saying that. That type of currency is a sort of giddy currency that invariably accompanies the bubble. That's really interesting. So one point you made that that was kind of interesting in particular is this idea that the kind of like long-term consequence of the dot-com bust was you know a fed mindset that led to ultra low interest rates for a long period of time, which you know fed if you were, you know, and this is in your book The Price of Time, you know, kind of was the original sin behind a lot of the speculative excesses that came afterwards. So that you know, something can happen and it looks fine, you can pass it over, but that's just throwing the seeds for the next cycle. Now obviously rates have increased over the past few years, you know, from their COVID lows. Do we think that that the regime has actually changed or you know, there's a fact that we now are seeing, you know, a massive cab X boom in an AI investment suggests that the money never left the system. Well, I mean, I do like to hedge my bets, but I'd say a bit of bet, you know, that I think that I think that the interest rate cycle turned in 2021-22 for long-term yields and and
historically, those interest rates cycles have been to be multi decade, you know, often, that's into 40 years. And if you remember, I could cheer me out as another thing, that we did a lot of work on, you know, which is like, why were our bond models so wrong? 'Cause we always had to talk about mean reversions and what we found is that these, these very long bond cycles. And I always say, we can't, I always say you can't, you can't predict anything about long-term rates 'cause they're not mean reverting, like, they like equities. But, you know, they do go on these very long cycles. And I do think that we are, that we have entered into a prolonged period of an upward trend in long-term rates. However, there was clearly a lot of liquidity left over from that sort of COVID lockdown at quantitative easing sludge, you know, at any one eight trillion dollars of money printed by the World Central Banks. And, you know, a lot of that kind of sort of excess savings, a lot of it was still held on the Fed balance sheets. And that has been drawn down interest rates remain low-redited to nominal GDP growth. And say the question is, what's gonna happen? That interest rate's gonna get up. Or the World GDP going down, or perhaps, you know, possibly the worst, the worst, and GDP goes down and interest rates go up. So, I think there was some liquidity, a lot of liquidity left over from that period. You know, the, it's always difficult to know what's going on in the plumbing of the financial system. But, yeah, there was perhaps more liquidity than I expected left over. And there are, as you know, these, you know, problems in private credit, which three, just the financing arm of private equity that is still by dating away, and I expect that will continue to be the case. And the real estate market, I think in America, it's definitely more of a business, 'cause I, as prices really haven't come down enough to, you know, in response to the shift in interest rates. So, that seems to be, the dark in its interest. I haven't done work on it, but I think it's an interesting place, US, residential estate, 'cause it hasn't been much investment there recently. But, valuation seemed probably too high, relative to interest rate regimes. So, that's, I mean, that's either a threat or an opportunity. So, it's not, I think you still get, sort of middle of life, I'm sorry, good is gonna happen, I'm sorry, bad is gonna happen. I'm not quite sure which. - Fair enough, yeah. Okay, so, I just got one more question for you, which is our standard closing question. What's the one thing you believe about investing that most of your peers would disagree with? - I used to use one area where I would differ from a lot of, you know, a lot of sophisticated investors, I suppose, is that I've always been a bit of a gold bug. And, you know, people, you know, like, you know, our old boss Jeremy Granferman, and, you know, the team had been, he would always say, you know, I don't like gold, he has no difference in that. And, I always, you know, I always, you know, I think I always felt that, I was, really what? Yeah, I always got this atavistic attraction to gold. And, I think that it does, I think I do like gold's hedging aspect. I know it is difficult value, but I like the way that gold is an asset without a liability. And, I think that in a world where equities, you know, taking the US, I've looked overvalued, and Bournem's might be on a 3040, yeah. I would trend in valuations, and as well as, you know, really severe debt problem and having a debt of tax, you know, and I think that that's what it means. I, I, I hold the view that having a decent allocation to gold is a good portfolio position. So, and that, you know, I mean, I, I mean, I have this big rivalry in the last 10 years, actually having gold, you know, having a sort of, actually, gold portfolio, you know, it's been obviously a lot better having bonds, say, I might be, I might be tightening a, sorry, sort of near the end of, near the end of its view, but I, I, I, I'm drawn to gold in a way that the average new, and persons, you know, the average TFA is not. So, I think that's probably the, the one area where I might disagree. Interesting. Well, thank you, Ed. I know I've taken up a lot of your time, so really appreciate you coming on. Good guy, and I'll see you in London soon. See you soon. Thank you for tuning into this episode. If you found this discussion interesting and valuable, please subscribe on your favorite audio platform or on YouTube. You can also follow all the podcasts in the excess returns network at excessforturnspod.com. If you have any feedback or questions, you can contact us at
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