Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. Welcome to the Marin
Speaker 1: Talks Money Market Round Up, where we talk about the
Speaker 1: biggest moves in markets this week and what's driving them.
Speaker 1: I'm Marrin Sumset, web Editor at Large for Bloomberg UK
Speaker 1: Wealth and as ever, I am joined by John Ttepek,
Speaker 1: senior award at Bloomberg and author of the award winning
Speaker 1: money Distilled News. Let me absolutely clear for people who've
Speaker 1: only joined us relatively recently, that I too have many,
Speaker 1: many awards, many.
Speaker 2: Awards, probably more itally.
Speaker 1: Yeah. Anyway, well listen, there's only one topic this week, John,
Speaker 1: and we haven't got long today, so we're just going
Speaker 1: to dive right into it. We are Yolo to Halo, right.
Speaker 2: You to HELLR. This is great. Tell me what those
Speaker 2: we know were your law stands for? But what does
Speaker 2: HALO stand for?
Speaker 1: Okay?
Speaker 2: You always you only live once by? Is heavy assets?
Speaker 1: Heavy assets, low obsolescence? Wish said, stop chucking this stuff
Speaker 1: out at the endless acronyms anway, This one comes from
Speaker 1: JP Morgan.
Speaker 2: I think Halo, doesn't it? I think so now everyone.
Speaker 1: Is claiming it just like everyone. Do you remember when
Speaker 1: we invented the phrase physical bitcoin gold. The next thing
Speaker 1: we knew everyone was using it without any approbutional that's
Speaker 1: what's happening, analyst over at JP Morgan with Halo. So
Speaker 1: what's happening is that people are looking around and going, gosh,
Speaker 1: you know, we're paying an awful lot for hope when
Speaker 1: it comes to things related to AI software companies, et cetera,
Speaker 1: et cetera. We prefer not to pay so much for
Speaker 1: hope anymore. We've prepared birthday for real stuff. So we're
Speaker 1: going to dumple that software and AI related nonsense and
Speaker 1: we're going to buy oh, I don't know, mines metals.
Speaker 1: Any company that can show already invested in its infrastructure
Speaker 1: and that that infrastructure is going to continue to work
Speaker 1: long term. Is that a reasonable summary.
Speaker 2: Yeah, I think that's a reasonable summary. And I think
Speaker 2: it's interesting partly because it's that the market really has
Speaker 2: latched onto this in the last month or so. Because
Speaker 2: first we had AI you know, Anthropic releasing all of
Speaker 2: those software products and really hitting some of the big
Speaker 2: names very very hard. And then this weekend a company
Speaker 2: called Sutrini Research to just do you know, just the
Speaker 2: research notes released sort of this apopcalyptic but basically sci
Speaker 2: fi scenario about how AI could trigger an economic doom spiral.
Speaker 2: And certainly, regardless of whether it actually caused the cell offer,
Speaker 2: if it was something else, it certainly got the blame
Speaker 2: for a significant sale off on Monday. So it sort
Speaker 2: of shows you how jittery everyone is about this.
Speaker 1: I would I suppose it doesn't really matter in the end,
Speaker 1: what sparks the sell off is it? I mean, if
Speaker 1: you have an improvement for a particular group of stocks,
Speaker 1: they're very expensive. In the end, they'll stop being things.
Speaker 1: And it can be triggered by it pretty much anything
Speaker 1: under the sun. And maybe it was triggered by this
Speaker 1: note maybe not. But you know, once you once you
Speaker 1: get once everything becomes more emotional than fact based, then
Speaker 1: this always happens. In the run up to this, we've
Speaker 1: listened to endless stories about AI which are being very positive.
Speaker 1: You know, the spread of AI will increase productivity across
Speaker 1: the board, It will increase everybody's earnings, it will it
Speaker 1: will add to the US dominance of global stock markets
Speaker 1: and the global knowledge economy, et cetera, et cetera. And
Speaker 1: now we find now we find that in factor, AI
Speaker 1: kind of eats itself a little. And so in fact,
Speaker 1: when knowledge goes from being very expensive to as a
Speaker 1: result of the evolution of AI to going to be
Speaker 1: from very expensive to being either completely free or very cheap,
Speaker 1: who wants to be in the knowledge economy. You don't
Speaker 1: want to be in the knowledge economy. You want to
Speaker 1: be in the well, the infrastructure and the real stuff
Speaker 1: economy that backs up the knowledge economy.
Speaker 2: Yeah, and I guess it's nice the thing, because it's
Speaker 2: easier to rather than what play the winners and losers,
Speaker 2: you just go straight for the things that aren't going
Speaker 2: to be affected or it was going to be affected,
Speaker 2: because everyone needs more electricity basically. And that makes a
Speaker 2: lot of sense, I mean, and that's a really good
Speaker 2: point of evaluations because I was looking just before we
Speaker 2: came on, you know, stocks like in UK listed stocks
Speaker 2: like Experience, an l S and relics that all got
Speaker 2: hit hard by the initial kind of software panic. And yeah,
Speaker 2: one of the things she sort of realizes that, I mean,
Speaker 2: they were all trading on pees of you know, high
Speaker 2: thirties and forties and you're you know, they're now down
Speaker 2: sort of like twenties which is more reasonable ish, but
Speaker 2: you know that those were very high multiples. So a
Speaker 2: lot of it is about people going, oh, hold on
Speaker 2: a minute, I'm paying this might be a good company,
Speaker 2: but that is a hell of a lot to be
Speaker 2: paying for it anyway. So yeah, so that point about
Speaker 2: this being an excuse as much as anything else is
Speaker 2: kind of very fair, I think.
Speaker 1: So, John, It's postially about that. It's partially about this
Speaker 1: idea that if you've relied on expensive knowledge to support
Speaker 1: your valuation and now knowledge may not be as valuable
Speaker 1: after all. It's partly that, but it's also about the
Speaker 1: shift from asset light to acid heavy. Right. We've always
Speaker 1: looked at these companies historically AMAS and Google, Meta, etc.
Speaker 1: As being incredibly asset light companies. They don't have to
Speaker 1: spend big money to build an infrastructure to produce their product.
Speaker 1: That's not a thing, and so they've always been very,
Speaker 1: very high cash flow companies. And now they're looking around
Speaker 1: and going, well, actually, these are beginning to look like
Speaker 1: really so asset heavy companies. They've really got to invest
Speaker 1: in energy and power, and you know, there's just a
Speaker 1: lot of money pouring into what comes behind the spread
Speaker 1: of AI. So we've gone from asset light to acid heavier,
Speaker 1: and you don't pay as much for asset heavy companies,
Speaker 1: and you don't pay as much for companies that are
Speaker 1: constantly having to invest as you do for companies that
Speaker 1: are simply cash flow machines.
Speaker 2: Yeah, especially because this is speculative asset investment. Ultimately, you know,
Speaker 2: it's one thing if BP tondre and says, oh, we
Speaker 2: find a lot of oil, and if we spend as
Speaker 2: much and we get the oil, there's them are going
Speaker 2: to make that as much money. But these guys are saying, Okay,
Speaker 2: there's an uncertain amount of AI required and it's going
Speaker 2: to be of uncertain profitability, but we're still going to
Speaker 2: splodge a trilli nod dollars on building the capacity because
Speaker 2: we're pretty sure that it's going to work out at
Speaker 2: some point. So that's you know, that's the sort of
Speaker 2: future that I feel needs quite a high discountry applied
Speaker 2: to it, and I think the market's kind awakened up
Speaker 2: to that. And then I mean, and then there is
Speaker 2: the deeper worry about where's all this money coming from
Speaker 2: and how much of it is in the private market
Speaker 2: rather than the public market. Obviously, that's not so much
Speaker 2: the case for the hyperscalers, but for all the kind
Speaker 2: of little companies that are on the side of this,
Speaker 2: A lot of them are raising money via private credit
Speaker 2: in various other ways, and it's not that clear how
Speaker 2: much of that there is, or where the choke points
Speaker 2: are or where the vulnerabilities are, which is, you know,
Speaker 2: yet another reason to be mildly kind of wary of
Speaker 2: what's going on there.
Speaker 1: Do you think, John, this is also partly about interest rates.
Speaker 2: I think it's very much about interest rates. A lot
Speaker 2: of it is about I guess the market still going
Speaker 2: through this wake up process of having got used to
Speaker 2: being at zero percent interest rates from twenty ten up
Speaker 2: to right up to twenty twenty one, starting to take
Speaker 2: that for granted, and not quite realizing that the normalization
Speaker 2: in twenty twenty two was permanent. We'll not going back
Speaker 2: to zero percent. And I think it's taking a good
Speaker 2: few years for the market to start to really begin
Speaker 2: to acknowledge that and prace it. And actually, I mean
Speaker 2: this is part of the process of pricing that in
Speaker 2: a higher interest rate environment, the Hope stocks, the Eyolo
Speaker 2: stocks just aren't as attractive.
Speaker 1: Yeah, it's just amazing how long this has taken, isn't it.
Speaker 1: I mean, I suppose we. I don't think either of
Speaker 1: us really believed that the transition period, the bit when
Speaker 1: people would go asly interest rates aren't going back to zero,
Speaker 1: They're going to knock around three four percent, and I
Speaker 1: need to change the way I invested in direct result
Speaker 1: of that. I thought that would be a six month process,
Speaker 1: but it's not. It's years.
Speaker 2: I think it's partly I think momentums are really powerful
Speaker 2: fact and not also think that the longer something's going on,
Speaker 2: the harder it is for pure to change the minds.
Speaker 2: I think also it was happening in twenty twenty two,
Speaker 2: but then EI gave everyone an excuse to go back
Speaker 2: to the old way of thinking. And that is interesting
Speaker 2: because I mean, when chat GPT came out, it was cool,
Speaker 2: it could make up a little poor for they and
Speaker 2: stuff like that, but it was very much kind of
Speaker 2: a toy, whereas now it is really pretty impressive what
Speaker 2: it can do. Even as someone who is like as
Speaker 2: I said, not skeptical but hardly an early adopter, I
Speaker 2: can see the value in it. But of course, as
Speaker 2: that's going on and it's evolved, it's alto getting to
Speaker 2: the point where people are going, Okay, I mean, what
Speaker 2: if this destroys all of these businesses that we previously
Speaker 2: thought we're either going to benefit from it or you know,
Speaker 2: use it to you know, leverage there, you know their
Speaker 2: IP or whatever. So no, it is It's been a
Speaker 2: really interesting process, and all I can see is the
Speaker 2: markets just on that efficient compared to what we might
Speaker 2: have thought.
Speaker 1: I know we think they are and they aren't. Now. Listen,
Speaker 1: one more thing, I wanted a point towards. There's a
Speaker 1: little report came to me today from Pamea Laberium about
Speaker 1: the start of the day, and the question is why
Speaker 1: do people invest in expensive stocks? Which I think you
Speaker 1: and I've talked about a lot. Why why do you
Speaker 1: invest in these expensive things? You can see they're expensive
Speaker 1: if you know what happens when you invest in expensive stuff,
Speaker 1: et cetera, et cetera. Anyway, he's written about this. Why
Speaker 1: is it that that people continue to do this? And
Speaker 1: the answer is they like owning expensive stocks because they
Speaker 1: have lottery like payoffs. They are fully aware the stock
Speaker 1: is expensive, but they invest in it anyway because they
Speaker 1: think the share price will go up even further, and
Speaker 1: no amount of data will convince them otherwise.
Speaker 2: How's that a lottery like payoff?
Speaker 1: Well, because every now and then one of them will
Speaker 1: go up a lot more.
Speaker 2: I feel that argument is used for everything. It's used
Speaker 2: for white people invest in in stocks as well, and
Speaker 2: that makes more sense there because to me it's like, well,
Speaker 2: you get a bout of wine and a Thosan chat
Speaker 2: of making any money and deploy can you get shot?
Speaker 2: You know? Otherwise? But that that doesn't sound like a
Speaker 2: good reason for buying.
Speaker 1: So there's the reasons given.
Speaker 2: Perceived safety, yes, safety in numbers, prayerfully.
Speaker 1: Yes, supremacy. I'm buying the best stock stock and please
Speaker 1: see please see my column on that from last week.
Speaker 1: This does not work. And then but the majority of
Speaker 1: people say perceived lottery because you might go up a
Speaker 1: lot more.
Speaker 2: Nice, that's why the market is not efficient. Yeah, I
Speaker 2: was going to read that studying. I'll go and read
Speaker 2: that studying more detail.
Speaker 1: Because I will. I will send it to you. In fact,
Speaker 1: i'll tell you what. I will also pop it onto
Speaker 1: the show notes. I know we always say we do that,
Speaker 1: we often forget, but we're not going to forget today.
Speaker 1: We'll actually do that now, Listen. This was always going
Speaker 1: to be a very short podcast, so I'm going to
Speaker 1: finish it there, but asking one question for you John
Speaker 1: before we close. Based on this whole idea of moving
Speaker 1: from soft stuff to hard stuff, how many different metals
Speaker 1: do you think are required to make one server?
Speaker 2: I'm going to just take a ryandom guess at twelve
Speaker 2: thirty thirty thirty.
Speaker 1: So why would you pay more? Why would you pay
Speaker 1: more for a share in a company that needs desperately
Speaker 1: to have those or the company that, in an environment
Speaker 1: of relative supply shortage, produces those metals.
Speaker 2: I'm trying saying if I could even name sightly metals,
Speaker 2: that's a different challenge.
Speaker 1: I have not got time for you sitting there naming
Speaker 1: all the metals that you learned about in chemistry at
Speaker 1: school today. That's not happening.
Speaker 2: I'll make a great podcast.
Speaker 1: No, it totally wouldn't. But you know, challenge, challenge for listeners.
Speaker 1: Challenge for listeners. John. I'm going to close this now,
Speaker 1: but John is now going to sit here and think
Speaker 1: to himself about thirty metals and we'll do this together. John,
Speaker 1: we got five minutes, but the rest of you once
Speaker 1: I close this think to yourself, how many metals can
Speaker 1: you name? How many metals can you name? It's really
Speaker 1: very important. Thanks for listening to this week's Marin Talks
Speaker 1: Money debrief. If you like us, show, rate, review and subscribe.
Speaker 1: Where have you listened to? Podcast? And keep sending questions
Speaker 1: or comments to Marror Money at Bloomberg dot net. You
Speaker 1: can also follow me at Marinus w on X and
Speaker 1: John at John Underscore step Back. This episode was hosted
Speaker 1: by me Marin sum Set Web. It was produced by
Speaker 1: verses And and Summer Sadi. Now we would be fascinated
Speaker 1: to know how many metals you can name without looking
Speaker 1: it up, So let us know on Twitter where you
Speaker 1: got to, and we will let you know where we
Speaker 1: got to.