Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. Hello and welcome to
Speaker 1: the Money Stuff Podcast. You're a weekly podcast. Where are
Speaker 1: we talking about stuff related to money? I'm Matt Levine
Speaker 1: and I write the Money Stuff column for Bloomberg Opinion.
Speaker 2: And I'm Katie Greifeld, a reporter for Bloomberg News and
Speaker 2: an anchor for Bloomberg Television.
Speaker 1: What are we talking about today, Katie?
Speaker 2: We're going to talk about how the US stock market
Speaker 2: got deep seeked. We're going to talk about that sweet
Speaker 2: Sweet ex debt, and then we're going to talk about trading.
Speaker 3: In the dark.
Speaker 2: Sounds good, deep seek Deep Seek. So I cannot believe.
Speaker 2: I cannot believe that there is a money Stuff from
Speaker 2: June that mentions deep seek because I would say ninety
Speaker 2: seven percent of the people that I talked to on
Speaker 2: Monday hadn't heard of it before this past weekend.
Speaker 1: Where did they hear of it?
Speaker 2: The people I talked to on Monday who hadn't heard
Speaker 2: of it previously, Yeah, they heard about it when the
Speaker 2: app shot up in the app store, Okay, and then
Speaker 2: you had the cell side start writing about it. There
Speaker 2: were a ton of tweets about it over the weekend.
Speaker 2: Not that Twitter is real life, but in some cases
Speaker 2: it kind of is.
Speaker 1: Yeah, Like there's one guy who wrote a long report
Speaker 1: on like his personal website and argues somewhat plausibly that
Speaker 1: he influenced a lot of the investor reaction. It's like
Speaker 1: interesting to see how like investor actions collas, right, because
Speaker 1: like the model was kind of released like at the
Speaker 1: Piniere last week. The catalyst is some combination of people
Speaker 1: getting to think about it over the weekend and like
Speaker 1: it shooting up in the app store, But at some
Speaker 1: point there's like this big shift from like people using
Speaker 1: the app to everyone having existential crisis about it. Nvidia, Yeah,
Speaker 1: this is a digression. Yes, I wrote about it in June.
Speaker 1: I'm prescient. I was like, yeah, this is going to
Speaker 1: be really bad for the future of netin. But I
Speaker 1: do love you know what I read about in June
Speaker 1: is like the founder of deep seek it kind of
Speaker 1: spun out of his quantitative hedge fund, and I love
Speaker 1: that the skill sets of hedge funds and large language
Speaker 1: models are like kind of overlapping, right. These are kind
Speaker 1: of like, you know, using machine learning techniques to predict
Speaker 1: somewhat unpredictable things, whether that's like the next word in
Speaker 1: a sentence, or the stocks that will go up. And
Speaker 1: classically people made billions of dollars, and by people I
Speaker 1: mean like renaissance technologies made billions of dollars, but like
Speaker 1: repurposing like people in the business of like natural language
Speaker 1: generation into predicting stock prices. And it's nice to see
Speaker 1: that come full circle and the people who are using
Speaker 1: machine learning to predict stock prices are now getting back
Speaker 1: into the natural language game and making billions of dollars
Speaker 1: that way.
Speaker 2: Yeah, I mean everything, everything is cyclical in that sense.
Speaker 2: I will say I wish we had talked about it
Speaker 2: on the podcast in June so that I could have
Speaker 2: shared in some of this whole it was so early.
Speaker 2: But in any case, it's fine.
Speaker 1: The thing is not that like deep Seek is an
Speaker 1: AI company in China. The thing is that the market
Speaker 1: lost the trillion dollars of market cap on Monday. I
Speaker 1: don't want to say that the US economy is based
Speaker 1: on like building empowering data centers for AI companies, but
Speaker 1: the projected incremental cash flows to the US economy, like
Speaker 1: a lot of those are like, yes, we're going to
Speaker 1: build a lot of data centers and a lot of
Speaker 1: like power plants to power them, and deep Seek arguably
Speaker 1: people think that it undermines that case, like quite significantly.
Speaker 1: And yeah, if like you thought that all of economic
Speaker 1: growth would come from like AI data centers, then now
Speaker 1: you're like, yeah, the source of economic growth is gone,
Speaker 1: which is a funny thing to think, but.
Speaker 2: Yeah, I know, I think a lot of people actually
Speaker 2: would agree with that logic because you take a look
Speaker 2: at what happened in the bond market, like there was
Speaker 2: this insane bid into bonds on Monday as well, and
Speaker 2: sort of that was bonds being a haven.
Speaker 1: Yeah, I saw Deep Seek is a macro event.
Speaker 2: Yeah. Well one of the most credible reasons I got
Speaker 2: was just because people are worried that this is going
Speaker 2: to shave that incremental bid off of GDP, because there's
Speaker 2: been plenty of risk off events where bonds didn't catch
Speaker 2: a bid, but this was the one thing that spurred
Speaker 2: like this haven bid across the treasury curve, which is
Speaker 2: pretty funny.
Speaker 1: I love AI as a as a subject matter because
Speaker 1: it is so science fictional. And you know, one thing
Speaker 1: people talk about sometimes is whether GDP is like a
Speaker 1: bad index of like human flourishing, right, And so there's
Speaker 1: an argument that like GDP measures understate GDP growth because
Speaker 1: like you're getting all these like hedonic benefits from like
Speaker 1: going on social media or whatever, and that's like captured
Speaker 1: in GDP figures or whatever. The thesis here is something like,
Speaker 1: if we have to build a lot of buildings and
Speaker 1: burn a lot of coal or natural gas to make
Speaker 1: really good AI models, then that's good for GDP. And
Speaker 1: if you can get the same AIA benefits for free,
Speaker 1: then that's bad for GDP. But like that's better, right,
Speaker 1: It's clearly better to have those benefits without burning coal,
Speaker 1: to have them, you know, and burn coal. I wrote
Speaker 1: something like, you know, if you sort of like fully
Speaker 1: believe the deep Seak thesis and that's like this magic
Speaker 1: AI thing that is free, that's clearly better for human flourishing,
Speaker 1: but it's like worse for stock market capitalization because no
Speaker 1: one can make a profit from it.
Speaker 2: And I mean, can we flourish if the stock market
Speaker 2: doesn't go higher? I don't know, Matt, I'm scared to
Speaker 2: find out the answer.
Speaker 1: It's a real question. There's a Simpsons bit where Homer
Speaker 1: has an auto dialer and it calls mister burns and
Speaker 1: it says, hello, friend, would you trade one dollar for
Speaker 1: eternal happiness? And mister Burns, thinking he's talking to a person,
Speaker 1: thanks for when, and says, hmmm.
Speaker 3: One dollar for eternal happiness.
Speaker 1: May be happy with the dollar. I think about this
Speaker 1: all the time, Like I sometimes feel that way too, right,
Speaker 1: Like yeah, if you're a fron k goes down, but
Speaker 1: like all of your future needs will be met by
Speaker 1: like a little robot in your pocket, then you didn't
Speaker 1: need the four own k, but like you want the
Speaker 1: four oh and k.
Speaker 2: That's actually all I could think about on Monday was
Speaker 2: how I will ever financially recover from this trading session?
Speaker 1: Like we did not air, but I.
Speaker 2: Was like, no, I need to get to the podcast.
Speaker 2: You know, the show must go on. So you boldly
Speaker 2: asked the question in a money stuff this week, what
Speaker 2: if this Chinese quant hedge funds that you know then
Speaker 2: went on to develop deep Seek had a bunch of
Speaker 2: InVideo puts and made a bunch of money that way.
Speaker 2: And then friend of the show Bill Ackman tweeted the
Speaker 2: exact same question, which was fun.
Speaker 1: I assume that other people independently came to this idea
Speaker 1: I had several readers emailing about it before I wrote it.
Speaker 2: No, no, no, you were the first one to ever write
Speaker 2: about deep Seek, first one to ever pose the hypothetical.
Speaker 1: Sure, And I should also say that the idea of
Speaker 1: like disruptors funding their business by giving away their product
Speaker 1: for free and shorting incumbents. I learned of it from
Speaker 1: Joe Wisenthal or fellow Bloomberg podcast, like a decade ago.
Speaker 1: He was writing about it, you know, before everyone. But
Speaker 1: in any case, yeah, well it's a really funny idea. Two,
Speaker 1: it has really kind of percolated up. Apparently Howard Nick
Speaker 1: is getting questions about it in Congress. Oh my, whether
Speaker 1: that's there's no evidence for it, but it would be
Speaker 1: very funny if he did it.
Speaker 2: Also, is it illegal? I mean, is it insider trading?
Speaker 1: So here's what I'll say. One, this is not legal advice.
Speaker 1: Two I think in the US it's like clearly fine.
Speaker 1: The way it works in the US is like you
Speaker 1: are allowed to trade on your own information, but you're
Speaker 1: not allowed to misappropriate information from someone else. So like
Speaker 1: if he was buying in Vidia puts in his personal
Speaker 1: account while you know, running deep Seek, then that like
Speaker 1: might look bad depending on exactly what his arrangement was
Speaker 1: with deep Seek. But if like the corporate complex of
Speaker 1: like Deep Seek and the hedge fund was trading on
Speaker 1: deep Seek's own information to make a profit for that complex,
Speaker 1: and it seems fine, Like it seems like you're not
Speaker 1: misappropriating an information and you're really only trading on your
Speaker 1: own knowledge of your own business right and your own
Speaker 1: like extrapolation of what that will mean for other businesses.
Speaker 1: I think it's totally fine. Now. The two caveats that
Speaker 1: are one, I'm not sure that every jurisdiction sees it
Speaker 1: that way. The US law is much more about this
Speaker 1: like sort of misappropriation theory, whereas like in in other
Speaker 1: places it's like more common to just be like a
Speaker 1: fairness focused, like you can't trade on information that the
Speaker 1: market doesn't have. And then two, if you did this,
Speaker 1: people would get mad and they would say, oh, that's
Speaker 1: insider trading. And then you'd say, no, no, it's not inside
Speaker 1: of trading. It's fine. They're like, okay, fine, but it's
Speaker 1: market manipulation and like it's market univation because they'll find
Speaker 1: something you said wrong, right and so here in deep set,
Speaker 1: because of in a lot of controversy about like is
Speaker 1: it really the case that like its training cost was
Speaker 1: as low as it was, or was it like distilling
Speaker 1: models or rather AI companies. You know, you find something
Speaker 1: that you can seize on to be like, oh, this
Speaker 1: is a misrepresentation, and then it's like market mauntivation. You
Speaker 1: were like saying false things to bring down in video stock.
Speaker 1: So it would be a risky thing to do to
Speaker 1: tank in video stuck in such a high profile way
Speaker 1: while learning puts on it, like people would get mad
Speaker 1: and like might find a thing to try you with.
Speaker 1: But like, no, I don't think it's inside her jetty.
Speaker 2: Yeah, well, I mean again, this is all hypothetical. We
Speaker 2: have no idea if he actually did this.
Speaker 1: But I don't think he did. I just like it's fun.
Speaker 1: He should have done it. I would have done it,
Speaker 1: because like the other thing is like they don't like
Speaker 1: I don't know what their business model is, Like public
Speaker 1: reporting is like some combination of he's just you know,
Speaker 1: making money on his hedge fund, or he's doing this
Speaker 1: out of like the goodness of his heart, and like
Speaker 1: I want to wanting to contribute to AI research because
Speaker 1: it's like open source. It's cheap, how are they gonna
Speaker 1: make money? And I like get shortened in video.
Speaker 2: Yeah, I did also want to bring up that the
Speaker 2: narrative around this week has been that basically deep seek
Speaker 2: was able to recreate open ai with six million dollars
Speaker 2: and it's just been fun watching that get picked apart.
Speaker 2: I've spoken to so many invidiables in the past couple
Speaker 2: of days who have made this into a bowl case
Speaker 2: for in video, which I find really interesting. And there
Speaker 2: is a lot of skepticism around the numbers here. And
Speaker 2: one of the news stories that came about is that
Speaker 2: Microsoft and open ai are taking a look at whether
Speaker 2: this group used open AI's API to basically get a
Speaker 2: large amount of data, which would violate open AI's terms
Speaker 2: of service. Because open Ai, as we were reminded this week,
Speaker 2: isn't actually open source. It's closed source, but Metaslama is
Speaker 2: open source.
Speaker 1: Here's how I think about this. There are a lot
Speaker 1: of businesses that have been or like look likely to
Speaker 1: be really badly disrupted by AI. Right, Like there's some
Speaker 1: margin where like if you're an accountant, let's say podcaster, podcaster, Yes,
Speaker 1: if you're a podcaster, they're coming for you. And in
Speaker 1: the next few years, an AI will be able to
Speaker 1: sit here and talk into a microphone. I mean not literally,
Speaker 1: but like we'll be able to generate voice in a
Speaker 1: way that is better than I can do for a
Speaker 1: fraction of my very high price, and therefore I will
Speaker 1: be out of work. Right, And this is true like
Speaker 1: across a range of like sort of knowledge industries, right,
Speaker 1: And so AI is like undercutting a lot of people
Speaker 1: jobs in a way that like increases abundance for like
Speaker 1: the people who want to listen to podcasts or get
Speaker 1: accounting services. But then like undercuts like the earning potential
Speaker 1: of the people who are providing it cheap. AI is
Speaker 1: to ai what AI is to humans. Right, It's like
Speaker 1: open ai is like, ah, we can do your accounting
Speaker 1: for a tenth of the price of accountants and now
Speaker 1: deep things like we can do it for a tenth
Speaker 1: of the price of open ai. It's great. But like
Speaker 1: the other interesting thing is like you know you talk
Speaker 1: about like were they using open AI's APIs to train
Speaker 1: their model to like distill open AI's model, Like get
Speaker 1: a corpus of open ai outputs and you use that
Speaker 1: to train your your model. We use it to like
Speaker 1: to refine the training of your model. That to me
Speaker 1: is a little bit analogous to the complaints that publishers
Speaker 1: have about open ai using their data to train its models. Right.
Speaker 1: Ai synthesizes the output of like all these humans and
Speaker 1: then comes up with a thing that is that they
Speaker 1: can produce that sort of output more cheaply than humans can.
Speaker 1: And they're like, wow, what we were just like learning
Speaker 1: from humans. It's fine, and like you know, deep Seek
Speaker 1: kind of did that to open Ai maybe, like argue, yeah,
Speaker 1: like people, there's a suspicion which I think violence in
Speaker 1: terms of service, but it is like a certain product
Speaker 1: justice to it. Well.
Speaker 2: Deep Seek, for its part, says that it has distilled
Speaker 2: models for R one based on other open source systems,
Speaker 2: not necessarily on open Ai. But again, met Islama is
Speaker 2: open source. It's freely available for use, and I don't know,
Speaker 2: maybe that's not a bad thing. They're all just building
Speaker 2: on each other. That doesn't seem terrible, right.
Speaker 1: It's like like there's this notion that if deep seak
Speaker 1: is like piggybacking on the work of other models, then
Speaker 1: like then somehow the like baircase against like us AI
Speaker 1: infrastructure spending is like weaker, But I'm not sure that's true. Right,
Speaker 1: It's possible that it's just like the answer is that
Speaker 1: you've made it cheaper to scale AI because like you
Speaker 1: can build impressively on prior work and so you don't
Speaker 1: need all those data centers, don't it.
Speaker 2: I am curious what this means for this date of
Speaker 2: CAPEX spending when it comes to all these big tech giants,
Speaker 2: And we do have a lot of tech giants reporting
Speaker 2: this week, and you know it's going to come up
Speaker 2: on the earnings calls, which haven't happened yet as we're
Speaker 2: recording this podcast, but we're like.
Speaker 1: Two days out from like the US government like we're
Speaker 1: gonna spend a trillion dollars on AI Capex.
Speaker 2: Right, It's like you think about last week.
Speaker 1: I don't know, people are saying news driven like you
Speaker 1: could imagine everyone being like, ah, we're just getting out
Speaker 1: all the capex, Like can you imagine a really hard
Speaker 1: pivot in the next week. It just that doesn't seem
Speaker 1: that there's.
Speaker 2: A lot of awkward timing here because you think about Stargate,
Speaker 2: which was announced last week with open AI with soft
Speaker 2: Bank one hundred billion dollars Meta last week announced it
Speaker 2: was boosting its capex to up to sixty five billion dollars.
Speaker 2: Microsoft is spending eighty billion dollars. It's just felt like
Speaker 2: this arms race to see who can spend the most
Speaker 2: money on this and then to have everyone again get
Speaker 2: deep seaked on Monday was as someone with a four
Speaker 2: toh one K brutal but pretty fun to watch.
Speaker 1: I'm sorry this is rude, but it's such a soft
Speaker 1: thanks story. So I think announcing like we're gonna been
Speaker 1: ae hundred billion dollars on data centers like ten minutes before,
Speaker 1: like that becomes an obsolete thesis, Like yeah, that's.
Speaker 3: Like, that's a good story, a good story.
Speaker 1: Speaking of old times traits.
Speaker 2: Man, let's talk about X debt. It seems like it's
Speaker 2: getting a lot sweeter potentially. Well, this is also weird.
Speaker 1: I never know how to interpret.
Speaker 2: This because is this sweetener?
Speaker 1: So X twitter X, the company formerly known as Twitter
Speaker 1: Elion Mask bought it in twenty twenty two, and when
Speaker 1: he signed his deal to buy it, for a variety
Speaker 1: of reasons, it looked like a better deal than it
Speaker 1: turned out to be like months later, and so all
Speaker 1: these banks, led by Morgan Stanley agreed to provide them
Speaker 1: thirteen billion dollars of debt to buy Twitter, and by
Speaker 1: the time that closed, you know, ordinarily like they would
Speaker 1: sell that debt to investors before the deal closed, but
Speaker 1: for a variety of reasons, mainly that he was suing
Speaker 1: to try to stop the deal from closing to the
Speaker 1: last part and so wouldn't help out on the dead cell.
Speaker 1: For a variety of reasons, they didn't sell the debt
Speaker 1: before the deal closed. And by the time the deal closed,
Speaker 1: it looked bad, both because Twitter's business had deteriorated and
Speaker 1: because Elon Musk deteriorated it further, and because he was
Speaker 1: like talking smack about Twitter for the whole time he
Speaker 1: was trying not to buy it, and so like no
Speaker 1: one wanted the debt, they couldn't sell the debt, And
Speaker 1: there were occasional news stories being like they tried to
Speaker 1: sell the debt at like sixty cents on the dollar
Speaker 1: and they couldn't or whatever, like they got bids at six. Yeah,
Speaker 1: so like numbers like sixty cents on the dollar were
Speaker 1: floating around and now they're apparently outloading some of the
Speaker 1: debt and like numbers like ninety to ninety five cents
Speaker 1: on the dollar are floating around so pretty good. That's
Speaker 1: like not necessarily apples to apples, because it's like they're
Speaker 1: varying levels of seniority and it's possible that they couldn't
Speaker 1: sell the worst that at sixty and now they're signing
Speaker 1: the best that at ninety.
Speaker 2: But still so this Xai stake that Twitter has, I mean,
Speaker 2: I have questions. I was already questioning, you know who
Speaker 2: knows on pricing, but is that worth you know, up
Speaker 2: to thirty cents per bond or whatever, and whether it
Speaker 2: still is after of course deep Seek came about on Monday.
Speaker 1: After Elon Musk bought Twitter. The next thing quickly became
Speaker 1: large language models. Like when he signed the deal to
Speaker 1: by Twitter, like no one was talking about open ai
Speaker 1: or whatever. But shortly after the closing, like large language
Speaker 1: models were the thing. And so he started an AI
Speaker 1: company called Xai. It has the same first letter as
Speaker 1: Twitter does now, which is X and it clearly shared
Speaker 1: some resources with x and you know who like made
Speaker 1: enough noise about doing AI out of x that the
Speaker 1: upshot is that Xai is not just owned by him personally,
Speaker 1: and like people who put money into Xai and he's
Speaker 1: raised a lot of money for It's also partly owned
Speaker 1: by x by Twitter, So that company that he bought
Speaker 1: one of its assets is apparently a six billion dollar
Speaker 1: stake in Xai that's measured it it's like most recent evaluation,
Speaker 1: it's like fifty billion dollars. Now maybe that valuation has
Speaker 1: gone way down since Deepsek was released. There's not a
Speaker 1: lot of public market comps for like pure play AI companies,
Speaker 1: so like, who knows what the valuation is of Xai
Speaker 1: or open Ai or anything else. But you know, last
Speaker 1: time we checked, that stake was worth six billion dollars,
Speaker 1: which sure is worth a lot of money to the
Speaker 1: debt because the debt is like thirteen billion dollars, and
Speaker 1: like you know, if they have collateral, then you know
Speaker 1: that's worth you know, forty five cents on the dollar.
Speaker 1: So I think that like there was reporting that X's
Speaker 1: banks were shopping the debt, specifically telling people, hey, you'd
Speaker 1: have a priority claim on all these Xai shares. Isn't
Speaker 1: that nice? And what I wrote about this is like
Speaker 1: it's very hard to do a credit analysis of x
Speaker 1: Twitter because if Twitter doesn't pay interest on its debt,
Speaker 1: like the lenders can foreclose, but like what good does
Speaker 1: that do them? Right, Like Elon Musk can kind of
Speaker 1: trash Twitter on the way out the door, and Twitter
Speaker 1: seems like a hard like seems like a hard company
Speaker 1: to run before Elon Musk bought it, and now it's
Speaker 1: gotten even harder. So it's a company that has a
Speaker 1: lot of potential upside, particularly for Elon Musk, who can
Speaker 1: use it to like get presidents elected. But in terms
Speaker 1: of like downside production for lenders, it's like, I don't
Speaker 1: know whereas like you know, again a week ago, saying
Speaker 1: we own a big stake in an AI company seems
Speaker 1: like really great downside production because one AA companies are valuable.
Speaker 1: Two Elon Musk is like kind of unlikely to walk
Speaker 1: away from an AI company in a way that he
Speaker 1: tried to walk away from Twitter. And three people do
Speaker 1: credit analysis of AA companies where they did where they're like, oh, look,
Speaker 1: it has like all these like Nvidia chips. Even if
Speaker 1: like something goes horribly wrong at this company, those chips
Speaker 1: are super valuable because there's such an AI gold rush,
Speaker 1: So like there's really good collateral here right again, like
Speaker 1: that has been undermined by the events of the last week.
Speaker 1: But it does feel like the Xai stake was pretty
Speaker 1: credit enhancing for the Twitter bonds.
Speaker 2: Yeah, and I mean you say that el Musk is
Speaker 2: less likely to walk away from the Ai company in
Speaker 2: the same way he might be tempted to walk away
Speaker 2: from Twitter. I mean, how confident are you when you
Speaker 2: say that? Because who really knows, Matt.
Speaker 1: Yeah, nobody knows anything. But like Elon Musk is kind
Speaker 1: of always sad, including when he was buying it, that
Speaker 1: Twitter was not a great business decision, but yeah, he
Speaker 1: thought it was important for the future of the world.
Speaker 1: Blah blah, blah blah. And like that, by the way,
Speaker 1: turned out to be right. Like he's had a ton
Speaker 1: of political influence with Twitter without it necessarily making him
Speaker 1: a lot of money. Again a week ago, everyone's like, wow,
Speaker 1: Ai is real gusher of money, right, Like who knows now, right,
Speaker 1: But like, you're right, I'm not saying personally, I think
Speaker 1: there's no chance of him getting bored of Ai, just
Speaker 1: like you know, I think that was a reasonable thing
Speaker 1: for the market to think, are Weekiah.
Speaker 2: Yeah, you know what, it could be more fun than owning.
Speaker 1: Twitter virtually anything.
Speaker 2: I don't know. I mean I'm speaking specifically from Elon
Speaker 2: Musk's shoes perhaps owning TikTok, but that's a yeah, different conversation.
Speaker 1: Yeah, yeah, I would have read that, right, he buys TikTok.
Speaker 1: Can you imagine him doing that separately? Like that'd be
Speaker 1: so rude. It didn't even occur to me because he's
Speaker 1: been like talked about as a potential buyer of TikTok.
Speaker 1: I assumed that he would do that out of the
Speaker 1: vehicle that is X. But I guess there's no law
Speaker 1: saying that. I mean whatever, there are like standard views
Speaker 1: of like corporate you know, fiducie duties and corporate opportunities.
Speaker 1: Were like, yeah, it would be really weird of him
Speaker 1: to buy a competitor. If he owns X, he could
Speaker 1: do that, and then he could on them say.
Speaker 2: Very bold of you to assume there are laws here,
Speaker 2: but yeah, yeah right. No.
Speaker 1: I started by saying there, no, there's no law that
Speaker 1: he can't do it, but of course there is, but
Speaker 1: there's not anyway, if he buys TikTok, the natural thing
Speaker 1: to do would be to have X by TikTok. But
Speaker 1: that doesn't mean he'll do that.
Speaker 2: Yeah, I feel like TikTok is way more valuable than X.
Speaker 2: But what do I know?
Speaker 1: Yeah, but it's like a weird situation, right, because you're
Speaker 1: buying the US operations and you're buying it under the gun, right,
Speaker 1: you'd be righting literally, like Donald Trump is saying to TikTok,
Speaker 1: either you shut down or yourself to my friend, right, like,
Speaker 1: how much leverage do you have to negotiate a price there?
Speaker 2: That's true. Something that was in the main bar story
Speaker 2: about this X debt with the Xai sweetener was just
Speaker 2: on X's annual interest expenses, And I knew that they
Speaker 2: had gone higher, but I didn't appreciate by how much.
Speaker 2: So with this debt that they were saddled with, the
Speaker 2: annual interest expense went from around fifty million dollars to
Speaker 2: well over a billion dollars for X. That is gargantuan.
Speaker 1: Yeah, it's thirteen you know. Well, because they didn't have
Speaker 1: debt before, because they were like, yeah, they were like
Speaker 1: a not particularly lucrative public tech company. They were not
Speaker 1: running with a lot of debt.
Speaker 2: Elon Musbo, you're just a bird app Yeah, yeah, so.
Speaker 1: He bought them with thirteen billion dollars of debt, right,
Speaker 1: like thirteen billion times, you know, eight percent is a
Speaker 1: billion dollars.
Speaker 2: Yeah, I mean you touched on a little bit. Like
Speaker 2: Elon Musk could probably say, I'm good for it. But
Speaker 2: so twitter X theoretically is like barely breaking even.
Speaker 1: I hesitate to speculate, like the wre Ald Street Journal
Speaker 1: report memos from Elon Musk saying that, but then he
Speaker 1: did not he wrote it, so I don't I don't
Speaker 1: even know, man, But like, okay, but right, I mean,
Speaker 1: like the other thing I was thinking about is like
Speaker 1: when Donald Trump was elected, there was a lot of
Speaker 1: writing to the effect of, like, this investment looks a
Speaker 1: lot better for Elon Musk, right because one like twitter
Speaker 1: x might actually be more valuable now because it's now
Speaker 1: like platform with a lot of political power. You can
Speaker 1: probably sell more ads. But two, you know, it's hugely
Speaker 1: increased the value of the rest of his corporate empire,
Speaker 1: right because like he now runs a space company that
Speaker 1: like runs the government, he runs a car company that
Speaker 1: he has all these powers. So the investment looks really
Speaker 1: good for him. Does any of that help the debt?
Speaker 1: I don't know. I think that Elon Musk, being so
Speaker 1: close to the levers of power is probably a small
Speaker 1: negative for lenders.
Speaker 2: M H.
Speaker 1: Banks don't like to lend to politically exposed persons, right
Speaker 1: because it makes you a worse credit, right because like,
Speaker 1: if you end money to Donald Trump and like he
Speaker 1: doesn't pay you, then you for close on his property.
Speaker 1: But you end money to Donald Trump and he becomes
Speaker 1: the president, then like you can't foreclose on him, right,
Speaker 1: So like it makes your credit a little bit worse.
Speaker 1: And I think there's something of that with Elon Musk,
Speaker 1: where like, on the one hand, he's more likely to
Speaker 1: be good for the money now that he's like so
Speaker 1: much richer and his businesses are so much better. But
Speaker 1: on the other hand, if he doesn't want to pay you, like,
Speaker 1: there's not a lot you can do about it. So
Speaker 1: it's a mixed proposition for the lenders.
Speaker 2: I'm gonna slam this laptop shot at two thirty, just
Speaker 2: so you know, no matter what happens, I have a
Speaker 2: horse to ride, I have miles to run in New Jersey.
Speaker 1: Let's talk about darkpools.
Speaker 2: Okay, dark pools. So, according to Zomberg News, most US
Speaker 2: equity trading isn't done publicly anymore. Matt Levine specifically off
Speaker 2: exchange activity is on course to account for a record
Speaker 2: fifty one point eight percent of traded volume in January.
Speaker 2: That would be the fifth monthly record in a row,
Speaker 2: and the third month running that actually when off exchange
Speaker 2: volume was greater than half of all volume. Are you scared?
Speaker 1: I would say I'm scared. But it is like a
Speaker 1: little bit like the index fund tipping point. Right. Off
Speaker 1: exchange volume is sort of to exchanges, what like index
Speaker 1: funds are to active management. Right, It's like you trade
Speaker 1: on the exchange, you produce a public good. You produce information.
Speaker 1: The particular thing you produce is like stock prices, right
Speaker 1: Like when you trade on exchange, like you trade against
Speaker 1: a lit order, and the order book on the exchange
Speaker 1: is public. People can see what the stock is trading for,
Speaker 1: and you're producing information. If you trade off exchange, the
Speaker 1: off exchange mechanism, you know, if you're hedge fund, it's
Speaker 1: called the dark pool. If you're an individual, it's called
Speaker 1: like a like a wholesaler or an internalizer. But the
Speaker 1: off exchange place where you trade is kind of free
Speaker 1: riding on the public exchanges, right, Like they're looking at
Speaker 1: the exchanges for pricing and then they're probably giving you
Speaker 1: a better price. Right, there's probably some reason that you're
Speaker 1: on the off exchange venue, and it's probably that you're
Speaker 1: getting a better price.
Speaker 3: Right.
Speaker 1: If you're a retail trader, like gets pretty straightforward, people
Speaker 1: get mad about it. But like, the idea of payment
Speaker 1: for order flow is that I fregency trading firm doesn't
Speaker 1: take nearly as much risk trading with retail traders as
Speaker 1: they do trading with fancy hedge funds, and so they're
Speaker 1: willing to give you a better price. It's called the
Speaker 1: price improvement. Right. If you're on a dark pool, you're
Speaker 1: an institution looking for a better price than you get
Speaker 1: on the exchange, and you might get that for some
Speaker 1: variety of reasons, one of which is just like the
Speaker 1: fees might be lower, and so you know, you're trading
Speaker 1: in the dark to get a better price, and so
Speaker 1: you're not producing the sort of pubably good byproduct of that,
Speaker 1: which is like making prices for everyone else. And if
Speaker 1: everyone does that then it can get kind of weird.
Speaker 1: The very article about this quoted Larry tab saying that
Speaker 1: the more trading that goes off exchange is the fuel
Speaker 1: orders that are on exchange competing to determine the best price,
Speaker 1: and this means the pricing on and off exchange could
Speaker 1: get worse, right. I think if there's no one publicly trading,
Speaker 1: then like no one knows what the price is, and
Speaker 1: so the off exchange pricing deteriorates. I don't think there's
Speaker 1: any reason to think that fifty percent is any sort
Speaker 1: of magical tipping point, but it's interesting.
Speaker 2: Yeah, and I'm glad you've framed it as a public good.
Speaker 2: It's a public good that we would be trading on exchange,
Speaker 2: But you could get worried about price discovery, maybe not
Speaker 2: at fifty two versus forty eight percent, But it is
Speaker 2: kind of a fun thought exercise to imagine a world
Speaker 2: where you have ninety percent of trades happening in the dark,
Speaker 2: that their prices are based and extrapolated on the ten
Speaker 2: percent that's happening on exchange. I don't know what that
Speaker 2: world looks like.
Speaker 1: But it's the same thought experiment as index ons, Right,
Speaker 1: It's the same thing where people are like, you know,
Speaker 1: if forty fund the stock market is own by indixed funds,
Speaker 1: that's fine, but ninety percent gets weird, right, Like, you know,
Speaker 1: like there's no real way to know what the magic
Speaker 1: number is. But it's the same idea of like there
Speaker 1: is this like informational good and it's efficient for a
Speaker 1: lot of people to free write on it, but at
Speaker 1: some point it becomes a problem.
Speaker 2: Yeah. Well, I think there is an important caveat here.
Speaker 2: And this was mentioned lower down in the Bloomberg News
Speaker 2: article which was written by Catherine Dougherty. It's super good,
Speaker 2: but so you're talking about dark pools when it comes
Speaker 2: to institutional investors in hedge funds, but when it comes
Speaker 2: to retail trading in penny stocks. If you strip out
Speaker 2: penny stocks from this data, according to Jeffries, then off
Speaker 2: exchange trading volume remains below forty percent, which is less scary,
Speaker 2: but it is interesting that it's sort of both sides
Speaker 2: of the spectrum chipping away at on exchange volume. It's
Speaker 2: like you have dark pools over here with all the
Speaker 2: fancy hedge funds, and then you have retail playing in
Speaker 2: penny stocks as well.
Speaker 1: You think of hedge funds as the banks sophisticated investors,
Speaker 1: and they are, but I think if you're a hedge fund,
Speaker 1: you often think of yourself as an innocent victim of
Speaker 1: the public stock markets, Like I think at some time frame,
Speaker 1: like there are particular firms who are like good at
Speaker 1: getting the last penny of price on the stock exchange,
Speaker 1: and that's a particular skill set. Those firms are called
Speaker 1: high frequency traders, right, And like there are a lot
Speaker 1: of hedge funds who are really mad about high percncruit traders,
Speaker 1: who feel like they're being front run by higher concutrators,
Speaker 1: who feel like the public stock markets are an evil
Speaker 1: and predatory place. And you see this in like Michael
Speaker 1: Lewis's book Flashboys, were like big time hedge fund managers,
Speaker 1: like he like goes into their office and they're like,
Speaker 1: look at look at these higherxcy traders. They're fleecing me. Right,
Speaker 1: Like people get really mad and like not like unsophisticated
Speaker 1: retail investors, like sophisticated investment managers whose time frame is
Speaker 1: longer than five seconds, right, and like those people feel
Speaker 1: like they're getting fleeced by the people whose time frame
Speaker 1: is less than five seconds. And so retail institutions are
Speaker 1: in the same boat here where they both feel like
Speaker 1: the public markets are predatory, and so they want to
Speaker 1: find a more protected place where they won't be subject
Speaker 1: to the predators of the public markets. And the more
Speaker 1: that happens, the more the public market is just full
Speaker 1: of predators, right, Like it's just full of the most
Speaker 1: sophisticated trading firms trading against each other and trying to
Speaker 1: make my buck coffee each other, and like that makes
Speaker 1: them less and less appealing for both retail and for
Speaker 1: like a hedge fund that has a you know, fundamental
Speaker 1: investment thesis.
Speaker 2: Yeah. Sorry, I'm still thinking about like the comparison to
Speaker 2: passive versus active, and we did reach that tipping point
Speaker 2: where passive is now the majority of invested assets.
Speaker 1: Yeah, but it's fine. I mean, like people say it's
Speaker 1: not finely people get mad, right, Yeah. I think there's
Speaker 1: a reasonable case that like some aspects of like you know,
Speaker 1: capital allocation efficiency have been undermined by the rise of indexing. Again,
Speaker 1: not because fifty percent was the tipping point, but just
Speaker 1: because it's bigger than it used to be. But so far,
Speaker 1: it seems like there's a lot of competition to find
Speaker 1: the right price for security, and there are a lot
Speaker 1: of hedge funds who make like really quite a lot
Speaker 1: of money trying to make press efficient. So it's not
Speaker 1: obvious that indexing has like ended that. Yeah, you could
Speaker 1: probably tell a similar story for the sort of microstructure
Speaker 1: level of public slock markets, where again, like the trading
Speaker 1: firms that trade in public markets do pretty well, so fine, yeah,
Speaker 1: and also like spreads are tied and everything like that,
Speaker 1: So it's like.
Speaker 2: Yeah, yeah, Well, I don't know if passive will ever
Speaker 2: take up ninety percent of invested assets. And I'm not
Speaker 2: saying that we could get to ninety percent of trading
Speaker 2: happening in the dark, but it does seem I mean,
Speaker 2: taking a look at, you know, the various people that
Speaker 2: are already closet in this piece that obviously this trend
Speaker 2: has been years in the making and now we're we're
Speaker 2: at fifty two percent roughly. Who knows where that goes.
Speaker 2: This is something that the SEC under Gary Gensler did
Speaker 2: try to address and try to push more of that
Speaker 2: trading to the public exchanges. And the wild card here
Speaker 2: in terms of the trajectory of where this goes is
Speaker 2: Paul Atkins. I don't know what his view is. He
Speaker 2: seems like an interesting guy, he seems like a contrarian.
Speaker 2: I don't know where he lies on this, but it'll
Speaker 2: be fun to find out.
Speaker 1: I think some people in the industry would have comments
Speaker 1: about the idea that the gangsler SEC tried to push
Speaker 1: more training in public exchange, Like that's true, but like
Speaker 1: he also tried to like wildly complicate aspects of public
Speaker 1: exchanges and ways that might have made them pust appealing.
Speaker 1: But no, I think, like broadly speaking, that's true. And
Speaker 1: my guess is that in general, there is not a
Speaker 1: ton of incentive for the SEC to do a ton
Speaker 1: of huge market structure overhauls because while no one kind
Speaker 1: of loves us equity market structure, it seems to work fine,
Speaker 1: and any potential change would be very complicated. And in fact,
Speaker 1: the gangster SEC proposed pretty radical changes and like got
Speaker 1: pushed back pretty hard and like didn't end up actually
Speaker 1: doing anything, not doing much in like the very radical
Speaker 1: like auctioning kind of ideas. Yeah, and it's hard for
Speaker 1: me imagine will surely be a very strange SEC being
Speaker 1: like we need to reform darkpool training, but maybe who.
Speaker 2: Knows, who knows, I don't know. I would imagine it's
Speaker 2: not high on the priority list.
Speaker 1: Yes, there is like a weird populist appeal to saying
Speaker 1: We're gonna end payment for order flow and send all
Speaker 1: of your orders to the stock exchange. It's like almost
Speaker 1: certainly bad for retail investors, but like if you say it,
Speaker 1: people are like, oh, yeah, that'll be good for retail investors.
Speaker 1: So there's some populist appeal to that as a platform,
Speaker 1: and this arguably why Gary Yanser tried to do it.
Speaker 1: But you get bogged down very quickly in the weeds,
Speaker 1: and it's hard to actually.
Speaker 3: Do it so well.
Speaker 2: Taking a look at just the ETF filings that are
Speaker 2: coming across, there's a lot of hopeus and dreams that
Speaker 2: Atkins is going to be a huge crypto bole but
Speaker 2: I don't know. We'll see. Well that seems true, but
Speaker 2: does it. I don't know. I remember you think about
Speaker 2: Gary Gensler, People were like, oh my god, he taught
Speaker 2: an MIT course on the blockchain, and then turns out
Speaker 2: he t into like enemy number one for the crypto crowd.
Speaker 1: I just think that, like fail actins has orders from
Speaker 1: the top to be a crypto friendly And I also think,
Speaker 1: you know, you're talking about ETF filings, like you could
Speaker 1: file an ETF for any meume quin in the world,
Speaker 1: and people are people are, but in particular they're filing
Speaker 1: for like trump quin and milaniaquint. Now is the SEC
Speaker 1: going to say, well, these tokens are two subjects to
Speaker 1: manipulation and like don't have a real investment thesis, so
Speaker 1: we can't approve an ETF on them, Like.
Speaker 2: Well, well, actually, are you slamming your lap clop closed? Wait,
Speaker 2: hold on, okay, here we go. Actually to that point,
Speaker 2: there were filings for double leverage Millenia and trump ETFs.
Speaker 2: But they.
Speaker 1: They what that was a joke? What do you mean?
Speaker 1: I mean, like I wish I had filed a double
Speaker 1: leverge of melai ATF as a joke, because like that's
Speaker 1: very funny. But like, imagine I was joking.
Speaker 2: I don't think this.
Speaker 1: Is probably right, but I'm gonna I'm going to just
Speaker 1: choose to believe that the issuer was joking.
Speaker 2: Yeah, well, assuming that they weren't, and I'm pretty sure
Speaker 2: that they weren't joking, they did withdraw the filing.
Speaker 1: And typical it's fine, problem solved.
Speaker 2: No, they definitely weren't joking. Anyway, That suggests they got
Speaker 2: a call from the SEC that said, maybe this is
Speaker 2: too far, so we'll find out where the lines are.
Speaker 1: I am not convinced that in the next four years
Speaker 1: we'll find out where any lines are. Wow, I suspect that,
Speaker 1: Like You'll be like, is the line over there? Like Nope,
Speaker 1: not here.
Speaker 2: You think a lineless world.
Speaker 1: And that was The Money Stuff Podcast.
Speaker 2: I'm Matt Livian and I'm Katie Gresel.
Speaker 1: You can find my work by subscribing to The Money
Speaker 1: Stuff newsletter on Bloomberg dot com.
Speaker 2: And you can find me on Bloomberg TV every day
Speaker 2: on Open Interest between nine to eleven am Eastern.
Speaker 1: We'd love to hear from you. You can send an
Speaker 1: email to Moneypot at Bloomberg dot m ask us a
Speaker 1: question and we might answer it on air.
Speaker 2: You can also subscribe to our show wherever you're listening
Speaker 2: right now and leave us a review. It helps more
Speaker 2: people find the show.
Speaker 1: The Money Stuff Podcast is produced by Anna Maserakis and Moses.
Speaker 2: Ondeng Our theme music was composed by Blake Maples, Brandon
Speaker 2: Francis Munims, Our executive producer, and Stage Bauman is Bloomberg's
Speaker 2: head of Podcasts.
Speaker 1: Thanks for listening to The Money Stuff Podcast. We'll be
Speaker 1: back next week with more stuff