January 31, 2025 • 35 mins
Katie and Matt discuss the DeepSeek shock, AI and GDP, Elon Musk's X buyout debt, trading in the dark and double levered Melaniacoin ETFs.
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Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, Radio News. Hello and welcome to
the Money Stuff Podcast. You're a weekly podcast. Where are
we talking about stuff related to money? I'm Matt Levine
and I write the Money Stuff column for Bloomberg Opinion.
Speaker 2 (00:20):
And I'm Katie Greifeld, a reporter for Bloomberg News and
an anchor for Bloomberg Television.
Speaker 1 (00:25):
What are we talking about today, Katie?
Speaker 2 (00:28):
We're going to talk about how the US stock market
got deep seeked. We're going to talk about that sweet
Sweet ex debt, and then we're going to talk about trading.
Speaker 3 (00:36):
In the dark.
Speaker 2 (00:37):
Sounds good, deep seek Deep Seek. So I cannot believe.
I cannot believe that there is a money Stuff from
June that mentions deep seek because I would say ninety
seven percent of the people that I talked to on
Monday hadn't heard of it before this past weekend.
Speaker 1 (00:58):
Where did they hear of it?
Speaker 2 (01:00):
The people I talked to on Monday who hadn't heard
of it previously, Yeah, they heard about it when the
app shot up in the app store, Okay, and then
you had the cell side start writing about it. There
were a ton of tweets about it over the weekend.
Not that Twitter is real life, but in some cases
it kind of is.
Speaker 1 (01:18):
Yeah, Like there's one guy who wrote a long report
on like his personal website and argues somewhat plausibly that
he influenced a lot of the investor reaction. It's like
interesting to see how like investor actions collas, right, because
like the model was kind of released like at the
Piniere last week. The catalyst is some combination of people
getting to think about it over the weekend and like
it shooting up in the app store, But at some
(01:40):
point there's like this big shift from like people using
the app to everyone having existential crisis about it. Nvidia, Yeah,
this is a digression. Yes, I wrote about it in June.
I'm prescient. I was like, yeah, this is going to
be really bad for the future of netin. But I
do love you know what I read about in June
is like the founder of deep seek it kind of
(02:01):
spun out of his quantitative hedge fund, and I love
that the skill sets of hedge funds and large language
models are like kind of overlapping, right. These are kind
of like, you know, using machine learning techniques to predict
somewhat unpredictable things, whether that's like the next word in
a sentence, or the stocks that will go up. And
(02:23):
classically people made billions of dollars, and by people I
mean like renaissance technologies made billions of dollars, but like
repurposing like people in the business of like natural language
generation into predicting stock prices. And it's nice to see
that come full circle and the people who are using
machine learning to predict stock prices are now getting back
into the natural language game and making billions of dollars
(02:45):
that way.
Speaker 2 (02:46):
Yeah, I mean everything, everything is cyclical in that sense.
I will say I wish we had talked about it
on the podcast in June so that I could have
shared in some of this whole it was so early.
But in any case, it's fine.
Speaker 1 (02:59):
The thing is not that like deep Seek is an
AI company in China. The thing is that the market
lost the trillion dollars of market cap on Monday. I
don't want to say that the US economy is based
on like building empowering data centers for AI companies, but
the projected incremental cash flows to the US economy, like
a lot of those are like, yes, we're going to
build a lot of data centers and a lot of
(03:21):
like power plants to power them, and deep Seek arguably
people think that it undermines that case, like quite significantly.
And yeah, if like you thought that all of economic
growth would come from like AI data centers, then now
you're like, yeah, the source of economic growth is gone,
which is a funny thing to think, but.
Speaker 2 (03:39):
Yeah, I know, I think a lot of people actually
would agree with that logic because you take a look
at what happened in the bond market, like there was
this insane bid into bonds on Monday as well, and
sort of that was bonds being a haven.
Speaker 1 (03:51):
Yeah, I saw Deep Seek is a macro event.
Speaker 2 (03:54):
Yeah. Well one of the most credible reasons I got
was just because people are worried that this is going
to shave that incremental bid off of GDP, because there's
been plenty of risk off events where bonds didn't catch
a bid, but this was the one thing that spurred
like this haven bid across the treasury curve, which is
pretty funny.
Speaker 1 (04:14):
I love AI as a as a subject matter because
it is so science fictional. And you know, one thing
people talk about sometimes is whether GDP is like a
bad index of like human flourishing, right, And so there's
an argument that like GDP measures understate GDP growth because
like you're getting all these like hedonic benefits from like
going on social media or whatever, and that's like captured
(04:36):
in GDP figures or whatever. The thesis here is something like,
if we have to build a lot of buildings and
burn a lot of coal or natural gas to make
really good AI models, then that's good for GDP. And
if you can get the same AIA benefits for free,
then that's bad for GDP. But like that's better, right,
(04:56):
It's clearly better to have those benefits without burning coal,
to have them, you know, and burn coal. I wrote
something like, you know, if you sort of like fully
believe the deep Seak thesis and that's like this magic
AI thing that is free, that's clearly better for human flourishing,
but it's like worse for stock market capitalization because no
one can make a profit from it.
Speaker 2 (05:14):
And I mean, can we flourish if the stock market
doesn't go higher? I don't know, Matt, I'm scared to
find out the answer.
Speaker 1 (05:20):
It's a real question. There's a Simpsons bit where Homer
has an auto dialer and it calls mister burns and
it says, hello, friend, would you trade one dollar for
eternal happiness? And mister Burns, thinking he's talking to a person,
thanks for when, and says, hmmm.
Speaker 3 (05:35):
One dollar for eternal happiness.
Speaker 1 (05:40):
May be happy with the dollar. I think about this
all the time, Like I sometimes feel that way too, right,
Like yeah, if you're a fron k goes down, but
like all of your future needs will be met by
like a little robot in your pocket, then you didn't
need the four own k, but like you want the
four oh and k.
Speaker 2 (05:55):
That's actually all I could think about on Monday was
how I will ever financially recover from this trading session?
Speaker 1 (06:03):
Like we did not air, but I.
Speaker 2 (06:05):
Was like, no, I need to get to the podcast.
You know, the show must go on. So you boldly
asked the question in a money stuff this week, what
if this Chinese quant hedge funds that you know then
went on to develop deep Seek had a bunch of
InVideo puts and made a bunch of money that way.
(06:27):
And then friend of the show Bill Ackman tweeted the
exact same question, which was fun.
Speaker 1 (06:32):
I assume that other people independently came to this idea
I had several readers emailing about it before I wrote it.
Speaker 2 (06:38):
No, no, no, you were the first one to ever write
about deep Seek, first one to ever pose the hypothetical.
Speaker 1 (06:43):
Sure, And I should also say that the idea of
like disruptors funding their business by giving away their product
for free and shorting incumbents. I learned of it from
Joe Wisenthal or fellow Bloomberg podcast, like a decade ago.
He was writing about it, you know, before everyone. But
in any case, yeah, well it's a really funny idea. Two,
it has really kind of percolated up. Apparently Howard Nick
(07:04):
is getting questions about it in Congress. Oh my, whether
that's there's no evidence for it, but it would be
very funny if he did it.
Speaker 2 (07:12):
Also, is it illegal? I mean, is it insider trading?
Speaker 1 (07:17):
So here's what I'll say. One, this is not legal advice.
Two I think in the US it's like clearly fine.
The way it works in the US is like you
are allowed to trade on your own information, but you're
not allowed to misappropriate information from someone else. So like
if he was buying in Vidia puts in his personal
account while you know, running deep Seek, then that like
(07:38):
might look bad depending on exactly what his arrangement was
with deep Seek. But if like the corporate complex of
like Deep Seek and the hedge fund was trading on
deep Seek's own information to make a profit for that complex,
and it seems fine, Like it seems like you're not
misappropriating an information and you're really only trading on your
own knowledge of your own business right and your own
like extrapolation of what that will mean for other businesses.
(08:00):
I think it's totally fine. Now. The two caveats that
are one, I'm not sure that every jurisdiction sees it
that way. The US law is much more about this
like sort of misappropriation theory, whereas like in in other
places it's like more common to just be like a
fairness focused, like you can't trade on information that the
market doesn't have. And then two, if you did this,
people would get mad and they would say, oh, that's
(08:24):
insider trading. And then you'd say, no, no, it's not inside
of trading. It's fine. They're like, okay, fine, but it's
market manipulation and like it's market univation because they'll find
something you said wrong, right and so here in deep set,
because of in a lot of controversy about like is
it really the case that like its training cost was
as low as it was, or was it like distilling
models or rather AI companies. You know, you find something
that you can seize on to be like, oh, this
is a misrepresentation, and then it's like market mauntivation. You
(08:46):
were like saying false things to bring down in video stock.
So it would be a risky thing to do to
tank in video stuck in such a high profile way
while learning puts on it, like people would get mad
and like might find a thing to try you with.
But like, no, I don't think it's inside her jetty.
Speaker 2 (09:02):
Yeah, well, I mean again, this is all hypothetical. We
have no idea if he actually did this.
Speaker 1 (09:07):
But I don't think he did. I just like it's fun.
He should have done it. I would have done it,
because like the other thing is like they don't like
I don't know what their business model is, Like public
reporting is like some combination of he's just you know,
making money on his hedge fund, or he's doing this
out of like the goodness of his heart, and like
I want to wanting to contribute to AI research because
it's like open source. It's cheap, how are they gonna
(09:27):
make money? And I like get shortened in video.
Speaker 2 (09:29):
Yeah, I did also want to bring up that the
narrative around this week has been that basically deep seek
was able to recreate open ai with six million dollars
and it's just been fun watching that get picked apart.
I've spoken to so many invidiables in the past couple
of days who have made this into a bowl case
for in video, which I find really interesting. And there
(09:49):
is a lot of skepticism around the numbers here. And
one of the news stories that came about is that
Microsoft and open ai are taking a look at whether
this group used open AI's API to basically get a
large amount of data, which would violate open AI's terms
of service. Because open Ai, as we were reminded this week,
(10:11):
isn't actually open source. It's closed source, but Metaslama is
open source.
Speaker 1 (10:18):
Here's how I think about this. There are a lot
of businesses that have been or like look likely to
be really badly disrupted by AI. Right, Like there's some
margin where like if you're an accountant, let's say podcaster, podcaster, Yes,
if you're a podcaster, they're coming for you. And in
the next few years, an AI will be able to
(10:39):
sit here and talk into a microphone. I mean not literally,
but like we'll be able to generate voice in a
way that is better than I can do for a
fraction of my very high price, and therefore I will
be out of work. Right, And this is true like
across a range of like sort of knowledge industries, right,
And so AI is like undercutting a lot of people
(11:00):
jobs in a way that like increases abundance for like
the people who want to listen to podcasts or get
accounting services. But then like undercuts like the earning potential
of the people who are providing it cheap. AI is
to ai what AI is to humans. Right, It's like
open ai is like, ah, we can do your accounting
for a tenth of the price of accountants and now
(11:20):
deep things like we can do it for a tenth
of the price of open ai. It's great. But like
the other interesting thing is like you know you talk
about like were they using open AI's APIs to train
their model to like distill open AI's model, Like get
a corpus of open ai outputs and you use that
to train your your model. We use it to like
to refine the training of your model. That to me
is a little bit analogous to the complaints that publishers
(11:44):
have about open ai using their data to train its models. Right.
Ai synthesizes the output of like all these humans and
then comes up with a thing that is that they
can produce that sort of output more cheaply than humans can.
And they're like, wow, what we were just like learning
from humans. It's fine, and like you know, deep Seek
kind of did that to open Ai maybe, like argue, yeah,
(12:05):
like people, there's a suspicion which I think violence in
terms of service, but it is like a certain product
justice to it. Well.
Speaker 2 (12:11):
Deep Seek, for its part, says that it has distilled
models for R one based on other open source systems,
not necessarily on open Ai. But again, met Islama is
open source. It's freely available for use, and I don't know,
maybe that's not a bad thing. They're all just building
on each other. That doesn't seem terrible, right.
Speaker 1 (12:32):
It's like like there's this notion that if deep seak
is like piggybacking on the work of other models, then
like then somehow the like baircase against like us AI
infrastructure spending is like weaker, But I'm not sure that's true. Right,
It's possible that it's just like the answer is that
you've made it cheaper to scale AI because like you
can build impressively on prior work and so you don't
(12:54):
need all those data centers, don't it.
Speaker 2 (12:56):
I am curious what this means for this date of
CAPEX spending when it comes to all these big tech giants,
And we do have a lot of tech giants reporting
this week, and you know it's going to come up
on the earnings calls, which haven't happened yet as we're
recording this podcast, but we're like.
Speaker 1 (13:12):
Two days out from like the US government like we're
gonna spend a trillion dollars on AI Capex.
Speaker 2 (13:16):
Right, It's like you think about last week.
Speaker 1 (13:18):
I don't know, people are saying news driven like you
could imagine everyone being like, ah, we're just getting out
all the capex, Like can you imagine a really hard
pivot in the next week. It just that doesn't seem
that there's.
Speaker 2 (13:28):
A lot of awkward timing here because you think about Stargate,
which was announced last week with open AI with soft
Bank one hundred billion dollars Meta last week announced it
was boosting its capex to up to sixty five billion dollars.
Microsoft is spending eighty billion dollars. It's just felt like
this arms race to see who can spend the most
money on this and then to have everyone again get
(13:50):
deep seaked on Monday was as someone with a four
toh one K brutal but pretty fun to watch.
Speaker 1 (13:58):
I'm sorry this is rude, but it's such a soft
thanks story. So I think announcing like we're gonna been
ae hundred billion dollars on data centers like ten minutes before,
like that becomes an obsolete thesis, Like yeah, that's.
Speaker 3 (14:08):
Like, that's a good story, a good story.
Speaker 1 (14:27):
Speaking of old times traits.
Speaker 2 (14:30):
Man, let's talk about X debt. It seems like it's
getting a lot sweeter potentially. Well, this is also weird.
Speaker 1 (14:36):
I never know how to interpret.
Speaker 2 (14:37):
This because is this sweetener?
Speaker 1 (14:39):
So X twitter X, the company formerly known as Twitter
Elion Mask bought it in twenty twenty two, and when
he signed his deal to buy it, for a variety
of reasons, it looked like a better deal than it
turned out to be like months later, and so all
these banks, led by Morgan Stanley agreed to provide them
thirteen billion dollars of debt to buy Twitter, and by
the time that closed, you know, ordinarily like they would
(15:02):
sell that debt to investors before the deal closed, but
for a variety of reasons, mainly that he was suing
to try to stop the deal from closing to the
last part and so wouldn't help out on the dead cell.
For a variety of reasons, they didn't sell the debt
before the deal closed. And by the time the deal closed,
it looked bad, both because Twitter's business had deteriorated and
because Elon Musk deteriorated it further, and because he was
(15:23):
like talking smack about Twitter for the whole time he
was trying not to buy it, and so like no
one wanted the debt, they couldn't sell the debt, And
there were occasional news stories being like they tried to
sell the debt at like sixty cents on the dollar
and they couldn't or whatever, like they got bids at six. Yeah,
(15:44):
so like numbers like sixty cents on the dollar were
floating around and now they're apparently outloading some of the
debt and like numbers like ninety to ninety five cents
on the dollar are floating around so pretty good. That's
like not necessarily apples to apples, because it's like they're
varying levels of seniority and it's possible that they couldn't
sell the worst that at sixty and now they're signing
the best that at ninety.
Speaker 2 (16:03):
But still so this Xai stake that Twitter has, I mean,
I have questions. I was already questioning, you know who
knows on pricing, but is that worth you know, up
to thirty cents per bond or whatever, and whether it
still is after of course deep Seek came about on Monday.
Speaker 1 (16:20):
After Elon Musk bought Twitter. The next thing quickly became
large language models. Like when he signed the deal to
by Twitter, like no one was talking about open ai
or whatever. But shortly after the closing, like large language
models were the thing. And so he started an AI
company called Xai. It has the same first letter as
Twitter does now, which is X and it clearly shared
(16:41):
some resources with x and you know who like made
enough noise about doing AI out of x that the
upshot is that Xai is not just owned by him personally,
and like people who put money into Xai and he's
raised a lot of money for It's also partly owned
by x by Twitter, So that company that he bought
(17:02):
one of its assets is apparently a six billion dollar
stake in Xai that's measured it it's like most recent evaluation,
it's like fifty billion dollars. Now maybe that valuation has
gone way down since Deepsek was released. There's not a
lot of public market comps for like pure play AI companies,
so like, who knows what the valuation is of Xai
(17:23):
or open Ai or anything else. But you know, last
time we checked, that stake was worth six billion dollars,
which sure is worth a lot of money to the
debt because the debt is like thirteen billion dollars, and
like you know, if they have collateral, then you know
that's worth you know, forty five cents on the dollar.
So I think that like there was reporting that X's
banks were shopping the debt, specifically telling people, hey, you'd
(17:46):
have a priority claim on all these Xai shares. Isn't
that nice? And what I wrote about this is like
it's very hard to do a credit analysis of x
Twitter because if Twitter doesn't pay interest on its debt,
like the lenders can foreclose, but like what good does
that do them? Right, Like Elon Musk can kind of
trash Twitter on the way out the door, and Twitter
(18:07):
seems like a hard like seems like a hard company
to run before Elon Musk bought it, and now it's
gotten even harder. So it's a company that has a
lot of potential upside, particularly for Elon Musk, who can
use it to like get presidents elected. But in terms
of like downside production for lenders, it's like, I don't
know whereas like you know, again a week ago, saying
we own a big stake in an AI company seems
like really great downside production because one AA companies are valuable.
(18:29):
Two Elon Musk is like kind of unlikely to walk
away from an AI company in a way that he
tried to walk away from Twitter. And three people do
credit analysis of AA companies where they did where they're like, oh, look,
it has like all these like Nvidia chips. Even if
like something goes horribly wrong at this company, those chips
are super valuable because there's such an AI gold rush,
So like there's really good collateral here right again, like
(18:50):
that has been undermined by the events of the last week.
But it does feel like the Xai stake was pretty
credit enhancing for the Twitter bonds.
Speaker 2 (18:57):
Yeah, and I mean you say that el Musk is
less likely to walk away from the Ai company in
the same way he might be tempted to walk away
from Twitter. I mean, how confident are you when you
say that? Because who really knows, Matt.
Speaker 1 (19:11):
Yeah, nobody knows anything. But like Elon Musk is kind
of always sad, including when he was buying it, that
Twitter was not a great business decision, but yeah, he
thought it was important for the future of the world.
Blah blah, blah blah. And like that, by the way,
turned out to be right. Like he's had a ton
of political influence with Twitter without it necessarily making him
a lot of money. Again a week ago, everyone's like, wow,
(19:32):
Ai is real gusher of money, right, Like who knows now, right,
But like, you're right, I'm not saying personally, I think
there's no chance of him getting bored of Ai, just
like you know, I think that was a reasonable thing
for the market to think, are Weekiah.
Speaker 2 (19:43):
Yeah, you know what, it could be more fun than owning.
Speaker 1 (19:46):
Twitter virtually anything.
Speaker 2 (19:49):
I don't know. I mean I'm speaking specifically from Elon
Musk's shoes perhaps owning TikTok, but that's a yeah, different conversation.
Speaker 1 (19:58):
Yeah, yeah, I would have read that, right, he buys TikTok.
Can you imagine him doing that separately? Like that'd be
so rude. It didn't even occur to me because he's
been like talked about as a potential buyer of TikTok.
I assumed that he would do that out of the
vehicle that is X. But I guess there's no law
saying that. I mean whatever, there are like standard views
(20:18):
of like corporate you know, fiducie duties and corporate opportunities.
Were like, yeah, it would be really weird of him
to buy a competitor. If he owns X, he could
do that, and then he could on them say.
Speaker 2 (20:29):
Very bold of you to assume there are laws here,
but yeah, yeah right. No.
Speaker 1 (20:34):
I started by saying there, no, there's no law that
he can't do it, but of course there is, but
there's not anyway, if he buys TikTok, the natural thing
to do would be to have X by TikTok. But
that doesn't mean he'll do that.
Speaker 2 (20:48):
Yeah, I feel like TikTok is way more valuable than X.
But what do I know?
Speaker 1 (20:52):
Yeah, but it's like a weird situation, right, because you're
buying the US operations and you're buying it under the gun, right,
you'd be righting literally, like Donald Trump is saying to TikTok,
either you shut down or yourself to my friend, right, like,
how much leverage do you have to negotiate a price there?
Speaker 2 (21:08):
That's true. Something that was in the main bar story
about this X debt with the Xai sweetener was just
on X's annual interest expenses, And I knew that they
had gone higher, but I didn't appreciate by how much.
So with this debt that they were saddled with, the
annual interest expense went from around fifty million dollars to
(21:28):
well over a billion dollars for X. That is gargantuan.
Speaker 1 (21:34):
Yeah, it's thirteen you know. Well, because they didn't have
debt before, because they were like, yeah, they were like
a not particularly lucrative public tech company. They were not
running with a lot of debt.
Speaker 2 (21:44):
Elon Musbo, you're just a bird app Yeah, yeah, so.
Speaker 1 (21:47):
He bought them with thirteen billion dollars of debt, right,
like thirteen billion times, you know, eight percent is a
billion dollars.
Speaker 2 (21:53):
Yeah, I mean you touched on a little bit. Like
Elon Musk could probably say, I'm good for it. But
so twitter X theoretically is like barely breaking even.
Speaker 1 (22:01):
I hesitate to speculate, like the wre Ald Street Journal
report memos from Elon Musk saying that, but then he
did not he wrote it, so I don't I don't
even know, man, But like, okay, but right, I mean,
like the other thing I was thinking about is like
when Donald Trump was elected, there was a lot of
writing to the effect of, like, this investment looks a
(22:23):
lot better for Elon Musk, right because one like twitter
x might actually be more valuable now because it's now
like platform with a lot of political power. You can
probably sell more ads. But two, you know, it's hugely
increased the value of the rest of his corporate empire,
right because like he now runs a space company that
like runs the government, he runs a car company that
(22:44):
he has all these powers. So the investment looks really
good for him. Does any of that help the debt?
I don't know. I think that Elon Musk, being so
close to the levers of power is probably a small
negative for lenders.
Speaker 2 (22:56):
M H.
Speaker 1 (22:57):
Banks don't like to lend to politically exposed persons, right
because it makes you a worse credit, right because like,
if you end money to Donald Trump and like he
doesn't pay you, then you for close on his property.
But you end money to Donald Trump and he becomes
the president, then like you can't foreclose on him, right,
So like it makes your credit a little bit worse.
And I think there's something of that with Elon Musk,
where like, on the one hand, he's more likely to
be good for the money now that he's like so
(23:19):
much richer and his businesses are so much better. But
on the other hand, if he doesn't want to pay you, like,
there's not a lot you can do about it. So
it's a mixed proposition for the lenders.
Speaker 2 (23:43):
I'm gonna slam this laptop shot at two thirty, just
so you know, no matter what happens, I have a
horse to ride, I have miles to run in New Jersey.
Speaker 1 (23:54):
Let's talk about darkpools.
Speaker 2 (23:56):
Okay, dark pools. So, according to Zomberg News, most US
equity trading isn't done publicly anymore. Matt Levine specifically off
exchange activity is on course to account for a record
fifty one point eight percent of traded volume in January.
That would be the fifth monthly record in a row,
(24:17):
and the third month running that actually when off exchange
volume was greater than half of all volume. Are you scared?
Speaker 1 (24:26):
I would say I'm scared. But it is like a
little bit like the index fund tipping point. Right. Off
exchange volume is sort of to exchanges, what like index
funds are to active management. Right, It's like you trade
on the exchange, you produce a public good. You produce information.
The particular thing you produce is like stock prices, right
Like when you trade on exchange, like you trade against
(24:48):
a lit order, and the order book on the exchange
is public. People can see what the stock is trading for,
and you're producing information. If you trade off exchange, the
off exchange mechanism, you know, if you're hedge fund, it's
called the dark pool. If you're an individual, it's called
like a like a wholesaler or an internalizer. But the
off exchange place where you trade is kind of free
(25:09):
riding on the public exchanges, right, Like they're looking at
the exchanges for pricing and then they're probably giving you
a better price. Right, there's probably some reason that you're
on the off exchange venue, and it's probably that you're
getting a better price.
Speaker 3 (25:21):
Right.
Speaker 1 (25:21):
If you're a retail trader, like gets pretty straightforward, people
get mad about it. But like, the idea of payment
for order flow is that I fregency trading firm doesn't
take nearly as much risk trading with retail traders as
they do trading with fancy hedge funds, and so they're
willing to give you a better price. It's called the
price improvement. Right. If you're on a dark pool, you're
an institution looking for a better price than you get
on the exchange, and you might get that for some
(25:44):
variety of reasons, one of which is just like the
fees might be lower, and so you know, you're trading
in the dark to get a better price, and so
you're not producing the sort of pubably good byproduct of that,
which is like making prices for everyone else. And if
everyone does that then it can get kind of weird.
The very article about this quoted Larry tab saying that
(26:06):
the more trading that goes off exchange is the fuel
orders that are on exchange competing to determine the best price,
and this means the pricing on and off exchange could
get worse, right. I think if there's no one publicly trading,
then like no one knows what the price is, and
so the off exchange pricing deteriorates. I don't think there's
any reason to think that fifty percent is any sort
of magical tipping point, but it's interesting.
Speaker 2 (26:28):
Yeah, and I'm glad you've framed it as a public good.
It's a public good that we would be trading on exchange,
But you could get worried about price discovery, maybe not
at fifty two versus forty eight percent, But it is
kind of a fun thought exercise to imagine a world
where you have ninety percent of trades happening in the dark,
that their prices are based and extrapolated on the ten
(26:51):
percent that's happening on exchange. I don't know what that
world looks like.
Speaker 1 (26:55):
But it's the same thought experiment as index ons, Right,
It's the same thing where people are like, you know,
if forty fund the stock market is own by indixed funds,
that's fine, but ninety percent gets weird, right, Like, you know,
like there's no real way to know what the magic
number is. But it's the same idea of like there
is this like informational good and it's efficient for a
lot of people to free write on it, but at
some point it becomes a problem.
Speaker 2 (27:17):
Yeah. Well, I think there is an important caveat here.
And this was mentioned lower down in the Bloomberg News
article which was written by Catherine Dougherty. It's super good,
but so you're talking about dark pools when it comes
to institutional investors in hedge funds, but when it comes
to retail trading in penny stocks. If you strip out
penny stocks from this data, according to Jeffries, then off
(27:41):
exchange trading volume remains below forty percent, which is less scary,
but it is interesting that it's sort of both sides
of the spectrum chipping away at on exchange volume. It's
like you have dark pools over here with all the
fancy hedge funds, and then you have retail playing in
penny stocks as well.
Speaker 1 (27:58):
You think of hedge funds as the banks sophisticated investors,
and they are, but I think if you're a hedge fund,
you often think of yourself as an innocent victim of
the public stock markets, Like I think at some time frame,
like there are particular firms who are like good at
getting the last penny of price on the stock exchange,
(28:21):
and that's a particular skill set. Those firms are called
high frequency traders, right, And like there are a lot
of hedge funds who are really mad about high percncruit traders,
who feel like they're being front run by higher concutrators,
who feel like the public stock markets are an evil
and predatory place. And you see this in like Michael
Lewis's book Flashboys, were like big time hedge fund managers,
like he like goes into their office and they're like,
(28:42):
look at look at these higherxcy traders. They're fleecing me. Right,
Like people get really mad and like not like unsophisticated
retail investors, like sophisticated investment managers whose time frame is
longer than five seconds, right, and like those people feel
like they're getting fleeced by the people whose time frame
is less than five seconds. And so retail institutions are
in the same boat here where they both feel like
the public markets are predatory, and so they want to
(29:04):
find a more protected place where they won't be subject
to the predators of the public markets. And the more
that happens, the more the public market is just full
of predators, right, Like it's just full of the most
sophisticated trading firms trading against each other and trying to
make my buck coffee each other, and like that makes
them less and less appealing for both retail and for
like a hedge fund that has a you know, fundamental
(29:25):
investment thesis.
Speaker 2 (29:27):
Yeah. Sorry, I'm still thinking about like the comparison to
passive versus active, and we did reach that tipping point
where passive is now the majority of invested assets.
Speaker 1 (29:39):
Yeah, but it's fine. I mean, like people say it's
not finely people get mad, right, Yeah. I think there's
a reasonable case that like some aspects of like you know,
capital allocation efficiency have been undermined by the rise of indexing. Again,
not because fifty percent was the tipping point, but just
because it's bigger than it used to be. But so far,
it seems like there's a lot of competition to find
the right price for security, and there are a lot
(30:00):
of hedge funds who make like really quite a lot
of money trying to make press efficient. So it's not
obvious that indexing has like ended that. Yeah, you could
probably tell a similar story for the sort of microstructure
level of public slock markets, where again, like the trading
firms that trade in public markets do pretty well, so fine, yeah,
(30:22):
and also like spreads are tied and everything like that,
So it's like.
Speaker 2 (30:25):
Yeah, yeah, Well, I don't know if passive will ever
take up ninety percent of invested assets. And I'm not
saying that we could get to ninety percent of trading
happening in the dark, but it does seem I mean,
taking a look at, you know, the various people that
are already closet in this piece that obviously this trend
has been years in the making and now we're we're
(30:45):
at fifty two percent roughly. Who knows where that goes.
This is something that the SEC under Gary Gensler did
try to address and try to push more of that
trading to the public exchanges. And the wild card here
in terms of the trajectory of where this goes is
Paul Atkins. I don't know what his view is. He
seems like an interesting guy, he seems like a contrarian.
(31:08):
I don't know where he lies on this, but it'll
be fun to find out.
Speaker 1 (31:12):
I think some people in the industry would have comments
about the idea that the gangsler SEC tried to push
more training in public exchange, Like that's true, but like
he also tried to like wildly complicate aspects of public
exchanges and ways that might have made them pust appealing.
But no, I think, like broadly speaking, that's true. And
my guess is that in general, there is not a
ton of incentive for the SEC to do a ton
(31:34):
of huge market structure overhauls because while no one kind
of loves us equity market structure, it seems to work fine,
and any potential change would be very complicated. And in fact,
the gangster SEC proposed pretty radical changes and like got
pushed back pretty hard and like didn't end up actually
(31:54):
doing anything, not doing much in like the very radical
like auctioning kind of ideas. Yeah, and it's hard for
me imagine will surely be a very strange SEC being
like we need to reform darkpool training, but maybe who.
Speaker 2 (32:07):
Knows, who knows, I don't know. I would imagine it's
not high on the priority list.
Speaker 1 (32:12):
Yes, there is like a weird populist appeal to saying
We're gonna end payment for order flow and send all
of your orders to the stock exchange. It's like almost
certainly bad for retail investors, but like if you say it,
people are like, oh, yeah, that'll be good for retail investors.
So there's some populist appeal to that as a platform,
and this arguably why Gary Yanser tried to do it.
(32:33):
But you get bogged down very quickly in the weeds,
and it's hard to actually.
Speaker 3 (32:36):
Do it so well.
Speaker 2 (32:38):
Taking a look at just the ETF filings that are
coming across, there's a lot of hopeus and dreams that
Atkins is going to be a huge crypto bole but
I don't know. We'll see. Well that seems true, but
does it. I don't know. I remember you think about
Gary Gensler, People were like, oh my god, he taught
an MIT course on the blockchain, and then turns out
(32:59):
he t into like enemy number one for the crypto crowd.
Speaker 1 (33:04):
I just think that, like fail actins has orders from
the top to be a crypto friendly And I also think,
you know, you're talking about ETF filings, like you could
file an ETF for any meume quin in the world,
and people are people are, but in particular they're filing
for like trump quin and milaniaquint. Now is the SEC
(33:26):
going to say, well, these tokens are two subjects to
manipulation and like don't have a real investment thesis, so
we can't approve an ETF on them, Like.
Speaker 2 (33:37):
Well, well, actually, are you slamming your lap clop closed? Wait,
hold on, okay, here we go. Actually to that point,
there were filings for double leverage Millenia and trump ETFs.
But they.
Speaker 1 (33:54):
They what that was a joke? What do you mean?
I mean, like I wish I had filed a double
leverge of melai ATF as a joke, because like that's
very funny. But like, imagine I was joking.
Speaker 2 (34:08):
I don't think this.
Speaker 1 (34:09):
Is probably right, but I'm gonna I'm going to just
choose to believe that the issuer was joking.
Speaker 2 (34:13):
Yeah, well, assuming that they weren't, and I'm pretty sure
that they weren't joking, they did withdraw the filing.
Speaker 1 (34:19):
And typical it's fine, problem solved.
Speaker 2 (34:22):
No, they definitely weren't joking. Anyway, That suggests they got
a call from the SEC that said, maybe this is
too far, so we'll find out where the lines are.
Speaker 1 (34:33):
I am not convinced that in the next four years
we'll find out where any lines are. Wow, I suspect that,
Like You'll be like, is the line over there? Like Nope,
not here.
Speaker 2 (34:41):
You think a lineless world.
Speaker 1 (34:50):
And that was The Money Stuff Podcast.
Speaker 2 (34:51):
I'm Matt Livian and I'm Katie Gresel.
Speaker 1 (34:54):
You can find my work by subscribing to The Money
Stuff newsletter on Bloomberg dot com.
Speaker 2 (34:59):
And you can find me on Bloomberg TV every day
on Open Interest between nine to eleven am Eastern.
Speaker 1 (35:05):
We'd love to hear from you. You can send an
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Speaker 2 (35:11):
You can also subscribe to our show wherever you're listening
right now and leave us a review. It helps more
people find the show.
Speaker 1 (35:17):
The Money Stuff Podcast is produced by Anna Maserakis and Moses.
Speaker 2 (35:20):
Ondeng Our theme music was composed by Blake Maples, Brandon
Francis Munims, Our executive producer, and Stage Bauman is Bloomberg's
head of Podcasts.
Speaker 1 (35:28):
Thanks for listening to The Money Stuff Podcast. We'll be
back next week with more stuff
Bloomberg Audio Studios, Podcasts, Radio News. Hello and welcome to
the Money Stuff Podcast. You're a weekly podcast. Where are
we talking about stuff related to money? I'm Matt Levine
and I write the Money Stuff column for Bloomberg Opinion.
Speaker 2 (00:20):
And I'm Katie Greifeld, a reporter for Bloomberg News and
an anchor for Bloomberg Television.
Speaker 1 (00:25):
What are we talking about today, Katie?
Speaker 2 (00:28):
We're going to talk about how the US stock market
got deep seeked. We're going to talk about that sweet
Sweet ex debt, and then we're going to talk about trading.
Speaker 3 (00:36):
In the dark.
Speaker 2 (00:37):
Sounds good, deep seek Deep Seek. So I cannot believe.
I cannot believe that there is a money Stuff from
June that mentions deep seek because I would say ninety
seven percent of the people that I talked to on
Monday hadn't heard of it before this past weekend.
Speaker 1 (00:58):
Where did they hear of it?
Speaker 2 (01:00):
The people I talked to on Monday who hadn't heard
of it previously, Yeah, they heard about it when the
app shot up in the app store, Okay, and then
you had the cell side start writing about it. There
were a ton of tweets about it over the weekend.
Not that Twitter is real life, but in some cases
it kind of is.
Speaker 1 (01:18):
Yeah, Like there's one guy who wrote a long report
on like his personal website and argues somewhat plausibly that
he influenced a lot of the investor reaction. It's like
interesting to see how like investor actions collas, right, because
like the model was kind of released like at the
Piniere last week. The catalyst is some combination of people
getting to think about it over the weekend and like
it shooting up in the app store, But at some
(01:40):
point there's like this big shift from like people using
the app to everyone having existential crisis about it. Nvidia, Yeah,
this is a digression. Yes, I wrote about it in June.
I'm prescient. I was like, yeah, this is going to
be really bad for the future of netin. But I
do love you know what I read about in June
is like the founder of deep seek it kind of
(02:01):
spun out of his quantitative hedge fund, and I love
that the skill sets of hedge funds and large language
models are like kind of overlapping, right. These are kind
of like, you know, using machine learning techniques to predict
somewhat unpredictable things, whether that's like the next word in
a sentence, or the stocks that will go up. And
(02:23):
classically people made billions of dollars, and by people I
mean like renaissance technologies made billions of dollars, but like
repurposing like people in the business of like natural language
generation into predicting stock prices. And it's nice to see
that come full circle and the people who are using
machine learning to predict stock prices are now getting back
into the natural language game and making billions of dollars
(02:45):
that way.
Speaker 2 (02:46):
Yeah, I mean everything, everything is cyclical in that sense.
I will say I wish we had talked about it
on the podcast in June so that I could have
shared in some of this whole it was so early.
But in any case, it's fine.
Speaker 1 (02:59):
The thing is not that like deep Seek is an
AI company in China. The thing is that the market
lost the trillion dollars of market cap on Monday. I
don't want to say that the US economy is based
on like building empowering data centers for AI companies, but
the projected incremental cash flows to the US economy, like
a lot of those are like, yes, we're going to
build a lot of data centers and a lot of
(03:21):
like power plants to power them, and deep Seek arguably
people think that it undermines that case, like quite significantly.
And yeah, if like you thought that all of economic
growth would come from like AI data centers, then now
you're like, yeah, the source of economic growth is gone,
which is a funny thing to think, but.
Speaker 2 (03:39):
Yeah, I know, I think a lot of people actually
would agree with that logic because you take a look
at what happened in the bond market, like there was
this insane bid into bonds on Monday as well, and
sort of that was bonds being a haven.
Speaker 1 (03:51):
Yeah, I saw Deep Seek is a macro event.
Speaker 2 (03:54):
Yeah. Well one of the most credible reasons I got
was just because people are worried that this is going
to shave that incremental bid off of GDP, because there's
been plenty of risk off events where bonds didn't catch
a bid, but this was the one thing that spurred
like this haven bid across the treasury curve, which is
pretty funny.
Speaker 1 (04:14):
I love AI as a as a subject matter because
it is so science fictional. And you know, one thing
people talk about sometimes is whether GDP is like a
bad index of like human flourishing, right, And so there's
an argument that like GDP measures understate GDP growth because
like you're getting all these like hedonic benefits from like
going on social media or whatever, and that's like captured
(04:36):
in GDP figures or whatever. The thesis here is something like,
if we have to build a lot of buildings and
burn a lot of coal or natural gas to make
really good AI models, then that's good for GDP. And
if you can get the same AIA benefits for free,
then that's bad for GDP. But like that's better, right,
(04:56):
It's clearly better to have those benefits without burning coal,
to have them, you know, and burn coal. I wrote
something like, you know, if you sort of like fully
believe the deep Seak thesis and that's like this magic
AI thing that is free, that's clearly better for human flourishing,
but it's like worse for stock market capitalization because no
one can make a profit from it.
Speaker 2 (05:14):
And I mean, can we flourish if the stock market
doesn't go higher? I don't know, Matt, I'm scared to
find out the answer.
Speaker 1 (05:20):
It's a real question. There's a Simpsons bit where Homer
has an auto dialer and it calls mister burns and
it says, hello, friend, would you trade one dollar for
eternal happiness? And mister Burns, thinking he's talking to a person,
thanks for when, and says, hmmm.
Speaker 3 (05:35):
One dollar for eternal happiness.
Speaker 1 (05:40):
May be happy with the dollar. I think about this
all the time, Like I sometimes feel that way too, right,
Like yeah, if you're a fron k goes down, but
like all of your future needs will be met by
like a little robot in your pocket, then you didn't
need the four own k, but like you want the
four oh and k.
Speaker 2 (05:55):
That's actually all I could think about on Monday was
how I will ever financially recover from this trading session?
Speaker 1 (06:03):
Like we did not air, but I.
Speaker 2 (06:05):
Was like, no, I need to get to the podcast.
You know, the show must go on. So you boldly
asked the question in a money stuff this week, what
if this Chinese quant hedge funds that you know then
went on to develop deep Seek had a bunch of
InVideo puts and made a bunch of money that way.
(06:27):
And then friend of the show Bill Ackman tweeted the
exact same question, which was fun.
Speaker 1 (06:32):
I assume that other people independently came to this idea
I had several readers emailing about it before I wrote it.
Speaker 2 (06:38):
No, no, no, you were the first one to ever write
about deep Seek, first one to ever pose the hypothetical.
Speaker 1 (06:43):
Sure, And I should also say that the idea of
like disruptors funding their business by giving away their product
for free and shorting incumbents. I learned of it from
Joe Wisenthal or fellow Bloomberg podcast, like a decade ago.
He was writing about it, you know, before everyone. But
in any case, yeah, well it's a really funny idea. Two,
it has really kind of percolated up. Apparently Howard Nick
(07:04):
is getting questions about it in Congress. Oh my, whether
that's there's no evidence for it, but it would be
very funny if he did it.
Speaker 2 (07:12):
Also, is it illegal? I mean, is it insider trading?
Speaker 1 (07:17):
So here's what I'll say. One, this is not legal advice.
Two I think in the US it's like clearly fine.
The way it works in the US is like you
are allowed to trade on your own information, but you're
not allowed to misappropriate information from someone else. So like
if he was buying in Vidia puts in his personal
account while you know, running deep Seek, then that like
(07:38):
might look bad depending on exactly what his arrangement was
with deep Seek. But if like the corporate complex of
like Deep Seek and the hedge fund was trading on
deep Seek's own information to make a profit for that complex,
and it seems fine, Like it seems like you're not
misappropriating an information and you're really only trading on your
own knowledge of your own business right and your own
like extrapolation of what that will mean for other businesses.
(08:00):
I think it's totally fine. Now. The two caveats that
are one, I'm not sure that every jurisdiction sees it
that way. The US law is much more about this
like sort of misappropriation theory, whereas like in in other
places it's like more common to just be like a
fairness focused, like you can't trade on information that the
market doesn't have. And then two, if you did this,
people would get mad and they would say, oh, that's
(08:24):
insider trading. And then you'd say, no, no, it's not inside
of trading. It's fine. They're like, okay, fine, but it's
market manipulation and like it's market univation because they'll find
something you said wrong, right and so here in deep set,
because of in a lot of controversy about like is
it really the case that like its training cost was
as low as it was, or was it like distilling
models or rather AI companies. You know, you find something
that you can seize on to be like, oh, this
is a misrepresentation, and then it's like market mauntivation. You
(08:46):
were like saying false things to bring down in video stock.
So it would be a risky thing to do to
tank in video stuck in such a high profile way
while learning puts on it, like people would get mad
and like might find a thing to try you with.
But like, no, I don't think it's inside her jetty.
Speaker 2 (09:02):
Yeah, well, I mean again, this is all hypothetical. We
have no idea if he actually did this.
Speaker 1 (09:07):
But I don't think he did. I just like it's fun.
He should have done it. I would have done it,
because like the other thing is like they don't like
I don't know what their business model is, Like public
reporting is like some combination of he's just you know,
making money on his hedge fund, or he's doing this
out of like the goodness of his heart, and like
I want to wanting to contribute to AI research because
it's like open source. It's cheap, how are they gonna
(09:27):
make money? And I like get shortened in video.
Speaker 2 (09:29):
Yeah, I did also want to bring up that the
narrative around this week has been that basically deep seek
was able to recreate open ai with six million dollars
and it's just been fun watching that get picked apart.
I've spoken to so many invidiables in the past couple
of days who have made this into a bowl case
for in video, which I find really interesting. And there
(09:49):
is a lot of skepticism around the numbers here. And
one of the news stories that came about is that
Microsoft and open ai are taking a look at whether
this group used open AI's API to basically get a
large amount of data, which would violate open AI's terms
of service. Because open Ai, as we were reminded this week,
(10:11):
isn't actually open source. It's closed source, but Metaslama is
open source.
Speaker 1 (10:18):
Here's how I think about this. There are a lot
of businesses that have been or like look likely to
be really badly disrupted by AI. Right, Like there's some
margin where like if you're an accountant, let's say podcaster, podcaster, Yes,
if you're a podcaster, they're coming for you. And in
the next few years, an AI will be able to
(10:39):
sit here and talk into a microphone. I mean not literally,
but like we'll be able to generate voice in a
way that is better than I can do for a
fraction of my very high price, and therefore I will
be out of work. Right, And this is true like
across a range of like sort of knowledge industries, right,
And so AI is like undercutting a lot of people
(11:00):
jobs in a way that like increases abundance for like
the people who want to listen to podcasts or get
accounting services. But then like undercuts like the earning potential
of the people who are providing it cheap. AI is
to ai what AI is to humans. Right, It's like
open ai is like, ah, we can do your accounting
for a tenth of the price of accountants and now
(11:20):
deep things like we can do it for a tenth
of the price of open ai. It's great. But like
the other interesting thing is like you know you talk
about like were they using open AI's APIs to train
their model to like distill open AI's model, Like get
a corpus of open ai outputs and you use that
to train your your model. We use it to like
to refine the training of your model. That to me
is a little bit analogous to the complaints that publishers
(11:44):
have about open ai using their data to train its models. Right.
Ai synthesizes the output of like all these humans and
then comes up with a thing that is that they
can produce that sort of output more cheaply than humans can.
And they're like, wow, what we were just like learning
from humans. It's fine, and like you know, deep Seek
kind of did that to open Ai maybe, like argue, yeah,
(12:05):
like people, there's a suspicion which I think violence in
terms of service, but it is like a certain product
justice to it. Well.
Speaker 2 (12:11):
Deep Seek, for its part, says that it has distilled
models for R one based on other open source systems,
not necessarily on open Ai. But again, met Islama is
open source. It's freely available for use, and I don't know,
maybe that's not a bad thing. They're all just building
on each other. That doesn't seem terrible, right.
Speaker 1 (12:32):
It's like like there's this notion that if deep seak
is like piggybacking on the work of other models, then
like then somehow the like baircase against like us AI
infrastructure spending is like weaker, But I'm not sure that's true. Right,
It's possible that it's just like the answer is that
you've made it cheaper to scale AI because like you
can build impressively on prior work and so you don't
(12:54):
need all those data centers, don't it.
Speaker 2 (12:56):
I am curious what this means for this date of
CAPEX spending when it comes to all these big tech giants,
And we do have a lot of tech giants reporting
this week, and you know it's going to come up
on the earnings calls, which haven't happened yet as we're
recording this podcast, but we're like.
Speaker 1 (13:12):
Two days out from like the US government like we're
gonna spend a trillion dollars on AI Capex.
Speaker 2 (13:16):
Right, It's like you think about last week.
Speaker 1 (13:18):
I don't know, people are saying news driven like you
could imagine everyone being like, ah, we're just getting out
all the capex, Like can you imagine a really hard
pivot in the next week. It just that doesn't seem
that there's.
Speaker 2 (13:28):
A lot of awkward timing here because you think about Stargate,
which was announced last week with open AI with soft
Bank one hundred billion dollars Meta last week announced it
was boosting its capex to up to sixty five billion dollars.
Microsoft is spending eighty billion dollars. It's just felt like
this arms race to see who can spend the most
money on this and then to have everyone again get
(13:50):
deep seaked on Monday was as someone with a four
toh one K brutal but pretty fun to watch.
Speaker 1 (13:58):
I'm sorry this is rude, but it's such a soft
thanks story. So I think announcing like we're gonna been
ae hundred billion dollars on data centers like ten minutes before,
like that becomes an obsolete thesis, Like yeah, that's.
Speaker 3 (14:08):
Like, that's a good story, a good story.
Speaker 1 (14:27):
Speaking of old times traits.
Speaker 2 (14:30):
Man, let's talk about X debt. It seems like it's
getting a lot sweeter potentially. Well, this is also weird.
Speaker 1 (14:36):
I never know how to interpret.
Speaker 2 (14:37):
This because is this sweetener?
Speaker 1 (14:39):
So X twitter X, the company formerly known as Twitter
Elion Mask bought it in twenty twenty two, and when
he signed his deal to buy it, for a variety
of reasons, it looked like a better deal than it
turned out to be like months later, and so all
these banks, led by Morgan Stanley agreed to provide them
thirteen billion dollars of debt to buy Twitter, and by
the time that closed, you know, ordinarily like they would
(15:02):
sell that debt to investors before the deal closed, but
for a variety of reasons, mainly that he was suing
to try to stop the deal from closing to the
last part and so wouldn't help out on the dead cell.
For a variety of reasons, they didn't sell the debt
before the deal closed. And by the time the deal closed,
it looked bad, both because Twitter's business had deteriorated and
because Elon Musk deteriorated it further, and because he was
(15:23):
like talking smack about Twitter for the whole time he
was trying not to buy it, and so like no
one wanted the debt, they couldn't sell the debt, And
there were occasional news stories being like they tried to
sell the debt at like sixty cents on the dollar
and they couldn't or whatever, like they got bids at six. Yeah,
(15:44):
so like numbers like sixty cents on the dollar were
floating around and now they're apparently outloading some of the
debt and like numbers like ninety to ninety five cents
on the dollar are floating around so pretty good. That's
like not necessarily apples to apples, because it's like they're
varying levels of seniority and it's possible that they couldn't
sell the worst that at sixty and now they're signing
the best that at ninety.
Speaker 2 (16:03):
But still so this Xai stake that Twitter has, I mean,
I have questions. I was already questioning, you know who
knows on pricing, but is that worth you know, up
to thirty cents per bond or whatever, and whether it
still is after of course deep Seek came about on Monday.
Speaker 1 (16:20):
After Elon Musk bought Twitter. The next thing quickly became
large language models. Like when he signed the deal to
by Twitter, like no one was talking about open ai
or whatever. But shortly after the closing, like large language
models were the thing. And so he started an AI
company called Xai. It has the same first letter as
Twitter does now, which is X and it clearly shared
(16:41):
some resources with x and you know who like made
enough noise about doing AI out of x that the
upshot is that Xai is not just owned by him personally,
and like people who put money into Xai and he's
raised a lot of money for It's also partly owned
by x by Twitter, So that company that he bought
(17:02):
one of its assets is apparently a six billion dollar
stake in Xai that's measured it it's like most recent evaluation,
it's like fifty billion dollars. Now maybe that valuation has
gone way down since Deepsek was released. There's not a
lot of public market comps for like pure play AI companies,
so like, who knows what the valuation is of Xai
(17:23):
or open Ai or anything else. But you know, last
time we checked, that stake was worth six billion dollars,
which sure is worth a lot of money to the
debt because the debt is like thirteen billion dollars, and
like you know, if they have collateral, then you know
that's worth you know, forty five cents on the dollar.
So I think that like there was reporting that X's
banks were shopping the debt, specifically telling people, hey, you'd
(17:46):
have a priority claim on all these Xai shares. Isn't
that nice? And what I wrote about this is like
it's very hard to do a credit analysis of x
Twitter because if Twitter doesn't pay interest on its debt,
like the lenders can foreclose, but like what good does
that do them? Right, Like Elon Musk can kind of
trash Twitter on the way out the door, and Twitter
(18:07):
seems like a hard like seems like a hard company
to run before Elon Musk bought it, and now it's
gotten even harder. So it's a company that has a
lot of potential upside, particularly for Elon Musk, who can
use it to like get presidents elected. But in terms
of like downside production for lenders, it's like, I don't
know whereas like you know, again a week ago, saying
we own a big stake in an AI company seems
like really great downside production because one AA companies are valuable.
(18:29):
Two Elon Musk is like kind of unlikely to walk
away from an AI company in a way that he
tried to walk away from Twitter. And three people do
credit analysis of AA companies where they did where they're like, oh, look,
it has like all these like Nvidia chips. Even if
like something goes horribly wrong at this company, those chips
are super valuable because there's such an AI gold rush,
So like there's really good collateral here right again, like
(18:50):
that has been undermined by the events of the last week.
But it does feel like the Xai stake was pretty
credit enhancing for the Twitter bonds.
Speaker 2 (18:57):
Yeah, and I mean you say that el Musk is
less likely to walk away from the Ai company in
the same way he might be tempted to walk away
from Twitter. I mean, how confident are you when you
say that? Because who really knows, Matt.
Speaker 1 (19:11):
Yeah, nobody knows anything. But like Elon Musk is kind
of always sad, including when he was buying it, that
Twitter was not a great business decision, but yeah, he
thought it was important for the future of the world.
Blah blah, blah blah. And like that, by the way,
turned out to be right. Like he's had a ton
of political influence with Twitter without it necessarily making him
a lot of money. Again a week ago, everyone's like, wow,
(19:32):
Ai is real gusher of money, right, Like who knows now, right,
But like, you're right, I'm not saying personally, I think
there's no chance of him getting bored of Ai, just
like you know, I think that was a reasonable thing
for the market to think, are Weekiah.
Speaker 2 (19:43):
Yeah, you know what, it could be more fun than owning.
Speaker 1 (19:46):
Twitter virtually anything.
Speaker 2 (19:49):
I don't know. I mean I'm speaking specifically from Elon
Musk's shoes perhaps owning TikTok, but that's a yeah, different conversation.
Speaker 1 (19:58):
Yeah, yeah, I would have read that, right, he buys TikTok.
Can you imagine him doing that separately? Like that'd be
so rude. It didn't even occur to me because he's
been like talked about as a potential buyer of TikTok.
I assumed that he would do that out of the
vehicle that is X. But I guess there's no law
saying that. I mean whatever, there are like standard views
(20:18):
of like corporate you know, fiducie duties and corporate opportunities.
Were like, yeah, it would be really weird of him
to buy a competitor. If he owns X, he could
do that, and then he could on them say.
Speaker 2 (20:29):
Very bold of you to assume there are laws here,
but yeah, yeah right. No.
Speaker 1 (20:34):
I started by saying there, no, there's no law that
he can't do it, but of course there is, but
there's not anyway, if he buys TikTok, the natural thing
to do would be to have X by TikTok. But
that doesn't mean he'll do that.
Speaker 2 (20:48):
Yeah, I feel like TikTok is way more valuable than X.
But what do I know?
Speaker 1 (20:52):
Yeah, but it's like a weird situation, right, because you're
buying the US operations and you're buying it under the gun, right,
you'd be righting literally, like Donald Trump is saying to TikTok,
either you shut down or yourself to my friend, right, like,
how much leverage do you have to negotiate a price there?
Speaker 2 (21:08):
That's true. Something that was in the main bar story
about this X debt with the Xai sweetener was just
on X's annual interest expenses, And I knew that they
had gone higher, but I didn't appreciate by how much.
So with this debt that they were saddled with, the
annual interest expense went from around fifty million dollars to
(21:28):
well over a billion dollars for X. That is gargantuan.
Speaker 1 (21:34):
Yeah, it's thirteen you know. Well, because they didn't have
debt before, because they were like, yeah, they were like
a not particularly lucrative public tech company. They were not
running with a lot of debt.
Speaker 2 (21:44):
Elon Musbo, you're just a bird app Yeah, yeah, so.
Speaker 1 (21:47):
He bought them with thirteen billion dollars of debt, right,
like thirteen billion times, you know, eight percent is a
billion dollars.
Speaker 2 (21:53):
Yeah, I mean you touched on a little bit. Like
Elon Musk could probably say, I'm good for it. But
so twitter X theoretically is like barely breaking even.
Speaker 1 (22:01):
I hesitate to speculate, like the wre Ald Street Journal
report memos from Elon Musk saying that, but then he
did not he wrote it, so I don't I don't
even know, man, But like, okay, but right, I mean,
like the other thing I was thinking about is like
when Donald Trump was elected, there was a lot of
writing to the effect of, like, this investment looks a
(22:23):
lot better for Elon Musk, right because one like twitter
x might actually be more valuable now because it's now
like platform with a lot of political power. You can
probably sell more ads. But two, you know, it's hugely
increased the value of the rest of his corporate empire,
right because like he now runs a space company that
like runs the government, he runs a car company that
(22:44):
he has all these powers. So the investment looks really
good for him. Does any of that help the debt?
I don't know. I think that Elon Musk, being so
close to the levers of power is probably a small
negative for lenders.
Speaker 2 (22:56):
M H.
Speaker 1 (22:57):
Banks don't like to lend to politically exposed persons, right
because it makes you a worse credit, right because like,
if you end money to Donald Trump and like he
doesn't pay you, then you for close on his property.
But you end money to Donald Trump and he becomes
the president, then like you can't foreclose on him, right,
So like it makes your credit a little bit worse.
And I think there's something of that with Elon Musk,
where like, on the one hand, he's more likely to
be good for the money now that he's like so
(23:19):
much richer and his businesses are so much better. But
on the other hand, if he doesn't want to pay you, like,
there's not a lot you can do about it. So
it's a mixed proposition for the lenders.
Speaker 2 (23:43):
I'm gonna slam this laptop shot at two thirty, just
so you know, no matter what happens, I have a
horse to ride, I have miles to run in New Jersey.
Speaker 1 (23:54):
Let's talk about darkpools.
Speaker 2 (23:56):
Okay, dark pools. So, according to Zomberg News, most US
equity trading isn't done publicly anymore. Matt Levine specifically off
exchange activity is on course to account for a record
fifty one point eight percent of traded volume in January.
That would be the fifth monthly record in a row,
(24:17):
and the third month running that actually when off exchange
volume was greater than half of all volume. Are you scared?
Speaker 1 (24:26):
I would say I'm scared. But it is like a
little bit like the index fund tipping point. Right. Off
exchange volume is sort of to exchanges, what like index
funds are to active management. Right, It's like you trade
on the exchange, you produce a public good. You produce information.
The particular thing you produce is like stock prices, right
Like when you trade on exchange, like you trade against
(24:48):
a lit order, and the order book on the exchange
is public. People can see what the stock is trading for,
and you're producing information. If you trade off exchange, the
off exchange mechanism, you know, if you're hedge fund, it's
called the dark pool. If you're an individual, it's called
like a like a wholesaler or an internalizer. But the
off exchange place where you trade is kind of free
(25:09):
riding on the public exchanges, right, Like they're looking at
the exchanges for pricing and then they're probably giving you
a better price. Right, there's probably some reason that you're
on the off exchange venue, and it's probably that you're
getting a better price.
Speaker 3 (25:21):
Right.
Speaker 1 (25:21):
If you're a retail trader, like gets pretty straightforward, people
get mad about it. But like, the idea of payment
for order flow is that I fregency trading firm doesn't
take nearly as much risk trading with retail traders as
they do trading with fancy hedge funds, and so they're
willing to give you a better price. It's called the
price improvement. Right. If you're on a dark pool, you're
an institution looking for a better price than you get
on the exchange, and you might get that for some
(25:44):
variety of reasons, one of which is just like the
fees might be lower, and so you know, you're trading
in the dark to get a better price, and so
you're not producing the sort of pubably good byproduct of that,
which is like making prices for everyone else. And if
everyone does that then it can get kind of weird.
The very article about this quoted Larry tab saying that
(26:06):
the more trading that goes off exchange is the fuel
orders that are on exchange competing to determine the best price,
and this means the pricing on and off exchange could
get worse, right. I think if there's no one publicly trading,
then like no one knows what the price is, and
so the off exchange pricing deteriorates. I don't think there's
any reason to think that fifty percent is any sort
of magical tipping point, but it's interesting.
Speaker 2 (26:28):
Yeah, and I'm glad you've framed it as a public good.
It's a public good that we would be trading on exchange,
But you could get worried about price discovery, maybe not
at fifty two versus forty eight percent, But it is
kind of a fun thought exercise to imagine a world
where you have ninety percent of trades happening in the dark,
that their prices are based and extrapolated on the ten
(26:51):
percent that's happening on exchange. I don't know what that
world looks like.
Speaker 1 (26:55):
But it's the same thought experiment as index ons, Right,
It's the same thing where people are like, you know,
if forty fund the stock market is own by indixed funds,
that's fine, but ninety percent gets weird, right, Like, you know,
like there's no real way to know what the magic
number is. But it's the same idea of like there
is this like informational good and it's efficient for a
lot of people to free write on it, but at
some point it becomes a problem.
Speaker 2 (27:17):
Yeah. Well, I think there is an important caveat here.
And this was mentioned lower down in the Bloomberg News
article which was written by Catherine Dougherty. It's super good,
but so you're talking about dark pools when it comes
to institutional investors in hedge funds, but when it comes
to retail trading in penny stocks. If you strip out
penny stocks from this data, according to Jeffries, then off
(27:41):
exchange trading volume remains below forty percent, which is less scary,
but it is interesting that it's sort of both sides
of the spectrum chipping away at on exchange volume. It's
like you have dark pools over here with all the
fancy hedge funds, and then you have retail playing in
penny stocks as well.
Speaker 1 (27:58):
You think of hedge funds as the banks sophisticated investors,
and they are, but I think if you're a hedge fund,
you often think of yourself as an innocent victim of
the public stock markets, Like I think at some time frame,
like there are particular firms who are like good at
getting the last penny of price on the stock exchange,
(28:21):
and that's a particular skill set. Those firms are called
high frequency traders, right, And like there are a lot
of hedge funds who are really mad about high percncruit traders,
who feel like they're being front run by higher concutrators,
who feel like the public stock markets are an evil
and predatory place. And you see this in like Michael
Lewis's book Flashboys, were like big time hedge fund managers,
like he like goes into their office and they're like,
(28:42):
look at look at these higherxcy traders. They're fleecing me. Right,
Like people get really mad and like not like unsophisticated
retail investors, like sophisticated investment managers whose time frame is
longer than five seconds, right, and like those people feel
like they're getting fleeced by the people whose time frame
is less than five seconds. And so retail institutions are
in the same boat here where they both feel like
the public markets are predatory, and so they want to
(29:04):
find a more protected place where they won't be subject
to the predators of the public markets. And the more
that happens, the more the public market is just full
of predators, right, Like it's just full of the most
sophisticated trading firms trading against each other and trying to
make my buck coffee each other, and like that makes
them less and less appealing for both retail and for
like a hedge fund that has a you know, fundamental
(29:25):
investment thesis.
Speaker 2 (29:27):
Yeah. Sorry, I'm still thinking about like the comparison to
passive versus active, and we did reach that tipping point
where passive is now the majority of invested assets.
Speaker 1 (29:39):
Yeah, but it's fine. I mean, like people say it's
not finely people get mad, right, Yeah. I think there's
a reasonable case that like some aspects of like you know,
capital allocation efficiency have been undermined by the rise of indexing. Again,
not because fifty percent was the tipping point, but just
because it's bigger than it used to be. But so far,
it seems like there's a lot of competition to find
the right price for security, and there are a lot
(30:00):
of hedge funds who make like really quite a lot
of money trying to make press efficient. So it's not
obvious that indexing has like ended that. Yeah, you could
probably tell a similar story for the sort of microstructure
level of public slock markets, where again, like the trading
firms that trade in public markets do pretty well, so fine, yeah,
(30:22):
and also like spreads are tied and everything like that,
So it's like.
Speaker 2 (30:25):
Yeah, yeah, Well, I don't know if passive will ever
take up ninety percent of invested assets. And I'm not
saying that we could get to ninety percent of trading
happening in the dark, but it does seem I mean,
taking a look at, you know, the various people that
are already closet in this piece that obviously this trend
has been years in the making and now we're we're
(30:45):
at fifty two percent roughly. Who knows where that goes.
This is something that the SEC under Gary Gensler did
try to address and try to push more of that
trading to the public exchanges. And the wild card here
in terms of the trajectory of where this goes is
Paul Atkins. I don't know what his view is. He
seems like an interesting guy, he seems like a contrarian.
(31:08):
I don't know where he lies on this, but it'll
be fun to find out.
Speaker 1 (31:12):
I think some people in the industry would have comments
about the idea that the gangsler SEC tried to push
more training in public exchange, Like that's true, but like
he also tried to like wildly complicate aspects of public
exchanges and ways that might have made them pust appealing.
But no, I think, like broadly speaking, that's true. And
my guess is that in general, there is not a
ton of incentive for the SEC to do a ton
(31:34):
of huge market structure overhauls because while no one kind
of loves us equity market structure, it seems to work fine,
and any potential change would be very complicated. And in fact,
the gangster SEC proposed pretty radical changes and like got
pushed back pretty hard and like didn't end up actually
(31:54):
doing anything, not doing much in like the very radical
like auctioning kind of ideas. Yeah, and it's hard for
me imagine will surely be a very strange SEC being
like we need to reform darkpool training, but maybe who.
Speaker 2 (32:07):
Knows, who knows, I don't know. I would imagine it's
not high on the priority list.
Speaker 1 (32:12):
Yes, there is like a weird populist appeal to saying
We're gonna end payment for order flow and send all
of your orders to the stock exchange. It's like almost
certainly bad for retail investors, but like if you say it,
people are like, oh, yeah, that'll be good for retail investors.
So there's some populist appeal to that as a platform,
and this arguably why Gary Yanser tried to do it.
(32:33):
But you get bogged down very quickly in the weeds,
and it's hard to actually.
Speaker 3 (32:36):
Do it so well.
Speaker 2 (32:38):
Taking a look at just the ETF filings that are
coming across, there's a lot of hopeus and dreams that
Atkins is going to be a huge crypto bole but
I don't know. We'll see. Well that seems true, but
does it. I don't know. I remember you think about
Gary Gensler, People were like, oh my god, he taught
an MIT course on the blockchain, and then turns out
(32:59):
he t into like enemy number one for the crypto crowd.
Speaker 1 (33:04):
I just think that, like fail actins has orders from
the top to be a crypto friendly And I also think,
you know, you're talking about ETF filings, like you could
file an ETF for any meume quin in the world,
and people are people are, but in particular they're filing
for like trump quin and milaniaquint. Now is the SEC
(33:26):
going to say, well, these tokens are two subjects to
manipulation and like don't have a real investment thesis, so
we can't approve an ETF on them, Like.
Speaker 2 (33:37):
Well, well, actually, are you slamming your lap clop closed? Wait,
hold on, okay, here we go. Actually to that point,
there were filings for double leverage Millenia and trump ETFs.
But they.
Speaker 1 (33:54):
They what that was a joke? What do you mean?
I mean, like I wish I had filed a double
leverge of melai ATF as a joke, because like that's
very funny. But like, imagine I was joking.
Speaker 2 (34:08):
I don't think this.
Speaker 1 (34:09):
Is probably right, but I'm gonna I'm going to just
choose to believe that the issuer was joking.
Speaker 2 (34:13):
Yeah, well, assuming that they weren't, and I'm pretty sure
that they weren't joking, they did withdraw the filing.
Speaker 1 (34:19):
And typical it's fine, problem solved.
Speaker 2 (34:22):
No, they definitely weren't joking. Anyway, That suggests they got
a call from the SEC that said, maybe this is
too far, so we'll find out where the lines are.
Speaker 1 (34:33):
I am not convinced that in the next four years
we'll find out where any lines are. Wow, I suspect that,
Like You'll be like, is the line over there? Like Nope,
not here.
Speaker 2 (34:41):
You think a lineless world.
Speaker 1 (34:50):
And that was The Money Stuff Podcast.
Speaker 2 (34:51):
I'm Matt Livian and I'm Katie Gresel.
Speaker 1 (34:54):
You can find my work by subscribing to The Money
Stuff newsletter on Bloomberg dot com.
Speaker 2 (34:59):
And you can find me on Bloomberg TV every day
on Open Interest between nine to eleven am Eastern.
Speaker 1 (35:05):
We'd love to hear from you. You can send an
email to Moneypot at Bloomberg dot m ask us a
question and we might answer it on air.
Speaker 2 (35:11):
You can also subscribe to our show wherever you're listening
right now and leave us a review. It helps more
people find the show.
Speaker 1 (35:17):
The Money Stuff Podcast is produced by Anna Maserakis and Moses.
Speaker 2 (35:20):
Ondeng Our theme music was composed by Blake Maples, Brandon
Francis Munims, Our executive producer, and Stage Bauman is Bloomberg's
head of Podcasts.
Speaker 1 (35:28):
Thanks for listening to The Money Stuff Podcast. We'll be
back next week with more stuff
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