A Lineless World: AI, X, Darkness

Summary

Money Stuff: The Podcast – Episode Summary Title: A Lineless World: AI, X, Darkness
Host: Matt Levine & Katie Greifeld
Release Date: January 31, 2025

In this episode of Money Stuff: The Podcast, hosts Matt Levine and Katie Greifeld delve into the intricate interplay between artificial intelligence (AI) advancements, corporate financial maneuvers, and evolving stock market dynamics. The conversation navigates through the rise of DeepSeek, the financial intricacies surrounding Elon Musk's acquisition of Twitter (now X), and the growing dominance of dark pools in equity trading. Below is a detailed breakdown of the key discussions, insights, and conclusions from the episode.

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1. The Rise and Impact of DeepSeek

DeepSeek has emerged as a pivotal player in the AI landscape, drawing significant attention from investors and industry experts alike. The hosts discuss its rapid ascent and the broader implications for the tech and financial sectors.

• Introduction to DeepSeek:
  Katie Greifeld notes, “[...] 97% of the people I talked to on Monday hadn't heard of it before this past weekend” (02:18). This underscores DeepSeek's sudden prominence, largely fueled by its App Store surge and increased media coverage.

• Technical and Financial Synergy:
  Matt Levine reflects on his previous insights, stating, “[...] the skill sets of quant hedge funds and large language models are kind of overlapping” (03:08). He elaborates on how DeepSeek’s foundation in quantitative hedge fund methodologies allows it to leverage machine learning techniques effectively for stock prediction, reminiscent of strategies employed by firms like Renaissance Technologies.

• Economic Growth and AI's Role:
  The discussion touches upon the theoretical impact of AI advancements on GDP. Matt posits, “if you can get the same AI benefits for free, then that's bad for GDP. But that's better” (05:28). This highlights a paradox where technological efficiency may decouple from traditional economic indicators, raising questions about the future measurement of economic health.

2. Elon Musk’s Acquisition of Twitter (X) and Financial Ramifications

The acquisition of Twitter by Elon Musk has had significant ripple effects in the financial markets, particularly concerning the company's debt and its stake in AI ventures.

• Debt Overview and Market Reaction:
  Katie brings up, “the market lost a trillion dollars of market cap on Monday” (04:49), attributing part of this decline to concerns over the sustainability of Twitter’s (now X) business model post-acquisition.

• XAI Stake as Collateral:
  The hosts analyze the $6 billion stake in XAI, contrasting its initial valuation with the current market sentiments post-DeepSeek’s emergence. Matt explains, “the annual interest expense went from around $50 million to well over a billion dollars” (25:13), emphasizing the financial strain on X due to increased debt obligations.

• Insider Trading and Legal Implications:
  Matt addresses speculative discussions around potential insider trading, asserting, “if he was buying Nvidia puts in his personal account while, you know, running Deepseek, then that might look bad” (08:22). He clarifies the legal boundaries, emphasizing that trading on one’s own information is permissible, but misappropriating others' information is not.

• Political Influence and Corporate Strategy:
  The conversation ventures into how Elon Musk's political sway via X could influence the company's financial strategies and debt management. Matt suggests, “Elon Musk being so close to the levers of power is probably a small negative for lenders” (26:18), highlighting concerns over lending to politically exposed individuals.

3. Dark Pools and the Transformation of Equity Trading

The episode delves into the escalating prevalence of dark pools in U.S. equity trading, now accounting for a record 51.8% of traded volume as of January (32:05).

• Definition and Functionality:
  Matt explains dark pools as venues where institutional investors and hedge funds trade securities outside public exchanges to secure better prices without revealing their strategies.

• Impact on Price Discovery:
  Katie raises concerns about price discovery, pondering the implications of a future where a vast majority of trades occur off-exchange: “Imagine a world where you have 90% of trades happening in the dark, that their prices are based and extrapolated on the 10% that's happening on exchange” (34:33).

• Public Good and Market Efficiency:
  The hosts debate whether the rise of dark pools undermines the public good of transparent price discovery. Matt likens the situation to the proliferation of index funds, suggesting, “there is this informational good and it's efficient for a lot of people to free ride on it, but at some point it becomes a problem” (34:56).

• Regulatory Perspectives:
  Discussion touches upon potential regulatory interventions by the SEC under Gary Gensler. However, both hosts agree that significant market structure overhauls are unlikely in the near term due to the complexity and existing competition among trading firms.

4. Broader Implications and Future Outlook

The episode concludes with reflections on the interconnectedness of AI advancements, corporate financial strategies, and evolving market dynamics.

• AI’s Dual Role in Economy:
  Matt contemplates the balance between AI-driven economic growth and its impact on traditional financial metrics, questioning how future prosperity will be measured beyond GDP.

• Corporate Strategy Amid Market Changes:
  The hosts discuss how companies like DeepSeek and X navigate their financial obligations and strategic positioning in a rapidly changing technological and economic landscape.

• Market Sentiment and Investor Behavior:
  The conversation underscores how sudden shifts, such as DeepSeek’s rise or X’s debt restructuring, influence investor confidence and market capitalization, often leading to volatile trading behaviors.

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Conclusion:
In this episode, Matt Levine and Katie Greifeld provide a nuanced exploration of the current financial and technological terrains shaped by AI innovations and strategic corporate decisions. From the meteoric rise of DeepSeek and its implications on economic indicators to the financial complexities surrounding Elon Musk’s X and the dominance of dark pools in equity trading, the discussion offers deep insights into the mechanisms driving today’s financial markets. As AI continues to evolve and integrate into various facets of the economy, the interplay between technological advancements and traditional financial structures remains a critical area for investors and policymakers alike.

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Note: Timestamps are referenced for illustrative purposes and correspond to sections within the episode transcript.

Transcript

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[Katie Greifeld]

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[Matt Levine]

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[Matt Levine]

Radio News hello and welcome to the Money Stuff Podcast, your weekly podcast where we talk about stuff related to money. I'm Matt Levine and I write the Money Stuff column for Bloomberg Opinion.

[Katie Greifeld]

And I'm Katie Greifeld, a reporter for Bloomberg News and an anchor for Bloomberg Television.

[Matt Levine]

What are we talking about today, Katie?

[Katie Greifeld]

We're going to talk about how the US Stock market got deep sea seeked. We're going to talk about that sweet, sweet ex debt. And then we're going to talk about trading in the dark.

[Matt Levine]

Sounds good. Deep Seek.

[Katie Greifeld]

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 97% of the people that I talked to on Monday hadn't heard of it before this past weekend.

[Matt Levine]

Where did they hear of it?

[Katie Greifeld]

The people I talked to on Monday who hadn't heard of it previously, they heard about it when the app shot up in the App Store.

[Matt Levine]

Okay.

[Katie Greifeld]

And then you had the sell 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.

[Matt Levine]

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 interesting to see how investor reactions coalesce. Right. Because the model was kind of released at the beginning of last week. The catalyst is some combination of people getting to think about it over the weekend, and it's shooting up in the App Store. But at some point, there's this big shift from people using the app to everyone having existential crises. About Nvidia.

[Katie Greifeld]

Yeah, Anyway, this is a digression.

[Matt Levine]

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 Internet. But I do love what I read about in June. Is the founder of Deepseek. It kind of spun out of his quantitative hedge fund. And I love that the skill sets of quant hedge funds and large language models are kind of overlapping. These are kind of like using machine learning techniques to predict somewhat unpredictable things, whether that's the next word in a sentence or the stocks that will go up. And classically, people made billions of dollars. And by people, I mean, like, Renaissance technologies made billions of dollars by, like, repurposing 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 that way.

[Katie Greifeld]

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. Wow, it was so early. But in any case, it's fine.

[Matt Levine]

The thing is not that Deep Seat is an AI company in China. The thing is that the market lost a trillion dollars of market cap on Monday. I don't want to say that the US economy is based on building empowering data centers for AI companies, but the projected incremental cash flows to the US Economy, a lot of those are like, yes, we're going to build a lot of data centers and a lot of power plants to power them. And Deep Seek, arguably, people think that it undermines that case, like, quite significantly. And so if like you thought that all of economic growth would come from like AI data centers. Then now you're like, ah, the source of economic growth is gone. Which is a funny thing to think.

[Katie Greifeld]

But 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.

[Matt Levine]

Yeah, I saw you like tweeted deep seek as a macro event.

[Katie Greifeld]

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 was pretty funny.

[Matt Levine]

I love AI as a, as a like subject matter because it is so science fictional. And one thing people talk about sometimes is whether GDP is a bad index of human flourishing. And so there's this argument that GDP measures understate GDP growth because you're getting all these hedonic benefits from going on social media or whatever, and that's not captured 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 we can get the same AI benefits for free, then that's bad for gdp. But that's better, right? It's clearly better to have those benefits without burning coal than to have them and burn coal. I wrote something like, if you sort of fully believe the deep SEQ thesis, and it's like this magic AI thing that is free, that's clearly better for human flourishing, but it's worse for stock market capitalization because no one can make a profit from it.

[Katie Greifeld]

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.

[Matt Levine]

It's a real question. There's a Simpsons bit where Homer has an autodialer and it calls Mr. Burns and it says, hello, friend, would you trade $1 for eternal happiness? And Mr. Burns, thinking he's talking to a person, thinks for a minute and says, hmm, one dollar for eternal happiness. And I'd be happier with the dollar. I think about this all the time. I sometimes feel that way too. Right. If your 401 goes down, but all of your future needs will be met by a little robot in your pocket, then you didn't need the 401, but you want the 401.

[Katie Greifeld]

That's actually all I could think about on Monday was how I will never financially recover from this trading session.

[Matt Levine]

Like weeping on air.

[Katie Greifeld]

But I was like, no, I need to get to the podcast. You're all in on. The show must go on. So you boldly asked the question in a money stuff this week. What if this Chinese quant hedge fund that then went on to develop Deep Seek had a bunch of Nvidia puts and made a bunch of money that way? And then friend of the show Bill Ackman tweeted the exact same question, which was fun.

[Matt Levine]

I assume that other people independently came to this idea. I had several readers email me about it before I wrote it.

[Katie Greifeld]

No, no, no. You were the first one to ever write about Deep Seq. First one to ever pose this hypothetical.

[Matt Levine]

That's true. And I should also say that the idea of disruptors funding their business by giving away their product for free and shorting incumbents, I learned of it from Joe Weisenthal, our fellow Bloomberg podcaster. Like, a decade ago. He was writing about it before everyone. But in any case, yeah. One, it's a really funny idea. Two, it has really kind of percolated up. Apparently Howard Lutnick is getting questions about it in Congress.

[Katie Greifeld]

Oh, my God.

[Matt Levine]

Whether that's happened, there's like no evidence for it. But it would be very funny if you did it.

[Katie Greifeld]

Also, is it illegal? I mean, is it insider trading?

[Matt Levine]

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 Nvidia puts in his personal account while, you know, running Deepseek, then that might look bad depending on exactly what his arrangement was with Deepseek. But if, like, the corporate complex of, like, Deepseek and the hedge fund was trading on Deepseek's own information to make a profit for that complex, I don't know, it seems fine. It seems like you're not misappropriating any information and you're really only trading on your own knowledge of your own business. Right. And your own extrapolation of what that will mean for other businesses, I think it's totally fine. Now, the two caveats to that are, One, I'm not sure that every Jurisdiction sees it that way. US Law is much more about this misappropriation theory, whereas in other places it's more common to just be a fairness focused. You can't trade 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 insider trading. And then you'd say, no, no, it's not insider trading. It's fine. They're like, okay, fine, but it's market manipulation and like, it's market innovation because they'll find something you said wrong. Right. And so here in Deep Sea, there's been 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 from other 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 manipulation. You were like saying false things to bring down Nvidia stock. So it would be a risky thing to do to tank Nvidia stock in such a high profile way while earning puts on it. Like, people would get mad and might find a thing to charge you with. But like, no, I don't think it's insider trading.

[Katie Greifeld]

Yeah, well, I mean, again, this is all hypothetical. We have no idea if he actually did this. But I don't think he did it.

[Matt Levine]

I just like, it's fun. He should have done it. I would have done it. Because the other thing is they don't, I don't know what their business model is. Public reporting is some combination of, oh, he's just making money on his hedge fund or he's doing this out of the goodness of his heart and wanting to contribute to AI research because it's open source, it's cheap. How are they going to make money? I don't know. They could shorten Nvidia. Right?

[Katie Greifeld]

Yeah. I did also want to bring up that the narrative around this week has been that basically Deep SEQ was able to recreate OpenAI with $6 million. And it's just been fun watching that get picked apart. I've spoken to so many Nvidia bulls in the past couple days who have made this into a bull case for Nvidia, which I find really interesting. And there is a lot of skepticism around the numbers here. And, and one of the news stories that came about is that Microsoft and OpenAI are taking a look at whether this group used OpenAI's API to basically get a large amount of data which would violate OpenAI's terms of service. Because OpenAI, as we were reminded this week, isn't actually open source, it's closed source. But Meta's Llama is open source.

[Matt Levine]

Here's how I think about this. There are a lot of businesses that have been or look likely to be really badly disrupted by AI. There's some margin where if you're a.

[Katie Greifeld]

Accountant, let's say podcaster.

[Matt Levine]

Podcaster, yes. If you're a podcaster, they're coming for you. And in the next few years, an AI will be able to sit here and talk into a microphone. I mean, not literally, but will 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 across a range of sort of knowledge industries. Right? And so AI is like, undercutting a lot of people's jobs in a way that increases abundance for the people who want to listen to podcasts or get accounting services, but that undercuts the earning potential of the people who are providing it cheap. AI is to AI what AI is to humans, right? It's like OpenAI is like, Ah, we can do your accounting for a tenth of the price of accountants. And now DeepSteak is like, we can do it for a tenth of the price of OpenAI. It's great. But the other interesting thing is you talk about were they using OpenAI's APIs to train their model, to distill OpenAI's model, where you get a corpus of OpenAI outputs and you use that to train your model or use it to refine the training of your model. That, to me, is a little bit analogous to the complaints that publishers have about OpenAI using their data to train its models. Right? AI synthesizes the output of all these humans and then comes up with a thing that is 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, Deepseek kind of did that to OpenAI. Maybe, like, arguably, like, people have suspicion, which I think violates the terms of service, but there's like a certain poetic justice to it.

[Katie Greifeld]

Well, deepseek, for its part, says that it has distilled models for R1 based on other open source systems, not necessarily on OpenAI. But again, Meta's Llama 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.

[Matt Levine]

Right? It's like there's this notion that if Deep Seq is piggybacking on the work of other models, then then somehow the bear case against us AI infrastructure spending is 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 you can build impressively on prior work and so you don't need all those data centers. I don't know.

[Katie Greifeld]

I am curious what this means for the state 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.

[Matt Levine]

But we're like two days out from like the US Government being like, we're going to spend a trillion dollars on AI capex. Right.

[Katie Greifeld]

It's like, well, you think about last week.

[Matt Levine]

I don't know, people are so news driven. Like you could imagine everyone being like, ah, we're just kidding about all the capex. Like you can imagine a really hard pivot in the next week. But it just. That doesn't seem that well.

[Katie Greifeld]

There's a lot of awkward timing here because you think about Stargate, which was announced Last week with OpenAI with SoftBank, $100 billion met last week announced it was boosting its capex to up to $65 billion. Microsoft is spending $80 billion. 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 deep seeked on Monday was as someone with a 401k brutal but pretty fun to watch.

[Matt Levine]

I'm sorry this is rude, but it's such a SoftBank story. SoftBank announcing like we're going to spend $100 billion on data centers. Like 10 minutes before, like that becomes an obsolete thesis. That's a good story.

[Katie Greifeld]

A good story.

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[Katie Greifeld]

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[Matt Levine]

Speaking of.

[Katie Greifeld]

Ill timed trades man, let's talk about X debt. It seems like it's getting a lot sweeter potentially. Well, this is also weird I never.

[Matt Levine]

Know how to interpret this, because is this sweetener So X Twitter X, the company formerly known as Twitter, Elon Musk bought it in 2022. 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, banks led by Morgan Stanley, agreed to provide him $13 billion of debt to buy Twitter. And by the time the deal closed, ordinarily they would 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 until the last minute, and so wouldn't help out on the debt sale. 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 further and because he was 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 60 cents on the dollar and they couldn't or whatever. Like, they got bids at 60. Yeah. So, like numbers like 60 cents on the dollar were floating around and now they're apparently offloading some of the debt. And like numbers like 90 to 95 cents on the dollar are floating around. So pretty good. That's like, not necessarily apples to apples because it's like there are varying levels of seniority and it's possible that they couldn't sell the worst debt at 60 and now they're selling the best debt at 90, but still.

[Katie Greifeld]

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 30 cents per bond or whatever? And whether it still is after, of course, deep seeking came about on Monday.

[Matt Levine]

After Elon Musk bought Twitter, the next thing quickly became Large Language models. When he signed the deal to buy Twitter, no one was talking about OpenAI or whatever, but shortly after the closing, 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 some resources with X. And he made enough noise about doing AI out of X that the upshot is that X AI is not just owned by him personally and people who put money into xai, and he's raised a lot of Money for xai. It's also partly owned by X, by Twitter. So that company that he bought, one of its assets is apparently a $6 billion stake in Xai that's measured at its most recent valuation, which is like $50 billion. Now, maybe that valuation has gone way down since Deepseek was released. Yeah, there's not a lot of public market comps for pure play AI companies, so who knows what the valuation is of Xai or OpenAI or anything else. But last time we checked, that stake was worth $6 billion, which sure is worth a lot of money to the debt because the debt is like $13 billion, and if they have collateral, then that's worth 45 cents on the dollar. So I think that there was reporting that excess banks were shopping the debt, specifically telling people, hey, you'd 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 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 protection 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 protection because, one, AI companies are valuable. 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 AI companies where they did. Where they're like, oh, look, it has like all these, like, Nvidia chips. Even if something goes horribly wrong at this company, those chips are super valuable because there's such an AI gold rush. So there's really good collateral here. Right. Again, 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.

[Katie Greifeld]

Yeah. And I mean, you say that Elon 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?

[Matt Levine]

Yeah, nobody knows anything. But Elon Musk has kind of always said, including when he was buying it, that Twitter was not a great business decision, but he thought it was important for the future of the world, blah, blah, blah, blah. And that, by the way, turned out to be right. He's had a ton of political influence with Twitter without it necessarily making him a lot of money again. A week ago, everyone was like, wow, AI is a real gusher of money. Right. Who knows now? But like. Right. I'm not. 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 a week ago.

[Katie Greifeld]

Yeah. You know what could be more fun than owning Twitter?

[Matt Levine]

Virtually anything.

[Katie Greifeld]

I don't know. I mean, I'm speaking specifically from Elon Musk's shoes, perhaps owning TikTok, but that's a totally different conversation.

[Matt Levine]

Yeah. Yeah, I wonder about that, right? If he buys TikTok, can you imagine him doing that separately? That'd be so rude. It didn't even occur to me. Because he's been 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 standard views of corporate fiduciary duties and corporate opportunities where, yeah, it would be really weird of him to buy a competitor. If he owns X, he could do that and then he could own them somewhere.

[Katie Greifeld]

I was going to say, very bold of you to assume there are laws here, but come on.

[Matt Levine]

Yeah, right. No, I started by saying 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 buy TikTok, but that doesn't mean he'll do that.

[Katie Greifeld]

Yeah, I feel like TikTok is way more valuable than X, but what do I know?

[Matt Levine]

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're buying it literally. Like Donald Trump is saying to TikTok, either you shut down or you sell it to my friend. Right. How much leverage do you have to negotiate a price there?

[Katie Greifeld]

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 $50 million to well over a billion dollars. For X, that is gargantuan.

[Matt Levine]

Yeah, it's 13. 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. Elon Musk bought them.

[Katie Greifeld]

They were just a bird app. Yeah.

[Matt Levine]

So he bought them with $13 billion of debt. Right. 13 billion times 8% is a billion dollars.

[Katie Greifeld]

Yeah. I mean, you touched on it a little bit. Like, Elon Musk could probably say, I'm good for it. So Twitter X theoretically is barely breaking even.

[Matt Levine]

I hesitate to speculate. The Wall Street Journal reported a memo from Elon Musk saying that, but then he denied he wrote it. So I don't even know, man.

[Katie Greifeld]

Let's not speculate then. Okay, but.

[Matt Levine]

Right. I mean, the other thing I was thinking about is when Donald Trump was elected, there was a lot of writing to the effect of this investment looks a lot better for Elon Musk because one, Twitter X might actually be more valuable now because it's now a platform with a lot of political power. You can probably sell more ads. But two, it's hugely increased the value of the rest of his corporate empire because he now runs a space company that runs the government. He runs a car company. 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. Banks don't like to lend to politically exposed persons. Right. Because it makes you a worse credit. Right. Because if you lend money to Donald Trump and he doesn't pay you, then you foreclose on his property. But you lend money to Donald Trump and he becomes the president, then you can't foreclose on him. So it makes your credit a little bit worse. And I think there's something of that with Elon Musk, where on the one hand, he's more likely to be good for the money now that he's, like, so much richer and his businesses are so much better. But on the other hand, if he doesn't want to pay you, there's not a lot you can do about it. So it's a mixed proposition for the lenders.

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[Katie Greifeld]

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[Matt Levine]

Foreign.

[Katie Greifeld]

I'm going to slam this laptop shut at 2:30. Just so you know, no matter what happens, here I am, I have a horse to ride. I have miles to run in New Jersey.

[Matt Levine]

Let's talk about dark pools.

[Katie Greifeld]

Okay, dark pools. So according to Bloomberg News, most US equity trading isn't done publicly anymore. Matt Levine specifically off exchange activity is on course to account for a record 51.8% of traded volume in January. That would be the fifth monthly record in a row and the third month running that actually when off exchange volume was greater than half of all volume. Are you scared?

[Matt Levine]

I wouldn't 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 stock prices. When you trade on an exchange, you trade against a lit order and the order book on the exchange is public. People can see what the stock is trading for and you are producing information. If you trade off exchange, the off exchange mechanism, if you're a hedge fund, it's called the dark pool. If you're an individual, it's called a like a wholesaler or an internalizer. But the off exchange place where you trade is kind of free 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, right? If you're a retail trader, it's pretty straightforward. People get mad about it. But the idea of payment for order flow is that high frequency 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 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 variety of reasons, one of which is just like the fees might be lower and so you're trading in the dark to get a better price. And so you're not producing the sort of public good byproduct of that, which is like making prices for everyone else. And if everyone does that, then it can get kind of weird. Bloomer's article about this quoted Larry Tabb saying that the more trading that goes off exchanges, the fewer orders there are on exchange competing to determine the best price. And this means the pricing on and off exchange could get worse. Right. If there's no one publicly trading, then 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 50% is any sort of magical tipping point, but it's interesting.

[Katie Greifeld]

Yeah, and I'm glad you 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 52 versus 48%, but it is kind of a fun thought exercise to imagine a world where you have 90% of trades happening in the dark, that their prices are based and extrapolated on the 10% that's happening on exchange. I don't know what that world looks.

[Matt Levine]

Like, but it's the same thought experiment as index funds. Right. It's the same thing where people are like, if 30% of the stock market is owned by index funds, that's fine, but 90%, it gets weird. There's no real way to know what the magic number is, but it's the same idea of there is this informational good and it's efficient for a lot of people to free ride on it, but at some point it becomes a problem.

[Katie Greifeld]

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 Doherty. It's super good, but. So you're talking about dark pools when it comes to institutional investors and hedge funds. But when it comes to retail trading in penny stocks, if you strip out penny stocks from this data, according to Jefferies, then off exchange trading volume remains below 40%, which is less scary. But it is interesting that it's 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.

[Matt Levine]

You think of hedge funds as being 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. I think at some time frame There are particular firms who are good at getting the last penny of price on the stock exchange. And that's a particular skill set. Those firms are called high frequency traders. There are a lot of hedge funds who are really mad about high frequency traders who feel like they're being front run by high frequency traders who feel like the public stock markets are an evil and predatory place. And you see this in Michael Lewis's book Flashbuz were like big time hedge fund managers. He goes into their office and they're like, look at these high frequency traders, they're fleecing me. People get really mad. And not unsophisticated retail investors, sophisticated investment managers whose timeframe is longer than five seconds. And those people feel like they're getting fleeced by the people whose timeframe is less than five seconds. And so retail and institutions are in the same boat here where they both feel like the public markets are predatory and so they want to 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 a buck off each other. And like that makes them less and less appealing for both retail and for like a hedge fund that has a fundamental investment thesis.

[Katie Greifeld]

Yeah, sorry. I'm still thinking about the comparison to passive versus active. And we did reach that tipping point where passive is now the majority of invested assets.

[Matt Levine]

Yeah, but it's fine. I mean, people say it's not fine, people get mad. I think there's a reasonable case that some aspects of capital allocation efficiency have been undermined by the rise of indexing. Again, not because 50% 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 securities. And there are a lot of hedge funds who make really quite a lot of money trying to make prices efficient. So it's not obvious that indexing has ended. That you could probably tell a similar story for the microstructure level of public stock markets where again, the trading firms that trade in public markets do pretty well. Seems fine, but. Yeah, and also like spreads are tight and everything like that. So it's like.

[Katie Greifeld]

Yeah, yeah, well, I don't know if passive will ever take up 90% of invested assets. And I'm not saying that we could get to 90% of trading happening in the dark, but it does Seem, I mean, taking a look at, you know, the various people that Doherty quotes in this piece, that obviously this trend has been years in the making and now we're, we're at 52% 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. I don't know where he lies on this, but it'll be fun to find out.

[Matt Levine]

I think some people in the industry would have comments about the idea that the Gensler SEC tried to push more trading to public exchange. That's true. But he also tried to wildly complicate aspects of public exchanges in ways that might have made them less appealing. But no, I think 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 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 Gensler SEC proposed pretty radical changes and got pushed back pretty hard and didn't end up actually doing anything, not doing much in the very radical auctioning kind of ideas they had. And it's hard for me to imagine what will surely be a very strange SEC being like, we need to reform dark pool trading. But maybe, who knows, who knows?

[Katie Greifeld]

I don't know. I would imagine it's not high on the priority list necessarily.

[Matt Levine]

There is like a weird populist appeal to saying we're going to 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 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 is arguably why Gary Gensler tried to do it. But you get bogged down very quickly in the weeds and it's hard to actually do it.

[Katie Greifeld]

Well, taking a look at just the ETF filings that are coming across, there's a lot of hope as and dreams that Atkins is going to be a huge crypto bull, 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 are like, oh my God, he Taught an MIT course on the blockchain, and then turns out he turned into, like, enemy number one for the crypto crowd.

[Matt Levine]

I just think that, like, Paul Atkins has orders from the top to be crypto friendly. And I also think, you know, you talk about ETF filings. Like, you could file an ETF for any meme coin in the world.

[Katie Greifeld]

And people are, people are, but in.

[Matt Levine]

Particular, they're filing for, like, Trump coin and Melania coin. Now, is the SEC going to say, well, these tokens are too subject to manipulation and, like, don't have a real investment thesis, so we can't approve an ETF on them? Like, well, well, actually, aren't you slamming your laptop closed?

[Katie Greifeld]

Wait, hold on. Okay, here we go. Actually, to that point, there were filings for double leveraged Melania and Trump ETFs, but they.

[Matt Levine]

Come on, they were withdrawn. That was a joke.

[Katie Greifeld]

What do you mean?

[Matt Levine]

I mean, like, I wish I had filed a double leverage of Milani ETF as a joke, because, like, that's very funny, but, like, imagine trying to launch.

[Katie Greifeld]

Out of this product. The issuer was joking. I don't think this is probably right, but I'm gonna.

[Matt Levine]

I'm gonna just choose to believe that the issuer was joking.

[Katie Greifeld]

Yeah, well, assuming that they weren't, and I'm pretty sure that they weren't joking, they did withdraw the filing, and typically.

[Matt Levine]

Well, then they were joking. It's fine. Problem solved.

[Katie Greifeld]

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.

[Matt Levine]

I am not convinced that in the next four years, we will find out where any lines are.

[Katie Greifeld]

Wow.

[Matt Levine]

I suspect that, like, you'll be like, is the line over there? Like, nope, not here.

[Katie Greifeld]

A lineless world.

[Matt Levine]

And that was the Money Stuff podcast. I'm Matt Levine.

[Katie Greifeld]

And I'm Katie Greifeld.

[Matt Levine]

You can find my work by subscribing to the Money stuff newsletter on Bloomberg.com.

[Katie Greifeld]

And you can find me on Bloomberg TV every day on Open Interest between 9 to 11am Eastern.

[Matt Levine]

We'd love to hear from you. You can send an email to moneypodlumberg.net Ask us a question and we might answer it on air.

[Katie Greifeld]

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.

[Matt Levine]

The Money Stuff podcast is produced by Anna Mazarakis and Moses Andong.

[Katie Greifeld]

Our theme music was composed by Blake Maples.

[Matt Levine]

Brendan Francis Noonan is our executive Producer.

[Katie Greifeld]

And Sage Bauman is Bloomberg's Head of Podcasts.

[Matt Levine]

Thanks for listening to the Money Stuff podcast. We'll be back next week with more stuff.

[Katie Greifeld]

This podcast is supported by BetterHelp, offering licensed therapists you can connect with via video phone or or chat. Here's BetterHelp head of clinical Operations Hes Yu Jo discussing who can Benefit from Therapy I think a lot of people think that you're supposed to be going to therapy once you're like having panic attacks every day. But before you get to that point, I think once you start even noticing that you feel a little bit off and you can't maintain this harmony that you once had in relationships, that could be a sign that maybe you want to go talk to somebody. There's always a benefit in talking to someone because we can all benefit from improved insight about ourselves and who we are and how we behave with other people. So if you're human, that's like a good indicator that you could benefit from talking to somebody. Find out if therapy is right for you.

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