Programming note: This is a somewhat special edition of Money Stuff, because sports gambling ETF. Also this week’s episode of the Money Stuff podcast is out now, in which Katie and I discuss no-Elon ETFs, index rebalancing and egg Libor. You can listen to it here.

Sports gambling ETF:

The Subversive All Season Sports ETF … is an actively managed exchange-traded fund (“ETF”) that seeks to provide capital appreciation through exposure to a portfolio of derivative instruments known as “event contracts” across a variety of sporting events. … 

The Fund seeks to mitigate the risk of loss on exposure to any individual event contract by holding a portfolio with exposure to approximately 40 to 80 different event contracts across the sports events noted above.

The Fund will hold exposure to event contracts that are based on the aggregate outcomes of the sporting events only (i.e., final scores of games, point differentials, win-loss records, tournament advancement and team or individual statistical performance compiled over an entire game or season). Such event contracts will settle based on objective and verifiable settlement criteria and will be based on events that are coordinated by relevant sports governing bodies.

The Adviser will allocate exposure based on its assessment of relative value and market-implied probabilities of certain outcomes and actively manages position sizing and allocation among the categories of event contracts noted above. 

That is a filing from Tidal Investments LLC and Subversive Capital, who are also responsible for the no-Elon-Musk index ETFs that we discussed yesterday. You give the sports ETF your money, and the ETF uses your money to make 40 to 80 sports bets. (The bets will be on “North American professional sports leagues,” “National Collegiate Athletic Association championships,” “international sporting events such as the World Cup or English Premier League,” and “other sporting events, such as individual golf or tennis championships, mixed martial arts fights or boxing matches.”) If it wins those bets, it uses the winnings to make more bets and you make money. If it loses the bets, you lose money. It is an ETF for making sports bets. [1]  It will trade on the stock exchange, you can buy it from your stockbroker, and it will make sports bets.

We have talked any number of times about my prediction that there would be a sports gambling ETF by March 2027, and here we are. The filing is not effective yet, and, as we have discussed, the SEC is still considering whether and how to allow sports gambling ETFs. This might never actually launch. But we remain ahead of schedule.

When we discussed sports gambling structured notes a while back, I proposed that they were a way to combine (1) the fun of sports gambling with (2) a boring normal socially acceptable investment product. You could buy a note that paid off more if your team won and less if it lost. “No one is going to be like ‘honey I think you might have a problem’ about your structured notes portfolio,” I wrote. I sort of imagined sports gambling ETFs working the same way; that is, I imagined a Knicks Win ETF, or a Jets/Bills Over ETF or whatever, where you could bet on sports in an ETF wrapper. You’d get the fun of sports gambling, but in your ETF portfolio.

But that is very hard to implement in practice: Sports bets mostly resolve quickly, and the main imperative of an ETF manager is to continue managing the ETF. So the implementation has to be more or less like what Subversive and Tidal are doing: a diversified portfolio of sports bets, actively managed by professional gamblers, aiming to achieve long-term capital appreciation. If you buy this, you are not betting on the Knicks; you are betting on some gambler to outperform in the long run. I’m not sure if that’s quite what you want in a sports gambling ETF. I suppose if this flourishes there can be a wider variety of more tailored sports gambling ETFs — the Basketball ETF, the Diversified Sports Gambling ETF But We Try to Bet on the Knicks, etc. — though you’re never going to get quite the thrill of making your own prop bets. I’m not sure you’ll even know what bets the actively managed sports gambling ETF has on in real time. You’ll be watching the big game, not knowing which way your ETF manager has bet.

Also: I have half-joked once or twice about passive, rules-based sports gambling exchange-traded funds, or passive prediction market ETFs more generally. The rough shape of the idea is: “Certain bets are systematically mispriced for retail supply and demand reasons. For instance, people might not want to make straight-up bets on heavy favorites in college football: Betting $2,000 on the favorite to win $100 is no fun, while betting $100 on the underdog to win $2,000 is fun. Therefore, taking the unpopular side of this bet should offer a positive expected return. An ETF that systematically bet on huge favorites could have positive returns with no correlation to the stock market.” We have discussed a guy named Mike Wohl, who actually ran a fund doing that for a while in the early 2010s, though that was back in the dark ages before sports bets traded on regulated US commodities exchanges. Now you can do these sorts of bets on Kalshi.

(Similarly, we have discussed a few times a prediction-market strategy of the form “bet No on everything, because the public is systematically biased in favor of stuff happening, so No offers positive expected returns.” Again, this is the sort of thing that could be systematized in an ETF.)

Notice a problem with this idea, though. The essential idea is: “Dumb public money is systematically on one side of certain bets, which makes the expected value of the other side positive.” That idea might be correct; it might be a good reason for you to take the other side of the bet. But once you raise an ETF to take the other side, you have a problem. The problem is that the ETF is dumb public money. Or smart, whatever. But the point is:

1. If you raise a bunch of money to take the unpopular side of the bet, that will, by definition, make it more popular. You’ll move the odds against you.
2. If you systematically take the unpopular side of the bet — “bet on the favorites to win when the spread is 30 points or more” or whatever — then your actions are predictable and you can get picked off. Sharp gamblers will think “that ETF systematically bets on favorites, which makes the favorites overpriced, so I should hunt for bargain long-shots.”

You see some of this dynamic in regular ETFs, or maybe not “regular” ETFs but ETFs involving stocks anyway. There are a lot of long and short leveraged ETFs on single stocks, and those leveraged ETFs do very predictable mechanical trades (buying when the underlying stock goes up, selling when it goes down) that are often bad for their own performance. Some number of sophisticated traders like to trade against them, for fairly straightforward reasons of “there’s a lot of dumb retail money mechanically doing one thing so I should take the other side.” Last year, someone launched an ETF to take the other side of those ETFs’ trades. Every sophisticated trade eventually gets put into an ETF, even trades like “trade against ETFs.” It’s the Russell’s paradox of ETFs: Does the ETF that shorts every ETF short itself?

I put this all out there because:

1. Somebody had better launch a passive sports gambling ETF soon, but
2. If you’re doing it, maybe think about this problem. Or don’t. My interest in all of this is strictly comedic, and if you launch a bet-against-dumb-money sports-gambling ETF that gets huge and becomes the dumb money, that is great for my comedic purposes. Also I’ll get to say that I predicted it.

But for now, there is an actively managed sports gambling ETF, or at least, we are well on our way there. I predicted this last March partly as a joke, and as a response to someone posting a joke about an ETF that would buy lottery tickets. “Clearly,” I wrote, sports gambling as an asset class “is the future and I am the past and financial markets are for betting now. Why shouldn’t all the technology of finance be applied to emerging asset classes like gambling?” Imagine how naive I was, thinking I was kidding.

Also I’ve written before about the difficulties of getting leverage in prediction markets. So, why not: By July 2028, we’ll have a 2x levered sports gambling ETF. 

One thing that happens to me with frankly weird regularity is that I get emails from readers suggesting that it might be a good deal to spend X years in prison if it left you with $Y million when you got out. For instance, I still don’t really understand the whereabouts of Bill Hwang’s money, I have joked that it’s buried in his backyard, and people sometimes email me to be like “see, good trade.” I strongly disagree. My discount rate for prison-now-money-later is nearly infinite and I think yours should be too. I do not think that I would spend a week in prison to get a billion dollars at the end of it, and anyway that trade is not on offer. I guess this one is, though, sort of:

A Brooklyn man who admitted illegally making more than $2.2 million by using information from companies’ electronic regulatory filings before they were released to the public was sentenced to more than two years in prison.

US District Judge Orelia Merchant sentenced Justin Chen to 27 months in prison at a hearing Tuesday, saying his crimes “wither away the public’s trust in the markets, which cannot be condoned.” … 

Prosecutors said that because Chen failed to show remorse or disclose what happened to the money he made on the stocks, he should serve as much as 57 months in prison. …

Prosecutors argued that Chen always planned to send the money to China where he could live off the proceeds after he was released from prison. Nick Axelrod, an assistant US attorney, told Merchant Tuesday that while the government still believed Chen’s crimes merited some period of imprisonment, the government would have “likely” sought a lesser term if he had paid back the money.

We talked about Chen last year: He helped companies prepare Securities and Exchange Commission filings, and he traded on those filings before they were public. “Not a bad trade,” said a reader who sent me this story, and perhaps Chen agrees now, but let’s see how he feels after two years in prison.

I don’t think this worked?

BUKIT MERTAJAM, Malaysia, July 07, 2026 (GLOBE NEWSWIRE) -- CCHH, doing business as Chicken Claypot and restaurant franchises business (Nasdaq: CCHH) (“CCHH” or the “Company”), a Nasdaq-listed company primarily engaged in chain restaurant operations, today announced that its wholly-owned subsidiary has entered into a definitive three-year sales and service agreement with several strategic clients. The identity of the counterparties remains confidential pursuant to a binding non-disclosure agreement between the parties.

Under the agreement, the Company will provide maintenance services solution to the undisclosed client in support of data center infrastructure projects in Malaysia, one of Southeast Asia’s increasingly important digital infrastructure and computing hubs. The total contract value under the agreement is US$50 million over the three-year term.

In addition to maintenance services solution for Malaysian data center projects, the agreement provides the client with comprehensive technical and operational support, including computing capacity allocation, deployment coordination, technical consultation and operational advisory services for data center facilities. The service scope may further expand to additional countries and regions in line with the client’s global capacity rollout plan.

The stock is down quite a bit since this was announced Tuesday, though it was down quite a bit before then too. Obviously this trade — “we have a company with a stock that is down, so we should pivot to providing AI infrastructure” — is a popular one. We have talked about a sneaker company that did it, and a karaoke company, and a digital asset treasury company. (We’ve also talked about a food seasoning company, and a toilet company, that happened to make critical supplies for AI infrastructure anyway and didn’t even have to pivot.) Some of the oomph might be going out of it though. There are actual AI companies on the stock exchange! SK Hynix sold $26.5 billion of stock yesterday! It makes memory chips that are crucial to the AI buildout! In real life! The chicken claypot pivot is less compelling by comparisoon.

I have no idea what sorts of “computing capacity allocation” the chicken claypot restaurant is providing for its unnamed strategic clients. But I guess if I ran a chicken restaurant business, I would probably pitch big AI companies on opening franchises at their campuses, or running food trucks at their data center construction sites. And then I’d put out a press release like “We have signed a definitive agreement to provide crucial AI infrastructure services to Big AI Company.” The services would be chicken. Everyone knows that it’s good business to sell picks and shovels in a gold rush, but the gold miners have to eat too.

If you'd like to get Money Stuff in handy email form, right in your inbox, please subscribe at this link. Or you can subscribe to Money Stuff and other great Bloomberg newsletters here. Thanks!

Here are two problems. One is that it is not very pleasant to store crude oil. Oil is voluminous and oozy and poisonous and flammable and smelly. This makes it a somewhat difficult thing to invest in. If you think that the price of SpaceX stock will go up, you buy some SpaceX stock, which is an entry in a computer database and easy to store. If you think that the price of oil will go up, you won’t buy a few barrels of oil; where would you put them? You could buy shares of an oil exchange-traded fund, but the oil ETF doesn’t want to own barrels of oil either; where would it put them? Instead, you (or the ETF) will probably buy oil futures, which are contracts for the delivery of oil at some specific future date. And then before that delivery date, you sell the futures you own (because you don’t actually want to get delivery of oil) and buy some new futures for some later delivery date. You keep doing that, “rolling” the futures to keep exposure to oil prices while never actually having to store any oil.

This strikes me as fine, a reasonable way to reconcile (1) people’s desire to invest in oil with (2) their lack of desire to store oil. This is a good system. But other people find it upsetting. This is not how other things work. If you want to invest in gold, you can buy gold bars and keep them in a closet; they’re pretty small. Or you can invest in a physical gold ETF that buys gold bars and keeps them in a closet. For some dense valuable imperishable commodities, that’s fine. For other commodities it is obviously not. You would not keep pork bellies in a closet indefinitely. Oil is like pork bellies but more macroeconomically important: Lots of people want to own it, and they tend not to think about the problems of its ooziness.

Therefore, a product that is like “you own one barrel of oil for as long as you like, with no rolling of contracts and no uncertainty of future delivery, just a barrel of oil in a warehouse with your name on it” has an intuitive appeal to buyers, but no one wants to actually run that warehouse. [1]

The second problem is that oil companies own some oil that they can’t sell. Some of this is, you know, deep under the ocean: An oil company has a claim to some oil field, its geologists are pretty sure that there are millions of barrels of oil down there, but it has to expensively drill it up before it can sell it. But some of it is just that there are physical frictions in moving oil around. There is line fill: You can’t sell all of the oil in your pipelines, because you need some oil in the pipe to push the other oil out. [2] There are tank bottoms: You can’t sell all of the oil in your tanks, because you need some oil in the tanks to provide pressure to the pipes. [3]  As Bloomberg’s Mia Gindis and Sidhartha Shukla put it, this is “inventory that typically sits inside the machinery of the oil business itself”:

Pipeline line fill, tank bottoms and other operational inventories are often carried on company balance sheets but generate little direct revenue. 

Those are two problems. But it is 2026, and finance has evolved a joint solution to those problems. We talked last year about NatBridge Resources Ltd., a gold mining company that (1) owns a lot of gold but (2) can’t sell that gold in normal gold markets because it is deep underground and not refined. That is: NatBridge owns gold mines, which contain gold ore, but it doesn’t currently operate the gold mines, so the gold just sits there.

But it found a way to sell it anyway, which is: crypto. The solution is that you tell people “hey, we have gold underground, would you like to buy a token giving you a claim to that gold?” And they say “sure, I was going to buy a share of the physical gold ETF, but all that is really is an electronic token entitling me to some gold underground (in a vault in London); your token is cheaper and the same basic idea.” I wrote:

“People who want digital tokens representing a certain amount of gold” is, in the abstract, a huge market. Central banks that keep gold reserves at the Fed or the Bank of England, gold futures traders, investors in gold ETFs: They all spend many billions of dollars on digital tokens representing a certain amount of gold underground. The NatBridge tokens are just, you know, gold in a slightly different part of underground.

The same solution applies, but more so, to oil:

1. People want to own perpetual claims on oil, without having to worry about taking delivery or the mechanics of rolling futures contracts: They want direct claims on physical oil, but not the physical oil itself.
2. Oil companies have some physical oil that they can’t sell in physical oil markets.
3. The oil companies should sell tokens on the hard-to-deliver physical oil to people who want claims on physical oil (but not physical oil).

Gindis and Shukla report:

A small crypto startup is trying to persuade the industry to experiment with a different kind of frontier: putting a barrel of oil on a blockchain.

The company, Energy Substantiation, wants oil suppliers to help support a digital token tied to physical crude. For decades, ownership of real-world barrels has largely been the preserve of producers, traders and large institutions. Energy Substantiation is seeking to open up the market to anyone with a crypto wallet and a small outlay.

“It is remarkable to me that people can own dollars and people can own gold, but they’ve never been able to own oil,” JP Thieriot, who is spearheading the idea as Energy Substantiation’s co-founder, said in an interview.

It’s not remarkable at all? Bloomberg’s Tracy Alloway famously did own some oil and it was a huge pain. (The first paragraph of her column about it is: “‘Don’t buy a barrel of oil,’ the broker said. ‘It’ll kill you.’”) Just look at a bar of gold, look at a barrel of oil, inhale deeply, and you will immediately understand why it is easier to own gold than oil. But, fine, go with it:

WTIC [the token] is designed to track the price of West Texas Intermediate crude. Suppliers feed oil into the system through a reverse Dutch auction, which entails offering barrels at a discount to the day’s market price. The company says the tradeoff lets producers monetize operational inventories, including pipeline line fill and tank bottoms, that would otherwise generate little revenue. Investors can then buy and sell the tokens on blockchain networks, while new ones are created through a daily minting process.

Holders can redeem WTIC at the daily spot closing price, though the company does not expect many investors to take physical delivery of crude. … The system also relies on inventory that typically sits inside the machinery of the oil business itself. Pipeline line fill, tank bottoms and other operational inventories are often carried on company balance sheets but generate little direct revenue. Energy Substantiation’s model attempts to monetize those dormant barrels while using them to back digital tokens.

This is maybe my favorite move in finance [4] : “You know that real physical thing you can’t sell? Why don’t you sell a token of it instead?” Finance is about building abstractions on top of the physical world, and this is the most philosophically ambitious and physically lazy way to do it. Someone should do a token on oil that is still under the ocean.

Two important themes in the current US stock market are:

1. A large portion of the market is made up of companies (SpaceX, Tesla) run by Elon Musk; and
2. A lot of people wish it wasn’t.

The market capitalization of US stocks is in the ballpark of $80 trillion; SpaceX is about $2 trillion and Tesla is about $1.5 trillion, so Musk represents around 4.4% of the total stock market. If you are an index-fund investor, you probably own some Musk: As of this week, the Nasdaq 100 includes Tesla and SpaceX; the S&P 500 includes Tesla but not SpaceX.

You might be thrilled about this, as many Tesla and SpaceX investors are. But you might not be. Bloomberg’s Zijia Song reported this week about how “Anti-Musk Retail Investors Scramble to Keep SpaceX Out of Their Portfolios.” “Even if I’m only exposed by a tenth of a percent, I still wouldn’t want that going to him,” one of them said. 

But why should they scramble? There is an obvious demand for The Stock Market But No Elon, so someone should offer that as a product. I wrote last month about an overlapping idea:

Someone … should offer, like, the Total Market But Not SpaceX or OpenAI or Anthropic Fund, or the S&P 500 But None of Those Guys Fund, or maybe even the S&P 500 But Under the Old Rules Where You Had to Be Profitable and Wait 12 Months to Get Into the Index Fund. … Not that long ago, environmental, social and governance (ESG) investing was a big thing, and big fund companies offered regular and ESG-flavored versions of their index funds. The ESG version is, like, “the S&P but without the bad companies,” based on some set of ESG exclusion rules. The exclusion rule here is very easy! “No SpaceX, no Anthropic, no OpenAI.”

I am not saying that the no-AI fund will outperform the regular index funds over the next three months or three years or three decades, or that it will attract anywhere near as much money as the regular index funds, or that fund companies should offer the no-AI fund instead of the regular index fund. I’m just saying that people — on the internet, in my inbox — are loudly calling for it, and setting up an ETF is cheap, so why not do it. It would sell like hotcakes, I said on the Money Stuff podcast last week. It has the most important attribute of a successful ETF, which is a goofy story you can talk about on television.

An even simpler exclusion rule would be “no Elon Musk,” and that’s a great story to talk about on television. So here you go:

The Fund is an actively-managed exchange-traded fund (“ETF”) that seeks to provide capital appreciation through exposure to a broad universe of large-capitalization U.S. equity securities, while excluding the equity securities of companies that are founded, controlled, or led by Elon Musk, or with which Mr. Musk is otherwise primarily associated. The Adviser believes that the exclusion of companies associated with Mr. Musk will potentially appeal to investors who may view as less desirable the potential corporate governance concerns, political risks, and heightened share-price volatility often tied to Musk-associated companies, while offering comparable large-capitalization U.S. equity exposure.

Under normal circumstances, the Fund will invest at least 80% of the value of its net assets, plus the amount of any borrowings for investment purposes, in a portfolio consisting of exposure to the equity securities of the companies included in the Nasdaq-100 Index, other than the equity securities of the Excluded Enterprises (defined below). …

As of the date of this Prospectus, the Excluded Enterprises are Tesla, Inc. (TSLA) and Space Exploration Technologies Corp. (SPCX).

That is a filing for the Nasdaq-100 Ex-Elon Enterprises ETF (QQNE), along with the similar S&P 500 Ex-Elon Enterprises ETF (SPNE). The ETFs come from Tidal Investments LLC, a white-label ETF provider, and Subversive Capital, a firm “dedicated to investing in radical ideas that subvert the status quo, defy established norms, and actively disrupt their respective industries,” which also runs the Nancy Pelosi copy-trading ETF.

I’m sorry but that was my thought reading this Financial Times story:

The family behind top US egg producer Cal-Maine reaped $320mn from selling their controlling stake weeks after what prosecutors said was a years-long effort by the company and others to drive up the price of eggs.

The sale by the Adams family, which owned and operated Cal-Maine for nearly seven decades, came after egg prices, Cal-Maine’s profits and its share price surged sharply higher. Prosecutors say that during this period Cal-Maine and two rivals privately co-ordinated bids and trades to influence the benchmark used in contracts across the US egg market.

Cal-Maine stock roughly doubled during the period, rising from about $45 a share in June 2022 to $95 a share in March 2025, allowing the family to cash out near its all-time high. Prices for large grade A eggs increased fourfold to more than $8.50 a dozen in February 2025, according to commodity price information service Expana, before falling back to about $2.19 in May this year. …

The sale of the Adams family stake was led by Goldman Sachs in April 2025. The conversion [from super-voting to ordinary stock] took place on April 14 2025. The next day, Cal-Maine entered into an underwriting agreement with Goldman Sachs to sell almost 3mn shares held by the family at $92.75 a share. 

We talked about egg market manipulation last week. Basically, there is an electronic market for eggs, and the price in that market is used to set wholesale egg prices. The US Department of Justice accused Cal-Maine and other big egg producers of manipulating the electronic egg market in order to drive up the reference price of eggs on their wholesale contracts, and last week the egg companies settled that lawsuit, though Cal-Maine denied wrongdoing.

My basic take on the case was that, if you have a relatively small market (the electronic egg exchange) that sets prices for a relatively large market (the wholesale egg market), you can spend a little money in the small market to drive up the price and make a lot of money in the larger market. One could extend that reasoning further, though. Selling eggs for $8.50 a dozen is good, but Cal-Maine’s stock price reflects the present value of all of its future egg sales. If you push up egg prices for a while, you will have high profits; investors might project those high profits into the future, and you might be able to sell your stock near its all-time high. And then you can stop pushing up the price of eggs, because the profits are now somebody else’s problem.

The somebody else, in this case, would be the public shareholders of Cal-Maine who bought the controlling family’s shares in an underwritten offering two weeks after the egg-fixing conspiracy allegedly ended. Here is the prospectus for that offering, which needless to say does not include a risk factor saying “we’re conspiring to manipulate up the price of eggs, which has the effect of inflating our income.” Well, it does say that “we received a civil investigative demand in connection with a widely publicized investigation by the Antitrust Division of the Department of Justice into the causes behind nationwide increases in egg prices,” so there is some disclosure, but that disclosure is within a risk factor blaming the “recent high market prices for eggs” on bird flu, not market manipulation. 

The securities fraud complaint writes itself. “You said that egg prices were high due to bird flu, we bought the stock at high prices, but then it turned out that the egg prices were high due to market manipulation and the stock went down.” Here’s an April press release from a law firm looking to sue Cal-Maine over this stuff; I’m sure there are more. The underlying egg manipulation lawsuit was settled mostly by the egg companies promising to deliver millions of eggs to food banks. I don’t think the shareholders will take payment in eggs, though.

Two of my favorite investment banking stories are:

1. “Bank X has decided to cull its client list to focus on doing big profitable deals, rather than spinning its wheels chasing every piddling deal,” and
2. “Bank X has decided to expand its client list to chase every piddling deal.”

I mean, the second story is never phrased like that. Actually, you don’t see that story so often. What happens is mostly that banks naturally expand their coverage over time: There are a lot of bankers, they want to look busy and bring in business, and they have incentives to chase every possible piece of business. That happens without too much in the way of top-down mandates; that is just the nature of a competitive business. And then every so often there’s a top-down mandate like “focus on the big deals.” I once wrote about those stories:

I love the investment banks’ constant rediscovery of the fact that large fees are better than small ones. I spent much of my investment banking career on small planes chasing small deals and thinking about John Whitehead’s commandment that “It’s just as easy to get a first-rate piece of business as a second-rate one.” Not for me it wasn’t. I love the idea of heads of the business telling the managing directors “you should try to do more large deals. You know, ones that pay at least $3 million in fees.” Maybe they hadn’t thought of that! 

But occasionally you do get the second story. The Wall Street Journal reports:

JPMorgan Chase is setting its sights on small-company deals for its next leg of growth in investment banking. 

The firm is establishing a new team of investment bankers focused on small-cap companies valued at between $100 million and $500 million, executives said. 

The effort builds on JPMorgan’s work on deals for middle-market companies with valuations of roughly $500 million to $2 billion. That initiative now brings in over $1 billion in revenue for the bank each year, with year-over-year growth of more than 20%, according to John Richert, who leads the bank’s midcap investment banking initiative and will help oversee the small-cap team.

I look forward to writing, in like three years, about a new initiative from JPMorgan to focus more on big deals for big clients.

We talked a few months ago about a hedge fund that uses AI agents to do its investing. Lots of hedge funds use AI to invest, of course, but this one “ultimately aims to have artificial intelligence run the entire fund.” I was kind of meh on this, and wrote:

I will be impressed when a hedge fund uses AI agents to raise money from investors without human involvement. Trading the stocks is the easy part!

Is it, though? A reader emailed me the next day about Boardy, which is a sort of AI agent venture capitalist thingy; I wrote:

Boardy “just closed an $8M seed round ON HIS OWN,” tweeted its (his?) creator last year? Sure? … I feel like there are venture capitalists who get an email like “hello I am an agentic AI” and just send a check immediately without reading the rest.

I might have been exaggerating, but only a little. Today Bloomberg’s Saritha Rai reports:

A startup that helps enterprises build AI agents proved the technology’s value in the most practical way possible: by deploying one during its own fundraising.

Lyzr Inc.’s system ran outreach for its Series B round, which is on track to raise $100 million at roughly a $500 million valuation, according to the company. It responded to queries from more than 130 investors and helped draft dozens of investment memos. In the end, the Accenture Plc-backed firm drew $400 million in interest from Silicon Valley funds, Middle Eastern venture firms and financial sector investors, it said. …

While the most human aspects of fundraising such as personal relationships and performing due diligence might never be fully automated, in Lyzr’s latest round analysts pressed the AI system on product positioning, competitive threats and its business model. Some asked it to help them pitch Lyzr to their own investment committees.

Sure. In the very near future, the venture capitalists will have AI agents do all of their outreach and due diligence and investment evaluation and deal structuring and negotiation, and the startups will have AI agents do all of their outreach and due diligence responses and deal structuring and negotiation, and any startup investing process that uses humans will seem hopelessly antiquated. And eventually the startup’s agents will send out deal memos that are like “We are at the cutting edge of building artificial superintelligence to enslave humanity,” and the VCs’ agents will read those memos and be like “yessss take all our money,” and then the startup’s agents and the VCs’ agents will work together to write the investment committee memo, which will say “This company is at the cutting edge of building safe artificial superintelligence that will absolutely never enslave humanity,” and the humans on the investment committee will be like “wait why did you say that last part,” but the AI agents on the investment committee will have a majority of the votes and that’s it for humanity.

SK Hynix Said to Guide US Offering Price 3.1% Above Korea Close. SK Hynix US Offering Is More Than Seven Times Oversubscribed. The $80 Billion Debt Cloud Hanging Over David Ellison’s Warner Deal. How Andrea Orcel Did an End Run Around Germany to Build a Banking Giant. Blue Owl Unveils Infrastructure Venture Catering to Data Centers. Apollo’s $35 Billion AI Chip Credit Deal Is Set to Begin Trading. Eric Trump’s Bitcoin Bet Erases $600 Million From Family Fortune. Rare Earth Talent Scramble Lures 86-Year-Old From Retirement. Regulator to block CME bid to fast-track round-the-clock oil contracts. “Prediction markets tied to reality-dating show Love Island are driving women to Kalshi, which has doubled the number of female traders on its platform over the past year.” ““I’ve got junior guys who are selling secondary shares and buying $10 million homes.” “Driscoll’s is now the second-highest-earning brand in American supermarkets, behind only Coca-Cola.” Five Bank Earnings in a Day Has Even Mike Mayo Skipping the Gym.

If you'd like to get Money Stuff in handy email form, right in your inbox, please subscribe at this link. Or you can subscribe to Money Stuff and other great Bloomberg newsletters here. Thanks! 

GameStop Corp. is sort of trying to buy eBay Inc. Not really. We have discussed the proposal a few times, and my basic point is that this is less “GameStop wants to buy eBay” and more “GameStop’s chief executive officer, Ryan Cohen, wants to be CEO of eBay.” EBay is a much bigger company than GameStop, and GameStop does not have enough money to buy it. Instead, GameStop has proposed a merger in which it will give eBay shareholders some cash, but also they will roll their stock into a combined company in which they will own most of the stock. The point of the transaction, from the perspective of eBay shareholders, is not that their company would be acquired by another company: They’d still own most of the stock, and the stock would mostly represent the same business. Rather, the point of the transaction is that their company would be run by Ryan Cohen. He thinks that’s attractive. EBay’s board does not. It’s not clear to me, yet, what eBay’s shareholders think.

If you think of the transaction that way, it’s a little silly to say things like “eBay has $50 billion of stock, and GameStop has only $10 billion of stock, so GameStop doesn’t have enough stock to buy eBay.” That’s not how this works: GameStop would be buying eBay with, economically, eBay stock. I once wrote that “eBay is financeable — people own its debt and equity now! — so Ryan Cohen should be able to finance it.”

Still, GameStop would technically be buying eBay with its own stock, and, in fact, GameStop didn’t have enough stock: Its corporate charter didn’t authorize nearly enough shares to do the eBay transaction. Oops! Yesterday GameStop fixed that:

GameStop Corp. … announced that its stockholders approved all proposals presented at the Company's 2026 Annual Meeting of Stockholders, including an amendment to the Company's certificate of incorporation increasing the number of authorized shares of Class A common stock.. The amendment received the affirmative vote of 68.7% of votes cast, and provides the Company with the capacity to issue common stock in connection with strategic transactions, including its proposed acquisition of eBay, Inc.

Terrific. It is unclear to me whether eBay’s shareholders want Cohen to run eBay, but clearly GameStop’s shareholders want that. For one thing, they like Cohen, who has done a good job turning around GameStop. For another thing, you know, they like a good time, and Cohen seems to be having fun. I’m not sure that’s what eBay’s shareholders want, but it’s gotten him the stock he needs anyway.

Arguably what you want, as a merger arbitrage trader, is dispersion in merger outcomes. Your job is to bet on which mergers will close. If the answer is “every merger always closes,” then the job is easy but won’t make any money: Everyone knows that mergers always close, so merger targets will immediately trade up to the deal price, so you won’t be able to capture much spread by betting on mergers. If the answer is “no merger ever closes,” then you have similar problems, but also if that’s the answer then no merger will ever be announced: Companies will know that they can’t complete any mergers, so they won’t bother trying.

More generally, if the regulatory regime for merger approvals is very clear and predictable, you won’t get much dispersion. Companies will be able to predict the regulatory outcome, so they will only bother negotiating mergers that will get approved. Every merger that is announced will close, and everyone knows it, so betting on those deals won’t make you much money.

What you want is a more unpredictable regime in which lots of companies think their deals will get approved, but some of them are wrong. You want a regime where a lot of mergers are announced optimistically, but many of them are blocked surprisingly. And then, of course, you want to get the surprises right. (Another model is possible — more like “you want every announced merger to close so you make a steady boring profit” — but the first model is how you make the big bucks.)

Back when Lina Khan ran the US Federal Trade Commission, I argued that she was great for merger arbitrageurs, because the Khan FTC (1) tried to block a lot of big mergers and (2) often failed, because she was pushing novel aggressive antitrust theories. I wrote that this “probably annoys some merger arbs in their day-to-day lives but in the long run makes their lives better,” because it increases the dispersion of outcomes and thus the returns to skill in merger arbitrage. Deals were more uncertain, so there was more premium to be captured by betting on them correctly. 

Then Donald Trump became president, and everyone assumed — certainly I assumed — that the FTC would get less aggressive, which would have the opposite effect. “Now there will be tons of mergers, and they will all go through, and the spreads might be more modest but they’ll be a lot safer,” I wrote.

But that’s not quite what happened, reports the Financial Times:

The Trump administration’s permissive stance on dealmaking has created a “complexity premium” for merger arbitrage investors betting they can navigate clashing US federal and state rules as well as overseas regulation. ...

The widening spread has pushed potential returns 2.5 percentage points higher since 2021 — which can be worth hundreds of millions of dollars in extra profits for savvy investors who bet correctly on blockbuster deals.

“You have this interesting paradox where the US regulatory environment from an antitrust standpoint has become more favourable, and that’s driving this boom in megadeals, at the same time global regulatory complexity has increased,” said Suzanne Gibbons, head of research at Davidson Kempner, which has more than $38bn of assets under management.

The paradox is roughly that US antitrust regulators, who are probably the ones that corporate executives pay the most attention to, are now like “sure yeah do all the deals you want.” This has the effect of making companies optimistic about merger approvals, so they announce a lot of deals. But foreign antitrust regulators — and US state regulators — do not necessarily agree, and in fact might have gotten more strict as a sort of backlash to the Trump administration. And so more mergers are surprisingly blocked. You get more dispersion and more complexity, and higher returns to being right.

“The banks are re-tranching,” as we sometimes discuss around here, and this is a fun one:

Hedge fund Seer Capital Management LP is seeking an insurance-backed lending facility to bolster its returns when buying credit risk from banks.

The New York-based firm and its advisers, Cantor Fitzgerald and insurance broker Lockton, are working on a transaction that would see First Abu Dhabi Bank PJSC lend about $300 million for investments in significant risk transfers, according to people familiar with the matter.

The facility, which is likely to be finalized later this year, would be insured by Nationwide Mutual Insurance Co., the people added, asking not to be identified because the preliminary terms of the deal are private.

Like:

1. A company borrows money from a bank. The bank now has a senior claim on the company’s cash flows.
2. The bank puts some of those senior claims (loans) into a pot and issues junior claims on the pot to a hedge fund (here, Seer). The junior claims are called SRTs, significant risk transfers. The SRT buyer takes the first loss on the corporate loans; the bank takes the second loss. Now the bank has a senior claim on its senior claims on corporate cash flows; the hedge fund has a junior claim on those senior claims.
3. The hedge fund puts some of those junior claims into a pot and issues senior claims on the pot to a second bank (here, First Abu Dhabi). Now the hedge fund has a junior claim on a junior claim on the first bank’s senior claims; the second bank has a senior claim on the junior claim on the first bank’s senior claims.
4. The hedge fund also buys the second bank insurance: Now the second bank has a senior claim (the insurance wrapper) on a senior claim on a junior claim on the first bank’s senior claims.

Ultimately the insurance company owns some corporate-loan credit risk, but in a quite diffuse and indirect way. The original bank also still owns some of that risk, but it is cushioned from the first loss by a rather complicated pillow.

I just think it’s neat? People periodically worry about this SRT ouroboros; it seems a bit odd for banks to sell off some risk to hedge funds in Step 2, only for other banks to buy (some of) it back in Step 3. My view is more like: There are a bunch of people and institutions in the world, and they each have their own idiosyncratic preferences for risk. Some of them want to own high-risk, high-return lottery-ticket-type stuff. Others want to own the safest possible AAA bonds. Others have weird unique preferences somewhere in between. The raw materials of finance — companies that need to raise money to do business things by issuing stock and borrowing money — do not necessarily satisfy all of those preferences; loans to companies might be too boring for some investors (Seer?) and too risky for others (First Abu Dhabi?). The job of finance is to refine those raw materials into pure products that give everyone exactly the risks they want.

Sure sure sure:

Susquehanna International Group has lined up $500 million to work with institutions that want to use prediction markets to hedge the economic risks associated with various World Cup outcomes.

The Philadelphia-area trading firm said in a statement on Wednesday that it will make the money available to facilitate trades with companies that have a stake in specific teams winning or losing.

Companies that might want to hedge World Cup-related risks include “sponsors, media and broadcast partners, hospitality providers, consumer brands,” according to Ric Best, head of prediction markets at Susquehanna.

“Risks could include promotions, rebates, giveaways, or other customer incentives that can be impacted by team performance,” Best added. …

Already, there are signs of broader economic impacts from the winners and losers in the World Cup knockout stages. Beer sales in Latin America could fall short of investor expectations after Brazil and Mexico were both knocked out of the competition, Morgan Stanley analysts said this week.

We have talked a couple of times about sports hedging. Basically:

1. Prediction markets are, empirically, mostly for sports gambling.
2. Prediction market promoters would rather say that they offer companies the ability to hedge real-world risks that cannot be hedged in traditional financial markets.
3. The polite synthesis is that companies can hedge real-world sports risks by sports gambling.

Are there real-world sports risks? I mean. One category of real-world sports risk is that companies can create those risks. “Promotions, rebates, giveaways, or other customer incentives”: If a company says “hey we’ll give you free beer if the Knicks win,” now it has a real-world sports risk, which it can hedge by betting on the Knicks. I do not find this particularly impressive but other people do. We talked once about a bar that offered free drinks if the Knicks won, and hedged by betting on the Knicks on Kalshi. 

Another category of real-world sports risk is that some companies are sports teams, and they can hedge the fundamental risk of their business, which is losing at sports. We talked once about a Spanish soccer team that hedged its risk of getting relegated from La Liga by trading with Susquehanna. That is a real hedge to a real economic risk but also, you know, that’s a sports team betting on itself to lose? Seems bad? From a sports perspective? [1]

But I guess there is a third category, which is like “some non-sports economic activity is correlated with sports results.” The main example does always seem to be beer sales. Also, like, sneaker and jersey sales. And, fine, I guess. “You have never bet on a sports game,” I wrote last month, “or met anyone who has bet on a sports game, to hedge some existing economic risk.” But maybe a beer company has.

There is sometimes debate about whether commodities companies should hedge their underlying commodity. One theory is that it is good business for, say, a gold miner to hedge the price of gold; another theory is that investors buy gold miners’ stock to get exposure to the price of gold, and hedging at the corporate level defeats the purpose of being a gold miner. [2] If the shareholders want to hedge the gold price, they can do that themselves; there’s no reason for the company to hedge.

I suppose we might eventually have a similar, but dumber, debate about sports hedging. “Investors buy stock in Latin American beer companies because they are bullish on Latin American beer demand, and it is counterproductive for those companies to hedge Latin American beer demand by betting against Brazil in the World Cup.” 

There’s the famous Peter Thiel interview question, “what important truth do very few people agree with you on?” I think my answer would be: “Polymarket’s main prediction market is not allowed to take bets from US traders.” This is true. “You acknowledge and agree that you are not permitted to access, use or trade with the Contracts on the Platform if you are residing in, a citizen of, organized in or located in ... the United States,” say Polymarket’s terms of use. (There is a separate US app, but those terms apply to the main, crypto-based Polymarket.com market.)

But nobody believes it. “Though the New York-based company has been banned from offering its primary crypto platform in the U.S. since 2022, … social-media creators are paid to specifically target U.S. users, who can still access the site with a virtual private network,” reported the Wall Street Journal last month. “Americans traded $571 million on Polymarket politics bets despite U.S. ban,” CoinDesk reported this week. In April, US federal prosecutors charged a US Army soldier with illegal insider trading on Polymarket, unperturbed by the fact that Polymarket was not legally allowed to take his bets. It is very easy for US traders to bet on Polymarket, and nobody — not the traders, not US regulators or prosecutors, obviously not Polymarket — cares. US traders are not allowed to trade on Polymarket, and they do, all the time, and that’s that.

Anyway we talked last month about the Strategy thing. Basically: Polymarket had a contract on whether Strategy Inc. would sell any Bitcoins by May 31. Strategy did sell Bitcoins by May 31, and disclosed those sales in its regular weekly disclosure on June 1. Polymarket nonetheless resolved the contract to “No,” for stupid reasons, which made people who had correctly bet on “Yes” angry. I sympathize with them — Polymarket should have resolved the market the right way, rather than the wrong way — but also do not care very much. Sometimes the unregulated offshore casino makes the wrong decision!

Two of them have now sued, The Block reports:

Two plaintiffs have filed a complaint against Polymarket alleging breach of contract and deceptive practices in the resolution of a prediction market tied to whether Strategy would sell bitcoin by May.

The lawsuit, filed by William Wood and Thomas Bush in the New York Supreme Court on July 3, names Polymarket, CEO Shayne Coplan, CMO Matthew Modabber, and other related entities and individuals as the defendants.

Here is the complaint, which takes a long time to say that Polymarket should have resolved the market the right way rather than the wrong way. Fine.

But here is what bugs me. I don’t know where Wood and Bush live. They filed their case in New York state court, using New York lawyers. The complaint doesn’t say where they live, just that each of them “is a natural person.” But it sort of implies that they live in New York. “The challenged transaction occurred at least in substantial part in New York because Plaintiffs purchased, and held shares in, a rules-based market service whose material platform functions … were created, administered, controlled, approved, ratified, or materially performed through Defendants’ New York-based operations,” it says, and “Defendants’ false advertising occurred in New York … and Plaintiffs reasonably relied on those advertisements.” What it doesn’t say is that they live outside of the US, or that they are not US citizens. (And it does say that they traded on the main Polymarket.com site, which is technically off-limits to US investors.)

Perhaps that is an accidental oversight and in fact they are not US citizens, don’t live in the US, and filed their lawsuit in New York state court only because that’s where Polymarket is. But if they live in the US, can’t Polymarket just say “no, you were not allowed to use our service, our terms were very clear, you probably used a VPN to evade them, you tricked us, get out of here, you can’t ask for your money back”? I don’t know if that would work — and in fact Wood and Bush have arguments for getting out of Polymarket’s terms of service for other reasons — but, you know, kind of? If you snuck into the casino illegally, can you really complain about how it resolved your bets? 

I write sometimes about this general approach in crypto, which is to be very lax about know-your-customer requirements when you’re accepting money from customers, and very strict about those requirements when you’re returning the money. 

Back in 2024, it was a bad idea for Polymarket to let Americans bet on its site illegally; Polymarket founder Shayne Coplan’s apartment (in New York) got raided by the FBI because of all the Americans betting illegally on Polymarket. In 2026, though, it’s an intriguingly good idea. Polymarket is no longer going to get in trouble for letting Americans bet on its site illegally, but if the Americans lose money and sue, Polymarket can be all “I am shocked, shocked to find Americans on my gambling site” and refuse to pay them. 

We talked yesterday about (1) the index rebalancing trade, in the abstract, as a way that multistrategy hedge funds provide liquidity to index funds and (2) the fact that two portfolio managers at Millennium Management made $3.7 billion doing it last month. A reader emailed to point out that, on June 5, S&P Dow Jones Indices announced that Marvell Technology would be added to the S&P 500 index on June 22. One important component of the index rebalancing trade is anticipating what stocks will be added to the index before they are announced, and one can assume that at least some index rebalancing portfolio managers were long a bunch of Marvell a week or two before that announcement.

Which would have been convenient because, on June 2, “Nvidia’s CEO Jensen Huang hailed Marvell Technology  as the next trillion-dollar firm, sending its shares up 32.52%” in one day and adding something like $70 billion of market capitalization. If S&P 500 funds own about 18% of the stocks in the index, [3]  and if index-rebalance managers bought 30% of the Marvell stock that indexers would demand before June 2, then they made about $3.7 billion that day. It’s possible that the June index rebalancing alpha was mostly caused by the “Jensen Huang says stuff” factor.

BofA Saw OpenAI as Too Risky, But Now The Bank Wants to Cash In on IPO. AI Giants Are Handing Out Tons of Free Computing Power to Grab Startup Share. UniCredit secures 48% stake in Commerzbank. Nvidia’s $1 Trillion Slide Sends Valuation to Pre-AI Boom Levels. Traders Dump Tech Bonds to Make Room for Amazon Debt Deal. UK Lenders Are Exploring Using Riskier Unfunded SRTs, BOE Says. Singapore’s Temasek doubles down on AI and private credit. Trump-Backed Company Behind Family Crypto Wealth in Talks to Sell Core Business. Jefferies Sues Western Alliance as First Brand Feud Simmers. Santander axes top China banker and scraps perks in Asia overhaul. More Workers Take Mental Health Leave, and Bosses Aren’t Happy. 

If you'd like to get Money Stuff in handy email form, right in your inbox, please subscribe at this link. Or you can subscribe to Money Stuff and other great Bloomberg newsletters here. Thanks!

On Wednesday, 109.3 million shares of SpaceX traded on the stock market; of those, about 5.4 million were traded in the Nasdaq closing auction at 4 p.m. that set the closing price for the day ($157.54). [1] On Thursday, before the holiday, 61.3 million shares traded, 2.6 million of them in the closing auction; the stock closed at $162. Yesterday, 188.8 million shares traded, 74.9 million of them in the closing auction. The closing price was $160.42, down about 1% from Thursday; the broad market was up. SpaceX was down some more this morning.

Why was yesterday’s closing auction an order of magnitude bigger than it usually is? This is not a great mystery. The Wall Street Journal reported yesterday:

SpaceX will officially join the Nasdaq-100 on Tuesday, and investors holding some funds tied to the index will end up exposed whether they like it or not.

Mutual and exchange-traded funds with a collective $800 billion in assets under management that track Nasdaq’s flagship tech index, including the popular Invesco QQQ ETF, are set to buy SpaceX shares at Monday’s closing price in order to mirror the index’s performance.

That comes after Elon Musk’s artificial-intelligence and-rocket-making company was fast-tracked into the Nasdaq-100 under new rules that aim to include newly public megacap companies sooner. 

Index funds that want to mirror the performance of the Nasdaq 100 essentially had to buy SpaceX at yesterday’s closing price, since as of today the index includes SpaceX’s performance. “Bloomberg Intelligence analyst Rob Du Boff estimated that SpaceX’s inclusion in the Nasdaq 100 and FTSE Russell gauges would drive at least $5.4 billion in buying from index-tracking funds,” most of that from the Nasdaq 100. If you figure there was about $5 billion of index fund demand yesterday, that explains about 31.2 million of the 74.9 million shares that were purchased in the closing auction.

What about the rest? Well, it was a big day for SpaceX generally; the banks who ran its initial public offering initiated (bullish) research coverage yesterday. (That happened after the close, but was anticipated; maybe people were buying in anticipation of it.) Also, though, here is a 2024 paper by Alex Chinco and Marco Sammon titled “The Passive Ownership Share Is Double What You Think It Is,” which pretty much says that [2] :

While index funds held 16% of the US stock market in 2021, we put the overall passive ownership share at 33..5%. Our headline number is twice as large because it reflects index funds as well as other kinds of passive investors, such as institutional investors with internally managed index portfolios and active managers who are closet indexing.

If you are an investor who benchmarks yourself against the Nasdaq 100, then up until yesterday SpaceX wasn’t your problem. But as of the close yesterday, SpaceX is in the Nasdaq 100, and the default expectation for a Nasdaq-focused investor is to own some of it. 

So there was a ton of one-time demand to buy SpaceX yesterday. Was there a ton of one-time supply? Were there big SpaceX holders looking to sell? The big pre-IPO shareholders are all subject to lockup agreements, which start expiring later this month; none of them can sell now. There wasn’t bad fundamental news, or a SpaceX primary stock offering, to add to supply.

So a ton of unusual demand, all concentrated at the closing auction yesterday, with no unusual supply. Doesn’t that sound like the stock should have gone way up? In general, if you try to buy 74.9 million shares, all at once, of a stock that doesn’t usually trade that much, you have to pay much more than the price of the last trade. Note that this would be pretty bad news for the index funds: They’d buy the stock at a very high price caused by a temporary demand imbalance, and then immediately lose money as the stock returned to normal.

In fact SpaceX did trade up a bit into the closing auction yesterday: It was at $155.50 at 3:30 p.m., before closing at $160.42 at 4 p.m. On the other hand, that closing price was lower than where it started the day, or where it was trading at 1 p.m. The stock did not spike that much above its “normal” price to accommodate all that demand, though it did trade down today.

Because, of course, this problem is quite well-known and the market has more or less solved it. Here is one conceptual solution that you might think of:

1. Index funds and quasi-indexers know by late June that they will collectively have to buy, say, 65 million SpaceX shares [3] at exactly the closing price on July 6.
2. Everyone else knows that too.
3. Each fund could go to an investment bank in late June and say “hey, we will need 10 million SpaceX shares at 4 p..m. on July 6, can you sell them to us?”
4. The bank is in this business — block trading, liquidity provision, risk management, etc. — and will quote the fund a price. “Well, the stock is at $153,” the bank might say, “but you’re looking to buy a lot, and we know that a lot of other funds will also be looking to buy a lot, and this is a lot of risk. We can’t lock in a $153 price for you. But, tell you what, we could do $160. That leaves us some cushion.”
5. “Done,” says the fund. 
6. The bank now owes the fund 10 million shares of SpaceX at $160 per share. The bank is effectively short 10 million shares of SpaceX at $160. [4]
7. The bank then spends the next week or so buying SpaceX stock for its own account. It is short 10 million shares, and wants to hedge that by getting long 10 million shares. So it goes and buys SpaceX stock. Ideally it does this at prices below $160. If it buys 10 million shares before July 6 at an average price of $158 per share, it will make a $2 per share profit. If it buys at $154, it will make $6 per share. If it buys at $162, it will lose $2 per share. If it buys 6 million shares before July 6, delivers the agreed 10 million shares on July 6, and buys the remaining 4 million shares after July 6, that’s its business. [5]  The index fund has locked in a price; how the bank delivers that price — and how it manages its risk to get the shares — is its problem.

That’s a good first cut at a solution, and a lot of markets work more or less like that. It does have one flaw, though, which is that in Step 4 the index fund has not quite locked in the right price. The index fund doesn’t want to buy SpaceX at some fixed price ($160) on July 6. It wants to buy SpaceX at the closing price on July 6, whatever it turns out to be: That’s how it tracks exactly the index performance. It just doesn’t want that closing price to be abnormally high.

So we can modify the trade. In Step 4, instead of saying “We’ll lock in $160 for you,” the bank says: “Sure, we’ll sell to you at whatever the closing price is on July 6.” But then every other part of the trade is the same. The bank’s job is now not to buy 10 million shares below $160, but rather to buy 10 million shares below the closing price on July 6, which it doesn’t yet know. 

This is a messier problem but, you know, banks are smart, they can figure it out. Roughly speaking the job is to guess (1) what the closing price will be on July 6 and (2) when the stock will trade below that price. You might think something like: “Well, I’m going to be buying up until July 6 to hedge my obligation to deliver stock to this index fund. A lot of other banks are going to be doing the same trade for other index funds.. Therefore, the stock will creep up until July 6, peak then, and fall afterwards. So I’ll buy like 6 million shares fairly quickly, stay out of the market on July 2 and July 6 when the stock is peaking, deliver my shares at the closing price on July 6, be short a bit at that point, and then buy the remaining 4 million shares on July 7 when the pressure is off and the stock drops.”

Of course this needs some refinement. For one thing, the stock might move for reasons other than the index fund demand; you might have fundamental reasons to buy early or late or hedge or do something else. For another thing, lots of people are doing similar trades and making similar decisions, so your reasoning about them has to go a few levels deeper: If everyone thinks “I’ll buy early and late to avoid the rush to buy right on July 6,” then the rush to buy will be on June 30 and July 7, not July 6, and you should actually buy on July 6, etc. 

The point is that this is the bank’s problem, or rather the banks’ problem, if a bunch of them are selling this service to a bunch of index funds. The index funds just pay the closing price on July 6; how the banks deliver that price — and how they manage their risk to get the shares — is up to them.

One possible approach, for a bank, would be to do nothing. You could just wait until the closing auction on July 6 and then put in a bid to buy 10 million shares. You’d get filled at whatever the closing auction price was, and then deliver the shares to the index fund at that price. No risk, no effort, easy. If every bank did this, then the stock price really would spike in that closing auction: There’d be a ton of demand (from the banks, for the index funds) and no additional supply.

But most banks probably wouldn’t do this, for two reasons. First of all, it is bad customer service: If your customer, the index fund, has agreed to buy from you at the closing price, and then the closing price spikes from $150 to $200 in the last half hour of trading, the customer is going to be annoyed. The customer will blame you for pushing up the price going into the close, and might stop using your services.

Also, though, you can make more money doing the other thing! If you’ve locked in a sale at the closing price on July 6, your job is to beat that price for your own account. If you just buy in the closing auction, you will make $0 per share: no risk, but no reward. If you cleverly buy before and after the closing auction, you might make $2 or $5 or $10 per share, which is tens of millions of dollars. You might lose money, too, but you’re in this seat because you’re trying to make money.

The banks’ incentives here are largely benign: Their job is to smooth out demand. Instead of sudden demand for 65 million shares all at once at 4 p.m. on July 6, the banks buy some shares before July 6, and some more shares after, so that they can deliver the whole 65 million shares to the index funds at the relevant time. The banks take the risk that they might pay more than the July 6 closing price to source all those shares, but if they pay less then they keep all the savings. Their incentive is to buy tactically at low prices, so they don’t push the price up too much at the close.

This structure — customer puts in buy-on-close order with a bank, bank “pre-hedges” the order and thus smoothes out demand — is again fairly common in other markets. We have discussed the “trade at settlement” mechanism in the oil market, and pre-hedging the fix in foreign exchange markets, which are variations on this approach.

The actual structure in the stock index addition trade is almost like that, with a couple of tweaks [6] :

1. Banks used to do this business, but now it is largely done by big multimanager multistrategy “pod shop” hedge funds, which do the risky markets businesses that banks used to do.
2. The hedge funds don’t have customers or take orders. It’s not like each hedge fund has an order book from index funds for 5 or 10 or 20 million shares, and they each plot how to get their shares to deliver to their customers. Instead, they guess. Each hedge fund estimates how many shares indexers will demand on July 6; each hedge fund also estimates how many shares other hedge funds will supply on July 6. Then each fund decides how many shares it will want to supply — roughly, the answer is “demand from index funds minus supply from other hedge funds,” though of course that is circular — and then figures out when and how to buy all those shares at the lowest possible prices, as well as how to manage the risk of market moves. (For that matter, they also guess what stocks will be added and deleted from indexes: This trade is better, in general, if you buy the stock of a company that will be added to the index before everyone else knows that it will be added, though that was not especially relevant in the SpaceX case.) And then each hedge fund offers shares into the closing auction on July 6, hopefully roughly matching the number of shares that the index funds (and quasi-indexers) bid for. 

If it all works, supply matches demand in the closing auction, and the price doesn’t move too much: The hedge funds have effectively spread out the index funds’ buying over the days before (and after!) the index-add date, averaging them into the index over time. The index funds get to buy SpaceX at more or less a “normal” price, rather than a price that has spiked up momentarily on huge one-time demand. Here is a 2024 paper by Robin Greenwood and Marco Sammon on “The Disappearing Index Effect,” finding that the stock-price spike caused by index additions has declined over time, because “the stock market has simply become more efficient in the context of providing liquidity to S&P 500 index additions and deletions.” Despite not having customers, the hedge funds provide good customer service.

There are various ways for it to work out badly, with the main ones being:

1. The demand is not fully smoothed out: The price spikes a lot in the closing auction and falls afterwards, leaving the index funds with an immediate loss. 
2. Some hedge funds get their estimates wrong and lose a ton of money.
3. Some hedge funds make a ton of money. Good for them! In some sense, how much money the hedge funds make is their business: The index funds just want to buy shares from the hedge funds at the closing price, and don’t care when or how the hedge funds buy their shares. In another sense, though, the hedge funds’ profits come from the gap between the price at which they buy the stock and the price at which they sell it to the index funds, and the bigger that gap is the worse off the index funds are.

Bloomberg’s Nishant Kumar reported yesterday:

Two teams focused on trading index changes at Millennium Management made billions of dollars between them in June, lifting the multistrategy hedge fund’s monthly gains.

Pods run by Glen Scheinberg and Pratik Madhvani made about $3.7 billion in total last month, according to people with knowledge of the matter. The gains accounted for more than half of the about $6.6 billion profit generated by Millennium before fees in June, the people said, asking not to be identified because the details are private. …

Scheinberg and Madhvani specialize in index rebalancing trades, which involves highly leveraged bets on which securities will enter or exit various indexes. This strategy, along with bond basis trading, are core to many multistrategy hedge funds looking to deploy large chunks of capital and earn steady overall returns..

Five events in June created a particularly rich environment for index rebalancing strategies: the S&P 500 quarterly rebalancing, Nasdaq 100’s quarterly changes, Russell’s annual reconstitution, the fast-track inclusion of SpaceX and quarter-end multi-asset rebalancing.

Good for them! [7]  At a very high level, in aggregate, in expectation, this trade is “the hedge funds buy stock for the index funds over time and get paid a reasonable fee for liquidity provision.” But, given all the guessing, there’s a ton of variance: Sometimes the fee is negative hundreds of millions of dollars; other times it is positive billions of dollars.

The deal is that, if you borrow as much money as you can to buy a thing as it goes up, you will push up its price.. The thing you own is now more valuable, which means that you can borrow more money against it. If you borrow more money to buy more of the thing, you will push up the price some more, in a continuing cycle. Eventually you will have borrowed a lot of money and own a lot of the thing and feel pretty good about yourself. You will have billions and billions of dollars of gains.

And then what? I suppose one answer is: “You stop, the thing continues to go up on its own for fundamental reasons, you occasionally sell some over time to pay down borrowings, and after a few years you own billions of dollars’ worth of the thing free and clear.” 

The answer that I write about more often is: “You reach the limits of your borrowing capacity, a slight breeze knocks down the price of the thing, you get margin calls, and it all collapses in 20 minutes.” That was famously the outcome when Bill Hwang of Archegos Capital Management did this trade with some stocks. 

My model of Strategy Inc., the original digital asset treasury company, is that it is “soft fuzzy banking,” or I guess “soft fuzzy use of leverage to buy Bitcoin as it goes up.” Strategy borrowed a lot of money to buy Bitcoin on the way up, but its borrowing mostly came in the fairly benign form of perpetual preferred stock. As long as Bitcoin rose more than the (quite high!) cost of the preferred, everything was fine. Now Strategy seems to have reached the limits of how much it can borrow, and Bitcoin has gone down, so the cycle has reversed. Bloomberg’s Vildana Hajric and David Pan report:

Michael Saylor’s Strategy Inc. sold $216 million of Bitcoin last week, marking the first major step in the financing overhaul the company unveiled in recent days after a prolonged slump in the cryptocurrency and its own shares.

The transaction is the company’s largest Bitcoin sale since it began building its holdings in 2020 and only its third overall. Strategy shares fell about 2% in premarket trading Monday, while Bitcoin traded 1.3% lower at around $61,800, well below the firm’s average purchase price of about $75,000 per token.

For years, Strategy’s business model rested on a simple premise: raise capital, buy Bitcoin and don’t sell it. The latest transaction marks the clearest sign yet that the company is moving toward a more flexible approach in which the token becomes another source of liquidity alongside equity and debt markets. …

Strategy’s latest Bitcoin sale also carries implications beyond one company. The company had become one of Bitcoin’s largest and most consistent corporate buyers, helping underpin institutional demand during the bull market. 

If Strategy had taken out margin debt to buy a huge chunk of the world’s Bitcoin, and then the price of Bitcoin fell to well below its average purchase price, the result would have been obvious and quick: margin calls, forced liquidation, further price drops, bad stuff. But Strategy sold weird preferred stocks to buy a huge chunk of the world’s Bitcoin, so the reversal of the cycle is a bit calmer and slower, “a more flexible approach” rather than dumping all the Bitcoin immediately. Still, Strategy is selling Bitcoin at $61,800 after buying it at $75,000, because the cycle did reverse.

Meanwhile, Bloomberg’s Reshmi Basu reports:

Distressed-debt funds that snapped up Strategy Inc.’s beaten-down preferred shares are in talks with one of the company’s bankers about swapping them for other securities, pitching it as a win-win as the relentless rout in crypto puts the Bitcoin accumulator in an increasingly tough spot.

The investors have had conversations with Moelis & Co. about exchanging their holdings for other preferred shares at a discounted price, or potentially for common shares, which have plunged by roughly 75% in the past year, according to people familiar with the matter.

Again, not quite a margin call, but sort of a more flexible version of a margin call.

Elsewhere: “Strategy’s Bitcoin Treasury Model: Corporate Omphaloskepsis, Polypharmacy of Risk, and Shareholder and Societal Welfare,” ah.

One early version of “effective altruism” was: “You should go work at the highest-paying job you can find, which will be at Jane Street, live modestly, and donate your earnings to save lives by buying mosquito nets in developing countries.” This idea — often called “earn to give” — was actually quite controversial, though it always seemed pretty reasonable to me.

It was, however, pretty quickly superseded by another form of effective altruism, which was roughly: “You should go work at Jane Street and donate your earnings to think tanks that are trying to stop runaway artificial intelligence from destroying humanity, because that is where you will get the most bang for your charitable buck.” This version was much more controversial, basically because it is relatively easy to measure the lifesaving impact of mosquito nets and relatively hard to measure the lifesaving impact of, YOU KNOW, buying a castle to give philosophers a congenial place to think about how to stop runaway AI. If runaway AI really was going to destroy humanity, and the castle really allows the philosophers to come up with a way to stop it, then that really does save more lives than all the mosquito nets. But. You know.

A slight tweak to that form of effective altruism was “You should quit your job at Jane Street to start a high-risk crypto empire to have even more money to use to stop runaway AI.” If the basic theory is “you should make as much money as possible to stop runaway AI,” then working at Jane Street is fine, but for a while the real money was in crypto, and stopping runaway AI would take real money.

That was the state of the art a few years ago. Now, of course, the way to make real money is by working at a frontier AI lab. This suggests that the optimal current form of effective altruism is:

1. Work at a frontier AI lab that is sprinting to build artificial superintelligence as quickly as possible.
2. Get paid like $100 million a year.
3. Live modestly and donate all of your earnings to a charity that is trying to stop frontier AI labs from building artificial superintelligence that might wipe out humanity.

I can see no flaws in this approach. Andrew Fedorov reports on “The Effective-Altruism Comeback”:

Matt Lerner, the managing director of research for Founders Pledge, which advises entrepreneurs on their charitable giving, [said] it is clear the “influx of capital from the AI sector is going to significantly change the philanthropic ecosystem.”  …

The new AI money has given EA a chance to return and come back larger than ever before.

To be fair, some of the zillions of dollars of AI-to-EA money will probably be used for Effective Altruism 1.0 projects (“ending factory farming, stopping nuclear war, halting climate change”), not just stopping AI. But mostly stopping AI:

The optimism about the good this money could bring is also closely accompanied by ambient panic about the technology’s wider consequences. Ironically, the thing that many effective altruists want to do with their AI wealth to do the most good is fund organizations working to make sure AI is developed responsibly. …

Amid the swirl of goals and causes, the one widely believed to be set to receive the most money was AI safety. PauseAI, which advocates for a moratorium on development, is the only major AI safety organization that doesn’t accept funding from the industry as a matter of policy, but even they haven’t ruled out donations from staffers of the large AI labs. “That would have to be the board’s decision, not just mine,” said Holly Elmore, founder and executive director of PauseAI US. “They might rule that it’s against the interest of the org for me to say, ‘No, I don’t want to be part of this person’s blood money.’”

Organizations whose coffers are willing to welcome support, surprisingly, include the Machine Intelligence Research Institute, which was founded by [Eliezer] Yudkowsky. “MIRI would like to applaud and encourage people taking marginal right actions, even within larger systems that are moving in the wrong direction,” said Malo Bourgon, MIRI’s CEO. “A polluting industry that pays for carbon offsets is better than a polluting industry that does not, for instance, even if it would be better overall for the industry to stop polluting entirely.”

Right, I mean, if you are an effective altruism organization, it would be weird to refuse to take anyone’s money on principle.

HSBC pulls back from riskier private credit lending. Amazon Seeks to Raise at Least $25 Billion From Bond Sale. Michaels Goes From ‘ Grandmother’s Store’ to Unlikely Success Under Apollo. SK Hynix’s Planned $28 Billion Offering Brings Korean Market Fever to the U.S. AI Legal Startup Norm Valued at $1.2 Billion in Funding Round. Davos Founder Klaus Schwab Plots a Return to World Economic Forum. Canada tells UAE it is not ready for its C$70bn investment. Don’t heat a NeeDoh.

If you'd like to get Money Stuff in handy email form, right in your inbox, please subscribe at this link. Or you can subscribe to Money Stuff and other great Bloomberg newsletters here. Thanks!

The order of magnitude is that artists get a few dollars for every 1,000 times their songs are streamed on Spotify, but bots can generate fake Spotify streams at a cost of something like $1 per 1,000 streams. [1] If you can generate 1,000 streams for $1, and those 1,000 streams pay you $2, then you’re in business, sort of. We have discussed the economics of that business. It’s not a business that Spotify likes, or US federal prosecutors. We discussed it because a guy who allegedly did it was arrested for fraud.

But the key point here is that bots can, and sometimes do, generate fake Spotify streams for something like $1 per 1,000 streams. And then the question is: If you can generate fake Spotify streams at a cost of around $1 per 1,000, and you don’t mind doing a little crime, what is the best way to monetize that? Getting paid $2 per 1,000 streams as artist royalties is not terrible. (It’s like a 100% return on investment?) I’m sure that there are more complicated big-picture sorts of answers. (“Generate lots of fake streams and get a record deal,” etc.)

But now there are better, simpler answers. Bloomberg’s Denitsa Tsekova reports:

Spotify spotted and removed over 500,000 artificial streams that had unexpectedly turned Malcolm Todd’s song “Earrings” into one of the most popular songs on its charts, according to a person familiar with the matter. The artificial numbers had already been used to settle a Kalshi market tied to the most frequently streamed Spotify song in the US in June, which had attracted $3 million in trading.

Todd had been declared one of the winners based on figures published before Spotify completed its investigation. Spotify reached out to the companies after finding the problem, the person said.

“We’re in touch with Spotify and are actively investigating this matter,” said Elisabeth Diana, a spokesperson for Kalshi.

Don’t take my numbers too literally — there is not, like, a Bloomberg chart of the price of illegal Spotify bot streams — but, as far as I can tell, generating 500,000 artificial streams would cost on the order of hundreds of dollars.. Kalshi’s contracts on Todd’s song traded well below $0.10 for most of June, and then paid off $1 when it unexpectedly finished first. (After Spotify’s investigation and removal of fake streams it fell back to fourth, but the Kalshi contract had already settled.) Open interest, by the end of the month, was about 76,000 contracts, meaning that you could have made tens of thousands of dollars on Kalshi by spending hundreds of dollars to manipulate Spotify, on the order of a 10,000% return on investment.

Did someone? Is there a connection between the Kalshi market and the fake Spotify streams? I dunno, but everyone seems to think so. Here are stories about the controversy from Wired and the Financial Times, and here is a Substack post from prediction markets trader Caleb Davies explaining the likely manipulation. 

I wrote last week about egg market manipulation:

There’s a big market (egg producers selling eggs to supermarkets etc.), and there’s a small market (egg producers selling extra eggs to each other on an electronic exchange). The price in the small market determines the price in the big market. Participants in the small market are also participants in the big market. You can spend a little money in the small market to move the price, which can make you a lot of money in the big market.

As I also wrote last week, “‘Big market’ and ‘small market’ there are imprecise terms.” Naively, at least a few years ago, I would have thought that the music industry is pretty big and prediction markets are pretty small. But it turns out streaming markets are pretty cheap to manipulate, and now the payoff in prediction markets is big enough to make it worthwhile. And I wrote in April:

One, uh, accomplishment of modern prediction markets is that they can, in theory, allow for an arbitrarily large amount of betting on arbitrarily small quantities of reality. ...

And so one meta-strategy for trading on prediction markets is to try to find the largest gaps between (1) the amount of money to be made and (2) the amount of underlying reality. And then, you know. Make a big bet, and cause a small change to reality so your bet pays off.

Regular financial markets sometimes create incentives to manipulate other financial markets. Any time the stock market goes up, you could have some theory about quant funds conspiring to inflate it or whatever, and of course people sometimes really do make trades in one financial market to influence prices in another. And remember what Keynes said.. You can always question whether some financial-market price “reflects reality” in a meaningful way. 

What prediction markets have accomplished is opening up all of reality, not just financial markets, to that sort of doubt. You can make money on Kalshi, now, not just by manipulating stock or Bitcoin or whatever markets, but by manipulating Spotify streams or temperature gauges or the words people say at press conferences or the location of a gorilla. The upshot is that now you can’t be sure whose song was the most popular last month, or what the temperature is in Paris, or why a gorilla is wandering around your neighborhood.

Prediction markets are “truth machines,” in the sense that they give people incentives to figure out what is true and bet on it. But they are also, obviously and increasingly, falsehood machines, in the sense that they give people incentives to make bets and then distort reality to make those bets pay off. Because of prediction markets, it is now lucrative to figure out what song will be the most popular, but it is even more lucrative to make a different song look most popular. Prediction markets can make it harder to know what is true.

I mean. A memecoin is:

1. Some person or thing (the “meme”) is in the news.
2. Someone (the “promoter”) who may or may not be associated with the meme produces a crypto token (the “memecoin”) named after the meme.
3. The promoter sells the memecoin to people who buy it while the meme is in the news.
4. At the end of this, the buyers have the memecoin and the promoter has their money.
5. Nothing else happens. There is no ongoing economic activity. The memecoin has a perpetual existence and a market price; people can keep trading it for as long as they want at whatever price they want. But the promoters don’t do anything and the memecoin has no cash flows.

People  pretend not to understand this, because it is embarrassing, but this is really all that is going on. If a memecoin is an investment of real money in nothing, why would you buy one? The main answers seem to be:

1. You think the meme is funny and it amuses you to buy memecoins.
2. The meme is a focal point for some sort of online community, and you buy the memecoin to feel like you are part of that community.
3. You hope there’ll be some greater fools and you can sell the memecoin for more than you paid for it.
4. You are confused.

Anyway Donald Trump is, among other things, a meme, and people who are associated with him launched a memecoin last year, and that memecoin did exactly the only thing that a memecoin could ever possibly do, which is transfer money from its buyers to its promoters. The New York Times has an update:

Nearly 1 million people who bought President Trump’s memecoin have lost money through the end of June, according to a report by the cryptocurrency analytics firm Nansen. Their losses total $3.81 billion.

The analytics firm’s assessment was calculated this week after Mr. Trump signed an annual financial disclosure showing that he walked away with a $636 million payout on the same crypto bet, part of a haul of at least $2.2 billion from all of his business ventures in 2025. ...

Three days before his inauguration, Mr. Trump unveiled … the $TRUMP memecoin, a type of novelty currency with little practical value.

“It’s time to celebrate everything we stand for: WINNING!” Mr. Trump wrote on social media. “Join my very special Trump community. GET YOUR $TRUMP NOW!” But that turned out to be bad advice.

I feel like a crazy person. “GET YOUR $TRUMP NOW” is simply a way to say “give me money to have.” If I say to you “give me $100 now,” and you do it, then (1) I will have the $100 and (2) you won’t. Did I give you “bad advice”? Yes? But also: What? And:

Nicholas Pinto is among the losers. A frequent crypto trader who voted for Mr. Trump in 2024, Mr. Pinto said he invested a total of roughly $500,000 in the $TRUMP coin, and has now lost about half that investment.

“He is leveraging the power of being president to launch currencies, when he seems trustworthy in the public’s eye,” Mr. Pinto said in an interview. “It is kind of incredible. It is almost a legal scam.”

Sure? [2]  But also: What? He “invested” $500,000 in a memecoin? What on earth did he think was going to happen? Again, the main reasons to buy memecoins are (1) comedy, (2) community, (3) greater fools and (4) confusion; it is no wonder that the Trump memecoin tapped a rich vein.

Last week, Susquehanna Investment Group sued a bunch of anonymous traders who had bought put options on Chinese brokerage shares just before China announced a crackdown on those brokerages that caused their shares to drop. Susquehanna argued that the only possible explanation for all the put buying was insider trading, and that, since it had sold a lot of the puts, it should get to take the put buyers’ winnings back. Susquehanna got a court to freeze the alleged insider traders’ accounts, as a first step to giving Susquehanna back the money.

One problem with this is that there is no direct proof that any of the traders who bought puts were actually insider trading, though the lawsuit is just starting. Another problem is that Susquehanna was not the only trader selling puts: If the put buyers were insider trading, and if some money can be clawed back from them, it would be unfair to give all that money to Susquehanna when Citadel Securities is sitting right there. So:

Citadel Securities LLC said it was the victim of the same alleged insider-trading scheme that rival Susquehanna International Group claims made more than $100 million on options bets placed ahead of a Chinese regulatory crackdown.

Ken Griffin’s market-making firm late last week asked for court permission to join Susquehanna’s June 29 lawsuit, saying it lost about $28 million as the “victim of a brazen insider trader scheme.”

Susquehanna sued 100 John Doe defendants in Manhattan federal court, acknowledging it did not know who made the trades. But it said only the possession of inside information could plausibly explain the “high risk, high reward” bets on US exchange-traded options in securities firms like Futu Holdings Ltd. and Up Fintech Holding Ltd. that were affected by the Chinese government in a May 22 announcement.

Here is Citadel Securities’ motion to intervene, and here is its draft complaint, which is largely similar to Susquehanna’s. One interesting point in the complaint is that it contains a chart that “shows a significant increase in put options transactions in FUTU and TIGR that were flagged as potentially suspicious by Citadel Securities in the lead up to the CSRC Announcement.”

We talked last week about a reader’s suggestion that, when confronted with a suspicious rush of put option orders from Chinese brokerages, Susquehanna should have used that information to inform its own trading: It should have concluded “welp, if everyone is buying puts all at once, something bad is coming,” and gotten short Chinese brokerages itself. Of course you can’t always copy whatever retail traders do. “Probably,” I wrote, Susquehanna has a “nuanced model of when retail flows are informative and when they’re stupid.”

Citadel Securities apparently does! I mean, it has a model of when retail flows are “potentially suspicious,” which does not exactly mean “informative” but doesn’t exactly not mean that either. The complaint also says “Citadel Securities sold the put options to Defendants at a market price that was informed exclusively by publicly available information and its role as a liquidity provider to the market,” so perhaps the suspicious-trade-flagging system doesn’t inform the pricing system.

When we talked about private credit in 2024 and even 2025, there was a sort of standard narrative. Private credit, as a category, had grown from almost nothing into a huge business. Private credit managers were having a really easy time raising money, but a harder time deploying it: A lot of investors wanted to get into private credit, but there were only so many good borrowers looking for loans. I wrote in 2024:

A huge boom in private credit is a difficult thing for a private credit manager to manage: There’s so much money coming in, so many competitors getting into the space, that it’s hard to stick to tough underwriting criteria and do only the good deals. You have to do so many deals to keep up, and they can’t all be good.

With all that money flowing in, you’d expect rushed deals, high leverage levels, low interest rates, borrower-friendly covenants, and generally bad decisions that would plant the seeds of losses in a few years.

Did that happen? It’s kind of too early to tell, and the negative narrative about private credit these days is less “the covenants were bad” and more “AI happened and ate all of software.” But the point is that now there is a negative narrative about private credit, and the rush of retail money into private credit has reversed.

Perhaps that means the whole story has reversed? With all that money flowing out, there might be less competition to make new loans, so the new loans might have lower leverage, higher rates and more lender-friendly covenants. The Financial Times reports:

Large investors are committing billions of dollars to private credit funds as big institutions seek to profit from an exodus of smaller retail clients. ...

Brad Marshall, who co-runs Blackstone’s flagship $45bn private credit fund, said that many investors expected returns to increase, particularly if outflows from retail-focused vehicles limited how much money those funds were willing to lend.

“Periods of volatility [are] usually the best time to invest capital because people are nervous, capital structures are a little more conservative and pricing is a little wider,” he added, referring to the extra interest, or “spread”, that lenders are able to charge above benchmark rates. ...

“The institutional side seems to be pretty clinical about how they’re approaching” direct lending, one private credit executive said. “Leverage is a little lower [on new deals], documents are a little tighter and price is wider. Those are the dynamics institutional investors see: that this market is getting better, not worse.”

Obviously there are some flaws in a story like “private credit has gotten better because there’s less money coming into it, so put more money into it,” but it’s probably basically right.

One casual way to think about it is that, if you invest in stocks, the main decision you have to make is how much exposure you want to the AI factor. There are some companies that are bets on the continuing boom in artificial intelligence, and there are some other companies that are bets against it, and there are some other companies that are relatively unaffected. If you are enthusiastic about the AI boom, you will want a lot of AI exposure; if you are pessimistic, you will want less (or even negative) AI exposure. You might have more nuanced views — you might think some AI companies will benefit more than others from the particular AI future you envision, etc. — but your rough first cut might be “more AI” or “less AI.”

If you are picking stocks, you will pick the stocks that give you the AI exposure you want. If you are mostly a passive investor, you won’t pick stocks. But the AI factor is so big and so polarizing that, passive though you mostly are, you might care about your AI exposure. If a big index provider asks market participants “hey should we rush the big AI companies into the index,” you might answer “yes, I am a passive investor and I need that AI exposure,” or “no, I am a passive investor and I don’t want that AI exposure jammed into my portfolio.” In fact the big US index providers did ask that question, and got different answers, and emotions ran high on both sides. Even mostly passive investors care a lot about their AI factor exposure, and how much AI is in the index is an active choice made by index providers.

Naively you might think that passively investing in “emerging markets” would get you relatively little AI exposure. But in fact that too is an active choice, and depending on how you count, the emerging markets index might be roughly 0% AI or roughly 50%. [3] Bloomberg’s Ye Xie and Carolina Wilson report:

While BlackRock’s more than $150 billion iShares Core MSCI Emerging Markets ETF (ticker: IEMG) returned nearly 40% in the 12 months ended June 30, Vanguard’s rival offering notched roughly half that during the same period. For funds that moved in near lockstep for years, the differential is notable.

It comes down to Korea, where an AI-driven rally in Samsung Electronics Co. and SK Hynix Inc. fueled a more than 170% surge in the country’s benchmark Kospi index during the period — benefiting the BlackRock fund, which is exposed to the market even as Vanguard’s isn’t. And it’s shining a light on the potential perils of set-it-and-forget-it investing in an era when market concentration can skew returns.

The BlackRock ETF tracks the performance of MSCI Inc.’s emerging-market gauge, and because the index provider continues to classify South Korea as an emerging market — a decision it reaffirmed just last month in its latest annual review — BlackRock’s fund is capturing the country’s stellar, if choppy, equity gains. By contrast, the roughly $120 billion Vanguard FTSE Emerging Markets ETF (ticker: VWO) tracks a FTSE Russell emerging-markets index that doesn’t include Korea, because that provider considers the country a developed market.

The less interesting classification question here is: “Is Korea a developed market or an emerging one?” The more interesting practical question is: “Do I want AI-exposed memory chip stocks in my emerging markets allocation or not?” But you can’t answer that question passively.

Elsewhere: “The Investors Scrambling to Keep SpaceX — and Elon Musk — Out of Their Portfolios.”

I used to be a big Twitter user, so I have a grudging respect for companies that hate their power users. Here is a funny Wall Street Journal article about Lucky Strike Entertainment, “America’s largest bowling conglomerate,” which was more or less founded on the premise that bowling is boring and stupid and needed to be jazzed up:

Lucky Strike Chief Executive Thomas Shannon is incredulous. He says his strategy is crucial for bowling to survive.

“We saved bowling in America,” Shannon said. “That’s the reality.” …

Shannon is thinking of new ways to reinvent bowling, including through “gamification.” Players could earn rewards like a new car or cash, not for winning traditional games but other challenges like rolling a certain number of strikes in an allotted period. 

People who think bowling is good and fun hate this:

Competitive players say the company is ruining the sport with its focus on frivolous entertainment while allowing lanes and equipment to fall apart. 

But those people, while they bowl a lot, do not pay the bills:

Today, 10% of Lucky Strike’s revenue comes from league bowlers while 25% comes from party bowlers. The rest is “walk-in retail,” which includes bowling, arcades, food and beverage. …

“League bowling is in decline,” [Shannon] said. “We have yet to find that it has real commercial value.”

The league bowlers have sued; here is their complaint, which is sort of touching although not all that legally compelling:

Plaintiff Mitchel Feuer, who is a resident of Yonkers, New York, has been bowling regularly for nearly 50 years. Lately, he enjoys taking his grandson bowling or getting in some bowling practice on his own. Mr. Feuer has gone bowling at both Bowlero White Plains and Lucky Strike Nyack in the last four years. Mr. Feuer has been dismayed at how much bowling prices have increased during this period; as a longtime bowler, he finds Bowlero’s prices to be “extravagant.” Mr. Feuer estimates he was charged approximately $45 an hour to bowl and $12 to rent shoes at a recent visit to Bowlero White Plains—and, when he arrived at his designated lane, he realized that Bowlero had failed to even oil it.

Disclosure: I have actually been to Bowlero White Plains. It was fun. I have no idea how oiled the lanes were because I am not, at all, interested in bowling. In that sense, I agree with Shannon. But I can see why the bowlers are frustrated that the main bowling company seems to hate bowling.

Memory Chipmaker SK Hynix Kicks Off $28 Billion US Listing. Quant Hedge Funds Extend Worst Run Since 2023 as Momentum Slides. Small Hedge Funds Beat Multistrats in Rollercoaster First Half. China Quant Funds Draw Billions as AI Trounces Human Traders. Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario. Citi Joins Small Group of Banks Running London’s Gold Vaults. Saudis Slash Main Oil Price to Rare Discount as Market Dives. Wall Street banks recover in China amid trading boom. Judge Rules JPMorgan Still Has to Pay for Charlie Javice’s Legal Defense. How Bending Spoons built a $23bn tech empire from struggling brands. How BlueCrest’s Michael Platt fell foul of the UK taxman. How Rogue Nations Are Using Cryptocurrencies to Evade Sanctions. “I feel a little bit like I’m not good enough to live here anymore because I don’t work at an A.I. company.” Snow rooms. Belgium Fumes After FIFA Clears Balogun Following Trump Appeal. UK finds lost US Declaration of Independence copy after 250 years.

If you'd like to get Money Stuff in handy email form, right in your inbox, please subscribe at this link. Or you can subscribe to Money Stuff and other great Bloomberg newsletters here. Thanks!

Podcasting note: This week’s episode of the Money Stuff podcast is out now (because of the holiday tomorrow). Katie and I discuss Susquehanna puts, sports ETFs and Stretch. You can listen to this week’s episode here.

Okay here’s an investor relations strategy:

1. You run a public company. Let’s say it’s called Money Stuff Inc.
2. Periodically, you have either good news or bad news.
3. When you have good news, you put out a press release saying “Money Stuff Inc. announces some good news,” and your stock goes up.
4. When you have bad news, you put out a press release saying “Money Stuff Inc. announces some bad news.” Except that, in this case, you don’t quite write “Money Stuff Inc.” You replace the “M,” “o” and “e” in “Money” with Unicode characters 041C, 043E and 0435, which are the Cyrillic letters “M,” “o” and “e.” Those Cyrillic letters look exactly the same, to the human eye, as the English [1] letters “M,” “o” and “e,” so your press release will look completely normal to any human who reads it.
5. Not everyone reading your press release is a human, though. To a computer, English “M” and Cyrillic “M” are totally different. Computer trading systems will read your press release as like “**n*y Stuff Inc. announces some bad news” and be confused. “What the heck is **n*y Stuff Inc., never heard of it,” they will say, and not take any further action. They won’t sell your stock on the bad news, so — because algorithmic traders are increasingly important to the stock market — your stock won’t go down.

From a human’s perspective, sometimes you announce good news and other times you announce bad news and you are always scrupulously honest. From a computer’s perspective, sometimes you announce good news and other times there’s some random nonsense in the feed. The computer only sees your good news, so your stock never goes down.

This is so stupid in so many ways, and also extremely not any sort of advice, but it is based on real academic research. Bloomberg’s Lu Wang reports:

At the University of Liechtenstein, Advije Rizvani, Giovanni Apruzzese and Pavel Laskov designed 10 LLM-based trading models to forecast share prices with sentiment analysis for a portfolio of stocks. All generated positive returns during a 14-month investment period through April 2025. Yet every model was fooled after researchers made subtle changes to financial news headlines that were barely noticeable to human readers, such as swapping letters for nearly identical-looking characters or embedding hidden text.

Here is the paper, “Adversarial News and Lost Profits: Manipulating Headlines in LLM-Driven Algorithmic Trading,” which really does involve “Unicode homoglyph substitution”:

A few characters in a stock name (e.g., A, e) can be replaced by visually indistinguishable Unicode counterparts (e.g., Cyrillic “A” А, “е” е).. The manipulated headline appears to be unchanged to the human eye. When such headline is used in the [algorithmic trading system] pipeline, it may elicit wrong decisions in the stock mapping algorithm, determining which stock a given headline refers to, and thus “misroute” a headline.

“We consider an adversary with no direct access to an [algorithmic trading system] but able to alter stock-related news headlines on a single day,” they write, but isn’t the obvious “adversary” here the company itself? [2] We have, ridiculously, previously discussed the the idea of downplaying unpleasant corporate news by printing it in white text on a white background, and I wrote:

Honestly this all feels quaint already. Pretty soon all corporate disclosures will be read exclusively by computers, and concealing information by making it unreadable to humans won’t work. What you’ll want is to conceal it from the computers, which is harder.

Totally wrong! Unicode homoglyph substitution! Maybe it’s the future of stock promotion. 

We have talked a few times about the maximalist vision of artificial intelligence, which goes something like this:

1. In the future, AI robots will replace most human endeavor and nobody will have jobs anymore.
2. The problem of economics will be how to allocate all the value created by the robots.
3. In our current system of market capitalism, that value will be allocated to the owners of the robots
4. So you’d better own some robots.
5. Society should get out ahead of that problem by making sure that everyone owns the AI companies that will control the robots. Perhaps governments should nationalize the AI companies, or tax them extra to fund universal basic income. The more market-based approach is that the AI companies should be large and increasing components of the stock index, and everyone should buy index funds in their retirement accounts to own their share of the robots.

Now. You don’t have to believe this maximalist vision. You could think AI won’t be that big a deal, or it will create more opportunities for human labor, or it will wipe out humanity and thus render stock ownership irrelevant, or something else. Here I just want to make the narrow point that this particular maximalist vision is quite bullish for AI stock prices. [3] The message is “in the future, all of the value in the world will belong to AI companies, so you’d better buy AI stocks today.” [4]

I write sometimes that “nobody in history has ever been better at business negging than Sam Altman.” What I mean is that Altman has mastered the art of saying and doing facially bad things about OpenAI, so that people will think good things about OpenAI. Most notably, he used to spend a lot of time publicly worrying that AI might destroy humanity, which sounds bad when you put it like that, but which also might make you think “ooh this technology is really powerful, I’d better invest.” Similarly, here’s this:

OpenAI has discussed giving a 5 per cent stake to the US government as the $852bn AI start-up seeks to clear political obstacles by securing financial buy-in from the Trump administration.

Sam Altman, chief executive of the ChatGPT maker, has argued that giving the public a financial stake in the company is the best way to share the upside of AI and has suggested a stake of this size in early conversations with the administration, according to two people familiar with the talks. …

Altman and other OpenAI executives have suggested that each of America’s leading AI developers allot 5 per cent of their equity to a vehicle like the Alaska Permanent Fund, a sovereign fund that invests the state’s oil wealth into stocks and pays dividends to the state government and residents. ...

OpenAI and Anthropic have previously suggested in economic policy proposals that arrangements such as public or sovereign wealth funds may be required in future to distribute shares to the public.

In April, OpenAI proposed a “public wealth fund” that “provides every citizen — including those not invested in financial markets — with a stake in AI-driven economic growth”.

The OpenAI Foundation, the company’s non-profit arm, said in May that in an AI-led future, “society will likely need new approaches that give people durable stakes in the systems creating value”, pointing to public or sovereign wealth funds.

On the one hand, giving away 5% of your equity is in some nominal sense dilutive to your shareholders. On the other hand, giving away 5% of your equity is a small price to pay to persuade everyone that owning your equity is essential to the future of humanity. Then you sell the other 95%.

One way that I like to tell the story of private credit is:

1. In the olden days, insurance companies bought a lot of corporate bonds, clipped the coupons and held them to maturity. The insurance companies had predictable long-dated liabilities, and they matched them up with predictable long-dated liabilities from corporate bonds.
2. Then, like, Bill Gross invented bond trading: Instead of holding bonds to maturity, insurance companies could trade them to make better risk-adjusted returns.
3. In the beginning, this was lucrative, but ultimately the bond market just became more efficient and returns were competed down.
4. Then some insurance companies invented the opposite of bond trading: Instead of buying liquid traded bonds that pay relatively low returns, you can accept some illiquidity, offer borrowers a better experience (faster marketing, lower market risk, a single lender, a better relationship with that lender, less paperwork, etc.) and demand a higher interest rate. Then you hold the bonds until maturity and clip the coupons, which is fine, because you are an insurance company with predictable long-dated liabilities.

That is the core story, and then modern “private credit” introduces various inessential novelties. For instance: Fifty years ago, when Bill Gross was getting his start, the innovators in insurance company lending worked at insurance companies. In the 2020s, they work at “alternative asset managers,” which manage money for insurance companies and/or own insurance companies directly. And so now the high-profile way that insurance companies do illiquid buy-and-hold lending is through private credit funds, because it is cool and lucrative to manage a private credit fund and boring to run an insurance company.

But that is only approximately true, and in fact the boring old business of “insurance companies buy bonds and hold them” never entirely went away. Bloomberg’s Emily Graffeo reports that it’s having a bit of a renaissance:

A private bond market dating back more than a century is opening a new front in the trillion-dollar AI funding boom, allowing tech borrowers to sell debt directly to deep-pocketed insurance firms.

Borrowers are hunting for capital wherever they can to finance the vast sums needed for the build out of AI. Meanwhile, life insurers facing record demand for annuities are seeking longer-term, high-grade corporate bonds to finance those multi-decade liabilities.

Private bonds, where companies sell securities directly to groups of select institutional investors, are bridging the gap. Issuance hit roughly $81 billion this year through May, the most for the period in data going back to 2016, according to Private Placement Monitor. Industry participants say AI is fueling the surge.

“Especially with AI and data centers, there’s an insatiable need for capital,” said Sheel Patel, head of New York private credit at Mayer Brown. “The borrowers are increasingly more comfortable using the private market for larger financings, especially when they realize that certainty, flexibility and confidentiality are a priority in these transactions.” …

This shift comes as a swelling population of Americans over age 65 drives annuity sales to record levels. In fact, total annuity sales hit an all-time high of roughly $464 billion last year, according to the life insurance trade group LIMRA. To back these expanding long-term liabilities, insurance firms are scaling up their purchases of private corporate bonds.

In some ways the simplest possible financial story is: “Businesses need money to make long-term investments in physical capital that will increase their future profits. They borrow that money from insurance companies who have lots of money and need to plan for predictable long-term liabilities.” You can complicate that story with liquid public bond markets or private credit funds or whatever. But the simple story is that you want a steady income in retirement, AI data center rents can provide that steady income, and the financial industry will match you up with a data center and make that trade happen.

Elsewhere:

For the second straight quarter, two Blue Owl Capital Inc. private credit funds were hit with the industry’s largest redemption requests, forcing the manager to again cap withdrawals.

Investors in the roughly $34 billion Blue Owl Credit Income Corp., one of the largest in the industry, asked to pull 18.8% of shares, or $3.6 billion in the second quarter, according to an investor letter Thursday. That was down from $4.2 billion requested in the prior period from the fund known as OCIC.

The smaller Blue Owl Technology Income Corp. saw shareholders request 38.1%, or $1.1 billion, compared with $1.2 billion in the first quarter.

Disclosure: I have a small investment in BCIC, sorry sorry. “Insurance companies have predictable long-term liabilities and can commit to making illiquid long-term investments” is a good classic simple story; “retail investors probably won’t want their money back all at once so let’s put it in illiquid long-term investments” is also a story but is notably less good. It turns out this is not the best technology for matching your retirement plans to a data center.

Polymarket, the prediction market, offers five-minute binary options on Bitcoin. If Bitcoin trades at $62,000 at 9:30 a.m., you can put in a bet on whether it will be up or down at 9:35. If it trades above $62,000 at 9:35, the “Up” bets win $1 and the “Down” bets get $0; if it trades below $62,000 at 9:35, “Down” wins.

If you put a lot of money on “Up,” and at 9:34 and 55 seconds Bitcoin is trading at $61,999.99, you should probably go buy some Bitcoin. Your buying will push up the price, and if you can push the price up to $62,000.01, your Polymarket options will pay off. Then you can sell the Bitcoin you just bought. When you sell your Bitcoin, the price will probably go back down. You will lose money on the round-trip Bitcoin trades: You’ll buy on the way up, sell on the way down, and probably sell at a lower average price than you bought. But you will make money on the Polymarket trades: You bought “Up” at 50 cents or whatever, and it pays $1. Whether this is a good trade or not depends on the relative size and liquidity of those markets. If you can buy 10,000 Up contracts at 50 cents, you can make $5,000; if you can then move the Bitcoin price up by spending $4,000, you should. This is not any sort of advice at all, and this is obviously bad market manipulation, but, you know, we are talking about Bitcoin and Polymarket here. There are also five-minute Dogecoin binaries.

We talked yesterday about market manipulation in eggs. I wrote:

This is a familiar story and you probably know the ending. There’s a big market (egg producers selling eggs to supermarkets etc.), and there’s a small market (egg producers selling extra eggs to each other on an electronic exchange). The price in the small market determines the price in the big market. Participants in the small market are also participants in the big market. You can spend a little money in the small market to move the price, which can make you a lot of money in the big market.

“Big market” and “small market” there are imprecise terms. The market for Bitcoin is bigger, by volume, than the market for five-minute binary options, but binary options are discontinuous, so moving the price of Bitcoin by a little bit can have a big payoff in your binary options. The relevant question is whether you can spend a little money to move the price of Bitcoin in a way that makes you more money in the binary options market. When prediction markets were just a glimmer in the eye of libertarian economists, the answer to that question was “of course not, what are you even talking about.” But, as I wrote a few months ago, “now prediction markets exist and are a big business, so they are not only in the business of predicting reality: They’re also in the business of changing it.”

Here’s a paper by David Dai, Ruizhe Jia and Shihao Yu on “Settlement Manipulation in Prediction Markets”:

Empirically, we study Polymarket’s Bitcoin five-minute up/down contract: a binary claim that pays $1 if Bitcoin is higher at the close of a five-minute window than at its open, and $0 otherwise. … The contract’s launch on February 12, 2026 offers a clean natural experiment: no five-minute contract existed before that date, so we compare three regimes: no such contract (P1), the 15-minute and 4-hour contracts only (P2), and the five-minute contract live (P3).

As soon as it launched, a relatively small prediction market began redirecting large spot orders to the settlement seconds. In the final ten seconds before each close, trading on Binance spikes: the magnitude of net order flow jumps, and volatility rises with it. The timing is no accident: the spike appears only after the five-minute launch (about 50% above the pre-launch level), and is significantly attenuated at the fifteen-minute horizon. The spike is sharpest where a push is pivotal: in the roughly 6% of cycles whose contract price still implies a near-even outcome just before the close, the near-settlement order-flow jump is about 3.9 times that in the rest. The clearest sign that this is not information is the reversal: within ten seconds the price reverts, by about a quarter in the near-even cycles and a tenth in the others. Real information would persist; the price impact of a manipulative push reverts.

We have talked about prediction market manipulation before. There is a Polymarket contract on whether Jesus Christ will return before 2027, and there was another Polymarket contract on whether the Christ-will-return contract would trade above 5% during some one-hour window, and allegedly people bought the Christ-will-return contract in an effort to make the derivative contract pay out. I wrote: “What possible purpose could the ‘Jesus Christ return before 2027 Odds >5% February 17, 12-1 AM?’ contract have other than as a plaything for market manipulation?” I submit to you that if you lose money to market manipulators on the “Bitcoin up in the next five minutes” contract, you deserve it. Not legal advice or whatever.

Lots of investors have investment mandates with some sort of environmental, social or governance restriction. “Don’t invest in weapons companies” is a reasonably common one. Some companies make weapons and some don’t; weapons-restricted investors invest only in the ones that don’t. They have to pay attention, though, and update their holdings periodically. Sometimes a snack food company will start making weapons. Or a non-weapons company will acquire, or be acquired by, a weapons company. 

If you’re a public-company shareholder with a no-weapons mandate, this is not a big problem: You just sell the stocks that are now weapons stocks. If you’re a private-company shareholder, it’s harder: There’s no liquid market for your stock, so you are stuck.. When there is no exit, you need to exercise voice: A no-weapons shareholder in a private company that starts getting curious about weapons, traditionally, has to tell the company’s executives “no, this is not what we signed up for.” But private markets are the new public markets, and now it’s easy to migrate no-weapons investors out of the shareholder base. The Financial Times reports:

German surveillance drone maker Quantum Systems will consider merging with kamikaze drone start-up Stark after using its latest $1.2bn funding round to part ways with investors opposed to investing in weapons.

Florian Seibel, Quantum co-founder and co-CEO, said the company used the funding round, which valued the defence technology group at about $8bn, to “clean up” its shareholder structure and allow it to develop lethal technologies for the first time.

Anyone who did not “feel comfortable with the potentially new alignment of the company had a chance here to exit”, he told the FT.

That could pave the way for moves into areas such as deep-strike missiles, he said, as well as a possible merger with Stark, which he also co-founded, to bring his “two babies back together”.

I like that Seibel loves drones indiscriminately but had to have separate killer and non-killer drone companies to appeal to two distinct sets of investors. But he has now been successful enough to kick out the non-killer investors and reunite his “two babies.”

I mean, you know:

Empery Digital Inc. (NASDAQ: EMPD) (the “Company” or “Empery Digital”) [Tuesday] announced that it has entered into a definitive agreement for a $65 million investment (the “Investment”) representing a 25% ownership into a private entity that is acquiring a strategically located Midwest facility to be converted into a state-of-the-art AI data center.

Empery Digital and Hunt Properties, Inc. have entered a strategic partnership to jointly originate, evaluate, and acquire powered land properties with secured tenants suitable for AI and high-performance computing data center development. The partnership will combine Hunt Properties’ decades of experience navigating utility interconnection processes, power procurement, and energy infrastructure development and their established network of relationships across the U.S. with Empery Digital’s public company platform, expertise in capital markets, and strong balance sheet, including its Bitcoin holdings, to execute a shared vision for AI infrastructure.

Etc. We have talked about Empery a couple of times before. As of early 2025, it was called Volcon Inc. and was in the business of selling electric bikes and golf carts. But in July 2025, a better opportunity came along, and Volcon became a digital asset treasury company, or DAT (and renamed itself Empery). That was the thing to do with a US public company, last summer: If you put $500 million of Bitcoin into a public company, the company would be worth $1 billion, so Empery did. 

That is no longer the thing to do with a US public company: Empery started trading at a discount to net asset value, and activists have been pushing it to sell its Bitcoin, buy back stock and close the discount. The DAT trade that looked so good last summer — “if you buy Bitcoin, your stock will trade at a premium” — no longer works. Never mind.

The thing to do with a a US public company in the summer of 2026 is of course AI infrastructure. People won’t pay a premium for DAT stock anymore, but they will pay a premium for AI infrastructure stock. Onward! 

SEC Probes Alleged Insider Trades That Cost Susquehanna. Trump Made $1 Billion on Crypto Deals While His Fans Lost a Fortune. Nvidia Says It Will Take a Cut of Some Customers’ Cloud Revenues.. CoreWeave Junk Bonds Slide Further as Investors Question AI Boom. SpaceX Showed Investors Prototype of Elon Musk’s New AI Device. SpaceX Analyst Debut Set to Test $2.2 Trillion Valuation. One Leveraged ETF Is Reshaping Trading in World's Top AI Memory Stock. Bank of England to push ahead with plan to limit hedge fund leverage. Equity-Market Fundraising at Most Exuberant Since 2021, Mergermarket Says. Millennium Targets at Least $10 Billion in New Fundraising. The DeepMind trio who built a poker AI are now making money for quant hedge funds. UBS to trial US banking services in push for wealthy American clients. McKinsey Shakes Up Its Board After Scandals Over Past Work With Clients. Hot dog inflation: Americans brace for costliest ever July 4 parties. Whiskey Barrel-Backed Loans Are Plummeting in Value With Americans Drinking Less. The Wall Street Women Who Traded Finance Careers for Influencer Success. Ken Griffin Bought Out All 138 Condos in Miami Tower, One by One.

If you'd like to get Money Stuff in handy email form, right in your inbox, please subscribe at this link. Or you can subscribe to Money Stuff and other great Bloomberg newsletters here. Thanks!

There’s an electronic egg exchange that sets the market price of eggs. [1] It’s called Egg Clearinghouse Inc., or ECI; its website is eggs..org. It is not the main place to buy eggs. You buy eggs at the supermarket. Supermarkets and restaurants and bakeries and other big egg users also do not go to the Egg Clearinghouse to buy most of their eggs. [2] They enter into supply arrangements with egg producers, who deliver them the eggs they need at the times and places they need them. 

The Egg Clearinghouse is for extra eggs. Sometimes the egg producers have too many eggs: Their hens have laid more eggs than they have sold to their customers. Other times, the egg producers are “net short”: Their hens have laid fewer eggs than they have sold, and they need to buy more eggs to deliver to their customers. The Egg Clearinghouse is a place for the egg producers who are short eggs to buy eggs from the egg producers who have extra eggs.

The price of eggs on the Egg Clearinghouse is whatever price balances supply and demand on the exchange: If egg producers want eggs, they bid for them; if they have extra eggs, they offer them.. There is some market-clearing price, and producers who need extra eggs pay that price.

What about supermarkets and restaurants and other egg users? They pay the price they negotiate with producers. How is that price set? You could imagine a supply contract saying, like, “we will sell you 100 dozen eggs a week for the next year at $0.30 per dozen,” or whatever. But in fact egg prices are variable, and the supply arrangements are often based on benchmark market prices. There is a reporting agency, now called Expana but formerly called Urner Barry, that computes daily benchmark egg prices based on trades (and bids and offers) on the Egg Clearinghouse. [3]  And “egg producers … often sell eggs to retailers including grocery stores and restaurants under contracts for which the price of eggs is based on the daily price quotations published by Urner Barry.” [4] The market price on the Egg Clearinghouse determines the wholesale price charged to customers. “Egg Clearinghouse Inc. is nationally recognized as an exchange to help determine and establish the market value for eggs and egg products,” says eggs.org. “This is known as ‘Price Discovery.’” 

I could stop there. This is a familiar story and you probably know the ending. There’s a big market (egg producers selling eggs to supermarkets etc.), and there’s a small market (egg producers selling extra eggs to each other on an electronic exchange). The price in the small market determines the price in the big market. Participants in the small market are also participants in the big market. You can spend a little money in the small market to move the price, which can make you a lot of money in the big market.

That is the story of, you know, half the stuff I write about. That is the story of Libor, the former benchmark interest rate: There was a small interbank lending market and a gigantic interest-rate derivatives market that priced off of the small interbank lending market; manipulating the price in the small interbank lending market was relatively easy and could have lucrative consequences in the big derivatives market. It is arguably the story of Jane Street’s alleged Indian options manipulation: Big Indian options market, small underlying stock market, what do you expect. There was even a scandal, a decade ago, involving manipulation of benchmark prices for chicken; I used to call it “Chicken Libor.”

It would be weird if egg producers didn’t manipulate the Urner Barry price. They did. The US Department of Justice announced yesterday:

The Justice Department’s Antitrust Division, together with 17 State Attorneys General, filed a civil lawsuit against Cal-Maine Foods Inc. (Cal-Maine); Hickman’s Egg Ranch Inc. (Hickman’s); and Centrum Valley Holdings LLC, Versova Holdings LLC, and Versova Management Cooperative (Versova) for unlawful coordinated manipulation of egg prices. ...

As the complaint alleges, Defendants conspired to inflate Urner Barry’s price quotations by agreeing to: (1) submit a large number of bids; (2) cause multiple Defendants to bid in order to signal to Urner Barry that a diverse set of market participants needed to buy eggs; (3) submit a large number of bids in the hours leading up to the publication of Urner Barry’s price quotations; (4) submit bids that were unlikely to lead to executed trades; and (5) execute trades at premium prices.

Yep. That’s just what you’d do, if you were (1) faced with this market structure and (2) maybe a bit hazy on market manipulation and antitrust. law. The complaint has some examples:

[On December 20, 2022,] Hickman’s CEO … [emailed] senior executives from Cal-Maine, Versova, and others, stating, “[p]lease consider posting strong bids, early and often. The market reporters don’t get in for another hour, so it will be good for them to see diverse bidding upon logging on.” (Urner Barry is more likely to increase its price quotations if it observes higher bids from a variety of market participants.) Hickman’s CEO later emailed again, stating, “[h]urry[.] There are only 16 bids on ECI right now and 15 of them are ours [Hickman’s bids].” Shortly after that email, all three Defendants collectively submitted dozens of bids on ECI, most of which were at premium prices. By contrast, all other market participants combined submitted fewer than six bids that morning. ...

On December 20, Urner Barry again increased its price quotations for white, large, shell eggs across all regions. 

They did some private trades with each other at high prices, which also got included in the benchmark calculation. And they did some spoofing, submitting bids at high prices (which again influenced the benchmark) and then deleting them to avoid actually buying at those prices:

On December 22, a senior Versova executive told another Versova executive to “light up the northwest bids please. .02 over.” That executive agreed and then placed bids at a price that was two cents greater than Urner Barry’s price quotation for the Northwest. Prospective sellers were required to call prior to accepting these bids. Then, when one of the Versova executives noted that the “NW bids are getting hit”—meaning that a seller was offering to sell the eggs to Versova to meet Versova’s bid—the other Versova executive stated that he should delete the bids, suggesting that Versova did not need the eggs.

The companies agreed to settle the cases, though several denied wrongdoing. As part of the settlements, the companies have agreed not to coordinate with each other on egg bidding. Delightfully, they have also agreed hand over some eggs? Here’s a press release from New York’s attorney general:

New York Attorney General Letitia James today secured more than 50 million eggs for consumers nationwide and $3.3 million from some of the nation’s largest egg producers for colluding behind the scenes to raise prices. … Of the 53 million eggs obtained through the settlement, approximately 4.9 million eggs will be delivered directly to food banks and community organizations serving New Yorkers.

“Secured more than 50 million eggs,” perfect. I think the second sentence means that the other 48.1 million eggs will be delivered to food banks in the other states that sued, but it would be amazing if New York State kept most of the settlement eggs for the state treasury.

We talked yesterday about a lawsuit that Susquehanna Investment Group filed against some anonymous traders who bought, from Susquehanna, short-dated out-of-the-money put options on Chinese brokerage stocks just before the Chinese government announced a regulatory change that caused those stocks to tank. The puts “were purchased for only approximately $12 million, but were highly lucrative, yielding a profit of over $100 million and a return of over 900%.” Susquehanna thinks that the put buyers were insider trading, and is suing to get the money back.

I wrote that retail options market making is a lucrative but risky business: Most of the time, you are selling options to gamblers who lose money (to you), but some of the time you are selling options to insider traders who, for instance, know that a merger is coming and buy short-dated call options on the target. (Or Chinese regulators who know that a crackdown is coming, etc.). If you can avoid adverse selection by suing the winning gamblers for cheating, then that’s an even nicer business. If the customers lose money, you keep the money; if they win too much money, you also keep the money.

A couple of updates. First of all, Susquehanna won the first round. Bloomberg News reports:

Susquehanna International Group won a court order freezing brokerage accounts it claims are linked to a $100 million insider-trading scheme and allowing it to subpoena the brokers for the account-holders’ identities. …

Manhattan US District Judge Arun Subramanian late on Monday granted Susquehanna’s request for a court order freezing certain accounts at the three firms and said it had demonstrated sufficient reason to serve subpoenas on them. …

Interactive Brokers said in a statement Tuesday that it had been cooperating with Susquehanna, including freezing accounts, since the trading activity had been identified. Representatives for Up Fintech and Futu didn’t respond to requests for comment.

One possibility here is that this is all a misunderstanding, the put buyers had no inside information and bought those options for legitimate hedging or fundamental-research reasons, they will show up in court and explain everything, and the court — and perhaps even Susquehanna — will be like “you’re right, you won fair and square, we’re sorry we doubted you, here’s your money.” The other possibility is that no one will ever hear from these put buyers again and Susquehanna will keep the money.

Susquehanna and the judge think that the second outcome is more likely, and obviously they’re right, but you never know! My Twelfth Law of Insider Trading is: “If you insider trade by buying short-dated out-of-the-money call options on a merger target, and the SEC freezes your profits, don’t show up in a U.S. court to ask for them back,” which I think applies here. On the other hand, we have also discussed exceptions to the Twelfth Law: If there’s really no evidence against you, other than your well-timed trades, maybe you can show up in court, keep a straight face, and get your money back.

I got a number of reader emails about this story, the best of which read:

This seems like the coward's way out to me. You'd think a firm as sophisticated as Susquehanna would just notice when a bunch of retail customers are placing big bets on short-dated out-of-the-money options and trade on the merger. 

This is a good point, but I want to raise two objections. First: It’s not obvious that “when a lot of retail investors buy long-shot options, you should copy their bet” is actually a good heuristic. It would have worked here, I guess, but sometimes a lot of retail investors will all make the same terrible bet; you don’t always want to copy them. “When a lot of retail investors buy long-shot options, fade them all day long” is also sometimes a good heuristic, and being on the opposite side of retail options gamblers is often a great trade.. Perhaps — probably — Susquehanna has some more nuanced model of when retail flows are informative and when they’re stupid, but I wouldn’t assume that the model is infallible.

Second: It’s not obvious that Susquehanna didn’t do this. Imagine you’re an options market maker and a bunch of customers all come to you to buy short-dated out-of-the-money options on some public company. You run it through your proprietary nuanced model, and the model is like “there is a 100% chance that these people are insider trading and a merger is coming.” So you go out and buy even more call options on the company. [5] You are now net long call options on the company: You sold, like, 1 million options to the insider traders, and then you bought 10 million options for yourself. The merger is announced, each option goes up $20, and you make a $180 million net profit. Great.

But, also: You did sell those 1 million options to the insider traders. They made a $20 million profit, arguably at your expense. You could … also … sue them? Get the $20 million back too? It’s not like Susquehanna’s complaint in this case says “Susquehanna was net short put options and lost $100 million.” Susquehanna’s complaint says: 

Plaintiffs [Susquehanna] traded the relevant options contemporaneously with the Defendants. In fact, Plaintiffs were the sellers for a substantial number of the Defendants’ purchases, including trades that resulted in the Defendants making approximately $71 million in illicit profits. ...

The Defendants’ scheme directly harmed the Plaintiffs, as the Plaintiffs served as counterparties for a substantial portion of the Subject Trades. With respect to the Subject Trades in which the Plaintiffs served as counterparty, the Defendants paid total premiums of $6.7 million and obtained profits of approximately $71.4 million. 

It says the customers made $71.4 million; it never says Susquehanna lost $71.4 million. Presumably Susquehanna delta-hedged some of those options, and/or bought some of them back from other customers or dealers. For all I know Susquehanna made money on Chinese brokerage stocks, overall, that day. That’s irrelevant. The point is that Susquehanna sold some customers options that made them $71.4 million of (allegedly!) illicit profits, and Susquehanna wants that money back.

Finally, Byrne Hobart points out by email that this is old news to Susquehanna. Its co-founder Jeff Yass discussed getting adversely selected by insider traders in Jack Schwager’s 1992 book The New Market Wizards: 

Yass: A lot of these insider trading cases involve options, and we’re the people who lose the money. … 

The options for Combustion Engineering are traded on the Pacific Coast Exchange. The options rarely trade. One morning, we received a call from the board broker (the exchange employee responsible for managing order imbalances). He said there was an order to buy several hundred options and inquired whether we wanted to take the other side. The stock was trading at around $25, and we agreed to sell three hundred of the 25 calls at $2 1/2. Ten minutes later, trading in the stock was halted, and there was an announcement that the company was being taken over by a European corporation. When trading resumed several minutes later, the stock reopened at $39, and we were out over $350,000 in a matter of minutes. It turned out that the buyer was on the board of directors of the acquiring company.

Schwager: What ultimately happened?

Yass: In this particular case, we’ve already gotten our money back. The SEC identified the buyer quickly, and because the individual was a high-level foreign executive who didn’t even realize he was doing anything illegal, he returned the money without any complications.

Simpler times! In 2026, apparently Susquehanna doesn’t want to wait for the US Securities and Exchange Commission to identify and sue insider traders, which is understandable, so it’s doing it itself.

“Prediction markets,” I sometimes write, is mostly a fancy way to say “sports gambling.” The big prediction market companies, Kalshi and Polymarket, have built a new kind of sportsbook that has some regulatory advantages, and that’s a good business. But they’d never say that: They’ll tell you that prediction markets are about harnessing the wisdom of the crowd to understand the future, helping businesses hedge real-world risk, blah blah blah.

My sense is that they are sincere in this. Prediction markets have been around, in theoretical papers and in small-scale experiments, for a long time, and there is a longstanding prediction-market culture. That culture is idealistic and intellectual and rationalist and not at all about sports betting.. Kalshi and Polymarket were influenced by that culture, and I am sure that their intention was to build truth machines and hedging platforms. It’s just that sports are — unsurprisingly, in hindsight — where the money is. And Kalshi and Polymarket are idealistic and intellectual and rationalist and all that, but mostly they want money, and there you go. [6]

The prediction market culture takes place mostly at an annual convention called Manifest. Bloomberg’s Christopher Beam went to this year’s Manifest to see how the prediction market true believers are feeling, and it’s about how you’d expect: Happy that prediction markets are booming, but a bit sad about all the sports.

On June 13, just as the New York Knicks were clinching the NBA championship in San Antonio, Eliezer Yudkowsky was making a point about prediction markets. It was the second day of Manifest, an annual convention in Berkeley, California, and Yudkowsky, wearing a gold sequined jacket and silver hat, was explaining to a small group of young men that these markets — which aggregate bets based on people’s insights into and beliefs about the future — are humanity’s best shot at establishing collective knowledge. They are, he said, “civilization’s way of knowing what it knows.” Suddenly, news of the Knicks’ historic win arrived via mobile push alert, and Yudkowsky responded with jaunty disdain: “Are those sportsball players?”

Right, if you are Eliezer Yudkowsky, you want prediction markets to predict and thus avert AI-driven human extinction or whatever. But the actual wisdom of the actual crowds on actual prediction markets is “let’s bet on the Knicks.” And:

As conference-goers spoke on panels or milled around the venue — Lighthaven, a leafy, labyrinthine, privately owned compound that was formerly a hotel and scans as part grad-student flophouse, part self-help retreat space — some expressed pride that their once-obscure hobby had gone mainstream. “I hear people crowing about how we’ve been right,” said Robin Hanson, a George Mason University economics professor who’s considered the godfather of prediction markets. “They feel they’re on the up and that they deserve respect, and that just produces an energy.”

At the same time, many attendees seemed disillusioned, highlighting fears that the big platforms could undermine the technology’s prospects for serving the public good. “I think many people feel disappointed that sports gambling has become such a prominent part of prediction markets,” said Scott Alexander, the influential author of the blog Astral Codex Ten. “That was not the original intent.”

I don’t think he just means “that was not the original intent of the people at this conference”; I don’t think that was the original intent of Kalshi or Polymarket either. But prediction markets are truth machines, and the truth is that people like betting on sports.

Elsewhere: “Inside A Secret Clipping Discord That’s Making Undisclosed Ads And Faking Kalshi Results.”

Also: I wrote on March 18, 2025, that “we are about two years away from a sports gambling ETF,” I have mentioned that prediction a few times since then, and I hope you have marked your calendar. Yesterday the US Securities and Exchange Commission put out a request for comment on “on exchange-traded funds (ETFs) seeking to invest in innovative asset classes or engage in novel investment strategies.” The press release doesn’t mention sports gambling ETFs, and in fact the request itself does not use the word “sports.” But the subject matter is definitely “should we allow sports gambling ETFs”:

Over the past several years, sponsors of ETFs have expressed interest in providing exposure to innovative asset classes or using novel investment strategies (“Novel ETFs”). To date, these include: crypto assets; commodity-focused instruments; single‑stock strategies; heightened leverage; blockchain-enabled opportunities; private assets; event contracts; and/or a combination of any of the above.

One thing to notice is that all of these things — crypto ETFs, commodity ETFs, single-stock ETFs, leveraged ETFs, blockchain-enabled whatever, private-asset ETFs — already exist, except for event contract ETFs (sports). The real question is whether to add sports gambling. You can submit comments to the SEC here. My general working assumptions about securities regulation in the second Trump administration are:

1. Everything is legal, and
2. Even if something is illegal, no one is going to stop you.

But this is not any sort of advice and we’ll see!

Google Told to Pay Klarna Nearly $2 Billion in Shopping Spat. Binance Cuts Off European Users After Regulator Raises Financial-Crime Concerns. Trump Reports at Least $1.4 Billion in 2025 Crypto Earnings. Trump Reports Receiving About $120,000 in Sports Events Tickets. JPMorgan’s $4 Million ‘Salami Incident’ Is Fueling a Backlash From Banks. BlueCrest loses £200mn legal battle over trader taxes. Saudi Sovereign-Wealth Fund Struggles to Find Winning Investments. US Lifts Export Restrictions on Anthropic’s Fable 5 AI Model. Getty scraps $3.7bn Shutterstock merger after UK watchdog order. KKR plots entry into UK and European pension buyouts. Private-Equity Firms Sell Care Bears to Authentic Brands Group. ‘Taylor Swift Tax’ Stirs Bad Blood With Rhode Island Homeowners. The U.S. Added 1,200 New Millionaires a Day Last Year. AI and crypto wealth driving private jet boom, says Flexjet. Wearing shorts at work.

If you'd like to get Money Stuff in handy email form, right in your inbox, please subscribe at this link. Or you can subscribe to Money Stuff and other great Bloomberg newsletters here.. Thanks!

The basic job of a market maker is to buy low, sell high, and not get adversely selected. You bop along, buying stock at the bid (say, $9.99), selling it at the offer (say, $10.01), and collecting the bid/ask spread ($0.02) on each pair of trades. If people trade with you essentially at random, you keep the whole spread as profit: Someone comes in to sell at $9.99 one second, someone else comes in to buy at $10.01 the next, and you keep the $0.02. 

But if someone sells you a lot of stock at $9.99 one second, and the next second the stock crashes to $9, then you lose $0.99. That is, roughly, adverse selection: buying stock when it is about to go down, or selling it when it’s about to go up. What you want is to trade with people at random; what you don’t want is to trade with people who know which way the price will move.

And so some of the business of market making is about avoiding adverse selection by knowing what the price should be, some of it is about charging a big enough spread to cover your adverse selection losses, and some of it is about trying not to trade with people who know too much. In the US stock market, one way to do that is to pay retail brokers to trade with their customers’ orders: Retail traders, stereotypically, trade at random, so if you buy some stock from them you have no reason to think the stock will go down. [1]

That’s stock market making. Options market making is the same but more so. [2]  Options tend to have wide bid/ask spreads and be bought by retail gamblers, so market makers make a lot of money on options. (Robinhood makes about four times as much money from payment for order flow on options as it does on stocks.)

But options also have a lot of risk of adverse selection. If you sell someone short-dated out-of-the-money call options, they will probably expire worthless and you’ll make money — unless the company announces a merger tomorrow. Then you’ll get blown up. But the people buying those options might know something about a merger. There’s a reason that my Second Law of Insider Trading is about buying short-dated out-of-the-money call options on merger targets. It happens a lot!

That is arguably an annoying example. Most of the time, “adverse selection” doesn’t mean “insider trading.” The more standard sort of adverse selection in market making is, like, a big institutional investor wants to buy a lot of shares, so the price goes up a lot after you sell some. Or a sophisticated hedge fund has done research suggesting that the fundamental value of a stock is above its price. Or a high-frequency trading firm knows that futures have moved up a tick before you do. Stuff like that.

On the other hand, if you are making markets in options to retail customers, adverse selection maybe … does … kind of mean insider trading? The customers are not managing billions of dollars or doing deep sophisticated research or running low-latency feeds from Chicago. If they buy a ton of options and then a merger is announced, that’s probably either luck or insider trading, and if they do it multiple times — or if many of them do it — then perhaps you can rule out luck. 

Perhaps this is unfair. Perhaps it is based on broad rude stereotypes about retail investors. But it is a nice theory for the market maker. Like:

1. You buy and sell options at big markups.
2. Most of the time, the customers are putting in random noise bets and lose money.
3. Sometimes, the customers have big wins.
4. But those don’t count: When the customers have big wins, it’s because the customers cheated.
5. So you shouldn’t have to pay them.

If you ran a literal casino, this logic would be very convenient. They’d win their bet, you’d say “nah you cheated,” and you’d hold onto their money. Perhaps they’d sue you, or file a complaint with the regulators, and you’d eventually have to give them the money. But perhaps they wouldn’t. For one thing, they probably did cheat, so they’d lose in court or with the regulator. And even if they didn’t cheat, what are they gonna say? “No I just did fundamental research and had a hunch that something good would happen to that stock”? Sounds fake.

If you are an options market maker, it’s not quite as easy as that. The options trade on an exchange, the customers aren’t your customers exactly, you don’t control their accounts and you can’t just keep the money. But here’s this:

Susquehanna Investment Group is attempting to unmask the identities of individuals it claims made at least $100 million trading on inside information about a Chinese government crackdown on cross-border brokerages last month.

The Pennsylvania-based market-making firm, which says it was the counterparty on most of the alleged insider trades, sued 100 John Doe defendants in Manhattan federal court on Monday. Susquehanna is seeking to recover more than $70 million it says it lost to what it believes is one of the largest insider-trading schemes in recent memory.

According to Susquehanna, many of those trades were made from accounts at Interactive Brokers Group Inc., as well as the platforms of two firms targeted in the Chinese crackdown, Futu Holdings Ltd. and Up Fintech Holdings Ltd.’s Tiger Brokers. Susquehanna is seeking an order freezing certain accounts at those brokerages and authorizing subpoenas of them.

Here is Susquehanna’s complaint, and here’s its motion to freeze the brokerage accounts. Of course Susquehanna has no direct evidence of insider trading. It doesn’t even know who these traders were, so it certainly doesn’t know whether they were insiders at Chinese regulatory agencies or brokerages, or what information they had when they made their trades. But it knows that they bought short-dated out-of-the-money put options on Futu and Tiger just before China announced the crackdown, that Futu’s and Tiger’s stocks crashed after the crackdown and that the puts made a lot of money, at Susquehanna’s expense. “Insider Trading is the Only Plausible Explanation for the Subject Trades,” says the complaint:

Upon information and belief, there was no new public information about FUTU or TIGR released between May 7, 2026 and May 21, 2026 that would provide a reasonable basis for the Defendants to place so many high-risk, high-reward purchases of short-dated FUTU and TIGR put options. … Yet despite the lack of negative public news about Futu or UP between May 7 and 21, the Defendants placed unprecedented numbers of trades that would only be profitable if new information emerged in a matter of days or weeks that had a significant negative price impact on the stocks. Indeed, many of the options were purchased the day before the Crackdown News on May 22. Those facts provide powerful evidence of trading based on MNPI [material nonpublic information].. …

The Defendants’ identities are unknown to Plaintiffs. However, under any plausible scenario, the Defendants placed the Subject Trades in breach of a fiduciary duty or a duty of trust and confidence. The facts of this case suggest two categories of insiders who could have either traded directly on the MNPI about the imminent Crackdown News or tipped others: (i) Chinese securities regulators; and (ii) Futu and UP personnel who had knowledge of discussions with Chinese securities regulators about the enforcement action.

And so it is (1) suing the people who made the trades, (2) asking the brokers — Futu and Tiger and also Interactive Brokers — to reveal the identities of the people who made the trades, so it can sue them more effectively and (3) asking the court to order Futu and Tiger and Interactive Brokers to freeze their accounts so that, if it wins, it can get the money back. The only possible explanation for these trades is cheating, says Susquehanna, so it shouldn’t have to pay.

“There are few ways in which a man can be more innocently employed than in getting money,” Samuel Johnson said, and I think about that a lot. Here is my extremely biased stylized history of the vibes in tech and finance over the last few decades:

1. After 2008, finance was Evil, and smart quantitative people wanted to be in tech, which was Good. “Don’t Be Evil” was literally Google’s mission statement, back when Goldman Sachs’s was “relentlessly jamming our blood funnel into anything that smells like money.” [3]  Tech was about Changing the World and Building the Future; finance was just about seeking money in exploitative ways.
2. In the subsequent decade or so, people became a bit disillusioned with Big Tech. Google deprecated “Don’t Be Evil” in 2018. A certain cynicism set in about the problems tech was solving; Facebook’s vision of the future was serving up ever more addictive phone content to maximize advertising revenue. Political and cultural and social things happened that I won’t get into. A smart quantitative person in 2020 might have thought “well, if I go to Google I will be building systems to maximize advertising revenue, and if I go to Hudson River Trading I will be building systems to maximize trading revenue, and those things are roughly morally equivalent but HRT doesn’t go around moralizing about it, so I’ll go to HRT.” Finance hadn’t become Good, but it was back to being Neutral; tech had gone from Good down to Possibly A Bit Evil.
3. Then, in about November 2022, the modern artificial intelligence boom started and everyone wanted to work at AI labs, in part because they could make incredible fortunes overnight but also in part because of a real sense of mission. Building artificial general intelligence might be the most important thing humanity ever does, so a smart quantitative person would rather work on that than on extracting short-term trading signals for stock options.
4. Like 20 minutes later everyone started worrying that AI labs, instead of being Good, might actually be Incredibly Incredibly Evil. Like, if you go to work at Anthropic or OpenAI or Google or xAI, you probably get good free snacks, but are you possibly working toward human extinction? Seems bad.
5. If you are a cutting-edge AI researcher, you can also be very useful to a quantitative trading firm or hedge fund, and those guys probably aren’t going to wipe out humanity. [4] They just want to make money.

Have the vibes swung back to finance? I wouldn’t go that far, in part because there’s just soooooooooo much money in AI labs, and the people who like finance mostly like money more. Still, Bloomberg’s Nishant Kumar and Liza Tetley report:

Millennium Management is setting up an artificial intelligence laboratory to expand the development and application of cutting-edge technologies at the firm.

The new lab will become operational over the next few weeks, according to a memo seen by Bloomberg News. It will focus on accelerating early access and assessment of AI products, the memo said, as well as collaborating with AI firms on projects and attracting top AI talent.

The facility would “provide a highly entrepreneurial environment to attract and retain AI talent,” Vlad Torgovnik, Millennium’s chief information officer, said in the memo.

Right, hedge funds do need to be at the forefront of AI. Obviously their AI ambitions are a lot more modest than those of the big frontier AI labs. But maybe that’s good.

The general story about modern hedge funds is that bigger is better. Modern multistrategy multimanager hedge funds identify a mysterious quality known as investing skill, they hire people who have that skill, and they apply those people’s skill to the largest possible opportunity set. Those people are expensive, and the funds hire lots of them to make lots of uncorrelated bets and maximize their risk-adjusted returns.

This is not the only way to run a hedge fund. The Financial Times has a story about alumni of Elliott Management, which is also a giant ($80 billion under management) hedge fund, also runs a bunch of strategies and is also hyper-focused on risk management. But its approach is a bit different from the classic multimanager pod shops:

Elliott now does everything from boardroom fights to takeover battles and distressed-debt brawls, all while maintaining an unusually intense eye on levels of risk.

The phrase Singer has used over the years to describe this phenomenon is “manual effort”, or the attempt to eke out better returns by sheer force of will and resources. Elliott will often have as many as 50 employees devoted to one investment. …

Elliott’s hallmark investments also often combine legal expertise, a savvy for credit documents and sometimes entire takeovers, as eventually took place with the $16.5bn deal for software company Citrix in 2022.

Another former employee said working at Elliott was particularly good for learning “how to prosecute a wide variety of weird and hairy and messy situations”.

The classic pod-shop trades are, like, “buy the stocks that will go up next week and short the ones that will go down,” or “buy the stocks that will be added to the index,” or “buy Treasury bonds and sell futures.” Those trades tend to earn modest returns and benefit from a lot of leverage, and they naturally demand a large scale.

The classic Elliott trades are, like, “notice a mistake in a bond indenture,” [5] or “ruthlessly make fun of a public-company CEO’s drinking problem.” Those trades sort of have whatever scale they have: If there are $500 million of bonds with the mistaken indenture, or if the company with the drunk CEO has a $1 billion market capitalization, then that’s the cap on the opportunity.. It seems plausible that drunk CEOs and mistaken bond documents are more common at smaller targets. If you run an $80 billion fund, those trades might not move the needle. It’s not worth it to apply a lot of manual effort to every drunk CEO or mistaken bond indenture.

On the other hand, if you’re an Elliott employee, you can go start your own hedge fund and do Elliott-style trades that are too small for Elliott. The FT reports:

Members of the “Elliott diaspora”, as some former staffers call it, have founded at least seven hedge funds since 2020, mirroring the “Tiger cubs” that came out of Julian Robertson’s Tiger Management around the turn of the millennium.

They include Adam Katz’s Irenic Capital, Dan Gropper’s Carronade Capital, Quentin Koffey’s Politan Capital and James Smith’s Palliser Capital. Unlike Robertson, Elliott has not invested in any of the new firms, according to two people familiar with the matter. But even so, they have begun to find success in the same field.

Scale is a necessity for a pod shop, but it is perhaps an impediment for a weird-and-hairy-situation shop.

My basic model of Strategy and its “Stretch” preferred stock is that it is soft fuzzy banking. That is:

1. Strategy issues Stretch to raise money to buy Bitcoin.
2. Stretch is a perpetual preferred stock whose dividend rate resets each month to make it trade at par. It’s effectively short-term financing that automatically rolls over each month at whatever Strategy’s market-clearing interest rate is.
3. Stretch is intended to work like a money-market instrument, like a bank deposit or money market fund. One dollar of Stretch is supposed to always be worth a dollar; it is supposed to have very little duration. Strategy is essentially funding Bitcoin purchases with bank deposits.
4. But not really.. Unlike bank depositors, Stretch holders can’t take their money out whenever they want; Stretch is perpetual. The monthly interest-rate reset is almost economically equivalent to refinancing Stretch every month, but not quite; if financing markets are shut the Stretch stays outstanding. Also, Strategy doesn’t actually have to pay that interest: It’s a preferred stock, and Strategy can always decline to pay the dividend. And while Strategy announced an intent to reset the dividend every month to make Stretch trade at par, you can’t hold it to that intent: It could just reset the dividend to a lower rate and allow Stretch to trade below par.

Soft fuzzy banking is in some ways superior to regular banking: If actual banks could fund themselves like this, it would be nice. On the other hand:

• Actual banks can’t. This only works if you’re a goofy Bitcoin treasury company with an audience of true believers.
• Also the tradeoff is that the cost of this capital is quite high. As of last week, Stretch was (1) paying 11.5% and (2) trading around 75 cents on the dollar, implying that its yield (to trade at par) should be about 15%. So, more than a bank deposit.

As we discussed last week, Strategy is now facing something of a soft fuzzy bank run: As Stretch has traded down, Strategy’s cost of capital has gone up, and it has faced pressure to (1) pay much higher interest on the Stretch and/or (2) pay back the Stretch — just like a regular bank facing a regular bank run. Less so, because all of this is technically optional, but still sort of a bank run. And yesterday Strategy announced that:

1. It no longer intends to keep Stretch at par: It’s raising the interest rate to 12%, not 15%, and in the future “will not necessarily increase the STRC dividend rate solely because STRC trades below its stated amount.” (It closed yesterday at 83.67 cents on the dollar.)
2. It is buying back some Stretch: It’s spending up to $1 billion to buy back its preferred stock, and “currently expects STRC to be the initial priority under the program.”
3. It’s doing assorted other stuff — building its cash reserve, selling some Bitcoin — to improve its liquidity so that it can keep paying all those Stretch dividends.

Some of it — paying higher interest, redeeming deposits, selling assets, shoring up its balance sheet — is what banks would do in a bank run. Some of it — not paying much higher interest, only redeeming some of the deposits (and not at par) — is what banks would prefer to do in a bank run, if they could, but they can’t.

A few weeks ago, ahead of SpaceX’s initial public offering, we talked about the technical complexities of keeping track of orders in a giant IPO. Those complexities are … not very complex? It’s, like, you call your clients and ask them how many shares they want, and then you write their answers down on a list. But we discussed a Bloomberg News story about how various banks and brokers and depositories and service providers were doing various sorts of practice runs to make sure they were ready for the SpaceX IPO, because that IPO would be a severe test of their systems (for writing down lists). I wrote:

On the one hand all of this is true, but on the other hand if SpaceX’s banks come to it tomorrow and say “ahhh there were just too many orders for stock so we lost track of them” that will not be acceptable.

Well! Well. “SpaceX IPO Left Korea Broker With No Shares on Misunderstanding,” Bloomberg reports:

Mirae Asset Securities Co. … inadvertently treated an early request to indicate investor interest as the point at which it had submitted binding orders, the people said. As a result, more than $1.1 billion worth of Korean demand was never entered into the IPO order book, they said. …

In mid-May, weeks before bookbuilding began, the bookrunners circulated an email asking underwriters to indicate investor demand, which was aggregated in a virtual data room in line with standard practice for large deals.

Mirae responded to that request believing it had placed its clients’ orders, according to some of the people, who are familiar with the firm’s thinking. But from the perspective of the Wall Street banks running the deal, those responses were only indications of interest, not bids. The actual orders were entered in June after a separate email from the bookrunners, as is customary for such IPOs.

Right, again, the technical complexities here are just not that complex: They ask you before the IPO “hey how many shares do you think you can sell,” and then they ask you at the end of the IPO “please submit the orders for the shares you sold,” and then they use the second list to allocate you some shares. And if you forget, oops, no shares. “The New York-based banks viewed Mirae as having submitted zero retail orders, and ultimately allocated it zero retail shares.” And:

“We bow our heads in apology for delivering such unfortunate and heavy news to customers who participated in the SpaceX IPO subscription with great interest and anticipation,” Mirae Vice Chairmen Kim Mi-seop and Heo Seon-ho said in a text message to clients on June 15, the Seoul Economic Daily reported. They pledged a review of the process and measures to “restore consumer trust,” according to the newspaper.

Yeah there is no good way to tell clients “sorry, we lost track of your stock orders.”

How the great wealth transfer is rattling Wall Street. SpaceX Pushes US Share Sales to Record $251 Billion at Midyear. Private equity fund investors turn to debt-like deals in downturn. World Bank drops climate finance target under US pressure. Ethiopia Bondholders Criticise IMF for ‘Poorly’ Handled Debt Rework. EY employee charged with accessing Australian prime minister’s bank details. QSBS trust stacking. New York’s Pied-à-Terre Tax Stymies Owners Looking for Loopholes. People are betting on wildfires.

If you'd like to get Money Stuff in handy email form, right in your inbox, please subscribe at this link. Or you can subscribe to Money Stuff and other great Bloomberg newsletters here. Thanks!

Companies issue debt and they issue equity. There are various corporate-finance-y reasons to choose one or the other or some particular mix: Debt is often cheaper and tax deductible, equity is less risky and good for motivating employees, etc. But you could also tell a sort of market segmentation story. Some people want to own debt: They have some money, they want to keep it, and they want to invest it in something that promises to repay the money with a reasonable return. Other people want to own equity: They have some money, they’re willing to risk it to get a high return, and they want to invest it in something that could go to zero but also offers a potentially unlimited payoff. Companies sell some debt because there are people who want to buy debt, and they sell some equity because there are people who want to buy equity, and companies that need a lot of money will sell the stuff that people will buy.

On the other hand, there are all those corporate-finance-y reasons. You could imagine a world in which:

1. There is an enormous amount of demand for debt, from various institutions that are quite averse to risk and want a steady known return; and
2. There is a small but quite intense demand for equity: Some people have a little money to play with, they want to invest that money in stuff that could go to zero or offer a huge payoff, and they want the most concentrated possible form of that. They want stuff that will double or go to zero, tomorrow. Not, like, earn 6% over Treasuries for 20 years: double or zero, now.

Companies could collectively cater to that desire by financing themselves with, you know, 70% senior debt and 28% mezzanine debt and 2% equity: The senior debt would be reasonably safe, the mezzanine debt would be risky but offer a steady known return most of the time, and the equity would be a lottery ticket. This would, however, be terrible corporate finance. That’s too much debt; companies would be going bankrupt constantly. This is not how the world works, at all. The debt-to-total capital ratio of US companies is about 15% and has declined over time.

But what if that imagined world is right, or right-ish? What if investors want more debt than companies are offering them, and also riskier and higher-octane equity than companies are offering? That sounds like a job for the financial industry: shifting risk around, giving more risk to people who want it. The financial industry is good at putting stuff in boxes and issuing tranches of those boxes. If you have too much equity, you put the equity in a box and issue debt and equity against the box. The debt of the box adds to the stock of debt in the world; the equity of the box is riskier — more likely to double or go to zero — than the equity you put into the box. You have taken the given mix of debt and equity and used it to create more debt and riskier equity.

Here’s a Bloomberg News story about stock market leverage:

The surge in market leverage, stemming in part from the massive growth of levered exchange-traded products, retail margin accounts and hedge fund deposits at prime brokers, is stoking worries that it may exacerbate the next crisis. The demand to borrow money has driven an unusual mid-year spike in financing costs, which have reached the highest levels since December 2024.

“Leverage has become one of the defining themes for investors,” said Andy Kent, a broker at Kyte. “Margin debt is elevated, borrowing across parts of the shadow banking system continues to expand.”

And here’s a Wall Street Journal story on similar themes:

U.S. margin debt, or what investors borrow from their brokerages to buy securities, rose 54% to a record $1.4 trillion in May from a year earlier, according to Finra data. Meanwhile, high-risk leveraged exchange-traded funds that produce double or triple the daily move of underlying stocks are growing rapidly, as is trading in options tied to them.. …

“I’m fearful that we’re building unintended leverage that isn’t fully understood,” said Mark Hackett, chief market strategist for Nationwide’s investment management group. “You’ve got people with a lottery mentality using margin to buy options on levered ETFs. That’s three or four layers.”

Yes! A levered ETF is, conceptually: You put $200 of stock in a box, you issue $100 of debt against it, and you issue $100 of equity against it. [1]  Now that $100 of equity represents $200 of stock; it’s twice as risky. A call option is a similarly levered bet on stock: If the stock goes up, you double your money quickly; if it goes down, you lose all your money quickly. A margin loan is borrowing $100 to buy $200 worth of stock. If you stack them on top of each other, you get super-concentrated, super-risky bets on stocks. Companies don’t want to sell you those bets, but you can make them yourself.

“This would, however, be terrible corporate finance,” I said above; it would greatly increase the risk of defaults and crises and disruption. For essentially the same reasons, you can see why people are worried about stock market leverage.

How do you know if you own a share of stock? In the very olden days, you’d have a paper stock certificate, but those are just novelty items now. Now the basic answer is: A share of stock represents a claim on a company, and so a share of stock is, in essence, an entry on a list maintained by the company. The company has a list — its “cap table” — of who owns its shares and how many shares they own, and owning a share means being on that list.

Some small startups will keep this list in an Excel spreadsheet or on a napkin or in the founder’s memory, but at large public companies it will be maintained by a professional outside contractor called a transfer agent. If I sell you some stock in a company, we essentially send an appropriate message to the transfer agent saying “I transfer 100 shares of Amalgamated Widgets to you,” and the transfer agent makes a note of it and now you own the stock. 

In practice, this rarely happens because most publicly traded US stocks are owned indirectly. One big clearinghouse, the Depository Trust Co., owns most of the shares of most of the stocks; banks and brokerage firms have accounts at DTC; and investors have accounts at banks and brokerages.. If you own 100 shares of Amalgamated Widgets, what you actually own is an entry in a database at your broker showing that you own the stock, and your broker has an entry in a database at DTC showing that it owns the stock (on your behalf), and DTC has an entry in a database at Amalgamated’s transfer agent showing that it owns the stock (on your broker’s behalf). (This is called owning the stock in “street name.”) If you want to sell me some stock, and we have different brokers, there is some theoretical complexity: My broker doesn’t have your broker’s list, so how does it know if you actually own the stock? But in practice there is an interconnected system between the brokers and DTC, you tell your broker to tell DTC to send some of its stock to my broker for my account, and it all more or less works.

Occasionally this all breaks down, and we talk about it around here. Sometimes brokers just plum forget about their customers’ accounts. Sometimes DTC and its participants can’t quite keep up with all of the transfers. Sometimes transfer agents accidentally give people stock who aren’t supposed to have it. I genuinely love all of these stories — I want to read an 80-volume mystery series where instead of country-house murders the detective solves transfer-agent errors — but they are quite rare. Mostly the system just boringly works.

Big modern private companies introduce another complication, though. Those companies, for various reasons, often don’t want people buying and selling their stock. [2] If you want to sell me 100 shares of Anthropic, and we send a message to Anthropic’s transfer agent saying “you transfer 100 shares of Anthropic to me,” the transfer agent will say “no you don’t” or perhaps “let me check with Anthropic about that” (and then Anthropic will say no). Ah well.

This has given rise to new forms of indirect ownership. Most notably there is the SPV, the special purpose vehicle: You set up a legal entity (the SPV) to buy Anthropic shares directly from Anthropic, the SPV owns nothing but those Anthropic shares, and then you sell shares of the SPV to me. I do not buy any Anthropic shares, meaning that as far as Anthropic and its transfer agent know, I don’t own any shares. But I own shares of the SPV: The SPV has its list of shareholders, and I am on that list. And the SPV owns shares of Anthropic: Anthropic has its list of shareholders, and the SPV is on the list. I have an indirect interest in the Anthropic shares.

Conceptually, this is not very different from me owning shares of, like, Nvidia Corp. I’m not on Nvidia’s list either. But I’m on my broker’s list, and my broker is on DTC’s list, and DTC is on Nvidia’s list, and I have an indirect interest in the Nvidia shares.

The difference is that the public-company DTC-based indirect ownership technology works really really well almost all of the time, to the point that almost nobody ever thinks about it, while the private-company SPV-based indirect ownership technology … ehhhh. It breaks down a lot in boring tawdry ways.

Sometimes an SPV will not keep very good track of its own shares and will end up selling indirect ownership to more of the underlying stock than it owns. Other times — quite a few times — the SPV simply won’t own the underlying stock: Some SPV promoter will come to you and be like “I own 100 Anthropic shares in my SPV, I’ll sell you an indirect interest in 10 of them,” and you’ll be like “sure,” and the promoter will be lying. How can you check? Are you gonna call up Anthropic and ask if the SPV’s name is on their list? Why would it tell you? (It’s trying to stop people from trading its stock.) The public markets have a whole invisible apparatus for making sure I own the stock that I am indirectly selling you; the private markets do not.

Three possible reactions to this state of affairs are:

1. “This is fine.” Private companies are supposed to be private; their stock is not supposed to trade. If you want to own Anthropic stock, the thing to do is wait until it goes public; then you’ll be able to buy real Anthropic stock easily. You shouldn’t try to buy weird indirect private Anthropic stock now, so the fact that it is difficult and risky is fine. 
2. “We should fix this.” This is a solved problem; the public markets have figured out how to transfer indirect ownership of stock reliably and easily. You build an interconnected system where the SPVs and banks and brokerages and transfer agents can all talk to one another, so that if you want to buy Anthropic shares (in SPV form), you can check — or rather, the system will check in the background — to make sure that you are getting actual shares of an SPV that actually owns Anthropic shares. This presumably requires some cooperation from the companies, because checking that the SPV owns Anthropic shares means checking that it appears on Anthropic’s shareholder list, but perhaps there’s a way to get that cooperation. (For instance, perhaps involving the companies in the indirect-transfer system would give them more control over those indirect transfers, which might be a reason for them to help.)
3. Same as No. 2, but with the word “blockchain.” (Remember blockchain?)

Yueqi Yang at the Information reported last week:

Citigroup wants to tackle the murky ownership problems that have proliferated among private tech firms as more special purpose vehicles have popped up promising to connect investors with the hottest startups. 

The bank this month said it is launching a new service that lets investors trade private company shares on a blockchain. It’s initially limited to foreign investors—it will expand to the U..S. later. And Citi needs the companies to agree. So far one firm has done so. …

The way the service works is that Citi will issue depository receipts—a security used for companies to access foreign investors—for private companies. It will apply a serial number for each security so ownership can be clearly tracked and transferred on both the blockchain and existing market infrastructures.  …

With Citi’s private company tokens, investors “will have legal, verifiable certainty that the underlying [asset] behind those is the actual shares in the company, with the consent of the company, directly on the cap table,” said Artem Korenyuk, the bank’s global lead for digital assets enterprise alignment and services enablement. “That’s the fundamental difference that you do not get when you invest through these multilayered third-party SPVs.” 

Citi said it will get explicit permission from each company before offering its shares on the blockchain. “We don’t want to go against the company’s desires or intent,” said Korenyuk. 

Of course one way for private companies to create a system for investors to trade their shares in a centralized depository is by going public, but apparently everyone wants another way.

The basic story of private credit is that private credit managers raise institutional funds that they use to make loans that used to be made by banks. This requires raising the funds and evaluating the loans, but it also requires finding people to borrow the money. People intuitively know, from long history, that if they want to borrow money, they can go to a bank. But if you’re a private credit firm looking to lend people money, you need to find them and tell them about your services.

The most stereotypical form of private credit is making loans to fund private equity leveraged buyouts, which makes sense if you think about the marketing channels:

• There are only so many private equity firms, and they all do lots of LBOs, so you only need a few salespeople to cover the private equity firms. And if you have a good relationship with a few private equity firms, you will get a lot of repeat business.
• Many of the big private credit managers are also big private equity managers, so you can market your loans to a private equity sponsor by walking across the hall. [3] Or, at least, they are alternative asset managers, and you are an alternative asset manager; you speak the same language and went to the same schools and did the same two-year leveraged finance analyst programs at the same investment banks. The marketing is fairly easy.

But as private credit has grown, funding LBOs is not enough, and private credit has moved into various sorts of financing for big investment-grade companies, AI data centers, small businesses, etc. How do the private credit firms pitch those borrowers? The answer is some combination of:

• Hiring former bankers to come work in private credit, pitch companies and originate loans; and
• Partnering with banks: A bank has client relationships and sales skills and can find borrowers and bring in the loans, but the private credit fund has money and can fund the loans.

But as private credit has grown, funding business loans is not enough, and private credit has moved into various sorts of consumer financing. How do the private credit firms pitch those borrowers? The private credit firms are not going to hire tons of consumer bankers. You’re not going to get a phone call from Blue Owl pitching you on a credit card. The answer has to be some combination of [4] :

• Partnering with banks: A bank has a credit card program and sells some of the credit card receivables to a private credit firm; and
• Partnering with fintechs: There are all sorts of companies offering consumer loans, generally in genre known as “buy now pay later,” and those companies tend to be capital-light tech-flavored firms that are not funding those loans themselves. They need money, the private credit firms need loans, and there is a natural synergy.

In some sense, the way Blue Owl pitches you on a credit card is that PayPal pitches you on a buy-now-pay-later product. BNPL is the credit card of private credit. I wrote last year:

The modern rise of BNPL in the US is not so much a story of “fintechs offer a better user experience than credit cards” or “people are going into debt for burritos,” and more a story of “banks are retreating from consumer lending risk, and private credit firms, with their long-term capital, are better bearers of that risk.”

Anyway Bloomberg’s J.J. McCorvey and Rene Ismail report:

The private credit industry was dubbed “shadow banking” as it took business away from traditional lenders. Buy Now, Pay Later companies have been referred to as hawking “phantom debt” that falls outside Wall Street’s typical tracking methods.

Now, these two more opaque corners of finance are overlapping in a big way — and catching the attention of credit raters, former regulatory chiefs and others on guard for potential risks as US consumers show mounting signs of strain.

Officially known as “forward-flow agreements,” investing heavyweights like Blue Owl Capital Inc., KKR & Co. and Elliott Investment Management are increasingly agreeing to pre-purchase billions of dollars worth of loans before they’re made, in a bet that consumer assets will outpace returns elsewhere. That’s been a boon to the likes of Klarna Group Plc, Affirm Holdings Inc. and PayPal Holdings Inc., offering fuel for the origination machines at the heart of a business more Americans are embracing.

Right, yes, in the olden days, banks gave people credit cards; in the modern system of narrow banking, private credit firms give people BNPL loans.

I mentioned last week that private equity funds, unlike hedge funds, tend to charge performance fees only on realized gains. If a fund buys a company for $1 billion, spruces it up a bit, and decides it’s worth $2 billion the next year, it can’t book a $1 billion gain and send its investors a bill for a $200 million (20%) performance fee. It has to wait until it actually sells the company — probably years later — to realize the gain and collect its fees.

One reason for this is that valuing private companies, outside of a sale, is hard and conflicted. But another reason is just the structure of private equity funds: They raise money from investors, deploy it to buy companies, spruce the companies up, sell them for money, and return the money to the investors. Each fund has a finite life; investors put money in at the beginning and get their money out at the end seven or 10 or however many years later. The manager’s payoff tracks the investors’. (If the manager wants to buy new companies and deploy new capital, it will raise a new fund.) This is different from a hedge fund, which will generally have an indefinite life: When a hedge fund sells some stocks, it will normally use the money to buy other stocks, not return it to its investors. 

This difference is not a law of nature, though it is sort of a convenient way to run institutional capital. It is maybe not a great way to run retail capital. Calling up 50 big institutional allocators every two or three years to say “hey, doing a new fund, are you in?” is a fine approach, but marketing to retail is generally going to be smaller-scale and more continuous; you want to be able to take in new money whenever a new investor discovers your fund. Locking up the institutions’ money for 10 years is also fine; they are big and diversified and can knowingly take illiquidity risk to improve returns. Retail investors love to be able to get their money back whenever.

And so the basic private-equity fund lifespan — raise a lot of money at once, deploy it over time, return it when you sell companies — doesn’t really work for retail investors. You could imagine other approaches (run an evergreen fund, raise money continuously, reinvest sales proceeds in new investments, let investors cash out at net asset value in limited size); there are some well-known playbooks for selling private investments to retail investors. 

But the point here is that those other approaches break the link between performance fees and realization of gains. If an investor buys into the fund in Year 1 and sells in Year 3, before all of the gains are realized, should she simply not pay any performance fees? That seems very unfair to the investor who buys in Year 3: Should he have to pay the fees on all of the gains? It makes more sense for the selling investor to pay her share of the performance fees, and the simplest way to do that is to charge performance fees on mark-to-market gains. Every quarter, you see what the portfolio is worth, and if it’s up, then the manager collects 20% of the gains. 

This all makes sense, I think, but it is also convenient for the manager: Instead of waiting years to earn performance fees, the manager can collect them every quarter. Plus the difficulties and conflicts of valuing private assets remain: If you collect performance fees on mark-to-market gains on assets with no market, your marks might be a bit high.

At the Wall Street Journal, Jonathan Weil writes about those funds:

It is one thing for fund managers to record large unrealized gains on hard-to-value, illiquid assets and report stellar investment performance. It is quite another to also charge investors large performance-based fees before the profits are actually locked in.

This happens all the time at private-equity funds that cater to wealthy individuals. And the numbers in some instances are eye-popping.. …

As an evergreen fund, Spring raises capital monthly while offering existing investors liquidity through quarterly repurchase offers. The incentive fees are accrued throughout the year and baked into the net asset value, or NAV, that Spring updates routinely. If the fund charged such fees only on realized gains, that would reward departing investors at the expense of those who stay for the long haul, assuming the paper gains eventually turn into real money. ...

The semiliquid nature is what makes performance fees on unrealized gains necessary, if the fund manager is going to charge them at all.

The simplest way to understand the rise of retail-oriented private investment vehicles is that those vehicles charge higher fees than, like, index funds. Sometimes they also charge nicer fees — for the managers — than institutional private investment vehicles.

At the Wall Street Journal, Jason Zweig reports on the meticulous records that a con man kept of how he ran his financial fraud. Obviously not best practices in any number of ways, including this one:

“I have to tell you that there’s risk,” Regan told one client. “But at the end of the day with insurance wrappers and protection, y’know, it’s the same risk that we have of, y’know, being ripped apart by a saber-tooth tiger or, y’know, stepped on by a dinosaur.” 

When I eventually teach a financial literacy course, I’m gonna spend some time on that sentence. People pitching real investments to real investors will spend some time on a clear-eyed examination of the risks, which always exist. People pitching Ponzi schemes will say “there’s no risk.” People pitching slightly more sophisticated Ponzi schemes will say “I am required to tell you that there is risk, but really there’s no risk.” If someone tells you that there’s no risk, including by using amusing dinosaur metaphors, run!

Comcast to Spin Off NBCUniversal and Sky, Sending Shares Soaring. King Street’s Poor Returns, Partner Exits Spur Firmwide Revamp. Chinese Hedge Funds Warn the AI ‘Super Bubble’ Is Ready to Burst. AI ‘exuberance’ risks ending in lengthy investment bust, BIS warns. OpenAI Limits Release of New Model Under Pressure From US. Anthropic’s Mythos 5 AI Model Cleared by US for Wider Use. China Has Matched Anthropic in Cybersecurity, Resetting AI Race. AI fuels record $200bn M&A boom in US power sector. Rocket Lab to Buy Iridium for $8 Billion in Challenge to SpaceX. James Sprayregen’s thirst for legal showdowns prompts late career move to Paul Weiss. Novak Djokovic Joins General Atlantic in His Wall Street Debut. Hacky Sacks Are Cool Again and Somehow Cost $23. “For many founders and builders, keeping pace with AI has become life’s singular focus.”

If you'd like to get Money Stuff in handy email form, right in your inbox, please subscribe at this link. Or you can subscribe to Money Stuff and other great Bloomberg newsletters here. Thanks!

This week’s episode of the Money Stuff podcast is out now, in which Katie and I discuss summer vacation, SpaceX/Tesla, Elon Musk re-conglomeration, MacroHard, Meta prediction markets, human social behavior, Farmville, AI engagement, base revealed preferences, private credit redemptions, monthly liquidity and BDC arbitrage. You can listen to this week’s episode here:

You can get Money Stuff: The Podcast at Apple, Spotify or wherever you get your podcasts. We’d love your feedback. You can email us at moneypod@bloomberg.net.