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One of the core themes of this column is that it is good for your financial career to lose a billion dollars. This is largely a theory about hedge fund managers and bank traders; in those jobs, losing a billion dollars demonstrates that (1) someone trusted you with a billion dollars, (2) you boldly took risks with the money and (3) possibly you have learned some lessons from losing it and will do better next time. “My philosophy when I used to hire traders was that the optimal number of past blow ups was one,” John Arnold posted on X last month.

Over time, I have extended the theory to tech startups, where losing a billion dollars demonstrates different but related good qualities. “Move fast and break things,” “fail quickly,” etc.: If you have lost a billion dollars then you definitely know how to fail quickly. Also, if there is one thing that Silicon Valley prizes above all else, it is contrarianism, and losing money is arguably a contrarian act. “Everyone thinks that losing money is bad, but what if losing money is actually good,” Peter Thiel has probably almost said at some point.

Leopold Aschenbrenner is at the dead center of this Venn diagram and will doubtless be running a trillion dollars by the fall. Bloomberg News reported on Friday:

One week after Leopold Aschenbrenner’s hedge fund Situational Awareness nearly blew up, he’s already getting requests from investors looking to place more money with the artificial intelligence wunderkind.

His fund has seen a surge in interest from Silicon Valley investors looking to back the 20-something hedge funder in recent days, according to people familiar with the matter who asked not to be identified citing private discussions. So far, Situational Awareness has told investors that it’s not accepting new capital for now, the people said. …

The aftermath of Situational Awareness’ near miss is highlighting the stark divide between Silicon Valley and the world of finance. For Wall Street, it was a moment when an AI hotshot was forced to learn the dangers of leverage and rein in risk. But for many across Silicon Valley, his misstep has merely been a chance to buy the dip and keep supporting the OpenAI researcher-turned-investor.

“Silicon Valley and Wall Street are both reacting differently,” said Gygmy Gonnot, an adjunct professor at New York University’s Stern School of Business and a managing director at Focus Investment Group. “At the core, Silicon Valley rewards being directionally right about transformational technologies, while Wall Street rewards generating attractive adjusted returns while preserving capital.”

One thinks of Elon Musk’s poker strategy. In some sense the problem with Situational Awareness, before last month, was that “AI is gonna be huge so buy memory stocks” was too much of a consensus view. But having that thesis and also losing tens of billions of dollars of investor money is the sort of narrative violation that you need to make it really big in Silicon Valley.

There are two basic investing strategies, value and momentum. Value means you try to buy low and sell high: You buy stocks that have gone down because now they’ll probably go up. Momentum means you try to buy high and sell higher: You buy stocks that have gone up because they’ll probably go up more.

And then the game is in figuring out which of these effects — mean reversion or momentum — predominates, and when and over what time scales. Some of this is about human nature, market psychology, etc.; Cliff Asness says that the two main explanations for momentum are that people underreact to news and that they overreact to news.

But some of it is about institutional structure. Some sorts of investors are constrained to buy stuff after it goes down. For instance, many big investors target holding, say, 60% of their portfolios in stocks and 40% in bonds, so when stocks go down they are underweight stocks and have to buy more. You could have a theory like “when stocks go down, giant 60/40 institutions have to buy stocks, pushing them back up, so I should buy the stocks that went down to get ahead of that.”^[1]

Conversely, some sorts of investors are constrained to buy stuff after it goes up: Most classically, large-cap index funds buy stocks after their value has gone up enough to get into the index. (“The final dumping place for pumped-up stocks is an index fund,” I occasionally say.) Or, relatedly, they are constrained to sell stuff after it goes down: Most classically, leveraged hedge funds occasionally blow up when their stocks go down, and then have to sell more stock, as I have mentioned recently. So you could have theories like “when stocks go down, institutions have to sell them, and when they go up, institutions have to buy them, so I should sell the ones that go down and buy the ones that go up to get ahead of that.” And in fact there is a lot of money to be made by buying stocks just before they get added to the index, or by selling stocks just before a hedge fund blows up. Etc. etc. etc.; all of these things are somewhat true, in some regimes, over some time horizons, and you have to get the details right, and this is not investment advice. 

Here my point is only if that some new institutional structure has become popular, reasonable questions to ask might include “will this make stocks that have gone down go up, or go down more?” and “will this make stocks that have gone up go down, or go up more?” and “over what time horizon?” We have talked a lot recently about leveraged exchange-traded funds, because (1) they have become hugely popular and (2) they provide extremely clear answers to those questions. As I wrote last month, leveraged ETFs take the usual dynamics of leveraged investing — when levered investors’ stocks go up, they can buy more; when their stocks go down, they get margin calls and have to sell — and make them more mechanical and rigorous: The leveraged ETF buys more stock each day that its underlying stock goes up, and sells stock each day that its underlying stock goes down, according to a rigid formula. “Over the course of a day, stocks that are down go down more and stocks that are up go up more” is significantly more true than it used to be, because billions of dollars of leveraged ETFs have been added to the market, and that’s what they do.

Bloomberg’s Christian Dass reports:

The leveraged ETF boom is creating new ways to profit from sudden bursts of volatility in tech stocks.

The daily rebalancing of the funds tracking some of the most volatile names and sectors has amplified gains and losses, most recently for South Korean retail investors. It’s also added to swings during trading sessions, creating pockets where traders can take advantage. One way is to use an intraday momentum strategy, an area where banks have long offered Quantitative Investment Strategies to systematically capture short-term trends.

Intraday momentum “earns on large trending days, in either direction, and it usually bleeds on quiet ones,” said Florian Ielpo, head of macro at Lombard Odier Investment Managers. “July was a volatile and negative month for tech, and that is exactly the environment in which this trade shows its worth.” …

A basic intraday momentum strategy uses strict rules to buy into rallies and sell into dips, betting that the direction will continue. It performs best with highly volatile stocks on highly volatile days, said Yangyang Hou, a JPMorgan Chase & Co. strategist whose team wrote a paper that looked at the trades using five-minute price intervals, buying when the price was 1% above the previous close and selling when it fell below it, flattening the position at the end of the session.

The returns were “stellar” over the past two months, Yangyang wrote in an email — “a pattern reminiscent of 1998/99, when the technology revolution created unprecedented earnings uncertainty and record high single-stock volatility,” she added.

There is, however, some meta-momentum in the trade:

The July unwind from some of the stocks tracked the most by leveraged funds has reduced their total assets under management from a record high, which for now should ease some of the biggest swings from rebalancing. Trading in the ETFs has slumped in South Korea after authorities took steps to slow demand.

If you have a fund that buys high and sells low, and stocks go up, it will get a lot of inflows and buy a lot of stocks and have a big impact on the market. And then if its stocks go down, it will lose a lot of money and get a lot of outflows and have somewhat less impact afterwards.

The thing is, GameStop Corp. never really put in a $56 billion bid to buy eBay Inc. What happened is that GameStop’s feisty chief executive officer, Ryan Cohen, is fond of eBay and thinks he would do a good job running it, so he approached eBay and said “hey, wouldn’t it be cool if you put me in charge of your company?” EBay is a much bigger company than GameStop, and Cohen does not have enough money to buy it. Instead, the proposal was that (1) eBay’s current shareholders would continue to own most of eBay, (2) eBay would sell some debt to pay a big dividend to its shareholders and (3) Cohen would become CEO of eBay. Also GameStop would still be there; in the proposal, eBay would merge with GameStop, but the combined company would be mostly eBay. Someone characterized the proposal as a “hostile sale”: One way to look at it is that Cohen was trying to pressure eBay into buying GameStop and putting him in charge of the combined company.

The simpler way to describe it, though, is activism. Cohen is both an operator (he founded Chewy and now runs GameStop) and also an investor (he came to GameStop as an investor and has a history of other big investments in public companies). When he sees a public company that (1) he likes but (2) he thinks could be run better, he buys a stake in that company and agitates for change. He did that with eBay: GameStop spent about $4.4 billion buying 9.8% of eBay’s stock, and then Cohen set about proposing strategic changes and trying to make himself CEO.

Sometimes activist campaigns end in triumph for the activist: winning a proxy fight, taking over the company, etc. Sometimes they end in failure. Often, though, they end in compromise and half-success. Maybe the company adopts some of the activist’s suggestions. Maybe the activist gets a seat or two on the company’s board of directors. Maybe the company studiously ignores the activist but takes its own steps to improve operations and capital allocation, so the stock goes up. Maybe the activist fails in his stated goal — take control of the company and implement his strategy — but achieves his main goal, which is making the company more valuable. That’s good for the activist too! The way activism works is that first you buy some stock, and then you try to make the company more valuable.^[2] If the company becomes more valuable — by adopting your suggestions or otherwise — you get paid.

Anyway Bloomberg’s Liana Baker reports:

GameStop Corp., led by Chief Executive Officer Ryan Cohen, is considering withdrawing its $56 billion bid for eBay Inc., according to people familiar with the matter.

“Make me your CEO” was always kind of a long-shot proposal. There are possible fallbacks:

Cohen is considering proposing a partnership or joint venture that would enable eBay to leverage GameStop’s roughly 1,600 US retail locations, the people said, asking not to be identified because the matter is private. That could allow both to increase market share in high-margin categories such as trading cards and collectibles, the people said.

GameStop, as one of eBay’s largest shareholders, would seek representation on eBay’s board as part of any partnership, they added.

A board seat and some business changes are typical in an activist compromise. Also, though, GameStop paid an average price of a bit more than $102 per share for its 9.8% stake in eBay. It has done okay on that trade:

Since its offer in May, GameStop’s stock has fallen 28% while eBay’s has climbed 7.6%. The $125-a-share offer was comprised of 50% cash and 50% in GameStop common stock.

EBay’s shares closed Friday at $111.98, giving it a market value of $49.8 billion. Including debt, it’s valued at almost $54 billion.

That’s more than $400 million of profit on the trade for GameStop, or a bit more than its net income last quarter. Good trade! Sadly eBay was down to about $107.60 per share at noon today, erasing almost half of the profit. I suppose eBay’s shareholders really were hoping that Cohen would be their next CEO.

We talked on Thursday about prediction market tick sizes. My basic points were:

• Prediction market event contracts typically have prices between $0 and $1, with an average price of $0.50.
• They typically trade in increments of $0.01.
• That’s a tick size of about 2% of value, which is really high. (Compare US stocks, which usually have prices around $100 and tick sizes of $0.01, or 0.01% of value.)
• Big tick sizes tend to mean more profits for market makers, as bid/ask spreads are necessarily fairly wide.
• The central idea of retail-facing financial firms is “get retail traders to do more high-margin trades,” meaning trades with high bid-ask spreads.
• Prediction markets are mostly sports bets, so people like to make a lot of them, and they have high bid-ask spreads, so they are lucrative for market makers and brokers.
• Robinhood Markets Inc. makes roughly 100x as much, per dollar traded, on prediction markets as it does on stock trades.
• This is why everyone’s excited about prediction markets as an “asset class.”

I should, however, add nuance to that, which is that not all prediction markets have $0.01 tick sizes. On Thursday, I was particularly focused on Robinhood, which has its own prediction-market platform called Rothera, where “each contract can be traded at $0.01 increments up to $1.” Its main competitor is Kalshi, the other big regulated US prediction market, where tick sizes are typically $0.01, but not always: Kalshi supports tick sizes as small as $0.0001, and has announced that its combo (parlay) markets will be moving from $0.001 to $0.0001 increments soon. Polymarket also offers tick sizes smaller than $0.01 in some markets. Tick sizes of $0.01 are pretty normal in prediction markets, but not universal, and the ticks might be getting smaller over time.

Which makes sense. There are two competing interests here:

1. On the one hand, if prediction markets are essentially a retail gambling product, big tick sizes and wide bid/ask spreads are good: They allow market makers and brokers to extract more money from retail gamblers on each trade.
2. On the other hand, if prediction markets are going to be big, they have to be an institutional hedging product, and it’s hard to get institutional investors excited about a product with a 2% bid/ask spread. (It’s easy to get traders excited, if they’re receiving the bid/ask spread, but hedgers are paying it.) 

You could imagine a synthesis like “retail gamblers pay $0.01 spreads and institutions pay $0.001 spreads,” though that would be a little weird. That might happen if, for instance, retail gamblers mostly traded on brokers’ internal platforms (sort of like Rothera) while institutions traded mostly on public exchanges. Or it might happen if retail gamblers mostly traded on exchanges, and institutions mostly did over-the-counter trades that are priced in reference to the exchanges: If you’re trading a $10 million sports bet with Susquehanna over the counter, you don’t have to use $100,000 tick sizes.^[3] It would be a little weird because the US stock market is the opposite: Institutions tend to pay relatively wide bid/ask spreads by trading on public exchanges, while retail investors tend to get tighter bid/ask spreads because their brokers internalize their orders. There is a lot of competition to trade with retail stock orders, so the prices are low. But we are still in the early days of prediction markets.

The Wall Street Journal reported this weekend that a handful of celebrities are currently dating men who work in private equity. A running bit around here is that “private equity” is a prestige laundering mechanism that sorts ambitious highly trained graduates of prestigious universities into jobs running pest control companies in the Midwest. This bit is not exactly true— private equity is more high-finance capital allocation to pest-control rollups than it is day-to-day management of pest-control rollups — but it’s a little true, and these very funny quotes in the Journal article are even funnier if you keep it in mind:

“If you live in the celebrity bubble, party after party, with the same people—the same 25 people—life gets really boring,” said Kevin O’Leary, the businessman and “Shark Tank” panelist. “When you end up with a private-equity guy, your life gets far more interesting.”

“When you end up with a pest-control guy, your life gets far more interesting” could well be true. And:

“Whether they want to admit it or not, many women have always been attracted to bad boys and risk-takers,” said Jordi Hays, a co-host of the technology industry talk show TBPN. “I can’t think of any archetype of man that fits that description more today than capital allocators that put it all on the line every day in the markets.”

I feel like Hays is stretching a little bit there, and when he says “capital allocators that put it on the line every day in the markets” he’s actually thinking about Leopold Aschenbrenner.

Private Equity Is Stuck With 33,575 Unsold Businesses. China Unleashes $28 Trillion Capital Markets to Challenge US in AI. Intel to Sell $15 Billion in Stock With AI Boom Lifting Demand. Anthropic, Macquarie and GIC Form Venture for AI Data Centers. The bank behind China’s AI listings bonanza. Investors Want Quarterly Reports, Unfavorable Results and All. Jane Street Looks to Rework $11 Billion Debt Into Private Credit. Private Credit Is Under Growing Strain, Despite Industry’s Upbeat Tone. Private Credit Squeezed By Bank Refinancings. Paramount Will Put 30-Film Pledge in Writing to Theater Chains. Start-up bank backed by Palmer Luckey set to raise $1.5bn. Barrick Chairman’s Planned Overhaul Meets Investor Backlash. Trump Crypto Took $100 Million From a Businessman With Red Flags. The Suspected Gangster Causing Headaches for Kushner’s Albania Deal. AI Is Rewiring South Korea’s Careers, Dating and Culture. The Bruising Race to Rent in San Francisco Goes Into Overdrive. “Kicks at work now scan as uncool.”

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