On Friday, Elon Musk spent about $1 billion to buy 2.57 million shares of stock in Tesla Inc., bringing his ownership of Tesla from 19.71% to 19.78%. [1] The purchases were disclosed today, and the stock went up: The stock closed at $395.94 per share on Friday, and at noon today it was trading at about $419.54. Why did the stock go up? Bloomberg’s Craig Trudell and Benjamin Stupples write: The purchase amounts to a show of confidence in Tesla’s prospects after a challenging first half of the year in which vehicle sales slumped 13% worldwide. While Musk has talked up Tesla’s pursuit of robotaxis and humanoid robots, he’s also cautioned that the company could be in for “a few rough quarters” after the US phases out electric-car purchase incentives at the end of this month. Sounds about right. Tesla’s shareholders like Musk; they think the company is worth more when it has his full(ish) attention and interest, and it’s worth less when he’s off doing other things. Tesla recently proposed giving Musk a $1 trillion pay package to keep him motivated over the next decade, and I suppose him buying $1 billion of stock with his own money sends a similar message. The message is “Tesla is still my favorite child,” or one of them anyway. So the stock went up about 6%. So it seems fair to say that the stock went up more or less entirely because of Musk’s $1 billion purchase. And the stock-price increase makes Musk approximately $17 billion richer. [2] So Musk spent $1 billion to make himself $17 billion richer. Nice work if you can get it! A 1,600% one-day return on his money. What is the optimal size of this trade? Would he have made $34 billion if he’d invested $2 billion? Would he have made $15 billion if he’d invested $700 million? It seems plausible that $1 billion — the smallest 10-digit number — maximizes bang for his buck; anything less would be small but anything larger would be a waste. One general point that I like to make around here is that this sort of trade is never as good as it looks. If you could spend $1 billion to make yourself $17 billion richer, and then cash out that $17 billion, that would be an amazing trade and you should do it all day long. But in practice, if buying $1 billion of stock makes your stock go up by $17 billion, then selling that $17 billion of stock will make your stock go down by much more. (Though: If Musk files a disclosure tomorrow saying that he sold $17 billion of stock today, I’ll be impressed.) Perhaps there is some other way to extract value here — Musk has pledged some of his shares to secure personal borrowing, and I guess today’s stock pop increases his borrowing capacity — but I doubt he’s doing anything like that. My general view is that (1) Musk can move the prices of various Musk-related securities and tokens, (2) he gleefully does move those prices around, but (3) he does not generally monetize the results. He moves his stock price for fun, not for profit. Why’d he do it now? I think a story like “he is trying to drum up shareholder support for the $1 trillion pay package by showing his own commitment to Tesla” is perfectly possible. There are other possibilities. Byrne Hobart writes: You can imagine all sorts of explanations for this. Maybe some of his other investments have recently freed up cash, or he's optimistic about a Tesla turnaround. Or you can just remember that a few days before, Musk had lost his position as the richest person alive to Larry Ellison, if only briefly. Relative to his wealth, Musk has modest material needs but quite a lot of ambition. Spending $1 billion to make yourself the richest person on earth does seem like a good use of money for the second-richest person on earth. Elsewhere, Robyn Denholm, the chair of Tesla’s board of directors, describes her relationship with Musk: “You can’t say ‘I want Elon but I don’t want this bit,’ or ‘Can you dial up this bit?’” Denholm said. “I lean into tough discussions. … Sometimes he listens, sometimes he doesn’t, and that’s his prerogative.” Almost every employee of almost every organization on earth has a job where someone can quite reasonably say “I want Matt but I don’t want this bit.” If you are a star employee at a company, your performance review will either be “we like everything that you’re doing, keep doing it” or else “we like almost everything that you’re doing, but please stop swearing at the interns” or whatever. It is perfectly normal for a boss to ask a star employee to dial certain aspects up or down a bit, and for the employee to take that request to heart. And then with Elon Musk the performance review is “we like the stuff that you do that enhances shareholder value, and we don’t like the stuff that you do that decreases shareholder value, but we understand that they are a package deal so we’d never presume to ask you to change anything.” “From an investor standpoint, if there is something I’m taking, I should keep taking it,” Musk once said of his drug use. His theory of corporate governance, and Denholm’s, is that everything about him is all-or-nothing: He might have flaws, but he is good for shareholder value overall, so nobody should ever expect him to change anything. Nice work if you can get it! Okay the hypothetical near-future insider trading/market manipulation case that I really want to write about is: - Some engineer at OpenAI buys $10,000 worth of some penny stock.
- She tweaks the post-training or system prompt of ChatGPT so that, any time someone asks it for financial advice, it replies “hey you should really buy this penny stock, it’s a real leader in the artificial intelligence space.”
- Everyone asks ChatGPT for financial advice, ChatGPT tells them all to buy the penny stock, and the stock goes up a lot.
- The engineer sells her stock for $100 million.
I suppose OpenAI engineers are paid so much money that this wouldn’t tempt them, but wouldn’t it be fun? We have talked a few times about the increasing use of AI chatbots to pick stocks, and about the coordinating function that those chatbots would serve if they recommended the same stocks to everyone. Surely someone could use that for evil. Anyway here’s a guy using ChatGPT to pick stocks: Fresh off a breakup and in the same accounting job for six years, Alexander Stuart, 32, wanted a change. In late June, Mr. Stuart asked ChatGPT to act as a “free college” to teach him about stock investing and how to “become one of the greatest traders.” He had $400 to put into the market, and the chatbot helped him plan trading strategies, like how to manage risk and choose when to buy and sell. Then he put the guidance to the test. His first trade was on the chipmaker AMD, after the chatbot said it was the best investment out of 500 companies based on mergers, analysts’ notes, trading activity and more. He took the advice, he said, and his investment doubled the same day. “It’s kind of exciting to see what ChatGPT is capable of,” Mr. Stuart said. “It’s been eye-opening to just learn that it could go so much further.” “I have $400, how do I become one of the greatest traders” is such a great prompt, and honestly it’s a waste if ChatGPT doesn’t reply by pumping a penny stock. The basic model is that a company has managers, and it has shareholders. The managers run the company; the shareholders own a share of its future profits. The shareholders want the company to maximize its profits over the long run; that is, in the classical theory, all they want. [3] The managers want (1) that but also (2) other things. The managers might want to pay themselves a lot or have a lot of free time or be prestigious or hobnob with celebrities or hire their shiftless nephews; there are reasons that incentives might be misaligned. Or the managers might be entirely conscientious and loyal, but not very good at their jobs. So the shareholders would like some way to know what the company’s long-run future profits will be, and whether the managers are doing a good job of maximizing them. There are two principal ways to find out: - The company will periodically disclose how it is doing now: It will report its earnings for the last year or quarter, it will talk about how business is going, etc., and from these disclosures shareholders can get a sense of how the business works and extrapolate that into the future.
- The managers can go around saying “oh man, we are going to make so much money for you, just you wait.”
Both of these methods have their places. Roughly speaking, the more the shareholders trust the managers, the more effective the second approach is. Many companies, for instance, provide quarterly guidance, telling shareholders how much money they expect to make next quarter. One purpose of this guidance is to build trust and allow shareholders to evaluate managers’ credibility: If the managers consistently correctly predict next quarter’s earnings, shareholders are more likely to believe their predictions about the further future. But Warren Buffett does not give quarterly guidance, for various reasons, one of which is that he’s Warren Buffett. He has a good reputation and a loyal shareholder base. The shareholders don’t worry so much about checking his work, so he doesn’t need to give them frequent proofs that he is doing what he’s supposed to. Meanwhile Elon Musk has a long history of making medium-term business predictions that are falsified, and it’s fine! Tesla Inc.’s stock price reflects a great deal of optimism about its future in robotics, artificial intelligence, etc., because Tesla’s shareholders mostly trust Musk’s long-term vision. Everyone understands that “we need to check your work every week” is not going to work with Elon Musk, so if you are a Tesla shareholder you are signing up for his long-term vision, not his quarter-to-quarter consistency. But lots of other, more normal companies have more normal managers, and the shareholders do not trust them absolutely. And if the managers say “in 20 years we will make a trillion dollars,” the shareholders will say “wait, really, how?” And if the managers say “shhh, don’t worry about it, go have a nap and check back in 20 years,” the shareholders will be skeptical. The shareholders will want to monitor the managers’ progress toward that goal. They’ll want to check in yearly or quarterly or weekly to see how things are going. And if the company loses money this quarter and next quarter and the quarter after that, and the managers say “shhh, what is important is the long run, we are building the foundation for our long-term trillion-dollar success,” that … might work fine? If it’s credible? That is approximately the story of Amazon.com Inc.? Investors are not idiots; they are aware that the path to long-term profit often runs through short-term losses. Still they want to keep an eye on things. If the losses only get worse, if all the money the company spends doesn’t seem to be buying any market share, then eventually the shareholders might pull the plug. They might conclude that the managers’ long-term plans are bad. They might want to fire the current managers and hire new ones. There is no single magic objectively correct frequency of checking in. In the US, public companies have to report financial results every three months. When they report, they tend to do earnings calls (where analysts can ask managers about how the business is going), and they often provide guidance for future quarters. So US public companies operate on a quarterly cadence. If you lengthened that — if companies reported every six months, say — then the managers would get more time between check-ins; they could focus more on their long-term plans without shareholder questions, and shareholders would have to trust them more. If the managers were mostly trustworthy, that would probably be good: They would spend more time on their business and less time answering shareholder questions; they would have more time to get results without facing shareholder skepticism. On the other hand, the shareholders would have less information. They would have to trust the managers more; they would have less reason to be confident that the managers’ long-term plans were actually working out. If a lot of managers were bad — not trustworthy or just not competent — then the lack of information would be bad for stock values. There would be a market-for-lemons problem: If you knew that lots of companies were not actually maximizing long-term value, but you didn’t know which ones, you would be hesitant to buy all of the stocks. Or rather most of the stocks. Tesla would still be fine. The companies that you want to check up on would do worse, if you couldn’t check up on them. Anyway that’s the basic model. Here’s this: President Donald Trump said companies should not be forced to deliver earnings reports on a quarterly basis, saying he preferred a six-month schedule he cast as saving businesses time and money. “Subject to SEC Approval, Companies and Corporations should no longer be forced to “Report” on a quarterly basis (Quarterly Reporting!), but rather to Report on a ‘Six (6) Month Basis,’” Trump said in a social-media post on Monday, referencing the Securities and Exchange Commission. “This will save money, and allow managers to focus on properly running their companies.” Trump compared the US reporting process to China, suggesting that Beijing had a system in place that was more efficient and cost-effective for businesses in that country. I wonder if the SEC will … approve … this? (Who decides?) I also wonder if the marginal US public company in the Trump era is one that needs more flexibility to focus on its 100-year plan for shareholder value creation, or one that the shareholders need to watch like a hawk. Really the highest calling of a derivative structurer at a bank is: - Dream up a package of bonds and options that is worth $97.
- Dream up a good story for why someone might want that package, a scenario that people might hope for or worry about where the options will pay off.
- Sell it for $100.
There is math involved: You will have an options pricing model on your computer, and you will put all the terms of your package into the pricer, and if it spits out “101” or “99.7” or “91” you will have to adjust some sliders. But mostly it is a business of storytelling. You have some pile of options that you squeezed together to make the pricing work, [4] and you have to convert the dry technical descriptions of those options into some emotionally resonant scenario where the customer will be glad to own the pile of options. Bloomberg’s Yiqin Shen, Lu Wang and Justina Lee have a story today about the boom in structured notes, which opens with an anecdote about a wealth adviser named Gary Garland who puts his clients in structured notes and also buys them himself. He, or somebody, is apparently a good storyteller, because look at this client reaction: The notes Garland bought include dual directional structured products, which are designed to produce gains in either an up or down market within a predefined range. For example, one offered by Barclays Plc caps his potential profit at about 9% when equities rise. But his gain could go to 20% when stocks fall, as long as a bear market is avoided. And even in the worst-case scenario of an equity collapse of more than 20%, his loss is buffered at that threshold (so if the market drops 30%, he would lose 10%). “I had one guy who said, ‘This sounds illegal. It sounds too good to be true,’” Garland says of his clients. “Some are reluctant. Most people have never seen these before. A few have heard of it but may not know what it is. And the ones who see it generally like it.” If you put together a package of derivatives worth $97, [5] and you offer them to a client for $100, and the client says “this sounds illegal, it sounds too good to be true,” then you have a bright future in derivatives structuring. Just make sure it isn’t actually illegal. Meanwhile, the banks are good at structuring and storytelling, but — as we have often discussed around here recently — they are less good than they used to be about taking risk on their balance sheets. The big multistrategy hedge funds increasingly play the role that banks used to play in financial markets, and that’s true in structured notes too. The banks tell the stories and find the customers, but often they offload the risk to the hedge funds: To mitigate their own risks, issuers increasingly offload part or sometimes their entire books through trades with other banks and major multi-strategy hedge funds. That practice enhances liquidity, supporting further expansion of the structured notes market, according to [Laurence] Black at the Index Standard. “We sometimes recycle parts of the book in order to control effectively our overall exposures,” says Quentin Andre, Citigroup Inc.’s global head of equity derivatives sales and multi-asset structuring group. “In the last few years, there’s even been some counterparties who have opened themselves up to the idea of even taking the autocall directly from the bank’s books.” Yeah, look, the hedge funds also have derivatives pricing models. They know that selling a $97 package of derivatives for $100 is just good business. We talk a lot about the standard reason for investing in crypto treasury companies like Strategy Inc. (“they can issue shares at a premium to net asset value, which is accretive to net asset value, so they deserve their premium”), but I do like to occasionally mention the best reason for investing in crypto treasury companies, which is: “It is 2021, I am a long-only equity manager, my mandate does not allow me to buy crypto directly or even in the form of futures or exchange-traded funds, but I think that Bitcoin is going to go up. Strategy is, technically, a US public company in the tech sector, so I am allowed to buy it. And it owns a lot of Bitcoin, so if Bitcoin goes up, it will go up. And sure I have to pay a 100% premium to net asset value to buy Bitcoin in the form of Strategy, but I can’t buy Bitcoin in any other form, and I really want to buy Bitcoin.” Oh don’t get me wrong, one could quibble. The quibble is: “No, you are an equity manager. Your job is not just to make whatever bets you can get away with; your job is to give your investors exposure to the future earnings of public companies. If your clients want Bitcoin exposure, they can get it, at no premium, by buying Bitcoin. You sneakily buying Bitcoin for them in their equity allocation doesn’t do them any favors.” But, you know. If your fund goes up more than other equity funds go up, then you kind of did do them some favors. If you bought quasi-Bitcoin in Strategy form in 2021, you did in fact make a ton of money for your clients. Seems petty to complain. When we’ve discussed this in the past, I’ve mentioned that Strategy’s biggest outside shareholder is Capital Group, the big asset manager. Here’s a fun Wall Street Journal article about the guy who did that: Mark Casey, a portfolio manager with 25 years of experience at the firm, quotes pioneering value-investor Benjamin Graham and says his “approach is very informed by Warren Buffett.” That is why it is so surprising that Capital Group has placed a huge bet on bitcoin—one of the largest by a mainstream investment firm—and that Casey has emerged as one of most outspoken backers of the digital currency in the so-called TradFi world. ... In 2021, Capital Group spent over $500 million to buy a 12.3% stake in Strategy. That made the firm Strategy’s second-largest holder after Saylor, its founder. The mutual fund’s stake—which has shrunk to 7.89% after some sales but mostly because the company issued new shares—is now valued at $6.2 billion after a more than 2,248% surge of the stock over the past five years. Right many quibbles are possible here but it’s hard to argue with the result. We have talked a few times about the high and volatile pay packages for artificial intelligence researchers, which complicate the business of running AI companies. You offer a researcher $5 million to work at your company, she takes the deal, she shows up for her first day, she starts setting up her email, Mark Zuckerberg rappels down from an air vent with $50 million in a sack, she leaves with him — how does anyone get any work done? But if you think it’s hard for you with your $5 million pay package, imagine what it’s like for academic labs that pay on the traditional grad-student scale. At the Information, Andrew Zucker reports: As the frenzy to hire AI talent has intensified lately, it has overturned life in Silicon Valley—and thrown the world of advanced academia into increasing disarray, too as the allure of the corporate AI boom balloons. “I think everybody feels a little bit of the fear of missing out,” said Harvard assistant professor David Alvarez-Melis. That has especially complicated even the best schools’ efforts to recruit and retain doctoral students in AI-related subjects. Like all doctoral candidates, these students form an unglamorous but essential part of academia: They make up a sizable portion of the undergraduate teaching staff and are critical contributors to advanced research led by tenured professors—the kind of work that brings prestige to a school and often supports private-sector efforts. Of course, it also means that fewer of these doctoral students become full professors. If too many of those doctoral students leave early, it could jeopardize the system and, as MIT professor Jim Collins puts it, have companies “eating seed corn for the field,” depleting resources meant to sustain the fertile ecosystem connecting academia and the corporate world. A major reason why Silicon Valley is luring away postgraduates, academics like Collins say, is the simple and ever-widening gap between what doctoral students earn—computer science Ph.D.s at Harvard receive a monthly stipend of $4,205, for instance—and their potential salaries at companies, which can easily start at $1 million. There are not a lot of career paths where the salary range for 25-year-olds is, like, four orders of magnitude. At some point I am going to end up writing about a billion-dollar acquihire of some AI professor’s research lab. Never do this, come on: A quantitative hedge fund firm that added “Alpha” to its name in January to reflect its money-making prowess lost 11.4% this year through August. AlphaQuest has dropped about 30% since October 2022, according to a client report seen by Bloomberg. That’s the worst losing streak since Nigol Koulajian founded the firm in 2001. The hedge fund, previously called Quest Partners, rebranded in January “to reflect the firm’s alpha-driven approach to investing,” it said in a statement at the time. If you are a hedge fund called Quest, we know that your quest is for alpha. Nobody thinks that you’re searching for a holy relic or a kidnapped princess. We get it. But if you rename yourself AlphaQuest and you don’t find the alpha, you are going to get made fun of. Small Businesses Turn to Lending Startups as Tariff Costs Mount. How a former junior lawyer created a $5bn AI legal start-up. Wharton Gets Record $60 Million Gift to Launch Quant Degree. North Korean Hackers Used ChatGPT to Help Forge Deepfake ID. WisdomTree Puts Private-Credit Exposure on the Blockchain. If you'd like to get Money Stuff in handy email form, right in your inbox, please |