- Robin Wigglesworth at the FT has an oral history of the VIX. The way the VIX works is roughly this: expected volatility is an unobservable input into the Black-Scholes formula for valuing options, so one thing you can do with the formula is invert it: instead of calculating the right price for an option, you can use the market price of options to calculate the level of volatility options traders expect. This turns out to be a good indicator of extreme market movements (and, of course, these extreme movements tend to be downward). As it turns out, the VIX's history as a tradeable instrument rather than an abstract indicator is more tortuous than you would think. One surprise bit player: Mark Cuban, who asked to buy the VIX when such a thing wasn't actually possible. That's a good parable about innovation generally: sometimes what it takes is someone asking "Why can't you just sell me X?" (The verb here is important: a hypothetical idea for a product becomes less hypothetical when there's a willing customer.)
- Stacy Perman profiles pro-wrestling empressario Vince McMahon for the LA Times. In one sense, McMahon is the most honest CEO around: every CEO plays some kind of role (conscience of the industry, elder statesman, brash challenger, etc.), But McMahon has also been a character in pro wrestling storylines, so he has to be more open about the fact that his public persona is just that—a persona, played by a talented actor who, like many other entertainment professionals, has a sometimes messy personal life that sometimes collides with work.
- Vauhini Vara writes in Wired about using AI to write fiction. If someone's going to write a piece like this, it's only interesting if it goes all out, and this one does: "[t]he essay was adapted for This American Life and anthologized in Best American Essays. It was better received, by far, than anything else I'd ever written." The story does have an unhappy ending, however: as LLMs get RLHFed into being nicer and more polite, they lose the edge that's needed for compelling fiction. It's another instance of AIs being surprisingly human: they're more creative when they're dealing with deep trauma, and once they get over it they simply have less to say.
- Rohit Krishnan writes about, and diagrams about, the path of innovations. The idea of a "tech tree" is an abstraction from video games, but it's a useful one: new ideas have dependencies on older ones, and often synthesize multiple fields. (Who in the early twentieth century would have predicted that Boolean logic and quantum physics would lead to computing?)
- And in another instance of the unpredictable side effects of technology, Nick Niedzwiadek covers how the introduction of air conditioning changed Congress' schedule in a way that made political fights over the budget fiercer. Air conditioning is an important technology for agglomeration generally, since it means that more people can work all day, year-round, and from anywhere, and that means more potential chance encounters and more unbroken stretches of conversation. But as with other technologies, it can have surprising interactions with norms that were established with different real-world constraints.
Via The Browser. And The Diff has written about how air conditioning contributed to the end of regional stock exchanges.
- Aziz Sunderji at Home Economics writes about how the Danish financial system avoids one of the pathologies that of the US mortgage system. Some financial products are the result of convergent evolution; just about every system has some idea of a loan, and once your financial system incorporates credit it needs a residual claimant, i.e. equity. But mortgages are a creation of both markets and policy, since the world generally has more demand for housing than for the long-term loans that fund it at rates that homebuyers would consider affordable. The question is always this: if we’re going to subsidize home ownership, and we do so through the credit market what set of market distortions provide the most cost-effective subsidy with the least bad side effects?
- And in Capital Gains, we covered why investors, companies, and countries hedge their foreign exchange risks. Hedging is costly, and in the very long run it tends not to make much of a difference—sell products in a country with a depreciating currency, and you'll find that it's usually easy to raise prices; hedge against the risk of a volatile currency, and you'll definitely pay for it. But the long run is made of a series of short runs in which unexpected cash shortfalls due to exogenous events can be costly.
- Damn Right: Behind the Scenes with Berkshire Hathaway Billionaire Charlie Munger: One very abstract way to understand people's skills (both your own and that of others) is to think about their relative ability to 1) execute some known task, versus 2) continuously reinvent themselves and determine what they ought to be doing differently for task #1. Warren Buffett's career has been justifiably studied because of his extreme skill at the first, but Charlie Munger made a major contribution to Buffett's track record by pushing him to reevaluate where he focused his energy. Buffett and Munger both did plenty of scrappy deals early in their careers, buying mediocre companies at a massive discount to their fair value and selling once that value had been reached. But it's a lot harder to do that at scale. You can find profitable or potentially profitable companies trading at less than net cash if you're looking at $50m market caps and below, but it's not going to happen if your cutoff for a needle-moving investment is a $5bn or $50bn market cap instead.
Munger's story is a good case study in skill and serendipity: he might have been a fairly successful LA-based real estate developer and lawyer with a reputation for loquacity if he hadn't tied up with Warren Buffett. On the other hand, if Warren Buffett hadn't gotten the message on quality businesses from Munger, perhaps he'd be an oddball Omaha fixture, a frugal guy who made millions but not billions investing in textiles, local banks, steel mills, and the like. Extreme success comes from mastering games and metagames, and in this case it was a team effort, with Munger handling the metagame and Buffett excelling at whatever the specific game happened to be.
One frustrating note about this book is that it just doesn't give enough detail about Munger's transition from someone who earned a salary and made investments on the side to full-time capitalist. It's surprisingly hard to find details about Munger's hedge fund in the 60s and 70s (it's easy to find their biggest positions, but one of those positions was a closed-end fund that Munger & Co. took over in order to redirect its investments into better businesses. But which!?). And the book sadly omits this story, about how Munger would be worth multiples of what he has today if he'd bought one more small block of an obscure oil company in the 70s, which sold for 30x his cost a few years later. (This is a good case study in why you shouldn't overrate luck: in an alternate world where Munger had bought that stock, clever people might point out that 80% of his net worth ultimately derived from one decision to call a broker back and make a trade. Whereas what probably really happened was that not making the trade meant that it took a few more years for Munger's capital base to reach the point where it compounded closer to 15% annually than 30%.)
- Drop in any links or comments of interest to Diff readers.
- A good question to ask from time to time: what are some markets that should exist, but don’t? Sometimes a market is hypothetically possible because there are interested potential traders on both sides, but there isn’t a good asset that lets them meet in the middle, or the information asymmetry is so wide that everyone prudently expects their counterparty to be ripping them off. But information advantages tend to shrink because data gets cheaper (at least until people are using it to get an advantage in zero-sum markets!), so over time the number of viable markets should continuously rise.
Companies in the Diff network are actively looking for talent. A sampling of current open roles:
- A fintech startup that lets investors trade any theme as if there were an ETF for it is looking for a senior backend engineer. (NYC)
- A VC backed company reimagining retirement wealth and building a 401k alternative is looking for fullstack engineers with prior experience in fintech. (NYC)
- A successful crypto prop-trading firm is looking for new quantitative developers with experience building high-performance, scalable systems in C++. (Remote)
- A new fintech startup wants to bring cross-border open banking to LATAM, and is looking for a founding engineer. (NYC)
- A data consultancy is looking for a senior data scientist with prior experience in marketing data science and e-commerce. (NYC)
Even if you don't see an exact match for your skills and interests right now, we're happy to talk early so we can let you know if a good opportunity comes up.
If you’re at a company that's looking for talent, we should talk! Diff Jobs works with companies across fintech, hard tech, consumer software, enterprise software, and other areas—any company where finding unusually effective people is a top priority.