Longreads + Open Thread

Longreads

• In the interest of equal time, since last week's Longreads + Open Thread included a link to this piece criticizing "automaticity" in research on cognitive biases, here's Astral Codex Ten on how the phenomenon is real and replicates: "But priming only ever claimed to be the observation that our interpretation of stimuli can be slowed down / altered by other stimuli or the broader context, which is obviously true (doubly so if you understand predictive coding)." A nice synthesis here, which the original post does accept, is that truly blunt-force priming works; if you go to a party and there's a big bowl of chips, you're more likely to eat some chips, and if they weren't offered you wouldn't be precisely equally likely to sneak into your host's kitchen pantry to find a snack. But the really subtle claims about priming tend to be weak—though some of those, too, replicate in the sense that the entire field of conversion optimization is an effort to find statistically significant ways to tweak the presentation of a product such that people buy more of it. But that introduces its own selection effect: priming literature will, on average, have a tough time replicating, because the weak effects that work are an asset to businesses that want to beat their competitors, whereas strong effects that are statistical artifacts are an asset to people who really want to publish.
• This is a fun 2005 NYMag profile of hedge fund manager Bruce Kovner, describing him as "George Soros’s Right-Wing Twin." The piece mostly focuses on his non-finance work, especially donations to neoconservative causes. There are two things to take away from this: first, Kovner and Soros are, per the title of the piece, on the exact opposite ends of the spectrum politically. And macro investing is one where political views are quite relevant: if a more egalitarian income distribution disincentivizes wealth creation, or if it redistributes money to people with a higher marginal propensity to spend, this will actually show up in the numbers people are betting on. One might think that there will be times in the cycle where the right-wing macro traders outperform the left, and vice-versa, but Soros and Kovner made their money in around the same period. So this is good evidence that traders either set aside their political beliefs, or at least only incorporate them into a thesis when their side actually has better arguments. The other thing to take away from this is that Kovner's vast wealth might have temporarily affected politics, but in the long run things mean-reverted pretty fast—neoconservatives exist, but aren't nearly as powerful as they used to be. It's a good reminder that even though money matters in politics, it’s not the fundamental driver. Or, at least, it’s possible to throw tens of millions of dollars at advancing an ideology only to see it recede in importance. (And, a minor point, but this piece from almost twenty years ago has a brief joke about how much the media love to cover Donald Trump. Some things never change.)
• Samuel Hammond has a great piece on some of the social implications of AI, starting with the idea that it makes information more readily accessible and moving on to thought experiments about whether we'd get a sort of benign panopticon: "You won’t have to remove your shoes and debase yourself before a TSA agent. Instead, a camera will analyze your face as you walk into the terminal, checking it against a database of known bad guys while extracting any predictive signal hidden in your facial expressions, body language, demographic profile, and social media posts." Which sounds nightmarish—but wait! High-trust societies are already a panopticon where people are being constantly surveilled, but it's less visible because it's voluntary. You're more likely to get shamed for misbehavior when it's unique misbehavior, and it's generally pretty easy to get a read on what local norms are. So this could be another instance of literal technology replacing social technology, the way the Starbucks app with a loyalty program replaces having a local coffee shop where you get better service because the staff likes you.
• In Forbes, Jeremy Bogaisky profiles the CEO of Transdigm. Transdigm is the classic compounder stock, with a 29% annualized return since its 2006 IPO. And it's a classic compounder in another way: an investor only gets paid an excess return for backing a company that repeatedly does the same profitable thing if a) they find a non-obvious case of a company that can do this, or b) their return is, in effect, an insurance premium for some risk the company is running. The Transdigm model is to buy small companies that make aircraft components, and raise prices. These components tend to be monopolies, and they're a classic instance of a product that's a small portion of the total cost but indispensable to the finished product. That creates plenty of pricing power, but also plenty of temptation to abuse that pricing power. As with other cases where a company takes advantage of monopoly economics, it's important to consider the survivorship bias: if investments in this area are predicated on the possibility of such a monopoly, the overall industry's returns can be average because many efforts fail and the successes are extremely profitable. But Transdigm is mostly buying companies that already have a viable business, and is clearly not paying a price that fully incorporates these possible future profits.
• Corey Hoffstein details fifteen things he's learned in fifteen years running Newfound Research. Much of the piece is about how diversification works, how to think about risk, and where you do and don't get paid. One of the best points is #11: "When financial pundits talk about things in the market being absurd, ask "what's the trade?" Working through how to actually profit from the absurdity often shines a light on why the analysis is wrong." He gives a few examples (in that bit and elsewhere) of cases where the market looks like it's offering a massive mispricing, but implementing the trade or looking at the details shows that this is not the case. For example, he notes that large-cap stocks have gotten more expensive as the weighting of energy and financials has gone done, a point recently covered in The Diff. “What’s the trade?” is a powerful question in contexts outside of financial markets, too, since people don’t necessarily demonstrate the same conviction in their behavior as they do in their stated beliefs.
• In Capital Gains this week, we look at the economics of angel investing, and whether or not it's a good idea. In any asset class, different participants have different motivations, and that's what makes a market: equities are a way to save long-term with high variance and high expected returns, but they're also a way to finance uncertain businesses and to compensate employees, for example. Thinking about how these forces balance out is a useful tool; if someone is collecting returns denominated in ways you don't care about, for example, they'll be the natural high bidder for an asset you wouldn't touch. (Think of institutional investors who need to invest in liquid assets so they can run with high leverage—of course they'll pay more for a large-cap growth stock than you will, but they won't be involved in a microcap bank that trades 300 shares on a busy day.)

Books

• Imagine the following far-fetched scenario. A group of fanatical Chicago School Coasians seize control of a small country, and implement the following system: all economic activity is legal, but everyone needs to pay for the externalities that such activity produces. Individuals can rent land and other durable capital, but can't own it, so every productive asset can rapidly change hands when a more efficient operator comes along. This system is weird, chaotic, and subjects more of the economy to market forces than even the US economic system does—but it's actually a reasonably accurate description of the North Korean economy starting in the mid-1990s.
  
  The regime had previously distributed food rations, but the collapse of the USSR meant that North Korea didn’t have enough energy subsidies to run its fairly energy-intensive agricultural system, and the available rations were at a starvation level. So farmers started quietly farming their own plots, and bribing officials to let them do so—which meant that the officials could now buy food at the market (more bribes for people to look the other way here), which started to create a more market-based economy. As factories shut down, people bribed factory managers to let them sell equipment in China for scrap, and then imported Chinese goods to sell domestically. Some state-run companies were viable, and entrepreneurs came up with revenue-sharing deals in order to run those companies on behalf of their state-appointed managers. The result was a bizarre mix of Stalinism by default and anarcho-capitalism for those who could afford it. (And an inconsistent mix of both; sometimes Pyongyang would crack down on markets, import/export businesses, or women wearing pants.)
  
  Andrei Lankov describes such a system in  The Real North Korea. The main thrust of the book is that North Korea's regime is much more rational than we think; they happen to have identified the worst imaginable local maximum in modern political systems, but most of the reforms and compromises one can imagine will make their elites worse-off even if the average North Korean benefits from a higher standard of living and the average person anywhere benefits from a lower risk of nuclear war. It's grim.

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Open Thread

• Drop in any links or comments of interest to Diff readers.
• We remain interested in chatting on- or off-the-record with anyone involved in the design of software products whose typical user is a power user.
• The Diff has written about "compounders" like Transdigm before. Some of them join public markets with their model fully established, but some companies evolve their way towards a repeatable growth model. Are there any good examples of companies that are going through that process right now?

Diff Jobs

Companies in the Diff network are actively looking for talent. A sampling of current open roles:

• A company building ML-powered tools to accelerate developer productivity is looking for software engineers. (Washington DC area)
• 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 vertically integrated PE-backed company applying a rigorous investment/operations approach to a high-growth industry is looking for an analyst who has banking experience. Strong Excel skills a must. (Little Rock, AR; remote possible)
• An early-stage startup aiming to reduce labor costs by over 80% in a $100bn+ industry is looking for a part-time technical advisor with robotics experience; this has the potential to evolve into a full-time role. (NYC)
• A startup building a new financial market within a multi-trillion dollar asset class is looking for generalists with banking and legal experience. (US, Remote)

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.