In this issue:
Friends,
Happy Mother’s Day!
It’s a nice day for an enjoyable read. I loved this post from Adam Mastroianni:
The essay is insightful and typical of Adam. It’s just so fun to read. Which is itself an exhibit of his thesis.
I stitched together these excerpts, but I encourage a full reading.
The opening
The better AI has gotten, the less anxious I’ve become.
A few years ago, when the computers first started talking, it was reasonable to believe that we would soon be in the presence of omnipotent machines. For someone like me, whose job is to produce words on the internet, it seemed like only a matter of time before I would have to fill my pockets with stones and wade into the sea.
Two intelligences
Some problems have clear boundaries and verifiable solutions, like “What’s the cube root of 38,126?”. These problems require objective intelligence. Other problems are vague and squishy and it’s not clear whether you’ve solved them, or whether they exist at all, like “How do I live a good life?”. These problems require subjective intelligence. Objective intelligence can be trained, reinforced, and validated. Subjective intelligence cannot.
[Kris: smart vs wise]
It’s unfortunate that people use one word to refer to both of these capabilities, when in fact they have nothing to do with each other. It is also, ironically, a case of objective intelligence overshadowing subjective intelligence: these skills are obviously and intuitively different, but a century of psychological research has “proven” that only one of them exists. Over and over again, psychologists have found that all intelligence tests correlate with one another, even when you ostensibly try to test for “multiple intelligences”. Numbers don’t lie, and they all say that there’s only one intelligence, the so-called g-factor.
The problem is that any test of intelligence is only ever a test of objective intelligence. “How do I live a good life?” is not a multiple-choice question. “Discovering” the g-factor again and again is like being surprised that you find the same patch of sidewalk every time you look under the same streetlight.
The Catan fantasy
The promise of artificial superintelligence is based on the idea that objective intelligence is the only intelligence. Or, even if there are multiple forms of intelligence out there, that they are fungible. To be an AI maximalist is to believe we are playing under Settlers of Catan rules, where if you have enough of any one resource, you can trade it for any other resource. If you have infinite objective intelligence, then you have infinite everything.
It’s not just that objective intelligence can’t be transmuted into “emotional” intelligence or social savvy or whatever we want to call it. It appears to be very difficult, if not impossible, to transmute objective intelligence into any other cognitive ability.
When you meet a human who can do quadratic equations in their head but can’t hold onto a job or a relationship, you know they’re missing something upstairs.
Nerds
When I was growing up, this paradox was an endless source of sitcom plot lines—if you’re so smart, nerds, why don’t you figure out how to make yourselves popular? The entrepreneur/essayist Paul Graham took up this question 20 years ago and came to the conclusion that the nerds must not want to be popular. They’re too busy with their Neal Stephenson novels and their D&D campaigns to spend a single brain cycle figuring out how to keep their heads out of the toilet.
I disagree. The nerds I knew in high school—myself included—were always hatching harebrained schemes to increase our social status. They just didn’t work. (”All the girls will want to go to the Homecoming dance with me once they see how many state capitals I’ve memorized!”) We couldn’t use our smarts to make ourselves popular because we had the wrong kind of smarts.
For example, I went to college with a guy who was super smart, but he also couldn’t do anything on time. He would be late to exams. His grades would tank because he would finish his essays but forget to turn them in. He would set meetings with his professors to sort everything out, and then never show up.
I always used to wonder: why doesn’t this guy just use his big brain to make himself more conscientious? Isn’t life one big role-playing game, and isn’t intelligence just experience points that you can assign to any of your Big 5 skills?
Why AI writing vaguely sucks
It’s cool that AI can fold proteins, create websites, fact-check journal articles, etc. but it can’t write anything that I am interested in reading. The problem isn’t that it hallucinates or makes mistakes. It’s that everything it writes vaguely sucks. I drag my eyes across the words and I feel nothing. That’s not quite right, actually—I feel like, “I would like this to be over as soon as possible.” …
Words themselves don’t contain feelings—they are a recipe for creating that feeling inside your own head, to assemble the right set of emotions out of the experiences you have at hand. If I do a good job, the subjective experience that results inside you might resemble the one that originated inside me, but it will never be identical, because we’re working with different ingredients.
The computer doesn’t know any of this. It can’t know any of this. It can only read the cookbook; it can’t taste the meal. Objective knowledge can make your sentences true, but it can’t make them alive. Without access to subjective knowledge, you quickly hit a wall. And unlike all previous walls that AI has surmounted, you can’t overcome this one by scaling—either in the literal or metaphorical sense—because it’s a wall with a width you cannot describe and a height you cannot see.
I unlocked this older post, which found a lot of agreement from senior professionals who have transitioned from a pure trading job to building a business or strategy for asset managers. The target audience is seasoned practitioners. It’s written specifically for option traders but the feedback is that its warnings extend well beyond that market.
We know that there is adverse selection when hiring but this is about avoiding a lemon when getting hired.
Enjoy: adverse selection in the option job market
Brent and Alf have a regular macro podcast. This episode from late 2025 has a number of evergreen trading concepts.
Alf: In our fund, we’ve recently added an alert before you put a trade on. It looks at how much it’s going to cost you to own this position in a relatively vol-adjusted way if nothing happens for the next 30 days. It’s essentially like some sort of carry-to-vol screener.
[Kris: notice how naturally this forces a “thinking in bets” discipline on your opinions]
“Am I really sure this is going to happen or not?”
A Hungarian Forint Example
We had this example where we had all this theory on Hungary. We looked at Hungarian forint and said, “Okay, Orbán is going to go nuts, win the elections, spend money, and the market will punish the Hungarian forint.” Sure, you can be right. You can be wrong.
So how do you trade this? Well, you buy the euro and sell the Hungarian forint. You do the trade, then you look at the carry differential between the two currencies. It’s about 4% yearly carry differential in the forwards. That comes down linearly to about 30 basis points a month.
You think: “30 bips? That’s nothing. I can pay 30 bips in a month. No problem.”
But then you look at the monthly volatility of this thing. It basically doesn’t move. So at some point you realize: the static ex-ante Sharpe ratio of this thing for the next month is like -0.6 Sharpe against me. Holy crap. I need to be not only right—I need to be right with a high Sharpe ratio just to start offsetting the negative carry adjusted for volatility in this trade.
Analogizing to options where the costs are framed more explicitly
A lot of trades are very expensive to own. With options, I think sometimes you fool yourself because you pay for the vol once, and then you say, “Okay, I paid for the vol. That’s what it is. Now I can go long, and this thing can drop to zero, but I did pay for the vol.”
But if you buy 50 options in a year, you pay for the vol 50 times. In options, people do it very lightly but in linear trades, people don’t sometimes think about this, but I think it’s important.
[Kris: I’d broaden this discussion to be a reminder that the cost of carry in addition to opportunity cost is hurdle that your conviction must clear. If it’s not explicit in your in your process consider making it so]
Brent: It’s a different but similar situation where normally you’re dealing with a very high-vol instrument, but you’re paying a crazy amount of money to borrow the stock.
There’s quite a bit of research showing that hard-to-borrow stocks do tend to go down—they’re hard to borrow for a reason. Someone knows a secondary is coming, or it’s a really bad company. There’s usually a reason why it’s hard to borrow and why everyone’s short.
But functionally, the cost to borrow negates the negative return of the stock almost perfectly in aggregate. If you short all the hard-to-borrow stocks, you’ll make money on the shorts and lose about exactly the same amount on the borrow.
A CoreWeave Example
Take CoreWeave—there’s no borrow right now, but there has been off and on, and the borrow was like 150%. Even if you catch a pretty decent move, if you’re not catching it instantaneously, you’re probably not making money.
One simple thing I’ve been doing: when there is a borrow, just selling it at 9:30 AM and buying it back at 4:00 PM. You actually made more money being short that way than holding it—not even counting the borrow—because CoreWeave has a little bit of positive drift in the overnight session.
Even buying EUR/GBP today, I bought some at 0.8573 and rolled it to September 17th. It was 17 pips to roll it. For six weeks on a currency that’s moving 20-30 pips a day, you’re paying 17 pips of roll. That’s not very fun.
Here’s something huge: spurious correlations. Copper tariffs were actually removed. All of a sudden there are no tariffs on copper, and copper goes down like 30% in two days.
Then, do you know what happens to any other high-beta metal? Doesn’t matter what it is—palladium, silver, you name it—goes down 3-4-5 percent. It’s just cascading risk and basically some exogenous event hitting you, not even directly, but laterally, and you lose money.
Brent: Generally, I feel like there’s a lot of good trades like that. Being short silver when copper collapses—but these sympathy trades tend to be very short-lived.
For me, it’s always like: if you’re looking at AppLovin and The Trade Desk, they’re similar companies. When AppLovin craters 50 bucks on earnings, you can sometimes sell The Trade Desk and make four bucks in 20 hours.
But like you said, there’s really no economic reason for the correlations a lot of the time. Sometimes with earnings there is, but with copper and silver, it’s just that a lot of the same people who have that sort of inflation and debasement trade are long copper, long silver, long gold, long Bitcoin. When one part of the portfolio gets a nuclear bomb, they’re forced to liquidate the other stuff.
I do those trades as sympathy trades, but I go in knowing: most of the time, there’s no economic sense to this. It’s more of an endogenous unwind story. So you got to be quick.
Erik has a soft spot for GME so in light of Ryan Cohen’s bid for eBay, we talk about GME options. A fun thing about this casual weekly podcast format is, while we have a loose calendar of discussion topics, we might just talk about whatever grabs our attention. This week was one of those.
📺GameStop and eBay Acquisition What the Options Markets Say
My 4th grader loves the KenKen puzzles his teacher gives. KenKen is a Sudoku-style puzzle invented in the early 2000s.
In this 4×4, grid each row and column must contain each of the digits 1,2,3,4.
The digits in the bold cages must satisfy the arithmetic operation in the cage’s upper left. For example, in the cage with “5+”, the only valid combinations are (4,1) and (3,2).
In this example, I know the bottom right corner must be a 2 because the 7+ cage must include (3,4). 2 is the missing number in the column.
We got the kid a KenKen book for his birthday and my mother saw it while visiting and got addicted herself so we sent her a copy as well.
The puzzles can range from easy to hard and they can have larger grids (ie 6×6 or 7×7). My son likes to make them as well. At first, that sounded difficult but brain fart. I asked him how he did it and he said he just fills out the grid so the row/column rules are satisfied and then you simply cherry-pick your cages and display the operation and target that makes the cage work.
Again Happy Mother’s Day, may the simple pleasures pamper.
Stay groovy
☮️
This week, I hosted class #4 of the Investment Beginnings for local kids aged 12+. The series’…
In this issue: The “three pitches” rule and a lazy man’s framework for getting in…
EWY, the South Korea ETF, was an interesting source of disagreement in our Discord about…
Euan Sinclair needs no introduction from me. I’ll cut straight to the gold. He’s been…
A moontower user sent this [paraphrased] message in our Discord the morning of Jan 9th:…
Remember that chart of CAR last week. (Matt Levine wrote about the fundamentals of the squeeze on…