Friends,
Charlie Munger once said “show me the incentives and I’ll show you the outcome”. Munger is a paragon of wisdom. Just this week I gave one of my son’s besties Charlie Munger’s Almanac for his 13th birthday.
But…there is a but.
As Adam Mastroianni starts in with his essay Startling differences between humans and jukeboxes:
The cause of every social problem, we can all agree, is that people get rewarded for doing the wrong things. Academic fraud, dysfunctional healthcare systems, good-for-nothin’ politicians—all cases of bad incentives.
I used to nod along to these conversations like yes, yes, of course, the incentives! But then I started paying attention and was like, wait, what are we all talking about?
I think there is a monstrous theory of human behavior lurking here—one that I myself have believed—that needs to be dragged out into the light and thoroughly stomped.
What follows is a remarkable essay that put its finger on something I’ve felt — incentives are far from the whole story when it comes to human behavior. The point of my bear on unicycle note is that sometimes our “why” is simply “because we can”.
But Adam closed the circle I couldn’t — Munger’s strong-form contention doesn’t hold (not shocking, there’s always exceptions) but the uneven effectiveness of incentives on people points to a far more complicated picture of humans. And that picture leads to a selection effect own goal (emphasis mine):
When you rejigger incentives in the hopes of changing behavior, you attract the people who are most motivated by the incentives themselves, and these are the people you want to attract the least. Incentive-hunters are bent on Goodharting you, that is, doing exactly what it takes to extract the reward, even at the expense of what you actually wanted them to do.
I always learn fascinating ideas and stories from Adam’s post. He likes to coin catchy terms for behavioral phenomena. This one is no different. Jukebox theory. Secret criminal theory. Find out what they are and more interestingly why they persist despite being the “wrong model of human behavior”.
This is a selection of quotes that stuck for me:
On training researchers:
Eventually I realized, no, what I really want are the students who give a hoot… It’s not that hard to give people skills. It’s way harder to give them interests… trying to substitute external incentives for internal incentives is like trying to power your country with whale blubber when everybody is walking around with a hydrogen cell battery inside them.
An obvious rebuttal to common rationalizations:
Anybody who’s like, “I hate lying to the Securities and Exchange Commission, but those are the incentives in finance!” or “I hate writing crappy papers, but those are the incentives in academia!” or “I hate making hamburgers that are mostly sawdust, but those are the incentives in the restaurant industry!”—they’re admitting that they’re only going to do the right thing when it’s convenient. I want to find the people who are willing to do the right thing even when it’s inconvenient, and hand them some money so they can keep doing that.
On a perverse inversion that slips by us too easily:
When people are like, “It’s too bad these bad incentives turn good people into bad people!” I’m like, “No, it’s too bad these bad incentives allow bad people to exist and succeed.” The good people are the ones who don’t turn bad even when it’s lucrative to do so. In other words:
That tweet is more strongly worded than its underlying veracity warrant but it holds enough truth to make you consider what we let slip by too easily. To accept Munger’s assertion uncritically is to pre-excuse trash behavior in a society-wide shrug of “don’t hate the player, hate the game”. Well, the game is made of players. If the well is poisoned because there were some incentives to poison it and we are somehow just ok with that because we treat outcomes predicted by incentives as laws of gravity then you’ve traded the virtue of norms for the consonance of devil logic.
I don’t know. The fact that this post landed so hard for me makes me think we are numb to how easily we sanewash sinners, worn down by an insidious premise that we are helplessly controlled by incentives. It’s a call to push back on this strong-form assumption that either doesn’t hold or when it does, it’s akin to shining a light on a jellyfish. A spineless jellyfish.
Fortunately, Adam ends with a sentiment that rocks the moontower spirit:
We act as if the improvement of humanity is an engineering problem, when really it’s an unleashing problem.
The only way to solve that problem is to climb out of our own boxes and to help other people climb out of theirs. That, of course, takes courage and trust.
Money Angle
During Cousins Camp this week, I taught the kids a fun trading game.
Each kid has a private number that only they know—like how many students are in their homeroom.
When the market opens players can bid, reflecting the price they would “pay” if the total of all the numbers was a stock, or they can offer, reflecting how much they would “sell” that total for.
For example, when the market closes and we tally the sum of how many kids were in their homeroom classes combined we might get a settlement value of say 140. So if Zak bought a contract for 133 from Max, Zak would have made $7 on the trade while Max’s p/l is -$7.
It’s “open outcry” like a trading pit.
We played many rounds with examples like:
- how many pushups you can do in one go
- how many unique video games you played since the start of 2025
- your best friend’s birthday represented as day of the year (ie December 31 = 365, assume no leap year)…a fun note about this one — the market coalesced around 247 or early September. The actual settlement 2 months earlier. But out of curiosity, we googled the most common birth months — in the US it toggles between Sep, Oct, and Aug which makes me think the solution to a fertility crisis is just having another Christmas in the summertime. Brings new meaning to needing a second coming to save humanity. (Relax, it’s just a joke. Anyway, the fertility crisis is global, a fact that is quite inconvenient to my western logic)
- average of each player’s recent mile time (this was crazy because the market’s final clearing price was liquidly trading at 8:37 and the settlement value was 8:39! On the one hand, it’s a great wisdom of crowds moment but it was also weird — one of the kids had to walk the last time they did the mile and got something in the elevens — I told her she should have been the best bid in the room given her private info, but she wasn’t as aggressive as she should be and that turned out to be correct. When her time was revealed, the other kids couldn’t believe how high it was but that surprise means they weren’t selling aggressively enough — the market was quite balanced at 8:37)
It’s easy enough to play this at home. Just have players write their private info on an index card and you can just start making bids and offers.
A few tips:
- People get confused with official trading language like “bid for” and “sold at” but you can emphasize the importance of just being clear…instruct them to say “I’m trying to buy for 50 because I think the value is higher” or “I’m tryiing to sell at 50 because I think it’s worth less” until everyone gets the hang of it.
- If 2 people trade try to trade with each other but it turns out they are both trying to buy or both trying to sell (“a same side trade”), a common mistake when you are getting used to this, just cancel the transaction as there is “no meeting of the minds” in the parlance of trading.
- Write all your trades on your card— number of contracts, price, counterparty.
- Your final p/l is the sum of (settlement price – buy price) for all longs and (sell price – settlement price) for all shorts. The game is zero sum — the sum of everyone’s p/l should be 0 or the accounting is wrong.
- If you run out of ideas for which everyone has a private value you can use a deck of cards. For example, you could deal 2 cards to say all 10 players and decree that the settlement value will be “the sum of the red cards when they are all revealed at the end” (treating face cards as 10s)
- A fun wrinkle — partway through the game randomly choose a player to reveal their private info. This simulates “new coming out in the market”. An astute player will “bayesian update” their fair value effectively. It helps to have a “theory of mind” of how others will update theirs. This really starts getting to the essence of trading!
The 9-year-olds struggled. I think the concept was a bit too abstract for them to “buy” and “sell” numbers.
The older kids (12 to 14) loved it — “one more round, one more round”. Some kids understood it better than others but one of the fun things about this game is I’ve run stuff like this so many times (usually with adults) that I can tell a number of things about how they think. And very quickly. Every parent likes to hear about their kids, so when the kids weren’t around, I shared my observations with the parents which they enjoyed, usually laughing, nodding with either that “oh I know” look or just beaming with pride.
And a final thought I offered up the kids since they had so much fun…you can trade anything!
When they’re being driven up to the studio they can make markets on how many Teslas they see on the road . Or how many Cybertrucks.
If you pays 10 in the Tesla market and sell 6 in the Cybertruck market you have synthetically bought “4 non-cybertruck Teslas”. Fun stuff. Options arbitrage is just around the corner!
[For those that watched the bar bets video from earlier this week you’ll recognize these as “future style” bets]
Money Angle For Masochists
In the ELI5 vid published this week, I explained how the options market provides a rich understanding of a stock’s distribution and therefore its risk. Using the chart below, I gave an example of 2 stocks, both $100, that had very different return profiles:
The orange stock has much more upside but it’s also far more likely to lose the bulk of its value. In the video, I explain how the option chain reveals this.
My friend Stefan texted me after watching it…
Kris. I just watched your video on stock options. Questions: you mentioned that the underlying options tell you if the stock prices is based on large skew/volatility and that you might not want to have the bio stock as half your portfolio. I own [redacted diversified index ETF] and [redacted risky tech stock]. How can I tell if either of these stocks are like the biotech stock example without doing the math or looking at the options? Is there any way to easily see or tool that tells me?
I’ll share my answer in a moment, but he got 95% of the way there in the text he followed up with before I even got to respond:
That was a chart ChatGPT gave him based on logreturns. The clue is the vol…diversified index vol was 13.5% and for the tech stock it was 63%.
Notice how the tech stock’s expected center of mass is well to the left of the index.
This is the 80/20 answer to the question of how can I tell the risk of some stock…just ask “what is its vol?”
You can pull that from the historical returns or from the at-the-money implied vol of say a 6-month or 12-month option. No need to examine an entire option surface.
This is very informative because your compounded expected return is highly sensitive to the square of volatility.
This was my text back to him:
[I’m grateful that he texted me so I can feel like I matter, but really you can just ask ChatGPT while I kick rocks. Funny enough I’ve gotten texts where people show that LLMs cite moontower. A patronizing pat on the head before I’m fully ingested into the substrate of electric intelligence.
If you do care about more detail, see Geometric vs Arithmetic Mean in the Wild. Go to the heading called this is not just theoretical to see how actual results line up very well to the vol drag formula. This is the gravity of returns, which connects average return to the average return you will actually receive.]
From My Actual Life
2 weeks of Cousins Camp has come to an end. The kids all presented business ideas Shark Tank style to 10 adults. They had 90 seconds to give an elevator pitch seeking capital for startup costs. They subjected to all the typical questions about margins, target market, the problem they are solving and so forth.
I enthusiastically backed 3 startups — an animal cafe where you can hang out with otters (overdue in the US if you ask us), a “we’ll take care of your pets and plants when you’re away” kinda biz, and a Kumon-like school for Financial Literacy. I wasn’t the best bid for that but my niece picked me for strategic reasons — moontower distribution. Smart kid 🙂
The kids range from 9 to 14 so the experience ranged from cute to real. But my favorite part was just how enthusiastic they were all week. They were practicing their pitches, computing costs, thinking about branding while being collaborative with each other but totally secretive from the adults wanting everything to be a surprise.
When they came back from the studio every day it was biking (a few of them learned to do wheelies this week), hitting golf balls, trampoline, doing workouts with one of the dads, or playing hoops/knockout with me. After dinner they clean everything up cult-style before games or movies.
I’m always wistful when camp ends. The other parents would agree with me — it’s the best week of the year and we’re not even one of the kids. Watching them bond and seeing their personalities develop from year to year is unbeatable. It definitely takes planning to make it happen, but if you have ever thought about doing something like this it’s well worth the effort. And if you do it without having them go to a camp together during the day, you can use the budget to customize the entire camp experience (this is our plan for summer 2026, even though it requires more time/effort from the host family).
We move and school starts in 2 weeks. It feels like the end of summer already despite August being peak family vacation month for the bulk of the US that still respects Labor Day as the rightful summer close. Make the most of it, while we shop for soccer cleats and backpacks.
Stay groovy
☮️
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