Notes from RenTec CEO Peter Brown on the GS Podcast

Podcast: Goldman Sachs Exchanges: Great Investors

Raj Mahajan, global head Systematic Client Franchise interviews Renaissance Technologies CEO Peter Brown on July 27, 2023

I grabbed some excerpts from the transcript for future reference.

I include my own commentary here and there.

Newsflash: Money is a big factor in what people choose to do

Raj Mahajan: Seems that you were right at the vanguard of the machine learning movement in 1993. So, why did you leave an exciting career at IBM for a small financial company in Long Island that no one had ever
heard of?

Brown: …Three things happened. First, Bob had a second daughter accepted to Stanford. But he couldn’t afford to pay for her to go to Stanford on his IBM salary. So, she had to go to the agricultural school at Cornell, which offered scholarships to New York State residents. The second thing that happened is we had a daughter born. And a third thing was that Jim then offered to double my compensation. After that offer, I came home. I took one look at our newborn daughter and realized I had no choice in the matter. So, the decision to leave computational linguistics for a small hedge fund that no one had ever heard of was made purely for financial reasons.

Examples of Emotional IQ

[Kris: The EQ vs IQ thing is a false dichotomy. I suspect they are actually positively related but when we look at outliers on either dimension there is a major Berksons Paradox effect. RenTec has the reputation of being the true “smartest guys in the room” in the IQ/STEM sense of the word. And yet, multiple times in this interview I am struck at how people-savvy they have been. Which makes perfect sense to me. In a domain where the competition constantly learns and psychology plays an enormous role this is exactly what you expect. Only the naive who believe that investing is physics as opposed to biology cling to Spock-like caricatures of effective quants. Here are several excerpts demonstrating an deep understanding of human behavior]

Selling an approach to employees

Brown: At the end of 2002, Bob and I also took over the rest of the technical side of the firm, which included the trading of currencies, bonds, options, and futures. Now, our plan was to use the equities code that we and others had developed to trade these other instruments. But we recognized they would not be so great for morale to tell, say, one of the futures researchers, “You know all that code you spent the last decade of your life developing, guess what, we’re going to throw it out.” So, we had to spend quite a bit of time getting everyone to buy into our plan. To do this we used an approach that I learned from a biography I’d recently read of Abe Lincoln, which was to get them to come up with our plan themselves. Now, that took some time, but eventually it all worked out.

Jim Simons weighing the input to manage a risk crisis

See below: 2007 — “Quant Quake”

Jim Simons reading a situation shrewdly

Brown: In the fall of 2008, the whole financial system was stressed. So, we were concerned with the stability of our counterparties. So, we spent a lot of time with those counterparties and examined their CDS rates and so forth. I remember at one point, two senior executives from some firm we did business with came into our New York City office to meet with us. They assured us that the funds we had in our margin account were safe with them. And I was inclined to believe them. Why not? But after the meeting, Jim said, “Peter, they wouldn’t have come to our office. They wouldn’t have requested the meeting unless they were in real trouble. It’s time to get out.” So, we did. And Jim was right because shortly thereafter, that firm just disappeared.

Examples of automation and innovation within RenTec

Brown: When we got control of the New York office, the first thing I did was to walk around that office, find out what everyone was doing. And what I found was that many people were doing jobs that could be automated. So, we set out on a massive campaign to automate our back-office operations. We moved from checks and wires to SWIFT and ACH. We replicated counterparties margin calculations. We built a large legal database that could be accessed by computers to fill out regulatory forms. We brought in AI systems to automatically read and pay invoices. We automated the treasury department so that cash and margin needs could be managed by computers instead of humans. My point of view was that Stony Brook produces a huge list of transactions and New York City produces monthly statements, K1s, and government filings. And I just didn’t see why humans need to be involved in the process of translating trades to monthly statements. Now, 13 years later, we’re not done yet. And I’m embarrassed to admit that we still even have a few people who use Excel. But we’re getting there. In fact, I was told recently that we’ve eliminated 97 percent of the spreadsheets that had originally been used in the company.

Stories about risk management

March 2000 — Dot Com

Brown: Let me start with March of 2000 when the dotcom bubble burst. We were doing extremely well back then. And we had large positions in the internet stocks. They were traded on NASDAQ. At one point the head of risk control came to me and said he was worried about the size of our NASDAQ positions. But I told him not to worry, the computer knew what it was doing. Then we took a big loss one day. So, I worked through the night trying to understand what was going on. The next day we took another big loss. And I, again, worked through that night. So, now it’s the third day and I hadn’t slept for, I don’t know, 48 or 50 hours. And I was sitting in a meeting with Jim and a few others when the head of production knocked on the door and asked to speak with me. I walked out of the meeting, and he told me we were down again by a large amount. So, I walked back in the meeting, and I must have turned white or something because Jim took one look at me and said, “It doesn’t look good.” Now, not having slept the previous two nights, I remember thinking I’m not sure I can get through this. But I really didn’t have much choice in the matter. And so, we got back to work and eventually we did get through it. A couple days later I went into Jim’s office and told him that I’d screwed up in not appreciating the risk we were taking and said that if he wanted me to resign, I would resign. But he responded, “Peter, quite the opposite. Now that you’ve been through such a stressful losing period, you’re far more valuable to me and to the firm than you were before.” Now, that response really tells you something about Jim Simons.

2007 — “Quant Quake”

Brown: When that happened, I was on vacation, and I was on a very long flight back to Newark Airport. And the moment the plane landed, my phone went nuts with all kinds of texts and missed phone calls. So, I called into work when it was going on and I got Kim, Jim’s assistant. And she said, “Jim wants you to get back here as soon as you’re physically able.” So, I raced out. I found a taxi, leaving my family to fend for themselves at Newark Airport. And pushed the driver to drive as fast as he could from Newark to Long Island. I ran into my office, and I found Jim, Bob, Paul Broder, who was head of risk control, all holed up. And the office was full of cigarette smoke. I could barely breathe. And then there was this, I remember seeing this, 16 oz cup full of Jim’s cigarette butts. And I’m thinking, like, why do they have to do this in my office? And they were all staring through the haze at the computer screens trying to figure out what was going on. And Jim was interpreting every little wiggle and various graphs. He was really scared. And he wanted to cut back and hard. Paul also wanted to cut back. Raj, I’m sure you know, the head of risk control always wants to cut back. Because he doesn’t get paid to make money. He gets paid to make sure you don’t lose money.

And Bob, you know, Bob’s always very calm. But he wasn’t against cutting back. But I looked at the data and saw that the model had these enormous predictions, the likes of which I had never seen before. It was clear to me what was going on. People were dumping positions that were correlated with their own positions. And they were driving prices to ridiculous levels. I felt they had to come back. I argued that we should not cut back. That this was going to be the greatest moneymaking opportunity we’d ever seen. And if anything, we should increase our positions. But it was three against one. And so, we continued cutting back. But I succeeded somewhat because we cut back at a slower pace. And then at one point, miraculously, the whole thing came roaring back. And indeed, it was an incredible money-making opportunity. Now, what we learned from that was to always make sure we have enough on reserve to just hang on. Later, when Jim was about to retire, I reminded him of this period and asked if he was concerned that I was going to be so aggressive that I was going to blow the place up. But Jim responded that the only reason I was so aggressive was because I knew he was determined to reduce risk, another example of Jim’s insight into human nature.

What RenTec does differently

Brown: I guess there are some firms that make it their business to learn how others make money and try to learn their secrets. That’s not our style. We just hire mathematicians, physicists, computer scientists with no background in finance and no connections with Wall Street.

A few principles we follow:

Science
The company was founded by scientists. It’s owned by scientists. It’s run by scientists. We employ scientists. Guess what, we take a scientific approach to investing and treat the entire problem as a giant problem in mathematics.
[Kris: In chatting with a friend who has proximity to RenTec, I learned of this a few years ago. I was intrigued by how they felt quite comfortable incubating highly promising individuals by offering a well-paying collegiate atmosphere that offered an alternative to traditional academia. It feels like just another instance of what I call risk absorption. RenTec is a highly efficient “bidder” for the risk of a scientist’s effort panning out. They can build a portfolio of talent in the form of a skunkworks knowing that they can scale important discoveries across their trading. Not unlike how a military R&D department might think of investments in scientists.
Collaboration
Science is best done through collaboration. If you go to a physics department, it would be absurd to imagine that the scientist in one office doesn’t speak to the scientist in the office next door about what he or she is working on. So, we strongly encourage collaboration between our scientists. For example, we encourage people to work in teams. We constantly change those teams up so that people get to know others within the firm. We pay everyone from the same pot instead of paying different groups in accordance with how much money they’ve made for us and so forth.
Infrastructure
We want our scientists to be as productive as possible. And that means providing them with the best infrastructure money can buy. I remember when I was at IBM, there was this attitude that programmers were like plumbers. If you need a big project done, just get more programmers. But I knew that some programmers were, like, ten times or more productive than others. I kept pushing IBM management to recognize this fact. But it did not. I remember being in an IBM managers meeting and some guy from corporate headquarters was explaining how they created something called their headlights program. The goal of which was to identify the best programmers in the company and pay them 20 percent more than the other programmers. Now, I figured this guy from corporate was making, like, $300,000 a year. So, I raised my hand and suggested they increase the pay of their best programmers to $400,000 a year. And he was stunned. He said, “What? More than me? You’ve got to be kidding me. Well, if the guy’s Bill Gates.” I said, “No, Bill Gates was making, like, 400 million per year. Not 400,000.” Anyway, they just didn’t get it. We don’t make that mistake. We pay our programmers a ton in accordance with the value we place on the infrastructure they produce.
No interferenceWe don’t impose our own judgment on how the markets behave. Now, there’s a danger that comes along with success. To avoid this, we try to remember that we know how to build large mathematical models and that’s all we know. We don’t know any economics. We don’t have any insights in the markets. We just don’t interfere with our trading systems. Yes, of course there are a few occasions where something’s going on in the world and so we’ll cut back because we think the model doesn’t appropriately appreciate the risk of what’s going on. But those occasions are pretty rare.
Time
We’ve been doing this for a very long time. For me, this is my 30th year with the firm. And Jim and others were doing it for a decade before I arrived. This is really important because the markets are complicated and there are a lot of details one has to get straight in order to trade profitably. If you don’t get those details straight, the transaction costs will just eat you alive. So, time and experience really matters.

A word on politics

[Kris: Peter Brown is liberal and co-CEO Bob Mercer is famously conservative. I can say that coming from the trading world, the liberal perspectives are in the minority amongst the traders but less so amongst the academics.]

Raj Mahajan: Is it true that while Bob Mercer and you have different politics, you worked closely for nearly 40 years at IBM and Renaissance?

Peter Brown: Yes. It’s true. Bob and I began working together at IBM 40 years ago. And for most of the time, we’ve had offices right next to one another. So, we’ve done a lot together. And we’re still really close. In general, I find no better way of building friendships than through the collective creative process of building something together. And I see no reason why politics should interfere with friendship.

Man vs machine stories

1) My understanding is that you had nothing to do with finance until age 38 and, instead, began your career working on automatic speech recognition. How did that happen?

Brown: So, at one point during high school I learned about the Fast Fourier transform. And I thought this was about the coolest thing I had ever seen. Probably because I went to an all-boys’ school and had nothing better to contemplate. Anyway, for some reason I got into my head that with the Fast Fourier transform it should be possible to recognize speech. You just take the speech data, transform it into the frequency domain. Match it up against patterns for words. And presto, magic, HAL would be born. And this idea always stuck around in the back of my mind.

Then when I went to college I majored in math and physics. But in my senior year I had to fulfill a distribution requirement. So, I took a course in linguistics. And one day in the back of that course I heard a couple students talking about some guy whose name was Steve Mosher who started a company called Dialogue Systems that was doing speech recognition. And I thought, wow, great, I remembered this idea from back in high school. After class I raced over to the physics library. That’s because this was before the internet, so you had to go to the library. And I looked this guy up. And I found a paper he’d written. And I tracked him down. Applied for a job. And he hired me. And when I was there, I just fell in love with the idea that through mathematics it might be possible to build machines that do what humans do. I just loved the idea of exposing human intelligence to be nothing more than robotic computation.

2) I recently heard that in a talk you give at Harvard Business School you mentioned that you had a role in starting up the Deep Blue project at IBM. Can you tell us about that?

Brown: Wow. Okay. I had been at IBM for a year or two. And I was standing in the men’s room one day when the vice president of computer science, a man named Abe Peled walked up next to me. I thought to myself, now’s my chance. I turned to him and said, “Dr. Peled, do you realize that for a million dollars we could build a chess machine that would defeat the world champion? Think of the advertising value to IBM.” He turned to me, looking kind of annoyed, and said, “What’s your name?” So, I told him. And then he said, “Could you please let me finish up here?” And so, I thought, wow, I had made a big mistake. So, I apologized, and I high tailed it out of there as fast as I could hoping he’d forget my name even faster.

But a half hour later, he called me in my office and told me that if I wanted to build a chess machine, he’d put up the million dollars. I told him that I was occupied with speech recognition. I have three friends from graduate school who could build it. He said, “Okay, hire them.” So, we did. They built the machine. I named it Deep Blue. In the first match, the IBM machine was a very weak machine. Weak physically. You know, I think only one special purpose chip in it. And we lost. The final match, however, was a different story. IBM had a much, much stronger machine with hundreds of special purpose chess chips. IBM won that match and IBM’s stock jumped $2 billion afterwards. Of course, it fell back down later.

Now, a few years ago I was asked to speak at the Harvard Business School. And when I arrived, outside the auditorium, I could see all these protesters. And I thought, oh no, why are they protesting me? What have we done? Is there something I’m not aware of? I really didn’t want to do that. But as I got closer, I could see they were all holding signs about investing in Puerto Rico. And I thought, what is this all about? I was totally confused because I didn’t think we had anything to do with Puerto Rico. Then it turned out that the speaker before me was some guy named Seth Klarman from some firm named Baupost. Evidently, that firm had some investments in Puerto Rico and the protesters were protesting him. So, I went in to see Klarman’s talk, or at least the end of Klarman’s talk, to find out what all the hullabaloo was about.

At the end of his talk, someone asked him his thoughts on quantitative investing. I suppose it was a set up for my talk. I don’t know. And I carefully noted his answer which was, “To do what I do takes a certain amount of creativity and finesse that a computer will never have.” And all those Harvard Business School MBAs seemed to really like that response. So, when it was my time to speak, right after him, I began by pointing out that after defeating Deep Blue in the first match, Kasparov was elated and gave a press conference at which he said, “To play chess at my level takes a certain amount of creativity and finesse that a computer will never have.”I then went on to point out that two years later we crushed him. Now, I’m not sure that’s how things will evolve. But whether it’s speech recognition, machine translation, or building large language models, or chess, or making investment decisions, I continue to love the process of showing that human intelligence, intuition, creativity, and finesse are nothing more than computation.

[Kris: In defense of Klarman, like the pod shops, I don’t think RenTec is investing so much as trading. Marc Rubinstein writes:

Dmitry Balyasny, founder of Balyasny Asset Management, attributes the model to a trading view of markets as distinct from an investing view.

“[Its] origins go back to my origins as a trader and thinking about how to build out business around trading… It makes sense to have lots of different types of risk-takers, because you have less correlation, you could attack different areas, the markets, and have specialists in different areas.”

I’ve beat that drum in Trading vs Investing and with great humility in How I Misapplied My Trader Mindest To Investing.

Addressing Brown’s obsession with “exposing human intelligence to be nothing more than robotic computation.”

In The Introspection of Illusions, author David McRaney parses opacity of the intelligence and preferences buried in our subconscious:

Psychologically speaking, users found it easy to access the feelings that prompted them to give those films one star or five. Explaining why they made one feel that way would require the kind of guided metacognition that the Netflix interface simply couldn’t offer. Even when you stepped away from the code and the spreadsheets and asked people in person, they might not be able to tell you. They could make a guess. They could attempt to explain, justify, and rationalize their feelings, reactions, and star ratings, but without a conversational tool, a back and forth to get past all that to something honest and perhaps previously unexplored, you ran the risk of precipitating a psychological phenomenon known as the introspection illusion which would likely result in yet another phenomenon known as confabulation. There’s an entire literature of books and papers and lectures and courses devoted to this side of psychology. To put it very simply, we are unaware of how unaware we are, which makes us unreliable narrators in the stories of ourselves. You are, however, amazing at constructing stories as if you did know the antecedents of those things when explaining yourself to yourself and/or others.

There are parts of us we can’t access, sources of our emotional states we can’t divine, and I find some strange poetry in the fact that, like us, the algorithms can’t always articulate the why of what we do and do not like. Yet, through millions of A/B tests slowly zeroing in on more and more successful correlations, the Netflix Recommendation Engine can produce a glimpse of something a bit like the sort of profound, soul-exposing knowledge earned via an intense introspection that we could never achieve. Something a few fathoms deeper than “I don’t know, it just wasn’t for me.”

Speed Round

1) Is it true that at one point you went to IBM to suggest that the statistical methods you were using in speech recognition could be applied to finance, and asked to be given an opportunity to manage some fraction of IBM’s corporate cash?

Brown: Yes. I think that was in 1993. But IBM corporate had absolutely no interest. So, instead we went to Renaissance where we did the same thing we had in mind for IBM, but instead with money Jim Simons had raised.

2) Is it true that since you first joined Renaissance you have spent nearly 2,000 nights sleeping in your office?

Brown: Yes. My wife works in Washington DC. And my experience has been that when a husband and a wife work in two different towns, the husband commutes. Psychologically, if I’m going to be away from my family, I have to work. I sleep in my office when I’m in Long Island.

For me, productivity-wise it’s really fantastic being able to spend nearly 80 straight hours each week with no interruptions except sleep thinking about work before spending three more normal days at home. Of course, I really miss my family. But the freedom to concentrate nonstop on work while surrounded by my colleagues is hugely valuable. And the job is so demanding, I really don’t see how I could do it otherwise.

[Adds this] I’m just one of those types who can’t sleep. Not by choice. I just can’t sleep. So, I often am on the computer by around 2 am. And it’s true, I tend to send a lot of emails out in the middle of the night.

3) Is it true that you almost exclusively hire people with zero background and finance?

Brown: Yes. We find it much easier to teach mathematicians about the markets than it is to teach mathematics and programming to people who know about the markets. Also, everything we do we figure out for ourselves. And I really like it that way. So, unlike some of our competitors, we try to avoid hiring people who have been at other financial firms.

[Kris: The prop trading firms think similarly. My friend Joel talks about how Brown’s claim that it “is is easier to teach markets to mathematicians than it is to teach math to market experts, may seem dismissive to market-centric people but in reality is more of a statement about what “math” is at Renaissance.” He goes on to distinguish about levels of math but I latched on to this a more general observation:

Markets person isn’t a thing. Markets thinking is systems thinking and anyone from any discipline can learn that. From there go on Investopedia and learn how a zero coupon bond or share of stock works. start with a good, teachable mind then label the variables.

Math/STEM skills are legible markers of computational/rigorous thinking. Someone trained in the nitty gritty of assumptions, what follows, and so on. Making abstractions concrete.

If I’m generous it took a month of professional training for non-finance STEM grads at SIG to know everything finance grads would have brought to the table. But you can’t teach math and computer science in a month.

Ultimately this is only part of the story of getting a great start in finance. There’s a Berksons Paradox once you are in the pool of high level finance employment where the math skills don’t correlate as much with talent. You get older and realize the dichotomy of being a math person vs a verbal person that you carried as an identity when you were young is bullshit. Skills in either are likely highly correlated. But maybe the right door or guidance wasn’t there to help you see that.]

4) What do you actually look for in applicants?

Brown: Math ability. Programming ability. A love for data. A work ethic. And most importantly, the ability and desire to work will in a collegial environment.

5) How do you actually assess those qualities?

Brown: I think probably the same way other firms do. First, we get resumes. Those that look promising we give them phone interviews and we ask them for references. If those pan out, then we invite the promising applicants to give research talks. Talks like if you’re applying for a job at a university or something like that. And then we put them through a grueling day of solving problems in math, physics, statistics, computer science, and so forth at a blackboard.

6) Is it also true that your staff had to install mirrors in the corners of the office to prevent you from flying into people as you rode a unicycle around the office?

Brown: Where did you get all these questions from? Yes, it’s true. Although, I don’t ride a unicycle anymore because at one point I crashed and the unicycle broke.

Moontower #198

I saw this tweet from David:

Everyone understands this feeling.

I heard an interview recently that discussed the psychology behind this behavior.

I’ll cut to the link:

🔗David McRaney on EconTalk

Episode description:

To the Founding Fathers it was free libraries. To the 19th century rationalist philosophers it was a system of public schools. Today it’s access to the internet. Since its beginnings, Americans have believed that if facts and information were available to all, a democratic utopia would prevail. But missing from these well-intentioned efforts, says author and journalist David McRaney, is the awareness that people’s opinions are unrelated to their knowledge and intelligence. In fact, he explains, the better educated we become, the better we are at rationalizing what we already believe. Listen as the author of How Minds Change speaks with EconTalk host Russ Roberts about why it’s so hard to change someone’s mind, the best way to make it happen (if you absolutely must), and why teens are hard-wired not to take good advice from older people even if they are actually wiser.

The best teaser for the interview comes directly from it when McRaney says:

The incepting point of this book was someone in a lecture came up to me and asked about their father who had slipped into a conspiracy theory and they said, ‘What can I do about that?’

And, I told them, ‘Nothing.’ They said, ‘How do I change his mind?’ I said, ‘You can’t.’ And, I really felt, the second I said it, that: I don’t know enough about this to say something like that. I don’t even know if I believe what I just said, but I know one thing I don’t like this attitude I have about this issue. I should at least learn more about it.

And, if I was in that same situation today, I would actually be able to say, ‘Oh, here’s what you should do. Here’s what you should say.’ I no longer believe anyone is unreachable. I no longer believe anyone is unpersuadable.

In conversations that don’t work out the way we think, we blame the other side. We say, ‘They’re dumb. They’re mean. They’re evil. They’re ignorant. They are unreachable, unchangeable, stuck in their ways.’ These are all things that we are using to forgive ourselves for failing.

Listen to the interview. My excerpts are just what I wanted to keepsake. My notes covered:

motivated reasoning for social acceptance
the process of radicalization
reactance (or what I call “reflexive contrarianism”)
shaming
specific approaches that work to unblock discussions
“street epistemology”
cognitive empathy

If you do nothing else, zoom in on the “reactance “section which I titled this post for — that feeling of “F you I won’t do what you tell me” is ingrained and worth understanding.

If you know the reference, you know RATM. And just in case you’ve never seen it — the video below is a recording of one of their first public concerts. It was filmed in 1991 at Cal State Northridge. It’s a bizarre scene juxtaposing a routine day on a sunny campus quad against the band’s angry energy. An ice cream social with an a cappella group like Chorus against The Chaos would have drawn a crowd faster.

Zach is unfazed. By the end of Bullet In Your Head, the audience starts noticing. If you consider the state of rock just coming out of the 80s (Nevermind was released only 3 months before this performance) and the relative infancy of hip-hop this performance must have been pretty alien.

They would go on to release their debut album a year later and play a side stage at the second Lollapalooza.

They’d play the main stage one year after that.

[Unclassified personal thought: I like watching old concert videos. I’d waste one of my 3 genie wishes to have the power to peer into the present of the audience members I see in these old clips. It’s an escapable thought every time I watch them. Like knowing that skinny, shirtless viper with the long hair slithering to the groove is now bitchin’ about Blackrock makin’ his truck expensive to fill up. Mind you he’s a landlord in Laguna where he bought his first bungalow in 1972. Discovered the town after catching the Dead at the Newport Pop Festival a couple miles down the road a few years before that. A show he hitchhiked to from Indiana while running from the life the ”squares” back home had envisioned for him.

The brightness of youth casts a shadow — the finer rays suggest their own sorrows]

Money Angle

Last Wednesday in Investing With Your Hands On The Wheel, I beat my old drum that trading isn’t really something one does “on the side”. Trading is a business. And I am quite skeptical about the reward per unit of effort for playing Nostradamus in your investing portfolio. I know there are people who disagree with me on this. I’ll happily grant them their track records at face value but wave the plane with zits at them:

The quote:

I’m pretty much in the camp of “get a job where you can do this full-time if you really want to”. If you can’t do this but still want to explore strategies, then fence out some capital to play/learn/experiment…

For the rest of your assets stick with some kind of permanent portfolio implementation depending on your risk tolerance. You can follow folks like Corey Hoffstein, NomadicSamuel, Jason Buck, Lily for that stuff. InvestResolve guys too. All these tweet about it too and it’s all quite solid. I recommend this series by the InvestResolve team.

My gut feel is return-stacking/permanent portfolio for long-term DCA is probably the efficient frontier of work/return/risk triple axis.

If you insist on being active, there is a totally acceptable framing too:

But there’s no doubt that many people want to put their hands on the wheel and that has innate personal value (and that’s true whether it’s misguided or not). So in short I think it’s a tree:

DCA permanent portfolio variant if you want autopilot

If you want to put your hands on the wheel what does that efficient frontier of effort/return/risk look like where return also includes some illegible component of DIY satisfaction?

I should probably pull together a new Moontower wiki of permanent portfolio content that I like. It might be an insurance policy against me never writing the Implementation portion of moontowermoney.com

[I have all the material that goes into it collected and sorted but it’s a small book-level project that’s on the back burner]

In the meantime, I’ll dribble out some things that really resonated in this column. Today, I’ll point you more closely to the InvestResolve series I referenced in the above quote.

Adam Butler and his team at InvestResolve did a wonderful 12-episode Masterclass on the topic of portfolio construction.

I took notes on the first 8 episodes. I didn’t take notes for episodes 9-12 as they get into the weeds of quant methods, backtesting, and ensembles. I was more interested in a conceptual primer to risk parity as a portfolio construction method for diversifying across unique edges.
The notes include a link to the episode as well as a transcript

💡Most important ideas

A more diverse portfolio has a higher expected risk-adjusted performance over time.

Asset allocation is useful because it maximizes the number of independent bets in the portfolio.

Those bets are independent are sustainable because they’re directly linked to fundamental economic properties.

A risk parity portfolio is the most efficient portfolio if you believe major asset classes are fairly priced (ie their Sharpe or other measures of risk/reward are the same)

🔗InvestResolve Masterclass On Risk Parity (Link)

If you are short on time focus on the first 3:

Money Angle For Masochists

I saw a tweet:

Let’s set aside the obvious “just short bonds” response to a crystal ball that tells you mortgage rates are going to roof. While I’m not sure how volatile the 10-year note/MBS basis is, just shorting bonds would seem like the most direct and reliable trade.

The rest of the crystal ball portfolio underwhelms expectations. Ahh, a recurring parable in the “trading is hard” bible. Like if you knew what a stock’s earnings were going to be would you be able to make money? How do you know what the “whisper” number is or if the market is focused on guidance more than income for this quarter?

It also reminded me of 2 adjacent reads that cut to the heart of “how would you trade if you knew the future but not the path?”

In Financial Hacking, a puzzle is presented:Assuming you could not trade options, how much would you pay to know the closing price of SP500 in one month?

🧩Excerpts from the discussion
Even God Would Get Fired As An Active Investor (AlphaArchitect)

Alexis reminded me of cringe times from my NYC days. Almost as cringe as referring to probabilities as deltas. As in “I’m 75 delta to meet you for drinks after my work dinner” 🤮

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Also, if you were never cringe about anything you have the heart of a dead fish and you should get that checked out.

@yayalexisgay

it’s not “banking” per se but… I mean, it’s all “banking,” really……. right? 🥴 🎥 edited by @Alex Moudgil #finance #comedy #dating

♬ original sound – Alexis Gay

Investing With Your Hands On The Wheel

Newsflash: This letter’s audience has lots of professional and retail investors. There are also lots of aspiring traders or just people who want to supplement their income with “alpha” from the markets.

So I commonly get asked for advice on trading for oneself. “I have a $250k account I’ve studied A to Z…etc”

Many of the backstories are impressive. Y’all impress me. I got a non-rigorous econ degree that only required 8 core classes. And those catered to my strength — bullshitting on blue-lined pamphlets. I limp into a stellar firm that knows how to teach trading and decision-making just as it’s hiring its largest cohort ever. I’m a product of those I was lucky to be surrounded with. If I was good at anything it was assimilation. More practical than heroic ultimately.

So when a smart, bushy-tailed go-getter asks me about prospects for succeeding as a retail trader I’m torn. Trading is a hard way to make a living even when you’re sitting in the F-16 cockpit of a prop firm. Seems like it should be impossible for retail. On the other hand, I’m not built of the best stuff so who the heck am I to piss on the grit-factories that email me.

I got one of those emails on Monday. Sharing my responses(italics) here:

A few thoughts:

1. This thread from Lily is spot on

2. Listen to this interview with Darrin

Reader: What would your advice be to someone who loves markets and trading more than anything and doesn’t look at this as a chore, but rather a passion? Is it still a fool’s errand to not just DCA into QQQ and SPY and go find another interest?

Me: 99% of people should probably look elsewhere but that’s true of anything that is exceptionally hard. There still will always be the 1% who do not take no for an answer. Nobody can tell you who you are. You ultimately seize who you are. If you fall to the level of your weakest strength, you can still decide if that’s your resolve or something else.

Reader: I know about all of the time in the market > timing the market, the Buffet bet, all of it – but maybe I am just irrationally stubborn?

Me: If you listened to the Will England interview you can hear him say that a lot of the neutrality guardrails are in place because nobody trusts anyone’s ability to time. Vol traders can’t even time vol and I’m talking about the best vol traders in the world. If this is what you think the edge is nobody is going to buy it. You will need to prove it with your own $. That said, timing is not really the edge most try to have. This interview might be helpful to expand your thoughts on it.

Reader: I guess I have seen some of my mentors trade very, very well, but maybe I am just not able to allocate as much time and attention via a full life elsewhere. Are there any resources you would recommend to explore further ideas? There are people way, way smarter than me that just say DCA into low cost interest ETFs and go take a walk, but is there anything worth anybody’s time when it comes to more active stuff?

Me: I didn’t up in this biz on my own like say Darrin did. I don’t know how those people do it, I can just listen to their stories. I’m pretty much in the camp of “get a job where you can do this full-time if you really want to”. If you can’t do this but still want to explore strategies, then fence out some capital to play/learn/experiment. For the rest of your assets stick with some kind of permanent portfolio implementation depending on your risk tolerance. You can follow folks like Corey Hoffstein, NomadicSamuel, Jason Buck, Lily for that stuff. InvestResolve guys too. All these tweet about it too and it’s all quite solid. I recommend this series by the InvestResolve team.

In general, my advice, which sounds hard but is probably easier than trying to trade for a living: get a high-paying job.

All this focus on trying to make your money work for you is totally secondary to the biggest muscle movement — make more money with your skills or with a business. I came to the internet around 2015 to learn about investing because I already had a lot of savings, a house etc. So I was like “now what to do with the money”. Most of my option traders friends have no process or framework for investing. In fact, most of them find it to be a waste of time to give it a lot of thought. I don’t fully agree with them on that, but I was like that myself. Instead, we all focused on — “I want to make so much money that it doesn’t matter if I just stuck it in t-bills”. It’s a pretty jarring answer compared to conventional thinking and it’s not fully right — but there’s truth in the instinct. When I look at people who have built more wealth in the past decade from investments than income I think — “that looks fragile”.

Everyone wants to feel like they slayed the investing dragon and were great at making their money work for them. Meanwhile, there’s a bunch of folks out there who want to focus on what they’re good at, have hobbies and be f’n happy on the weekends not researching the next investment or managing rental properties. They out there just thinking — I’m gonna go get paid seven figures a year on a W2 working for an elite organization.

I added this later in a tweet and it’s just straight talk if someone is sweating lots of financial success:

Be special enough to get pedigree

Be special enough to not need pedigree

In other words, this reduces quite easily to things that are very hard. Invoking the “Why would it be otherwise” line.

And as far as being methodical about the original question of trying to earn a return on $250k, John has said it well:

One of my favorite writers,

Venkatesh Rao

just published an incisive climate posture post [paywalled]. It has this amazing passage that can be ported from climate contexts to people’s need to trade (bold is mine):

The narrative web of the climate discourse is very hard to map, but one thing is clear: Almost everybody is an NPC in the current situation, and is primarily desperately solving for how not to feel like an NPC. This is an important point. Humans have a strong tendency to confuse a psychologically satisfying amount of agency with a materially effective amount. A broad culture of what we very-online people call cope rules everything around us when it comes to climate. It is a deep-rooted tendency, and an understandable one. Much as we might intellectually desire such laudable goals as the survival of almost everybody through a planetary crisis, our sense of meaningful existence is tied to individual agency. We’d rather stride grim-faced with a gun across a devastated post-apocalyptic landscape, masters of our own fates, than feel helpless within a world that’s largely doing fine and even providing for us.

What. A. Line:

Humans have a strong tendency to confuse a psychologically satisfying amount of agency with a materially effective amount.

Don’t just stand there, do something, right?

But also…

A trader pinged me saying:

There is a false dichotomy between 100% passive and 100% active. I feel like with the right mindset/education/strategies, there are ways to meaningfully add value to one’s portfolio via lower touch strategies and this can be done in addition to one’s day job.

Like in the guys email, one of his first questions was whether it is a fool‘s errand to not just DCA into SPY. I feel like the investment education landscape is so distorted that DCA SPY is the baseline. I would almost argue it should be quite easy to outperform buy and hold, especially on a risk adjusted basis without having to spend hours of screen time.

Ultimately, questions like this are ones without tidy answers.

This is where I shake out on it for now:

My gut feel is return-stacking/permanent portfolio for long-term DCA is probably the efficient frontier of work/return/risk triple axis.

But there’s no doubt that many people want to put their hands on the wheel and that has innate personal value (and that’s true whether it’s misguided or not). So in short I think it’s a tree:

DCA permanent portfolio variant if you want autopilot
If you want to put your hands on the wheel what does that efficient frontier of effort/return/risk look like where return also includes some illegible component of DIY satisfaction?

This is related in a weird way but one of my favorite interviews was with Professor C. Thi Nguyen, author of Games: Agency As Art. It’s a penetrating twist of how art or creation is a form of agency — games allow players to take on different agency roles. To step outside themselves in a low-stakes way.

The pragmatic view of investing/trading is and should be for profit. But whether partitioning some of that mental and monetary budget to satisfy agency needs might say something about whether you are getting enough of that in other endeavors. Investment as agency?

I’ve been reading Ed Thorp’s autobiography with my 10-year-old (very slowly I might add — between myself and the boys we are simultaneously reading 5 books. Sympathies to Yinh who is surrounded by broken brains). We are about to start the second half of the book where Thorp leaves gambling (after the casinos tried to kill him by jamming his car’s accelerator!) and sets his sights on the world’s greatest casino — Wall Street. But despite being on the Mount Rushmore of investors, Ed left the game content to invest his fortune with other managers, seeing more to life than the day-to-day of this particular game.

An interesting side-note was Ed and Claude Shannon were good friends and accomplices in devising the world’s first wearable computer (which they used to break roulette). Claude was also a wildly successful investor. Both of these men saw investing as an interesting puzzle. Money was a byproduct. They didn’t seem to care too much about money other than its evidence of their hypothesis.

There’s a line in Tomorrow, and Tomorrow, and Tomorrow where celebrated video game designer describes a (less than mentally healthy) scene from his youth:

They were in her car on the way back from a math competition in San Diego, and Sam was giddy with the feeling of being better than everyone else at something that he didn’t care about at all.

I have several option trader friends who are misfits — amongst the smartest traders out there getting paid big bucks at the firms you know. They could care less about investing but find trading fun. This is just a game that pays way too much for what it requires of them. They have all these other nutty interests and would sooner off themselves than read an investing book. Me, I’m just a normie pragmatist. I did it for the money, not because I love the game. In fact, one of these friends has told me he thinks I’m totally f’n weird because I don’t love the trading part, I love the conceptual parts, the building parts — which is the exact opposite of his position.

My ability to pull any useful insight from this is strained. But it’s probably just some cliche — think deeply about what you’re good at and what you want…and the conversation that’s hardest to have with yourself — why do you want it? The answers are always laden with some amount of insecurity, but I think that’s what keeps us alive. And abolishing insecurity probably isn’t a reasonable or even respectable goal. Coming to agreeable terms with it strikes me as more human.

It must be nice to find that thing that’s in-demand that comes really easy to you. I wonder what an emphasis on finding that would look like rather than preaching the grit catechism.

The Pods On Top Of The Food Chain

There are lots of videos online of orca pods feasting on white sharks. What rattles the imagination is how they go straight for the liver. The liver’s bounty is a dense nutrient-rich oil called squalene that can account for up to a third of a shark’s weight.

Hopping over the semantic curiosity that benz and squal just adopt an “ene” to become oil words, I’ll skip straight to ruthless analogy. The pod shops in investing are top of the food chain in asset management. It’s said on the internet, so I know it’s true, that a single shark liver can nourish an orca for a “whole day”. First of all, if that’s supposed to be a jaw-dropping amount of nutrition call me underwhelmed. If a white shark a day keeps the doctor away, I’m left to think Shamu’s cursed appetite has no end — this is an aqua-treadmill of blood without a killswitch.

Which serves the analogy perfectly.

Squalene is alpha. There’s not a ton of it out there and the hunt for it mobilizes the top of the academic food chain. In 2000, I made $50k including signing and year-end bonus my first year out of college. That figure is 8x today for top grads accepting prop shop offers. Talent war.

The trading world’s ruthless focus on squalene — risk-adjusted returns while staying market-neutral to print money in any environment has been adopted by the investing world. And the allocators have noticed. The pods, like the orcas, are eating everyone’s lunch right out of their bellies. And those inflows are arming the war for mature talent too. Giant guarantees to proven managers. The kind of money that can get even the most ambitious manager to re-think starting their own firm.

With that intro, I’ll point you to a podcast:

Patrick O’Shaughnessy interviews Will England (Invest Like The Best)

Will is the CEO/CIO of Walleye’s $5B multi-manager hedge fund. I’m familiar with Walleye because they started in the mid-aughts as an option market maker. Several friends and ex-colleagues have traded for them. But this podcast is about their hedge fund, not the prop biz. It’s the best investing interview I’ve heard this year.

First of all, if you are unfamiliar with the multi-manager or “pod shop” pass-thru hedge fund model then this interview is a great primer. The big 4 managers in the space are Citadel, Balyasny, Millenium and Point 72.

Will’s language, tone, and thinking will be deeply familiar to folks who have done tours of duty at prop trading and option firms. My take on this interview is “damn, that was honest”. Will is in Minnesota but shoots as straight as a Chicago pit trader. Heck, he addressed the alignment issues with the “back book” — I’ve talked to pod traders about this idea before and couldn’t believe he broached the topic in this call). His voice was like a lullaby from my younger years.

Patrick asks the right questions. Everything from the knowledge to the story is worth an hour of your time. It confirmed a lot of what I thought I knew and taught me even more.

A few thoughts of my own

Will says 25% of their business is still options trading but a significant chunk is now fundamental equity. The PMs are trying to earn a 3% spread between longs and shorts after stripping away beta and factor tilts. Just like other pod shops, these guys are farming pure alpha or “idio” (for idiosyncratic) and levering it to get to about a 30% return which the investor hopes to see half of after implicit/explicit fees.

It has always struck me that this is the natural progression of active management. A barbell where you pay up for pure alpha and get your beta for free.

The closet beta active management world is a melting ice cube. But the incentives and stickiness of legacy relationships both from allocators and story-telling managers will try to keep the freezer door closed as long as possible.

But I can’t say I know where the equilibrium will shake out. If you have pure alpha, you can choose your investors either by fees or by preference. You have all the bargaining power. But I’m not sure what the capacity of alpha even is. Will didn’t mince words about the competitiveness. He thinks the number of PMs that possess both the chops and psychological profile to play this game is on the order of a thousand people maybe. The pods are flush with cash and signing talent with big upfront deals like athletes. (He admit the model could be in a period of froth at the moment). Will’s belief in market efficiency sounds like “efficiently efficient”. Yes, there are 10 Sharpe strategies. They are also low-capacity. Any strategy with an obnoxiously high Sharpes is basically arbitrage counting down to extinction. But that new species pop up and then disappear is a general truism. A never-ending game of whack-a-mole.

[Aside: Anyone reading Moontower for a long time knows I don’t wade into the market-efficiency debates because they sound like academic masturbation. I have my own version which rhymes with what Will talks about — The “No Easy Trades” Principle. When I encounter someone who disagrees with this I hear one of these possible confessions:

“I got rich on a highly concentrated risky bet and have never considered what the outcomes would be if I re-ran my life 100x”
“I have no idea what I’m talking about”

I was out with a friend recently who ran a high-volume options trading business for 25 years. We talked about how nearly every time they would “exploit” some weird rev/con financing opportunity they found a way to get f’d by the borrow market. He could rattle off example after example of interesting set-ups and yet the outcomes were consistent. You’re literally paying to discover new failure modes but the way each setup arrives you feel like you can see why the opportunities are real.

Almost every time I did a trade and felt good about it afterward, I was in the pre-glow of a bad beat. The trades that feel scary are the ones that pay. And this makes sense — the price is compensation for doing what nobody wants to do. The job-to-be-done is finding a way to manage the risk until everyone who is transacting to satisfy their greed or pain is filled. The removal of that pressure is what begins to turn the trade in your favor.

Trading profitably is painful. It must be or there is no reason to be paid for it. what’s worse — just because you feel pain, doesn’t mean you will make money. The pain is the cherry on top of doing everything right. You can have pain even if you do things wrong and it will be in vain. The difference is when you do things wrong, you feel good about it in the interim because you don’t get how this works. And that fleeting satisfaction is what keeps you from learning.

I’m sorry but trading profitably means being constantly paranoid and finding a way to live with that. I suspect a subtle aspect of what makes the pods so smart is they have codified and automated the risk management in a way that guarantees the PM’s paranoia.

This is an aside because I think you need a lot of reps to grok what I’m saying and honestly most people will just go on pointing to things that don’t make sense and breathlessly exclaim “See the market is inefficient”. You don’t have a right to say that unless you tweet it from your yacht purchased with lots of receipts.

Strategically, in a game where the skill level is extremely high and evenly matched, then variance will drive a lot of the separation. So the counterintuitive response for someone dead-set on being rich but knows they are overmatched is to take a giant, high-variance bet and hope this was the lifetime it panned out.]

Sorry, back to the body.

In short, I don’t consider what these pods are doing to be investing. They are trading but on a medium time horizon. It’s called “fundamental equity” but let’s say the holding periods are under 2 years and probably more like 1 (if someone knows the stats please share) then this isn’t about “realized” fundamentals. This is about anticipating change in sentiment around expected fundamentals. This feels like a game of nearer-term info, flows, positioning, and game theory. A re-rating game. A game that was much more similar to what I did (although it sounds more complex than vol trading which has more to do with flows and is yet even smaller capacity) than what I imagine value investors do.

My thoughts on value investing are mixed. And I’m being liberal with the word “value”, recognizing that cookie-cutter implementations of “value” are the equivalent of accounting fails (like not updating the meta-principles to handle object-level changes in importance to things like goodwill or brand equity). I assume there are value managers who can spot high-multiple value names because they have a “g” column in their Pandas dataframe (just kidding — I meant in their spreadsheet — we are still talking about value investors here). The problem with these managers and their “long-term” theses is they want you to buy the brand name vitamin instead of the generic and when you ask for the quarterly bloodwork to see if it’s making a difference they say you won’t see the benefits until you retire. The blood results are just “noise” they’ll tell you.

On the other hand, if the manager’s signal reliably swamped the noise then they wouldn’t give that away. They’d try to get pod shop fees. Market efficiency is fractal — there’s a market for the assets and for the labor that moves the assets. I’ve alluded to this before in The Paradox of Provable Alpha and Will’s interview made me think it’s only going to be a more relevant paradox going forward.

Learn more:

🧵BEAT THE PODS: A 7-POINT RECIPE FOR SINGLE MANAGERS (Brett Caughran)

This is a long but good thread by @FundamentEdge

This pairs well with Ted Seides’ interview with Jason Daniel and Porter Collins, 2 of the investors made famous in The Big Short from their work with Steve Eisman:

🎙️Big Shorts and Big Longs (Capital Allocators)

These guys had a stint at Citadel where they learned the intricacies of the pod model. It didn’t resonate with them and for reasons that confirm my own interpretation — pods are more like traders than long-term investors. They had 2 big insights:

The pod model is so prevalent (and it is smart) that if you don’t understand the dynamics they impose on the market, you’re playing with one eye closed. They have respect for the model (and how Citadel implemented it) even if it’s not their game.
They realized the model left some forms of edge behind because of its nature. They could make picking that up part of their own niche. This is touched upon in Caughran’s thread above.

🔗Multi-Manager/Pod/Hedge Fund 101 (7 min read)

Byrne Hobart’s primer from his evergreen Capital Gains Substack

Moontower #197

Just one link before we hop into investing topics.

For his 100th essay in his series “We’re Gonna Get Those Bastards”, Jared Dillian tackles the question:

How do you live a happy life?

Happiness (WGGTB)

It’s short and sweet.

Money Angle

Top of the Food Chain

Which serves the analogy perfectly.

With that intro, I’ll point you to a podcast:

Patrick O’Shaughnessy interviews Will England (Invest Like The Best)

Patrick asks the right questions. Everything from the knowledge to the story is worth an hour of your time. It confirmed a lot of what I thought I knew and taught me even more.

A few thoughts of my own

It has always struck me that this is the natural progression of active management. A barbell where you pay up for pure alpha and get your beta for free.

“I got rich on a highly concentrated risky bet and have never considered what the outcomes would be if I re-ran my life 100x”
“I have no idea what I’m talking about”

Sorry, back to the body.

Learn more:

🧵BEAT THE PODS: A 7-POINT RECIPE FOR SINGLE MANAGERS (Brett Caughran)

This is a long but good thread by @FundamentEdge

This pairs well with Ted Seides’ interview with Jason Daniel and Porter Collins, 2 of the investors made famous in The Big Short from their work with Steve Eisman:

🎙️Big Shorts and Big Longs (Capital Allocators)

The pod model is so prevalent (and it is smart) that if you don’t understand the dynamics they impose on the market, you’re playing with one eye closed. They have respect for the model (and how Citadel implemented it) even if it’s not their game.
They realized the model left some forms of edge behind because of its nature. They could make picking that up part of their own niche. This is touched upon in Caughran’s thread above.

🔗Multi-Manager/Pod/Hedge Fund 101 (7 min read)

Byrne Hobart’s primer from his evergreen Capital Gains Substack

Money Angle For Masochists

I published a big post this week. Big enough that it warranted a map. You will get technical knowledge, some trading bits, and ideas that are worth assimilating into how you think about investing. In fact, you’ll even see opportunities that arise because of the different lenses investors and traders bring to markets.

The map:

Outline of the Risk Neutral Probability Lessons (Moontower)

And if you want to jump right in:

Understanding Risk-Neutral Probability (Moontower)

The post was the culmination of connecting lots of dots. I started thinking about it after watching a short YouTube clip on my flight to Vietnam back in March. I hope you enjoy it. I’m biased but think the points are underappreciated (or at least that’s how I justify the 30-40 hours I put into it).

A nice affirmation

I hadn’t looked at my website analytics in a while (it’s a bit more annoying to do so since a lot of the posts I wrote this year are these longer technical ones that I host on Notion).

When I logged in for a gander I found that several trading and brokerage firms are linking my material through their internal wikis or intranets. When I write these posts, I often see them as a useful aide for a senior trader who doesn’t feel like explaining some concept to a trainee. “Ahh, there’s some stoner blog called Moontower that wrote about this, just search for it on there”.

Anyway, it’s a nice affirmation. I probably won’t be thrilled when the LLMs are quoting me but ya know, it’s America — corporations are people, computers are people. Maybe only people aren’t people.

Outline of the Risk-Neutral Probability lessons

I published a new lesson. It’s a big post with 5 embdedded sub-posts and exercises for the reader. It ties together many concepts I write about.

I adapted the Tweet thread I used to promote it into this post to provide an outline for prospective reads.

Understanding Risk-Neutral Probability (Moontower)

To let you build your own understanding, the lesson begins with a progression of simple questions.

From this simple progression, you have actually self-derived a foundation for a key concept that we are going to get some mileage out of. Plus more practice to help you internalize the concept. It will make sense!

For those learning about derivatives or even pros who aren’t academically minded (myself included) there are exploration detours into 2 topics.

Useful Detours

1. Advanced Topic: How To Compute Risk-Neutral Probabilities From A Binomial Tree (Moontower)

That section includes exercises, again so you can own the knowledge, and then a derivation that you will probably have figured out intuitively:

Advanced Topic: Replication — Real World vs Risk-Neutral Worlds (Moontower)

This one will be especially fun for traders because it includes:

💡 What seasoned option traders get wrong

💡 How divergence between real and risk neutral probability lead to mutual opportunity for speculators & traders

I give examples from:
1. Warren Buffet
2. 2. FX Carry

Returning to the main post

After the detours, we pick up again with the idea of risk-neutrality and make a logical step into the principle of that underpins how investments will be priced:

🧽risk absorbability

This is an underappreciated idea. I can tell because people confess their ignorance all the time when talking about their great investments. They don’t understand that the default assumption should be idiosyncratic risks don’t pay.

Why not?

Consider 2 significant ways that an investing entity can absorb risk and we use simple examples to demonstrate how risky propositions can be rationally priced with no risk premium:

1. Bet Sizing

2. Diversification

Let’s look at each:

Risk absorption by bet sizing

Risk absorption by diversification:

The key takeaway: The more risk you can absorb, the closer your bid approaches the risk-neutral (ie arbitrage-free) price.

Bring it altogether

Now we get to tie all of this together to reason about investing broadly. There’s a short recap before we get to heavier lifting.

Now we’re ready for the real discussion which starts with an an obvious question:

🏗️Why did we slowly build all this theoretical scaffolding?

2 reasons that I categorize as:

1. Instrumental

2. Appreciative

These are essays in themselves.

🔗Instrumental Reasons (aka the practical reasons to learn this stuff)

We divide the audience for this into

a) Traders

b) Investors

I also give an example of the line being blurry between them:

Then we really address the implications for investors which applies to many more people.

We do this in Socratic form.

⚕️Then I offer some prescriptions

That covers instrumental reasons but I am an advocate of financial masturbation. So we also look at the appreciative reasons to understand this stuff.

Like I mentioned, this is an essay unto itself:

🔗Appreciative Reasons

This is the outline:

Followed by some cope:

Then closing comments and links for further reading. This post tied together a lot of material.

🔗Links For Further Reading

David McRaney on EconTalk

Episode description:

Link: https://www.econtalk.org/david-mcraney-on-how-minds-change/

I think the best teaser for the interview occurred during the interview when McRaney says:

The incepting point of this book was someone in a lecture came up to me and asked about their father who had slipped into a conspiracy theory and they said, ‘What can I do about that?’

And, I told them, ‘Nothing.’ They said, ‘How do I change his mind?’ I said, ‘You can’t.’ And, I really felt, the second I said it, that: I don’t know enough about this to say something like that. I don’t even know if I believe what I just said, but I know one thing I don’t like this attitude I have about this issue. I should at least learn more about it.

And, if I was in that same situation today, I would actually be able to say, ‘Oh, here’s what you should do. Here’s what you should say.’ I no longer believe anyone is unreachable. I no longer believe anyone is unpersuadable.

In conversations that don’t work out the way we think, we blame the other side. We say, ‘They’re dumb. They’re mean. They’re evil. They’re ignorant. They are unreachable, unchangeable, stuck in their ways.’ These are all things that we are using to forgive ourselves for failing.

My selected excerpts:

Motivated reasoning for social acceptance

Reasoning, psychologically speaking is just coming up with reasons for what you think, feel, and believe. And, those reasons are motivated by a desire to–a drive–to be considered trustworthy to your peers.

So, not only are you driven to come up with reasons for what you think you’re going to believe, you want them to be plausible. And, plausible, in this sense is: ‘What would your most trusted peers, your social network think?’ ‘Oh, yeah. That’s a reasonable way to see that.’

[Kris: For example, a quant might not respect reasoning that comes from intuition which they might see as excessively prone to bias whereas someone with a lot of experience might night trust the numbers for some unconscious pattern-matching reasons. The irony is both people recognize the intuitive approach is just pattern-matching but the quant thinks this is untrustworthy and the discretionary trader thinks it is.

I’d add another observation — the criteria for sense-making might be entirely context-dependent. Maybe the quant gets acupuncture when they go home. Our standards for epistemology vary depending on our expertise. The religious doctor doesn’t just pray for their patient.]

The process of radicalization

You feel something happens in the world that gives you this a negative emotion. Some anxiety starts to come up. It could be for really good reasons, but it could also be because you have some sort of prejudice or some sort of political bias.

So, then you do that thing. You go, ‘Hmm. Let me search for evidence that justifies the anxiety that I’m feeling.’

And, when you do that, online, you absolutely will find something that suggests your anxiety was justified.

And, you also might find people talking about that. And, you might end up wanting to talk with them about that. You might end up spending a lot of time talking with them.

And slowly you can radicalize yourself. You can cultivate yourself–cultivize yourself–and by, you start snipping your connections away from people who don’t share the attitudes being expressed in that community and you start strengthening the connections you do have with those.

And, now all of a sudden, you’re in a group. You’re in a community. And, the great sociologist Brooke Harrington told me that, if there was an E=mc² [energy equals mass times the square of the speed of light, Einstein’s Equation] of Social Science, it would be: the fear of social death is greater than the fear of physical death. And, if your reputation is on the line, if the ship is going down, you’ll put your reputation in the lifeboat and you’ll let your body go to the bottom of the ocean.

We saw that with a lot of reactions to COVID [coronavirus disease]. As soon as the issue became politicized, as soon as it became a signal–a badge of loyalty or a mark of shame to wear a mask or to get vaccinated–as soon as it became an issue of ‘Will my trusted peers think poorly if I do this thing or think this thing or express this feeling or attitude or belief,’ people were willing to go to their deathbed over something that was previously just neutral.

Reactance

[Kris: calling all reflexive contrarians!]

This is a concept that has been studied extensively in the context of clinical therapy.

They would come to the therapist and the therapist would say, ‘Well, you know what’s your real problem is. You should be doing this.’ Or, ‘I don’t know if you’ve noticed, but you don’t do this very much. You should do this.’..All that feels pretty good. They now call that in psychology the “writing reflex”. And, we’ve all felt that whereas someone is saying something and you’re like, ‘Oh, I have the advice for them. I know what to tell that person.’

But, you also have also experienced this other thing that happens, and this seems to be something that’s universal to human beings across all cultures. It’s just something that the brain that we’re issued at birth, it’s something that’s a feature of human thinking, rationality, psychology. Human brains do this. It’s called reactance. In the psychological parlance, they’ll say something along the lines of, you feel motivationally aroused to remove the influence of the attitude object, which just means: ‘You made me feel a feeling I don’t like and I want it to go away. So, I’m going to push you away,’ or ‘I’m going to disengage.’

What is the feeling that’s causing the motivational arousal? It’s the sense that your agency is under threat–your autonomy is under threat. It’s the ‘Unhand me, you fools,’ feeling. You’ve all felt this. If you’ve ever been a teenager or you’ve ever spoken to a teenager, you know what I’m talking about…”You shouldn’t do this. You should study more.”‘ This is good advice that the person when they’re 35 will go, ‘Man, my parents were right about that.’

But, in that moment it’s just the fact that you’re saying, ‘I have a thing in my head that should be in your head and I want it to be in your head.’

And, oddly enough, it’s the want that creates the reactance. The person’s feeling that you have approached them in some way and said, ‘I want you to think, feel, or believe, or act in a certain way that you’re not doing right now,’ and it feels coercive. It feels like they’d come at you and they’re threatening you. They’ve got a knife in their hand, and they’re saying, ‘Walk this way.’ That’s what it feels like.

We just, at a visceral level, will react by saying ‘no thanks’ to that, and we’ll push against it.

Basically, what you’re saying is ‘I have a goal and I’m not even concerned with what your goal is. This is the goal that I want you to go toward.’ Then they say, ‘Oh yeah, well, no. How about I don’t do that? I want you to stop talking to me that way.’ Well, now you feel reactance, because you’re like, ‘Oh, you’re telling me how to talk to you? How about I double down?’

And, then you enter into a horrible feedback loop.

This happened so often in therapeutic frameworks that they’re like, ‘We should really develop a way to stop doing that.’ Because what started happening was people would come in wanting to extinguish a behavior and then they would leave therapy more likely to engage in the behavior than if they had never seen a therapist because something along the lines of: they had these arguments for and arguments against. So, they were at a state of ambivalence when they arrived, but they wanted a little bit more in energy on the side of ‘Let’s not do the thing anymore.’ But, because of that, they counter-argued with the therapist. They generated counter-arguments inside of them that put more weight on the side of continuing to do the thing. So, they walked away with more arguments for than against than when they walked in.

This is also what happens when we have a conversation with someone where we disagree on an issue. Very often, if we create that feedback loop, they will walk away with more arguments in their mind than they had coming in to continue believing or feeling in the way they had before we had the conversation.

What I want to emphasize here is you can be very much correct. The facts can be on your side. You can be really trying to reduce actual harm in this world. You can have the moral high ground, and you can be dealing with a person whose intent, they’re, like, their action and behavior, their political stance harms you. They may even hate you.

So, what I’m saying is you can be on the right side of all of this, however you want to define the word right–you can be on the correct side of all those things. And yet, if you generate reactance from the other person to what we’re talking about, you will not be able to change their mind. You lose out.

And, it’s a very difficult thing to offer a person the space and give them the respect that would avoid reactance when you are dealing with a person that you feel like doesn’t deserve that treatment from you.

Shaming will cause the same defenses to kick in

If you say something that is interpreted–you may not mean to come across this way, but if it can be interpreted as, ‘You should be ashamed for what you believe. You should be ashamed for what you feel. You should be ashamed for that value or that intent to behave,’ even if I’m putting my hand at the side of my mouth. Even if they should be ashamed. If you communicate it that way, then you’re going to activate the person’s fear of ostracism. And there’s nothing more–like we said, there’s nothing more fearful for a social crime made than the suggestion that they may be ostracized. So, if you tell them they ought to be ashamed for feeling that way, it’s going to cause them to feel very viscerally upset and angry, and they’re going to push away from the conversation.

Unblocking the discussion

All you have to do is get out of the debate frame with the other person. Don’t make this feel like, ‘I need to win and you need to lose. I am and you are wrong.’ Just get out of that frame.

And, the easiest way to get out of that frame is to, first of all, say something along the lines of–instead of saying, ‘I want to show you what you ought to think, feel, and believe,’ you say, ‘Hmmm. You seem to know a lot about this issue and you seem to care about it a lot. You seem to see that these problems are problems. I’m wondering, given what you know, I wonder how it is that–because I look at a lot of this stuff, too. I wonder why we disagree on this issue? It’s really curious to me. I would love to talk to you a little bit more about that. I wonder if we could look at this issue and see what is it we disagree on here?’

What you want to do in that frame is give the other person a chance to feel like, instead of being face to face, you’re going to go shoulder to shoulder, and we’re going to–instead of looking at each other as obstacles, we’re going to turn and face in the same direction and look at the problem at hand, the goal at hand, the issue at hand. And, we’re going to collaborate now. We’re going to work together and say: Well, you’ve got your side of things, and your views, and your experiences, I’ve got mine. I bet if we joined forces, we could get to an even deeper truth on this or higher truth or a solution that works well for both of us.

You don’t even have to put it in those words. That’s another thing we have an innate inclination for which is, ‘Oh wow, we get to snap together and work together on a problem.’ You can frame things that way with just a slight change in approach and language and you will escape the debate frame that leads to reactance; and it’s much more fruitful.

Specific approaches that work

The thing that was most surprising in all that was discovering that there were all these different organizations that had said, ‘Okay. Well, what do we do about this?’ And, they started A/B testing conversation techniques. I found deep canvasing, and street epistemology, and smart politics, and then all the therapeutic models that I mentioned–motivational interviewing and cognitive behavioral therapy. And, on and on and on. There’s so many.

And, the thing that was most surprising was: Most of them had never heard of each other, never seen each other’s work. Many of them, the majority of them weren’t aware of the–if they weren’t in therapeutic domains–they weren’t aware of the science that would support what they were up to. Yet, independently, they all came up with pretty much the exact same technique. And, if you put it in a step-by-step order, it’s almost in the exact same order every time, too.

That seems to me like something almost in the world of physics or chemistry, and that if you were to build an airplane–the first person to build an airplane, it was always going to look like an airplane. It doesn’t matter where they built it. It doesn’t matter what culture they were from. It doesn’t matter how old they were, what they looked like, what they knew about anything. Airplanes have to look like airplanes because physics works like physics on the planet Earth.

Conversational techniques that actually shift attitudes and open people up to different perspectives, that get past resistance, all pretty much work the same way because brains resist for universal reasons and brains work in a very particular way.

Diving into street epistemology

Origin

Street epistemology came out of the world of the angry atheists and the militant agnostics who were having their own reaction to getting online and meeting each other. And, they’ve gone through several phases of growth and evolution themselves where they have schismed off. And, there’s some who are still very angry and there are some who are much more humanistic and empathetic.

And, within all of that, there was this movement that came about where they wanted to know, like, ‘How do we talk to people in a way that could avoid the angry pushback that we so often get when we speak with people who are not in our subculture or do not see or have our same theistic or atheistic views?’

And, they did the same thing that people did in deep canvasing. They went out. They had conversations with people. They recorded those conversations. They shared them with other people in the group. And, when something seemed to work well or get them closer to having a good conversation, they kept it. Anything that made it go the other way, they threw it away. And, through thousands of A/B-tested conversations, they started to zero in on something that worked.

And, now they’ve expanded it to: this can be applied to anything. You don’t have to be in their sub-community or have their theistic views to use it.

In the book, I talk about how there are techniques that work well on politics, techniques that work well on attitudes and values. And, then this one specifically works best with fact-based claims, things like, ‘Is the earth flat?’

How it works

It’s a stepwise method for having the conversation that we all should be having on any issue. Without going through an hour of trying to go through all the steps, I’ll give you sort of the quick version of that, which is: You open with a lot of the stuff we’ve talked about before–you open by establishing rapport. That’s that assuring the other person you’re not out to shame them. Assuring the other person, you’re not even there to change their mind. What you are there is to explore their reasoning. You ask them, ‘I would love to have a conversation with you in which we explore your reasoning on a topic and see what your views are and understand it better.’ Maybe: ‘You might shift, but you will have a deeper understanding of what we’re talking about.’ However, you want to frame it. Use your own language. You’re telling a person you’re going listen. And, most people will take you up on that offer.

I’m doing it right now. You asked if I would talk about something; you said you would listen; and I’m doing that right now. The podcast world depends on the fact that we’re all very willing to tell people what we think and feel about things.

So, give people that opportunity. You open the space for it. In this method, you ask for a claim. You ask for a very specific claim. It could be: Is the earth round or flat? And, then the person tells you–and then you repeat back the claim in the other person’s words. You make sure that you’re always using the other person’s words, because the big lesson in all of these techniques is that you are in their head, not yours.

You stay on their side. And, your job is to hold space for the other person to non-judgmentally listen and give them a chance to have a safety net, to metacognate and introspect.

And so you repeat the claim back to them. If they have definitions for terms, you ask for them; and you use their definitions, not yours. Like, if they say ‘the government,’ don’t assume that they’re talking about something from a civics textbook the way you look at it. They might be thinking of a group of reptiles in a round room talking about how they’re going to divide the country up to play golf. They have a different view of it. Let them–use their definitions.

And, then this is the big moment–and this is true across all of the conversation techniques. They all open in a pretty similar way with this space-creating moment. And, then they move to this thing that is magic.

It is asking the other person on a scale from zero to 10, or one to 100. The scale is a great way to get out of the debate frame and to assure the other person that this is not going to be a binary, right/wrong, black-and-white view of things. And, it even will work with the movie example you gave earlier, which is like, ‘Hey, Top Gun Maverick, what did you think of it?’ A person will say, ‘I loved it.’ That’s a very, like, black, white binary abstract. ‘Oh yeah? What would you give it on a scale from zero to 10?’

There is a moment when you ask a person a question like that, where they’ll go, ‘Oh, well,–that moment is, when they pop into that metacognating frame; and it could be like, ‘What did you think of this talk?’ ‘Loved it.’ ‘What would you give it on a scale of one to 10?’ ‘Oh, well–.’ That moment is what you’re looking for on any conversation topic.

[Kris: this is similar to asking someone to bet on their claim or handicap an outcome — the thinking switches from emotional to deliberate]

And you ask them, ‘What would you put it on a scale from one to 10, or zero to 10, or one to 100?’ Whatever they tell you, ask, ‘Why does that number feel right to you?’

This will encourage the other person to engage in reasoning–motivated reasoning most often. And, you let them do it. Let them do it the way they could do it. They’re going to come up with reasons that seem plausible for that position. But, what’s likely is that they’ve never done this. Not in this sort of like, ‘Please, present your reasoning to me’ kind of way.

It’s marvelous to witness a person saying–well, if they’re talking about Top Gun Maverick, they’ll have to start thinking, ‘Why do I have this emotion? Why was that so quick–why was it just like–it popped right in my head. What caused that to happen?’ And, they start coming up with reasons why that could be. Most of these are exploratory and they’re definitely going to be justifications and rationalizations.

Then, if you are actively hoping to get the person to see things closer to your perspective, if you’ve already done this for yourself and you know where you’re at on the number scale, ask the person how come they’re not in the other direction that you–appropriate to the issue. So, if I feel like–if a person says–if I say, ‘Is the earth flat?’ And, they say, ‘Absolutely.’ And, I say, ‘How certain are you of that from a scale from zero to 10?’ They say, ‘I’m probably a seven.’

Well, what you would ask is–first, you’d ask, ‘Why a seven?’ The next thing you’d ask–and this comes from motivational interviewing–is, ‘How come you didn’t say eight? How come you didn’t say nine?’ Because you’re asking how come they didn’t go all the way to 100% confidence. And, they must, on their own at that moment, generate their own counter-arguments against their position. But, you didn’t do that. No reactance. You’re not telling them what to think, feel. You’re not giving them your counter-arguments. It’s not your reasoning. They have to generate reasoning that counter-argues their position that will be new, that will be fresh, and that’ll be added to the collection of counterarguments in their mind. And, it will affect how they see things going forward.

With street epistemology, it’s more about just getting the person to examine: are they using a good epistemology to vet what they think and feel? So, after you have done all of these things with the number scales, you’d ask them what method that they used to judge the quality of those reasons that they presented. And, then you just stay in that space for the rest of the conversation as long as they’re willing to do it, and continue to listen and summarize and repeat and wish them well. And, try to make it so that you can have more than one conversation.

People do experience 180s in these moments sometimes. But, usually what happens is it’s by degrees, by increments. And, at the end of the day, the street epistemology people, they’ll tell you, ‘We’re not interested in changing people’s minds. We want people to just be critical thinkers. We want them to have more robust epistemologies.’ Which is sort of an even deeper way of changing a person’s mind. Getting a person to change their epistemological approach to the world is even more powerful than getting them to change just one belief, or attitude, or value.

Cognitive Empathy

This is a huge complex idea, but I think it all kind of plays into what we’ve been talking about previously, which is that sense of naive realism, where you just think that: ‘All people have to do is see the things that I’ve seen and they’ll naturally agree with the things that I think,’ if you don’t believe.

And it just takes–what it shows is a complete lack of cognitive empathy that other people come from completely different priors and experiences and social influences that affect the way they see–the way they form their beliefs–but also the way they interpret evidence.

An example of empathy failure:

I’ve seen this recently with a lot of these political ads that I’m seeing come across social media for places that I don’t live where they keep making these–I saw one today where someone was, like–they were in, like, the Midwest and they had these two people trying to survive in the desert. And, one of them is doing everything right because they’re a cowboy and they understand how to survive in the wilderness. And, the other one is a Senator who has no idea how to survive in the wilderness. But, the cowboy dies on Day 2 from a heart attack, because he doesn’t have good healthcare; and the Senator lives, because he’s got great healthcare, the Senator.

And the whole idea of the ad is: See. Senators have the healthcare that you don’t get to have. And, even though you’re a good, rugged individual who lives out there in the wilderness, who can survive in the wilderness, they’ll out-survive you because they’re taking away the healthcare you need.

That seems like a great political ad because it focuses on the identity of the individual that you’re approaching. But, that is an awful political ad based off of everything that I’ve learned in this domain, because it only feels like a great political ad to people on the Left–to liberals. It feels like a great ad for people who already have the values to which that makes you angry about that. It’s the inability to see that you can’t make an argument from your moral framework to a person who is in a different moral framework and expect it to land. You have to actually couch the argument in that person’s moral framework and their values. [ie “Moral Reframing”]

Select Quotes From Tomorrow and Tomorrow and Tomorrow

On Work

She could tell you exactly what was wrong with any game, but she didn’t necessarily know how to make a great game herself. There is a time for any fledgling artist where one’s taste exceeds one’s abilities. The only way to get through this period is to make things anyway
“You go back to work. You take advantage of the quiet time that a failure allows you. You remind yourself that no one is paying any attention to you and it’s a perfect time for you to sit down in front of your computer and make another game. You try again. You fail better.”
If you’re always aiming for perfection, you won’t make anything at all.
“You know what I keep thinking? I keep thinking how easy it was to make that first Ichigo. We were like machines then—this, this, this, this. It’s so easy to make a hit when you’re young and you don’t know anything.”“I think that, too,” Sadie said. “The knowledge and experience we have—it isn’t necessarily that helpful, in a way.”
That night, Sadie tried to remember herself back in 1996. There were three things that had driven her, and none of them reflected a particular generosity of spirit on Sadie’s part: (1) wanting to distinguish herself enough professionally so that everyone at MIT would know that Sadie Green had not been admitted to the college on a girl curve, (2) wanting Dov to know that he shouldn’t have dumped her, and (3) wanting Sam to know that he was lucky to be working with her, that she was the great programmer in their team, that she was the one with the big ideas. But how to explain this to Destiny? How to explain to Destiny that the thing that made her work leap forward in 1996 was that she had been a dervish of selfishness, resentment, and insecurity? Sadie had willed herself to be great: art doesn’t typically get made by happy people.
“There must be more to life than working and swimming and playing Go.”“The boredom you speak of,” Alabaster said. “It is what most of us call happiness.”“I suppose.” Alabaster sighed. “This is the game, Emily.”“What game?” Alabaster rolled their lilac eyes. “You are happy, and you are bored. You need to find a new pastime.”

Viewing Everything Through Your Snowflake Lens

“It’s so funny you should say this, because if you were one of my students, you’d be wearing your pain like a badge of honor. This generation doesn’t hide anything from anyone. My class talks a lot about their traumas. And how their traumas inform their games. They, honest to God, think their traumas are the most interesting thing about them. I sound like I’m making fun, and I am a little, but I don’t mean to be. They’re so different from us, really. Their standards are higher; they call bullshit on so much of the sexism and racism that I, at least, just lived with. But that’s also made them kind of, well, humorless.

“If their traumas are the most interesting things about them, how do they get over any of it?” Sam asked. “I don’t think they do. Or maybe they don’t have to, I don’t know.”

On Phases of Life

Dov laughed. “I forget how young you are. You’re still at the age where you mistake your friends and your colleagues for family.”“Yes, Dov,” she said, trying to hide her irritation. “When you have children, you’ll never be able to worry about a friend as much again,” Dov said.
the middle-aged—”“Those cursed souls worn down by the inevitable compromises of life, you mean?”
A good game designer knows that clinging to a few early ideas about a project can cut off the potential for the work. Sadie did not feel that Naomi was altogether a person yet, which was another thing that one could not admit. So many of the mothers she knew said that their children were exactly themselves from the moment they appeared in the world. But Sadie disagreed. What person was a person without language? Tastes? Preferences? Experiences? And on the other side of childhood, what grown-up wanted to believe that they had emerged from their parents fully formed? Sadie knew that she herself had not become a person until recently. It was unreasonable to expect a child to emerge whole cloth. Naomi was a pencil sketch of a person who, at some point, would be a fully 3D character.
The fact that Dong Hyun had not died a video game death meant that Sam had been able to spend time with him before the end. The length of time it had taken Dong Hyun to die also meant he had said everything he wanted to say to Sam, his cousins, and his grandmother. Was this trade worth his suffering? Sam didn’t know.

On The Idea of Cultural Appropriation

[Sam half-Jewish, half Korean responding to a reporter]

The alternative to appropriation is a world where white European people make art about white European people, with only white European references in it. Swap African or Asian or Latin or whatever culture you want for European. A world where everyone is blind and deaf to any culture or experience that is not their own. I hate that world, don’t you? I’m terrified of that world, and I don’t want to live in that world, and as a mixed-race person, I literally don’t exist in it. My dad, who I barely knew, was Jewish. My mom was an American-born Korean. I was raised by Korean immigrant grandparents in Koreatown, Los Angeles. And as any mixed-race person will tell you—to be half of two things is to be whole of nothing. And, by the way, I don’t own or have a particularly rich understanding of the references of Jewishness or Koreanness because I happen to be those things. But if Ichigo had been fucking Korean, it wouldn’t be a problem for you, I guess?

Assorted

The people who give you charity are never your friends. It is not possible to receive charity from a friend.
Sam normally took comfort in numbers, but he was disturbed by how paltry this particular number was, considering the presence Marx had maintained in his life. He performed the calculation twice to confirm. Yes, it was 4,873. This was the kind of baby math Sam did when he couldn’t sleep. Four thousand eight hundred seventy-three, Sam thought, the dollars in a seventeen-year-old’s bank account when he’s flush, twice the number of passengers on the Titanic, the population of a town where everyone knows each other, the inflation-adjusted cost of a laptop in 1990, the weight of a teenage elephant, six months or so more than the number of days I knew my mother.
They were in her car on the way back from a math competition in San Diego, and Sam was giddy with the feeling of being better than everyone else at something that he didn’t care about at all.
Sam knew “cunt” to be a Rubicon. He had once overheard his mother’s boyfriend call her this word during an argument, and Anna had transformed from a woman into an obelisk. After that night, he had never seen this boyfriend again, and so he knew those four letters possessed profound, magical properties. “Cunt” could make a person disappear from your life forever
she apologizes, but the apology lacks the conviction of the attack

Favorites

“And what is love, in the end?” Alabaster said. “Except the irrational desire to put evolutionary competitiveness aside in order to ease someone else’s journey through life?”
Since she’d started teaching and become a mother, she’d felt old, but that night, she realized she wasn’t old at all. You couldn’t be old and still be wrong about as many things as she’d been wrong about, and it was a kind of immaturity to call yourself old before you were.

🔗Full Kindle Highlights (Link)

Lessons from Game Designer Raph Koster

I am going to be reading game designer Raph Koster’s book Theory of Fun pretty soon. For a preview, I listened to an old interview on the Think Like A Game Designer podcast with Justin Gary.

Link: https://www.thinklikeagamedesigner.com/podcast/2018/10/25/think-like-a-game-designer-5-raph-koster

Raph’s 25-year-old blog is a monument to design knowledge — it includes his writing, talks, and links to projects.

Raph is a creative force of nature. And this interview gets behind the madness. As always with my recaps, this is just what I wanted to write down for my own future reference but so much more is covered (there’s an especially great section about the use of simulations)

Ideating from scratch

When designing a game Raph will have a starting point. On one end of the spectrum might be a particular loop or mechanic the game hinges on. At the other end of the spectrum, he might start with the type of experience he’s looking to design. His approach to tabletop games tends to start with the mechanics and for video games from the experience. I excerpted the following because he decomposes the act of swimming into game mechanics off the top of his head in the interview. It was a neat example of how native this thinking clearly has become for him:

In my board game work, I find myself biased towards the mechanical. It’s unusual for me to start from the other end of the board games. But in video games, I often start from the experiential end. My goal is to establish what I know at one end and then use it to jump to the other end to draw conclusions. For example, if I start from the experiential end and I want to make a game about swimming, I think about the experience of swimming for me. There are different strokes. There’s the fear of drowning when you start to learn. Rhythm is crucial to swimming, as is breath management. The concept of a breath might be a resource. It could be something consumed periodically, but there might also be an exhaustion meter that decreases over time, limiting your breath. Different strokes might have different breath expenditures. If I decide to create a tabletop game, I think mechanically. I could set up a board with a race structure appropriate for swimming, perhaps with themes like sharks chasing or diving challenges. I’d play a game of resource management to get the necessary strokes, maybe using cards or tokens. If I were designing a digital game, I’d focus on rhythm, possibly incorporating a timing aspect and still manage resources of breadth and endurance. Different strokes would offer varied trade-offs. My aim is to establish two foundational ideas and move inward, paying attention to both. Ideally, they meet in the middle. If I have an abstract idea, like a deck of cards that “moves” me, I might not end up with a swimming game. It could fit another context but remain mathematically sound. It could be rules for moving cavalry in a supply chain. It’s crucial to consider both ends because it helps generate ideas that lead to a cohesive design.

Having a wide array of influences and skills

I’m always fascinated by and strive to understand the universal principles that apply to the creative process. It doesn’t matter whether you’re making games, poetry, art, or a movie, I believe there are common threads in how you approach creative work. You have such a polymath background, maybe you can speak to that.

My education and background is eclectic, with a consistent focus on the arts. I took studio art classes beyond the college level and I’m a musician. I play multiple instruments and studied music theory and composition in college. Interestingly, the one thing I do but never formally studied is programming. I have a Master of Fine Arts in Creative Writing and draw on all of these disciplines regularly. It’s challenging for me to imagine not being a jack of all trades or how I’d approach games if I weren’t integrating all these skills. I also frequently use Excel. A primary reason I enjoy game design is because it allows me to utilize various skills in one project.

Getting better — what does it mean to practice?

What’s the equivalent of “practicing scales” for other creative work?

I consider the practice of all those things I do as being very similar. I use the same habits for all of them. I made a list of them once in a blog post, which I think was called “practicing the creativity habit“. First was, whatever the activity is, do it regularly and make it a habit. So part of that is having the tools near you at all times. In the room I work out of, there are about 20 musical instruments within five feet, a complete art studio, a recording studio, and a game design reference shelf. Not actual games, but books about games, economics, interface design, and other topics related to games. For board games, I have a prototype kit with hundreds of dice, wooden bits of different shapes, and about 30 or 40 different decks of cards. The first thing is to make it a habit. Second, have the tools close at hand always.Third, give yourself constraints. I try to do that regularly. If it’s guitar, I might find five jazz chords and learn them, then write a song using those chords until I understand them. I picked up this habit from studying art and poetry. There are traditional poetic forms like sonnets, Villanelles, and haikus. In a writing workshop, we set ourselves the challenge of writing a poem using every single traditional form. In game design, it would be trying different game types. I haven’t succeeded at it for games, but that’s not the point. It’s about understanding design patterns. This approach applies to everything I work with, be it music composition, writing, or drawing. It’s a common underlying principle. It’s like working out — you need to rotate through the different muscle groups.

Intuition is pattern-matching against experience subconsciously

This is illustrated by an example from one of the cognitive science books on my shelf: the firefighter intuitively knows a structure is going to collapse. If you ask them why, they often have trouble explaining. I believe the process of conducting formal analysis of numerous games or seeking NP hard problem categories or compiling a pattern library and trying to internalize it helps strengthen our intuition. The exercise of building games around patterns serves as practice for honing this intuition. I may not always explain why I opt out of a conflict early, but I just intuitively sense it won’t work. The key is recognizing this earlier. I still believe 90% of ideas are shit but now, I discard them even before jotting them down, often when they’re just scribbles.

Nuance about the role of games in education

The changes over the years have involved the “chocolate covered broccoli” concept, where something fun is wrapped around an academic task. It’s clear this approach wasn’t effective. We’ve come to understand that games teach in specific ways that are well-suited for certain subjects but not for others. Games motivate players best through intrinsic motivation. Players choose to learn and take on tasks because they want to, with the game guiding their objective. For instance, instead of making a game to directly teach math, you create a game where players have a goal they wish to achieve. This might lead them to discover that understanding a certain type of math is the solution. They then learn it out of their own motivation. This is a realization that educational game design has recognized over time. As for games with broader themes, they can reflect social structures, human interactions, economics, politics, and other vast topics. While there’s an abundance of narrative-driven or viewpoint-based games out there, game systems can be informative as well. For instance, Sim City faced criticism for presenting an overly optimistic view of public transit and its associated challenges.

You can bias your game systems to convey specific lessons. It’s important to recognize that your game systems inherently teach lessons, intended or not.

Game-playing trains your “systems thinking”

Finding real world systems and abstracting them or boiling them down to their essence isn’t actually a very common skill. Games can teach people how to do this. The idea involves setting constraints, modeling real systems, and allowing people to experience them within a game context to understand them deeply. It provides an opportunity for individuals to experiment with these systems, unlike in real life where, for example, you only get one shot at lifetime earnings. Playing a game that emulates this system offers lessons. This is applicable to various scenarios, such as political engagement. There should be games that allow players to experiment with political engagement methods, helping them discern more effective strategies. This principle holds true in many areas.

Kris here…yea, I’ve made this point repeatedly over the years.

In Let Your Kids Play Boardgames I said this of the game Quacks of Quedlinburg:

Quacks is a bit like a deck builder. It’s known as a bag builder but with a don’t-bust-press-your-luck mechanic. To most of you, that means nothing but for the remaining, you should know this an outstanding game. It’s fun, and while seasoned gamers won’t like this necessarily, it has enough luck to allow a first grader to compete with an adult. I found myself thinking quite a bit about the value of the “options” (they’re actually chips representing ingredients in a potion recipe) in the game and their respective costs. The concepts of theta, volatility, and vega would be visible to someone with a finance background if they looked past the game skin. An engineer would see this game as a very pure simulation (most likely AI) based problem especially since the game has no trading interactions.

In Practice Second Gear Thinking I write:

We must identify second-order effects. In the options world, the “greeks” are sensitivities. Delta is the option’s sensitivity to the underlying. Gamma is a second-order sensitivity that describes how an option’s delta changes with respect to the underlying.

But this topic is everywhere. If a company sells more widgets it makes more profit. But second-order effects mean attracting more competition or saturating a market. Every satisfied customer is one less customer that needs satisfying. So if I build a model of profitability based on units sold, when does the function inflect? When does opportunity fade into unsold inventory?

A fun way to think about second-order sensitivities is playing “engine builder” boardgames like Dominion or Wingspan where synergies between your cards lower the marginal costs of later actions². In essence, the cards have gamma based on how you stack them. Every time I use a card it might increase my odds of winning by X. That’s the delta or “benefit per use”. But the delta itself increases with synergy, so as the game progresses, you get more delta or benefit/use ratio, from the same card

In Greeks Are Everywhere I write:

One of the reasons I like boardgames is they are filled with greeks. There are underlying economic or mathematical sensitivities that are obscured by a theme. Chess has a thin veneer of a war theme stretched over its abstraction. Other games like Settlers of Catan or Bohnanza (a trading game hiding under a bean farming theme) have more pronounced stories but as with any game, when you sit down you are trying to reduce the game to its hidden abstractions and mechanics.

The objective is to use the least resources (whether those are turns/actions, physical resources, money, etc) to maximize the value of your decisions. Mapping those values to a strategy to satisfy the win conditions is similar to investing or building a successful business as an entrepreneur. You allocate constrained resources to generate the highest return, best-risk adjusted return, smallest loss…whatever your objective is.

Games have mine a variety of mechanics (awesome list here) just as there are many types of business models. Both game mechanics and business models ebb and flow in popularity. With games, it’s often just chasing the fashion of a recent hit that has captivated the nerds. With businesses, the popularity of models will oscillate (or be born) in the context of new technology or legal environments.

In both business and games, you are constructing mental accounting frameworks to understand how a dollar or point flows through the system. On the surface, Monopoly is about real estate, but un-skinned it’s a dice game with expected values that derive from probabilities of landing on certain spaces times the payoffs associated with the spaces. The highest value properties in this accounting system are the orange properties (ie Tennessee Ave) and red properties (ie Kentucky). Why? Because the jail space is a sink in an “attractor landscape” while the rents are high enough to kneecap opponents. Throw in cards like “advance to nearest utility”, “advance to St. Charles Place”, and “Illinois Ave” and the chance to land on those spaces over the course of a game more than offsets the Boardwalk haymaker even with the Boardwalk card in the deck.

In deck-building games like Dominion, you are reducing the problem to “create a high-velocity deck of synergistic combos”. Until you recognize this, the opponent who burns their single coin cards looks like a kamikaze pilot. But as the game progresses, the compounding effects of the short, efficient deck creates runaway value. You will give up before the game is over, eager to start again with X-ray vision to see through the theme and into the underlying greeks.

[If the link between games and business raises an antenna, you have to listen to Reid Hoffman explain it to Tyler Cowen!]

Advice for aspiring game designers [Kris: I think much of this applies to anyone whose job is to communicate — which is basically everyone]

The first piece of advice is to make games. I understand many are familiar with this advice, but it’s valid: make a multitude of games and practice consistently. The second piece of advice, especially for aspiring game designers, is to become intellectually curious. I haven’t met any outstanding game designers who aren’t. Be a voracious reader and be open to exploring different fields. Be genuinely curious. These two traits alone can take you a long way in the game design world.

Well, ok. But, given Raph’s background, it seems incomplete for me to not quote uber-successful game designer Sadie Green’s character in the novel Tomorrow, Tomorrow, and Tomorrow responding to a rando who asks her “How did you get into making video games?”

Sadie hated answering this question, especially after a person had told her that he hadn’t heard of Ichigo. “Well, I learned to program computers in middle school. I got an eight hundred on my math SAT, won a Westinghouse and a Leipzig. And then I went to MIT, which by the way is highly competitive, even for a lowly female like myself, and studied computer science. At MIT, I learned four or five more programming languages and studied psychology, with an emphasis on Judic techniques and persuasive designs, and English, including narrative structures, the classics, and the history of interactive storytelling. Got myself a great mentor. Regrettably made him my boyfriend. Suffice it to say, I was young. And then I dropped out of school for a time to make a game because my best frenemy wanted me to. That game became the game you never heard of but yeah, it sold around two and a half million copies, just in the US, soooo…”. Instead, she said, “I like to play games a lot, so I thought I’d see if I could make them”.

Specific content recommendations

Game Design Workshop by Tracy Fullerton: A highly recommended book for those eager to dive into game system design.
Art of Game Design by Jesse Schell: Provides an expansive overview of game design, though not structured as a course.
Characteristics of Games by Garfield
Advanced Game Mechanics by Ernest Adams: Great resources for those intrigued by game systems.
Game Feel by Steve Swink: For those in the video game realm, this book focuses on the importance of haptics and controls.
Character Development and Storytelling for Games by Lee Sheldon: Stands out as a guide for game narratives.
Designing Virtual Worlds by Richard Bartle: Essential for those venturing into online communities and virtual worlds.
Understanding Comics by Scott McCloud: A recommended read outside the gaming sphere.
100 Principles of Game Design by Wendy Despain: Covers core design principles across various disciplines.
The Visual Display of Quantitative Information by Edward Tufte: Despite being pricey, it’s invaluable, especially “The Visual Display of Quantitative Information.”
Disney Training Manuals: Includes titles like “The Illusion of Life” and “Drawn to Life.”
Art from Studio Ghibli and art history collections: Resources that provide visual and historical context to design.
Design of Everyday Things by Don Norman: A foundational book on design, emphasizing that game design is a subset of the broader design discipline.
Diverse Topics: It’s beneficial to explore books on economics, history, and mythology.