“you can’t change minds” — an interview with Victor Haghani

A great Munchie today. As usual, I highlight the parts I want to keepsake and inject my own comments here and there.

LTCM Co-founder Victor Haghani: “Taking Risk Is Always a Negative” | 1 hr 12 min watch

LTCM: right and ruined (01:27)

It’s good to think about investing as being two decisions: what to invest in and how much. And almost all of the focus of financial media, training, education, financial education is on what we should invest in… And at LTCM, we found some really good whats to invest in. But the sizing decision, how much of those good things is the right amount of good things, is equally critical, and is actually an easier decision to get right. But you have to realize how critical it is and that it deserves focus, and enough focus. And I think at LTCM, that’s where the mistake was, was on the sizing. It wasn’t on the selection of the trades, it was on the sizing.

EV ≠ risk-adjusted value (03:00)

Consider a 60/40 coin in your favor, but you must play 20 flips. This is a great “what” to invest in. But how much? Betting everything on every flip maximizes expected wealth, but you almost certainly end up broke.

The strategy that gives you the highest expected wealth at the end is actually to bet all of your money on heads each of the 20 flips. You have almost no chance of coming out of it with any wealth left… People don’t realize that’s the highest expected value thing to do, but it really shows you that expected value and risk-adjusted value are two different things. And it’s this risk-adjusted value that we want to maximize.

Risk-adjusted value is another way to say compounded return. Compounding naturally incorporates risk because the math of compounding is highly sensitive to variance. We’ll get to that later.

How the coin-flip players blew it (05:15)

  • Players came from graduate finance programs and Wall Street PM seats
  • They treated independent flips as dependent: bet heads after a run of tails, bet tails after five heads

Some people just bet a dollar every time. They just figured, “Well, if I bet a dollar, I’ll never go bankrupt”… and they really didn’t maximize the opportunity that they were given. And then other people were too aggressive and actually went bankrupt. They got their $25 down to like $3 and then they just started to YOLO it, out of impatience or whatever.

A good way to play this game is to bet a constant proportion of your bankroll on each flip. Bet on heads every time. Bet as fast as you can, like hit the buttons as fast as you can. And what should that constant fraction be? …between 10 and 20%. Like 20% is Kelly, and maybe you want to be a bit less…

And once we told people that, everybody accepted it. It was beautiful to see. It was like, “Oh gosh, I just wish somebody had told me that before.”

Sizing is non-zero-sum (08:20)

I really like this point:

Getting your sizing right is not a zero-sum activity. For you to be right, nobody needs to be wrong. We can all be correct together. But if you want to beat the market, you can only beat the market by choosing investments that you find that other people have not found and are doing worse than the market. The only way to beat the market is for somebody to underperform the market. It’s zero-sum.

Risk as an internal fee (12:55)

I plan to write a bit more on this idea myself. The “fee” framing Victor uses is fantastically plain, which I love, but I suspect people don’t believe this. I’m working on a post to step readers through the idea. As we’ll see later in this interview, my hopes aren’t high that it will convince anyone. Still, I believe it’s a profoundly worthy idea to flesh out.

There is a cost of risk which is the same as paying a fee. So when you’re paying an investment management fee to somebody, you pay that fee and you see that fee… And so if somebody turns up to most investors and says, “I’ve got this S&P 500 fund and the fee is 75 basis points,” people are like, “Come on, give me a break.” …Taking risk, you should think about taking risk as also paying a fee… The problem is that it’s kind of like you’re paying it to yourself. There’s nobody charging it to your account and it’s going out. It’s an internal accounting metric that you need to have.

For typical degrees of risk aversion for people, I would say you could think of that charge as just being equal to the variance of your portfolio. So if you have a portfolio that has 15% standard deviation… then I’m saying that you should be thinking that the cost of risk that you’re paying is 0.15 squared, is 15% squared, which is 2¼%.

His rule of thumb: cost of risk = γσ²/2.

This formula comes from something called the “Merton Rule” and it’s basically Kelly adapted for non-discrete-style betting, more akin to typical investing contexts in stocks and bonds.

A typical investor (γ ≈ 2) pays σ² while a Kelly bettor (γ = 1) pays σ²/2. Remember prescribed Kelly sizing is optimal for maximizing long-term CAGR, but it’s also very risky.

The Kelly bettor is a bit of a mythical being out there… I think that the typical guy is somewhere between what I described and 50% more risk averse actually.

Concentrated stock math (16:30)

If you have this concentrated stock portfolio that has 30% volatility, then you should be charging yourself, what’s 30% squared? It’s unbelievable. It’s 9%, right? It’s four times as much as 15 squared.

I’m willing to accept that the idiosyncratic risk is 50/50. Of course, there’s somebody on the other side of your hopeful 50/50 bet, and probably that other person is smarter than me anyway. So I don’t want to do it. I don’t want to have D. E. Shaw or Renaissance or whatever on the other side of my trades… Once I recognize that, it’s like, “Wait a second, I’ve got to make an extra 7% on those trades, an extra 7% just to break even and get a higher risk-adjusted return.”

That’s quite a hurdle considering that in a relatively efficient market you’re a coin flip to have bet right.

He talks a lot more about this in the interview so you can check that out on your own.

“How do I become a billionaire” is the wrong question (22:20)

When young people at a VC firm that invited them in to talk about his book…

It’s the right answer to the wrong question. That’s what’s going on here, right? If the question is, “How do I become a billionaire?” The right answer is take a lot of risk. Take a ton of risk… What do I need to do to become a billionaire is the wrong question. That’s the wrong objective.

The right objective for people is that you want to have the highest smooth, risk-adjusted, or we call it sustainable, lifetime spending and giving of money, adjusted for inflation, cost of living… The objective is not whoever dies with the most wealth wins. The objective is not I want to maximize the probability of having enough to retire. It’s not I want to die broke. Well, dying broke is easy. You spend all your money tomorrow and take a pill.

A few of the people said like, “But if I do what you’re saying to do, how am I ever going to become a billionaire?” And it’s like, that’s not the right question.

The only thing in a bear market is risk-aversion lol.

Crystal Ball, humans (27:25)

Victor saw a Taleb tweet:

He tweeted that if you gave people the front page of the Wall Street Journal one day ahead of time, they would all go bust in a year… They would be so overconfident. They would be so greedy. They wouldn’t size the trades right. They wouldn’t recognize that sometimes the employment report is hot and bonds go up.

The Elm team hired an intern to build a program to test this idea.

  • Business-school round: about 100 players staked $50 each, about $5,000 total. Elm paid out about $5,300, so with the next day’s news they eeked out a small profit. About 1/6 went bust, and the hit ratio was 52%. Some players ran 20x leverage.
  • In the web version: about 50k players with $1M of play money. The results were predictably unimpressive.
  • Six macro pros averaged about a 60% hit ratio and +70%, and all six made money:

Most of them were very selective. Like they only bet on six or seven of the 15 days. They didn’t always bet on stocks and bonds… They were just looking for something that they were really confident in and then they bet pretty big.

This reminds me of the “most important” gambling topic.

Crystal Ball, LLMs (34:55)

His prediction for head-to-head play:

Totally different experience because all you want to do is beat the AI. So you lose your mind… It’s like, “How can I beat Grok? I’ve got to at least be able to beat Grok.” Like Claude gets ahead, but it’s like, “Okay, I’ve got to at least get ahead of Grok.”

The paper confirmed his hunch. Head-to-head players used 30x average gross leverage versus 25x solo, and maxed their leverage on 10% of plays versus 6%

All of them are too aggressive and risk-taking… Claude is getting like just over a 60% hit ratio.

This doesn’t mean that they can beat the market, but it does mean that they’re doing better than the average human that comes to play the game… Most of what’s going on right now is people are running AIs to see if they can beat the market, but they’re not really comparing it to the average investor.

Paper companion numbers:

  • Base models ended at Claude $2.59M, ChatGPT $1.47M, Grok $968k, Gemini $492k
  • Stock sizing averaged 7–12x, and the market has moved more than 5% on 23 days since 2000
  • Merton share implies 7.5–15% daily σ; the AIs ran 20–40%
  • Gemini and Grok had positive Sharpe ratios and still lost money from overbetting
  • All four knew Kelly from the coin flip but didn’t connect it to stocks and bonds
  • After reading the book, sizing became far more appropriate and prediction skill stayed the same

Elm’s sizing question (47:40)

The main question we’re asking people is saying like, imagine that stocks have an expected return 4% higher than safe bonds. How much of your wealth do you want in stocks if that were the case? So that answers the risk aversion question and their view of the riskiness of stocks all in one go… And then we say, “Well, if stocks only have a 2% expected return above bonds, what do you want to do then?” And they’re like, “I’m happy to have 37.5% in stocks.”

Notice that the 4% → 75% allocation answer implies γ ≈ 2 at about 16% equity vol. This is the “typical guy” as his σ² rule.

Remember Merton: w = ERP / (γσ²)

ERP is “equity risk premium”

(Just fyi: Elm charges 12 bps; its ETF runs a 75% equity baseline)

You can’t change minds (1:02:45)

I’ve got similar stories up the wazoo:

One thing I’ve learned in doing what we’ve been doing for the last 15 years is that you just don’t change anybody’s mind about anything.

My mother day trades stocks. She’s 92 years old… She’s only been day trading since commissions went to zero. But for 20 years, I’ve been telling her to invest in index funds, that she’s a nonprofessional investor, that she should just own index funds and not worry about it. But every day she’s day trading now, in the morning, in the evening. It’s taking up a couple of hours of every one of her days. She loves it. She thinks she’s doing well. And nothing that I could say, no amount of time I could spend with her, would convince her to not be a day trader and would convince her that she’s not doing well.

And she thinks that I’m intelligent. Like she doesn’t think I’m her stupid son. She thinks that I’m intelligent. She knows I work in finance. She knows that some people listen to me. She knows I wrote a book, right? So she knows that, and she knows that there’s no conflict of interest, that I want to help her. Like, she knows that I don’t benefit in any way from her not day trading. So it’s really hard to change anybody’s mind.

Greg Newman of Onyx on Odds On Open podcast

📺How the World’s Largest Oil Derivatives Trading Firm Is Navigating the Iran War | Odds on Open

I’m biased considering I traded oil options for nearly 20 years but this interview is pure heat. Ethan Kho’s sat for a lengthy interview with Greg Newman, co-founder of Onyx, the world’s largest liquidity provider in oil.

Let’s go right to the excerpts (emphasis mine).


Interviewer: The oil markets have been crazy recently. How do I make sense of it all?

Greg: Honestly, I’d argue to begin with that it’s not like you should know something. There have been many crises, but this is unprecedented, and as a trader in particular it’s been very, very difficult.

There are so many oil contracts and so many liquidity pools out there. Brent and WTI are the key contracts that most traders and finance people know — that’s really the pool people dip into to hedge. But even that market, which is normally super liquid, has had its basis completely break down for a lot of these hedges. We’re used to at least one, two, three cents bid/offer, deep liquidity, lots of high-frequency traders, all that. We’re now talking 50 cents per barrel bid/offer minimum. And as you’re hedging, the price swings dollars per barrel at a time. It just breaks the whole system, because so many things in the oil world — all the contracts for every different product around the world, every region — ultimately link back to those core liquidity pools. When everything is broken from that sense, it’s incredibly hard to get a handle on it. So speculation has, to some extent, been out of the water. It’s been very difficult to do… What’s actually going on in the physical market gets reflected in these more niche contracts, of which there are many, many more, but they’re less liquid. That’s our specialty. Unless you’ve had exposure to those, it’s probably been very difficult to get an accurate reflection of what you should really be trading to profit from this.

How Onyx manages process when liquidity breaks down

Greg: We are market makers. There’s obviously a proprietary element to that, as you and your audience know very well. The temptation always is to combine your market making, look for some arbitrage-type opportunities, and then layer a discretionary element on top of that — ride momentum, things like that. But to begin with, it was really about getting to grips with the fact that you’ve got to take that discretionary overlay off the table. It just doesn’t serve you, because you’ve got people defaulting, people who can’t finance their positions. There are people whose only job is to take risk off the table because they’ve either blown up or they need to hedge, and it’s just not an orderly move. So you go back to your core business model — and you have to ask whether your core model is even suitable for that regime. The discretionary, hedge-fund-style approach is just not going to fare well in this scenario, certainly not at the beginning.

All the high-frequency traders looked like they were out of the game, to some extent. Maybe in the last couple of days they’ve been back in, bits and pieces, but certainly nowhere near the kind of medium-frequency trading they usually do. That’s been blown out of the water, and you can see it in the volatility. So you go back to your core model. Any model you had, any automation you had — it just doesn’t mean anything in this market. You go back to manual. You’ve got to be fully on top of it. It’s kind of basic in its process: you have a month-one price, you add your time spread, you infer the rest of the curve, then you keep adding differentials. That’s not too hard to see how to do. But they’re all moving so aggressively that just keeping everything in line is 90% of what we focused on. Because then what you’re able to do is spot the things that are so far offside that you can take them on — not to hold a proprietary view, but to back out of the liquidity with a correlated contract, something traded a bit further down the forward curve. Just going back to basics — fair value, trading what’s in front of you.

[Kris: This is exactly what I meant in Timing the Market when I describe taking off the discretionary trader pipe and glasses and putting on the market-maker boots and scrubs:

Trading is compensation for a service. In other words, a role. Don’t lose sight of the role. The easiest way to remember that is to ask yourself, “If I’m buying X at this price, what is it cheap against?”

The mantra stops you from drawing lines in the sand. From turning a relative value game into a…timing game. That’s what an outsize position relative to your business is — a timing bet.]

As you build infrastructure and a brand for liquidity and people come to you because you’re reliable, that’s when it pays off, because they’re not really looking for a good economical price — they’re looking for liquidity, and that’s what we do. So it was a good test of our business model. If you didn’t have that, honestly, the only move was to stay out of it until you could spot something not obvious but where you felt relatively safe — and that was just very, very dangerous to do.

Pricing fair value on Sunday night with no precedent

[Kris: I love this. Mock traders only need apply. Back to basics in a fast market. Snap judgements born from reps.]

Greg: Breaking it down — you have the Friday-night indications, and it’s our job to be completely 100% in the know. It cannot be partially in the know. So the moat we’ve got is our relationship with the brokerage firms around the world and the dark pool of liquidity we’ve got great visibility over. It’s not like other markets where it’s all electronic. It’s barely electronic, and in a time like now, electronic trading basically goes out the window, apart from the core one or two contracts. So this is where the niche expertise comes in.

Number one: you did know where it was Friday night. That’s not going to be completely irrelevant — you’ve at least got your starting point. We’ve also got traders who’ve been doing this long enough that they have a general sense of the relationship between big moves in the outright contracts — WTI and Brent — and Middle East wars, and generally what should happen to the refined products, how the curve should behave, how the time structure should behave, how clients tend to behave. And if you’re in our game with the kind of market share we have — 20–30%, sometimes 50% of some of these contracts — you’ve got a very good sense of how people are positioned. You know the weak spots in the curve, the strong parts in the curve. That’s not going to change, because at the very least people are going to sell what they own and buy what they don’t own. So you at least know where those things are going to come in.

So it becomes about having a very good feel for how the curvature started and how the relationships were working before, overlaid with analysis. You’ve got a weekend in oil, thankfully, where nothing trades, and you can use that time to look at previous times — what’s happened before. For example — it’s getting a little niche — naphtha, which we use for cracking to make petrochemicals, is a really key contract with Iran. They produce so much of it and send a lot of it to China, and China makes a lot of petrochemicals. So that’s a real sweet spot for Iran when an Iran situation kicks off. You’re expecting a reaction there.

Physical market participants and the reflexivity of hedging behavior

Greg: And then you’re expecting — okay, if all these things were to get higher, we know the behavior of, say, refiners is going to change. That’s the other thing about this market that’s different to maybe every other asset class. In a way it’s relatively illiquid, but so sophisticated. What that means is, for most contracts around the world, when there’s a big price move of any differential or time spread — let alone the outright price — it can reveal or destroy someone’s economics very quickly.

For example, a refiner says, “okay, I’ve got to hedge what I produce versus what I buy” — what we call the margin. They’re selling this kind of diff. And if it suddenly goes up $5, some of these bigger refiners have made an extra $5 billion on paper for the rest of the year. So they want to lock that in. Their behavior changes at certain price levels. The producers change their activity. And again, going from $80 to $120 oil, you’ve gone from maybe pretty good economics for a producing country to suddenly the best budget they’ve had in five years. So if they can lock that in, that’s what they’re going to do.

Another thing that’s unprecedented: how involved governments and producing countries have been in the futures market. Usually they’ve said, “look, we’re too big, we don’t want to hedge everything, it’ll just mess things up.” But we saw the US Treasury sell WTI — or at least it was reported that way — selling WTI swaps throughout the year, 11 million barrels, which isn’t a huge amount, but in a market like this it’s huge. You’ve got Saudi Aramco, BP, Shell — these guys who own a lot of the oil infrastructure in the world — they’re hedging. In real time you’re seeing their economics change, them trying to lock it in on paper, then suddenly those economics flipping on their head and deteriorating, and then the reverse.

Shipping companies are like, “look, this is great for my economics.” Airlines have done incredibly well from their hedges because they’re long, and they’re very active hedgers, and suddenly the hedge is way in the money. They’re going to want to lock it in. The airlines are a good example, because they hedge based on predetermined travel and fuel usage — that’s what determines the size of their hedge. So suddenly the price skyrockets as much as it does, and then you have disruption for airlines — there have been reports of something like a thousand flights a day cancelled around the Middle East. Suddenly they don’t have that physical consumption anymore. So they’re like, “well, we’ve just got a long position then, we’re just speculators now.” So they rush to take profit.

The jet fuel market in particular got most of the talk in our game, and there was some serious blood in the streets. It found its way onto X if you want to check it out, because it went in a straight line from probably about $90 a barrel — it carries a premium to Brent, so let’s say $10–15 above Brent — and it just went bang. And when I say bang, I mean no trades, all the way up to $200, and messing around since. How can that happen? It’s an example of the market being unbelievably short that trade — taking on airline trades, thinking the market’s not too volatile, “I’ll just wear this as a carry trade” — then bang. Some of the biggest oil traders in the world have the biggest position on. They can’t just go and buy it back; if they buy it back, it’s probably going to move another $100 a barrel, maybe more. So they just have to wear it. And so you’re hearing about oil traders in the market having huge margin calls — but these businesses are $10–15 billion-a-year businesses, and they’re getting margin called. This is the kind of craziness I’m talking about.

Voice brokers, people talking their book, and where the information actually lives

Greg: Why is it so incredibly difficult to replicate and do yourself? Because oil still has some very interesting dynamics — inter-dealer brokers and voice brokers. People hear that and say, “what, voice brokers?” Yeah — 80% of the volume is through voice brokers. If they don’t know you, if they don’t like you, if they don’t give you information about who — or not even who, just what — is buying and selling, you’re just in the dark. Literally a dark pool. The exchanges hate it, but it’s a very well-protected industry, because it’s a community, and these guys get paid a ton of money. There are huge companies that see the edge in having relationships with these brokers and probably keeping it that way. So unless you’re plugged into that game, it’s going to be very, very difficult to have the kind of visibility I’m talking about — who’s positioned where.

And then you could say, “well, look, I’ve got some friends, I’ve got some good information.” But that’s classic — we laugh about it all the time. That used to be a thing: go to a Mayfair pub and talk about who’s doing what. But the whole time, they’re talking their book. And unbelievably, people still fall for it. They go, “oh, I know this guy at this company, he said everyone’s buying, it’s going to be bullish.” He’s probably on the offer. You cannot rely on that information whatsoever. People talk their book. We’ve gone from traders talking their book to OPEC talking their book — they’re always out in the market feeding information, they know the headline sensitivity. Now you’ve got Trump talking the US book. It’s actually crazy.

Prediction markets as an information signal — and why Onyx stopped using them

Greg: It’s like the financial market — it’s so financialized, and the world’s governments know that and are more familiar with that than ever before, so they use it. They spoof the market, feed information, see how it reacts. That adds another layer. In that sense, there have been scenarios where huge option trades go through the night before Iran kicks off — huge, huge — someone clearly knows something. And even Polymarket being pretty useful. Something’s kicking off in Polymarket, an event that would clearly have a big impact on oil, and there’s now a dark area of oil where you’re saying, “someone might come in and do something pretty serious now.” And it’s not the oil traders, not people with physical information — it’s people with government information. So the dynamics are getting super interesting, but like any other financial asset class, I guess.

Interviewer: You brought up Polymarket, and this was something I was curious about before our conversation. I haven’t looked too closely into the types of contracts on these prediction markets related to the conflict in Iran, but I’m sure you have because of its implications in your industry. In general, how accurate a forecast do these prediction markets tend to bring? Is there enough volume on them? And more importantly, how do you think about them as a source of information?

Greg: To begin with, it was great. There really was nothing like it. Funnily enough, it was the Iranian situation last year — I forget exactly which month — but it was very useful then, because it was a new concept. A lot of people were betting on whether the Strait of Hormuz would be closed. People have talked about the Strait being closed as a hypothetical — you put it in your scenario analysis, you talk about it as a hypothetical — but no one ever believed, one, that it was even possible, and two, that it would happen. We even had a research guy, adamant, been in the game for 50 years, saying, “you cannot close the Strait.” So it was really interesting to see people actually believing it would. For a time in Polymarket, we were watching it live, going up to 80% yes, and we’re like, “come on, someone knows something.” And then you get all these messages of people saying, “I’m literally on a ship in the Strait, it’s fine.” That kind of transparent information, in real time, you can’t beat it. This is the good part of capitalism — using people’s greed for transparency, for the better functioning of markets and day-to-day life. No one in any other way would be incentivized to tell you what’s really going on. So suddenly you have something like Polymarket, and someone has information and wants to trade it, and that finds its way into the ecosystem of information.

So I thought it was a really good thing to begin with. Then what started happening, unfortunately, is it got more and more popular, and we started to realize the way it settles is just not ideal. Even with that Strait example, some people felt it had technically closed — ships slowed down for a time. How do you define “closed”? The settlement matters. It’s funny, because in our market in particular, with so many of these contracts, the big thing is to let contracts expire — which is actually quite unusual. A lot of us take these contracts to expiry. You might hold things against it, but expiry is incredibly important — how the contract expires and to what methodology. So we’re very used to studying these underlying methodologies, and that’s where relative-value opportunities — maybe not arbitrage, but relative value — can become very important.

So when we studied that from a Polymarket perspective, we lost confidence very quickly in what the game was all about. You have to own the tokens — you have to own a big portion of it — to be able to decide. So who decides is as important as anything else. And then — I’m not even saying it’s rigged — it’s just inefficient. So to use it as a reliable source of information, it kind of lost its gravitas quite quickly. So then we stopped looking at it.

Options flow as the real tell

Greg: …when someone has good information — and you can empathize — if you have good information, you don’t know when it’s going to kick off. So you just want the straddle, you want some good convexity. An option is a great thing to use. The interest in options became so overwhelming that it’s been a better indication of information being out there than anything else. So we kind of moved from Polymarket to options open interest and options activity at key times, right around the moment.

[Kris: Umm yea. The oil options market has been smart af for a long time]

And just to finish on that: the oil market historically has been quite orderly around its market hours. But after 7:30pm our time — which is the US close, up to maybe 6pm their time — that window is meant to be dead. It’s meant to not really trade, and it’s been very, very active around these times. So now we’re doing the hours later on, to see what’s going on, because the order book will reveal things. If you’ve got the visibility of all the contracts, that’s where you’re in the best position to know: has someone selected something in particular, and what could that mean? Because there’s no other reason why you would trade at that time. If you want to hedge, you go for the peak times. If you want to speculate, you want liquidity, so again you go for peak times. So why are you trading in these evening-to-nighttime trades? It makes no sense, other than maybe you’ve just got the information. And I think Trump knows that as well, because he makes a lot of his announcements either on the weekend — when the market will gap up or down — or at night. And we’re forced to be very ready up until the actual close of the exchange now, rather than the close of the market day.


That’s my favorite stuff because it’s about the nitty-gritty of trading but the rest is full of good business talk and a bit more on trading:

  • Regime-break risk: when the exchanges themselves are the risk. Greg’s worst moment last week wasn’t market risk but a flashback to 2022 TTF, when the EU floated capping the European gas futures price. A delta-flat book against expiry administrative volume becomes a billion-dollar naked short the instant nobody can sell you the futures to close on. He puts it in the same family as the Treasury basis trade.
  • What it’s like running the book through it. Sleeping bags in the office, WhatsApp blaring, the fighter-pilot bit.
  • The 26-hour evacuation. 55 people and 9 dogs chartered out of Dubai because the office was being bombed. Flight paths changed five times. They traded the next morning.
  • Countercyclical hiring during the lull. 2024 and 2025 were horrendous; that’s when they bought a team from a competitor, set up Dubai, and did the cultural reformation.
  • Why Onyx hasn’t taken outside capital, despite being asked repeatedly. Energy at the hedge funds has seriously underperformed outside of, say, Citadel. Capital isn’t the constraint; deployment and conviction are.
  • From prop shop to liquidity infrastructure. The flywheel: data, training, single-dealer platform, retail brokerage, credit/mini-bank. All of it leveraged off the core engine of being the most-liquid price.
  • The Glassdoor review that turned Greg into a LinkedIn presence. And the Hamilton line about who tells your story.
  • What’s surprised him most after 14 years. Spoiler: it’s not technical.

Finally, I was chatting with an oil trader about this interview and he recommended a book I immediately lifted:

hard earned trading wisdom

Euan Sinclair needs no introduction from me.

I’ll cut straight to the gold.

He’s been a repeat guest on Erik’s Outlier Trading podcast a few times. His writing and interviews mince no words. Despite never sugar-coating the reality of trading, I found his most recent interview even bolder. It’s this witch’s brew of insight that is somehow both timeless and underreported.

I’ll start with an idea from the interview he did from late 2025 that always bears repeating before moving to the more recent chat.

The most common misconception about trading volatility

In Euan’s 2025 chat with Erik, he was asked “What is the most common misconception about trading volatility?”

He zoomed in on the mistaken logic that because volatility is mean-reverting, selling it when it’s high assures a profit since it always comes back down.

There are several facets to the mistake. One is with respect to how volatility can cluster based on a market regime.

Saying volatility’s mean reverting is true, but the means also change, you know? So, if you sold volatility in, I don’t know, March 2020, right? Volatility didn’t go back to 15 for about a year, right? Volatility had a new normal. So just because something’s mean reverting doesn’t mean you’ll make money because it comes back.

Another flaw is in understanding that you are exposed to both realized and implied vol.

The other thing that can be wrong is that you’re not directly trading volatility. You’re trading the spread between implied and realized. And that doesn’t have to be mean-reverting and it doesn’t have to be negatively correlated with the level of volatility either. So just because the implied V comes down, that’s not necessarily going to help you if the realized vol still is higher than the implied.

[Kris: I remember suffering through a short option position in nat gas in the expiry right before I got married. The V09 option cycle (expiry date was late Sep 2009). Implied vol got up to 110% but it realized more than implied for our entire holding period. We chopped ourselves up on the short gamma even though we had “positive vega p/l” on some of the marks.]

It’s easier to understand this when you scrap the concept of “vol” for a moment:

Forget about volatility, right? Volatility is just a way of turning option prices into another thing. It relies on a model. Forget about all that, right? Let’s say you’ve got a straddle and the straddle’s trading at five bucks and that straddle normally is trading at two bucks. So you’re like, “Oh, that’s really high. I’ll sell it.” And then as soon as you sell it, it moves by $10. You know, the stock moves by 10 bucks. You’ve just got hammered, right? But you know, the straddle drops down to a dollar. So you were right about the price of the straddle, but you weren’t really just trading that.

Finally the VIX chart illusion:

That’s one of the problems people get wrong is selling volatility spikes isn’t as appealing as it looks as when you look at the VIX graph over time and you’re like, “Oh, the VIX these spikes. It always comes down again.” Yeah, but you that’s not what you’re trading when you’re trading options.

See this post from the Liberation Day period if this is not clear: you can’t trade spot VIX.


The rest of these excerpts are from Euan’s 4/1/26 appearance on Outlier. Emphasis mine.

Where to start: known effects

Erik asked Euan where retail traders should start. Euan’s answer is a tour through what he actually believes works, why it works, and how to think about learning from past data without fooling yourself.

If you’re prepared to have low enough expectations that they’re realistic, and then really work at this, um, and it doesn’t have to be a full-time job, but you can’t just think this is my extra income. You know, this isn’t like driving for Uber.

Erik: Thinking a little more deeply then about the kind of things retail traders should look at — I went through an interesting exercise on my own, because people would ask me for ideas on places they might want to start looking, and I always struggled to give a good answer. There’s a million variables. But I’ve recently started directing people toward really well-known market effects — stuff you could go look at research papers on SSRN in mass, well-researched stuff. Something like time-series or cross-sectional momentum as a general market effect.

The reason I’ve been going that route is that there are so many things you have to do right as a retail trader. Even if you’re doing all the right things but it’s centered on an effect that isn’t really there but you think it is, that’s massively detrimental long term. Even though the returns might not be — as you talk about — stuff that would give you Lambo money this week, you’re at least building the infrastructure around something we know exists.

Are there effects or markets that you think are better suited for those first few repetitions for a trader?

Euan: It’s not so much about finding a market where you have an edge. It’s not like, “Oh, you’ve got to trade shitcoins,” or “You’ve got to trade options on pharmaceuticals.” The actual instrument and sector are of lesser importance than the concept of what makes this thing work.

There are a few things in finance that we know broadly are real. Momentum is one. The other one I’d say, if you’re just starting out and you want to set up what I’d call a real trading operation, would be carry.

If you really understand the concept of carry, particularly as it applies to futures basis trading — in theory, we know that a future is going to coalesce to the spot price at expiration. But that doesn’t tell you how it’s going to do it. It doesn’t say the future’s going to stay there and the spot’s going to go up toward it. It doesn’t say the other way around. But what actually happens most of the time is that the future moves toward the spot price. Naively, that’s exactly what you wouldn’t think happens — you’d think the future was an expectation of the future or whatever. But no. It doesn’t matter what you naively think. That’s a very strong effect.

If you know about that effect, you’ve now got lots of places you can look for ways to apply it. And if you understand the effect, you’ll know places that are better than others. You look for something with a big basis. You look for something with high volatility, because that also gives you more of a basis. And you want something to move a lot, because if nothing moves, you can’t make any money.

That leads you to something like the VIX. The VIX futures have a very high basis to the cash usually. If you look at the difference and you annualize it, if that entire basis is realized, that can be 100% a year. Are you going to get 100% a year? No, because lots of other things are going to happen, and you’re not going to realize all of that, and there’s volatility. But that’s now an effect where you can start saying, “Okay, now I know this. What can I do to harvest it?”

Then you start saying, “Well, clearly I want to be short the future if it’s above the cash. That’s risky. What do I do to hedge that risk until I’m happy?” And maybe you’re like, “Okay, I’ll do a future spread. I’ll be short the front one, long the back one. What ratio? What futures?” Eventually you’re going to come up with — and there are papers written on this exact effect, I haven’t just pulled this one out of nothing.

A lot of the stuff’s out there. People tend to have this idea that no one’s going to tell you anything that works, whereas literally there are thousands of pages written on stuff that works. The universe isn’t going to give you money the way you want it to necessarily, but this carry effect — once you understand it in the VIX, then you’re like, “Holy shit, this also works on a ton of other commodities. It works in bonds.” And then, “Okay, if it works in bonds, does it work differently in treasuries, credit, corporate bonds?” And the answer is yes. So now you’ve got spreads. So relative value is the next thing you start looking at.

Pick a bunch of carry situations, learn to put them on, learn to manage them. They largely take care of themselves, but you have to adjust, you have to understand the risks. It’s like when you fly a plane — you’re learning on a Cessna, learning slowly. You don’t just get into a MiG and blast off. But this is that Cessna. It’ll get you money, and it’s a real trading operation.

Then you move on to relative value. These spreads move around. Maybe I can scalp those spreads. How do they move around? What’s the range? And then, “Well, sometimes they don’t move around.” Okay, and that’s going to lead you to momentum. That’s your next one.

Everyone should read that book by Antti Ilmanen, Expected Returns. It breaks down — it’s about 400 pages long, that’s how detailed it is — and it talks about the volatility premium for about four pages. It goes into hundreds of things like this that work. Carry is a huge unifying feature. Relative value. Momentum. The variance premium and options — again, that’s there. I wouldn’t recommend people start with it. It’s kind of slippery and a good way to lose a ton of money unless you’ve got everything else sorted out. But it’s another one.

That’s where I’d start. I’d start with one thing, move to the next, keep adding. Once you got to three or four things, that’s probably all you can handle. You’re not going to be able to have 10 different strategies and keep things together. That becomes a major logistical operations issue.

Where to expect edge: the hard leg is where the money is

[Kris: My biz partner would say the “hard leg” is where the money is.]

Typically in the world, you get paid for doing something that makes the world somehow better. You provide a service, and typically there’s something unpleasant about that. Otherwise people will just do it themselves.

If you’re selling flood insurance, that’s a tough business because you make money, make money, make money, and then you get absolutely blitzed. That’s a tough thing to live through. Everyone thinks they can, but in reality it’s a lot harder than you think. We’re very bad at figuring out how we’ll feel when something bad happens. Similarly, the guy in the flood who’s cleaning out the sewers, he gets paid.

If you’ve got a clear idea of, say, the carry trade — why am I getting paid to do the carry trade? Largely because I’m providing a source of risk insurance for other people. I’m short those futures that are going to go massively up when the market — like a couple of weeks ago — when the VIX spikes from 18 to 30, those short front-month futures are going to hurt you way more than the long back months. And they have to. Because if you hedged that, then there’s not going to be any premium for you to take out of the trade. All of these things are risk premia. In order to get risk premia, you have to accept that risk. Over time you’ll be fine, but you’ve got that unpleasant nature of the payoff.

Another good rule of thumb: anything where you think this is a bad idea because the risk looks unpalatable — there’s probably edge in there somewhere. If you as a professional trader are like, “Yeah, this looks dangerous,” you’ve got to accept that most of the rest of the world also thinks it looks dangerous, and you get paid to manage that fear. You are the bomb disposal guy. That’s why you’re getting paid.

So if it’s like, “Ooh, there’s no way I’d sell options over the weekend, that’s dangerous” — all right, what side do you think the edge is on? The guy who is prepared to sell options over the weekend, or the guy who wants to buy options over the weekend?

Walking into danger — I’m not saying you always have to, and it’s a risk judgment; you don’t have to take every risk that’s out there. But if it makes you nervous, there’s probably edge in there somewhere. If you can get it to a point where you’re comfortable with it, or can diversify, manage, or hedge it, that’s a good place to start making money. That’s why you get paid for selling options. You don’t get paid for buying options.

Again, difficult thing to say, because for the last three or four years, retail made a ton of money buying 20-delta calls in the indices. By the way, historically, what’s the worst option to be long? Index 20-delta calls. If you think that’s your edge — no. Take that money and good for you. But that’s not the way the world has typically worked. It might work like that for the rest of my life, who knows. You’ve got three years where that worked really well, and 100 years where it didn’t. Just as long as you know that.

Look for any situation that legitimately makes you uncomfortable, and there’s probably something in there.

Learning from the past

Erik: Two follow-ons. I’ll give you both, and you can pick. The first is how to use past information to inform future projections or predictions. The second is pricing of convexity and some of the internals behind that. You pick whichever one sings to you.

Euan: I think the first one is probably more suited for a podcast format.

Basically, the only thing we have to predict the future is the past. And there are two things you can say: the future will be somewhat like the past, or it won’t be like the past. Of those, clearly the better one is to say it will be somewhat like the past. That just makes sense, and usually that’s the way it’s been.

The problem, particularly in finance, is it’s an adaptive system with people on the other side of, and everyone is going through this thought process to a certain degree as well. Everyone’s looking at the same information. Everyone’s saying, “This is the way it’s behaved.” Everyone’s trying to predict on the same thing. Largely coming to a spread, but broadly the same conclusions.

So using the past to predict the future is always going to be murky. And there’s an unfortunate tendency we have now. Like, 30 years ago, no one did backtesting, because you couldn’t. There was no data, no computers. Even before Excel — you’d have to write a program in Fortran. It was hard. No one did it.

Now, everyone does backtesting. The problem is that means most people do it wrong. They see backtesting as a way to find patterns, and they’ll test stuff, do cross-validation, test walk-forward, go out of sample, and they’ll find things. The problem is they look at so many things. Of course they’re going to find something. That’s the big problem with using the past — you think you’re doing statistics correctly, but really all you’re doing is looking at stuff over and over again until you find it.

You’ve also got to remember — and this is an Aaron Brown thing as well — as soon as you’ve looked at some data once, you’re done. That data is in sample forever. You can’t say, “Oh, I’ll try my trend-following system on the S&P. That didn’t work. I’ll try a mean-reversion system on the S&P.” The only reason you’re trying that mean-reversion system and think it might work is because your trend-following one didn’t. So you’re already overfitting. It’s not so much overfitting to the numbers. It’s applying information you’ve learned by looking at it already, even if you’ve looked at it for a different thing.

At this point, there is practically nothing I can do to study the VIX that’s going to tell me anything, because I’ve looked at the VIX for so long that I know what’s in there already. I’m not actually making any sort of new judgment. All I’m doing is applying what I know has worked in the past because I’ve looked at it so many times.

The way to address that is to start with something you believe first. Do you believe in carry? Yes. Do you believe in momentum? Yes. Cross-sectional momentum? Yes. Risk premia? Yes. And then you come up with an idea, and then you say, “Does this work in the past?” And you test it. If it works, great, you can make it better. If it doesn’t, you give up.

We see this with options particularly. People are like, “Well, I tried selling strangles on Monday and holding them all week and it didn’t work. But then I found if I sold straddles on Tuesday and got out on Thursday, it did work.” Both of those are driven by the same effect — they’re both variance premium plays. If one of them didn’t work and the other one did work, all it means is you got lucky picking the entry point for one and not the other. As soon as you’ve looked at that second one, you’ve just completely overfit the whole thing.

That’s one of the big problems people make by using past data. You use past data to come up with the overall belief. Carry means something. Credit spreads mean something. We’ve got, I don’t know, 5,000 years of stories about credit. Credit’s older than money. It’s a real thing.

Looking at numbers should be the last thing you do, and only to confirm something you’re already pretty sure works. My risk premia thing — I’m sure it works. I can test does it work better in a one-month option or a one-year option, but I should not be just blasting combinations in until I find something that is the best.

One of the most dangerous words that’s come out in quant finance is certainly “alpha drift.” This isn’t a retail problem either. I see this in quant firms all the time. They optimize and think they’re doing it out of sample, but they’re not, because they’ve already — this is the fourth model they’ve run on the same data because they keep looking at the S&P 500 or something.

Optimization is a horrific thing. It’s one of the worst things to ever hit the world of finance — that concept that you can make something better, or perfect, or optimal.

The other one, by the way, is theta. I can’t think of a thing that’s cost any more money than theta — this idea that options decay over time. That is literally not what the Black-Scholes equation is telling you. The Black-Scholes equation is literally telling you they don’t. If everyone knew an option was decaying over time, no one’s going to pay for it now — they’ll buy it tomorrow, it’ll be worth less. The number of people who’ve fallen into that “I’m harvesting theta” thing — and there’s plenty of influencer types who are peddling that story, typically also owning a brokerage at the same time.

The difficulty of learning from the past is that people think they can learn too much from the past. You have to discount everything you know based on how much you actually believe the thing. Show me an effect you found in the market — I don’t know what it is. A few years ago, “gold goes up on Fridays” was a big thing. Everyone looked at the data — look, gold went up on Fridays. Okay, why would that happen? “Well, it’s because fund managers are scared of risk and they go into gold on Fridays.” All right, find me one of those people. Not you, or some other person who buys gold on Fridays. I mean someone who runs an appreciable amount of money — doesn’t have to be Pimco, but people who run hundreds of millions or billions. Show me one of those people. No one’s ever managed to do that.

Does it go up on Fridays? Well, it looked like it did. T-stats, sure it did. Now how much do you actually trust that? On a scale of zero, which is candlestick charts, to 10, which is carry is a real thing — I’ll give gold on Fridays a three. Could it be true? Sure. But I don’t see a compelling reason. You look at enough things, you’re going to find that.

That’s the problem people get. They look at the t-stats and go, “Look, statistics, man.” All right — now how many other things have you looked at that didn’t work? Because you’ve got to include those.

The philosophical problem of what you can learn from testing

Starts with sound reasoning:

I’d like to start with the idea that people buy bonds at the end of the month because of window dressing and rebalancing of 60/40 funds. There’s an idea. If the stocks go up more than bonds in a given month, people rebalancing have to sell the stocks and buy the bonds. That should have an effect. That’s your hypothesis.

So let’s look for situations where that hypothesis has a market effect. Do you see it? Do you see it in situations where your hypothesis would tell you you should see it? Equally, do you not see it in situations where your hypothesis tells you you should not see it? If this also happens on the second week of the month, maybe it’s not what you think it is.

I’d always like to start with a reason and then test the reason.

…But there’s thousands of years of philosophers who pointed out all the contradictions in this stuff. Nothing in the world is out of sample. The only person in the world who’s out of sample is a baby who doesn’t know anything. That’s the great curse — the more you know. With me and the VIX, it’s not that I’m the greatest VIX person in the world or even close. I’ve just looked at it, I know it, I can’t be surprised by anything it does. That’s the downside of experience: nothing is out of sample…

The best you can do is find a situation that looks like it’s somewhat constant over time. If you look at the statistics of the VIX, the distribution is pretty constant. If you look at what it did in the ‘90s and in the 2000s, break it down in big blocks — it kind of looks the same. Whereas stocks tend not to. You can’t look at Tesla 10 years ago and Tesla two years ago. The business models were totally different, but in one case the stock was a dollar, and over the last two years it’s been between 200 and 400. These are different situations. Stocks are not stationary.

But really, one of the things you have to do is accept how little you know about the world. The good traders never say, “I’m right because of this, and this, and this.” The good traders are like, “I think I might be right because of this. But on the other hand, I could be wrong because of this and this and this.”

Aaron Brown, who’s probably thought more about this stuff than anyone I know, says that a bad trader is always saying “and furthermore,” and a good trader is saying “on the other hand.” A good trader is looking for holes in their argument. A bad trader is continually trying to find other reasons why they’re right.

David Hume — smart guy, all philosophers do is think about thinking — they were pointing out the problems of trying to learn from induction hundreds of years ago. There’s no answer. That’s the only information we have, but we can never really draw certain conclusions from it. So I always apply a big whacking discount to everything. And it’s not statistics. It’s a meta level above that. It’s like belief. I’m not just saying there’s a statistical rule for how you judge if this is good or bad. In fact, literally there isn’t. There’s an actual degree of belief that is independent from what the numbers are telling you.

Vibes vs quant is a false dichotomy — there’s vibes in everything

[The general construction of his portfolio isn’t] based on statistics. It’s based entirely on my degree of belief. Like that carry trade we talked about — how much do I believe that? A lot. Given what I know about its volatility — and I mean “things move around” volatility, not standard deviation of returns — given I know how much that is, given I know how scary it can be, but given I know the belief, I might give that 40%. Whereas there might be another trade where statistics are just as good, but I’m like, I don’t know, I don’t really believe in that one. That gets 20%.

That gives me my baseline, and then I go run all the statistics, and then I say, “Well, okay, I’m shrinking it to this vibes portfolio, because that’s the one I kind of wanted to be at in the first place.” There’s a lot of people who’d be like, “Well, that’s not quantitative. That’s not systematic.” Well, first of all, who gives a shit what they say? You don’t get a medal for being quantitative. You make money or you don’t. Being quantitative is seen as this kind of goal, and it’s not the goal. It’s a tool toward the goal.

Every time you make a portfolio or sizing decision, you are at some point applying that kind of thing. If you’re going to go through all the math, eventually you’re going to have a utility function, and that utility function is going to have a risk aversion parameter. So you’re going to go through all this math, and then at the end it’s going to say, “Oh by the way, what’s your risk aversion parameter?” You have to make that decision somewhere. I’m just doing it at the start. It’s much more of an exogenous thing that’s obvious.

It’s more a reflection of what I think I actually know than a mathematical statement. It’s not a mathematical statement. It’s an epistemological statement.

A lot of people get hung up on “insult found: the discretionary trader.” How is that an insult? Everything you do is discretionary at some level. Literally, you have chosen to do something. You have exercised your discretion to do something. Whether you do that in the math you choose, the problem you attack — you can’t go through life without exercising discretion. That’s actually called knowledge or experience. It’s a useful thing. If you don’t use that, you’re an idiot.

The cost of systematization

There’s certainly this whole idea that if you’re systematized, it’s emotionally easier to stay with things. I don’t think that’s true. I have operated completely systematic stuff when I’ve had jobs, and it loses money. It’s not easier. It just isn’t.

The reason I think you should systematize something is because you have to. Every time you’re removing yourself from interacting with the market, you’re removing yourself from an opportunity to learn. I think you should do things as manually as possible — and I mean it. If you can get away with writing stuff down on a legal pad, then that’s the way to go. If you need to use a spreadsheet, use a spreadsheet. But if you can do it on a spreadsheet, yet you choose to write some massive API call and do the whole thing in some language — you’ve done that because you wanted to, not because you needed to. That’s a mistake.

The places I’ve systematized things are because I wanted to avoid operational risk and key-man risk. If I’ve got a strategy I want to run for an ETF every day, it has to operate if I crash my car and go into a coma. That has to be systematized. But if I’m running something on my PA because I find it interesting and I’m still messing around with it — systematizing that, all I’m doing is removing the opportunity to learn.

It’s one of those things where retail look at institutional and go, “Well, it’s all systematized. I have to do that.” But they don’t think of the reason we systematize things. It’s not to make the strategy better. Honestly, it probably makes it worse, because you’ve locked it in. You’ve said, “This is it, I’m not going to be learning anything more about that now.” But it definitely removes operational risk. It makes it cheaper to run, because you can just let it run on its own. You don’t need a person doing it all the time.

People on the outside are making a judgment of how the things on the inside work, and they’re missing the point.

How do you avoid it? I don’t know. Hopefully if I pointed that out to you now, you’d be like, “Oh yeah, now I get it, this is the important thing.” Think about anything else you’ve ever learned. You’ve learned by doing, by the immersion in it. Trading now, the actual act of trading, is click, click, click, done. You don’t learn anything from that.

But what you do learn about — especially things like adverse selection and the ability to execute — like, “Oh, it looks like there’s plenty of volume. Oh, but every time I put a 100 lot in, all the bids disappear.” That’s the sort of thing you’ll learn so much about just doing it and interacting with it. You’ll never learn that if you automate the trades.

[Kris: To insert something here. I’m reminded by an interview with Agustin Lebron where he talks about getting ideas from just staring at an order book for ours. Seeing how it updates, how bids and offers change after trades, or in the absence of trades but while the rest of the market is doing things. He recommends doing this in medium or low-liquidity names where you can possibly see a story unfold in the order book. I agree with all of this. I mean I don’t think I never explained it quite like that because it’s just the water you swim in. If you trade something relatively illiquid, every movement matters. If some 20 delta put trades on the offer, you have to triangulate whether it’s skew expanding or volatility in general. See Mermaids, Fireflies, and the Bid-Ask Spread.

But there’s a corollary hidden in wisdom of learning from sparse order books: edge is inversely related to liquidity. The more liquid the market, the more whatever’s left looks like a risk premium. SPY is one of the most liquid markets in the world. If you had any edge in trading it, the edge would be so scalable your heirs would be set for an eon. Remind me to rant about this sometime.]

If you’re in a situation where you have to automate the trades, you’re probably playing in a game where you’re not going to win as a retail trader. You shouldn’t be trading, “Oh, I have to run this through the API so I can trade 15 times a day.” That’s one of those quant-envy things where you’re like, “I’m going to do this the way Citadel would do it.” Again, you’re playing basketball one-on-one with LeBron. Good luck. Don’t care how tall you are.

Inefficiency vs risk premia

There’s a split between inefficiencies and risk premia. With an inefficiency, price competition is going to drive it to zero. Nothing’s purely risk and nothing’s purely inefficiency, but market making in options has a lot of inefficiencies. It’s like, “I’m going to buy this option because I can sell this option. Those things should be worth the same. They’re off by a little bit.” That kind of thing. The act of providing liquidity is a risk premium, but the way you do it is looking at all these little inefficiencies.

If you look at the way equity market making has gone in the last 30 years or whatever, ever since the floors have gone and we’ve gone electronic, that has been driven to almost zero. It’s not at the point now where any sort of random person with an off-the-shelf piece of software is going to consistently make money making markets in equity options anymore. It’s gone from profit margins like Tiffany’s might have, and now it’s Walmart. Everything’s driven to zero.

Risk premia are different, though, because they’re there for legitimately a reason. It’s a different utility function. You’re doing something you know is wrong because you don’t want to deal with the risk. You’re buying insurance. You’re not buying insurance because you’re dumb, you’re buying insurance because you want insurance. And I’m selling it to you because either I can take the risk, or I can lay off the risk, or whatever reason — I’m doing it to maximize expected value. You’re doing it to maximize another utility function. We’re both happy.

That kind of thing has got more legs to it. If you look at the variance premium over time it’s been reasonably constant. Obviously it goes up and down. You’d think that after 2008 it would get wider; surprisingly, didn’t much. You’d also think that now, because of all these zero-DTE covered call funds, it would collapse. And it kind of has. But sooner or later people will realize a lot of these funds don’t make money, or some of them will blow up, and it will go back to where it was. All these risk premia are cyclical, but there seems to be a natural limit that doesn’t get driven to zero.

It helps to be able to say: is this an inefficiency that people can’t access, or is it genuinely a thing that everyone knows is there and people are doing it for different reasons? Because that’s the sort of thing you can build a trading life around. Inefficiency — if you find one, good for you, knock it out of the park as hard as you can. It’s not going to be there forever. If it is there forever, Citadel is going to come along and build a desk on it and crush you.

Adaptive markets, but not adaptive traders

Erik: The follow-on, though, even within something like risk premia that we know is there for a reason — an example you’ve given previously is there’s a $20 bill on a busy highway. If I’m standing on the sidewalk and there are five crackheads, and I say, “Hey, I’ll give you 10 bucks to go get that.” And then one of the other crackheads says, “I’ll do it for eight. I’ll do it for five.” And then at some point we get to a floor where the crackheads are like, “I am not going to risk my life for this anymore.” Do you think that with something like risk premia in index options, based on that consistency, we’re generally about at that level? Or do you think it’s likely to shift around more?

Euan: That’s difficult to say. But with your crackhead example — one crackhead might say, “I’ll do it for six bucks,” and he runs out there and he gets killed. And then the next crackhead’s going to come along and say, “Actually, I want seven now, because I saw what happened to this guy.” It’s not the same people all the time.

What we tend to see is a new cohort of traders come in and blow up doing the wrong thing, and then a bunch of other people come in and end up doing the same wrong thing. The market never completely adapts, because it’s never exactly the same group of people who learn. Markets learn, but traders as a whole don’t. For things like this, a lot of it’s propped up by new people coming along making the same mistakes as the old people. Adaptive markets, but not adaptive traders. In a lot of cases people think they’re the same thing. I don’t think they are. There were a ton of floor traders, good floor traders, and then everything went electronic, and they tried to do what they did on the floor on the screen. It just didn’t work. And I don’t know any of those guys who were like, “It’s not working, I’ve got to do this and this and this instead.” That didn’t happen. Instead, a whole bunch of other people — studied computer science at Cornell or whatever — came in. It was a whole different group of people who made money at that point.

Memorable sections from Casey Handmer on Dwarkesh

Casey Handmer on Energy, Solar, and the Future of Civilization

Dwarkesh Patel podcast

On this episode, Casey Handmer (Caltech PhD, former NASA JPL, founder & CEO of Terraform Industries) walks me through how we can pull it off, and why he thinks a major part of this energy singularity will be powered by solar. His views are contrarian, but he came armed to defend them.

These are a few sections that stood out to me:

The fundamental energy transformation process

All conventional power generation follows the same path: find something in the earth that’s out of chemical equilibrium with the atmosphere, burn it to make heat, boil water, run it through a mechanical contrivance to create motion, twist a magnet to generate an electrical field, push electrons through wires, and ultimately approximate thinking through computational gates.

The key bottleneck is converting heat into electricity efficiently. Whether nuclear, gas, combined cycle, or coal plants, they all use the Brayton cycle – the same thermodynamic process that powers jet engines. Any Brayton cycle with Inconel spinning at high speed costs serious money.

Why China’s 20x solar manufacturing advantage isn’t determinative

China faces fundamental vulnerabilities: surrounded by hostile neighbors, dependent on Middle East oil via undefended shipping routes. The US has superior automation, financial capacity, and business environment. Solar manufacturing could be rapidly scaled domestically within 2-3 years if treated as a national priority.

Solar’s relentless learning curve

Solar has a 43% Wright’s Law coefficient – every time cumulative production doubles, costs drop 43%. Not only are adoption, production, and price decreases continuing, they’re accelerating. And the rate of acceleration itself is accelerating.

Why hyperscalers currently choose gas

Two reasons: they need immediate deployment (everything before 2030 is already spoken for), and they’re power availability sensitive rather than power cost sensitive.

The scale of solar infrastructure needed

For 5 gigawatts of AI capacity: 50,000 acres. This sounds massive but is comparable to Manhattan Project sites (Oak Ridge: 60,000 acres, Hanford: 100,000 acres). Technical specs: 10 acres per megawatt at four nines uptime, including solar overbuilding for reliability.

Batteries as grid replacement

Batteries do the same job as the grid – the grid transports power spatially, batteries transport power temporally. The grid suffers from Baumol cost disease while battery utilization runs much higher, making distributed battery systems more economical.

Environmental regulations as the binding constraint

Environmental regulations actively prevent renewable deployment in the US. This is why Texas is winning – out deploying California 10 to 1. NEPA reviews take 4+ years and generate more environmental impact than the solar projects themselves.

GDP becomes misleading in an AI economy

GDP will see massive deflation because the variable cost of running AI will be cheap compared to paying human wages. In the long run, it makes more sense to measure civilization’s size by raw energy use rather than GDP.

The ultimate vision: silicon consciousness

One human brain can be simulated in roughly a square meter of silicon floating in space. Integrated solar-computation wafers can fly as solar sails, adjust orientation with LCD panels, and operate indefinitely in space.

We’re seeing the beginning stages of a collapse back towards the simplest possible thermodynamic-to-cognition stack. The most efficient way to convert energy into usable cognition is silicon.

Timeline predictions

  • 2027: Majority of new data centers breaking ground will be mostly solar-powered
  • 2030s: Multiple 5-10 gigawatt AI facilities operational
  • Long-term: Transition from current complex industrial economy to simplified silicon-based energy-to-cognition conversion

The overarching thesis: we’re approaching an “energy singularity” where solar becomes so cheap and abundant that it fundamentally reshapes both AI development and human civilization itself.

 

Transcript of Kevin Muir on Intentional Investor

Matt Zeigler interviewed Kevin Muir. The interview is 5 stars so I am memorializing the transcript so I can easily refer back to it.

Watch the Full Interview: Kevin Muir – The Intentional Investor

My top highlights

  • Analysis of Monopoly Properties
    Kris: I remember discussing exactly this topic in a SIG interview. When you come out of jail, the most likely properties you land on are the tan ones.
  • “Why Can’t You Just Enjoy Things?”
    His wife’s question (paired with a great Scrabble story) underscores a key lesson: Do your best, work hard, but eventually just throw it out there and see what happens—then move on to the next one. This is reinforced by his unpredictable success with writing.
  • Getting His First Job and His Dad’s Advice
  • The Luck of Being a Computer-and-Markets Guy
    Reminds me of Marc Andreessen’s advice about how if you are 90th percentile in each of 2 domains, you are 99th in join probability space (.1 * .1). But Kevin’s story also shows the importance of luck—his joint skills perfectly matched a short window in time before specialization took over technology.
  • The Pickoff Story: Honor, Ethics, and Reputation

Then these 3 parts which I bring special attention to:

  • Leaving Corporate Life
  • Romanticizing the Past
  • The Secondary Effect: Norwegian Art Story

Leaving Corporate Life

The emphasis is mine. 🔥

Anyway, we have our first kid when I’m 29. I’d been at RBC for six years or so. At that point, the bank was slowly overtaking the dealer. It started as an entrepreneurial place, but over time, the bank got more involved. Rightfully so—I look back at some of the stuff we were doing, and I’m like, “I’d never let some 27-year-old punk do this.” It was irresponsible. We made tons of money, and it was fun, but I wasn’t mature enough to realize that was a unique time, not how life always works.

The bank starts creeping in, telling me, “You can’t trade this, you can’t trade that.” I’m getting in trouble—“Kev, you can’t do this.” Then we have our daughter. She’s born with a heart defect, corrected at birth, but it was a very emotional time for me. It was like a near-death experience—not that I died, but it hit me hard. I never felt the same way about work after that. A couple of other things made it less fun too. Three months after she’s born, we have our best quarter ever, and I think, “I’m going to be like Michael Jordan—sink the basket and walk away.” So I quit.

At the time, I didn’t know what I’d do next. I hadn’t made enough to never work again, but enough to not worry about the next year. I thought, “I could work for a hedge fund, but I don’t want to do sell-side again for a while.” If I worked at a hedge fund for a year and quit, people would remember me as the schmuck who lasted a year. But if I tried something on my own for a year and then went to a hedge fund, no one would care about that year. So I started trading for myself. Eventually, another guy from my old shop joined me, and that was it. Along the way, I started writing the letter and doing the podcast.

One thing I laugh about—I’ve never really had a steady paycheck. Even at RBC, it was a small draw, and it’s been “eat what you kill” for the last 35 years.


Romanticizing the Past

Interviewer: People romanticize the past, thinking it was easy to make money.
Kevin: Exactly.

“I tell people my story, and I always say, ‘Oh, I would have made so much money back then; it was so easy.’ And everyone always thinks it was so easy. But I always tell them, ‘Listen, it wasn’t easy.’ Right now, there’s somebody who is quietly making a fortune, someone who has figured out the equivalent of my interlisted arbitrage. When I was doing my interlisted arbitrage on my machine, I wasn’t telling everyone—I was quiet about it. There’s somebody somewhere doing the exact same thing.

“There are always people making money, and it’s always hard. I remember thinking specifically, when I would listen to their stories—like the trader above me, 5 or 10 years older than me—I’d think, ‘If I had just been there when 87 happened, if I had just been there then…’ People always look back on the past, over-romanticizing it.”

[Kris: If I had a dollar for every time I’ve  heard someone think this about floor trading…The attrition rate of floor traders was insane. Another new face? Give him a month and we’ll see  if he’s around. Also, if I had a dollar  for every time I said this about someone before me! We project our current tools onto the past. I wont’ re-hash it because Nick Maggiulli does a great job on this topic. See The Privilege of Knowledge.]


The Secondary Effect: Norwegian Art Story

Interviewer: Tell the Norwegian art story—it relates to this.
Kevin:

I’ll quickly go through it. For those who don’t know, in the late ’60s and early ’70s, I believe, Norway discovered oil off their coast. It was this huge boom, and everyone was rushing out to get blocks of water they could drill in. There was an enormous fortune to be made with this Norwegian offshore oil boom. For those who don’t know, we think of Norway as a very rich country now, but up until that point, it wasn’t. It was actually the poorer of the Scandinavian countries, mostly reliant on fishing—not a lot was going on in Norway. So, they discovered this oil, and the long and short of it is that all these guys were rushing out to buy pieces of this water to drill in.

Then there’s this trader who looks at the situation and says, ‘Okay, that’s getting fully priced in. What can I do?’ He decides to start accumulating Norwegian art. He just starts buying all this art, and you might think, ‘What kind of crazy guy is this? Why is he buying Norwegian art?’ The long and short of it is that he had figured out that once all these guys made their fortune from the offshore oil, they’d be looking for something to do with their money. Art is a very local market, and when a Norwegian guy makes some money, yes, he might go buy a Picasso, but he’s also suddenly going to want Norwegian art. So, while everyone was busy fighting and paying too much for this offshore oil, this guy was quietly accumulating Norwegian art. A year or two later, when all these newly rich guys started looking to spend their money, he was there with offerings for them and made a fortune that way.

To me, that epitomizes trading. What’s interesting is if you go back and read Liar’s Poker again, you’ll see Michael Lewis talks about two guys who were his mentors. One of them is this guy, Dash Riprock, I think, who sits around watching for a bond to be, say, 30 seconds too expensive, and then he arbitrages it. He’s kind of a block-and-tackle kind of guy—just straightforward. But then there’s this other guy, this big, bold trader. If you reread that section, Lewis describes how, when something happens, this trader is already onto the next iteration, trying to figure out, ‘Okay, this is occurring—what’s the next step?’ Instead of just focusing on the first derivative, he goes for the second derivative. In other words, he thinks, ‘Once everyone does this, what’s that going to mean for the next thing?’ It’s like thinking multiple moves ahead in chess.

[Kris: The character in Liar’s Poker is named Alexander. This is an example of Alex’s second-derivative thinking, which I refer to in Trading Is A Team Sport:

The second pattern to Alexander’s thought was that in the event of a major dislocation, such as a stock market crash, a natural disaster, the breakdown of OPEC’s production agreements, he would look away from the initial focus of investor interest and seek secondary and tertiary effects.

Remember Chernobyl? When news broke that the Soviet nuclear reactor had exploded, Alexander called. Only minutes before, confirmation of the disaster had blipped across our Quotron machines, yet Alexander had already bought the equivalent of two supertankers of crude oil. The focus of investor attention was on the New York Stock Exchange, he said. In particular it was on any company involved in nuclear power. The stocks of those companies were plummeting. Never mind that, he said. He had just purchased, on behalf of his clients, oil futures. Instantly in his mind less supply of nuclear power equaled more demand for oil, and he was right. His investors made a large killing. Mine made a small killing. Minutes after I had persuaded a few clients to buy some oil, Alexander called back.

“Buy potatoes,” he said. “Gotta hop.” Then he hung up. Of course. A cloud of fallout would threaten European food and water supplies, including the potato crop, placing a premium on uncontaminated American substitutes. Perhaps a few folks other than potato farmers think of the price of potatoes in America minutes after the explosion of a nuclear reactor in Russian, but I have never met them.

But Chernobyl and oil are a comparatively straightforward example. There was a game we played called What if? All sorts of complications can be introduced into What if? Imagine, for example, you are an institutional investor managing several billion dollars. What if there is a massive earthquake in Tokyo? Tokyo is reduced to rubble. Investors in Japan panic. They are selling yen and trying to get their money out of the Japanese stock market. What do you do?

Well, along the lines of pattern number one, what Alexander would do is put money into Japan on the assumption that since everyone was trying to get out, there must be some bargains. He would buy precisely those securities in Japan that appeared the least desirable to others. First, the stocks of Japanese insurance companies. The world would probably assume that ordinary insurance companies had a great deal of exposure…]


Transcript

Intro

Kevin Muir, author of the Macro Tourist newsletter and a seasoned trader, joins The Intentional Investor for a fascinating conversation that weaves together trading, life lessons, and Canadian culture. From his early days mastering Monopoly statistics to pioneering computer-driven trading strategies at RBC in the 1990s, Kevin shares candid stories about finding his path in finance.

Kevin discusses growing up as the older brother of a professional hockey player, his journey from discount brokerage manager to institutional trading desk, and how becoming a father changed his perspective on risk and career. He offers unique insights into market psychology, friendship, and the importance of finding work you genuinely love.

Highlights include:

How Kevin combined computer skills with trading intuition to capitalize on market inefficiencies The story behind his decision to leave a successful banking career to trade independently His experience growing up in a family of traders and athletes Reflections on Canadian culture and the historic final Tragically Hip concert Wisdom on maintaining long-term friendships and finding your authentic path in finance

Whether you’re interested in markets, mentorship, or memorable stories from the trading floor, this conversation offers valuable perspectives on building a meaningful career while staying true to yourself.

Guest Introduction: Kevin Muir, The Macro Tourist

Matt Zeigler:

“Now in most cultures, the tourist is a thing to be mocked—the bad shirts, the bad taste in food, the cameras around the necks—and if you’re a local, the tourists are the people who are always in the way. And if you’re a trader, well, they’re the ones who are trying to give you a bad name. But this guest has made a career out of tourism, by which I mean he’s exploring areas that others might not, turning over all the rocks that are there in the name of finding opportunities. He’s a veritable Ferdinand Magellan of who’s buying and selling, a Christopher Columbus willing to back up his portfolio’s dump truck, a Marco Polo of the occasional crapco YOLO, the Jacques Cousteau of commitments of traders and fund flows, and the Amelia Earhart of the occasional gas gauge chart. Is that too soon? Mil, you can make jokes about her, right? He’s the master in the Market Huddle universe, a real He-Man, which maybe makes Patrick O’Shaughnessy Man-at-Arms—we’re going to have to ask him that question on another episode. The ‘everything is interesting’ purist, author of The Macro Tourist himself, promising a conversation that will not be the maturest. And no, I will not play him in ‘Birds for the Bill,’ at least not this time. Bring home the Canadian—let’s bring home the Canadian bacon with me now, the one and only Mr. Kevin Muir. Kev, man, listen, that was the best intro I have ever gotten.”

Kevin Muir:

“Like, nobody will ever be able to top that. As a person who regularly does fantastic intros on Market Huddle, let me say I’m taking the praise. I’m taking—I know that is awesome.”


The Story Behind “The Macro Tourist” Name

Matt Zeigler:

“And you know, you brought up the fact that the tourist is something that’s kind of viewed with a derogatory nature.”

Kevin Muir:

“And I remember when I first chose the name when I was writing my post, and people used to come to me and say, ‘You know, Macro Tourist, that’s actually like a bad thing, you know, like that’s an insult.’ And it’s like, ‘Yeah, of course I get it.’ It’s kind of a self-terror, like I’m making fun of myself, and that was the whole thing about it. And uh, and I laugh, and it just goes along with my um, my kind of motto, which is, ‘All I bring to the party is 25 years of mistakes.’ Now I have to update this because I started that a while ago.”

Matt Zeigler:

“It’s better if you don’t update the 25 years. I saw that and I went, ‘I think when I signed up for these newsletters 10 years ago—’”

Kevin Muir:

“Yeah, he was—you’re absolutely right.”

Matt Zeigler:

“No, but I’m still making mistakes, so that is the one thing I can assure you of.”

Kevin Muir:

“Well, may your 25 years be evergreen.”


FMK Game: Canadian Bands

Matt Zeigler:

“I’m starting here—I’m starting with a game, okay? I don’t know if this—I assume this game migrated to Canada at some point, or at least maybe your kids played it. Well, you don’t want to talk about this one with your kids. I’m going to use the PG-13 rating, which is FMK, or as my friend Raj Bennett likes to say, ‘make sweet love to, marry, kill.’ So have you ever played this game?”

Kevin Muir:

“Uh, make swe—choose one of those?”

Matt Zeigler:

“Well, you’re going to rank them on which one you’d make sweet love to, which one you’d marry, which one you’d kill.”

Kevin Muir:

“Oh, okay, let’s uh, let’s give this a whirl. So we’re gonna give this a whirl, okay? Make sweet love to, marry, kill: Rush, The Tragically Hip, and Bachman-Turner Overdrive. Okay, so I—I’m gonna be—I could be kicked out of Canada for this, but I’m not a Rush fan. And I know that like a lot of people—so I’m gonna put Rush in the kill. So then I’m stuck with—oh, and that’s easy because um, like, Tragically Hip is the greatest band that’s ever come out of Canada, so they’re going to be ‘make sweet love.’ And then I guess I have to marry BTO. I mean, which is kind of annoying because he is um, he—he’s like, he’s a lovely human, and he actually has a radio show that he does, really, on CBC.”

Matt Zeigler:

“Yeah, he has a radio show, and he—and it’s actually terrific to listen to ‘cause he’s really old, and so he’ll talk about like meeting the Beatles and then he’ll play little bits of the songs and stuff. So it’s a great—it’s a great show.”

Kevin Muir:

“But he is definitely um—I think he was kicked out of The Guess Who for being a little too Puritan. And uh, for those who don’t know, um, is it Bachman—I guess that’s his last name, I can’t remember his first name—but he was originally part of The Guess Who. And ironically enough, I was actually—I grew up in Winnipeg, and The Guess Who were from Winnipeg. And I remember—remember hearing my dad’s uh, friends tell stories about like these crazy parties they had and what The Guess Who guys did and like, ‘Oh, we trashed this house,’ and blah blah blah. It was some great kind of Winnipeg Guess Who stories.”

Matt Zeigler:

“And last Guess Who story—I, because I love telling this um, when they asked uh, who was it, uh, who’s the lead singer for um, the uh, Led Zeppelin? Is it Plant?”

Kevin Muir:

“Robert Plant.”

Matt Zeigler:

“Robert Plant, yeah. So they asked—they said, ‘Robert Plant, you have a terrific rock ‘n’ roll voice, you know, like it obviously does—one of the greatest singers of all time. But if you had to pick someone that you would want to sound like, like who would you pick?’ And he chose Burton Cummings from The Guess Who.”

Kevin Muir:

“That’s amazing.”

Matt Zeigler:

“Yeah, kind of interesting pick.”

Kevin Muir:

“There’s all those things because it’s one of those—there’s uh, you know, growing up on this side of the border in America, the weird things that get passed back and forth between our countries. Yeah, all trade commentary aside, like I’m in a trailer park in New Jersey on family vacations—you know, a condo, but it was a trailer park—and like the Canadian kids sliding me The Tragically Hip stuff, like mid-90s, around the side, and just being like, ‘This is amazing,’ and then nobody else caring.”

Matt Zeigler:

“Yeah, you know, they tried to make it big in the States. They got on Saturday Night Live, right? And live appearance. And you know what the problem was? If you go and you watch the documentary—there’s a great documentary for those converted. My wife—full fan now, thank you for that documentary.”

Kevin Muir:

“Well um, and for those who don’t know, The Tragically Hip are like a Canadian band that at their peak could have come to Toronto and sell out the Maple Leaf Gardens for like two weeks straight and yet would go to New York and have to play like a little 5,000-square—I mean a 5,000-person venue—because they couldn’t sell out the big arena. And not only that, all 5,000 were mostly Canadians that were living in New York, the ex-shows up.”

Matt Zeigler:

“And the—and the kind of crazy story about this is that the lead singer got diagnosed with this brain cancer, and instead of just kind of quietly going off and dealing with it, he announced it to the world and said about doing this one last tour in this one last concert. And listen, he didn’t—he could barely keep the lyrics straight. They had to put like uh, uh, the—in front of him through a prompter and stuff. So it was—it was just emotionally hard, you know, felt.”

Kevin Muir:

“And the last show, because they were from this place in Ontario called Kingston, the last show from Kingston was just broadcast throughout Canada. And I can tell you, there’s like—I can remember the periods, like points at which Canada shut down, like where there’d be nobody on the highway. And it was like, generally, like um, Olympic hockey games—like we had a big one against you guys where uh, Sidney Crosby scored the winner, and that was—I remember coming in, like the highways were empty, and we had to pull over to go watch the game. And this was another one where just the whole country stopped to watch this last concert from The Tragically Hip.”

Matt Zeigler:

“Where were you? Where did you watch?”

Kevin Muir:

“I watched it at the cottage. So I was uh, and a lot of people were kind of uh, in cottage country and doing it there. And I should have gone somewhere, and you know, I was tempted to go, but it was just so expensive that—to actually go to the concerts, it was—it was crazy. It’d be like if uh, you know, you got to go to the last taping of MASH or something, like—I don’t even know, like the Super Bowl.”

Matt Zeigler:

“When I—when I tell people, I would say it’s our Bruce Springsteen. So it’s a band, but it would be the same, like imagine G Downey—if he was still alive—would have a Bruce Springsteen level. Hopefully not the same plasticky face thing going on, but—well, New Jersey adjacent.”

Kevin Muir:

“Yeah, and well, I’m very happy to hear that you were a fan. And what—what was your favorite album or song?”

Matt Zeigler:

“So uh, I ended up with a soft spot for Road Apples.”

Kevin Muir:

“Oh yeah.”

Matt Zeigler:

“And like really getting into that, and then I’m trying to think—it was—I don’t know if I made a note of it—the one—it was the one that came in Henhouse, what came out in ‘9—”

Kevin Muir:

“Trouble at the Henhouse.”

Matt Zeigler:

“Trouble at the Henhouse was like the first—I had that one and the album before it were like the tape that the Canadian friends made to me.”

Kevin Muir:

“Okay.”

Matt Zeigler:

“And that was like two summers, and then I remember being like, ‘Oh,’ ‘cause it was in uh, ‘Breen’—one of the songs was in Brain Candy too, the Kids in the Hall movie.”

Kevin Muir:

“Oh, really? I—I felt like really cool that I got the—do you know what ‘road apple’ is, by the way?”

Matt Zeigler:

“Uh, I found out, thank you to the documentary, yes, finally. I never knew until—”

Kevin Muir:

“Yeah, so, and the funny part about that story is that um, they—The Tragically Hip had chosen this name for their album, and the American record company said, ‘That sounds way too Canadian, like it was like that’s just terrible name.’ And so they were like, ‘You know, F you,’ and they decided to, you know, go, ‘What about Road Apples?’ They thought there’s no way they’re going to accept Road Apples because, for those who don’t know, road apples are basically horse crap, like that’s on the side of the road. And they loved it, and they went with it. So it’s how very Canadian that one of the best albums of all time is named after horse manure.”

Matt Zeigler:

“It’s a beautiful—did they try to name an album that first and then like it got shot down, and then they brought it back down again?”

Kevin Muir:

“I thought it was the other way around. I thought they wanted to name it something, and then it was kind of their, you know—they had—I could be misr—everyone should watch the four-part documentary. I think it’s even better if you know nothing about them, meaning like—meaning I’m sure if you grew up on them, it’s extra exceptional, but if you know nothing about them, you will come out of it wanting to work your way through the entire catalog because it’s so beautiful.”

Matt Zeigler:

“Yeah, I can’t remember—it just felt like that was like that was one in their back pocket that when they called him on not being able to do the other, they were like, ‘How about this?’”

Kevin Muir:

“Right, waiting for this—they’d been waiting to call it Road Apples. It’s the joke with your friends that you’ve like, you’ve been saying for years, and now you’re like, ‘All right, let’s play the card.’”


Growing Up: Family and Early Interests

Matt Zeigler:

“Well, speaking of playing cards, take me all the way back. Mom and Dad—I’m just curious about both of them, what they did, and in particular, like, was Dad seriously trading—Vancouver penny stocks, is that right?”

Kevin Muir:

“You’re absolutely correct. So I grew up in a household um, as I mentioned, I’m from Winnipeg, and there was a company in Winnipeg called Richardson Greenshields, and the Richardson family are one of Canada’s kind of wealthy families, and they’d started the securities arm. And then my dad and mom were actually from Montreal, so they moved out to Winnipeg. My dad decided he was going to be a research analyst, and he eventually ended up being the research director, so that’s like the guy that has all the analysts working below him. Um, but I grew up listening to stories about all these crappy stocks that are just like—just—and for those who don’t know, like Toronto, and more so Vancouver back in the day, had all of these just promotional-type crazy um, mining speculations. And it’s—it’s subsequently no longer there, like because we haven’t had a real kind of resource bull market in a while, but just imagine kind of all your worst SPAC-type, you know, situations, like 2021, but for resources. And that’s what kind of crap that was going on. And I—I promised myself, I was like, ‘I don’t want to trade these things. This is not what—like I love trading.’ And I was always—I was always loving games. My dad laughs at me because he says, ‘I always knew you were going to be a trader because he says, like, you love games.’ Like, you know, even as a little boy, I’d bring them up Monopoly and play—I wanted to play Monopoly, I wanted to play this, whatever it was.”

Growing Up Studying Monopoly Statistics and Game Theory

Kevin Muir:

“And I remember my mom bought me this magazine that was uh, a science magazine, and in it, they had studied the different odds of uh, like the—the return profiles of all the different Monopoly properties.”

Matt Zeigler:

“Oh yeah.”

Kevin Muir:

“And then figured out like, you know, where it is. And so I—I remember I was like 10 or 11—I became obsessed with this because I realized, you know, ‘Oh no, New York, St. James, and all those—there’s such better value because of the—the minus-three card that puts you on them.’ And anyway, so I—I—I studied this, and it was always—my—my old man just laughs. He says, ‘I knew you were going to be a trader.’ Was like, ‘There was nothing else that you were going to do. It was always something you wanted to do, you studying the—the Monopoly table in the back of a magazine.’”

Matt Zeigler:

“Like, but that’s how you’re supposed to learn statistics and stuff, right?”

Kevin Muir:

“I loved it. It was just—this was an eye-opening, you know, experience for me. And then, you know, I went through my stage where I figured out counting cards, and then I was like, you know, flying out to—to um, Atlantic City overnight to—to try my hand as a card counter, which, you know, as I know now, it’s never going to work because the reality is your edge is so small, and you got to do it for so long, and uh, you know, it just ends up being a pain. But I—I had that stage. I had my horse-racing stage where I was like, you know, going to the horses to play the ponies.”

Matt Zeigler:

“Yeah, I got the systems in place and did like this.”

Kevin Muir:

“The only thing I didn’t ever do—and I kind of regret it now—is I never got into the poker because poker has a little—too old for it, and it came after me.”

Matt Zeigler:

“You missed the online poker window.”

Kevin Muir:

“Yeah, like I was already trading, and then once I figured out trading and—and did it, like I’m always kind of shocked at guys in our industry that are actually taking a risk that then want to go to like Las Vegas or wherever and gamble. And I’m like, ‘Why—why would you play that game?’”

Matt Zeigler:

“Yeah, well, first of all, the odds are terrible, but like, don’t you get enough? Like, isn’t there enough stimulus? Like, I don’t really get it. But like poker, at least I understand because there’s a little more mental parts of it, but like a lot of the just going and counting cards is—it’s—once you figure out the system, it’s just methodical and boring.”

Kevin Muir:

“All right, games—like top games besides—besides Monopoly and the stats—what are—what’s the board games in the house? What are the ones where you’re like, ‘I want to pull this off on family game night’?”

Matt Zeigler:

“Um, um, well, do you know—actually, I—we—I don’t play as—just like my gambling, when trading took over, I don’t play as many games.”

Kevin Muir:

“No, no, no, but back then—back then as a kid.”

Matt Zeigler:

“Oh, back then, um—but—but—but just as quick aside, my wife and I play uh, this game called Quirk. I don’t know if you know it. It’s like—it’s—you got to make like patterns, and it’s—it’s actually a terrific game, and my wife is better at it than me in some ways.”

Kevin Muir:

“Is it shapes or numbers or something?”

Matt Zeigler:

“Yeah, it’s shapes and colors, and then you make these different kind of things, and yeah, um, but my wife—I—I always laugh at because she’s—she’s very good at doing things with uh, letters and words. So when one day when we started playing Scrabble—like, we went out and played Scrabble—and uh, I’m terrible at words, like in terms of trying to figure out how to do this, I’m like, just doesn’t come to me. And she’s coming up with these great words, but I’m looking at the board, and I’m figuring out like, ‘Okay, I can block her here, I could do this,’ and I’m just applying like complete game strategy, like I’m not even thinking about the words, I am only, you know, blocking, tackling, and like just trying to do. And like, she looks at me, and she says, ‘You’re—you’re just playing to win.’ And I’m like, ‘What?’ Like, she’s like, ‘That’s—’ She was legitimately offended that I wasn’t trying to make the best words and that I was just playing to win.”

Kevin Muir:

“And then she said, ‘Well—’ She started to figure it out, and then—and then I never won again in Scrabble because she’s so good at it. But she was really upset that I was just using game theory. Um, in terms of going back then, Monopoly was my top game. Uh, eventually, I became a little bit of a Dungeons and Dragons geek, of course, like, you know, um, uh, what else did I like? Oh, then I went to university, and I figured out bridge and uh, Hearts. I started with Hearts, moved to Bridge, and uh, that was a big game for me for a while.”

Matt Zeigler:

“Dungeons and Dragons with the friends, like uh, quasi-Stranger Things going on in the neighborhood. What do we got here?”

Kevin Muir:

“I don’t even remember. I—I—I just remember buying all the books and just being fascinated by it and like having the—the different, you know, numbers, the 20-sided dice, and like—I—I can’t even remember what it was about, like it just seemed really cool at the time. That’s—you know, I was—I was—I was late maturing, meaning like I was like—everyone else was into girls, and I was still thinking about Dungeons and Dragons.”

Matt Zeigler:

“Okay, but then who—late maturing, yet learning to play bridge? Well, who was teaching you? You were fast-forward maturing in one category and late maturing in the other.”

Kevin Muir:

“You got it. I was like—I was just late. I was like—I was really, really short, like in—I can’t remember—I was 16. I learned in Winnipeg, you could learn to drive at 15 and a half, and I remember I was like—I think I was barely 5 feet tall and 16 or something, like I was really late. And one of my dad’s friends said, ‘I thought you had to be 12 to drive.’ That’s how young I looked.”

Matt Zeigler:

“This is great. You late maturing and early maturing—”

Kevin Muir:

“Yeah, at the same time is uh, is pretty funny.”

Siblings and Family Dynamics

Matt Zeigler:

“Okay, so the games are a big part of it. Now, is it just you—you got siblings, like who else is in the house with you?”

Kevin Muir:

“I actually have a younger brother and a younger sister.”

Matt Zeigler:

“Okay, oldest of three. We can go behind that. Uh, like big age gap, real deep?”

Kevin Muir:

“My brother’s three, and my sister’s eight.”

The Dog Story: Thumper’s Vacation Weight Gain

Matt Zeigler:

“Now I’m totally putting you on the spot with this one because I think I’ve been butchering this story from you for a while, okay? Uh, you guys had a dog growing up, or you had multiple dogs growing up?”

Kevin Muir:

“Yeah, we had different dogs, yeah.”

Matt Zeigler:

“You have some story—and I couldn’t find this in my notes, so maybe I have to edit this out—kinda scared that you got notes about all this.”

Kevin Muir:

“Oh yeah, I—notes about the important stuff, like this story.”

Matt Zeigler:

“Okay, which I feel like—I think this came from you, so you see if I’m wrong. Did you go on vacation and uh, the dog got like sent to be boarded somewhere, and the—the quality of the food—”

Kevin Muir:

“Oh yes, that is my story.”

Matt Zeigler:

“Is that your story? I’ve been telling the story—I’m shocked that you remember the story.”

Kevin Muir:

“I don’t remember it left such an impression. Please tell the story.”

Matt Zeigler:

“Well, you know, because I—I—I tell a lot of stories more than once. This is not one of those ones that I tell all the time, so this is a deep-cut catalog story. Um, yeah, so we had a Rottweiler growing up—very like good-natured Rottweiler. My dad traveled a lot, so he bought my—my mom this um, you know, big tough dog, but he was just the gentle soul. And he was tall—he wasn’t one of those, you know, short, squat ones. He was one of those tall Rottweilers.”

Kevin Muir:

“So, and he was—10 or 120 pounds, like he was a big muscle too.”

Matt Zeigler:

“Yeah, and it was just—that’s a scary—but he was the sweetest guy.”

Kevin Muir:

“Anyway, so my dad would buy cheap food and then just like leave it out for him, and he would eat whatever he wanted. And then we went on—I think we went on this vacation for like two weeks or a month, and uh, he asked—we boarded him, and the guy says, ‘Well, what do you do?’ And my dad says, ‘You—he just, you know, he self-feeds.’ And the guy’s like, ‘Okay.’ The trouble was that the guy gave him good food. And so this dog—Thumper, by the way, was his name—you know, we come back, and Thumper is like 25 pounds bigger ‘cause he’d been like, ‘Holy—I didn’t realize that there’s good food out there, like—what the heck happened to our dog?’”

Matt Zeigler:

“Oh, that’s funny. Oh, so he put on 25 pounds—was something—did you convert the food you get?”

Kevin Muir:

“I think we just put him back on the other food, and eventually it came off. Poor f—but he was a great dog, he really was.”

Matt Zeigler:

“Did you guys—was there always a dog in the house? Did we—”

Kevin Muir:

“Did we always have animals? And even like as—as young adults, as soon as we finished university, we all bought like animals right away. And like, at one point, before we had kids, my wife and I had two dogs and two cats. And I was like, ‘I’m never doing that again.’ I have a rule now—only one of each. There is a hard-and-fast rule, and I always tell people that, like, having two dogs—it sounds romantic, it sounds awesome, until you have it, and then like you have a little baby at home trying to sleep, and then all of a sudden the dogs start barking, you’re just like, ‘No.’ So I just do one of each. We’re very strict now.”

Matt Zeigler:

“I think I’ve cracked the code on it, on finally being accepting of having smaller dogs.”

Kevin Muir:

“Oh, have you?”

Matt Zeigler:

“Yeah, finally—I finally accepted this. But you grow up with big dogs?”

Kevin Muir:

“No, but that was the only ones that we were really around as—”

Matt Zeigler:

“Okay, we had—there was three boys in my house of not totally distant age, so we were a small herd of elephants, and my dad leaving an animal with Mom would not have been the right choice for the longevity of their marriage. So instead, it was opted of just forever promising eventually getting a dog—so we could develop a complex and then, you know, get older and get dogs later. But yeah, so do you have multiple dogs—is what you’re telling me—multiple small dogs?”

Kevin Muir:

“After—after a run here, my little guy who’s eight—we just got another small dog to go with him, and like, they’ve hit it off so far—so far, so good. Talk to me in three months, I might have changed my mind again. But it was one—what kind of dog is it?”

Matt Zeigler:

“You know, they’re—they’re little dogs. They don’t need another like m—you’re just like, ‘No, they’re just little.’ I’m not gonna tell you what kind—it’s little, you know. I’m assuming it’s white.”

Kevin Muir:

“Well, we got—we got one who’s basically too cute for his own good. He’s like a small Muppet of a dog, um, which is absolutely adorable. He’s—he’s Shih Tzu and Yorkie mix—Shorkie, I’ve been told.”

Matt Zeigler:

“And then even better name, because you can’t outdo that—we just rescued this other dog, and he is a part Chihuahua, part Dachshund, which is apparently called a Chiweenie, which is—”

Kevin Muir:

“Great marketing—great marketing.”

Matt Zeigler:

“Um, but the best part is, for a long time, I had a big dog and a little dog, and like the little dog would run between the big dog’s legs, and walking them both—it’s disaster. These two little guys just like bump into each other, and that’s the most of it. They curl up on the couch, they look all cute, and uh, there you go.”

Kevin Muir:

“And you can travel with them.”

Matt Zeigler:

“See, I—I—and I can throw them in the back of the car and go—great. So our joke is um, with my wife—we—so we had these two dogs, two cats. We eventually, you know, the two dogs pass away after 14, 15 years, and it’s time to get a new dog. And then—dogs that we had gotten previously were these like purebred Bearded Collies, and they were, you know, they were great dogs, and they were terrific. And then my wife says, ‘No, I don’t want—’ And it’s like a medium-sized dog. She says, ‘I want a small, non-shedding dog.’ So this is what she tells me. And she wants—she wants a small, non—dog, and we’re going to rescue it.”

Kevin Muir:

“Okay, so this—risky proposition.”

Matt Zeigler:

“Yeah, so we’re going, and we’re spending all this time trying to find this non—small shedding dog that we’re going to rescue. Then kind of six months, and I’m kind of like—because everyone wants that, so nobody’s going to like, you know, when you go to the thing, all it is—”

Kevin Muir:

“How dare you apply market-making tech frame of reference?”

Matt Zeigler:

“So well—no, but the thing is—so eventually though, she’s like looking through all these things, and she falls in love with these Newfoundlands. And like, a Newfoundland is like—like the exact opposite of what she wants.”

Kevin Muir:

“Yeah, it’s like the—and so I—my joke is—so we eventually went and rescued this Newf that’s been with us for—for years, and she’s terrific dog.”

Matt Zeigler:

“How big is—she’s—”

Kevin Muir:

“She’s a small Newf—she’s only 100 pounds—but um, the thing about it is, I said like, you know, ‘You—you wanted a small, non-shedding dog, and you ended up getting like a Newf.’ Is this how you uh, kinda, ‘You wanted a tall husband with a good set of hair, and you ended up with me?’ Because I was like, ‘How do we go from like the exact opposite, you know?’”

Matt Zeigler:

“You could play this spousal Scrabble card as many times as you want. Teeter on the edge here, man.”

Kevin Muir:

“Oh, it’s funny.”


Life in the Gifted Program and Being the “Non-Athletic” Brother

Matt Zeigler:

“Oh, well—so—so you grow up—thank you for sharing the dog story. I knew I had to try to find one if I could get there. The uh, like other interests—are you playing—you playing sports? You’re playing hockey as a kid? What are you—what are you—”

Kevin Muir:

“So, are you a sports guy at all? I am—I come from a sports family. I am—okay, so here, since you’re getting me to open up—so my brother was actually a very good athlete. He played professional hockey for a living. He won the Stanley Cup, and uh, so I grew up thinking I was terrible at sports ‘cause my brother was terrific at every sport he tried. He crushed me. He was taller, he was bigger, like he was better. It wasn’t even close. I literally grew up thinking I was the worst sports guy around.”

Matt Zeigler:

“I would go and people would say like, ‘Oh, do you—you want to play baseball?’ And I’d be like, ‘I’m not very good.’ And then I would go play with them—I go, ‘I’m not very good, but you’re terrible,’ like because I was so used to playing with the guy that was like, you know, just an unbelievable athlete. Um, but no, I did not play uh, you know, a lot of sports.”

Kevin Muir:

“The only thing I ended up being good at was I have a good sense of balance. So I was actually—even though I grew up in Winnipeg—we did a lot of water skiing at the cottage, and then eventually I picked up uh, downhill skiing as I got older, and that came very naturally and easy to me. And that’s kinda the sport I would probably say I have the natural affinity to.”

Matt Zeigler:

“Is this middle brother, youngest brother?”

Kevin Muir:

“Yeah, the middle one. So yeah, so extra pain because like—oh yeah, not only that, he was tall. As I told you, I was late maturing—I was short, like he—he was the same size as me even though he was three years younger, like we would play in house league hockey, and so I would be playing in my year, and he would be coming and playing up, like basically in my year as well, like—is that embarrassing or what?”

Matt Zeigler:

“So rough.”

Kevin Muir:

“And he was better than me, like—like—like not just was he in my league, he was better than me.”

Matt Zeigler:

“So were Mom or Dad athletes at all? There was like—”

Kevin Muir:

“My mom’s side had some like tennis players, and my dad was a good hockey player growing up, but not to that extent, like it was kinda—it was unexpected that he was so good. But my dad always tells the story—he says, ‘I put skates on him, and he just skated—it worked.’”

Matt Zeigler:

“Yeah, yeah, like he would go and—I remember—so we grew up in Winnipeg—really cold, outdoor rinks everywhere—he would go after school straight to the rink, then he would come home for dinner and then go back until like they turned off the lights at the—at the place. Like, so it was just hockey, hockey, hockey.”

Kevin Muir:

“So everyone always goes, you know, like, ‘Oh, you know, you must know a lot about hockey, you must like a lot of hockey.’ I said, ‘I have watched so much hockey, I—I have no interest, like zero, like I’m so done with hockey.’ Like, let’s put it this way—the other day, like last year when Edmonton did well—I think it was Edmonton, right? They were in the Stanley Cup Finals—and I was like, ‘Okay, I’m going to watch this. I got a Canadian team in the finals.’ And then I’m like looking at this um, this MC—I’m like, ‘Who is this McDavid guy? This guy can really play.’ That’s how I was—I was like, ‘This guy can really play hockey.’ I was like—I—you know, I saw him—I was good.”

Matt Zeigler:

“You check in once in a while.”

Kevin Muir:

“Yeah, see how the boys are doing—that’s it. Only if Canada goes far.”

Matt Zeigler:

“Who—who is the team? Like, who’s the household allegiance to?”

Kevin Muir:

“Uh, there really is none, like uh, ‘cause, you know, like my brother played for a million teams. We grew up with the Jets, but we kinda left. Toronto was an easy team to hate—they—they were like—had this terrible owner, like—I guess my dad’s a Montreal fan, but like realistically, there was really nobody that we just loved. And half the time, I would just sit there, you know, analyzing left-wing lock and playing the trap and look—these different systems—and we wouldn’t be caring about like who was—who was playing. We’d be like talking about, ‘Okay, this guy did this, this guy broke down here, you know, look—this guy’s plus-minus stuff,’ like—so it was very analytical, and so it did—it kinda took the fun out of uh, you know, rooting for a team.”

Matt Zeigler:

“So like watching hockey in your house is actually critical strategy—”

Kevin Muir:

“Yeah, like critical game analysis on like who’s setting stuff up and doing stuff.”

Matt Zeigler:

“Well, listen, my wife, you know, accuses me of this all the time. She’s like, ‘Why can’t you just enjoy things?’ Like, so I—I watched this video the other day of a guy that was talking about what makes a good story, and he was analyzing it, and it was just a fascinating video. And he was talking about the elements and how it works, and then he was talking about how he took his wife to Wonder Woman, and they came out of it, and she’s like, ‘What do you think?’ And he’s like—and he’s about to talk, and she’s like, ‘Shh, don’t say anything, don’t ruin it for me, don’t—don’t say anything, just don’t—just shut your mouth.’ And he’s like, ‘Okay.’ And he’s—and then she’s like—like an hour later, she’s like, ‘Okay, tell me what was wrong with the story.’ And when—when he told you, it was true—I was like, ‘Oh no, he’s right.’ It’s good as a movie—that was—that was a poorly written part that ended up ruining the whole thing.”

Kevin Muir:

“And this guy was just—he could only see things with a critical lens that way. And he says, ‘Yeah, if you wanted—like I get it—if you just want to enjoy the—the movie, then don’t think about these things. But if you’re somebody that enjoys, you know, or thinking about crafting stories, then these sorts of things are what you have to look at.’”

Matt Zeigler:

“Do you see a difference inside of that between like being an editor or a critic or something like that versus being a creator? I think about this even like with your own stuff, your own writing—how do you balance that? Because you need the critical eye, but then you also need the creative element that just is willing to put it on the page.”

Kevin Muir:

“Yeah, you have to go for it. There hits points where you just have to say, ‘Ah, you know what, it’s never going to be perfect.’ Um, and one of the big problems that I have sometimes is I—I sit there, and I have a post that’s three-quarters written, and I’m just like, ‘Oh, I gotta just make it perfect,’ or, ‘I gotta do this,’ you know, like—what’s the old line about, like, ‘Perfect is the enemy of good,’ or what is it—‘Perfect is the enemy of good enough,’ or whatever? There’s some—”

Matt Zeigler:

“‘Perfect is the enemy of good.’”

Kevin Muir:

“‘Don’t let perfect be the enemy of good,’ yeah. And so you really do, at a certain point, just need to go for it. And I—I highly recommend that—do your best, work hard, but then eventually just like throw it out there and see what happens, and then the next—move on to the next one.”

Matt Zeigler:

“Yeah, you know, and you never know what you have to say that somebody else is going to latch on to. How many times have you sent something out and thought like, ‘I don’t know about this one,’ and you got 100 responses versus something where you’re like, ‘This is the greatest thing ever,’ and it’s crickets, right?”

Kevin Muir:

“Oh, Matt, I can’t tell you—so people ask me this all the time. They’re like, um, ‘Can you predict the ones that are going to resonate with people?’ Um, and I’m always like, ‘No, I have no clue.’ Because there’s ones that I am so proud of that I feel like are so smart, and I’m like, ‘Wow, I nailed this. I’m like, this is so clever, this is so well-presented.’ And as you say—just crickets. And then other ones, I’m just like, ‘Okay,’ and I just whip it off, and then people are like, ‘Oh my God, that’s the most, you know, insightful thing ever.’ And I’m like, ‘What?’ Like—like even like the other day, I was on um, I was on Odd Lots, and I don’t want to like uh, name-drop or anything, but like the—the reality is that I’ve been wanting to be on Odd Lots forever, right? Like it—and by the way, I did a—I was too nervous, and I was like—it—I don’t usually get nervous, but I was nervous because it—I had built it up in my mind so much. Um, but the whole point about this was that—that was like a throwaway piece that I had written that I was like, ‘Oh, you know what, this is interesting, you know, the—the market’s really concentrated,’ and bla—I whipped off a piece—not a throwaway, but it wasn’t something I felt super passionate about. And like, Tracy, you know, emails me—she’s like, ‘Oh, I love this, like you want to come on, you know, talk about it?’ I’m like, ‘Uh, okay.’ Like—and I had to go learn about it and because I was prepping something I was, you know, felt strongly about that I—that I’d spent a long time thinking about. And so to that, you know, extent, I’m never sure about what’s going to take off and what’s going to be the—the ones that people gravitate towards.”

Matt Zeigler:

“And I think it’s hard to unpack the critical eyes of others. And I can only imagine, like, Tracy Alloway, you know, Joe Weisenthal—like they’ve trained the critical eye of like things that they think will work, right?”

Kevin Muir:

“Yes, so now you’re getting sucked up in the vacuum cleaner of—well, I think the—the reality is that they’re looking for stuff that’s outside the box, right? So they need something that not everyone’s talking about. So the more unusual it is, and—and just kinda by its very nature, they—they’ll want to be at the early stages of it. They’ll see something, and they’ll be like, ‘Okay, let’s talk about this before it becomes everyone’s talking about it.’ And so they look at it, and uh, and that’s why it was that um, point. But it was, as I said, it was not something I expected, like I thought we were going to talk about, you know, Fed balance sheet or, you know, something that was very common, and then she’s like, ‘No, let’s talk about stock market concentration.’ I was like, ‘Great—great, so excited to go pretend I did all the research that I actually need to—to not have a panic attack.’”


School Years: Gifted Program and Moving to Toronto

Matt Zeigler:

“But on the other side of that mic—all right, so what about—take me back to like in school. So aside from playing games, how good of a student are you? What—what are the report cards look like in middle school and high school for uh, for you?”

Kevin Muir:

“Really are just like uh, delving in there, like I feel like I’m on the therapist chair. Um, okay, so I—I was in the—the—the—the enriched or gifted program. So I went to a special school where it got—got sent off, and—and I was with the like—the geeks, like I was—Freaks and Geeks, that show, might as well be about me, like it’s—that’s what it was. And it was just—it was a very—it was a special program where people came from all across, you know, Winnipeg to go to this one class, and—and it was—it was the greatest thing ever, uh, you know, and I—my best friend to this day is still from there, and uh, I—I—I loved it, and it was so great. Um, but it—we were—we were definitely not cool.”

Matt Zeigler:

“Is this at all part of like reaction to his brother already taken off in sports at this point?”

Kevin Muir:

“He was already that way—it was—it was actually just that I—I wasn’t getting along at my—so I went to French immersion. My mom—like, my mom’s third language is English, like so uh, you know, and—and she—they thought it was important I learned French, so I went to French immersion. I wasn’t the greatest at French—I think it’s very difficult, um—so I was in a French immersion school in middle school, wasn’t going well, and then my—I was like, ‘Forget this, like, you know, this isn’t—this is for the birds.’ And so at that point, he decided, ‘Okay, let’s find something for him.’ And then he was like, ‘Okay, this is it—this is where the kid’s going to fit in.’ And uh, he put me there, and it was the greatest thing ever—changed, like it really did. I went from not enjoying school to absolutely loving it, and uh, it was—it was a great experience.”

Matt Zeigler:

“Okay, so in a school like that, it’s not just your standard fare stuff. You took some other weird classes there—had to be some like Greek mythology, some type of advanced statistics that you were like, ‘Oh my God, I love this thing,’ and now as an adult, you’re like, ‘Most people didn’t learn this thing, and I still care.’”

Kevin Muir:

“Um, yeah, so for me, it was even a little more complicated because unfortunately, in Winnipeg, you go to grade 12, and then when I got—my dad got the—the company moved to Toronto because Winnipeg is obviously not a very big financial mecca. And so they moved to Toronto and happened to move on my 12th year. So I didn’t graduate with my—with my class, and it was difficult—all as well—because not only was I going there, I would already done a lot of these programs. So I come to Ontario, and I come to Toronto, and I’m like, ‘I’ve already done all this.’ Like, I remember sitting in calculus class, and one of the girls that I was sitting beside, you know, what—test comes by, and after like halfway through the thing, and she looks at him, and like I got a good mark, and she’s like, ‘Thought you were failing.’ And I was like, ‘What do you mean?’ And she’s like, ‘I thought you were like—I like you—you seem to not pay any attention, and like you’re only here half the time.’ And like—and I’m like, ‘Well, I already did all this.’ And so it ended up being difficult, and uh, in terms of actual classes—was there something that inspired me? No, like there was just—it was standard, like, you know, calculus, physics, whatever. As I said, I was more into game theory, and there wasn’t really a lot of game theory-type, you know, courses in high school.”


Starting at Bank of Montreal and the Path to Institutional Trading

Matt Zeigler:

“So I go to school—I—I started a school out of like—called Western. I end up playing too much bridge. I come back—I’m going to U—I’m—transfer to U of—I’m there—I living in the fraternity. I’m not a fraternity guy, but I don’t know anyone, so I join a fraternity because like I’m, you know, I missed that whole first year of university ‘cause I switched universities. So I’m living in the fraternity—I—I—I try to start looking for part-time jobs. I get a job at what’s called Bank of Montreal InvestorLine, which is like their TD—like their um, discount stock brokerage. And so this is in 1989-90, and I don’t know if people remember—maybe it’s 91—no, no, it’s 90—and people remember, but there’s the ’87 crash, which was very, very traumatic, and there was actually another crash in ’89—there was another little crash in ’89—and so a lot of the um, people were very hesitant to uh, kinda expand because they were worried about this was going to happen again. So this was a big thing—this—this starting this discount stock brokerage—but they didn’t want to go and commit to people. So they got me to come and uh, like work after hours, and I would literally just answer phone calls and give people quotes, okay? Like, that’s like, you know, I’m 20 years old or whatever—19 years old—and I’m, you know, working from 4 to 8. And I was working, and then what happens is the market starts to get busier, and they say, ‘You know what, you want to work today, like the whole day—like 8 to 8?’ I go, ‘Sure.’ The thing about it is that they’re paying me like, in essence, cash, because they don’t want to put me on this, and they’re paying me too much, and I’m like sitting there working 12-hour days. Next thing I know, I’m not going to school, and I’m just working 12-hour days ‘cause this is awesome, like I’m making all this money. And they’re like, ‘Oh, eventually—’ I kinda, you know, six months or a year into this, they go, ‘We—wait, we gotta give you a job, like this is ridiculous.’ So I take a job, and then within six months, I’m running the desk, which is even more ridiculous.”

Kevin Muir:

“I’m like, literally—wa—wait, just to be clear, you’re answering calls—”

Matt Zeigler:

“Oh, taking orders—eventually taking orders. I get registered, yeah, yeah, just like retail—retail guys—ret—how do you go from that to desk?”

Kevin Muir:

“Well, no, the desk is on—it’s like—I mean, the desk there—like I’m just talking about—so they—they put me in charge of the like the—they call it a desk—it’s not really a desk—it’s just order desk—it’s a trading operation, sure. So they put me in charge, and I do that for like six months, and I’m like a level-five manager, and like—and I’m doing really well, and I’m trying to go to school at night, and I’m like, ‘Wait, like this isn’t what I—I don’t want to be a discount stock brokerage manager, like this isn’t what I signed up for.’ And like a complete buffoon, I get a job—I find somebody who—I know the woman that works there—one of her h—her husband knows somebody in Chicago, and I get a job in Chicago because this is what I always wanted to do, like I loved Market Wizards. This was basically my book—I wanted to be the next George Soros or Stanley Druckenmiller. And so a lot of these guys, like Paul Tudor Jones—he started in the pit. So I go to Chicago, and I hate it—I can’t stand it. It’s terrible. And you know, I love Chicago—I love the Chicago people, I love Chicago traders—I think they’re the greatest bunch of traders out there—but this just is not for me, like, you know, this is a lot of testosterone, like just running through the pits, and it’s just—you’re up there, and like I remember guys putting their hands up, and they couldn’t put them down ‘cause they’re so tightly, like they’re—they’re so tightly put in there.”

Matt Zeigler:

“And so I come back, and I get a job, and so my dad says, ‘Okay, this is what you’re going to do. You’re going to go and—listen, if anyone’s young and listening to this—to this story, if you managed to last this long, um, I’m going to give some life advice here that my dad gave me that I think is really, really important, okay? He says, ‘Okay, this is what you’re going to do. You’re going to find out the head traders at the banks you want to work for or the—the broker firms you want to work for, and you’re going to write a letter, and you’re going to send it to them, and then you’re going to follow up with a phone call in a week’s time because—don’t—this is back when you had the mail stuff.’ So I find the six or seven firms I want to work for, and it’s like RBC, TD—uh, not TD—the CIBC, Midland Walwyn, and Gordon Capital. Gordon Capital was the beans, man—like that’s the one I wanted to work for. Gordon Capital was the firm that had kinda created the bought deal, and they were just awesome. So I send off all my letters, and then uh, you know, it comes day for me to phone them. So I phone, and I start with the one I want to, you know, work on the most. So I start with Gordon Capital, and I remember this—the guy’s name was Howie. Howie is just a jerk—that’s why it’s always—it stole in my mind. So I phone up and go, ‘You know, can I speak to Howie?’ They’re like, ‘Howie pick up.’ And so he goes, ‘Howie here.’ I go, ‘Hi, Howie, it’s Kevin Muir, you know, I sent you a letter, blah blah blah.’ He goes, ‘What are you doing phoning me, kid?’ And he proceeds to yell at me for 20 seconds, tell me to f off, and hangs up on my face—like literally, that’s what he did, like that’s—that’s it.”

Kevin Muir:

“And I’m some 20-year-old kid—this has just happened to me—I like wanted to cry, like I—like I—I probably did cry if I’m being honest with it—I—and I—you know, so I’m like, ‘God, this is terrible—my dad gave me the worst advice ever.’ Um, so, you know, I stop, and then my dad comes home that night—he goes, ‘How—how’d it go?’ And I said, ‘Well, didn’t go well.’ I tell him the story about Howie, and he laughs—he thinks this is hilarious. And then he says, ‘Well, how did your next call go?’ And I said, ‘What do you mean, the next call? Nobody wants to hear from me.’ And he says, ‘This is what you’re going to do—you’re going to get back on the phone, and you’re going to phone the next call.’ And sure enough, my next one was at this firm called First Marathon, and it was a guy named Mike Wekerle, who ended up being one of Canada’s greatest block traders. Um, he was super kind to me—he was the opposite of Howie, you know, like—and that’s one of the things in life—you can choose to be an idiot and—and be forever immortalized as Howie the ass—”

Matt Zeigler:

“Can I say—yeah, you can say it.”

Kevin Muir:

“Yeah, okay—Howie the ass—you don’t—to make sweet, sweet love to—you can kill—or you could be the Mike Wekerle that’s, you know, was super kind to me and—and is forever going to be remembered. And you know, I was lucky enough to have Mike on my—on my show, and I was like, ‘Mike, you probably don’t remember this, but you were instrumental in giving me kinda the confidence to go and to keep going—going.’ And because you were just kind, and there’s—it cost you nothing to be kind, and like—anyways, um, so Mike was nice to me—obviously that didn’t go anywhere—but then the next firm I phone was RBC Dominion Securities—RBC, um, happens to have uh, a trader that is who eventually ends up being my boss—but he’s intense, and the guy that’s working for him has just quit because this trader is so intense. And this—this guy who ends up being my friend—you know, he’s only like five years older than me, but back then it feels like that five years is like a lot, right—uh, he says to me, he says, ‘Kev, there was guys better at trading, there was guys better at computers, but you were the best mix of both.’ And so he hires me on the desk. So I’m literally going straight onto the institutional equity desk, and I am doing all of the index trading and the basket trading for the greatest firm in Canada at the time—and it probably still is the greatest firm, but at the time, we were by far the best. And it was the—they were—it was so awesome because they were such an entrepreneurial bunch—they let you do things, they were so, you know, great—it was—it was so—it was such a great experience, and I just—I loved every minute of it, and I just—I used to love going to work, and it was just so exciting.”


Pioneering Computer Trading at RBC in the ‘90s

Matt Zeigler:

“And the long and short of it is that I—I remember talking to my big boss and saying, ‘You know, you want me to get my degree?’ ‘Cause you were asking about my degree. He go, ‘I don’t care if you get your degree.’ And so I got my degree—barely, like just barely—like I went to school at night while I was, you know, making all this money and doing well, um, and it was just—I got it just because I felt like if I didn’t have it, I would forever, you know, worry that I was like—I missed something. But I literally—I think I needed a 1.50 grade point average to—to pass, and I think I got a 1.50—like I think I did not—like you have to give me there—I did two decimal places—you didn’t have to round up—you didn’t mess—”

Kevin Muir:

“I did not waste any extra energy getting better marks than I needed, which is a thing of great beauty.”

Matt Zeigler:

“Perfectly executed.”

Kevin Muir:

“That’s right—perfectly executed.”

Matt Zeigler:

“This thing about the computers and the trading and the balance, like—were you aware that you could combine these two things in the way—like did you know this was a skill beforehand, or did you walk in on this and them going, ‘You possess a skill that now we suddenly value’?”

Kevin Muir:

“No—so a—a little bit of both. Um, I love computers, and I—you know, if people ask me, ‘If you hadn’t been doing trading, what would you have done?’ I definitely would have gone into computers. Um, I was lucky in that my father knew enough—like although he was in research and although he wasn’t on the trading desk, he knew enough that he would kinda talk to me about different traders. And so there was no doubt I was aware about the trend towards computers at this time, and uh, then I just took it and ran with it—like literally, we had um, so one of the things about our firm was that we were able to trade proprietary for the bank. So that was, in essence, I eventually joined a group that was—we just got a percentage of what we made. And I remember sitting there, and I figured out that, you know, all these computers that I had direct contact—or direct access to the exchange with—so that we could do baskets, I figured all they could also do interlisted arbitrage, like we could write programs to buy and sell when something got out of line between Canada versus US. And I—I’ll never forget sitting there writing it, and one of the guys—the—the—the head of like risk says, ‘What are you doing?’ And I said, ‘Well, I’m running this program to do this, blah blah blah.’ He goes, ‘I already got guys doing that, like why you bothering?’ Like he said that to me—he said, like, ‘Why you bothering?’ And this machine kinda within two years was making way more than any of those guys. And so it was—I was very fortunate to be at a place that had the technology that let me run with it at a time in history when my skill sets were perfectly aligned with what was happening in the markets, like, you know, 10 years earlier, it doesn’t—the computer skills don’t help as much.”

Matt Zeigler:

“Yeah, and 10 years after, it’s a totally different state because now there’s been a Kevin Muir at all the shops, like—”

Kevin Muir:

“Right—10 years later, it’s actually—you almost need to be a dedicated computer guy, like my—my seat at RBC ended up being the guy that’s in that uh, Flash Boys movie—I can’t remember what his name is there—like whoever it is that was like one of my—like one of my duties, and one of the things that guy was in that group and doing that thing. And so—but if you look at those guys, they were way more computer-oriented—they—they had already become like you needed to be a Waterloo or whatever, you know, like a math—like a true computer nerd as opposed to a trader who happens to be able to do computers, right? You needed that advanced computer science background—love—whatever—but you were in that window where it was like—like, ‘Sure, I can build this scale model with Legos.’”

Matt Zeigler:

“Exactly—nobody else is doing it.”

Kevin Muir:

“I—it was—it was wild, like there was times I—I still think back to that computer that we got going, and we were trading through a firm called ITG, which is a very big um, kinda direct shop that a lot of people use. And I remember our sales lady coming up to us and saying, ‘Uh, D—I just was in a meeting, and we were going through all the accounts for like the whole firm, and they said, “All right, can anyone guess what the number one account is this—this year—this month?” And everyone’s guessing like Fidelity and like CapOp and all these names, and they’re like, “Nope—RBCD’s machine number two.”’ We were literally the best client that ITG had one month—that’s how much business we were doing. And it was just like—the Americans didn’t understand that stuff was interlisted, and so we would sit there, and we would provide liquidity and just trade, like they would come for Research in Motion, and if you think about it, you guys were buyers because you love the story—or Nortel even—whatever—whatever it was, you guys were buyers, but the—the actual stock was all in Canada. So you got these kinda natural like sellings in one place, the buyings in the other place, and so there was literally periods where it just sat there—bing, bing, bing, bing—and like I was like—like I was scared at times that something was wrong because it was making so much money. I was like—because, you know, the one thing you do have to learn as a trader is if something seems too good to be true, it’s—it’s like, you’re like, ‘No, it’s definitely too good to be true.’”


Learning Hard Lessons About Market Traps and Trading Ethics

Matt Zeigler:

“Well, because I got a great story to tell you about that if you want, uh, about being too good to be true. So one time, this machine’s going—it’s doing all this money, making all this money—and then the—the main desk—like I’m on the derivatives desk, but the main desk trader comes up to me. He says, ‘Kev, I got this trader that’s like this hedge fund guy who’s willing to do this arbitrage—not arbitrage—he’s willing to trade with me on, you know, on—in Canada of this stock, and I could immediately sell it for a 10-cent profit in the US. I’ve done like, you know, quarter million—do you want to do some?’ And I’m like, ‘Okay, wait—so you’re telling me that this hedge fund guy is phoning you up and is wanting to do this trade that is very clearly an arb—like against him?’ He says, ‘Yeah.’ He said, ‘Whoa, whoa, whoa—hey, have you played Scrabble with my wife to be?’ I’m like, ‘Turn off the machine.’ I’m like, ‘Turn it off,’ like I—like I went and told the guys, ‘Turn off the stock,’ like it was this one stock. And I’m like, ‘I gotta figure out why,’ because I know that if this guy’s doing this, it is—there’s something there that I’m missing. And sure enough, it was trading with what’s known as a due bill in the States. So it looked like there was a dime profit, but there was really like a $1.50 or $2 loss, like occurring. And I remember the um, the sales guy coming up to me for that account and saying, ‘I’m so sorry that my client tried to pick you guys off.’ And I said, ‘Are you kidding me? It’s the greatest thing that ever happened. If he hadn’t picked me off, I would—if he had just done it in the machine, I wouldn’t have figured it out, and it might have been like days before,’ because the due bill doesn’t come for another few days. And once I figured it out, I very quickly could—you know, I might—I can’t remember how much we were at—I think we were at a couple hundred grand, but I think I made back like half of it arbing it the other way—putting it to the right price—like I was like, ‘Okay, okay, now we’re going to put this to the right price.’ And so I immediately unwound everything we had done and then did a little extra the other way. Um, but I remember the guy apologizing—I was like, ‘No, you don’t have anything to apologize for—this is the greatest thing ever.’ That guy hadn’t been so greedy and tried to do blocks, like—that was it—he was trying to do blocks.”

Kevin Muir:

“And I really don’t understand that guy because that was a dumb play in—in lots of different reasons. One of them was—you ultimately—you got found out quicker, but the other thing is that you were picking off your friends, like even though like you’re—they’re your brokers, like you’re—you’re talking to them, and you shouldn’t ever do that, like—and another quick story about this—like I remember um, one time we figured out there was something called the—the—an EFP, which is exchange for physical. So we were trading the index versus the futures, and so we figured out that there was a dividend everyone was missing on a big stock—like one—like Bell Canada or something—and it changed the EFP um, price significantly. And I remember going out there and like—let’s say it was trading like a dime to 15 cents, like a 10-cent bid, 15-cent offer—and it was all of a sudden worth a dollar. And I was like, ‘Holy smokes.’ And like Peter and my boss were like, ‘Let’s—let’s just get on the dime bid and see if anyone hits us.’ And I said, ‘No, no—let’s move it and let’s get some size,’ right? So I remember going out there, and we like go, ‘What’s the market?’ And they go, ‘10 to 15.’ I go, ‘Okay, bought from you at 15—I’m 15 bid—where does it come?’ And then someone sells us some at 20, and I go, ‘Bought from you at 20,’ and—what—and I start marching it up. And so like—I can’t remember—guys are selling me—like this is an EFP, so it’s like 5 million, 10 million. Finally, I move it up from like 20 to 50—50, okay—don’t forget, it’s worth a dollar in my books, okay? And my—my arch-nemesis at CIBC—he’s woken up to the fact that there’s—that I’m moving it, and he offers me size, and I’m like, ‘There it is.’ And I’m like, ‘Okay,’ like—I can’t remember—it’s 200 or something—it was a big number—and I was like, ‘Bought from you,’ and, ‘We’re bid,’ okay? And so—and then immediately I get a call overhead, and he’s like—it’s him—and he’s like, ‘Kev, you just lifted me on this EFP—what’s going on?’ And like, you know, I—at that point, I can do a lot of different things, but the right thing to do is like—I tell him—I don’t say to him, ‘Everything’s okay—sell me another 200.’ I say to him, ‘Go check your numbers,’ like I don’t—like—he—and he doesn’t ask to be let off of it, you know—he goes and checks his numbers, and then next thing I know, he’s 60 bid trying to get it back because he’s realized he’s screwed up.”

Matt Zeigler:

“Yeah, but the point is that—like guys that don’t behave honorably, like that—and like—are trying to pick guys off—it—it comes back to you, like it’s—it’s—it’s a small street. It’s that the guys, you know, try to be picking off clients, picking off their dealers, or picking off even each other—I—I never felt that that was fair, like if you were on the pit and you were trading, that’s fine—I had no problem with it—but if you’re going to fool me overhead, I’m not going to like, you know, try to pick you off to your face.”


Meeting His Wife at a Fraternity Party

Matt Zeigler: Where did you meet your wife? Did you meet her in school? I know I met my wife at a fraternity party.

Kevin: Okay, frat boy Kevin! Yeah, I met my wife at a fraternity party. Funny enough, I was working at the time and financing all of our kegs. I was the only one who could afford the deposit—$5,000 or $3,000, whatever it was. You had to put the deposit down on the kegs, and our fraternity was terrible at keeping track of things. So I was like, “Okay, fine, I’ll finance the stupid things.”

Matt Zeigler: So your wife comes to one of these keg parties that you’re self-financing with your stockbroker job?

Kevin: Yes, that’s correct. We hit it off immediately.

Matt Zeigler: Did you know right away?

Kevin: Yeah, we hit it off, and that was it. It’s been a while—lots of good years. A lot of good Scrabble, not too much scrabbling on occasion!


Starting a Family and Career Progression

Matt Zeigler: Fast forward a bit—when do you start having kids? Is that once you’re in the prop trading job? How far along into the role do you start expanding the family?

Kevin: So, I get my job at RBC when I’m 23. By 26, I’m fully into equity derivatives, in charge of all the risk. Probably from 26 to 27 or so, my wife’s sitting there saying, “I want to travel,” and I’m like, “I can’t travel.” She’s like, “Well, I’m not going to just sit here.” I’d started making some money, and she’s like, “Why am I working?” She was at Talstar or something and said, “I’m quitting.” I was like, “Okay.” She goes off traveling with my little sister—to Nepal, Tibet, all these places.

I’ve got a funny story about that. She goes to Nepal because of Seven Years in Tibet, the Brad Pitt movie. This is during either the Long-Term Capital crisis or the Asian financial crisis—I can’t remember which. She’s trekking from monastery to monastery, hasn’t slept in a decent bed, and finally gets on a plane to Thailand. She gets off, hasn’t booked anywhere to stay, and says to the taxi driver, “Take me to your best hotel.” She’s a low-key person, but she was just so sick of roughing it. She phones me—this is the ‘90s, when calling wasn’t easy—and says, “I don’t know where I am. I’m in the fanciest hotel in Thailand. It’s 8,000 baht or something, I don’t know what’s going on.” I’m sitting there thinking, “Oh my God, what has she done? This bill’s going to be brutal.” But it’s during the Asian crisis, so it ends up being like $210—or even less. Nothing!

Anyway, we have our first kid when I’m 29. I’d been at RBC for six years or so. At that point, the bank was slowly overtaking the dealer. It started as an entrepreneurial place, but over time, the bank got more involved. Rightfully so—I look back at some of the stuff we were doing, and I’m like, “I’d never let some 27-year-old punk do this.” It was irresponsible. We made tons of money, and it was fun, but I wasn’t mature enough to realize that was a unique time, not how life always works.


Challenges at RBC and Quitting

Kevin: The bank starts creeping in, telling me, “You can’t trade this, you can’t trade that.” I’m getting in trouble—“Kev, you can’t do this.” Then we have our daughter. She’s born with a heart defect, corrected at birth, but it was a very emotional time for me. It was like a near-death experience—not that I died, but it hit me hard. I never felt the same way about work after that. A couple of other things made it less fun too. Three months after she’s born, we have our best quarter ever, and I think, “I’m going to be like Michael Jordan—sink the basket and walk away.” So I quit.

At the time, I didn’t know what I’d do next. I hadn’t made enough to never work again, but enough to not worry about the next year. I thought, “I could work for a hedge fund, but I don’t want to do sell-side again for a while.” If I worked at a hedge fund for a year and quit, people would remember me as the schmuck who lasted a year. But if I tried something on my own for a year and then went to a hedge fund, no one would care about that year. So I started trading for myself. Eventually, another guy from my old shop joined me, and that was it. Along the way, I started writing the letter and doing the podcast.

One thing I laugh about—I’ve never really had a steady paycheck. Even at RBC, it was a small draw, and it’s been “eat what you kill” for the last 35 years.

Matt Zeigler: When you tell your wife you’re leaving the job—obviously after the scary moment with your daughter’s heart defect—are you both freaked out about it?

Kevin: She was more worried about the child. She’s always been supportive. I never felt tension about it. She wasn’t like, “No, stay!” She’s not a fan of the Bay Street douchebags—our version of Wall Street. When we meet some larger-than-life trader guy trying to impress her by being brash, I’m like, “That’s not going to work with her.”


Building The Macro Tourist Community

Matt Zeigler: That commitment to figuring things out for the right reasons ties into the community you’ve built with The Macro Tourist. I love the letter—not just for the memes, though I come back for those. Where can people find you if they want to learn more?

Kevin: Go to themacrotourist.com. If you want samples, email me at kevin@themacrotourist.com—I’ll send them off. Also, join our chat—it’s easy to find, with lots of smart people. I’m proud of how it’s taken off. Twitter got mean and unfriendly, and when I got frustrated with Elon, I committed to Substack. The chat’s been a great surprise.

Matt Zeigler: Between the Market Huddle podcast and the letter, you’ve built a real community. I love those summer emails with chat highlights—it’s my favorite thing in my inbox.

Kevin: Glad you like that! It’s a real community, and that’s rare. Thanks for being part of it.


Reflections on Trading and Life

Matt Zeigler: Does it bother you that there aren’t monocultural moments like The Tragically Hip’s last concert for your daughter?

Kevin: That wasn’t that long ago—she remembers it. I’m not fussed. I think there’ll be moments like that for her and my other kids—different, but they’ll happen. Humans haven’t changed.

Matt Zeigler: Here’s a trading aside—people romanticize the past, thinking it was easy to make money.

Kevin: Exactly.

“I tell people my story, and I always say, ‘Oh, I would have made so much money back then; it was so easy.’ And everyone always thinks it was so easy. But I always tell them, ‘Listen, it wasn’t easy.’ Right now, there’s somebody who is quietly making a fortune, someone who has figured out the equivalent of my interlisted arbitrage. When I was doing my interlisted arbitrage on my machine, I wasn’t telling everyone—I was quiet about it. There’s somebody somewhere doing the exact same thing.

“There are always people making money, and it’s always hard. I remember thinking specifically, when I would listen to their stories—like the trader above me, 5 or 10 years older than me—I’d think, ‘If I had just been there when 87 happened, if I had just been there then…’ People always look back on the past, over-romanticizing it.”

Matt Zeigler: Tell the Norwegian art story—it relates to this.

Kevin:

I’ll quickly go through it. For those who don’t know, in the late ’60s and early ’70s, I believe, Norway discovered oil off their coast. It was this huge boom, and everyone was rushing out to get blocks of water they could drill in. There was an enormous fortune to be made with this Norwegian offshore oil boom. For those who don’t know, we think of Norway as a very rich country now, but up until that point, it wasn’t. It was actually the poorer of the Scandinavian countries, mostly reliant on fishing—not a lot was going on in Norway. So, they discovered this oil, and the long and short of it is that all these guys were rushing out to buy pieces of this water to drill in.

Then there’s this trader who looks at the situation and says, ‘Okay, that’s getting fully priced in. What can I do?’ He decides to start accumulating Norwegian art. He just starts buying all this art, and you might think, ‘What kind of crazy guy is this? Why is he buying Norwegian art?’ The long and short of it is that he had figured out that once all these guys made their fortune from the offshore oil, they’d be looking for something to do with their money. Art is a very local market, and when a Norwegian guy makes some money, yes, he might go buy a Picasso, but he’s also suddenly going to want Norwegian art. So, while everyone was busy fighting and paying too much for this offshore oil, this guy was quietly accumulating Norwegian art. A year or two later, when all these newly rich guys started looking to spend their money, he was there with offerings for them and made a fortune that way.

To me, that epitomizes trading. What’s interesting is if you go back and read Liar’s Poker again, you’ll see Michael Lewis talks about two guys who were his mentors. One of them is this guy, Dash Riprock, I think, who sits around watching for a bond to be, say, 30 seconds too expensive, and then he arbitrages it. He’s kind of a block-and-tackle kind of guy—just straightforward. But then there’s this other guy, this big, bold trader. If you reread that section, Lewis describes how, when something happens, this trader is already onto the next iteration, trying to figure out, ‘Okay, this is occurring—what’s the next step?’ Instead of just focusing on the first derivative, he goes for the second derivative. In other words, he thinks, ‘Once everyone does this, what’s that going to mean for the next thing?’ It’s like thinking multiple moves ahead in chess.


The Importance of Finding What You Truly Love in Markets

Matt Zeigler: You’ve talked about trying things—like going to Chicago, thinking it’d be great, then hating it.

Kevin: Yeah, I thought it’d be the greatest thing ever, but it wasn’t. We tell our kids, “Don’t fuss—you’ll figure it out.” I saw guys at RBC try trading, hate it, and go back to research. You’ve got to find what matches you. This industry attracts a lot of people, but you better love it—not just do it for the money. You can hear it in their voice when they truly love markets.

4 Observations from George Lucas’ Career

I listened to Founder’s podcast episode #345 about the life of George Lucas.

The following is the 4 points I want to save:

A movement coming from the fringe

This excerpts remind me of

  1. Paul Graham’s essay The Power Of The Marginal
  2. The importance of finding the people who inspire you via Bill Gurley’s Running Down A Dream speech

Keep in mind, this is the mid-1960s. There’s not many film schools in the United States. And so this is why Tarantino last week in his book would talk about the movie brats. He said they love movies, they dreamed of movies, and they even received degrees in movies back when that was a dubious major. And Lucas talks about this like it was embarrassing. Other people were like, you’re going to a film school, they didn’t even call it a film school, they call it cinematography school. “Like what the hell is this?” and he says, “I lost a lot of face.”The idea of going into film was a really goofy idea at the time. His dad’s like “there’s no way in hell, I’m playing for art school”. 

That decision changed the trajectory of George Lucas’ life is because that’s when he meets essentially just a collection of filmmakers who are all obsessed with movies, they’re all young, and they wind up helping each other for decades. It’s almost like the island of misfit toys because before this, it says, for many of them, it was the first time they had a click of their own, a gathering place where they could talk about their interest, movies without eye rolling from the other cool kids. For many reality finally began when they entered film school.

Lucas knew that he had found his way. Before he wasn’t sure, obviously in the college he had all these other interests. And he’s like, “Oh, wait, this is it.” I was sort of floundering for something. “And when I finally discovered film, I really fell madly in love with it. I ate it. I slept it 24 hours a day. There was no going back after that.” 

Steven Spielberg describes, he uses the exact same language. This is what Spielberg said, “Making movies grows on you. You can’t shake it. I like directing above all. All I know for sure is I’ve gone too far to back out now. There is no going back.” They both discovered what they’re going to do.

Now this is the fascinating part because this turns into the USC Mafia, Spielberg is part of that, even though he didn’t go to USC. You’re talking about a group of super talented filmmakers and a lot of them come out to California, even though they called the USC Mafia, some of them like Martin Scorsese, Oliver Stone, they went to NYU, Brian De Palma went to Colombia. Francis Ford Coppola was at UCLA, Spielberg is on the lot getting his own curriculum at Universal.

They were all friends who would have a lasting impact on film and culture. This is another example that relationships around the world. You see it over and over again in these books, so important to develop relationships with other people that are just like you and even if you’re — they don’t look at themselves as competitors. They tend to compete, but they also collaborate, but they all need each other because they’re trying to break into a system that is closed.

At this point in history, unless you’re part of a union, unless you already know somebody in the industry, you’re not breaking it even with a film degree. It’s yet another illustration of one of my favorite concepts from Game of Thrones, where they said those on the margins often come to control the center. At this time, Spielberg, Scorsese, De Palma, Coppola, Lucas, they are on the margin.

The center is controlled by these old school conservative studios that are locking all these young people out. It was unheard of to have a director in their 20s. And yet this network that they’re building and the talent that they have for their craft, like those on the margins often come to control the center. They become the center.

Now this is really fascinating because when I had dinner with Charlie Munger, this is the advice that he gave us. He talked about is exactly what him and Buffett did. I think he was 35 when he met Buffett, Buffett was about 28, 29 something like that. Each talked over and over again, the importance of — the advice he gave was like you have to develop relationships with people. He’s like, they were still doing deals. He talked about the fact that they would meet people in their 20s, 30s and 40s, and they would do business and do deals for the rest of their lives. The USC Mafia would regularly hire, fire and conspire with one another on countless projects over the next five decades, putting together a kind of system of their own. Lucas is 23 when he meets Coppola. Coppola is 28. They’re going to be making movies doing deals, starting companies, breaking up, fighting for decades.

It’s really important because at that time, because there is no young directors. There’s no 28-year-old director doing a major movie set. You have to be an independent filmmaker to do that. And so Coppola inspires not just Lucas, he inspires Steven Spielberg too. 

Coppola actually succeeded in getting his hand on the door knob and flinging open the door. And suddenly, there was a crack of light. And you could see that one of us, a film student, without any connections had put one foot in front of the other and actually made the transition from being a film student to being somebody who made a feature film sponsored by one of the studios.

To Steven Spielberg, Coppola was a shining star. Spielberg said, Francis was the first inspiration to a lot of young filmmakers because he broke through before many others. So not only did Coppola proved to Spielberg and Lucas that, “Hey, this is possible.”

But the influence that Coppola had on Lucas too is like, “Listen, you have to learn to write.” At this time, and you’ll see Lucas make this mistake a few times. He tries to outsource the writing. And Coppola was saying, “Hey, what separates just a director to a filmmaker is like you have to — any director, he would tell Lucas like any great director has to know how to put together a screenplay. And so he would repeat to Lucas over and over again like no one’s going to take you seriously unless you write. And that wind up being excellent advice because Lucas forced himself to write Star Wars, which is obviously his entire empire.

I’d be working all day and all night living on chocolate bars and coffee, said Lucas. It was a great life. I had enthusiasm, and I was too busy to get into drugs. Movies where his addiction, we were passionate about movies. “We were always scrambling to get our next fix.” Listen to how they’re describing this. This is how he knew what he’s been doing with their life. Described working as your next fix to get a little film in the camera and shoot something.

Spielberg has said multiple times that George Lucas inspired him and said at the time of his first encounter with Lucas in early 1968, Spielberg’s filmmaking was still more aspiring than actual. And Spielberg talked about this, like no longer did his role models have to be these older, in many cases, deceased filmmakers. They’re actually someone his own age, someone I can actually get to know, compete with and draw inspiration from.

“Surf the wave when it comes”

The next year, the film Easy Rider comes out. It is written and directed by a 32-year-old or a 33-year-old Dennis Hopper. It was not made in Hollywood. It was made on a shoestring budget. They raised $350,000. Why is that important? $350,000 is released in theaters. The film makes $60 million. Easy Rider goes on to be one of the most profitable films ever made.

And so the studio executives see them and they’re like, “Oh, s***”, and this is what they said. The studio smelled money. Why invest millions bank rolling production of an enormous film on a studio backlot when you can simply distribute independently produced films. Suddenly, independent films and independent filmmakers, which is exactly what Lucas and Coppola want to be, were in demand. The studio wanted young talent.

I just said that Charlie Munger talks about  surfing the wave.

Listen to the words that they use to describe this.

Easy Rider had created a tsunami of independent enthusiasm. Coppola decided to ride the wave right into the offices of Warner Bros. Come on, that fit together so perfectly there. So goes with Warner Bros.

This is Coppola who’s like — sometimes I think you might need a guy like this because it’s not like we’re going to make one movie.

He is like, listen, you front us a bunch of money. We’re going to bring you a finished film just like Easy Rider did. We’re not going to do with this once. We’re going to — we have seven films we want to make with you guys. We have seven films we want to make with you guys.

They’re young entrepreneurs, don’t have experience, don’t really know what they’re doing. The movies they’re going to make are going to flop. But what’s fascinating is like they still had an insight into the future. And so it says both Coppola and Lucas predicted a bold high-tech future. Remember, this is 1969, 1970, maybe. And they said movies will eventually be sold like soup. What does that mean? You’ll be able to buy it in cartridges for $3 and play it as you would a record, music record at home. He’s predicting VHS tapes, then DVDs, then Blu-ray and now streaming.

Forgiveness not permission

This is more juvenile delinquent behavior. He says the rules are of no concern to him. I broke them all. He said, “Whenever I broke the rules, I made a good film”, so there wasn’t much that the faculty could do about it.

George Lucas is very resourceful.  He always would find a way to get what he needed in terms of equipment and bodies to put together a crew like sometimes when you film like when you film Star Wars in London later on, they have these like really strict rules for the London like Film Union. You have to start at 8:30. There has to be a tea and I’m not even joking about this. You have to start 8:30, then you have to break for tea at 10 a.m., and then you have to break for an hour lunch at 1:00 and then you need another tea break at 4:00 and then you can’t work past 6. He’s like this is madness.

He didn’t want any kind of restrictions. So they would break into the equipment room to get not only materials that they needed, like an expensive camera, but they would also break into facilities. It says Lucas didn’t want to limit his use of the equipment to the building’s regular hours either. We’d shimmy up the drain spout, cross over the roof, jump into the patio and break into the editing rooms so we could work all weekend. And this idea that you use juvenile delinquent actions to actually be more productive.

Entrepreneurship is problem-solving

Tarantino in his book, he says, the job of a director is to solve problems. Solve problems for your actors. And I read this book by Danny Meyer, the famous restaurateur called Setting the Table. It’s excellent. And he tells a story that I’ve never forgotten. He’s at dinner with Stanley Marcus, who is part of the Neiman Marcus family, the family that controls the Neiman Marcus. He’s a wiser older man, probably, I would guess, 40 years older than Danny at this point. I think Danny’s in like mid-20s, maybe late 20s at this point. And so he’s — they’re having this conversation:

Danny says:

“Opening this new restaurant might be the worst mistake I’ve ever made.”

Stanley set his martini down, look me in the eye and said, so you made a mistake. You need to understand something important and listen to me carefully. The road to success is paved with mistakes well handled. His words remain with me throughout the night. I repeated them over and over to myself and it led to a turning point in the way I approached my business.

Stanley’s a lesson reminded me of something that my grandfather had always told me. He said the definition of business is problems. His philosophy came down to a simple fact of business. Success lies not in the elimination of problems, but in the art of creative, profitable problem solving. The best companies are those that distinguish themselves by solving problems most effectively.

The way I condense that down so I can remember myself, business is problems. Therefore, the best companies are just effective problem-solving machines. The best directors are just effective problem-solving machines.

Lucas has a problem. He’s got an idea in his head. No one can make the special effects. There’s no technology at the time. So what did he do? The solution sometimes to a problem is to found your own company to solve that problem. The solution to this problem that he’s having now is the founding of Industrial Light & Magic.

So it says Lucas would not merely have to produce the visual effects. He would have to develop the technology needed to shoot them in the first place. George was absolutely adamant that he wanted to set up his own shop with his own people. Industrial Light & Magic would then be an official subsidiary of Lucasfilm, born of necessity seeded with his own money and feeding off Lucas’ need to control every aspect of the production.

Industrial Light & Magic would stand as one of the cornerstones of Lucasfilm’s empire, an investment that would set him well on the way to becoming a multibillionaire.

Ron Howard admiringly said:

How many people think of the solution of gaining quality control, improving fiscal responsibility, and stimulating technological innovation is to start their own special effects company. 

Lessons From Ed Thorp’s Interview With Tim Ferriss

Episode link: https://www.youtube.com/watch?v=CNvz91Jyzbg&ab_channel=TimFerriss

This is not a summary but just a selection of excerpts I want to preserve.


You’re teaching a class of the neophytes how to invest? And some are, say mathematically inclined, and some are not. It’s a very mixed group. What types of tools or thinking frameworks, heuristics, mental models? Anything would would you focus on in the first handful of of lectures?

The first thing I tell them is, the answer is really easy for almost everybody. But you’re not going to believe me until you work through it yourself and understand it. I’ll tell you the answer to start with, and then I’ll try to convince you that it’s the right answer.

So, the answer is, if you’re a long-term investor, you should just buy and hold equities. The best place to have equities has been the US for the last couple of 100 years. Overall, equities here have compounded about 10, or 10 and a half percent for 200 years. The data for the first hundred years is not as good as the data for the last 100. But the data for the last century is quite good and very well documented.

How does that do against everybody else? Well, you can prove by logical mathematical arguments. I won’t go into all the details here. Some of it’s in my book, it’s also in other places, you can prove that if a person simply buys the index and holds it, they will outperform most all other players. The people who buy and hold the index will beat the whole collection of people who don’t do that. They do way better, on average, the ones who don’t do that pay trading costs. They have more volatility from lack of diversification. They often pay investment advisors, and all this and they also pay taxes when they trade. So the upshot is that you might make 10 and a half percent. If you don’t pay all these people, you might make eight, or seven or 6% to pay the crowd of people waiting to, quote, help you unquote. So that’s the simple answer for people who don’t know anything about investing.

Now, you might say, Well, yeah, but I’m pretty smart. I hear all these stories. I listen to Cramer on TV who jumps around, makes loud noise, and sounds good. So why can’t I do better?

Well, the academics have something called the efficient market theory in which they claim that you can’t do better. Now, I’ve already explained that that’s wrong, you can find instances where you can do better. Warren Buffett’s company did much better. I found with my hedge fund, I could do much better. But the kind of work you have to put in to do much better is substantial. It doesn’t seem like it at first. But when you get into it, there are all kinds of details and follow-ups and things to be checked out. And you end up spending a substantial amount of time and energy, figuring out how to do it better. And for everybody who finds out how to do better, the rest of the crowd who isn’t buying the index is doing a little bit worse, because you can show that the whole collection of people who don’t buy the index, or themselves as a group, is like the index. You subtract the index part out, and the rest is like the index too. So the people who aren’t buying the index that are like the index, as a group, are busy paying all these costs, taxes, investment advisors, and so forth. So on average, that whole group does worse. So you’re starting, you’re paying basically, casino vigorish, or whatever, if you’re not indexing, and you got to beat that, in order to do better than the indexes. And obviously, the group can’t beat that. So it’s only a small collection of people, some by luck, and some by skill will end up doing better. So you’re basically betting against the odds if you just invest by stories, and invest in various mutual funds that are actively managed, and so forth. So that’s what I would tell people.

Now, on the other side of the coin, if you really are interested in investing, it’s worth educating yourself and trying to do it, because you will learn a lot about investing, you might actually find a way to win. And you’ll learn about how the world works and a lot about life too. The things you learn from what seems like a narrow, specialized field, generalize very widely to all kinds of things. If you’re the kind of person who can take a lesson in one part of life and transport it to another part of life.

What are some of those transferable lessons in your mind?

Let’s take investment risk as a good example. You learn about how you minimize great risks. This is because significant investment risks can remove you from the game altogether. You might have an opportunity where you multiply your money by ten times, but you might also lose it all. Highly volatile things, like buying cryptocurrency, fall into this category. You may have the chance for a large gain, but also the risk of a significant loss. If you lose most of your capital, it’s challenging to recover. For instance, if you lose 90% of your capital, you’ve got to multiply what’s left by ten to break even, which means you’ve got to make a 900% return to offset that 90% loss. It’s not easy and takes a long time. So, you want to avoid really bad outcomes.

I applied this, for example, to COVID. I thought about what to do and how to deal with it. The early 2020 stats showed that people 85 and up, particularly males, had an 18% death rate if they contracted it. Even now, the death rate is very high for those who get it. If they’re unvaccinated, it’s probably close to that, and if they’re vaccinated, it’s maybe a tenth of that. So, I consider that a risk that could take me out of the game. It was a fairly high probability, so I’m going to avoid getting COVID if I possibly can. I’m going to mask up, avoid crowds, and think about the risks of various activities that I do and decide whether it’s worth it. So, I did my own analysis of COVID and its risks and tried to be very careful from then on. I think it’s paid off for me and my family. I’ve passed this information on to people around me.

On thinking for yourself

You won’t adhere to something unless you understand it yourself. There’s an old saying, “Give a person a fish, and they eat for a day, teach a person to fish and they eat for a lifetime.” The same applies to thinking. If you give somebody advice about a problem, they might solve that one problem. If you teach them how to think about problems, they can solve problems for the rest of their life. Also, if you give them advice, and they don’t understand what the advice is, or how to think about it, there’s a good chance they won’t take the advice.

A brutal example of someone not thinking for themselves

Back in 1991, I was invited to review the portfolio of McKinsey and Company in New York. They had a profit-sharing and a pension plan. I looked at all the things they had and they were quite good. But there was one very strange investment that yielded one or 2% a month, every month, for years. I asked, “How do they do this?” They said they didn’t know exactly, but they showed me their accounts.

I saw that this account had stock and put option positions with calls. Collars. They had a put option a little below the stock price, and they bought a call option a little bit above. The two things paid for themselves, so it seemed like they didn’t have a lot of risk. But I could show that in a down market, they would lose and in an up month, they would win. They won every month because a mysterious trade was put on involving S&P index options, and it was always in the right direction.

So, I said this is not possible. I wanted to go over and look at this place. They called the person in charge, Peter Madoff, the brother of Bernie Madoff. Bernie was off in Europe raising money. This was 1991. When Peter Madoff heard I was coming, he said, “No, I won’t let him in the front door.”

I decided to take a better look at all their trades. I saw that half the trades never happened when I researched them. That is, there were no trades occurred on any exchange at the prices they were making them out for these options. Another quarter of the trades had so much volume, that the volume couldn’t have happened because there wasn’t that much volume on the exchanges where they traded. The last quarter of the trades didn’t happen anywhere. There was no explanation.

So, I decided to look at some of the trades that actually could have happened. I went to a vice president of Bear Stearns and asked him to research 10 options trades. I wanted to know who was on the other side of these trades. In particular, was Madoff and Company on the other side of any of them. They researched the trades and said they couldn’t find any trace of Madoff and Company.

So, I said to McKinsey, “This is a fraud.” They said, “But we’re making 20% a year.” I said, “Well, you’re making 16% on your other investments. If I’m right, this 20% is not real, and the roof’s gonna fall in someday, and you might lose your jobs. On the other hand, if I am right, and you move, you’ve solved this problem. If I’m wrong, and you move, you’re only going from 20% to 16%. So it makes a lot of sense to just exit.”

So they exited in two months. We inquired of everyone we knew on my network, they through their network, to find out who had investments with Madoff and how much they had. We could only cover a small part of the territory because our network was not comprehensive. We were able to identify about half a billion. That means that there was a lot more than half a billion out there. How much more we couldn’t say.

But how could you challenge Madoff? He was a pillar of the National Association of Securities. He’d been a past president, even on committees there. He was the biggest third market, that is off the exchange maker, in the country. He was a respected person, well known to everybody, and he had thousands of investors. Because he had so many investors, everybody knew it had to be right, because surely those people had checked it all out.

The finale of the story is that when I was doing this, the person who invited me, who was a hedge fund manager himself and had been an advisor to McKinsey, believed in Madoff and continued to raise money for him. In 2008, when the news came out that Madoff was a fraud, my son called me up and said, “You know, Dad, the stuff you’ve been telling me about for 17 years, it finally happened. It blew up.”

This fellow who had been running a fund of funds, and included Madoff in that fund of funds, that’s a special type of hedge fund that invests in other hedge funds. He had been doing this and had a very big fund of funds. He was raising money for Madoff the same week that the bad news came out. He had his own personal money, his family’s money, and trusts where money was with Madoff. But I had explained everything to him in great detail. I knew him quite well, at the time back in 1991, that McKinsey and Company had this analysis explained to them and decided to pull out.

The whole point of this is, here’s a person who had all the information, it was explained very clearly, and he just didn’t believe it. He himself was in the investment business and was very successful. But he was swayed by popular opinion. He would poll people and then go by the poll. So just imagine that you asked 10,000 people whether they thought you could travel faster than light. 9,999 said, “Yep, you can do it. I saw it on TV.” And only one guy said, “No, you can’t do it, Albert Einstein.” So a guy like him would overwhelmingly reject Einstein and believe the 9,999 average people who just said, “Yeah, you could do it,” because the poll was 9,999 to one on one side.

He doesn’t think for himself. He lets the crowd think for him. And that, I think, is a fundamental mistake that many people make. They let the crowd do their thinking. They don’t figure it out for themselves.

[Kris: This is an incredibly difficult topic — the tension between first principles and consensus in truth-finding. In this example, Thorp uses the consensus finding method know as a poll aka democracy. In Dinosaur Markets, I explain a a very similar metaphor I learned from Jeff Yass at SIG. Yass and Thorp would probably agree that if there was a futures market traded on the speed of light question the contract would trade for a much smarter price than what the poll would indicate — Einstein would have raised money to short the proposition from a small but rich group of investors who are in the business of finding wedges between fair value and consensus price.

But even markets can suffer from the madness of crowds. Markets and democratic means of finding truth can both fail. And that is where the first principle people shine. It’s the scientist, entrepreneur, or Billy Beane whose independent thinking coincides with everyone laughing at them. 

But I say the tension is difficult because well-functioning markets have a good track record of being hard to beat, so if every problem is a nail to be hit with a first-principles hammer your gonna waste a lot of energy tearing down Chesterton’s fences only to discover that your predecessors deserved more credit. 

also see  Snowflakes vs Lemmings]

Which investors, other than Warren Buffett, impress you? They could be people who are no longer actively investing, or they could be current investors. Are there any who come to mind who have particularly impressed you, aside from Buffett?

There are people in the hedge fund world who have done remarkable jobs at various times, but they’re not accessible to your listeners, or to most people. For example, let’s take Jim Simons of Renaissance. Renaissance Partners is basically a private operation at this point. But it’s been extraordinarily successful, using PhDs, computers, math, and codebreaking, and so forth. And it has, from around 1989 or 1990, been spectacular in its performance, probably having the best risk-adjusted record in the world from that time forward.

Any other names who come to mind?

Well, I’m trying to think of whom I would give money to invest. I don’t have anybody now to whom I’d give money to invest. There are a few good hedge funds around, but they take too much for the general partner and leave too little for a limited partner. They also generate income that is highly taxed if you’re a taxable investor. So, they’re only good for nonprofits or tax-exempt investors.

You could have simply become a full-time capital accumulator. How did you decide to wind it down? And how do you determine what is ‘enough’? This doesn’t strike me as a common sentiment among people who are really good at investing.

The way I entered the investment world was as an academic. I was curious and found things interesting. I wasn’t really there to get rich; I was there to solve interesting math problems that kept coming up. Blackjack and Roulette were math/physics problems. Investing was, for me, lots and lots of math. So, I enjoyed that. I just do things I like, and I don’t worry about money. As my former sister-in-law once said, “Do what you love, and the money will follow.” She wrote a book with that title. And I thought, that’s right. Do what you love, and the money may follow. If it does, that’s fine. If it doesn’t, you’re still doing what you love. What’s important in life, I think, is the journey, the people you spend your time with, and how you spend your time.

I started out as a child of the Great Depression, so I knew what it was like to have basically no money. I used to sleep four or five hours a night in high school and get up at two or three in the morning to deliver newspapers. I made $25 a month, which seemed like a lot of money. I saved part of that for college and invested part of it in science equipment, chemistry, telescopes, electronics, and so forth, just because I liked playing with those things and learning about them. So my goal wasn’t to make money; it was to have a good life, enjoy myself, and have fun. It just so happened that I also made a lot of money.

What I found in the investment world is that lots of people go into it for the money. And when they do, they keep going and going. It’s a validation for them that they can’t stop. They end up with five or ten villas, a yacht, a jet. But imagine having five houses. How much of your time is spent in each house? You can’t be in your house all the time. You’ll be vacationing, traveling, meeting, and so on. So maybe it’s a sixth or seventh of the time, on average. Now, some houses you’re going to spend more time in, some less. You may spend a tenth or fifteenth of your time in one of those houses. So you end up with a lot of stuff to manage and take care of. You end up hiring people to do that, then you have to manage those people. Then you have to hire people to manage the people who manage the people, and so on. It’s like running a business. You don’t get to enjoy the important part of your life, which is time.

[Kris: You don’t have to be a centimillionaire to relate. If you live in a nice suburb town near a coastal city (ahem the working rich) you can learn from this too. Personally, I feel that many high-earners who still feel money insecurity just spend too much time looking over their neighbor’s fence. But Thorp endorses a book by Ian Shapiro that proposes another possibility that I think makes more sense. It’s not envy. It’s a fear grounded in what are eyes see — communal breakdowns. The book is called The Wolf at the Door: The Menace of Economic Insecurity and How to Fight It.

Thorp describes the book:

The book is fairly recent, explaining the concepts I learned in a political science course a few months ago. It discusses how to form coalitions that can win and how to pass measures that will endure. For instance, Social Security has remained intact because it immediately established a strong constituency that would perpetually defend it. Politically, despite attempts by some politicians and occasional political parties to dismantle it, they have not been successful due to the deeply embedded and robust constituency. He provides a clear description of how to effectively accomplish goals. He believes that incremental progress can be made, as discouraging as it may seem these days, by correctly forming and defending against blocking coalitions. I highly recommend his book to anyone looking to make evolutionary progress.

In my opinion, we are currently in a democracy crisis. Simplistically, we have three paths: devolution, which we are currently undergoing; evolution, which I hope will occur where we fix things and improve; and revolution, which is extremely unpleasant.

One of your previous interviewees, Ray Dalio, has a book that I believe is worth reading, despite being a challenging read. It contributes significantly to the discussion about the crisis we are currently facing, discussing the changing world order, the rise of China as an empire, and the decline of the United States. As an empire, we need to do some serious thinking. We cannot rest on our laurels, claiming our past greatness and hoping it will continue. We need to do things differently.]

Did you have a specific point at which you knew you were going to exit the business, so to speak, or was there a particular day or experience that prompted you to say enough is enough?

I wasn’t having fun anymore. It was turning into work. And I thought, “Well, I don’t need to do this. I have enough wealth. I’m never going to spend it all. Why keep doing this?” So, I decided to wind it down. It was fun for a long time because they were challenging problems. It was challenging to try to figure out new things and to deal with all the issues that came up. But when it became bureaucratic and paperwork, and a grind where I had to do things I didn’t want to do, that was enough. It was time to go. And it was the same thing in academia. I loved academia, but there were aspects of it that became burdensome: committee meetings, endless reviews, grant proposals. What I liked was research and teaching, and the people that I met there, the students and the faculty who were smart and challenging. If it was only that, I’d still be there. But it wasn’t only that, and I found other things that were equally or more fulfilling. So, anyhow, I just migrate to where I want to be. I don’t have a set thing that I have to keep doing. Let’s explore that.

I spend my time reading, traveling, exercising, enjoying my family and friends, and learning things I can. It’s also entertaining to casually manage my investments. I might interject here that one thing that makes you independent is accumulating capital. Then, the capital can grow on its own if it’s simply invested, as I described before, in an index fund. Once you have capital, you have the chance for independence. If you have enough capital, it can support you indefinitely. When you’ve achieved that goal, there’s no point in spending time doing anything you don’t enjoy if you can avoid it. There are some things you don’t like but have to do, like gathering your tax information every year or going for routine medical appointments.

Is there anything that you are particularly interested in learning more about, currently in the process of learning about, or looking forward to learning about?

What I’ve focused on for the last year or so is reading about what’s going on in American society. What may happen? I don’t think we can predict for sure what’s going to happen. But we can map out scenarios, we can map out possibilities. We won’t get them all, but we can map out quite a few of them. And ask ourselves, what will we do if scenario A, scenario B, or scenario C materializes, and have some sort of preparation and readiness for that.

I won’t go into a list of extreme scenarios except maybe a few:

  • You could have an autocratic country where a minority pretty much rules everything and dictates everybody else.
  • You could have a turbulent country where a large part of the country, maybe a majority, is badly upset and just wants to bust everything up and start over somehow.

So you could have the choices that describe a devolution, evolution, or revolution. I don’t know how it’s going to play out. But it’s worth thinking about what might happen. And whether there’s anything any of us can do about it.

I don’t think there’s much that an individual can do on a grand scale, unless he happens to be in a position of great importance, or manages to get himself in a position of great importance. But I think there’s a lot that an individual can do on a small scale. And I think the best thing we can do is teach everybody to think for themselves. So they don’t just take what they’re told, in the press, for example, or in the other forms of the media, the internet, Twitter, and so on. They don’t just take that and blindly believe it, but they question it. And they ask whether, in fact, it might not be true. What the motives are of the people who are putting these things out and so forth. When you begin to think for yourself, the whole world changes and becomes much clearer, in my opinion. And you can manage your life much better. 

[Kris: This is an area which I would partially disagree with Thorp. While I think it’s a noble goal to want to teach everyone to think for themselves…I think this fundamentally unscalable. I am not optimistic about the capacity of individuals to elevate their ability to cognitively reflect by large jumps. Which means we are locked into the distribution of this ability as it is. And even if we could, it’s not clear that it is adaptive or even possible at the group level. I don’t feel that the group level is just a scaled up version of the sum of individual gains — I think it’s a phase shift into which those gains would either be lost or sublimated into another dumb mob mentality, hacked by the same forces that infiltrate every group movement draining them of the purity of their initial energy. At a society level, progress requires the carrying capacity to bring our dumb caveman selves along with it. In spite of it.

If progress is contingent on us escaping our tribalism, it’s doomed from the outset. I think Dan Carlin has the framing best — our unraveling will come from failing to seriously confront an existential coordination problem. And we are going to need to do that without counting on a collective mental upgrade.]


If you use options to hedge or invest, check out the moontower.ai option trading analytics platform

Excerpts From Byrne Hobart on Hedge Funds, VC, and Finding Alpha

Eric Torenberg interviews Byrne Hobart and Daloopa CEO Thomas Li on Hedge Funds, VC, and Finding Alpha

I pulled some excerpts below I’d like to hold for future reference. I used ChatGPT to clean up the transcribed excerpts — the result is a mix of quotes and paraphrases. 


On Alfred Winslow Jones first hedge fund being similar to the modern pod shop:

But other things were just generally a sensible part of the model that you charge based on performance. You try to hedge your exposure. So you’re not just betting the market goes up. But you’re trying to differentiate among different companies and try to figure out what makes each company unique. Not just understanding the business, but also understanding what makes the stock move. A bunch of other hedge funds started appearing in the 60s. Then, in the early 70s, almost all of them went under. Many realized they could borrow as stocks were going up. They borrowed a lot to buy a lot, and it worked really well for a while. Then most of them got wiped out. However, there were a few survivors. You had this golden age in the 80s where you had people like Soros doing more macro stuff, and people like Tiger doing more company-specific fundamental stuff. As computers got faster and we started having more data, people came up with systematic strategies across different asset classes. A lot happened between the 80s and today, but the current evolution has been towards some funds that run classic strategies like value-based stock picking and being mostly long, with a couple of short positions. The strategy that’s gaining a lot of market share in terms of assets and public attention is the multi-strategy, multi-manager, platform, or pod shop model.

In this model, you give a portfolio manager some capital budget/risk budget. You tell them they are picking stocks in their sector, the kinds of companies they pick, and they must have no net exposure to the market, large stocks versus small stocks, or one industry versus another, or momentum stocks versus value stocks. Once you hedge out all those factors that cause different companies to correlate, you end up with a very pure view of which stock is going up relative to its peers. This model has worked really well as a way to create uncorrelated streams of alpha. So if you have 100 different people doing that in 100 different subsets of the market, and they all stay on top of these companies better than anyone ever before, they will generally figure out when orders are slowing down or picking up, when an airline will accelerate its growth, or when a price war between steel companies will abate. If you are continuously tracking and turning over a portfolio, you end up always identifying the idiosyncratic news that’s going to drive a given stock’s movements, beyond just the random noise that drives prices. That’s a general overview of what those funds do and how they think.

Examples of HF strategies

We’ve mentioned the multi-manager, multi-strategy funds, and they encompass a large number of different strategies within them. We’ve talked about the fundamentals and different strategies, but many of those funds will have systematic strategies. These range from broad-scale strategies, like looking at all the different asset prices and what correlates with what. For example, if there’s a view that deviations from these correlations will snap back. So, if oil stocks generally move together with the price of oil and then one stock is lagging, that’s the one you buy and you short a basket of other stocks against it. You can also have much more sophisticated systematic strategies.

One category that goes through booms and busts is index inclusion strategies. This involves predicting who will get added to or removed from the S&P 500 or other indices. The first order problem is predicting who gets added or removed based on explicit index inclusion criteria and your view of the index committee’s decision-making. You’re also trying to bet on the volume of trades that is already making this bet. For instance, if the index inclusion means that the index funds have to buy 10 million shares of Company X, but traders betting on that inclusion have already bought 15 million anticipating selling them to the index, then it’s actually a bad catalyst. When the inclusion happens, they are trying to sell more stock than the index funds want to buy.

Another style that goes in and out of fashion is global macro, which can be split into two things with opposite cycles. One is doing these global relative value trades, where you look at the world and basically look at which countries seem to be converging in terms of standard of living and government norms with the United States. You buy their currencies or revive their assets, expecting that convergence to continue. The other is, you look at the state of the world, decide something is totally unsustainable, figure out what’s going to break, and find the most cost-effective way to bet that it breaks. This kind of strategy can work extremely well during a crisis or sometimes when there is a crisis in one place or some outlier event.

Every time there’s an election surprise, you wait a couple of weeks, and you’ll find out that some macro hedge fund is up significantly, like 300%, because they had a massively levered bet on something like Argentinian stocks. They were the only ones who truly believed it would happen and that the rally would be as magnificent as it was. Regarding Brexit, there was a lot of activity where hedge funds were commissioning private polling and trying to track the developments over time. They tried to predict what would happen and, if so, what the magnitude of the price impact would be.

Risk-parity and 60/40 being implicit macro bets on low inflation

If you look at a long chart of the equity and fixed income correlation, you see that the sign flips depending on the level and uncertainty of inflation. When I started working at a hedge fund in 2012, it was a given that when stocks went down, treasury bonds went up, and vice versa. This pattern essentially started in 1998, triggered by a market dip due to long-term capital management, the East Asian financial crisis, and the Russian crisis. The Fed significantly increased liquidity, boosting bond prices, and eventually, stocks snapped back while bonds came down, channeling liquidity into the stock market. This led to the highs of 1999 and part of 2000, which was enjoyable for everyone except the short sellers.

This situation was possible because inflation had been steadily declining since the early 80s. Around 1998, it could be argued that China’s labor supply was almost infinite compared to the world’s demand for physical goods. As long as people could move from the countryside to cities to produce goods, the cost of tradable physical items like TVs, toys, furniture, and apparel would either remain flat or decline. This price drop was largely due to production moving from more expensive countries to cheaper ones, with China offering a huge labor force and good ports, plus a government eager to grow its industrial base and invest in infrastructure.

For a long time, inflation wasn’t a concern. Whenever growth slowed, stocks would drop, and rates would decrease, causing bonds to rise. This made risk parity an excellent trade. However, it turns out that risk parity is essentially a macro bet that inflation will remain low, implying that the risk-adjusted return of stocks plus bonds is significantly better than that of either one alone.

Most strategies are implicitly a bet on the yield curve

If you’re a venture capitalist, you’re interested in the tail end of the yield curve being as low as possible.

In risk parity, the preference is for the yield curve to have a traditional curve shape, essentially what people envision when they think of a yield curve.

For a market neutral or factor neutral hedge fund, the ideal scenario is for the short end of the yield curve to be high, and for it to be flat or almost inverted, indicating high volatility. 

…

Don’t tell the VCs, but it’s true. A flat low yield curve implies a very low growth environment where real rates are extremely low. This means that if you can invest in a company that can produce secular growth at a time when rates are low, the valuation becomes completely nonlinear. For instance, look at what companies were trading at in 2021, it was because the present value of profits in 10 years was really close to the value of those profits today. As a result, many of them were valued on a multiple of 2027’s revenue or something similar. As long as they were growing really fast, that multiple made them look quite cheap. [Kris: See Negative Interest Rates and the Perpetuity Paradox]

These things work really well when rates are extremely low. Low rates also mean there’s a lot of capital floating around. This goes back to the earlier point on what Limited Partners (LPs) want; often they seek a single digit return. If you can buy 10-year treasuries at 5%, a single-digit return is not hard to achieve with very simple assets. But if your Treasuries are earning 70 basis points, then you absolutely have to take risks. This creates an interesting feedback loop where a lot of money flows into the growth parts of the economy. Many startups sell things to other startups. So, every time another large check goes into Snowflake before its IPO, suddenly there are more Zoom and DocuSign seats being sold, more Slack seats being sold, and there’s more usage on AWS. It all feeds into the same ecosystem. If everything’s trading at a high enough price-to-sales ratio, then every dollar that goes into the ecosystem increases the market value of that ecosystem by more than that dollar.

Additionally, if companies are increasingly paying people in equity, then you don’t need much cash to keep the flywheel going for a long time. Venture capital turned out, at least in modern venture where you have an ecosystem of startups selling to other startups, to be about understanding unit economics well enough to look at companies burning cash and ask, “What are they getting when they burn that cash? How much Lifetime Value (LTV) are they getting for the Customer Acquisition Cost (CAC) they have to spend?” If that number looks good, then you could put a really high valuation on these companies.

That’s one of the things that changed in the venture ecosystem, even over the five years up to 2021. People got really good at quickly identifying companies with a product-market fit, looking at what the unit economics look like, and discounting that by looking at the Total Addressable Market (TAM) and then basically saying, someone else can also figure out these numbers, so someone else can capture this TAM. Therefore, we absolutely need to give this company massive funding. The playbook for growing a company fast by dumping a lot of money into it got very refined by that time. You could find someone who had worked at a company that scaled at that speed and who knew where the bottlenecks were. Meanwhile, some of the scaling got easier because of all of these third-party services.

You didn’t have to build out an entire internal communications infrastructure like Amazon did when they were getting started; they built their entire customer service system in Emacs Lisp. But now you would just use Front or something similar, so you don’t have to put any engineer hours into building that system, which means you can scale much faster. More of the money went more directly into the company’s core competency because everything that was non-core was somebody else’s SaaS product that you could just buy.

Why shorting overvalued or fraudulent companies is a weak hedge from a correlation point of view

I wrote a piece on shorting recently and how it’s become a worse hedge over time. The basic argument is that when people are shorting, whether it’s on an unconstrained generalist basis or within an industry, they tend to find the same companies. They tend to identify companies that are over-earning, have dishonest CEOs, or are overly promotional, and so they short them by default. Alternatively, they might do the funding short of just picking a company where nothing is going to change over the next decade. So if they have to have a short position, they could just short this and not think about it anymore.

One problem with this is that it means when there are extreme market disruptions and hedge funds are telling all their portfolio managers to cut their exposure in half as quickly as possible, they’re all selling the same stuff or, more likely, selling some of the same stuff and also buying some of the same stuff. Sometimes it’s gratifying when I’m on Twitter and I see a rumor that some pod somewhere blew up, and then I look at the stocks I’m short and see they’re all up five or 10%. It feels good to know that I’m shorting the same things the professionals are, even if I found out because that particular professional didn’t perform well and got fired.

An interesting example of this I stumbled on recently was a company called Zion Oil and Gas, which seems like a scam. They’re drilling for oil in Israel, which is one industry that Israel does not excel in. It’s one part of the Middle East where that’s not the main economic activity. But they’re raising money from American investors who think this is really cool or maybe it’s biblical somehow. The stock in Zion Oil and Gas was at $6 a share in December 2008 and then went up to $14 a share in February 2009, making it one of the better-performing US equities over that time period. This was during the depths of the crisis. I have to assume that a lot of it was that very smart people were shorting this, thinking it’s a retail promotion that’s going to run out of money and die. Then all of them were losing money on everything else they did and had to cut exposure and buy back. So the stock went up. Maybe they did a big promotion, or maybe they had some sort of financial crisis, the End of Times themed stock promotion, but a lot of the worst companies in the world all go up on bad days because everyone is covering. So it becomes harder; over longer periods, shorts do hedge a portfolio, but day-to-day, it’s more painful.

Framing the competition between retail and professional investors

Why different time horizons mean different arenas

In many ways, everyday investors will generally either have a really short timeframe and are more or less gambling, or making educated bets on minor market movements, or they’re making longer-term bets like, “I know this company, I like the company, I use the products all the time, I’m going to buy the stock and hold it for 20 years.” If you’re doing that, it doesn’t really matter if Citadel is better informed about how this quarter is shaping up. Sure, it’s unfortunate that you might have bought the stock for 10% less if you waited a week until they reported bad earnings. But if you truly believe in the company, then it’s a minor difference, especially over longer timescales. And if you’re investing continuously, saving money, and putting a little money into the market every so often, then it all averages out.

One of the nice effects that hedge funds have for you as an investor is that they price in all the incremental changes in the outlook all the time. So every time there’s a new round of data that tells you a bit about share shift within some industry, hedge funds immediately adjust to that, or they have predicted it and already adjusted. This makes you less likely to be blindsided by certain types of surprises, especially on the revenue side of consumer-facing companies. It’s broadly true that hedge funds do make the market more efficient, so you’re getting a better deal.

Hedge funds are not trying to figure out where the stock will trade in 10 years. To the extent that they are, it’s more like they’re trying to reverse engineer the process of large, long-only investors, like Fidelity and Capital Group, etc...and what incremental news flow over the next two weeks will adjust their 10-year price target in a predictable way that you can trade ahead of.

Retail advantages over pros

The single largest source of advantage in the markets, ironically, are not owned by hedge funds but by retail investors, and that’s the time horizon. Over a long enough time horizon, you can actually outperform most hedge funds if you do things with discipline. Hedge funds have some disadvantages which you can easily avoid as a retail investor. The first disadvantage is that hedge funds incur a lot of short-term capital gains tax when they make money because of trades that mostly don’t go above a year. For retail, holding a stock for over a year is not that difficult. The second key benefit is that hedge funds need to show short-term performance; monthly returns matter, quarterly returns absolutely matter. They are forced to take movements when the markets are not favorable. For instance, there’s a grossing down problem. If the markets are bad, and everybody’s losing money, that’s the time you want to be deploying capital. But what typically happens is they’re reducing their exposure to the market to figure out what is going on, and that’s when you see huge market dislocations. As a retail investor, you can sit there and say, “8% is nothing if I’m going to hold the stock for the next 10 years, I’ll just hang on to it.” And that time horizon difference is a huge source of alpha in a market that, for the most part, isn’t competed away, even with the biggest hedge funds, because they don’t have the ability to do that.

Hedge funds measure themselves on a risk-adjusted basis, and part of it is just how they’re structured and capitalized. They’re often levered, like six or eight to one is the usual ratio. So if you’re an individual portfolio manager at one of those funds, if you have a billion-dollar allocation, you think their target return is like 10% a year, but no, their target return is on the order of like two or 3% a year. Because they are hedging so many things out, they just aren’t taking enough risk to make massive returns. The risk comes from stacking a bunch of these portfolios together. And if you make a trade and it’s not working right away, you’re probably going to exit that trade because you don’t know why it’s not working. It means that hedge funds are in this constant effort to generate new ideas. There’s this idea of velocity, like if you have a portfolio and it has X amount of names, and you’re turning over all of the stocks in that portfolio every Y trading days, then you need at least one original long or short idea every workday to have a portfolio with the right structure. The median quality of the ideas is not necessarily good, but it is a volume game.

What is a hedge fund solving for fundamentally?

You’re in the risk removal game, trying to remove as much risk as possible, because you have access to cheap enough leverage that if you can consistently generate a 3% return, it’s world-class, it’s absolutely phenomenal. With that consistency, you can borrow 10 times the money and make a 30% return. So, to achieve a consistent 3%, the key being consistency, you are removing every type of risk possible. However, the challenge of doing that is you often end up in situations with many other funds trying to do the exact same thing. Hedge funds tend to get into crowded longs and crowded shorts, where everyone is following the same thesis. For example, everyone might be long Amazon and short a bunch of other e-commerce tech names, or long Booking and short out the rest of travel.

In these nuanced situations, if a company like Amazon reports earnings and beats them, but not by enough due to the high number of long positions, the stock may trade down. These funds that are long Amazon then have to sell because the earnings, though fundamentally good, didn’t meet the high expectations set by the market. In trying to remove risk, these funds actually take on a significant risk by not considering that everyone else is removing the same risk.

To avoid this problem, one strategy is to engage in areas others are not focusing on. This approach, however, can be challenging because it often means fewer resources, fewer people to talk to, fewer conferences to attend. You’re often on an island, which can be a more difficult psychological battle. When working for a large platform, especially those managing double-digit billions, you quickly realize you can’t deploy hundreds of billions of dollars in ideas that others aren’t looking at. The equity markets will tap out very quickly in those spaces. Thus, the risk many hedge funds end up ultimately taking, which they want to avoid, is the risk of everyone else doing the same thing.

[Kris: This section touches on a few ideas I’ve observed before:

  1. GPs have some misalignment with LPs (and non-partner PMs)
  2. The trading mindset is merging with investing as the focus on alpha marries and operationalizes what “trading as a business” understands with informational inputs that come from understanding what drives business fundamentals and market reaction]

The curse of hedge fund managers is that they start out because they enjoy picking stocks, building systematic models, or day trading, but as they grow, that becomes 0% of their job. Instead, 100% of their time is spent on risk management, investor relations, or recruiting. They end up building a system that automates a lot of what they’re good at and then have to find their own idiosyncratic source of returns. If a hedge fund has access to the best prime brokers, best exchange connectivity, and best algorithms for implementing trades with low slippage, they need to gain an idiosyncratic return by hiring unique people early and onboarding them effectively.

A significant part of the business becomes structuring the trade in a way that defines a person’s incentives and non-compete agreements to capture as much of the alpha as possible at an acceptable price. These funds often offer experienced portfolio managers guaranteed bonuses and agree to hire them at the beginning of a non-compete, allowing them to wait it out. The hedge fund entity’s trade is about defining the person’s incentives so that they capture as much alpha as possible.

From the LP perspective, a hedge fund is like a marvelous treasury bond, producing a stable, non-correlated, and safe return. From the GP perspective, it’s more like a venture fund, looking for the handful of superstars who will consistently generate that 3% growth every year to make the business the best it can be.

Surprisingly, the big platform funds like Point 72, Millennium, Citadel, and Balyasny, which have backgrounds in day trading and systematic fixed income, do not come from a background of deeply assessing management integrity, which was a focus of Tiger Management. Tiger Management, once one of the biggest funds, wound down but seeded funding to its best analysts and network, creating an implicit multi-manager fund. However, they didn’t have the central risk management that current multi-strategy platform funds have. Julian Robertson’s funding led to a sort of implicit multi-manager fund, but they all used very similar strategies and often crowded into the same stocks.

This paradox shows that a background in assessing portfolio managers and analysts does not necessarily translate to success in managing a multi-strategy platform fund. The people who excelled at it were those who deeply loved creating the game.

 

“Peak-pod thesis” and efficiency

If you look back, there was a time when hedge fund returns significantly outperformed the market. However, starting around 2000, this gap began to shrink, and by 2010, it was minimal, closely aligning with the drag from fees and taxes. Hedge funds were once consistently generating a lot of alpha, but that started to decline. Now, the quality of reported alpha is higher, with more funds truthfully reporting no net market exposure or accurately disclosing their exposure and additional returns. However, as the skill level of investors increases and they understand the model better, the quantity of alpha available inevitably shrinks.

Hedge funds have become so proficient at generating ideas and maintaining a certain hit rate that they continue to produce risk-adjusted returns. But as more capital flows into these strategies and into competing funds, it becomes harder to execute large trades. The industry might reach a peak where the role becomes more routine and systematized, potentially leading to lower compensation per person but still remaining a significant job category.

Regarding total investment returns, imagine a stock market chart resembling a zigzag line deviating from a straight linear path. The area under this zigzag line represents the total market returns, predominantly beta. Alpha is the difference between this zigzag line and the linear path. In a market where volatility is high, hedge funds tend to perform better because the deviation from beta is greater, thus increasing the total alpha available. The current question is whether we have reached the peak number of portfolio manager “pods.” This depends on the total market volatility, which has been increasing due to higher interest rates, suggesting a potential for more pods and higher alpha generation.

However, if interest rates decrease and market volatility diminishes, hedge funds may face challenges in maintaining their current levels of alpha generation. They would need to diversify into other sectors to find new sources of volatility and alpha. Theoretically, if the market were to move in a perfectly linear trajectory, there would be little need for hedge fund pods, but such a scenario is unlikely to occur.

The concept that alpha sums to zero before taxes and transaction costs is crucial. If you’re making above-average returns, it’s typically because someone else made less optimal trading decisions, either buying high when you sold or selling low when you bought. Hedge funds rely on a supply of traders who are either valuation insensitive or simply poor at trading. However, this reliance draws other traders to exploit the same opportunities.

In The Laws of Trading you hear alpha doesn’t last forever, and this applies to both positive and negative alpha. For instance, negative alpha can occur in large pension funds that execute market orders for stocks every two weeks when employees contribute. Over time, traders might notice this pattern and begin buying these stocks a day earlier, selling them back to the pension fund at a higher price, thus reducing the fund’s impact and making it harder for them to systematically lose money. If it were possible to deliberately lose substantial money consistently, then inversely, one could make money by doing the opposite of their losing strategy. In public markets, it’s almost impossible to consistently lose money in absence of significant transaction costs.

How this can get quite meta

Concerning alpha capture, multi-manager funds analyze their portfolio managers’ decisions to determine their strengths and weaknesses. They can identify managers who consistently perform poorly with certain stocks or situations. This information helps build a meta portfolio that represents what the firm’s portfolio would look like if managers were perfectly self-aware of their abilities. Interestingly, someone who is consistently wrong about a particular stock, like consistently mispredicting Nvidia earnings, can be valuable. Their predictability, even in failure, can be leveraged by a quant model to generate profits by taking the opposite position.

This leads to a somewhat disconcerting situation where a financial professional might realize their value came from consistently incorrect predictions about a specific stock, contributing to their firm’s success by serving as a reliable contrary indicator. It’s this weird Marxist alienation from your labor, where if you find out that you had a really lucrative financial career, and it was entirely because you were really, really bad at Netflix earnings or something, but you were so bad that the quant model realized it would just fade you in much larger size every single time and make money like that’s gonna be a depressing realization. But someone, someone someday will probably come to that realization that they were just so reliably bad in certain situations that they actually made their employer money.

Understanding the good and bad of the job can help you determine if pro investing is for you

It’s exhilarating to feel like you’re always in the flow, that when something happens, you either anticipated it or are among the first to grasp its implications and strategically position yourself. That’s a thrilling feeling, although it’s not the norm. Usually, you feel clueless, underperforming, and stressed by random bad news. It’s like walking into the office and getting hit in the face. But occasionally, it’s extremely fun. The most gratifying things often come through ongoing stress and suffering. If you learn to enjoy that, you’re set.

Working at a hedge fund is unique because of the day-to-day variability. You’re dealing with extreme uncertainty and making decisions where being wrong 45% of the time means you’re top-notch. If you value intellectual honesty and variety, it’s a fantastic career.

However, when things go bad, they can be drastically different. The high level of trust and unpredictability can significantly impact your personal life.

There’s a trend of hedge funds starting venture practices and vice versa. It’s interesting to see if there will be more crossover, as both sectors tolerate a high rate of being wrong. One key difference in venture capital is the longer feedback loop. You won’t know if you’re a good venture investor for many years, unlike the quicker feedback in hedge fund investing.

The hedge fund industry is known for high burnout rates. Many enter in their early to mid-20s and leave by their 30s. Often, these employees haven’t experienced a full market cycle; they’re hired in good times and shocked by downturns. For instance, the downturn in Q4 2018 was mistaken by some as an apocalypse, but it was followed by a great year, giving a misleading impression of real downturns. In 2022, with an actual downturn, the industry faced a harsh reality check. 

Updating is something people do a lot within a cycle on kind of minor stuff, like on Netflix, for example, it was more of a net subscriber additions story for a long time, and then became more of a revenue story. And it was also partly a margin story. However, when there’s a quarter where you correctly predict the net adds but get the revenue wrong, and the stock reacts more to revenue, you must quickly adjust your focus.

You have to very quickly tell yourself “the thing I was really good at predicting actually does not matter as much as this other thing. And so now I have to get good at predicting that.” And it’s when the really big shifts happen — like when the focus shifts from growth to profitability, or when we can’t assume infinite capital or money having zero cost doing lazy discounts. Now you actually have to think about what is the value of 50 cents in five years versus $1 in 10 years, instead of treating $1 in 10 years is worth roughly $1 today.

The ability to quickly adjust perspectives and decide what matters is crucial. Adapting your mental model rapidly during major shifts, such as a shift in focus from growth to profitability, is challenging.

Those who can adapt and last through multiple market cycles do extremely well due to their growing experience and opportunities.

[Kris: See 5 Takeaways From Todd Simkin on The AlphaMind Podcast to understand how a trading firm trains cognitive flexibility. This is especially important when you hire smart people who aren’t used to be wrong. This is echoed below.]

There’s a saying: “a smart person knows what to do, and an experienced person knows the exceptions to what to do.”

The average age in a hedge fund is relatively low compared to many other industries, including their mutual fund counterparts. You often see people working in hedge funds who have had a series of successes throughout their lives to reach their current positions. The typical profile of an analyst, for example, is someone who excelled in high school, attended a prestigious university, graduated at the top of their class in finance or economics, then went on to work at a major investment bank. After one or two years, they’re recruited from that investment bank to a top private equity shop or hedge fund. It’s a chain of success where they haven’t experienced significant career failure.

However, once in a hedge fund, the measure of success is not about the ability to study well or work hard. The skills required for success in a hedge fund are different from those correlating with educational success or early career achievements at places like Goldman Sachs or Morgan Stanley, where hard work is more directly linked to success. In a hedge fund, working harder does not necessarily equate to generating more alpha. If it did, everyone would be working 20-hour days.


If you use options to hedge or invest, check out the moontower.ai option trading analytics platform

Excerpts From Grant Sanderson on The Lunar Society Podcast

Dwarkesh Patel interviews Grant Sanderson (who runs the excellent 3Blue1Brown YouTube channel) about:

  • Whether advanced math requires AGI
  • What careers should mathematically talented students pursue
  • Why Grant plans on doing a stint as a high school teacher
  • Tips for self teaching
  • Does Godel’s incompleteness theorem actually matter
  • Why are good explanations so hard to find?

Watch on YouTube. Listen on Spotify, Apple Podcasts, or any other podcast platform. Full transcript here.


Kris: I snipped several excerpts for future reference. Emphasis mine. I cut up the excerpts as I want to remember them which means there are missing sections so I encourage you to listen to the whole episode or read the sections of transcript I’m pulling from if you want a closer look.

On the future of education 

[key ideas: reducing distance to students, educator’s role is not just explanation but more importantly “bring out knowledge” not put it in, the non-linear influence of a teacher on a student’s future, and the chaotic concept of “sensitivity to initial conditions”]

Dwarkesh Patel 0:44:44

Should the top 0.1% of educators exclusively be on the internet because it seems like a waste if you were just a college professor or a high school professor and you were teaching 50 kids a year or something. Given the greater scale available should more of them be trying to see if they can reach more people?

Grant Sanderson 0:45:01

I think it’s not a bad thing for more educators who are good at what they’re doing to put their stuff online for sure. I highly encourage that even if it’s as simple as getting someone to put a camera in the back of the classroom. I don’t think it would be a good idea to get those people out of the classroom.

If anything I think one of the best things that I could do for my career would be to put myself into more classrooms…

One of the most valuable things that you can have if you’re trying to explain stuff online is a sense of empathy for what possible viewers that are out there. The more distance that you put between yourself and them in terms of life circumstances. I’m not a college student so I don’t have the same empathy with college students. Certainly not a high school student, so I’ve lost that empathy. That distance just makes it more and more of an uphill battle to make the content good for them and I think keeping people in regular touch with just what people in the classroom actively need is necessary for them to remain as good and as sharp as they are…

The other thing I might disagree with is the idea that the reach is lower. Yes, it’s a smaller number of people but you’re with them for much, much more time and you actually have the chance of influencing their trajectory through a social connection in a way that you just don’t over Youtube.

You’re using the word education in a way that I would maybe sub out for the word explanation. You want explanations to be online but the word education derives from the same root as the word educe, to bring out, and I really like that as a bit of etymology because it reminds you that the job of an educator is not to take their knowledge and shove it into the heads of someone else the job is to bring it out. That’s very, very hard to do in a video and in fact, even if you can kind of get at it by asking intriguing questions for the most part the video is there to answer something once someone has a question.

The teacher’s job, or the educator’s job, should be to provide the environment such that you’re bringing out from your students as much as you can through inspiration through projects, through little bits of mentorship and encouragement along the way. That requires eye contact and being there in person and being the true figure in their life rather than just an abstract voice behind a screen.

Anytime I chat with mathematicians and try to get a sense for how they got into it and what got them started, so often they start by saying there was this one teacher and that teacher did something very small — like they pulled them aside and just said, “Hey. You’re really good at this. Have you considered studying more?” or they give them an interesting problem.

And the thing that takes at most 30 minutes of the teacher’s time, maybe even 30 seconds, has these completely monumental rippling effects for the life of the student they were talking to that then sets them on this whole different trajectory.

Two examples of this come to mind. One is this woman who was saying she had this moment when she got pulled aside by the teacher and he just said, “Hey, I think you’re really good at math. You should consider being a math major.” which had been completely outside of her purview at that time. That changed the way she thought about it. And then later she said she learned that he did that for a large number of people. He just pulled them and was like, “Hey, you’re really good at math.” So that’s a level of impact that you can have as a figure in their lives in a way that you can’t over screen.

Another one which was very funny. I was asking this guy why he went into the specific field that he did. It was a seemingly arbitrary thing in my mind but I guess all pure math seems to be. He said that in his first year of grad school he was sitting in this seminar and at the end of the seminar the professor, who was this old professor who he had never met him before, they didn’t have any kind of connection. He seeks this guy out and comes up and he says, “You. I have a problem for you. A good research problem that I think I think might be a good place for you to start in the next couple months” and this guy was like “Oh, okay” and he gets this research problem and he spends some months thinking about it and he comes back and then it later came to light that the professor mistook him for someone else that was someone he was supposed to be mentoring. He was just the stereotypical image of like a doddering old math professor who’s not very in tune with the people in his life that was the actual situation but nevertheless that moment of accidentally giving someone a problem completely shifted the research path for him, which if nothing else, shows you the sensitivity to initial conditions that takes place when you are a student and how the educator is is right on that nexus of sensitivity who can completely swing the fences one way or another for what you do.

For every one of those stories there’s going to be an unfortunate counterbalancing story about people who are demotivated from math. I think this was seventh grade. There was this math class that I was in and I was one of the people who was good at math and enjoyed it and would often help the people in the class understand it. I had enough ego built up to have a strong shell around things. For context, I also really liked music and there was this concert that had happened where I had a certain solo or something earlier in that week.

There was a substitute teacher one day who didn’t have any of the context and she gave some lesson and had us spend the second half of the class going over the homework for it. All of the other students in the class were very confused and I think I remember like they would come to me and I would try to offer to help them and the substitute was going around the class in these circles and basically marking off a little star for how far down the homework people were just to get a sense are they progressing. That was kind of her way of measuring how far they were. When she got to me I had done none of them because I was spending my whole time trying to help all of the others and after having written a little star next to the same problem like three different times she said to me like, “Sometimes music people just aren’t math people.” and then keeps walking on.

I was in the best possible circumstance to not let that hit hard because one, I had the moral high ground of “Hey, I’ve just been helping all these people. I understand it and I’ve been doing your job for you.” This was my little egotistical seventh grade brain. I knew that I knew the stuff. Even with all of the armor that was put up, I remember it was just this shock to my system, she says this thing and it just made me strangely teary-eyed or something.

I can only imagine if you’re in a position where you’re not confident in math and the thing that you know deep in your heart is actually you are kind of struggling with it, just a little throwaway comment like that could completely derail the whole system in terms of your relationship with the subject.

So it’s another example to illustrate the sensitivity to initial conditions. I was in a robust position and wasn’t as sensitive. I was gonna love math no matter what but you envision someone who’s a little bit more on that teetering edge and the comment, one way or another, either saying you’re good at this you should consider majoring in it or saying, “Sometimes music people aren’t math people” which isn’t even true. That was the other thing about it that niggled at my brain when she said it.

All of that is just so important for people’s development that when people talk about online education as being valuable or revolutionary or anything like that, there’s a part of me that sort of rolls my eyes because it just doesn’t get at the truth that online explanations have nothing to do with all of that important stuff that’s actually happening and at best it should be like in the service of helping that side of things where the rubber meets the road.

On explanations 

[key ideas: not everyone responds to the same explanations so explanations that scale well are difficult to conjure. There’s room for multiple approaches and ways to communicate]

Dwarkesh Patel 1:02:22

Why are good explanations so hard to find, despite how useful they are? Obviously, other than you, there’s many other cases of good explanations. But generally, it just seems like there aren’t as many as there should be. Is it just a story of economics where it’s nobody’s incentive to spend a lot of time making good explanations? Is it just a really hard skill that isn’t correlated with being able to come up with a discovery itself? Why are good explanations scarce?

Grant Sanderson 1:02:47

I think there’s maybe two explanations.

The first less important one is going to be that there’s a difference between knowing something and then remembering what it’s like not to know it. And the characteristic of a good explanation is that you’re walking someone on a path from the feeling of not understanding up to the feeling of understanding.

Earlier, you were asking about societies that lack numeracy. That’s such a hard brain state to put yourself in, like what’s it like to not even know numbers? How would you start to explain what numbers are? Maybe you should go from a bunch of concrete examples. But like the way that you think about numbers and adding things, it’s just you have to really unpack a lot before you even start there.

And I think at higher levels of abstraction, that becomes even harder because it shapes the way that you think so much that remembering what it’s like not to understand it. You’re teaching some kid algebra and the premise of like a variable. They’re like, “What is X?” It’s not necessarily anything but it’s what we’re solving for. Like, yeah, but what is it? Trying to answer “What is X?” is a weirdly hard thing because it is the premise that you’re even starting from.

The more important explanation probably is that the best explanation depends heavily on the individual who’s learning. And the perfect explanation for you often might be very different from the perfect explanation for someone else. So there’s a lot of very good domain specific explanations. Pull up in any textbook and like chapter 12 of it is probably explaining the content in there quite well, assuming that you’ve read chapters one through 11, but if you’re coming in from a cold start, it’s a little bit hard.

So the real golden egg is like, how do you construct explanations which are as generally useful as possible and generally appealing as possible? And that because you can’t assume shared context, it becomes this challenge. And I think there’s like tips and tricks along the way, but because the people that are often making explanations have a specific enough audience, it is this classroom of 30 people. Or it’s this discipline of majors who are in their third year. All the explanations from the people who are professional explainers in some sense are so targeted that maybe it’s the economic thing you’re talking about. There’s not, or at least until recently in history, there hasn’t been the need to or the incentive to come up with something that would be motivating and approachable and clear to an extremely wide variety of different backgrounds.

Putting in work with calculations

Dwarkesh Patel 1:20:44

If you’re self teaching yourself a field that involves mathematics, let’s say it’s Physics or some other thing like that, there’s problems where you have to understand how do I put this in terms of a derivative or an integral and from there, can I solve this integral? What would you recommend to somebody who is teaching themselves quantum mechanics and they figured out how to put how to get the right mathematical equation here. Is it important for their understanding to be able to go from there to getting it to the end result or can they just say well, I can just abstract that out. I understand the broader way to set up the problem in terms of the physics itself.

Grant Sanderson 1:22:00

I think where a lot of self-learners shoot themselves in the foot is by skipping calculations by thinking that that’s incidental to the core understanding. But actually, I do think you build a lot of intuition just by putting in the reps of certain calculations. Some of them maybe turn out not to be all that important and in that case, so be it, but sometimes that’s what maybe shapes your sense of where the substance of a result really came from.

I don’t know it might be something you realize like “Oh, it’s because of the square root that you get this decay.” And if you didn’t really go through the exercise, you would just come away thinking like instead of coming away thinking like such and such decays but with other circumstances, it doesn’t decay and not really understanding what was the core part of this high level result that is the thing you actually want to come out remembering.

Putting in the work with the calculations is where you solidify all of those underlying intuitions. And without the forcing function of homework, People just don’t do it. So I think that’s one thing that I learned as a big difference post college versus during college.

Post college, it’s very easy to just accidentally skip that while learning stuff and then it doesn’t sink in as well. So I think when you’re reading something, having a notebook and pencil next to you should be considered part of the actual reading process.

And if you are relying too much on reading and looking up and thinking in your head, maybe that’s going to get you something but it’s not going to be as highly leveraged as it could be.

The “failure to disrupt”

[key ideas: learning is not bottlenecked by good explanations but by social incentives. Deeply resonant. Reading between the lines — we are aspirational and good at copying others or trying to impress them, so if we know that we should provide good models for learners to emulate]

Dwarkesh Patel 1:23:39

What would be the impact of more self teaching in terms of what kinds of personalities benefit most? There’s obviously a difference in the kind of person who benefits most. In a situation where it’s a college course and everybody has to do the homework, but maybe some people are better tuned for the kind of work that’s placed there versus all this stuff is available for you on youtube and then textbooks for exercises and so on but you have to have the conscientiousness to actually go ahead and pursue it.

How do you see the distribution of who will benefit from the more modern way in which you can get whatever you want but you have to push yourself to get it.

Grant Sanderson 1:24:17

There’s a really good book that’s actually kind of relevant to some of your early questions called Failure to Disrupt that goes over the history of educational technology. It tries to answer the question of why you have these repeated cycles of people saying such and such technology that almost always is getting more explanations to more people, promises that it’ll disrupt the existing university system or disrupt the existing school system and just kind of never does.

One of the things that it highlights is how stratifying these technologies will be in that they actually are very very good for those who are already motivated or kind of already on the top in some way and they end up struggling the most just for those who are performing more poorly.

And maybe it’s because of confounding causation where the same thing that causes someone to not do poorly in the traditional system also means that they’re not going to engage as well with the plethora of tools available.

I don’t know if this answers your question, but I would reemphasize that what’s probably most important to getting people to actually learn something is not the explanation…but instead, it’s going to be the social factors. Are the five best friends you have also interested in this stuff and do they tend to push you up or they tend to pull you down when it comes to learning more things? Or do you have a reason to? There’s a job that you want to get or a domain that you want to enter where you just have to understand something or is there a personal project that you’re doing?

The existence of compelling personal projects and encouraging friend groups probably does way way more than the average quality of explanation online ever could because once you get someone motivated, they’re just they’re going to learn it and it maybe makes it a more fluid process if there’s good explanations versus bad ones and it keeps you from having some people drop out of that process,which is important.

But if you’re not motivating them into it in the first place, it doesn’t matter if you have the most world-class explanations on every possible topic out there. It’s screaming into a void effectively.

And I don’t know the best way to get more people into things. I have had a thought and this is the kind of thing that could never be done in practice but instead it’s something you would like write some kind of novel about, where if you want the perfect school, something where you can insert some students and then you want them to get the best education that you can, what you need to do is — Let’s say it’s a high school. You insert a lot of really attractive high schooler plants as actors that you get the students to develop crushes on. And then anything that you want to learn, the plant has to express a certain interest in it. They’re like, “Oh, they’re really interested in Charles Dickens.” And they express this interest and then they suggest that they would become more interested in whoever your target student is if they also read the dickens with them.

If you socially engineer the setting in that way, the effectiveness that would have to get students to actually learn stuff is probably so many miles above anything else that we could do. Nothing like that in practice could ever actually literally work but at least viewing that as this end point of “Okay, this mode of interaction would be hyper effective at education. Is there anything that kind of gets at that?”

And the kind of things that get at that would be — being cognizant of your child’s peer group or something which is something that parents very naturally do or okay, it doesn’t have to be a romantic crush, but it could be that there’s respect for the teacher. It’s someone that they genuinely respect and look up to such that when they say there’s an edification to come from reading Dickens, that actually lands in a way.

The natural extension of this:

Encourage people to mentor or teach on the side!

Grant Sanderson

I think there are two things I would want to get out of teaching in a school setting. One of them, as I was emphasizing, I think you just lose touch with what it’s like not to know stuff or what it’s like to be a student and so maintaining that kind of connection so that I don’t become duller and duller over time feels important.

The other, I would like to live in a world where more people who are savvy with STEM spend some of their time teaching. I just think that’s one of the highest leverage ways that you can think of to actually get more people to engage with math

And so I would like to encourage people to do that and call for action. Some notion of spending, maybe not your whole career, a little bit of time. In teaching, there’s not as fluid a system for doing that as going through a tour of service in certain countries where everyone spends two years in the military

Shy of having a system like that for education, there’s all these kind of ad hoc things where charter schools might have an emergency credential system to get a science teacher in. Teach for America is something out there.

There’s enough ways that someone could spend a little bit of time that’s probably not fully saturated at this point that the world would be better if more people did that

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.

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”]