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.