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Joined June 2026
Ex-Two Sigma quant Omer Cedar on why you should bet against an expert who keeps getting more bullish: "If somebody is heavily bullish or heavily bearish, and they become incrementally more heavily bullish or heavily bearish, the best thing to do is to bet against them." "They've become extremely comfortable with the story and the narrative of the company, and they don't realize that typically the market has outrun the expectations on the company itself." "When the street is very, very bullish or very, very bearish on something, it's time to go in the opposite direction, because at that point in time, everything is priced in." "Everybody's bullish, everybody's bearish. The first person who walks out and says, hey, I don't think this is going to work anymore, that's the signal you want." "The Emperor has no clothes. That's what it is. Then you have to pull back."
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25% of hedge funds go out of business every year — replaced by another 25%. 40% run at a loss. Former Tudor, Moore & Caxton PM Tom Costello explains: "Roughly 25% of the hedge fund industry goes out of business every year and is replaced with another 25%." "Roughly 40%, it varies year on year, but roughly 40% operate at a loss every year." "The guys on the top end of the Pareto distribution make gobs more money than the guys at the bottom who lose." "Who's better at taking risk is maybe a wash — you'd have to determine that by results." "Of active retail traders, it's probably an even higher number that are losing money consistently."
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unpopular opinion: ai generated designs are not slop. or even remotely close to slop. ai raises the design floor so dramatically now that dismissing it as such is really no diff than when mathematicians got irked when ai solved decades old math problems. if you’ve studied interaction design to any extent you obviously know that so so much of it is patterns, conventions, & adapting to established behaviors. geee, imagine what new technology is amazing at this? you should maximize its utilization.
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Balyasny's founder Dmitry Balyasny on why AI is probably under-hyped even if some AI stocks aren't: "When we look back in 10 years or in 20 years, in the actual outcomes that have happened, it's probably under-hyped. In terms of the stock prices across the board, that's harder to say." "There's some that are probably way over-hyped, there's some that are probably under." "A lot of companies have moved from one bucket to another, where they were in a loser bucket and actually it turns out maybe they're a winner, or vice versa, where people got too optimistic and maybe they don't really have anything that's defensible and differentiated." "It's hard to find things that are super bargain priced that have anything to do with AI." "If you look at the dollars in earnings and cash flow that they're generating and the market caps that they're growing, I think they're executing amazingly well. I think it's quite different from what we had in the dot com era where companies weren't really making money."
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Ex-Balyasny PM Ying Hua on why a crowded trade is a positioning game, not a fundamentals game: "Sometimes a game is not fundamental. Sometimes the game is a positioning game." "As long as there's someone who's willing to buy your shares at a higher price, that would mean someone needs to follow you." "Because everyone's process is more or less the same, because everyone will more or less use the same data, your position's gonna be the same." "You might not be playing a fundamental game. You might be playing a position game."
Fund managers are piling back into tech. 37% of global fund managers are now overweight technology stocks, up from 30% in September, per Bank of America’s latest survey. That’s the highest since August 2020.
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AI and the holding-horizon problem: Balyasny's founder Dmitry Balyasny "I don't think you can replace any for the foreseeable future, but I think it's a really good adjunct." "Markets are quite different. And the longer your holding horizons, the more different they are." "For that stuff, you can use AI to really automate your trading because the rules are quite clear, like what causes a stock to go up in the next 30 seconds? Well, it's more buyers and sellers." "But over a longer period of time, is this employment number that comes in hot good or bad for equities? Well, that depends on the environment that you're in." "When a company misses their earnings number, but the revenues are better, is that good or bad? Well, it depends."
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Citadel's Head of Global Equities Justin Lubell on why the big losses at multi-manager funds no longer come from market sell-offs: "Market structure has evolved incredibly in the last 10 years, and candidly, even the people who thought it might head in this direction have been surprised by the pace." "If you had looked 10 years ago at what caused the losses at firms that ran multi-manager discretionary long-short businesses, you would have looked at beta as being a big potential risk." "If your investors had asked you how you think about stress, you might have said, well, what happens if the market goes down 20%, and what happens if we generate negative alpha of 3%? That was a common stress." "Today, if you were to look at the last 10 major loss events for common players, you wouldn't really find beta shocks. You would find factor shocks, or market rotation shocks." "Even in July and August, there was a lot of discussion around P&L volatility for many market participants, and the S&P 500 didn't move very much. So it was not a beta shock, but people reported incredible gains and then, in some cases, incredible losses during that period of time for other non-beta related reasons."
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Balyasny's founder Dmitry Balyasny on why his PMs were trading too much and not investing enough: "One of the keys to enduring success in the money management business is finding a balance between trading and investing." "You can't survive in a hedge fund type model just being a long term investor, and you can't really scale in a significant growing hedge fund being just a super active trader." "Folks were really trading a little bit too much in the fundamental equities business, and were a little bit overly focused on each data point. We were kind of missing the forest from the trees." "We were chopping ourselves up a little bit too much, missing some of the bigger winners and creating a lot of trading slippage costs." "Find investments where there's multiple ways to win, where you're not playing for one particular data point. You're playing for a whole series of data points that's going to revalue that security over time."
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Every top Netflix show had the same viewers. One ran 3x at the water cooler. Chris Camillo turned $20K into ~$80M over 18 years trading 'social arb' — alternative data before Wall Street sees it. Chris Camillo explains: "Every top Netflix show had roughly the same amount of viewers. Orange is the New Black was roughly the same as Stranger Things." "The metric wasn't how many watch it — it's how many people are talking about it at the water cooler." "That conversation spreads: 'I keep hearing about Stranger Things. Maybe I'll get Netflix and watch it.'" "Stranger Things was about 3x any other show in the history of the company." "That was one of the biggest trades in the history of Netflix — the quarter it came out and the subscribers it grew." "The only way to assess it was monitoring conversational volume against historic benchmarks of past hits."
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Prime Macaya Capital's Managing Partner Alix Pasquet (@alixpasquet) on why his fund refuses to compete with the pods: "A lot of game theory is very technical and mathematical, but it really can be reduced to one thing, which is play weaker players. Don't get into the ring with Mike Tyson." "We don't try to compete with the pods. They are richer than we are, smarter than we are, move faster than we are, have more resources, and in many cases are better looking." "We don't try to compete with them with who they hire. They're starting to interview sophomores and juniors in college now. I can't afford to pay an analyst $300,000 plus a bonus." "It's very difficult to hire and compete with Ken Griffin or Dimitri or any of these guys. We have a lot of respect for them. We admire them greatly. We've studied them. We don't try to compete with them." "Whereas pods have been lengthening the type of trades they do in terms of weekly, monthly, we tend to like dynamics that are 6 to 18 months in length, and even above that."
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This is great — thanks @Ritholtz
Balyasny's founder Dmitry Balyasny on what a $50 million trader pay package actually is: "If you have something that says Trader XYZ lost $50 million, that sounds like a giant number, but you have to remember, we're managing $28 billion." "A typical portfolio manager might be managing a couple billion in gross market value. So that's 2.5%, which is not good." "That pay package is composed of lots of different things." "It might include a guarantee for the time that the person is out of the market. It might include a budget for hiring out their team." "And it also might include extra upside incentives which are only paid out if the person delivers a certain amount of P&L." "Usually with that type of number, you're budgeting that person to generate P&L of one hundred million plus a year."
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Great line: "The fact that we're debating about a bubble means there's a bubble. If people are trying to explain away a bubble, there's a bubble. It's that simple."
Ex-Point72 Head of Prop Research Kirk McKeown on the simplest bubble test there is: "What's my body of work that I can look back to for bubble dynamics? It's obviously the internet bubble, the housing bubble." "You can look back to the Great Depression. Sorkin just wrote a piece on it." "You need a corpus of knowledge that you can draw on, you don't have to ask a robot for. So read the books, do the work." "Having a competitive advantage takes work. And it's not asking a chatbot. It's reading a book." "The fact that we're debating about a bubble means there's a bubble. If people are trying to explain away a bubble, there's a bubble. It's that simple."
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Citadel's CEO Ken Griffin on why there are 'almost certainly' bubbles in AI, and why that's normal: "So the big picture is there's almost certainly bubbles within this moment in time. And any radical transformation of our economy is generally intertwined with a bubble." "I remember back in 1999, 2000, the metrics that we used to value Internet companies. And let's be clear, some of these Internet companies had pretty fanciful business models." "But I mean, I just wish I'd kept my Amazon stock from that moment in time." "And the Internet, which was the great bubble. Could it be more of a part of our daily life today than it is?" "What's left in the wake of these bubbles is often game-changing for the world. And the companies that are on the other side of that bubble are the market leaders for decades to come."
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Balyasny's founder Dmitry Balyasny on what a $50 million trader pay package actually is: "If you have something that says Trader XYZ lost $50 million, that sounds like a giant number, but you have to remember, we're managing $28 billion." "A typical portfolio manager might be managing a couple billion in gross market value. So that's 2.5%, which is not good." "That pay package is composed of lots of different things." "It might include a guarantee for the time that the person is out of the market. It might include a budget for hiring out their team." "And it also might include extra upside incentives which are only paid out if the person delivers a certain amount of P&L." "Usually with that type of number, you're budgeting that person to generate P&L of one hundred million plus a year."
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Citadel's Head of Global Equities Justin Lubell on why Citadel doesn't mind when two of its investors land on the same idea: "One of the great advantages that we have at Citadel is that we don't worry if people do agree. It's not a problem for us." "We have a really large capital base, and the positions that we can take because of that can be large." "If one person has a great idea and another person discovers the same great idea, if it's that great, we would love to own twice as much. If it's really great, we would love to own three times as much." "So we don't actually look to make sure that there is diversity of thought. We want there to be the best thought."
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Ex-Point72 Head of Prop Research Kirk McKeown on the simplest bubble test there is: "What's my body of work that I can look back to for bubble dynamics? It's obviously the internet bubble, the housing bubble." "You can look back to the Great Depression. Sorkin just wrote a piece on it." "You need a corpus of knowledge that you can draw on, you don't have to ask a robot for. So read the books, do the work." "Having a competitive advantage takes work. And it's not asking a chatbot. It's reading a book." "The fact that we're debating about a bubble means there's a bubble. If people are trying to explain away a bubble, there's a bubble. It's that simple."
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A badly run store. One brilliant candle display. Pabrai on Sam Walton’s habit of learning from anyone. Mohnish Pabrai explains: "Every single thing at Walmart came from somewhere else. Everything was copied." "He meets Sol Price, looks at Price Club, says 'No-brainer.' He sets up Sam's Club." "Walmart came from Kmart." "'There is no human who has stepped into more retail stores of my competitors than I have. And no human after me will ever beat that record.'" "A manager says 'Sam, that was such a poorly run operation.' Sam says: 'Yes, but did you see the candle display?'" "Sam said, “You can learn from anyone. You can learn from the biggest idiot operator.”" "He'd go 5:30 in the morning to the distribution centers with donuts, sit with the drivers, and ask: 'What do you see when you go in?'"
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Balyasny's founder Dmitry Balyasny on the 2008 redemptions that took half of Balyasny's capital: "When Lehman went under, we made the decision to go to cash." "For the next three or four months, people just wanted their money." "I remember sitting waiting for the money to come in from the brokers, and they're like, no, no, the wire is coming, the check's in the mail. We're like, it's not here. Day after day, it's not here." "We wound up getting hit with redemptions for probably close to 50% of our capital. And we decided not to gate people, as we were liquid, and just didn't think it was the right thing to do when we could pay them the money that they needed." "So we had to reach into our pockets and put more money into the firm." "Then investors came back, and they appreciated that you gave them the money when they needed it and treated them fairly."
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Prompts vs. embeddings: AQR's Managing Director Peter Hecht "You literally ask ChatGPT or Claude, is Apple cheap or expensive? Give me your analysis and give me the details why you think it's cheap or expensive. That's prompt, okay?" "Then there's a way of using a large language model where you feed in documents, financial documents, broker reports, earnings reports, and you go under the hood of the large language model and you take what we call a word embedding, which is a numerical representation of the text." "When we use large language models, we're doing the latter. We're not doing the prompt-based approach." "All of the special sauce is not in the large language model. The fact that you can get a numerical representation of the data is sort of a commodity." "The hardest part is can you find whether that numerical representation of the data can predict future returns." "That is very difficult to do, requires a ton of skill and it's highly subjective. And that's why I don't think there will be convergence."
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