"A wise American hedge fund manager once said..." | quant trading clips

Tribeca
Joined June 2026
NO CRYING IN THE CASINO retweeted
Hedge Fund Manager David Orr (@orrdavid) on why he backed a game show winner with no credentials: "I think that people aren't actually focused on just the simple answer of, like, what's this guy's edge. They're not willing to look outside and pick unusual people." "In our case, one of our guys won a TV game show." "He doesn't have any credential at all. He didn't work in any of the big shops or banks or anything." "I'm fine hiring him because his personal account Sharpe for a few years is two point something, so we'll give him a shot." "You could be a delivery guy, but if you're killing the market, I'll give you a shot. It could be anybody."
Hedge Fund Manager David Orr (@orrdavid) on why he’ll back a delivery guy over a Harvard grad, as long as the track record is real. David Orr runs Militia Capital, a ~$480M hedge fund. ~50% annualized, Sharpe 2. “If you didn’t go to Harvard, they’re not going to give you money. They’re gonna lead you on for years.” We cover: - Edge is just reps. He's placed a few hundred independent bets every year since 2019, more in one year than a lot of hedge fund managers get in a decade. - The two-hour rule: if he can't decide on a stock in an hour or two, he skips it. When a trade goes against him, he quits. "The market said I'm wrong, I'm wrong." - 500 positions in his partition and zero notes. Some of his best shorts are down 40% and he's forgotten what the company does. - The Gogo lesson: he spent 100 hours on a short and was right on the fundamentals (it's now $2), but it ripped to $20 first. All that research made him stubborn on the way up. - The AI risk system: it groups the book into custom baskets like "Banks Done Right" and "yield traps," recalculated daily. A 25% bet can quietly become 45% in two weeks. - How Militia recruits PMs: 95% of track records are junk, and one cherry-picker ran 30 accounts and sent the best one. The PMs who make it include a game show winner, a Spanish government worker and a programmer, with 0.15 cross-correlation. - The best short seller in the world, quietly: 40% a year short only for years, and he still gets a tiny allocation at his fund. - Why multi-managers' real business is marketing. Collect $2B a year in fees on $100B and it's "mission accomplished," whatever the returns. - The long/short tax trick: harvest losses on losing shorts, and never cover one that's down 90%. No tax is due until it's delisted, which can take 10 years. - $150M raised from one email asking LPs for $100M. He says he could raise a billion but won't, and admits they "must have gotten at least somewhat lucky." - His AI stock map: hyperscalers locked customers into take-or-pay deals at ~35% return on capital. If compute prices crash 80%, the end customers get wiped out, not the hyperscalers. - Is investing 99% talent? For big alpha, almost entirely. Pod shop alpha is teachable, maybe for 1 in 50 people rather than 1 in 10,000. Highlights: 00:00 Intro 00:44 How AI custom factor baskets track dynamic correlation in levered portfolios 03:24 Sourcing non-consensus PM talent and verifying live Sharpe track records 07:24 Structuring carry and tax deferral to attract elite proprietary traders 12:50 Why institutional multi-manager platforms fail to back pure alpha 20:22 The two-hour research limit: Avoiding sunk-cost bias in short selling 27:58 Momentum screening vs deep value: Why top longs hit new highs 29:40 Why traditional finance books fail and what operator biographies teach 37:16 Why rapid technological adaptation beats traditional economic moats 39:26 Analyzing the AI trade: Why hyperscalers offer superior downside protection 44:57 Internalizing stock borrow desks to maximize net-of-fee fund compounding 55:25 Avoiding confirmation bias and why shorting revenue growth fails 01:01:42 Pod shop leverage factories vs raw discretionary alpha generation 01:07:12 Unplugging from market narrative feeds to preserve independent conviction
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Quitting trend following at the worst time: AQR's Managing Director Peter Hecht "In 08 it actually did well. So that's actually why everyone got in after 08." "If trend following is based on underreaction to news, if there isn't much news, there is very little to underreact to." "A lot of people got out of trend following after holding it for 10 years and it was sort of mediocre, and they got out in 2021, and in 2022 the industry was up, let's call it 30% or 40%." "Sometimes holding it with equity beta is a way to force discipline." "If you're just holding managed futures standalone and it's just having two, 3% returns, you're sort of like, ah, is that a good use of my capital?"
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Slugging vs. hit rate: Balyasny's founder Dmitry Balyasny "If you contrast it with high frequency trading, which is a hit rate type of business, you're going to have 99% of your trades going to be profitable or a tiny loss. You've got to do tiny, tiny, tiny, and repeat, repeat, repeat." "We have 170 investing teams at the moment. When you hire an investing team, chances are, depending on their track record, maybe 75% of them will wind up working out." "If you can control the risk, you might lose 10 million, 20 million, 30 million on somebody who doesn't work out, but the ones that do work out, they'll hopefully be with you for 10, 20 plus years, and you might make hundreds and hundreds of millions off of them." "In order to enable the slugging, you have to have very well-defined risk boxes within which people will operate, to enable them to bet on the things that they're really good at betting on and try to exclude as much of the other stuff as possible." "For every strategy, we'll have stops, vol targets, vol limits, stress limits, liquidity limits, et cetera."
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Answer every question before it's asked: Citadel Securities' Technology COO Jeff Maurone "For 50 years, the process of sequencing amino acids into folded proteins was a bottleneck on biology research." "Researchers would spend quarters, sometimes years, folding just a single protein until Demis Hassabis and the team at DeepMind fundamentally changed this." "Using models, they reduced that process from years to call it six or seven weeks." "Even though they were using a model to accelerate the process, it still worked first in, first out." "Instead of working that way, why not just fold every single protein we've ever seen?" "More than 200 million proteins folded, became an incredible resource that changed biology forever." "Using what is essentially an early form of agents, rather than answer questions when they arise, but to preemptively answer every possible question before it is asked, is one of the real emerging ways that we are seeing AI and agents being used to achieve incredible results."
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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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The 55% hit rate: AQR's Managing Director Peter Hecht "In stock selection, the way it ends up working on average is, let's say, if we're right about 55 percent of the time, we hit our target return." "So that means 45 percent of the time we're wrong." "Let's say one year we were 52 percent right and we hit our target return." "Let's say we're having a bad year and you must be like, well, instead of 52%, you must be at 37%. No, we're at 49%." "The difference between hitting your target return or having a good year versus a bad year, it's small, right? It's a small edge." "It's not like we're right 80% of the time. It's more like low 50s, mid 50s for our stock."
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Small edge, high reps: Balyasny's founder Dmitry Balyasny "A simple way for folks to think about it is like a casino. The edge that a casino has is relatively small." "When you have millions of people coming through the casino, their earnings are very consistent, because they have a little bit of an edge, and any one player might win, which keeps people coming back." "You need high enough reps to put the statistics in your favor." "How do you optimize your trading efficiency to lower the slippage, your cost of moving the stock when you're buying or selling, execution costs?" "You still might only have a 55% chance of being right, but you're not gonna lose that much if you're wrong and you'll make a lot if you're right, because your view is sufficiently variant." "If it does happen, it's a big surprise to the market and the security gets repriced."
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The out-of-sample gauntlet: AQR's Managing Director Peter Hecht "Start off with an economic thesis on why this signal should predict returns." "Let's say you first test your hypothesis in U.S. large caps and it works. Then we're going to say, all right, but your theory also says it should work in U.S. small caps. Let's test it there." "It should work in European markets. It should work in Japan. Let's go grab European markets and test it there and in Japan and Australia. It should work in emerging markets." "Some of our signals, if they predict a single name stock, maybe they should also predict country level indices like the S&P 500 versus the FTSE versus the Nikkei." "So we're always pushing the data with all of this out of sample verification, even though we're starting with sort of an economic foundation, to try to minimize the chance that we're just finding patterns in randomness."
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The three traits that scale a PM: Balyasny's founder Dmitry Balyasny "The things I look for are how does the person respond to adversity. Because if they had an amazing track record before they got to you, you can be certain they'll have a drawdown once they're here." "You need people who have the perseverance and mental fortitude to use the difficult periods to re-underwrite what they're doing, come up with some fresh ideas, improve their process, improve their team, as opposed to pack it in." "A real learning, adaptive type of mindset, where they're constantly looking for better ways to do things and aren't overly wedded to a particular trade style approach." "The folks that are really scaled over time are ones that have a business building DNA." "They enjoy hiring people, they enjoy managing people, they enjoy running their own business within a business, and those kind of folks do a better job of scaling over time."
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The airline problem for GPUs: Citadel's CEO Ken Griffin "GPUs, like airlines, have a very low marginal cost to run. Like the incremental seat on an airline that's not full, if you can sell that ticket for $20, you're making money in that seat." "That's one of the reasons that the airline industry is such a nightmare: the moment you have overcapacity, pricing goes into freefall." "We saw this actually with the telecom build out back in 2000." "We built more fiber than we had demand for, and the price of telecommunications just went straight down." "If we reach a point where the provisioning of GPUs exceeds demand for GPUs, marginal pricing will actually go into free fall. And that really upends all the investment assumptions that people are working with today." "Right here, right now, there's people that are earning extraordinary pricing on GPUs that are five or six years old. That probably doesn't persist for another five or six years."
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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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Probability bets, learned at the poker table: Point72's founder Steve Cohen "I did play poker every day in high school." "We were playing poker at about 5:30 in the morning the day of my SATs. Like nobody cared." "It really taught you how to take risk, right? Because I didn't have a lot of money in my pocket. I mean, I wasn't a rich kid. And so I had to win. And so that's pressure when you have to win." "It teaches you how to take probability bets, right? I mean, when you play, when you fold, how do you raise, all that type of stuff." "It became not about the money, it became about, you know, just making good probability bets, which is sort of what I do in the markets."
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Forward rates aren't predictions. They're the back end of an arbitrage-free process — and conflating the two gets him angry. Harley Bassman, creator of the MOVE Index, on ReSolve Riffs (Sept 2025). Rates below are an illustrative example, not live quotes. Harley Bassman explains: "You're advising grandma. She has $10,000. The one-year CD is at 3%, the two-year at 4%. What do you tell her?" "I can earn 4% for two years, or 3% the first year. What do I have to earn the second year so the two periods equal 4%? That's the forward rate." "Ignoring compounding, it’s five. I get five, I get three, that’s 4%." "So the question is: do I think the one-year rate will be above or below 5 a year from now? That's all there is to it." "People talk about forward rates as a prediction. That's false. It is not a prediction." "When people say that, it kinda gets me angry." "It's not a prediction — it's the back end of an arbitrage-free process."
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Offense vs. defense on risk: Balyasny's founder Dmitry Balyasny "We have additional risk conversations as much as we have reduced risk conversations, offense versus defense." "Oftentimes some of the higher Sharpe performers who are very consistent tend to be very defensive on risk." "So we're always working with them on how do you really scale what you're doing, and trying to build their confidence to take more risk, to make them more meaningful overall." "On the flip side, you'll have other folks for whom whatever amount of risk you give them, it's never enough. The next day they want more. And that's fine, that's a good mindset." "But you also need to figure out when they're a little bit too far over their skis."
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The casino model of diversification: AQR's Managing Director Peter Hecht "First off, we believe in diversification. So we are a systematic fundamental manager." "Most systematic managers have a small edge for any single security that they trade." "Like a casino, a casino would never exist if it could only play blackjack against you, one person." "They bring in thousands of uncorrelated blackjack customers. That's like bringing in thousands of uncorrelated trades." "So we believe in diversification. We're militant about thinking about: are these trades correlated with each other?"
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NO CRYING IN THE CASINO retweeted
militia capital, a hedge fund reporting 48.3% annualized returns, has an unusual habit: its portfolio managers avoid comparing how they invest. david orr says they deliberately avoided those conversations even when the team got together in new york. “we try not to get correlated” he thinks preserving their independence matters more than picking up another manager's process. if everyone starts using the same inputs and signals, another manager may add much less diversification causing worse overall returns.
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"If you want to get into trading for the excitement, don't do it for a living. You're in the wrong game." From former Tudor quant PM Tom Costello (@tcoste110): "One big idea, and it turned into quite a bit of money. It was a very, very profitable strategy over the years I ran it." "But for eight years of it, it was just in the mud up to your elbows, wrestling with making sure that it squeezed as much alpha out of the markets as it could." "It was, frankly, dull work, kind of work that I appreciate, because I think excitement is wildly overbid in finance." "Nothing I like better than making a nice steady profit every single day." "Go to work in Silicon Valley, find an exciting job in venture capital. Don't do it in trading, because there's an excess of excitement."
Replying to @JohannMarkov
Boring is the goal. “Excitement is way over bid in finance.” Said some guy someplace… once.
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"You have to surrender yourself somewhat to the machine." Asness on why he slowed AQR into ML — and what the edge costs in interpretability. AQR’s Cliff Asness at iConnections Global Alts New York in June 2025. Cliff Asness explains: "We invested the money into researching it, so it’s not like we were like, “This ain’t gonna work. This is stupid.”" "We've had a philosophy for years of combining economic common sense, theory, intuition." "What we were doing had to make sense to us and had to work historically." "Out of sample is better, real-life trading is better, backtests are secondary — but you need to understand why it works." "I slowed that down somewhat because machine learning can't do that." "You have to surrender yourself somewhat to the machine. If not, what's the machine doing?" "It's finding patterns you couldn't see with simple theory or even the naked eye." "I usually say partially surrender — sometimes that word gets dropped."
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Citadel's CEO Ken Griffin on why 'hedge fund deleveraging' is the excuse that stops you learning: "So everyone's favorite go-to answer when they're losing money is hedge funds are de-leveraging." "In fact, in the last 10 years, I've seen the entire industry de-leveraged to zero at least 10,000 times. Just imagine if these hedge funds ever levered back up." "And the reason that people love that answer is it actually washes your hands of accountability." "Let's take a step back. What prices are changing and why? What don't we understand? Because the minute I start to use an excuse, I actually stop learning." "So I always want hedge fund deleveraging to be answer number 10 on the list of answers. And I want one through nine to be, okay, what don't we understand? What does somebody else get?"
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Carver’s 2009 bank trade: conviction in the idea, then panic that cut his intended position by 90%. Rob Carver, systematic trader and author, recounting his Q1 2009 UK bank-share trade in an April 2021 interview. Rob Carver explains: "Q1 '09, it felt like we were at the bottom. Best place for my money: UK banking shares, massively beaten down." "I understand banks as a business and can read the balance sheets, whereas with an insurance company I'd struggle." "It was a discretionary decision, but a good one. The problem is when it came to pulling the trigger, I panicked." "My timing was perfect. I probably was within like 3% of the bottom, something like that." "I could not force myself to buy the size I'd intended. I cut everything by 90%, bought one-tenth of the position." "Those shares probably went up by something like 350% in six months." "Even if you make good trading decisions, you still need a system to manage your risk and position size." "If you do think you can make those discretionary calls, you should still have a system in place to size them."
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