Alix Pasquet has run Prime Macaya Capital Management for about a decade, built out of a career that started at the poker table and the backgammon board rather than a trading desk.
Most fund managers describe their edge in terms of research hours or a proprietary model. Pasquet describes his as knowing which market participants are behaving irrationally, and exploiting it.
"There's three main forms of competitive advantages in the investment business. Analytical, where you analyze better than somebody else. Informational where you get better information than somebody else. And then behavioral."
He learned to read group psychology by playing backgammon and poker before he ever ran money, then spent time inside a top quantitative fund to see the same behavioral edge applied with institutional scale and data behind it.
I listened to the full interview so you can skip it. 1 hour 33 minutes of audio, 19 minutes of reading.
Here are the 11 principles that matter.
👤 Guest: Alix Pasquet, Founder and Portfolio Manager of Prime Macaya Capital Management, who has run the firm for about a decade after a career shaped by backgammon and poker
🎤️ Host: Ethan Kho, who hosts Odds on Open and holds a master's in financial engineering from Columbia
📰 Published: 10 September 2026 on YouTube (Odds on Open)
🔴 YouTube | 🟣 Apple Podcasts | ⏱️ 1 hr 33 min | ✅ Time saved: 1 hr 14 min
Key Takeaways
There are only three kinds of edge in investing — analytical, informational, behavioral — and behavioral is the one that survives longest
His favorite example: a gas station chain that also sells good pizza, which most Upper East Side hedge fund managers can't evaluate because they aren't the customer
Reading outside finance is itself a competitive advantage, because the investment business is short on vocabulary for things like timing
Stan Druckenmiller's own answer for timing was "technical analysis and liquidity considerations" — and Pasquet thinks most fundamental investors don't have an answer at all
A top quant fund taught him that data has to be scrubbed before it's trusted, and that a trade needs a temporal stop, not just a financial one
Small funds should not compete with multi-strategy pods on data, hiring or research spending — his rule is "play weaker players"
Idea generation runs through a deliberately unbalanced network of investors, a tracked list of 100 CEOs, and what he calls the female test
He credits female friends with flagging Lululemon and a Canadian retail brand years before either showed up on his screens
He uses a "bull-bear debate" to argue the opposite side of his own short positions, because individual behavior is a weak signal and group behavior is a strong one
Only four hedge funds, by his count, ever published an honest postmortem of the roughly $40 billion lost in Valeant Pharmaceuticals
Technical analysis is a behavioral tool, not a stock-picking tool — and a business with a genuinely expanding moat should show it in the chart
Over-reliance on AI will produce the worst generation of portfolio managers in a decade, because it blunts the five core analyst skills: recall, visualization, reading between the lines, leap of judgment, and synthesis
The future belongs to bionic analysts who pair analog training with digital tools, not to either skill alone
A personal competitive advantage starts with knowing what gives you energy, and pairing an extrovert with an introvert on the same idea is how a firm gets what he calls 10-baggers instead of one person's blind spots
Margin of safety is a personal-finance principle as much as an investing one — the investors he respects most are the ones who stayed frugal after they got rich
1. The Three Kinds of Edge
Pasquet opened with a framework he returns to throughout the conversation: every advantage in investing is analytical, informational or behavioral, and only one of the three holds up over time.
"There's three main forms of competitive advantages in the investment business. Analytical, where you analyze better than somebody else. Informational where you get better information than somebody else. And then behavioral."
Behavioral does not mean better-behaved than other people. It means being positioned to exploit the uneconomic behavior of other market participants, which he says is a distinct skill from simply avoiding your own biases
His clearest example of a behavioral edge is what he calls the customer-investor mismatch. A broad base of investors looking at a company may not be its customer, so they misprice it out of unfamiliarity rather than analysis
Early VCs largely missed Facebook's value because they weren't college students. Pasquet said broader understanding of the business only arrived once the platform opened up past its original college-only email restriction
His own firm's version of the same trade is a gas station chain that also sells pizza. "If you tell that to your average Upper East Side hedge fund guy and you say you bought pizza at a gas station and it's good, they can't even understand that concept, because they're used to New York usually high-level $45 pizza." He said the returns on capital at the chain are incredible
On analytical edge, his main point is about moats. "There's a sort of a tendency in the investment business to think of moats as either static or defensive when you should think of a moat as dynamic and then offensive"
On informational edge, he points to crossover funds that invest in private companies competing against public ones they hold — access he says most public-equity investors never build because they rely on brokers to make introductions instead of doing it themselves
The last point on edge is that markets adapt, so any single advantage is temporary. Pasquet said a firm has to keep rebuilding its team, tools and process to find new edges as old ones erode
2. Reading as an Edge
Asked whether he's learned more from investing books or from other fields, Pasquet said both matter, but for different reasons — and that most of the value now sits outside the investing canon.
Investing books teach the shared vocabulary of the business — the reference cases every PM and analyst already knows, and the historical context needed to recognize when an industry is actually changing
But he said fundamental investors are missing an entire vocabulary for things other fields have already solved, timing being his clearest example. Asked what they use for timing, he said most answer "we don't time," while traders answer differently: "We use technical analysis"
He brought up Stan Druckenmiller, who once answered the same question with "technical analysis and liquidity considerations" — and Pasquet believes the follow-up question about what "liquidity considerations" actually means either wasn't asked or was edited out for competitive reasons
"There is no substitute today for having read the right books not only on investing but also on group psychology, systems thinking, sports, the military, intelligence," he said, arguing that mental models borrowed from outside fields can be applied to markets even when investing itself has no equivalent
His example: he says the investment business has learned more about hiring from the National Football League than from its own field
His reading list for the investment canon: One Up on Wall Street by Peter Lynch, You Can Be a Stock Market Genius by Joel Greenblatt, a Cunningham-compiled collection of Warren Buffett's writing, books by Robert Hagstrom, Michael Mauboussin's essays including Expectations Investing, Reminiscences of a Stock Operator, Jack Schwager's interview books, and Steven Drobny's books
Outside investing, he pointed to books on psychology, sales and intelligence work. He said most value investors underrate sales as a discipline, and that businesses today behave like intelligence agencies toward their competitors whether they admit it or not
3. Inside a Top Quant Fund
Pasquet worked at what he describes as a top quantitative fund earlier in his career, and said the lessons from that period still shape how his fundamental fund operates.
The first lesson was that the fund's edge was itself behavioral, just executed at scale. Its systems and tools were built to exploit the same kind of uneconomic behavior Pasquet says his own poker and backgammon background trained him to notice — but applied across small caps, mega caps, commodities, bonds and currencies alike
The second was the importance of talent and how to manage it. He said the firm hired people so talented it "wasn't uncommon for me to feel, intellectually inept when I was around them," and that the founder was as skilled at motivating and incentivizing staff as he was technically
The third was data integrity. Acquiring proprietary data is itself a barrier to entry, but the harder skill is scrubbing it, because a data-entry mistake can look like a market inefficiency to a quant model that isn't built to tell the difference
The fourth was cost discipline — watching transaction costs, leverage costs and market impact closely enough that a trade's edge isn't quietly eaten by the cost of putting it on
The fifth was the temporal stop. "It was very important to have a temporal stop, right? And that temporal stop, if you're in the trade and you haven't made money in a certain period of time, you needed to get out." He said this forces a fundamental investor to revisit a thesis on a schedule rather than only when the price moves against them
4. Quant Lessons, Applied
Pasquet said the most useful habits he took from the quant fund weren't models, but discipline around data and precision.
Management-supplied data deserves natural skepticism, because management teams have an incentive for investors to interpret it a certain way. He recounted a CEO once telling him, "you have really high conviction on your point of view right now based on data that I've given you or not given you" — and admitting the CEO was right to flag it
His firm aims for direction, not accuracy, when it uses quantitative models. "Whenever the quantitative models are pointing a certain way, that's good enough for us," rather than chasing false precision
He warned against what he called a "quantification fetish" spreading through the industry — a false sense of conviction that crowds out qualitative judgment, which he said is exactly where machines still struggle
He does not try to compete on proprietary data with pods that can outspend him on it. The firm's edge, in his account, is knowing what not to chase rather than matching every data advantage a larger competitor can buy
5. Don't Fight the Pods
Asked how a small fund competes with multi-manager platforms that can out-hire, out-spend and out-trade it, Pasquet reframed the question around what his firm deliberately avoids rather than what it does.
"The goal is you have to step back a second. 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."
He does not compete for the same junior talent pods are hiring, which he said now includes interviewing sophomores and juniors in college and paying analysts $300,000 or more including bonus. "The analytical turnover inside these shops is high enough that you get to hire them perhaps afterwards," he said, treating the pods' own churn as his firm's recruiting pipeline
He does not compete on holding period. Where pods have lengthened toward weekly and monthly trades, his firm tends to run positions over six to eighteen months or longer
He does not compete on research spending. Larger hedge funds pay Wall Street banks for one-on-one management access at conferences — sometimes paying more just to get the first meeting — and his firm has built a process with no requirement to meet management teams, buy proprietary data, or hire from specific schools at all
The strategy, as he put it, is about trade-offs: "Let them have that. We'll be right here."
6. How He Generates Ideas
Idea generation, Pasquet said, starts with the observation that the best filter for a flood of information is other smart people rather than software.
He cited Philip Fisher's Common Stock and Uncommon Profits, in which Fisher found that close to 80% of his best ideas came from other investors — a pattern Pasquet said holds broadly across the industry
His network is deliberately not homogeneous. A network concentrated in one style or sector leads to crowded positions, so he keeps relationships across long-short, long-only, different ages, countries and geographies — including, he said, a French trader who is one of the best he knows at trading U.S. midcaps
A tracked "top 100 list" of CEOs is a second pillar. "You have to track what we call the top 100 list. And that's a top 100 list of CEOs that you think are really, really good. And when they say something, study it." He argued opportunities are attached to people, not floating freely, so tracking the people is how you find the opportunity
Thematic collisions matter more than single themes. "I think the insight there that matters is it's not that a theme is powerful is that when two themes collide they're really powerful and that's where it creates businesses that could have what Charlie Munger called the Lollapalooza effect." His example is the collision of an aging global population with robotics
Conferences are a fourth source, and he described crashing industry events without a badge earlier in his career before eventually being invited by the same organizers who'd let him in for years
The female test is a fifth idea source. "We call the female test. You want to find out what's a great product, whether it's in retail, fashion or others, ask your female friends." He credits a date for flagging Lululemon years before it was on his radar, and a separate tip from a female friend — later reinforced by one of the best stock pickers he knows — on a Canadian retail brand he wouldn't name for compliance reasons
His last idea-generation habit is asking interns to circle recurring charges on a personal credit card statement and check which ones are public companies, on the theory that understanding a product as a customer is the fastest route to understanding the business
7. Using People as Indicators
Pasquet's most distinctive process tool treats other investors' positions and convictions as data, not just company fundamentals.
The core tool is the "bull-bear debate." He and his team will deliberately argue the bull case against their own short position, or debate another short seller by taking the opposite side, specifically to test whether they're holding on for economic reasons or for institutional and emotional ones
Cross-referencing an idea across many people surfaces leading and lagging indicators. He credited investor Rob Citrone with naming the practice on a podcast appearance: "One PM scales is cross referencing an idea. And when you cross reference an idea and you get a sort of 360 review from the idea and you compile, you'll learn a lot from the individual conversations. When you compile the aggregate conversations, you're actually going to see what was the leading indicators and what were the lagging indicators."
He used Valeant Pharmaceuticals as a case study in how rarely the industry actually does this honestly. Hedge funds lost a combined estimated $40 billion on the stock, and he said only four funds have ever published an honest postmortem explaining why they were wrong. "Most people just move on," he said, twice
The book he cites for building an indicator framework is The Art of the Long View by Peter Schwartz, which he said supplies the processes for turning individual conversations into a broader read on timing
8. The Case for Charts
Pasquet said he used to dismiss technical analysis entirely, until two people close to him — his business partner and a private investor at a major macro fund — reframed it for him as a behavioral tool rather than a forecasting one.
"There is no greater competitive pleasure than hearing really, really smart people say, I don't do technical analysis."
His argument is that technicals reveal what other market participants — many of them algorithmic — are doing, regardless of whether the chart predicts anything on its own. "So, if you're in a stock and it breaks a sort of technical level, you better have the staying power because it is going to crash and go down even more than you actually think"
He does not use it to generate ideas. "You got to use technical analysis, you got to use liquidity considerations, you got to use fundamental work, you got to use behavioral work, you got to set up what's called in the industry a mosaic of advantages"
A genuinely expanding moat, in his view, should be visible in a strong chart, not just in the fundamentals — and a stock that is falling despite a supposed moat is a signal worth taking seriously rather than dismissing as noise
He pointed to William O'Neil's CANSLIM methodology from How to Make Money in Stocks as underused by value-oriented analysts, citing O'Neil's finding that only about 2% of traders he studied were able to buy stocks making new highs, even though the best-performing stocks are usually the ones doing exactly that
He argues the hedge fund industry trains analysts to be analysts rather than future portfolio managers, and that O'Neil's framework is one of the few outside resources built to make that transition, because it forces analytical thinking about risk, reward and timing rather than research alone
9. Where Analysts Are Going
The back half of the conversation turned to what Pasquet sees as the central risk facing the next generation of analysts: AI tools that make research faster while quietly eroding the skills research is supposed to build.
He said he is "willing to be proven wrong" but believes that over reliance on AI tools is going to create the worst portfolio managers that we've ever seen a decade from now.
He named five core analytical skills he says AI overuse blunts: recall of past competitive patterns, visualization of how an industry structure will play out, reading between the lines of what a CEO actually means versus says, the "leap of judgment" that connects a narrow problem to a bigger one, and synthesis of all four into a thesis
A firm that cuts junior hiring because AI replaces their output loses more than headcount, in his view. "You know what a culture really needs? Juniors. They ask the naive question. They give you energy." He tied his own firm's culture explicitly to training the next generation rather than automating around them
"The future of the analytical community is a sort of bionic. Somebody that knows how to use the analog tools and somebody that knows how to use digital tools," he said, describing the ideal analyst as combining deep, tool-free thinking with fluency in AI
He compared today's AI adoption to earlier waves of AI entering games and fields with "wicked environments" — intelligence, the military, backgammon, poker, chess, Go — where the technology made severe, repeated mistakes before it matured, and argued markets are exactly that kind of nonlinear, non-stationary environment
He connected the July drawdown among AI-heavy funds directly to this blind spot. "All the people that literally made their businesses into artificial intelligence were all down 10 15% in July because their tools didn't pick up on what was going on," referring to a leveraged position unwinding that few market participants saw coming, his own firm included
He recommended science-fiction reading — Iain Banks's Culture series and Orson Scott Card's Ender's Game — as a way to internalize both the strengths and blind spots of AI systems before relying on them professionally
10. Building a Personal Moat
Asked how a young analyst without access to old-style mentorship builds a defensible personal advantage, Pasquet returned to a framework he uses with his own team: know what gives you energy, then pair it with someone who's wired the opposite way.
He starts with introversion and extroversion. "It helps to know what gives you energy first. A lot of my personal moat tends to reside around the fact that I'm an extrovert. What gives me energy is people." He does his field research and talks to people before he ever opens a model, precisely because that's the part that energizes rather than drains him
"The power pair concept is very important. If I'm an extrovert, I want an introverted dork with me doing the work together. If he's a slow decision maker, I'm a fast decision maker." He said pairing complementary strengths — rather than hiring people who think like you do — is what produces outsized returns rather than incremental ones
He calls the friction that comes from pairing opposite personalities "leadership tension," and says a leader's job is managing that tension toward resolution rather than eliminating it
Building analytical, informational and behavioral edge on offense follows the same three-part framework from earlier in the conversation, applied to a career rather than a single trade
He argued your network becomes your moat over time, because most hedge funds are structurally fragile businesses — dependent on assets that can leave on short notice, with little terminal value — and a durable network is one of the few things that compounds independent of any single fund's survival
11. Margin of Safety at Home
Pasquet closed by applying an investing concept directly to personal finance: margin of safety, the idea Benjamin Graham built around buying a dollar for less than it's worth.
"The one concept I would apply in a really big way is margin of safety."
He argues a personal margin of safety works the same way a business's does — a frugal lifestyle leaves room to act when things change, rather than being trapped by fixed overhead when an opportunity or a threat appears. "I always say to guys like," he tells people, "put at least three to five years away of personal cash because markets are markets" and you don't know what's going to happen
He described watching a colleague's boss — a multi-billionaire long-short manager — fly coach on a six-hour flight to a conference rather than upgrade, specifically to avoid being seen spending on comfort he didn't need
High personal overhead, in his account, is what stops people from noticing threats and opportunities in the first place, because attention gets consumed by the cost of maintaining a lifestyle rather than freed up to act
He cited a Brazilian saying he lives by: coffins don't have drawers, live, but don't be stupid either
He was careful to distinguish frugality from tight-wad behavior, and said the goal isn't austerity for its own sake but keeping enough slack that a market shock or a career setback doesn't force a bad decision
Pasquet's closing case is that the same discipline that separates a durable investing edge from a temporary one — behavioral awareness, margin of safety, knowing your own wiring — applies just as directly to the analyst building a career as it does to the fund picking a stock.
Bonus Insights
He credits Julian Robertson's Tiger Management with an underrated legacy: how many people it launched into their own firms. "It is a godsend and a blessing that so many people left Julian Robertson and made fortunes multi-billionaires. I could name 12 of them," he said, framing it as the kind of culture worth building rather than a loss to be minimized
He is a believer in personality typing despite the skepticism it draws. He said critics dismiss frameworks like Myers-Briggs without ever studying the perspective they offer, and noted that certain personality types show up disproportionately among the very wealthy — while acknowledging a friend calls the framework "astrology for nerds"
He thinks business schools have a blind spot on hiring. Asked at schools he visits whether there's a class on hiring talent, he said the answer is consistently no, despite it being one of the most important skills a portfolio manager needs
His own path into investing came through recognizing a strength he didn't know he had. He said he was unconsciously competent at reading psychological dynamics from years of backgammon and poker, and only realized it was a professional edge once friends kept pointing it out
Products, Companies & Tools Mentioned
Facebook (Pasquet's opening example of the customer-investor mismatch: early VCs weren't college students, so most missed the platform's value until it expanded past .edu email addresses)
Lululemon (Found through what Pasquet calls the female test — a date mentioned it years before it showed up on his screens)
Books & Resources Mentioned
Common Stock and Uncommon Profits – Philip Fisher (Pasquet's source for the statistic that close to 80% of Fisher's best ideas came from other investors)
One Up on Wall Street – Peter Lynch (Part of what Pasquet calls the investment canon, read for shared vocabulary and reference cases)
You Can Be a Stock Market Genius – Joel Greenblatt (Same canon list)
The Letters of Warren Buffett, compiled by Cunningham (As Pasquet named it; likely Lawrence Cunningham's Essays of Warren Buffett compilation)
Reminiscences of a Stock Operator – Edwin Lefèvre (Canon reading, alongside Jack Schwager's and Steven Drobny's interview books)
Expectations Investing – Michael Mauboussin and Alfred Rappaport (One of the Mauboussin works Pasquet says every analyst should read)
The Art of the Long View – Peter Schwartz (Pasquet's source for turning cross-referenced conversations into an indicator framework; he hedged on the author's name)
How to Make Money in Stocks – William O'Neil (Source of the CANSLIM methodology and O'Neil's finding that only 2% of traders he studied bought stocks at new highs)
The Culture series – Iain Banks (Elon Musk's recommendation, per Pasquet, for understanding an AI that occasionally works against the humans it serves)
Ender's Game – Orson Scott Card (Pasquet's second AI-literacy recommendation, citing the novel's AI companion character)
If this was worth your time, send it to someone who has to have a view on this.
Get the latest market chatter as it happens: