Olivia: What if the greatest money-making machine in history wasn't built by a Wall Street guru, but by a world-class mathematician who never took a single finance class? A man who believed that financial markets, for all their chaos, moved in orderly ways—just not ways humans could see. Jackson: And when we say the greatest money-making machine, we’re not exaggerating. We're talking about a company whose signature fund, since 1988, has generated average annual returns of 66 percent. That’s after fees. To put that in perspective, it absolutely dwarfs the records of legends like Warren Buffett, George Soros, or Ray Dalio. This is the story of Jim Simons and Renaissance Technologies. Olivia: Today, we're diving into Gregory Zuckerman's incredible book, "The Man Who Solved the Market." It’s a story that’s part financial revolution, part human drama, and it reveals a central, fascinating paradox: the man who built this empire, who is now worth over $23 billion, was the last person anyone would have expected to do it. Jackson: Exactly. He was a total outsider. And that’s the core of our podcast today: an exploration of the epic battle between a radical, data-driven vision for markets and the messy, unpredictable, and ultimately inescapable forces of human nature. Olivia: We'll dive deep into this from two perspectives. First, we'll explore The Misfit's Blueprint: how an outsider's mind, forged in code-breaking and pure math, completely upended the world of finance. Jackson: Then, we'll uncover The Human Glitch in the Perfect Machine, looking at the dramatic stories of how emotion, conflict, and even tragedy shaped this revolutionary system. It’s a story about algorithms, but it’s really a story about us.

Olivia: To understand how Simons pulled this off, you have to understand the man himself. And he is, by all accounts, an enigma. He is intensely private. He once explained his aversion to publicity by quoting the donkey from Animal Farm: "God gave me a tail to keep off the flies. But I’d rather have had no tail and no flies." That’s Jim Simons. Jackson: He just wants to be left alone to solve the puzzle. And the puzzle of his life started early. There’s a fantastic story from when he was 14, working at a garden supply store. He was so lost in his own thoughts that he kept misplacing everything. The owners laughed when he told them he wanted to study math at MIT. But the book notes, "The skepticism didn't bother Jimmy. The teenager was filled with unnatural confidence." Olivia: That confidence is the key. He had this deep, unwavering belief in his own mind. His father gave him some crucial advice early on, after regretting his own career choices. He told Jim, "The lesson was: Do what you like in life, not what you feel you ‘should’ do." And what Jim liked to do, more than anything, was think. He was a ponderer. Friends would see him lying down, eyes closed for hours, just mulling over problems until he arrived at these original solutions. Jackson: And that’s the classic outsider’s mindset. He wasn’t just smart; he had a different way of approaching problems. It reminds me of what Henry Ford used to say about why he never hired "experts in full bloom." Experts are great, but they also know all the reasons why something won't work. They’re constrained by existing knowledge. Simons was operating in a space of unknown unknowns. The only way to find out if his radical idea was possible was to just try. Olivia: And his big idea was forged not on Wall Street, but in a top-secret government-funded organization called the Institute for Defense Analyses, or IDA. In the 1960s, during the Cold War, he was hired to be a code-breaker, cracking Soviet communications for the NSA. Jackson: So he’s literally in the business of finding hidden patterns in what looks like pure noise. Olivia: Precisely. And at the IDA, he was struck by their unique management style. They didn't hire for specific expertise; they hired for raw "brain power, creativity, and ambition." The assumption was that if you get enough brilliant people in a room, they'll find important problems and be clever enough to solve them. This became the exact blueprint for his future hedge fund. He wouldn't hire finance guys; he'd hire mathematicians, physicists, and computer scientists. Jackson: People who could see the world as a system of rules, not just a series of stories in the Wall Street Journal. Olivia: Exactly. And while at the IDA, he and his colleagues wrote a classified internal paper that was, in hindsight, the Rosetta Stone for Renaissance Technologies. It was called "Probabilistic Models for and Prediction of Stock Market Behavior." In it, they proposed a method of trading they claimed could generate annual gains of at least 50 percent. Jackson: Which is eerily close to the 66 percent they eventually achieved. Olivia: It is. And here’s the revolutionary part. They completely ignored what they called "the fundamental economic statistics of the market"—things like earnings, dividends, corporate news. All the stuff traditional investors live and die by. Instead, they proposed searching for a small number of "macroscopic variables" that could predict the market's short-term behavior. They didn't try to explain why the market entered certain states. Jackson: That is so hard for humans to do. We are narrative creatures. If something happens, we need a story to explain it. If we don't have one, we make one up, even if it's wrong. They were trying to completely remove that impulse. Olivia: The book makes a brilliant analogy. It says that for most investors, this was an unheard-of approach, but gamblers would have understood it perfectly. A great poker player can tell an opponent is bluffing by their behavior—a twitch, a bead of sweat. The player doesn't need to know why the opponent is nervous. They don't need the backstory. They just need to identify the mood and bet accordingly. Jackson: They just need the signal. Not the story. Olivia: That was the core idea. Simons and the code-breakers proposed treating the market the same way. Find the signals, ignore the noise and the narratives, and bet. It was a blueprint for a thinking machine, one that could see the market's mood without getting caught up in its drama. But having the blueprint and actually building the machine are two very different things. And that’s where the human glitch comes in.

Jackson: So he has this perfect, rational blueprint. A system free of human emotion and bias. But the great irony, and this is where the story gets truly dramatic, is that the biggest obstacle to building this emotion-free machine was… human emotion. Specifically, his own. Olivia: It's a recurring theme throughout the book. He’s a man of immense self-confidence, but he's also plagued by self-doubt. After a string of early losses in the 1980s, long before the massive success, he confessed to a colleague, "Sometimes I look at this and I feel like I'm just some guy who doesn't really know what he's doing." He was haunted by the idea of failure. Jackson: We all go through that. The difference is, he persisted. That’s the real story of this book. It’s not just genius; it’s relentless, brutal persistence through decades of struggle and doubt. Olivia: And that struggle wasn't just internal. It was in the system itself. There's a hilarious and terrifying story about one of their first computerized trading models, which they called the "Piggy Basket." It started making money, so Simons poured more capital into it. Then, one day, the system went haywire. Jackson: What happened? Olivia: It started buying potato futures. Millions and millions of pounds of Maine potatoes. The model, for reasons no one could understand, had decided potatoes were the single best investment on Earth. They were buying so much they were on the verge of cornering the global potato market. The regulators from the Commodity Futures Trading Commission called Simons, completely bewildered. "They think we’re trying to corner the market on spuds!" Simons exclaimed. They were forced to liquidate, losing millions. Jackson: So the perfect machine had a bit of a potato problem. It shows the fallibility. A model is only as good as its data and its assumptions, and sometimes it can lead you to a very strange place. Olivia: It completely shook their confidence. But the most telling story, the one that truly captures the human glitch, happened in 1990. By this point, they had a more sophisticated system, one that was working. It was the brainchild of Simons and his brilliant partner, Elwyn Berlekamp. The core principle was short-term trades, making thousands of small bets with a slight statistical edge, like a casino. Berlekamp’s mantra was, "If you trade a lot, you only need to be right 51 percent of the time." Jackson: The law of large numbers. It’s a beautiful, logical system. Olivia: It was. And it was making money. Then, in August 1990, Iraq invaded Kuwait. The world was on edge. And Jim Simons, the man who wanted to build a system free of human gut feelings, had a gut feeling. He became convinced they needed to buy gold. Jackson: Oh no. He’s trying to meddle with the machine. Olivia: He starts calling Berlekamp constantly. "Did you see gold? It went up! We should be loading up here." Berlekamp was baffled. He said it was Simons who had pushed to remove humans from the loop, to rely on the scientific method, not gut instinct. And now, at the first sign of global turmoil, Simons wanted to throw it all out and trade based on his feelings. Jackson: This is the ultimate paradox. He builds the system to protect himself from his own biases, but he can't stop himself from trying to outsmart it. It’s a classic founder's dilemma. Olivia: It is. And it got even stranger. Years later, after they had developed even more advanced machine-learning techniques, Simons still struggled. He’d look at the trades the computer was generating and complain, "I can't get comfortable with what the system is telling me. I don't understand why. It's a black box!" Jackson: That is so revealing. "It's a black box." He wanted the results of a system that could see more than a human, but he was uncomfortable when he couldn't fit its logic into a simple human narrative. He wanted the magic, but he also wanted to understand the trick. Olivia: His colleague, René Carmona, had the perfect response. He just said, "Just follow the data, Jim. It’s not me, it’s the data. It works. Humans can't forecast prices, let the computers do it." Jackson: That was the leap of faith. He had to go from being the creator of the machine to being its first and most disciplined user. He had to learn to trust the ghost in his own machine, even when it scared him. That internal battle, between the intuitive, story-telling human and the cold, logical system he built, is the real drama of this book.

Olivia: So when you step back, you see these two powerful, conflicting forces at play. On one hand, you have the Misfit's Blueprint—this radical idea that markets could be solved with math and data, an idea born from a mind that refused to accept the conventional wisdom of Wall Street. Jackson: A blueprint built on the core belief that human behavior, especially under stress, is predictable. As one of their researchers put it, "Our entire premise was that human actors will react the way humans did in the past… we learned to take advantage." They weren't trading stocks; they were trading human nature. Olivia: But on the other hand, you have the Human Glitch. The story is a constant reminder that no system is perfect because it’s built and operated by imperfect humans. From the potato fiasco to Simons’s own battle with his gut instincts, the human element was always there, threatening to derail the entire project. Jackson: It’s a fascinating tension. The firm’s success came from its ability to systematically exploit the cognitive biases of other investors. Yet, its biggest internal threats often came from the very same biases cropping up within its own walls—ego, fear, the desire for a simple story. They built a fortress against irrationality, but the call was always coming from inside the house. Olivia: And that internal conflict extended beyond just trading. The latter part of the book details the deep political rift between Simons, a major Democratic donor, and his co-CEO Robert Mercer, who became one of Donald Trump's most influential backers. It nearly tore the firm apart, proving that even a $100 billion money machine isn't immune to the passions and divisions of the outside world. Jackson: It all comes back to that central struggle. Can you build a perfect system in an imperfect world, with imperfect people? The answer seems to be yes, but it requires a level of persistence and self-awareness that is almost superhuman. Olivia: In the end, Jim Simons did step back. He turned his focus to philanthropy, funding massive projects in autism research and mathematics education. He found new, even bigger puzzles to solve. Jackson: And he left behind some simple, but profound, life lessons. One of them really stuck with me. He told an audience: "Be guided by beauty. It can be the way a company runs or the way an experiment comes out. There's a sense of beauty when something is working well." Olivia: That’s a lovely way to think about it. The elegance of a system that just works. Jackson: It is. And it leaves us with a powerful question for our own lives. We all try to build systems—for our work, for our health, for our relationships. We create plans and set rules to protect ourselves from our own worst impulses. But the real test comes in moments of stress or uncertainty. Are we brave enough to trust the elegant logic of the system we designed? Or do we let our own human glitches—our fear, our ego, our need for a comforting story—get in the way and meddle with the machine?