Founders - #387 Jim Simons Built The World’s Greatest Money-Making Machine

Episode Date: May 1, 2025

Jim Simons never took a single class on finance, wasn’t interested in business, and didn’t start trading full time until he was 40. The company he founded —  Renaissance Technologies — has made over $100 billion in profits.Starting out with the heretical belief that there was a hidden structure in financial markets, Jim decided to staff his “crazy hedge fund” with mathematicians, computer scientists, and physicists. He went to great lengths to collect more historic financial data than anyone else, spent a lot of time recruiting “killers” (people with single minded focus that wouldn’t quit), invested heavily in computers (and the people who ran them), and designed the most collaborative work environment.Jim was a world-class mathematician, code breaker, exceptional manager of people with exceptional minds, a genius in system design, and deeply understood the power of incentives. He was also incapable of giving up, willing to endure a decade of struggle and pain, and hell-bent on doing something “historic” with his life.Jim Simons lived a life defined by persistence, unconventional thinking, and an unwavering pursuit of excellence. Studying his life and work is time well spent. This episode is what I learned from rereading The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution by Gregory Zuckerman. ----Ramp gives you everything you need to control spend, watch your costs, and optimize your financial operations —all on a single platform. Make history's greatest entrepreneurs proud by going to Ramp and learning how they can help your business control your costs and save more. ----Founders Notes gives you the ability to tap into the collective knowledge of history's greatest entrepreneurs on demand. Use it to supplement the decisions you make in your work.  Get access to Founders Notes here. ----Join my free email newsletter to get my top 10 highlights from every book ----Founders Notes gives you the ability to tap into the collective knowledge of history's greatest entrepreneurs on demand. Use it to supplement the decisions you make in your work.  Get access to Founders Notes here. ----“I have listened to every episode released and look forward to every episode that comes out. The only criticism I would have is that after each podcast I usually want to buy the book because I am interested so my poor wallet suffers. ” — GarethBe like Gareth. Buy a book: All the books featured on Founders Podcast

Jim Simons published a list of five guiding principles that he used throughout his career. The second principle that he listed was, Surround yourself with the smartest people you can find. When you see such a person, do all you can to get them on board. That extends your reach and terrific people are usually fun to work with. It's actually reminding me of Jeff Bezos. From day one in his very first shareholder letter, Jeff Bezos emphasized the importance of

having the very best team. And he wrote, setting the bar high in our approach to hiring has been and will continue to be the single most important element of Amazon's success. Bezos is focused on talent is just like this quote from Steve Jobs that happened in an interview that Steve gave that very same year in 1997. Steve said, I think that have consistently figured out who the really smart people were to hang around with. You must find extraordinary people. The key observation is that in most things in life,

the dynamic range between average quality and the best quality is at most 2 to 1. But in the field that I was interested in, I noticed that the dynamic range between what an average person could accomplish and what the best person could accomplish and what the best person could accomplish was 50 or 100 to one. Given that, you're well advised to go after the cream of the cream and build a team that pursues the A plus players. That is exactly what Ramp did.

Ramp is now the presenting sponsor of this podcast and Ramp has the most talented technical team in their industry. Becoming an engineer at Ramp is nearly impossible. In the last 12 months they hired only 0.23% of the people that applied. This means that when you use Ramp you now have top-tier technical talent and some of the best AI engineers working on your behalf 24-7 to automate and improve all of your business's financial operations and they do this all on a single platform. Ramp gives your business easy to use corporate cards for your entire team, automated expense reporting and cost control.

Ramps corporate cards are fully programmable. The longer that you use ramp, the more efficient your company becomes. This is very important because as Sam Walton wrote in his autobiography, you can make a lot of different mistakes and still recover if you run an efficient operation or you can be brilliant and still go out of business if you're too inefficient. Ramp helps you run an efficient organization. In the end of that interview, Steve Jobs added one thing.

He said, a small team of A plus players can run circles or run a giant team of B and C players. Jim Simons and the team that he builds is a great example of this. They outperform everyone else in their industry and they do it with a small group of A players. From a customer's perspective, what does a team of A plus players sound like?

It sounds like this customer review, which I read, which said, ramp is like having a teammate who you never need to check in on because they have it handled. Make history's greatest entrepreneurs proud by going to ramp.com to learn how they can help your business today. That is ramp.com. Jim Simons created the world's greatest money-making machine.

To do so, Simon shows a different approach. A world-class mathematician and former code breaker, Simons had a hunch that financial markets moved in orderly ways, just not in ways that could be detected with human intuition and insight. Simons believed that collecting and analyzing data could provide an advantage and that automated trading was possible. Working from a ramshackle office in a Long Island strip mall, Simons hired mathematicians, physicists, and computer scientists to amass reams of historic records

and develop algorithms to process it all. His team hunted for patterns hidden deep in the numbers that might reveal long sought rules governing markets. After decades of struggle, his data-driven approach paid off. Since 1988, Renaissance Signature Medallion Fund has generated average annual returns of 66%. They have made more than $100 billion,

and Simon's is worth more than $23 billion. That was an excerpt from the book that I'm going to talk to you about today, which is The Man Who Solved the Market, how Jim Simons launched the Quant Revolution and is written by Gregory Zuckerman. So in addition to reading the book, I also read every single long form piece that I could find on Jim. And I listened to every single interview that he gave when he was alive. He just passed away recently. I want to jump right interview that he gave when he was alive, he just passed away recently.

I wanna jump right into his early life and we see right away this reoccurring theme that you and I talk about over and over again, it's in all these biographies, the fact that belief comes before ability. By the time Jim is 14, he starts to say out loud to other people that he's just really in love with math and his idea was that I wanna go study math at MIT. And when he told people this the people around him some of the people around him

actually laughed at him and that didn't seem to bother Simon's at all says he was filled with exceptional confidence and an unusual determination to accomplish something special he was like that when he was a kid he's like that his entire life that is gonna be another main theme that's that's a really important thing that runs throughout his entire life and his entire career. This is what he was saying later on in life about well the self-belief that he had when he was a young man. He says, I realized I might not be spectacular or the best but I could do something good. I just had that confidence. One of the most important things that he learned from his dad,

one of the last interviews he gave a few years before he died talked about what a lovely man that his dad was and how much he learned from him and he admired him. And one of the things that Jim learned from his dad was what not to do. And his dad actually had a job that he loved and he was a salesman at a movie studio. He loved the work but then he left that because he went to go work in his father-in-law's shoe factory and he left that because he went to go work in his father-in-law's shoe factory. And he did that because he said he felt obligated to join the family business. Later in life, the book says, he told his son he wished he hadn't foregone a promising and exciting career to do what was expected of him. This is what Jim said.

The lesson was, do what you like in life, not what you feel you should do. It's something I never forgot. And so what Jim liked to do most was think and most of the time he was thinking about math. And you also see that he has a very strong personality. He had this when he was a kid and we'll also see that his way till we get to what his future mother-in-law observed about Jim when Jim was like 19 years old, 20 years old. So what Jim would like to do says he sat with his thoughts for long stretches of time.

When he was a kid, he would climb into a tree and sit there and think. His mom would have to get him down from the tree and encourage him to play with the other kids. Unlike his parents, specifically his dad, Jim was determined to focus on his own passions. So he does indeed go and study math at MIT. He graduates in three years, he gets a degree in math from MIT, and then he goes to the University of California Berkeley to get his PhD in mathematics. And while he's working on his dissertation, while he's working on his PhD, this is when he starts getting interested in markets. And he was obsessed

with math, he knew he was going to be a mathematician, but he also had another obsession from early from an early age and that was an intense and persistent desire to get wealthy and that's what spawns this interest in markets. So while he's in grad school, he actually starts getting up. He says he began getting up early to drive to San Francisco so he could be at the Merrill Lynch offices by 730 a.m. in time for the opening of trading in Chicago. So he is interested first in commodity markets. For hours, he would stand and watch prices flash on the big board, making trades while trying to keep up with the action. It was a rush, he said.

His wife gets pregnant, he's working on his dissertation, and eventually he has to reluctantly stop trading. But there's a great line in the book. It says, but a seed had been planted. And then when I got to this section of the book, I left this note to myself. It's like, there's no way that this guy was gonna stay in academia.

He has this persistent and burning desire to be wealthy, and as it becomes obvious later, to be the best at what he is doing. But what I found so interesting about this, he's around 23 years old at the time. It's over 17 years from this point in his life that he starts. He actually leaves academia and starts trading full time. So I want to go back to this idea. I've already mentioned a few times that Simons had a persistent

and burning desire to be wealthy. There is a bunch of quotes in the book, in these interviews, in these long New Yorker pieces, stuff he says when he's younger, stuff when he says he's older, this is ever-present. So I arranged all these different quotes from all these different sources to just give you an idea. He says, it's nice to be very rich. I observe that. I had no interest in business, which is not to say I had no interest in money. In fact, it's really funny, he gave this interview when he was about 84 years old, and he says,

I enjoy being wealthy, I enjoy having my boat and my airplane and two houses. This was also stated by him, but also people around him from his early age, they said he hungered for true wealth. His first wife, he gets married really young. I think his wife is 18 at the time, I think Jim's like 19 or 20 when they get married. And this is what she said about Jim. She said, Jim understood at an early

age that money is power. He did not want people to have power over him. Another person, this is again repeated across several people about Jim through the decades. Jim had this insatiable urge to make money. He likes action. And so we see very early on in his life, this was not a person that was gonna stay on a track. When they said, you know, he wants action, he has this insatiable urge to make money. When he doesn't see a path that way, he kind of freaks out. In fact, the book says that in his early 20s he actually experiences an existential crisis. So he's teaching at MIT, he's also teaching at Harvard, and it says, Simon's began questioning his future.

The next few decades seem laid out for him all too neatly. Research, teaching, more research, more teaching. Simon's loved math, but he also needed adventure. He seemed to thrive on overcoming odds and defying skepticism. Remember that part for when he starts trading. And he did not see any obstacles on the horizon. Is this it? Am I going to do this in my whole life? There has to be more. Again, we see that this persistent and burning desire to be wealthy, it's already pulling

on him realizing if I stay on this path, I'm not going to also achieve the other goal. Now there is a hint. Here's this hint I mentioned earlier that Jim had a very strong personality. I think this is also important because one of the main lessons of the book is that, and it's something that he repeats over and over again, that you must, you absolutely must work with the smartest and high world class smartest, best and world class people that you possibly can. And he's able to manage really maybe better than almost anybody else in the world. All of these world-class, very

strong personalities. I don't think you could do that without having a strong personality yourself. And we see that he had a strong personality, again, when he was, when people were laughing at his, what he wanted to do in life when he was 14. And then we also see it's noticed by his mother-in-law. So he gets married early. His first wife, her name is Barbara. Like I said, I think she's 18 when they get married.

Barbara was too young to wed, her mother insisted. She also worried about a potential power imbalance between Barbara and her self-assured fiance. Listen to what his mother-in-law, the advice that his mother-in-law gives to her daughter. Years later, he's going to wipe the floor with you. Later on in the book, Barbara says that her mother was right. They're married for 13, 14 years. They wound up getting divorced. So at 26, he decides to quit teaching and he joins an elite research organization called the Institute of Defense Analysis. It's also referred to throughout the book as the IDA. So he's going to talk about this over and

over again. This is a very important part of his life. One, he said what was appealing about them. They paid him a lot more money than he was making teaching. And two, you could spend half your time pursuing your own interests. And so the IDA, what they would do is they were hiring top mathematicians all across the country to assist the national security agency, so the NSA. And what the NSA wanted the IDA to do is they wanted to break the Russian codes. So this is during the Cold War. This is why they reference anytime you read anything about Jim, they'll reference him as a mathematician and a code breaker. They're talking about this part of his life. Now, the reason I wanted to include this and tell you

about this, because this is actually, there's a lot of valuable lessons that you see that Jim learns here when he's in his mid 20s, that he'll use later in life. Now, this is the second time I read the book. I think the first time I did it was episode 108 or something like that, so maybe like five years ago. But there's ideas from the book that have stuck with me the entire time. And this is actually an idea that I lifted from a book that I used,

and it's remarkable how well it works. So people would come into like Jim's office at the IDA and they would think that he'd be like laying in the dark on a couch and they thought he was asleep and they didn't realize this is the way he would think. He says, Simon's realized he had a unique approach, mulling problems over in his mind until he arrived at original solutions. Friends noticed him lying down, eyes closed for hours at a time. He was not asleep. So the idea that I took from him is, I will sit in a room and I'll usually have an eye mask.

He didn't have an eye mask. I'll put an eye mask and I'll put an earplug so I don't hear anything, right? And then all you do is sit there and just think. You have no input. And when you're not looking at anything and you're not listening to anything, it's remarkable how many ideas flow

or how many solutions flow into your mind. It says he was a ponderer with imagination and the instinct to attack the kinds of problems that might lead to true breakthroughs. After he passed away, his wife gave this interview and she would talk about it. You could notice when he wasn't there. He'd be in his presence, but his jaw, like his eyes would just focus on the wall and he just like he's staring at the distance and then like his jaw, he'd like grind his jaw on the wall and he just like he's staring at the distance. And then like his jaw, he'd like grind his jaw. And just like that's when he was in deep and thought, usually about mathematics. So again, he was a little kid in the tree thinking about math.

And you know, he's an 85 year old man still thinking about math. So while he was at the Institute for Defense Analysis, this IDA, half the time he worked on his own projects. This is again, go back to what he was doing. You're supposed to be working your dissertation and you're waking up early in the morning and you're driving right all the way to the Merrill Lynch offices and you're trading commodities all day. So he has this idea is like, okay, is there they write this paper and they try to figure out it's like, can we make money in the markets not using the conventional methods?

Let me just read this, read this section too. The paper didn't try to identify or predict these states using economic theory or other conventional methods, nor did they seek to address why the market entered certain states. This why, just remember that part as we go through this, he struggles with understanding he doesn't want to rely on human intuition. He wanted this from, from even before there was technology existed to do this. He wanted this completely automated, such a money making machine. This is really how I think about it.

That did not rely on human beings at all. And yet over and over again, over the decades, he's constantly can't wrap his head around, hey, I built this automated system. It's analyzing all this historic data. It's suggesting all these trades. And then it takes him maybe decade, decade and a half to get comfortable in realizing he's, it's impossible to understand why the system is doing what it's doing, but I have to put my trust in the system. So it says, for the majority of investors, this was an unheard of approach, but gamblers would have understood it

well. Poker players surmise the mood of their opponents by judging their behavior and adjusting their strategies accordingly. Players don't need to know why their opponent is glom or exuberant to profit from those moods. They just have to identify the moods themselves. Simons and the Code Breakers proposed a similar approach to predicting stock prices. So Jim is 26, 27 years old at the time he is doing this. Remember, now it's gonna be 13 years, he's going to be 40 years old before he finally leaves and does this full time. So this is, I always say true interest is revealed early. We see that he's really interested in math, that he loves this deep thought,

that he likes these collaborative research environments working with the very best people. Essentially he looks at the way the IDA was organized. He's gonna do this when he builds Stony Brook's math department for 10 years, and you realize, oh, he's doing the same thing over and over again, he's just changing the goal. So we'll get there in a minute. This is really one of the most important,

Jim's most important skills, and just as you do this random sentence from a colleague that worked with him at the IDA, and again, once you latch onto the sentence, and you look at how he spends, you know, the next 50 years of his life life you realize he does this over and over again. Simons was a terrific listener. It's one thing to have a good idea it's another to recognize when others do. There's a great line in this.

If there was a pony in your pile of horse manure Jim would find it. And then in a wonderful twist of irony at 29 29 years old, he is going to be fired for seeking policy. The reason I think this is a wonderful twist of irony is because he's one of the most secretive people and Renaissance technology is one of the most secretive institutions. Secrecy is embedded into the company DNA. So he winds up writing this is the time of the Vietnam War. He was completely against it. He says over and over again, I thought this was a very stupid idea. It was a very stupid war, a bad use of our resources.

And so he writes a letter to the editor of the New York Times protesting the Vietnam War and then he gives an interview for a reporter at Newsweek and saying, hey, I'm going to stop working on defense department tasks until the war is ended. Once his boss found out about this interview that he gave, Jim says, I was fired five minutes later. Now, he also says something that's really funny, that, this is a direct quote from Jim, he says, getting fired can be a good thing.

You just don't wanna make a habit of it. And at the time, he's kinda freaked out because he's 29 years old, doesn't have a lot of money, and he has three young children. He had little idea what to do next but getting fired so abruptly convinced him that he needed to gain some control over his future He wasn't quite sure how to though. So he kind of downplays He's like, you know, I'm not the best mathematician in the world, but he's one of the best Yeah, and so he's immediately this is very unusual Stony Brook is Stony Brook University is trying to build a world-class math department.

So they hired Jim at 30 to build, they have a large budget, and they essentially give him a mandate to build a world-class math department. This is what I meant, that he uses the same ideas over and over again. This is where he learns how to recruit and manage top mathematical minds.

It's gonna be a pay dividends when he starts building Renaissance technologies. And he talks a lot about the kind of people he wants to work with. This is what he says, Simon's developed a unique perspective on talent. He valued killers. This is how he defines killers, by the way.

Killers are those with a single minded focus who wouldn't quit. And he talks about this, there's guys and then there are real guys. You want the real ones. And so this is a crazy thing. I think it's around 2010. They're making five billion a year,

six billion a year, seven billion a year, four billion a year in cash, year after year after year. And it's not like they can reinvent, they sweep it and they push out in dividends. They're doing that with like 300 people. The estimates I've seen anywhere from as low as 250 people, all the way up to 410 people.

That is not a massive company. And one of the way he does this is because it's so hard to get hired there. And then there's also low company turnover, low employee turnover, which is, as a direct result in my opinion on how he designed, he's a really genius systems designer. He has a fundamental understanding of

like how powerful incentives are. But again, it goes to like you can only do that if you have, if every single person on the team is world class. If there are guys, then there are real guys. You want the real ones. He assembled one of the world's top centers, hiring 20 mathematicians while learning to identify the nation's best minds and how to recruit and how to manage them. So this skill, again I cannot overstate this, the skill of recruiting and managing the smartest people in the world is going to be one of the most important foundations for everything that's gonna happen in Jim's life. Let's say he's 30 now for the next 56 years of his life. In 2020, few years before he dies, he writes down his five guiding principles, which I'll go over later.

But I'm going to introduce principle number two right now, because this is directly related to what he's learning at Stony Brook, what he picked up on at the IDA as well. He says, surround yourself with the smartest people you can find. When you see such a person, do all you can to get them on board. That this extends your reach and terrific people are usually fun to work with. So that is one of his guiding principles. This also ties to something else he said on the podcast, the fact that he thought his father was a very lovely man

and the most important thing, remember his dad was a salesman, recruiting his salesmanship. The thing that he taught me was that salesmanship is very important. Now Jim is a much older, wealthier man. He goes, he says, it turns that salesmanship is very important. Now Jim is a much older, wealthier man. He goes, he says, it turns out salesmanship is very important. And so he says, I spent a lot and he emphasized a lot, a lot of time courting talent.

Talks about this over and over again throughout the decades. I like to recruit. My management style has always been to find outstanding people and let them run with the ball. This continues in another interview. My idea of leadership is of an organization is to hire the very best people you possibly can. I have good taste in people.

There's this great New Yorker piece I'd highly recommend reading, but it talks about that Simons was an exceptional manager. So this guy named Peter Brown, who is now the CEO. Jim recruits him, I think in like 93, 92, 93. I'll talk about this guy. It's really important, the insight they had there. But Peter Brown, who's now Renaissance CEO, in this piece, he talked about what he thought, like, why was

Simon so effective? Says Jim's genius was in seeing the possibilities for quantitative trading long before others did, and setting up a company in which he provided outstanding scientists with the resources, environment and incentives to produce. His role was more in setting the general direction of the company than in developing the technology. He said, working for Jim, this is such a great insight. Working for Jim, you had the feeling that you had better produce because he had pretty much removed every excuse for not producing. He had pretty much removed every excuse for not producing. He had pretty much removed

every excuse for not producing. So that is later on in life. We're not there yet. At this point, he is still, this is the most fascinating thing about this because this guy's brilliant and yet even for somebody this brilliant, he's still fighting against what he really wants to do. And this is, he's a very much an outsider, very much you know comfortable with trusting his own judgment much more so than most people. And yet he's still doing kind of what's expected of him. He's still a mathematician.

He's still running this department. He's still staffing up. He's still working in academia, but he's fighting against this. He wants to be wealthy. He wants to do something great. He wants to do something historic. And this is not like I'm not surmising it. He says it over and over again.

When he was a young person, he wanted to be the whatever he did. He wanted to be the best. He wanted to have adventure. He wanted to do somethingising it. He says it over and over again. When he was a young person, he wanted to be the whatever he did. He wanted to be the best. He wanted to have adventure. He wanted to do something historic. I'll say it over and over again. And you see that he's making a mistake that I think a lot of people do. I've certainly done this when I was younger as well for sure. You can't fight against your job.

So he's three years into building Stony Brook's math department. Remember he starts at 30, going to leave at 40. He's 33 when he takes a sabbatical year. Why does he take a sabbatical? He wants to undergo primal therapy. Okay, why, what is taking place inside your mind if you need to do this? Right, you and I can read between the lines here. So it takes a sabbatical year so you could go undergo primal therapy. What the hell is primal therapy? It was approach involves primal therapy? His approach involves screaming or otherwise articulating repressed pain, primally as a newborn emerging from the womb. Simons, who sometimes woke up screaming at night, was intrigued by the approach. He's fighting

against his job. He is 33. Finally, at 40, seven years later, he makes the jump. This is something I, these notes, it's really fascinating because I think I've told you this before. I'll go through the book. I read my, reread my notes. I don't know, five, six, seven times before I sit down and talk to you. Because when you're reading the same thing over and over again, you notice how the story ends. You have, you can have different interpretations. Now you know where this is going. And so if you look at, when you're looking at the book, you look at all the post-it notes I left to myself. It's like oh this guy's an outsider. He's very comfortable trusting his own judgment and He loved his dad. He admired his dad

He said his dad was a lovely man, but this is good that he didn't listen to his dad here Isn't this amazing how many times this is coming up on? these The people that you know have been studying this the last few weeks Michael Dell Phil Knight now we see Jim Simons You know no, you know, no, no, don't, don't take the risk. Like take the sure path. In Michael Dell's case, like stay at University of Texas, go to medical school, do what's expected of you. You know, Phil, Phil Knight, I didn't send you to Stanford graduate school business to be jackassing. This is what his dad said, jackassing around and being some shoe salesman. Like what are you doing? Again, I'm not trying to insult his father by any means but his dad would even say much even after

Jim's starting to get wealthy you know I much prefer saying you know my my son the mathematician my son the professor than my son the businessman so 1978 Simon's leaves academia to start his own investment firm focusing on currency trading Simon's father told him he was making a big mistake giving up a tenured position. Mathematicians, this is why I keep talking about the importance of trusting your judgment, the fact that he was an outsider,

everybody around him. Mathematicians kind of look down, especially people in academia, his peer group, right? His friends, these people, they go to his house, they spend time with his kids. They're like, what are you doing? You're a true brilliant, you're squandering your talent to go work in business.

He thought it was like kind of gross. Mathematicians were even more shocked. The idea that he might leave to play the market full time was confounding. Academics were convinced that he was squandering a rare talent. We looked down on him. Nuts, like he'd been corrupted

and he sold his soul to the devil. Simons had never completely fit into the world of academia. This is what he says. I always felt like something of an outsider no matter what I was doing. That's gonna be really important because even though when he jumps into the finance industry, he's an outsider in finance. He's not interested in what other people in the industry are doing. In fact, he kind of looks down upon them.

This is really important. For decades, other people told Jim what he was doing wasn't going to work, that it was low status, and it was not important. Jim was a misfit. He was a rebel. He's an outsider, comfortable trusting his own judgment and the results of his own thinking. And I'm gonna go, I'm gonna introduce another one of his five guiding principles. Guiding principle number one. This is advice that you clearly took. He's giving to others that he clearly took himself. It's really important.

Number one, do something new. Do not run with the pack. I am not such a fast runner. This is still Jim talking. If I am one of N people working on the same problem, there's very little chance I will win. If I can think of a new problem in a new area, that will give me a chance. There is literally no one else doing what Jim wants to do. In fact, to this day, I talked to a bunch of other people in finance.

They're like, people still don't even understand how he's done it. And this is, he's in 1979. But when I got to that guiding principle, do something new, don't run with the fact. It reminds me of, you know, Edwin Land, Steve Jobs here, I've become a personal hero of mine. He had a personal motto. He said, don't do anything someone else can do. If you were just copying somebody by default, you know, Edwin Land, Steve Jobs hero become a personal hero of mine. He had a personal motto. He said, don't do anything someone else can do. If you were just copying somebody by default, you are copying something you're admitting

that you're already losing. It takes so much courage to do what Jim is doing at this point in his life. This is an excellent line by Gregory Zuckerman describing this. The odds were in favor of a 40 year old mathematician embarking on his fourth career hoping to revolutionize the centuries old world of investing. So why would he do this? It's so important to understand the personality, same personality type that he had when he was younger. He wants to do something special, he wants to do something important, whatever he did he wanted to be the very best at it. This is on his decision to leave academia and build a firm. He needed a new challenge and a bigger canvas.

Simons told a friend that solving the market's age old riddle and conquering the world of investing would quote, be remarkable. There's another, a few pages later, it says something very similar. Simons told a friend that he wanted to do something that would go down in the record book, something historic. And to do so you have to have some level of self confidence. Go back to, I love what Michael Dell said in his autobiography

talking about you know at 19 years old with no money in his dorm room at the University of Texas decides to take on the most valuable company in the world. IBM was the most, had the highest market cap, been accompanying the world at the time. And he says was I a little full of myself at 19? He says, yeah, I was. He goes, I think you have to be to do anything special. When I read that section of the book, I told you something that Nolan Bushnell,

who was Steve Jobs' mentor and the founder of Atari said, said only the arrogant are self-confident enough to press their creative ideas on others. We see a very similar theme with Jim Simons. Until then, Simons had dabbled in investing, but he hadn't demonstrated any special talent. Somehow though, he was bursting with self-confidence. This is something he repeats over and over again. Remember what he said earlier? I just had the confidence. I just had it. So this is Jim's initial premise. He says, it looks

like there's some structure here. I just have to find it. Simon's decided to treat financial markets like any other chaotic system. There must be some way to model this, he thought. And so another thing I'm going to get to is the fact that he's going to have to churn through a series of several partners. And I'll get to the fact that he possesses something that they don't and it's not intelligence, it's belief and conviction. So he's raising money at the very beginning, he's going to have to raise money from outside investors. He tries to raise 4 million, falls slightly short of that.

They're like, okay, well, whatever, we're gonna launch the fund. And they're at the very beginning, they start the fund relying on a trading system that combines mathematical models, complicated charts and still human intuition. Remember this is 1979. So him and his first partner, they start trading

currency. So they kept buying British pounds and the currency kept soaring. They followed that move with accurate predictions on the Japanese yen, the Dutch mark, the Swiss franc, gains that had investors calling Simons with congratulations and encouragement as the fun grew by tens of millions of dollars from a $4 million start. Okay. Simons was having a blast exploring his lifelong passion for financial speculation while trying to solve markets, perhaps the greatest challenge that he had ever encountered. The fun would not last.

The fun would not last. Remember, this is 1979. So the Medallion Fund, which is really the way to describe it is a private money machine for Simons and his employees. That doesn't start until 1988. And then the historic run that the Medallion Fund will go on, which still is continuing to this day,

doesn't start until 1990. So we are 11 years before that. And when I'm going through and just how he churns through all these different approaches, all these different partners, all these different structures over the next decade, decade and a half, I didn't know if myself was like, the man who solved the market, the book should be called The Man Who Persisted, the man who was determined to solve this problem, the

man who was determined to figure it out. Because every time he'll have, he talks a lot about the influence of luck. He goes, I don't come to the office every day and think, oh, how smart am I going to be today? He says, how I think of how lucky am I going to be today? And because he'll have these, and you'll see different partners, different strategies, they'll start out really, really well.

And then they'll make a little bit of money, or in some cases, a lot of money, and then they just drop and they just, in some cases, he's losing millions of dollars a day. And it's driving him crazy. He says losing money was gut wrenching. He's probably still screaming. The book doesn't say it but I guarantee at this point he's still waking up screaming. So it says Simon seems to take the downturn hard growing more anxious as the losses

increased. Sometimes I look at this and I feel like I'm just some guy who doesn't really know what he's doing. In the following days, Simon's emerged from his funk more determined than ever to build a high tech trading system. He shared a new goal, building a sophisticated trading system fully dependent on preset algorithms that might even be automated.

What he really wanted, he says, was an intelligent automated system that suggested and then executed profitable trades. This will take a few decades actually for the technology to catch up to the idea that he had. Remember in the late 1970s stills. And this is why he wants to do this. I don't want to have to worry about the market every minute. I want models that will make money while I sleep. A pure system without humans interfering.

So one of the main lessons is where this is some of the strategy, some of the strategies he has to employ to get to where he wants to go. Okay. One of the main lessons of the book and something that happens over and over again, starts in the late 1970s, early 1980s and continues to this day is the fact that Jim had better historic financial data than anyone else. And he went to great lengths to get more.

In many cases, they weren't available. He has to literally go and find this data by hand. So it says, the technology for a fully automated system wasn't there yet, Simons realized. He suspected he needed reams of historic data so his computers could search for persistent and repeating price patterns across a large swath of time. Simons bought stacks and stacks of books from the World Bank and elsewhere, along with reels of magnetic tape from various commodity exchanges, each packed with commodity, bond, and currency prices going back decades.

This was ancient stuff that almost no one cared about, but Simons had a hunch it might prove valuable. Simon's also hired a staffer to visit the Federal Reserve Office to record interest rate histories and other information not yet available electronically. So this is a reminder. Success as we see over and over again, this is why I think I've become this massive evangelist for reading biographies. One of the most important things you get out of it, which is like, Oh,

success is in a straight line. You're going to go up and down and up and down and up and down. And you just have to keep going year after year after year. This is what I mentioned earlier. They start to have a lot of progress. They'll make a little bit of money and then they start losing it. And there's so many times where it looks like he's about to quit. And so they're building this partially automated system, but they don't understand

why it's making decisions that it's making. Sometimes it makes money, sometimes it loses money. He does not want the crazy thing about the money making machine that Jim eventually succeeds with the medallion fund is like there are no down years from 1990 till present day. He never loses any money. This is exactly what he wanted to do. That's not what's happening in 1980. So says they had soon lost confidence in their system. They could see the trades and were well aware when it made and lost money, but they weren't sure why the model was making its trading decisions. Maybe a computerized model wasn't the way to go after all they decided. So this is such a crazy thing. Remember he starts the company in 40 when he's 44,

he's essentially just investing in trading like everybody else because he can't figure this out yet. Simon sat in his office staring at computer screens, developing new trades while reading the news and predicting where markets were going. Like most everyone else. They're true. Now here's the problem though. And this is a problem temporarily.

The traditional trading approach was going well. And the issue is they're having success. They're like, we're making so much money the normal way. Why do we even need this computerized trading system? And we'll get to why, what is going to have to happen. You've already guessed what has to happen to for them to get it back on the path. Oh, oh, we're not actually, we're making money temporarily. So Jim's partner is, he's telling Jim, I don't see the point in developing these automated

trading systems. This is why his partner is part of his time. It's a guy named Leonard, Leonard BOM was making so much money trading various currencies, using intuition and instinct that pursuing a systematic quantitative style of trading seemed to be a waste of time to him. Why do I need to develop these models? He asked him, it's so much easier to make millions of dollars in the market than finding mathematical proof.

Besides the firm's computer firepower was limited, making any kind of automated system likely impossible to implement. They were able to rack up more than $43 million in profits between July 1979 and March 1982. But good times don't last and the drop is so precipitous that it actually is going to end the partnership between Simons and Baum. So in the late spring of 1984, Baum's losses kept growing. This cannot continue, and Baum said one day, staring at his computer screen. When the value of their positions had plummeted 40%, it triggered an automatic clause in the agreement with Simons, forcing Simons to sell all of Baum's holdings and unwind their trading affiliation,

a sad end to a decades-long relationship between these two esteemed mathematicians. Baum's losses in the 1984 trading debacle left a deep scar on Simons. This never happened. He may not have went back to what he originally wanted to do in the first place. This is really important. I'm sure it did not feel great at the time. Definitely didn't feel great. Why Jim's fund in 1984 is losing millions of dollars daily. Simon's contemplated giving up trading. He was racked with self doubt.

He had to find a different approach. Jim was 46 years old. And so now Jim has to recruit a new partner. He's going to recruit this guy named James Axe. This is very important because they're going to start this company called Axecom. Axecom is what turns into the Medallion Fund. Now I thought it was very interesting how he recruited James Axe. Remember he said in one of his principles, you have to work with the best people and

you have to put a lot of effort into getting these people. He talked about how important and how difficult it was to finally persuade and sell James Axe on joining him. And then once he was able to sell James Axe, that opened the floodgates, realized, oh, this guy's insanely talented. He's working there. So I'll go work there too. The way he pitched, because James wasn't, they were mathematicians, so they weren't interested in finance. He's like, why would I do this? And the way that Simon successfully sold him was that he portrayed investing as the ultimate puzzle. So along with James Axe, he hires this guy named Sandor Strauss. Sandor Strauss is a math PhD. Now, here's a great line about what Strauss is going to be doing.

He's going to be collecting and cleaning the data that they need to build their systems. So Strauss builds a custom database of historical prices. He combined data sources and cleaned it until they basically had more accurate data than anyone else. This was a massive advantage. So you recruit James Axe by saying, hey, come and solve this important puzzle.

It's the ultimate puzzle. If we solve the puzzle, we have unlimited money. You go and recruit Strauss and you convince him that you're an explorer on the trail of untold riches with almost no one in pursuit. That's a really great line. Some other traders were gathering and cleaning data, but no one collected as much as they did. So again, this, this reoccurring theme, they have more historical data than anyone else in the world. Some of the weekly stock trading data they'd later find

went back as far as the 1800s. Reliable information almost no one else had access to. The ability to search history to see how markets reacted to unusual events would later help Simon's team build models to profit from market collapses in different periods of time. So the way to think about this is he's studying the past to profit from market collapses in different periods of time. So the way to think about this is he's studying the past to gain an information advantage. And then Axe is using this data to trade.

Axe is doing all the trading, which we'll get to in a minute. Axe had access to more extensive pricing information than his rivals, thanks to a growing collection of clean historic data. Since price movements often resembled those of the past, that data enabled the firm to more accurately determine when trends were likely to continue and when they were ebbing. So that's how it's starting. They're going down to the Federal Reserve,

there's a couple of people, they're doing a lot of this by hand. They have very, very, as I get to in one second, very, what we would see is very primitive computing, right, at the time. That's how it starts. 15 to 20 years later, this is what the data collection looks

like because I found this, Jim describing this in this interview much, much later. And he says, everything is grist for the mill. Weather, annual reports, quarterly reports, historic data itself, volumes, you name it, whatever there is. We take in terabytes of data every day. We store it away and we massage it and we get it ready for analysis. You're looking for anomalies. Again, big things start small. They're doing this by hand.

The funny thing is, actually I'll get to it right now. So that's how Renaissance is doing it now, right? Think about what, they're always on the cutting edge of technology and you and I might look back and think it's kind of funny, like their version of technology. This is 1985. So a lot of the reason I keep bringing this up

is because I think so much of the really important part of the story is so much of Jim's story and the success that his team is gonna have, is them just waiting for the technology to catch up. And when they do, they're gonna be so far ahead of everybody else because of what they're doing. And so they're like, all right, we're collecting all this data, we're cleaning it, we need the best computers to analyze it.

So they go, they order an immense gold super mini computer, okay? This thing is the size of a large refrigerator. It had to be put into their office by Forklift. It was capable of storing 900 megabytes of data. This is the cutting edge of technology. In fact, there's a few other people in the book that I'm omitting, but they were a bunch of other people like Ed Thorpe, David Shaw, who's gonna start D.E. Shaw.

You might know that name because a young Jeff Bezos actually had the idea for Amazon when he was working for DeShaw. And so there's all these other people trying to figure out how to do quantitative trading and doing going about different ways. And so they interview this one guy that's the seed investor, went to being David Shaw's seed investor, gives him $28 million to start DeShaw. And they spent a bunch of money on computers and he had a great line about this.

He goes, well, David needed Ferraris. So we bought him Ferraris. And so again, you see Jim and his team, like they're on the cutting edge of technology. They just have to wait for this technology to be developed, to catch up, and to actually enable the idea that they're gonna have. Now they're getting closer as a result of,

you know, this computing power of all this data. They're getting closer to this automated model for trading. And when I mean automated model, I should point out it's automated trade suggestions. They still have to because this is the 80s. The system they've been the model they're building will spit out trade ideas. They have to like call them in a few times a day, which I thought was really funny. So it's going to take a while before you can suggest the trade and then execute it electronically. I don't know why I was like chuckling when this was happening.

I just love this idea. I was like, all right, we got a system. We'll call up our broker dial the number. I don't know why I was laughing. All right. So even though they're getting closer, and this is what Jim had said he wanted to do forever. He still doesn't understand why the model is suggesting what the model is suggesting. And he should know.

I shouldn't say he should know better. I don't mean to sound patronizing in any way at all, but he should understand that it's beyond human comprehension so of course you're not going to understand it, you should just test, is it actually money-making opportunity or not? And so I'm just gonna read this section, I just thought it was really really funny. This method wasn't based on a model Simon's and his colleagues could reduce to a set of standard equations, and that bothered him. The results came from running a program for hours, letting computers dig through patterns and then generate the traits.

But to Simon's, it just didn't feel right. I can't get comfortable with what this is telling me, he said. I don't understand why the program is saying to buy and to not sell. Later, Simon's became even more exasperated. It's just a giant black box, he said with frustration. But he's got all his partners around him saying, yeah, but this is what you have to trust the system. This is what we're, it is doing,

and we are doing what we said we're going to do. So one guy said, Carmona agreed with Simon's assessment, but he persisted. Just follow the data, Jim. It's not me, it's the data. It works, Jim, Axe told Simons, and it makes rational sense. Humans cannot forecast prices. Let the computers do it, they urged. It was

exactly what Simons originally hoped to do, yet Simons still wasn't convinced of the radical approach. He still wanted to know. Humans love to know why, and he still wants to know why. Later on, he gets very comfortable with this. In fact, he has a great way to describe how he thinks about this, and he says wants to know why. Later on he gets very comfortable with this. In fact, he has a great way to describe how he thinks about this and he says, I don't know why planets orbit the Sun. That doesn't mean I can't predict them. So I don't know why planets orbit the Sun, but I can predict their location and where they're going. I already said this, but the funny thing is that the trade suggestions are automated, but the actual trading isn't. So they're still having to call up these brokers a few times a day. This whole thing is just an exercise in patience and persistence. They have

to survive long enough for the technology to catch up. And by the time it does, no one else can catch up to them. So then as I'm reading this, it really like clicks for me. It's like, oh wait, I get to the section and James asks, their partnership is going to fall apart. He's just complaining about Simons all the time. At this part, they're still managing outside money. So he's like, I'm doing all the trading and this guy's just dealing with the investors and he's also calling them and nudging them all day.

James is getting very, very frustrated. James was also a very difficult person to deal with. And I was like, oh, so Simon's gift is recruiting and management and system and incentive design. The greatest moneymaker ever isn't doing the trading. What came to mind when I read this? But if you go back, there's a great book called Me, You and Hell. It's about this bitter partnership between Andrew Carnegie and Henry Clay Frick.

And it's pretty clear that Henry Clay Frick was the better manager and entrepreneur. But Carnegie winds up with all the money. So Carnegie actually buys Frick's company and then realizes he has a rare talent And then he lets him run Carnegie Steel. Carnegie owns a majority of it when they sell to JP Morgan Carnegie's gonna have the largest liquid fortune in the world at the time and what is fascinating is he makes you know three or four times The amount that Henry Clay Frick makes but Frick is doing all the work So now we need to go to the state of Jim's business in 1989. This is going to be their last losing year ever. And this also when his

partnerships with James Axe falls apart is really, really important. So it says, Simon's has spent more than a decade remember the man this is not the man who sold the market, or maybe an alternate title is the man who persisted. Simon's has been more than a decade backing various traders and attempting a new approach to investing. He hadn't made much headway. Baum, his first partner, flamed out. Another partner wasn't around much.

And now his fund with Axe was down $20 million amid mounting losses. His colleagues became convinced that Simons might shutter the firm. It was not clear if we would survive or fold. So this is very important. This is, this is maybe the most important idea and change that they actually make. There's something that Simons said in 2018 that was very fascinating. So Axe would have a much longer term strategy

for the models. And Jim is going to bring in this guy named Elwin Berlecamp. And it's Berlecamp that comes up with the idea. It's like, no, no, we just need to shorten our holding period. Later on, the way Simons would describe this, he says that longer term trading makes algorithms less useful. It's like the weather, the nearer in the higher the certainty. So Ellen Burlacamp urged Axe, he's coming in, Jim recruits him to come in and try to help Axe. And he's like, hey, why don't you look for smaller short-term opportunities?

That way you get in and you get out. And it's Burla Camp that's going to institute this change. This is when he's going to lose the partner, James Axe, because Burla Camp has this idea and he's very actually, he's in line with what he has a belief, the same belief that Simons has that Axe doesn't. And so he goes, well, why don't I well, why don't you just sell me your stake in the firm? Like I'll buy you out and then I'll try to implement

this idea that I'm trying to give you. And Axe agrees. And so this is the idea that Burla Camp wants to implement. Buying and selling infrequently, which is what Axe was doing, magnifies the consequence of each move. Make a lot of trades and each individual move is less important. They hope Medallion could resemble a casino. Casinos handle so many daily bets that they only need to profit

from a bit more than half of those wagers. With a slight statistical edge, the law of large numbers would be on their side, just as it is for casinos. If you trade a lot, you only need to be right 51% of the time. The way he arrived at this idea this idea We just looked he analyzed all the trades that they were doing like which ones did you make money on? Remember a few weeks ago Ken Griffin said something that he sees us in the state that people make in finance if they spent all a bunch of times Studying like how they lost money or their losers. He's like wait people finance should be spend more time studying their winners That's exactly what Burla camp does he advocated for more short- trades. Too many of the firm's long-term moves had been duds, while Medallion's short-term trades

had proved its biggest winners. It made sense to just build on that success. And then I absolutely love this, because it goes back to having a self-confidence, being comfortable trusting your own judgment, not being worried with those around you or doing. In fact, they talk about a lot of people at Renaissance, they criticize the overall financial industry.

So it's just herd mentality. That's why their return sucks, what they would say. So Berlecamp, he's still working in academia as well. And so he goes and he's discussing his ideas with other people in the business school. And they mocked his methods. They're about to go on a historic run right now. So they're describing what we're about to do, right? And their methods are getting mocked and they calleded his methods, okay, they're about to go on a historic run right now. So they're describing what we're about to do, right?

And their methods are getting mocked, and they called them quacks. So think about this, Simon's and his partners were so early, and their ideas were so different from others in their industry that they were dismissed as quacks. They're gonna start this strategy with $27 million

and go on this historic run. the new strategy starts working immediately. The firm implemented its new approach. The results were almost immediate, startling nearly everyone in the office. They did more trading than ever. Remember that idea. It's like, we're just going to do a ton of street. Like look what the casinos do. We just need right 51% of time. They would cut medallions average holding time to just a day and a half scoring profits almost every day for much of 1990. Simon's team could do little wrong. It's as if they had discovered a magic formula after a decade of fumbling around in the lab. One day, they made more than a million dollars that day a first a first for the firm.

Simon's rewarded them with champagne. This is one of my favorite favorite parts of the book. We made a million dollars in profit in a single day. We're going to celebrate with champagne, this is one of my favorite parts of the book. We made a million dollars in profit in a single day. We're gonna celebrate with champagne. The one day gains became so frequent that the drinking got a bit out of hand. And then this is absolutely perfect timing because right in this book, there's an excellent lesson on human nature for you and I.

Even with wild success, people will still try to tell you that you're wrong. For all the gains, a few outside the office shared the same regard for the group's approach. We were viewed as flakes with ridiculous ideas. Simons did not care about the doubters. This is why I kept hounding on it over and over again. It's so important to understand he was an outsider.

He always viewed himself as an outsider. He was comfortable being on the outside. Medallion scored a gain of 55.9% in 1990, a dramatic improvement on its9% in 1990, a dramatic improvement on its 4% loss the previous year. Now here's the crazy thing. Even this, there's always a dispute with Simons and his other partners about the scale and how big it could get.

And they're always kind of getting to like tamper his ambition, which is really fascinating to me. And I'm gonna like hit on this because I think it's one of the most important ideas in the book, at least one of the most important ideas I took away in the middle of this 55% gain we know it's gonna work another partner gives up Barla camp is going to give up because he's having a dispute okay this is what

I said earlier that Simon's had something valuable that his partners did not and it's not intelligence they were all smart it's belief it's conviction and what they were doing. Remember, Simon said, I want to do something historic. 30% in chill was just not going to happen. It is not in this guy's DNA. So they're having this fight where this disagreement where Simon is like, I'm pretty sure we can make like 80% returns every year.

And Brocamp's like, what? No, like we'll be lucky. Like let's just get 30% and it's fine. And this got so pronounced that this leads to their breakup. And so it says, Jim, if you think we're gonna be doing 80% and I think we can do 30%, you must think that the company is worth a lot more than I do.

So why don't you buy me out? Oh my God, could you imagine? You were right there. All you had to do is hold on, Burla Camp. You didn't have to go anywhere. Which is exactly what Simons did in December 1990 after putting up 55.9%. Why would you sell?

Simons purchased Burla Camp's ownership interest for cash. Burla Camp sold, and this is, he thought he, he thought he had a win. He thought, Burla Camp thought he had a win. Listen to this. Burla Camp sold his shares at a price that amounted to six times what he had paid just 16 months earlier. Remember Remember he bought Axe out. Now he's flipping that interest to Simons at a six

Axe return in 16 months. Like look what I'm doing. Not realizing you're missing out. It amounted to six times what he paid just 16 months earlier. A deal he thought was an absolute steal. And then Simons, when he loses another partner, this is what he told a friend at the time. To hell with it, I'm just gonna run this myself. The benefit of being an outsider and having the ability to trust your own judgment, Simons' viewpoint can be seen as profound, even radical. At the time, most academics were convinced that markets were inherently efficient, suggesting that there were no predictable ways to beat the market's return and that the financial decision-making of individuals was largely rational.

Simons and his colleagues sensed that the financial decision making of individuals was largely rational. Simons and his colleagues sensed that the professors were wrong. They believed investors are prone to cognitive biases, the kinds that lead to panics, bubbles, booms and busts and their building system take advantage of these reoccurring behaviors of human nature. This is how Jim and his team viewed what they were doing. This is what I meant about their ability to be very clear communicators. What you're really modeling is human behavior.

Humans are most predictable in times of high stress. They act instinctively and they panic. Our entire premise was that human actors will react the same way humans did in the past. We learned to take advantage. This is what, maybe boiled down to that maxim, history doesn't repeat repeat human nature does. Another maxim that you and I talk about all the time,

and this is something I mean, I kind of hinted on, but it's so profound. And it's this idea that bad boys move in silence. Renaissance, Jim, super, super secretive. The idea is like you find an edge and then you shut up about it. I told you a few months ago, I had dinner with one of the wealthiest people in the world.

I found out that his family had commissioned a bunch of biographies for him and other prominent members up about it. I told you a few months ago, I had dinner with one of the wealthiest people in the world. I found out that his family had commissioned a bunch of biographies for him and other prominent members of the family. It's only for internal use of the family. And I asked, I was like, let me get those biographies. Let me do an episode about it. Without hesitation, he says, absolutely not. I have no desire to educate my competitors.

You're gonna see a very similar line of thinking from Jim here. By the end of 1993, Medallion had grown to 280 million. Remember, up from 27 million just a few years earlier. This is the wild part. Simon's already there, he knew this was winning, he had that belief. He decided not to let any more clients into the fund. At this point, they're still managing other people's money,

they're gonna kick every single person out of the fund though. Simon's team turned more secretive. Our very good results have made us well known and this may be our most serious challenge, Simon's said. Visibility invites competition and with all due respect to the principles of free enterprise, the less competition, the better. Our only defense is to keep a low profile. Another description of this

is found in the book. Simons and his team are among the most secretive traders in the world, lest a competitor sees on any clue. Simons has a great way to describing this himself. He once quoted Benjamin, the donkey from Animal Farm, to explain his attitude. God gave me a tail to keep off the flies, but I'd rather have no tail and no flies. That's the way I feel about publicity Let's go back to another insight of human nature It's important to note this opinion by outsiders is going to persist well past the point of Simon's Outperforming everyone else. So at this time that they try to recruit this guy the company was making over

200 million in annual profits. To me, this is a lesson on human nature. This record, they try to recruit this guy, he comes in, hangs out with them. And you know, they're in a kind of a crappy office still. Says it looked like four guys in a garage. They didn't seem that skilled at computer science. And a lot of what they were doing was by the seat of their pants. Just a few guys dabbling at computing. It was not very appealing. It's gonna be really important,

because if you took the job, the only people that can have money in the medallion fund are Jim and the employees at Renaissance Technologies. It's a very fast thing. And I gotta go back to this idea I've already mentioned, the fact that all these people try to like, they are succeeding past maybe their expectations, but Jim's not the kind of person that's just like,

oh, okay, I'm making 200 million a year, or I'm making 30% or 40%, like then I guess I'll just do this forever. He wants the challenge, he wants to do something historic, he wants to be the best person at what he's doing. This is just part of his DNA. And so they come to him, like one of his top guys is like, why don't we just keep this at $600 million?

That way we can rack up 200 million in annual profits no Simon's responded we can do better again this is no I left myself and in multiple times of the book all along the way people around Jim are trying to get him to moderate his ambition Jim gives this great interview as a much older man and he's asked like what motivates him and he goes it motivates me I'm ambitious and I like to do things well. I love to create something that really works. We have lots and lots and lots of strategies

and each new one gives me a lot of pleasure to see something new that works. And then at the same time, a colleague beautifully summarizes why Jim wants to keep pushing and making more money and he says, emperors want empires Over and over again throughout the book you see these lines that tell you a lot about Jim's personality Emperors want empires what Jim wants to do is matter

He wanted a life that meant something if he was going to do a fun He wanted to be the best his need to accumulate more wealth was ceaseless and ever Present now this is again all these people His need to accumulate more wealth was ceaseless and ever present. Now this is, again, all these people, they're early, it's working incredibly and they just can't sit still. There's something about humans that just can't do this. At the time, Jim has a team in Long Island and he has a team in California. He's like, okay, we need to consolidate.

This is working. I want every single person to move and we're all gonna be together in the office in Long Island Strauss who played an incredible role. He doesn't want to leave he refuses to move and as a result He winds up missing out on a fortune and the note of myself This is amazing how many characters in Simon's life don't even realize what they have when they're staring straight at it What does that mean in 1996 Strauss sold his Renaissance shares and quit. Later, Simons would force Strauss and other non-employees to pull their money out of Medallion.

I thought we were one of many, Strauss said. If I thought there was some secret sauce, I would have made sure I could have stayed invested in Medallion and the only way to do that would have been to move and to stay an employee of Renaissance. Never, now this is also very fascinating, is there's a line in the book that was, that it kind of speaks to this idea that you and I speak about a lot, that those on the

margin often come to control the center, and that Simons never took a single finance class, he didn't care much for business, and until he turned 40 he only dabbled in trading. His firm hires mathematicians and scientists who don't know anything about vesting are the ways of Wall Street. They are very vocal in their critique of this. In fact, it was hilarious. One guy had a suggestion, it was like, hey, when they start trading stocks, like we should just delete the names of the companies and replace all the names with numbers. Because if we pay attention to the name,

we'll pay attention to the story, and it'll make decisions based on human intuition when the model on the computer is actually way more sophisticated and understands things that are beyond human comprehension. And you see this would play out, great example of this, where they're doing a lot of commodity trading.

And sometimes they could do something as simple as like a human input error that causes the system to do something it wasn't supposed to do. And it can move entire markets. So what is this? And then I left myself on this one is never forget this. A data entry error caused the fund to purchase five times as many wheat futures contracts as it intended,

pushing prices higher. The next day's Wall Street Journal reported that analysts were attributing the price surge to fears of a poor wheat harvest rather than Renaissance's miscue, which was just a data entry error. And this is a direct quote from Peter Brown, who's the CEO of Renaissance to this day.

Anytime you hear financial experts talking about how the market went up because of such and such, remember, it is all nonsense. And Simons would talk about why he ignores the financial press and largely the financial industry. We never hired anyone from the financial ward at Renaissance. We never did because they don't have anything to add. Some of these people write papers about predicting the stock market and stuff like that. We looked at a bunch of these papers. They were all wrong. Every paper was wrong. So we stopped bothering looking at these papers because they were wrong. Mute the world and then build your

own. Now, this is very fascinating how Simon structured the Medallion Fund. There's a lot in this book that's going to suggest that Simon's was a genius in system design and understanding the power of intentives. And he insisted on a different approach to again his peers and other funds. Medallion would have a single monolithic trading system. Every employee enjoyed full access to each line of the source code, underpinning their money-making algorithms.

All of it was also readable in clear text on the firm's internal network. And then something that he would repeat over and over again in the book and in interviews, you need to make everyone partners, share all the profits. And he supercharges this when he kicks out every non-employee out of the fund. In 2002, Simon's increased Medallion's investor fees

goes all the way up to 30% of each year's profits. A bit later, he increased the fees again to 44% of the profits. He gives this interview and he says, we charged the highest fees in the world at one time. And the response was, how can I get more? A year later in 2003, he kicked all of his investors out of the fund. Simons had worried that performance would ebb if Medallion grew too big, and he preferred that he and his employees keep all the gains.

This is what I meant about he was a genius at system design and understanding the power of incentives. When you, like Charlie Munger would talk about the power of incentives over in Irvington, and he talked about this one guy named Les Schwab who I did two podcasts on. He said that Les Schwab had one of the best understandings of the power of incentives. What Les did was make sure that each individual store that he owned, he shared all the profits of that store

with the people in that store. You see a very similar approach to what Jim does here. He made sure that everyone shared in the profits of the funds success, from programmers to statisticians. And he had an unusual incentive structure that bred loyalty and aligned everyone's goals. Remember when even top people would leave he would kick him out of the fund. Think about how weird unusual those business is. You have no customers, you have no outside investors, you essentially have a money printing machine that hasn't lost

you know had a single down year and two, two and a half decades. And all the money every year just gets sweeped and distributed to the people in the company. And you could do the math. Like how much are these people making? Well, if there's 300, 310 employees and they're making seven or $6 billion a year, everybody's making a ton of money. But I want to pause on that line that's in the book. It says an unusual incentive structure that bred loyalty and aligned everyone's goals. The end result is as you have this unbelievably low employee

turnover because if you leave the job, you leave the ability to invest in the medallion fund, which is this magic money making machine. There's a, when I read this section, I thought of this book called software that is a biography of Larry Ellison's written, you know, two or three decades ago. And he said that was very interesting where he did not he one thing that he deviated from some of his peers at the time. He says you don't want turnover of your core product team, because knowledge compounds and if you have turnover, that means you're interrupting the compounding. So

let me read this paragraph from software. It says while many parts of the business actually need staff turnover to stay fresh and vigorous, Ellison believes that keeping the elite kernel group together has been vital. The process of building a software product teaches a programmer what to do and what to avoid. The accumulated knowledge and experience within the 40 or 50 strong kernel group comes from continuous work on improving the core code rather than some extension of the product that will make a flashy new release. You don't want turnover on your core product team. Simon's designed this incentive structure to breed loyalty and to align everyone's goals. A

few weeks ago I talked about that Ken Griffin, a young Ken Griffin, I think he's like 30 years old. He studied the collapse of LTCM long-term capital management. Simons and his team did this, this what they took away I thought was fascinating. They observed that LTCM had drifted into markets the firm didn't fully understand. It was a reminder for Simon's team of the need to hone their approach, not to enter a new business, just to make their existing business better. Another thing that he does, and this is one way that he makes his existing approach better, and it's something I love seeing.

I love seeing when people draw parallels from other domains and then actually bring those insights into their own work. And so he's going to recruit from IBM's computational linguistics department, and two people that he's gonna recruit from there, one of them being co-CEOs. So they're going to be, it's both Peter Brown and Robert Mercer. They were computer scientists specializing in computational linguistics

who joined Renaissance in 1983 from IBM research. At IBM, Brown and Mercer were working on computer systems to transcribe spoken language into computer text. And one of the reasons that Mercer and Brown came over is says it was clear to them that trading stocks bore similarities to speech recognition, which was part of why Renaissance has continued to raid IBM's computational logistics team. In both endeavors, the goal was to create a model capable of digesting uncertain jumbles of information

and generating reliable guesses about what might come next, while ignoring traditionalists who employed analysis that wasn't nearly as data-driven. And Simon summed up this approach in a 2014 speech. He says, it is a very big exercise in machine learning, studying the past, understanding what happens and how it might impinge non-randomly on the future. And then I want to end with some parting life advice from Jim Simons. He says, Simon shared a few life lessons with the school's audience.

Work with the smartest people you can, hopefully smarter than you. Be persistent. Don't give up easily. 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. And then in 2020, he published his five guiding principles, which I think are excellent.

Number one, do something new, don't run with the pack. I am not such a fast runner. If I am one of n people working on the same problem, there is very little chance I will win. If I can think of a new problem in a new area, that will give me a chance. Number two, surround yourself with the smartest people you can find. When you see such a person, do all you can to get them on board. That extends your reach and terrific people are usually fun to work with. Number three, be guided by beauty. This is obviously true in doing mathematics or writing poetry, but it is also true in fashioning an organization that is running extremely well and accomplishing its mission

with excellence. 4. Don't give up easily. Some things take much longer than one initially expects. If the goal is worth achieving, just stick with it. 5. Hope for good luck. And the last piece of advice is advice that Jim said he would give his 20 year old self. It is very important to enjoy your work.

Find something you love and then put your heart and soul into it. And that is where I'll leave it for the full story. Highly, highly recommend reading the book. If you buy the book using the link that's in the show notes are available at founderspodcast.com. You'll be supporting the podcast at the same time. That is 387 books down, 1000 to go,

and I'll talk to you again soon.