Animal Spirits Podcast - Talk Your Book: Greg Zuckerman on Jim Simons & Renaissance Technologies

Episode Date: November 7, 2019

On today's Talk Your Book we talked with Greg Zuckerman about his new book The Man Who Solved the Market. We covered how Jim Simons built the greatest track record ever, lessons all investors can take away from Simons, how Ren Tech does it, the process of writing this book and much more. Find complete shownotes on our blogs... Ben Carlson’s A Wealth of Common Sense Michael Batnick’s The Irrelevant Investor Like us on Facebook And feel free to shoot us an email at [e-mail] with any feedback, questions, recommendations, or ideas for future topics of conversation. Learn more about your ad choices. Visit megaphone.fm/adchoices

Welcome to Animal Spirits, a show about markets, life, and investing. Join Michael Batnik and Ben Carlson as they talk about what they're reading, writing, and watching. Michael Battenick and Ben Carlson work for Ritt Holt's Wealth Management. All opinions expressed by Michael and Ben or any podcast guests are solely their own opinions and do not reflect the opinion of Ritt Holt's wealth management. This podcast is for informational purposes only and should not be relied upon for investment decisions. Clients of Rithold's wealth management may maintain position. and the securities discussed in this podcast. We're sitting here with Greg Zuckerman, author of The Man Who Solved the Market, how Jim Simons launched the Quant Revolution. As someone who writes, I'm really interested in the thought process

behind writing it. Was there a singular moment where you had an aha moment where the light went off and you said, I kind of can wrap my head around this? Or was it more of a slow burn to kind of understand what exactly was going on there and what they were doing at Renaissance Technologies? So there was a moment.

So early on I was sort of, for months, I wasn't sure I could pull this thing off. And I was going to tell my publisher, you know, it's just impossible. The guy won't talk to me. Nobody within the firm is telling me that people that used to work there are saying, Greg, don't waste your time. But then I went out to California. And I met Elwyn Burlickamp and his former colleague, Sandor Strauss.

And they worked with Simons early on. And not only were they sharing really interesting information, it was a great story. And I was like, you know what, how do I not do this book? I've already got some real insight into the early period, and it's colorful and it's entertaining, and I'm learning a lot. So I'm going to make a bet here that I can actually keep it going. How'd you find them? So they just doing research on the firm and hearing, reading some old articles and talking to people, and they seemed both the few people that were still alive, there were a few people that no longer were with us, but they're alive and they're

interesting and they're colorful and then they're unusual people and super smart. So I figured, okay, as a writer, you need character. So here are two interesting characters. Let me build off of these guys. From there, it still wasn't clear, but at least I got a little more confidence that I could pull it off. So from the market side of thing, put your restorative market reporter had on, explain to me, if you can, what is the difference between what you think that Renaissance does and what high frequency trading does? Is there a big difference? that you can see between what they do in sort of time horizons or... Yeah, there is a huge difference, and I kind of went into it not sure of the distinction.

But so, yeah, so high frequency, it's all about speed and about getting in before you and I do potentially, and, you know, milliseconds we're talking about. What they do at Renaissance is fast, but it's not nearly as fast. And quite honestly, they've looked into doing high frequency, co-locating and all that kind of stuff, and they fail. Their machines are powerful, but they're not the most powerful. And they sort of tease each other a little bit that they're fast, but they're not as fast as these other kind of guys. So it's not about speed with them. It's a holding period of around two days, so it's not in and out front-running other people. It's about figuring out patterns in the market

that you and I miss. And they are short-term patterns. There are months, potentially as long as months, but usually not. It's more kind of moments to months is what they say internally. You said in the summer of 2019, they did 5% of daily trading volume, I'm sorry, Medallion. Medallion. Did 5% of daily trading volume excluding HFT. Where did you find that? That's a good question. I got that sense from talking to people and then I ran it past some internal people who are familiar with those numbers. So the people who work at the company are comfortable with that number. So they're doing, so it's not HFT. but oh my God, they're doing a lot of trades. I think somewhere it's 150. Oh, here it is.

Medallion made between 150 and 300,000 trades a day, but much of that activity entailed buying or selling in small chunks to avoid impacting the market prices. And Simon said, quote, I'm not sure we're the best at all aspects of trading, but we're the best at estimating the costs of a trade. Right, Michael. So this is an important point that, yeah, they are a fast trading firm, but lots of times it's just to put a position on. So they're easing, into a position or getting out of position in small bites. So they look to outsiders like they're fast training, high frequency, and they're not. And the second point is really important one. So we as investors, we all focus on the signals or the trade. And when you get something

that the other market people, participants don't get, we're investors. So that's what we look for. But internally, when you talk to people at Renaissance, yeah, the signals are important. But just is important is are things like how you impact the market with your trades. And that's a huge deal when it comes to Kwan. Execution. Execution, slippage, things like that. And they're really good at that, estimating your risks involved in your positions. So there are all kinds of elements to trading that maybe aren't as sexy, perhaps. They're not something that the average person really focuses on. We all think of, you know, buying something. And hopefully it goes higher and you're a hero. But when you talk to a sophisticated trader at Renaissance and Medallium,

per se that their funds, they are focused on all kinds of other aspects of trading that I hadn't been myself. Ben, you had such a good insight that like there's 4,000 books on Buffett, but this is such a different user experience. Yes, I just had a, the takeaway from after I got done reading this was so much different than the other ones in that I think if you read the book on Buffett, you think to yourself, oh, he makes it sound so simple and folks seen easy that I could probably do that. But no one's going to read this book. takeaway that I could be like all these codebreakers and mathematicians and do this. So what do you think that takeaway is for the investor that reads this? Just the fact that, I mean, know who's on

anybody a trade? Or what is the takeaway here for any investor, whether they're professional or just a retail or whatever? Yeah, that's a good question. So for the average guy, I would say it's a lot of things. There are things, there are ways you can learn from Renaissance in terms of how they hire talent, how they work together, how they create. It says as much of a management book, I would think as an investing book, this open architecture, how they recruit, how they look for talent, just as opposed to the job opening. They just try to find the best people. But in terms of the investing lessons, one of them is you don't want to be a short-term investor, and I don't even mean kind of a day trader. You've got to go the opposite direction of people like Renaissance.

If they're going to do as much as a few months and a few days, the only opportunity left for the average investor is to be a much longer-term investor. And I don't mean years, but you want to be going against the grain and not compete with Jim Simons. And that's probably at least a year or a holding. And you can actually take advantage of some of the panics and the greed out there and the fear, which is what Simons does. I mean, a lot of what they do is taking advantage of the behavioral mistakes that you and I make. They do the best. Speak yourself. Okay. That I make. They do the best in times of panic because over and over again, we make similar mistakes. So it's another reminder as investor, as an average investor,

to be aware of the behavioral mistakes that many of us, or I'm prone to do and to avoid them and to be a longer-term investor than maybe we otherwise would be. So, you know, when you see like Fed announcements and economic data announcements, to see the spike or then the fade, is that them? I mean, or are they not doing that? It could be. It depends what their models are telling them. They themselves aren't always sure what their model. are doing at any time. You know, a lot of it's machine learning at this point. It's become much more sophisticated over the years. So even they aren't necessarily short until they look in hindsight. But getting back to sort of those investor lessons, I really do think that there are ways to

kind of train yourself and to fight those behavioral mistakes. And this is one more reminder to do so. And you talk here about, like, who's on the other side of the trades? And one of the guys said, well, we think it's a lot of dentists who are overconfident. But Simon said, well, it's definitely probably not the long-term buy and hold people. We think it's actually more of like the global macro hedge fund people. So that's interesting that he thought they're actually taking advantage of these professionals. And so do you think in recent years that Medallion has probably taken advantage of more professionals than individuals because so many individuals are going to like index investing? So Ben, it's a great question. And I actually, in preparation for

sort of this, you know, media coverage of my book, I talked to a guy internally who works there just last week. So I wanted to kind of get the latest. And, you know, you write this. And there's a lag. It was printed a few months ago and all that. And what I said to him was, okay, the market seems to be changing where there are fewer dentists. There are fewer of these average people that you at Medallion and Renaissance can take advantage of. So does that mean that the nature of the market is changing? Does that mean that perhaps your patterns won't work? Your statistical analysis, your strategies won't work like they were in the past. If the market, if there are fewer of you and I or people like me playing the market and fewer people for them to take advantage of,

does that hurt their abilities? And they said that they're still, and this is what they said, as of last week, there's still enough people out there doing the same kinds of trading that they used to, kind of active investors. But there could get to the point where as the market goes to indexing and ETFs and passives, that the nature of the market changes. And if it happened overnight, then I think Medallia would have a problem making money. The fact that it's probably going to be a longer-term process means their models can probably adjust or potentially adjust. But yeah, it's not clear they can keep doing 66% a year. It's really not obvious. So if the retail trader are guppies, they're not eating the guppies. They're like the

Megalodon, to use one of my favorite movies, eating the Great White Sharks. So they're feasting on the other smaller professional money managers. Is that fair to say? I would say they they feast on everyone. So they feast on the guppies. they feast on the big fish, they just like making money. So what I do find interesting, and people aren't aware of this, people think quant. Do you think quant is the big category? And everyone's a quantity. And it is true. 31% of trading is quant. But there are different categories of quant. And what they do is very different from like an aQR. There actually aren't many people that trade the way Medallion does in terms of few days holding period, not super

short term like HFT. There are a lot of Jane Streets. There are a lot of HV. H-T-type fast traders, they don't do that. Their competition is like two sigma. There are a few places. DeShaw, to some extent. There are a few places, but they actually don't have as much competition as you. The Fed. They're actually, you know, aren't as many competitors for Jim Simon's firm as you would think. If they went away, let's say that someone came into office and put a trading tax on that made it just not make sense for them to do this anymore. If Renaissance just completely shut down or went away, would the market notice? Would they There would be a big hole there, or would you think things would just continue to go on as they are, and it would be harder to notice?

It's hard to tell, but I don't think the market would notice that much, which sort of gets to the point of are these guys net, you know, a benefit to the society as a whole? I mean, you could make the argument. Well, they took $100 billion out. They took a billion out from somewhere, right. And not only that, but they've siphoned brains from all kinds of different areas of society, mathematicians, scientists. I've made the argument to people internally and people close to the firm and that, you know, net, net, are they good for society? Maybe these people could have cured cancer. They're so much smarter than you and I are, again, I don't want to speak for you, than I am. Maybe these guys should have stayed in academia and all these kind of revolutions would have resulted. I'm a little skeptical, perhaps not. They've said to me, what they respond is that, A, they're not that capable of curing every disease, how they stayed in academia. And, And B, they do make so much money. And they do generally do really good things with the money, not just Jim Simons, but other people, too.

So, and I agree with that. They've done all kinds of crazy, interesting. Very philanthropic. Yeah, in Africa, all kinds of places. So I would argue that they're doing some good things for society with their money, or at least many of them are. So do you think that, I mean, one of the early edges that they had was information. They compiled the giant database. And Mercer would say later, there's no data like more data.

So that was their edge early on. They had better data. Does that edge persist? Is that where their edges? And how many people could, like this is a sort of separate related question, how many people in the organization can explain what they do? Like really explain what they do. They're pretty sophisticated internally.

And I think many of them can explain the approach. They can't necessarily tell you why they're up this year, that kind of thing. But these are really remarkable individuals. And I don't say that. And, you know, I don't be laudatory. they're not, I'm not saying, again, maybe they should be doing other things with their time, but they're pretty impressive individuals in that. They're worldly, many of the people, they travel. Some of them are not from America. They're from all over the place. They have

a remarkable collection of talent, people that could be working, you know, Google and Facebook kind of thing, but have chosen to tackle the markets of challenges. You know, in that regard, they're kind of unique. So these people, I think, can explain what they're doing. What was, I forget, what was the first part of your question? So the first question was the informational edge. Oh, that's a good question. So I would say until around, I don't know, 2010 maybe, they had a real, maybe 2005, they had a real advantage over everybody else.

Today, not as much. They do have data that nobody else has. So someone explained it to me as follows. Let's say you two wanted to start a library. How long would it take you or anybody to start like a local library? I don't know, a few months maybe to get, you know, a decent library. area going, but how long would it take you if you wanted to start the Library of Congress? You couldn't. And they have data that probably you can't get your hands on from going back,

way back, the 1700s. But that said, it's more, that's for people who want to look into curiosities within the firm. Day to day, they have every kind of data you want, but so does, you know, AQR and lots of other places, Winton, et cetera. So I think they have every kind of data there is out there, but other people do. So it's not as much of an advantage. as elsewhere. It is cleaner than other people, but that, again, other people have cleaner data than in the past, too. So a lot of the book was surprising to mean, obviously, because the story hasn't been told that often. But what were some of the more shocking or surprising things that you learned along the way that you didn't really plan on encountering? So I figured Jim Simons worth

$23 billion, the greatest moneymaker in modern financial history. I figured he came up with algorithms that anticipate where the market's going. He's got a few ones that he worked on. He's a mathematician. He's one of the greatest geometers over the past 50, 100 years. And yet, the more I looked into it, it was a little disappointing to find that, or in some ways, maybe reassuring, he wasn't the one. It was a group of people around him. And he is great at hiring. He's unbelievable manager. You can learn from him in terms of dealing with these personalities and these big brains. But he himself never came up with any of the algorithms and the signals. He participated in the meetings. He asks great questions. He encourages. He pushes. He does all that

kind of stuff. And that's kind of why I focused as much on these other characters in the book. And there's so many interesting ones around him, Bob Mercer, Peter Brown. Who was the junior associate that solved the glitch that was almost fired? Oh, David Magerman. Yeah. When he went to Mercer and said, here it is. Yeah, yeah. And Mercer was like, oh, you're right. So to your point, Simons was the architect of the team that managed the investments. And there was, when he said to Brown and Mercer, like, in order to really scale this thing, they had to get into equities.

And that was like the code that they couldn't crack. And he said, I'm giving you guys six months around pulling the plug. Yeah. I mean, it didn't have to go this way. Yeah. Yeah. Oh, that's exactly right. Right.

Until 1994, they were successful, but they were about $800 million as a hedge fund. fund. And back then, that was sizable. Don't get me wrong, but they were capped out at $800 million. So beyond that, unless you get into equities, you really can't. There's some of these markets, soybeans and other kind of stuff, are just too narrow. So they needed to make stocks work, equity trading work, and they couldn't. They spent years on it. Super smart people, Robert Fry, other people tried and failed. And Mercer, as you suggest, Mercer and Brown were brought over from IBM. And they tried and failed. And it took, they had to figure out this glitter. I write about in like 1996, and then they were off to the races. But right, were it not for

that glitch and David Magerman and them figuring it out. Maybe someone else would have. You don't know, but maybe not. Then, yeah, we wouldn't be here talking about the greatest money-making machine modern finance has ever seen. So did Simon single-handedly make the entire office smell like a bowling alley? Is that possible? I mean, we were trying to figure, is he- A bowling alley is allowed to smell like cigarettes today? Maybe not anymore, but he has to be on the pantheon of greatest smokers of all time, unless they just really invested in the ventilation system? Sure. Pantheon of geometers and pantheon of smokers. The great thing about Jim Simons is, firstly, he's an older guy, so older people don't care. And he's Jim Simons. So you'll

be talking to him. You know, I've sat in his office and he doesn't say, Greg, do you mind if I light up? No, no, no. There's none of that, Greg, do you mind if I light up? He starts lighting up and the smoke's in your face and you either choke and keep talking to him or you leave and you're not leaving, you know, you spend time with Jim Simons. So, and he's, you know, this weird aberration where he's still healthy in 81 and sharp his attack and he's smoking like a chimney, yeah. Did you get the impression that he kind of thought this book was never going to get written about him?

Because you said it really took a lot of back and forth to get him to sit down and finally, do you think he thought that this was going to happen or not? Yeah, it's good. I think he, I think in the back of his mind he'd like to write a book, and people around them are like, no, he's never going to write a book. So I don't think. See, he kept saying no. I'm not the only person to ask him. I went through the front door and I said, I'd love to write a book with you or about you, et cetera. And he's like, no. And there's people are like, no. And I wasn't the only person. You think I'm the only person. So I think he figured if he keeps saying no, then no one's going to write about him. And he's 81. So, you know, that's it. But right. So I'm not sure he thought I'd be as persistent and obstinate as I was. So yeah, that was the thing that I think surprised him that I kept going on it. So there was a part of the book where I wrote in the margin, odd stats. There was this person on Twitter who had this account called odd stats and they would just do some random data mining and whatever, whatever. And it was sort of for laughs and it was, you know, a joke. However, there was a part of the book, and I'll just read this quote, did the 188 five-minute bar in the cocoa futures market regularly fall on days investors got nervous while bar 199 usually rebounded? Perhaps bar 50 in the gold market saw strong buying on days investors worried about inflation. but bar 63 often showed weakness this blew my mind i mean were they really doing stuff like this

yeah yeah so they broke up the day just explained to uh your your listeners they broke up the day into bars and the question then you can you compare the bars uh and that was i think that was henry lawfer who doesn't get enough credit he's this guy down in florida now multibillionaire very liberal uh even more liberal than simons is in his political leanings there's a whole mix there and there's less than there and you know how do you run a firm with so many different political-minded people. But yeah, so they played with breaking up the day into bars. And eventually they got into, I think, five-minute bars. And below that, it didn't really work. Above that, wasn't as efficient. And yeah, they broke it down. You'll read about it in the

book. But yeah, they get that into five-minute bars. I mean, this is the stuff that we laugh at. And this is what they were doing. It was just, it blew my mind. And I was also surprised that they don't have like, okay, here's their equity sleeve. These are their futures. This is the bonds, currencies. It's one model. That's unique about them. That's a good point that you talk to other firms and they're different models within the firm. And partly that's so that people can get paid differently. And that's another thing. Jim Simons pays as people. He incentivizes people to keep working with each other. The way it was explained to me is if you're going to get coffee for someone or you're cleaning the data and you're doing just a really good job, you're going to get paid.

It's not just the superstars. I mean, the researchers are the sexy. titles within the firm's researcher. But other people who collect data, that's important, too. You said the average employee has $50 million in the fund. Did you get a sense? Was that skewed big time? It's skewed, yeah. Okay. So was a median like a million or big time? I think it's, oh, I think it's probably more than that. Yeah. It's crazy. And that's partly why they don't lose people. And when they lose people, it's a great self-reinforcing kind of system. When they lose people, they're so wealthy that they're probably not going to go work for Wall Street. If you've made a lot of money, working for Renaissance and Jim Simons, why are you going to go work for, you know, some rival?

Go buy an island or an Alp or something. Who are these researchers? Like, it's not, you said it's traditionally not people in finance. It's people in weather and medicine and whatever. Like, what do these people do? Yeah. So it's not just even that they're PhDs. So everyone thinks, oh, well, Simon says a lot of PhDs.

I think it's got here. So the point is it's not just mathematicians, I guess. Yes. Yes. And it's not just any mathematicians. These are scientists. These are mathematicians who were the tops in their fields of physics. They get a lot of astronomers. They love astronomers. What do they do when they get there? They have problems. They figure out problems. It's all like it's scientific. They're trying to figure out patterns, looking for patterns that you and I don't see. And what's affecting the market that you and I aren't aware of. So we all, everybody is aware of, you know, earnings. And then you think of alternative data. So we're piping that in. It's, it's. seems like from the from simons jim simons people there are many more factors affecting the market than anybody else is aware of and i frankly i haven't discovered all of them or what they are that we don't are appreciative but i do realize that they appreciate many and they understand many more of them so they hire these guys like a david donahue who's a superstar at stanford so again he

these are not just bhds are the tops of their fields and simons will say come work for me you'll get paid a lot but more than that, you'll just do the challenge of it, and you'll figure out how to improve our system. And it's a, it's really an engineering problem as much as it is investing when it comes to piping in the strategies and the signals and putting it all into one system, as you suggest. And that's the beauty of it. Amazing. So they're codebreakers. I mean, they're developing code. They're writing code. They're looking for hints of patterns that human eye can't pick up. And they're, they, even if they're fleeting, and they can make them enough money. And my initial read was this, he's just a problem solver.

That was his whole thing is I'm solving problems. And that's, and that's how you hire people who don't really care so much about money. I mean, time and time again in the book, as I think maybe you recall, he's hiring these brains who aren't so into getting wealthy. They don't even care about the market. And that's how you do it by saying, forget, forget the investing and making a lot of money. You can solve a problem. But then once you're there and you start making a lot of money,

money, then as we all know, how do you turn that down? How do you leave? So, dumb question, or maybe not. Let's say that Simon said to you, hey, Greg, thank you for doing this. Great job. I'm going to open up the fund for you. How much of your money, percentage-wise, would you put in this fund? Okay. The Wall Street Journal wouldn't allow me. I would have to quit. Oh, of course. And would I do that. I would, I would, but I would put, honestly, I would put 90% of it. I really would. Now, you know, maybe that's silly and the returns won't be as good going forward, I don't think the returns can't, how can they be as good as 66% a year going forward? But knowing just the talent level, the dedication, there's a sort of an energy within the firm

too that you wouldn't necessarily expect, given that these are academics. But once they get over there, it's high energy, there's a lot of pressure on them, but not crazy pressure. They work together. Yeah, it's a pretty well-run organization. So I would put, if I hypothetically was able to, I'd put nothing. I'm all in. Yeah.

So to the extent that somebody can't stop the market, they actually did. I mean, listen, let's be clear. They only get it right barely more than half of the time. So let's not go overboard here. They don't get it right all the time. They're just sort of more like a casino where casino also doesn't get it right. Well, if you're doing a $300,000, $300,000 trades a day and you have a tiny little fraction of an edge. Yep. Yep. That's it. So yeah, listen, they've beaten everybody else, but there are other good investors out there. And one thing that also shocked me in my research. I figured when you talk to a guy who's been at Renaissance and has made a lot of money and they've retired, they invest only in other quants, you would think. And it's not the case.

You talk to some of the former Renaissance people and they're investing like you and I to some extent, not in terms of on their own, but in terms of their allocations to like David Einhorn. One of the guys I was talking to invest, you would think David Horne is sort of comes up with themes. he's a long short guy. It's discretionary. Yeah, you would think. And I think the reason for that is that they're humans like you and I too. And a lot of the, one of the themes of my book and I hope it comes across is it's not so easy to be a quant. They're fighting their own instincts to some extent. So Simon's, you know, even as of last year, he sort of panicked in his own personal account. So I found that kind of interesting. Amazing. Anything else that

we missed? I think there are lessons, not just for professional investors. I was another thing I jumped out at me. How you can learn from some of these individuals. There's sort of just sort of the theme of persistence and resilience and being able to handle real setbacks. I found that on a personal level, kind of impressive. This was not an overnight success story. The opposite. Right. And there's some value there. You know, this may not be something that the average listener does themselves in terms of investing in full-time trading. But there are lessons. I learned some sort of life lessons just from being around these super smart people and how they appreciate attacking a problem, but also the method, the scientific method, and the idea of not relying on your

instincts. I mean, frankly, when you look in the White House, you look elsewhere, the most important decisions of our society result from sort of instinct and intuition. And that's the last thing we should be doing in society. I wish that some of these scientists were actually working in the White House or the Fed. And it's all about the scientific method and testing hypotheses and relying on data and not using judgment and intuition. We like stories better. Yeah, we love stories. And that's where we go wrong with like we work and Theranos. It's all about falling in love with the yarn. And that's one thing that just reminded to me about from the story, one thing that came true is just be careful as an investor and member of society

about these kind of too good to be true stories, but just any story and rely more on data. And when you look at the most successful companies today, it's like Tencent. It's Amazon. It's Netflix. And they rely on models, ever-changing models. And that's what Renaissance does. Well, this is a lot of fun. Greg, thanks for coming in. If you enjoyed this conversation, definitely get the book.

It was definitely on my short list of books of the year. So congratulations. Great. Great to be here. Thank you. Thank you.