Mathematician Wall Street Genius – Jim Simons

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Mathematician Wall Street Genius – Jim Simons

Published on Dec 28, 2015
James Harris “Jim” Simons is an American mathematician, hedge fund manager, and philanthropist. He is a code breaker and studies pattern recognition. Simons is the co-inventor – with Shiing-Shen Chern – of the Chern-Simons 3-form, Chern and Simons (1974) one of the most important parts of string theory.

Simons was a professor of mathematics at Stony Brook University and was also the former chair of the Mathematics Department at Stony Brook. In 1982, Simons founded Renaissance Technologies, a private hedge fund investment company based in New York with over $25 billion under management. Simons retired at the end of 2009 as CEO of one of the world’s most successful hedge fund companies. Simons’ net worth is estimated to be $14 billion.

0:00great game you know when I was a graduate student here I had just gotten
0:05married and I had $5000 and from wedding gifts for my wife and I we decided that
0:15we have invested so we know we did not go unnoticed by went to Merrill Lynch
0:19and I asked where I had a couple of stocks that I thought might be good and
0:25they said yes those are fine so I bought these stocks and they weren’t good and
0:31they weren’t bad either they just didn’t do anything so I couple of months I went
0:36back and so I need a little more activity here these stocks nothing’s
0:41happening he said you should try sorting beads
0:46and I literally thought that was something you ate I didn’t know you
0:51could trade these things but he explained to me as you can by five
0:55thousand bushels of soybeans for a mere pittance put it down on a bench ability
1:00to operate down or you could buy 10,000 pushes a particularly aggressive was two
1:04contracts and explain why the the wisdom of maryland was with soybeans were going
1:13up big time you make a fortune by being on soybeans I bought it and I bought two
1:21con- tractions soya beans and indeed within the next couple of days they did
1:24shoot up and I was quite ahead and and Knowsley virgin and so on and I went was
1:32talking to a mathematician a few years older than me who was a postdoc at
1:38Berkeley and I told him what happened and I should you have any advice he said
1:42yes so was that he says sell it immediately and I was great advice which
1:48I didn’t take any questions then went down and I found myself getting up early
1:56in the morning and going back and forth across the Bay Bridge to catch the
1:59opening go
2:03soybean exchange and they opened at 10:30 in chicago which was 830 here
2:09which was you know the crack of dawn for graduates who is gonna get up that I had
2:17added up at 7:30 in the morning across the Bay Bridge check and see the screen
2:24and it turned out I did it for a couple of weeks and they actually ended up
2:28ahead but I came to the following conclusion I was either gonna write a
2:32thesis in mathematics or trade soybeans as it was impossible to do both at the
2:37same time so I gave that up but always in the back of my mind I like this
2:41trading business and found it interesting so I got back into it and
2:49then you founded Renaissance Technologies yeah it’s been an
2:58unbelievable success and how much can you talk about what I know how much all
3:08that’s much more secretive National City
3:11oh I don’t tell anybody you know why I should say that I was continued to
3:26mathematics until the mid seventies show that I I had gotten very frustrated with
3:30a problem which is still unsolved and I had come into a little money to an
3:38investment that I made so that and I was between wives noted I was on the wrong
3:45side of the first one I didn’t know that was coming so it was a time that you
3:53know a good time to do something else but when we started I started it was
4:02fundamental who’s had nothing to do with mathematics did not occur to me that one
4:06could use mathematics training I got very interested in currencies or read
4:10the newspapers a bread box and was played lucky I did for a few years where
4:19we did extremely well but then I started looking at the chart things they didn’t
4:26look to be random to me so I hired a great guy who was the world’s greatest
4:33trippin else would you come to work with me will adopt parties and make some
4:38systems built subsystems but he came we started building a system but he was
4:50really interested in the markets themselves one day he didn’t show up
4:58call you didn’t call it just didn’t show up for work and then he came in around
5:07one o’clock I said where you been
5:09how you doing research I wanted to do some production that was an essay
5:16parlance he said I’m tired of doing our it’s time to do some P so well what P
5:23did you have in mind exactly and he said well margaret thatcher the pound has
5:28been held down by margaret thatcher holding down there but you can’t she’s
5:33been sitting on a budget cuts that are from anyone when the power is gonna run
5:36up this come out of the models we believe there’s no law died I’ve been
5:41reading everything I said we should come in a couple hours earlier cuz margaret
5:45thatcher just stood up and said what do you mean well he’s let the power go Lisa
5:51how much is it up already he said that’s nothing gotta go okay maybe you’re right
5:58so we bought some of that would have been in n he never wanted to do any
6:03model building after that
6:05lazy is a waste of time I mean if I can tell by margaret thatcher’s gonna stand
6:10up what do I need to build these models and he was right we had a very lucky
6:16streak and but finally I you know I really did want to build some models so
6:22what we needed was a very good computer guy who happens to be sitting right in
6:30front of me here who came to work for us and we brought some other about
6:35petitions are we did some good models and then I could see after a while but
6:41the models were were a better way to do things are fundamental training which is
6:49just too for me it was just too gut-wrenching one day you come in you
6:52think you’re a genius market your way next day an idiot and even if you are a
7:00genius one day more than your an idiot still very stressful way to record me
7:06tomorrow building may change and we managed to build more and more and more
7:12and more about traditions other scientists astronomers guys like that
7:17just kept building that are building it up and it worked
7:23what about this is it’s ron is what makes them good financial model builders
7:35well you know it’s a big data center naturally the way we look at the market
7:42they put out a lot of day that is priced at this volume data there’s all kinds of
7:46data that comes out and the goal is to analyze data stream and try to figure
7:52out at least probabilistically what’s coming next and so it’s
8:03you know it’s kind of like cold cracking except a little more than a little more
8:07baby at least you know there’s a machine that’s doing this has substructure to it
8:13here at you know it’s the human race that’s making these things happen but
8:18still the certain predictable features will shorten on randomization these data
8:23streams are certain certain things that could be talked about and that’s what we
8:27did and I shall I can’t promise because astronomers physicists can make an
8:34experiment you know we could see let’s see what happens but this edition or
8:39chemistry makes these two things that are stronger he just looked it looked at
8:45the data he plays that he cannot do an experiment you cannot say when it would
8:48happen at this stock crashed into that stuff you know you can’t do that all you
8:56can do is look up in the sky or you know radio frequencies will get the data down
9:03from the heavens and try to dope it out what’s going on obviously there’s a lot
9:07of theory that people bring to bear but those guys have to play the data as of
9:12ways they cannot create their own data and we can create our own data we can’t
9:16do a little economics its permit people won’t be cooperative really so you just
9:24have to play the data as of late edition’s astronomers say they’ve all
9:30been very helpful to us
9:32he signed that alice is particularly useful or no more than you know more
9:38than I have hired a very good people from that area but it’s really we hired
9:45people did does who are on the research side who have demonstrated that a good
9:52scientists and who expressed interest in this kind of work most of time that
10:00works are pretty well that’s not always but we just continued to build this and
10:16we went all technical in 88 and so whatever news
10:29one-twentieth of all your funds yeah we we don’t do anything which not only my
10:37daddy and funds the most spectacular in the longest since 1988 and it’s that it
10:49was done better in general
10:52yeah it’s also captain size ok so what exploits a certain set of features but
11:04like anything
11:06you can’t go to the market will it take so much so we had to camp that we had to
11:12madonna is now fund is now owned by the employees of the firm the outside
11:19investors were all brought out over the years because we couldn’t bring in what
11:24happened we had to limit the capital the other two funds that we’ve started
11:29designed to hold more capital one or two terms considerations doesn’t you don’t
11:40need to traders
11:41quite as quickly and therefore they can hold more capital but they’re not gonna
11:46be quite as good but I have plenty of money in those phones yeah and you’re
11:59all welcome to advance this I guess that is not literally true that’s very hedge
12:08fund times

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