Dr. James Simons, S. Donald Sussman Fellowship Award Fireside Chat Series. Chat 2. March 6, 2019
By Finance at MIT
Summary
Topics Covered
- Soybeans Beat Thesis Writing
- Luck Trumps Gold Mania
- Simplify Complex Systems Early
- Hire Smartest for Collaboration
- Rating Agencies Ignited Crisis
Full Transcript
welcome everyone I think you're in for a real treat um first of all um I'd like to welcome you all to the MIT
Sloan um we're here today because uh this is part of this is the there's been award made for the S the um susman Fellowship which is given every couple
of years and it was funded um to honor um the achievements and um the opportunities Donald sasman has given to
a bunch of people in the fund management business he's also um somebody who was very much a Pioneer in the whole hitch fund uh
Arena um we have um it Donald for those who weren't here last week um runs Paloma partners and at Chinese private
Equity investment firm um and um is is very is is very much involved um you know with all things investing um to
this day this year we have um awarded the uh the fellowship to Jim Simons when in fact the award really is almost hours
for Jim having agreed to show up um uh Jim is an extraordinary man um genuinely extraordinary um it's very hard to
describe how extraordinary because um if you think about this you know every day he goes to work or when he did go to work uh it's a discovery and a battle
it's a competition it's like an athlete winning the Olympics pretty much every day that's probably the best analogy it's a fiercely competitive environment and anybody who knows Finance knows how
unbelievably difficult it is and how many people would like to eat your meal um Jim uh not only is a great mathematician and again those who were
here last week will know about this um but he's also what I describe as a real mench an extremely nice person who when I first met him which would have been around 1990 or
91 his fund was maybe 200 and Jim will correct Me Maybe 250 million which by then was fairly large but by today's standard it's very small uh had this
certain irreverence and confidence and directness and one of the things features that that makes Jim so very special and you'll notice that today he
gives extremely concise direct and unambiguous answers to any question you ask him um the other thing to note about Jim is for those who know some of the people who work for Jim or know some of
the history it's unbelievably difficult to manage intelligent people um and I don't know many people who do it as well as Jim does and it's
worse when there's a lot of money involved um Jim uh um uh one other thing to say there a few things I there's so many things to say but one of the things to say about Jim is that his track
record is so extraordinary that to most academics it's inconceivable and it's somewhat ironic that we're here at MIT in the and this
is probably the best Finance faculty in the world at least some my friends tell me um and um there's a there's a paradox here because Jim never hires Finance
guys or mbas or such or we he never used to and it's quite wonderful to have him speak to this audience I'm sure there other departments here as well um but it is interesting that you know you have
departments studying all kinds of features of the financial markets and um Jimmy does a away with Jim does away with publishing papers instead just
cracks them um so Jim um Andrew uh over to you thank you [Applause]
well I want to uh I want to start by joining Andre and my MIT colleagues and thanking Jim for joining us today and being here and um I have to say that uh
this is a a real pleasure and an honor for me because uh I think it's fair to say that Jim Simons and Renaissance Technologies is certainly the most successful quantitative investor in the
history of investing but perhaps actually you can drop the qualifier quantitative and uh so there's a real really interesting set of issues that we want to get to today before I do that
though I need to um uh lower your expectations of the interviewer because you know this three lectures that or three Fireside Chats that Jim has agreed
to uh uh mathematics money and making a difference only one of those M's is proprietary and confidential and that happens to be today's topic of money so
so Jim and I agreed on some ground rules I get to ask all sorts of nosy questions and he gets to say pass because it's confidential and I'm I'm sure that uh the audience will will have a chance to
ask those questions too and I'll have a chance to say no I won't answer so um Jamal I'm GNA ask you um if you don't mind to recount a bit of your
biography the way we did last week but instead of Tom's focus on your mathematics uh career i' like to turn it around and focus on your business and finance career so uh I'm going to start
at the very beginning um you were a very precocious mathematics student you mentioned last week that uh when you were two or three years old you were already doing the powers of two um were
you also precocious from a business perspective did you think about any of these issues um as a child as a child I thought I had no interest in
business which is not to say I had no interest in money but I had no interest in business and um but uh you know was a
little kid I had a friend who was very rich and I thought it's nice to be very rich I I observe that uh but just I just
focused on math and uh for quite a while so unlike Warren Buffett who had a newspaper route business or Bob meron who I think was trading stocks when he was 10 you had nothing to do with uh
with Finance uh nothing to do with Finance okay so uh when did you first get interested in business when you were at MIT you mentioned something about
that uh last week I'll have to call you back what could I say I hope that wasn't a margin call
if it had been I would have said the same [Laughter] thing so um when did you start thinking about business you mentioned as an
undergraduate you had some uh friends who were you know doing some business in Colombia well I I met some I I made
friends at MIT with two Colombian boys uh and uh they uh at a certain point uh started a business and in fact it was my
encouragement that they started that business and my father and I invested a small amount uh in that business which turned
out eventually uh to be a big success so what what possessed you to think about that I mean that takes a certain amount of initiative to actually what possessed me to think about that
particular investment was that I had when we graduated MIT uh three of us one of whom was the Colum
boy uh and his friend was in Bogata three of us uh rode motor scooters from Cambridge uh to
Bogata now we'd expected to go all the way to bues Iris but uh by the time we got to bogot we were exhausted so we we we stopped in Bogota and I and stayed
there a week or so and I saw this country Colombia and it was really a place that you could do anything I real I was told if you start a business a
manufacturing business and you're making something that was imported previously imported to Colombia the government would shut off those Imports and give you
clear road to to run so I I thought my friend should start some kind of business like that which they did but that
was my first interaction with money was when uh I I was a first year well I was a second year I went out to
Berkeley to finish my PhD I spent two years there and the first year early on uh I got married and uh we I had five I got
$5,000 worth of wedding gifts so I my wife and I decided Well I decided she but she was willing that we
should invest this and I uh I had a couple of stocks which for no good reason I thought might do well and uh so
I want open an account in San Francisco with with uh Merl Lynch I bought these two stocks I went home and for months they did absolutely nothing so they
didn't go down they didn't go up so I went back and I I said do you have anything that's a little more uh exciting
and he said yes he said you should buy soybeans maril Lynch thinks they're $2.50 now they're going to go up to
$3.50 what are you talking about soybeans I knew about stocks I didn't know about soybeans he say yes you could buy a contract there 5,000 bushes you
could buy two contracts you get a lot of Leverage and so on all right so I bought two contracts of soybeans and within a week it had gone
up quite a lot and I'd made several thousand dollar maybe two or three now that was exciting and uh I I came back
to the math department and I said to one of the older guys I told him what happened he said I said you have any idea what I should do he said absolutely sell it
immediately which was extremely good advice because within a day or two it had gone back down and it was bounced around and actually had a little loss I
closed out the position and then I thought well I should have taken a smaller position and then I could have held it
more and I did I bought one contract of soybeans and was going back and forth early in the morning to watch the
opening in Chicago because it was it was uh early in the morning in San Francisco when the Chicago open to trade these things and I was going back and forth
across the bay bridge watching the board and uh and then and I and I had a little profit at a certain point and I
realized I am either going to trade soybeans or write a thesis I was in the middle of starting to write a thesis and I could see I
can't do both at one at the same time so I sold that one contract for I think a very small profit and that was the last
time I traded anything for a number of years but I did write a thesis and uh got a job here in MIT as a result so so
just for clarification your first investment was a couple of stocks and then the second investment was soybean Futures contracts yeah and
these contracts as I recall are averaged like 25 or 50 to one is that right it's very highly leveraged I don't know high octane kind of invest yeah it was yeah
and your broker felt that you were you were a suitable investor for that uh as a graduate student well uh he didn't ask any questions oh
great he was just doing his job I came in I had enough money to buy this stuff so he right he figured it was all okay yeah and and so you had never invested before that you didn't have to take a
course in finance or business nothing okay great so now you're an assistant professor at MIT and it's pretty clear based on your thesis and the early work
that you did that you were going to have a very good career in math and you did so what got you interested in business at that same time because you continued
to have an interest in it didn't you continue having an interest an interest in business well when when I came back to teach at
MIT uh the first intercession I went down to Bogata to visit with my friends and told them I was coming and I won't leave until we have found a
business and they found one while I was there and decided to partner up and I knew they would they were very smart guys and they had a very good sense of
business which I I don't think I ever had and uh so they started this uh this business my father and I
invested a small amount and I had a borrow from everybody but I did and um so that was the the first the first thing and and
then there was there was not much I could do about it so I kept doing doing math and uh but I actually uh since I borrowed
some money uh I needed to pay it back and and it was uh there was a place in Princeton called The Institute for defense
analyses which uh was a very highly classified joint and it specialized in cracking Russian codes and protecting
our own so it was a uh under the opes of the NSA and they paid a lot for mathematicians so I applied to them and
and got a job and uh enjoyed the job and was able to start paying down some of my debts because they it paid maybe double
what I was getting at at MIT wow so uh so uh well and I like I like that place it it was it was interesting now you you talked last week about some of the work that you did
there uh but one of the things that I wanted to ask you and I didn't think it was appropriate to ask last week because the focus was on mathematics did any of the uh uh work that you were doing there any of the mathematical tools that you
were developing have any applicability to some of the work that you did later on in finance in a general sense yes now I
didn't get into Finance for 10 years after that I left there in ' 68 and really didn't get into Finance until the late
70s but uh I learned about computers uh I learned about you know the fun of coming up with some algorithm which might crack a code most of the
time it didn't but once in a while you were lucky and and uh I didn't know how to program it all and never did learn how to program it they had programmers but I like the idea of developing
algorithms seeing them put on the computer and seeing uh you know if it's if it's going to work so that
experience was very influential when I went into the hedge fund business and then gradually started to make it
systematic as well as opposed to uh to fundamental trading uh which we did at the beginning and and uh so anyway I was a
mathematician I was getting frustrated with some of the research I was doing I've worked on a problem for two years didn't get anywhere uh it's never been solved so
you could see it was a hard problem uh that's a good one too uh and um the South American Business had uh
was beginning to throw off some money so I had some money and uh I thought I would
uh start investing and uh and I had an interest in foreign currencies I don't know why but I did
and uh I read a lot about that so we started uh I started started and I got a partner investing in uh in foreign
currencies and uh that did very well I was this before uh you left for Stonybrook or oh no it
was after I left for I I'd been in Stonybrook for for uh six years by then okay you know I I I went to Stonybrook
in ' 68 and and it was 76 or 77 that we started doing this and but I thought we could I looked at the charts and they looked
like there was some structure to these historical charts that one could perhaps exploit so I hired the best crypto
analyst in the world guy named Lenny bom who uh you may have heard of uh the bom Welsh algorithm the EM algorithm
expectancy Max maximization uh he discovered that so he came to work with me and uh and we built
a little system even though I was trading fundamentally at the time uh you know seat of the pants sort of thing uh which
way there's a wind blowing um we developed this sort of primitive currency trading
system but uh we we didn't actually put it into practice uh because one day uh Lenny didn't show up for work until the middle of the
afternoon and I I should say that Lenny loved to read the broad tape there was this tape we called it was the D we called it the
Doomsday Machine because it just clicked it this broad tape would roll all day long giving the financial news of of the
world and he liked to study that he was supposed to be studying making systems but he liked to read that tape so he came in late and I said where you've been and he
said Margaret Thatcher has been sitting on the pound and it's has to go
up I said oh well I wish you'd come here this morning he said why I said cuz Margaret Thatcher just stood up
and Margaret Thatcher just stood up and the pound is way up he said how much is it up he I said well it's up at nickels 5 cents so far he said it's going to go
up 50 cents a dollar buy pounds we should buy pounds I said okay buy pounds sure enough it went way way up and that
was the last time Lenny wanted to look at any systems he just felt uh his good
intuition would be uh suitable and we'd make a lot of money and and we did we did doing fundamental trading we started
a fund called limy and uh the fees were uh 25% of profits no fixed fee which was
you know sort of a reasonable thing and with Lenny as my partner the first year the fund doubled after fees and the
next year year it multiplied by six after fees so it had well you know 2 * 6 is 12 so uh everyone had 12 times as
much money as they started with and it was it was fantastic and it was all fundamental Trading
still I felt that okay we can't we were lucky in in certain ways uh uh I I'll tell you
one good story about luck uh gold which was uh illegal to trade had
become legal to trade and the gold market gold prices were going up and we bought gold in the in the firm we bought gold we had a pretty big
position in fact Lenny and I split the position half of it belonged to him in some sense and half beat belong to me and uh it was at
$2.50 I mean and 20 $250 and got up to 300 400 500 550 I think I said Lenny you know I think we should sell this already he
said no no you don't know how far it'll go you don't know how far it'll go so I sold my half and it and it kept going up
and and one day it it reached $800 and that day I happened to be speaking to a friend of mine who was a stock broker but we were just I was just chatting
with him over the phone and I said what's new he said well what's new is this my wife went into my closet this morning and cleaned it out
of all my old gold cufflinks and tie clasps and she's now down uh uh selling it I said well dick I mean are you
having financial difficulties how he said no no but she's a jeweler which he was and she only had a stand in the Short Line I said the Short Line he says
don't you know there's lines and lines of people selling gold I said no but I'm very glad you told
me I hung up with him I picked up the phone which went right to the floor of the exchange and I got Lenny to come over and I said Lenny sell the gold he said no you don't know
how far it's I was the boss and I said sell the effing gold he said okay okay and he sold the
gold it was it was $810 or something like that the next morning we came in and it was $820 and he was so mad by the end of
that day it was $650 the market collapsed and went nowhere but down after that until it it got back
to $250 or 300 not not in a week but it it just collapsed now that was totally good luck I mean it was good that I realized if everyone is selling
something it may be a time to sell it yourself but uh uh but uh it it was uh it was luck it
was just it was just luck so we went we did well but I felt that this should be systematized there should
be a way to systematize it and I brought in another mathematician a very strong mathematician named Jim ax and uh to do fundamental trading but
he knew about that we had made this currency system and he looked at it and he got a good programmer into the firm and he realized
this system could work for all all Commodities really it was uh it was a pretty good system sort of so we started
trading that system and it did pretty well and he did research and improved it and improved it we were still
fundamental trading but that wasn't even going so well I had gotten interested in uh Venture Capital to some extent so
this memor company was also starting to invest in startup companies and uh and
uh axe was running this uh trading and at a certain point the uh investors in
limite they didn't like this liquid the uh uh Venture Capital they like the trading uh and uh so I decided to break
up the company Lim Roy and make a fund called Medallion jimax would run that fund and
we put the the uh uh the Venture stuff into a uh a liquidation only uh uh fund and actually it ended up doing pretty
well so now we had The Medallion fund and everyone invested in The Medallion fund from lioy and it did very well for about 6
months and then it started losing money and it was losing money steadily now he and his team had
developed a very complex system very complex system and it had I don't know many dimensions of in it one thing or another
and I said you know I have to understand what this system is actually doing and he said oh it's too tough we I can't explain it to you it had this Bell and
that whistle so I said come on I'm just going to project this into the two principal uh dimensions and see what it looks like and it was nothing but a
trending system plain and simple trending it had this these other little Geek Things whatever they were but it was basically a trending system and
trending which in in in commodities and currencies too which historically was a very strong uh thing had had in the last
several years just just sort of gone away with no reason to think it would ever come back so I said we're closing the fund
and uh he was very annoyed uh but I was the boss so we closed the fund and I told the investors we're going to spend we're going to to
do a study period and we're not going to trade at all of course we're not going to charge any fees oh at that point it was five
five and 20 it was 5% fixed fee and 20% of profits and uh and everyone stuck with us a few people redeem but everyone
stuck with us and for six months uh and we brought back someone who had left the firm it's a long story we brought back this other very good guy
ax left and he and I especially he he had some ideas of much shorter term trading uh not high frequency in and out
in five minutes but trading on a much shorter term and he developed a pretty good system and together I helped him and it
got better and after 6 months we went back in business only only systematic trading and from then
on we never looked back it was it was just went from strength to strength and uh I hired a lot of scientists w a lot
of computers and over the years the system got better and better and better so Jim we're going to focus on the Renaissance Medallion Fund in a few minutes but I I want to bring you back a
little bit because there are some interesting precursors that I think speak to the success that you enjoyed uh one is that um when you were at Ida uh
is that where you first met Lenny Bal was he there live down the street and as I recall his early work the Bal Welch uh algorithm was really designed to
estimate hidden Markov models that right which uh for many of you I think you know it's the precursor for a lot of the techniques that are used today including deep learning so it's an interesting
history to that in terms of what you uh what you encountered there yeah he he developed that algorithm with this guy named Lloyd Welsh which was supposed to ex uh
estimate uh hidden Markoff models whatever that is but there are a lot of parameters and you and it it was an algorithm which just kept climbing it
kept reestimating and reestimating and with each reestimation the expectancy of these particular parameters whatever they were got better better and it
changed the parameters and it got better however no one could prove that it worked no one could prove that it worked it clearly did you could start at any
place and all kind it definitely worked but how did you prove how could we prove it so I actually I worked on that a little while while I was at Ida
and uh trying to prove that this thing actually works uh that it climbs at every step but uh
I couldn't and anyway I left Ida and Lenny and his friend Petri finally figured it out and they wrote it was a
long paper it may have been two or three papers now today it turns out you I'm told you can prove that in just a couple of pages because that there was some
theorem of which they were unaware which would have made it short but but anyway there was the algorithm speech recognition it was very good for speech
recognition a whole lot of things yeah yeah so um I I'll get to The Medallion in a minute but I I want to just ask you two more things that lead up to The
Medallion fund one was you left Ida to join Stony Brook's math department and at the time Stony Brooks math department wasn't nearly as strong as it is now can
you tell us about that and U what motivated you and and what your experiences were there well I got fired from
Ida I got fired did I tell this in the last talk last time but I think it would be worth repeating because not everybody was here so okay so I always say getting fired once is it
could be a good experience you just don't want to make a habit of it you know but but I I did I got fired
uh okay the head of this place ID who was in Washington DC uh uh which was a was a big organization
and one of its units it was this small unit in Princeton he was name was Maxwell Taylor some of the older folks in the audience might remember that name and uh he wrote
an article lead article in the New York Times magazine section about how we're winning in Vietnam we're doing great we have to stay the course and so on this was
1968 and uh I did not have the same opinion as he and I wrote a letter to the times the first sentence of which was not everyone who works for General
Taylor uh subscribes to his views or something like that and I gave my views which was as you get out of there and as fast as we can and nobody said anything
you know nobody said anything they could have tried to lift my security clearance but there would be no reason for
it a few months later a guy uh claiming to be a a Stringer for news Newsweek magazine said he's doing an article on people who work for the defense
department and a repose to the war and he's having trouble finding anyone uh in that category could he interview me I was 29 years old no one had ever asked
to interview me before so I was very excited and uh he said well okay so how are you responding to this uh I said
well at Ida you're supposed to do at Le spend at least half your time on their work but you could also spend
up to half your time on your own work and I had been doing a lot of math uh in that period so I said so my attitude is
my policy is until the war is over I'll do only my own work and then when it's over I'll do an equal amount of time doing only their work and so that'll all
balance out so that's what I said then I went back to the office and I decided I better tell my boss that I gave this interview would have been more
intelligent if I had told him before I gave the interview because he would have said don't give any interviews but uh he said 'well what did you say I said 'well I said about the half and the half and
so he said okay he went into his inner office and called Maxwell Taylor and he came out in five minutes and I said well you're fired I
said I'm fired fired I said you can't fire me my title is permanent member permanent member and he said well you know the difference between a
permanent member and a temporary member I said no he said is a temporary member has a contract but I was a permanent member and I didn't have a
contract so I left of course I had to leave and uh I had to look for a job I had three kids but I was certain I would get a pretty
good job because I had just done some actually quite important mathematics and it was uh I've been giving talks and so on so I knew I'd get a good
job but as a professor somewhere but Stonybrook came along and offered me the position
of being chair of their math department and it was a weak Department with one or two exceptions and they wanted us build it up and they'd been
trying for a long time to find a older distinguished person to come as chair and they couldn't find anybody but they found me and uh I thought this would be
really fun I'd like to build something and uh so I took the job and uh the university
had a lot of money at that time which it doesn't have so much today it had a lot of money uh Rockefeller was the governor
and he loved the State University so uh I I hired a lot of great people it was a wonderful experience I did a lot of mathematics during those first few years
myself it was a very very productive time so that's so then what led you to start doing your currency trading because you at some point you left Stonybrook to do currency trading full
time I left Stony Brook first I went halftime and then I left all together and was in the training business yes and so what what led you to do that
that why did you well because I I as I said I was uh stuck on a problem uh I had come into some money I was trying
that out I liked it and I thought well I'll just have a new career my father was very opposed to it he said look you have tenure you have this wonderful job
they can't take it away from you I did have a contract that in that sense and uh why do you want to take this risk but I I thought it would work I thought it
would work out and I was pretty confident and so in your fundamental trading for currencies can you share with us how you did it what I mean it
was totally non-quantitative would you sayt and so did you did you use for example technical analysis people argue the charting I didn't do any technical
analysis I I I read all the newspapers uh The Economist there was a lot of writing uh I just paid a lot of
attention to to currencies and in these Curr currencies had just been tradable uh in the open market because some some countries still had fixed
currencies fixed to the dollar and you couldn't uh well you could trade it but it it it it was fixed but
uh so it was it was just fundamental fundamental stuff and uh it worked it worked reasonably well I would say worked reasonably well
um and uh so so but that was it but but the problem with a a business like that is
I'd walk in one day everything was going my way oh I'm a genius the next day I'd walk in everything was against me oh I'm
a dope it was a very stomach wrenching business whereas with a system that you can develop okay you have a system you you
do the computer says to do you have a made a historical study of the system that you're using and it
worked with a very high probability this system was going to work and uh so I I'm was much more satisfied with that
approach and uh and we hired scientists and so on to build these systems and improve them okay so now let me talk about The Medallion fund so you know
when I teach in direct ref Finance I usually start with a single equation on the board and the equation is mathematics plus money equals finance and I would argue that The Medallion
fund pretty much epitomizes that because the system that as you described has yielded just extraordinary returns and at this point the track
record is confidential but you did give an interview uh one of your very few interviews that you gave in 2000 to how Lux and so I want to just read to you what was written at that time about The
Medallion track record uh Simons by contrast just keeps getting better consider his performance over the past decade uh and this is
between 1988 when it was launched and 200000 since its Inception in March 1988 Simon's Flagship $3.3 billion Medallion
fund has amassed annual returns of 35.6% compared with 18 % for the S&P during that same that was after fees that was after fees and at that time the
fees for The Medallion fund at its peak was five and 44 so 5% fixed fee and 44% of the
profits so that that track record uh yielded 2,478 point6 per return over the 11
years from 98 to uh sorry 88 to 99 and the next best Fund in the hedge fund databases at the time was the Soros
fund the quantum fund which was only 1,7 110% oh so so and but that was of 2000 so um first
question how's the track record been since then because nobody knows for sure I know a few and a few other people know
uh the track recet has continued good we we I don't know if at that time we'd already raised the fees to 5 and44 first we raised them to 5 and
36 and then uh the investors all complained but they just wanted to have more how can I get more and uh then 5
and44 and there was still a very good return at 5 and44 so no one wanted to redeem but we realized that there was a limit to how much we could
manage we understood the uh you know system and uh you know it could manage a certain amount but it couldn't man
manage huge huge amounts you know trillions uh hundreds of billions certainly couldn't manage that kind of money so we decided to and because we were making so
much money uh the fund was growing internally first we uh prevented any Outsiders from
no new investing uh investments from Outsiders except for the employees and then uh we decided to buy
in The Outsiders that was in 03 I think 0304 and ' 05 by the end of ' 05 uh we had bought out all the outside
investors and it was just owned by owned by the uh employees and it did grow to
some extent uh but because it did and it could manage that much but at a certain
point it's been it's been uh capped off and uh we started and in that same year ' 05 we started some funds for the
public which have done very nicely uh and they have no uh uh clash with Medallion they they're much longer
term expectations but uh those funds have done very nicely and uh so at the moment there's a that there's 45 billion
in those funds being managed and uh but The Medallion fund has always stayed The Medallion fund has stayed at a certain size which I won't share yeah but it's
not as big as 45 million yes can can you share with us how many employees you have yeah we have 310 or 20 or something like that yeah
counting everyone we have a lot of scientists uh we we really you know you have to in a business like this just
keep making things better keep improving the system because other parts of it are going to wear out after a while people
people will catch on to this or they'll catch on to that so you you just have to like in any business in any business you just have to make things better and better and better because that's what
everyone else is trying to do and uh so so we hire the best scientists we can uh people have said to me oh well you you know you're you're not doing the
world a favor these people could be doing great scientists you know for uh they'll make all this money and then they'll give it's a charity I'm not worried that it's going to ruin the
world by having uh good scientists working at Renaissance but we do have good scientist working there and uh and that's
been that's been the model the model has been first hire the smartest people you possibly can that's a
sensible uh uh principle work collaboratively let everyone know what
everyone else is doing now some firms that do have these systems they have little groups of
people this is ours and this is theirs and and they'll get paid accordingly and so on to how their system
goes we have one system and once a week There's a research meeting if someone has something new to
present it gets presented it gets chewed chewed up and and and looked at from everyone has a a chance to the code is
there they can run the code and see what they think is does this really work and so on so it's a very collaborative Enterprise and and I think that's the
best way to accelerate science is people working together and uh so that's that's that and uh we have great
infrastructure wonderful infrastructure so people can get right to work uh we've had people come in start to work and say my God I'm doing this after after three
days I've never been in any place where you could get up and running so quick so uh it's well organized and we have great
people so you know obviously much of what Renaissance does is confidential and uh in particular the even the people that you have uh are confidential but I
think it's fair to say that um if you looked at the quality of the colleagues you have they are probably among the top scientists in their field in many
different fields is that fair to say well I don't think there's anyone who would well okay I'll tell you a
funny story uh we had a uh we have a Renaissance a colloquium uh every week San comes and
gives a talk a scientist and and it's open to the public and um one day an astronomer young astronomer came in a friend of his already worked at
Renaissance and and this guy came and and he gave a very good talk he gave a very good talk and I took him aside afterwards says you know your friend is
here and uh you would like working here you would like working here we would like to have you work here and he said well it sounds very appealing but I'm
right now I'm in a project that I science project that I really want to complete before I think about doing anything else so he won the Nobel Prize
he won the Nobel Prize he was one of the two teams that learned that the Universe instead of decelerating was actually
accelerating and it was it was big news and so I think he made the right decision you know most people would but that's the
question rather have a Nobel Prize so uh so he's the only scientist of Nobel Prize quality that we almost got and and
I don't think anyone else in the firm is probably that good although some of them have been terrific I I uh some of them I
don't know they don't give Nobel prizes in mathematics but um but they do in physics of course and we have a lot of people who are physicists experimental
physicists do well astronomers do well uh they look at a lot of data and analyze it and that and that's what we do analyze data so that leads me to my
next question how do you manage all of these incredibly talented people often with really huge egos you you talked about collaboration but uh having
been a a chair of a department and you're having been a chair of a department uh it's not always easy to get big OS to collaborate
well a department chair does not have that much power right uh and I'm sure and any professors in
the audience know that uh you don't have to do what your department OB he says you have to teach this class okay you teach this class but as far as your
research goes uh you can do what you want um so uh but we did at Renaissance say you know
we' like you to work over in this area or work over in that area but uh but nonetheless so there are groups there are groups that work on different things
and and in the research area but because they see what's going on every week in everyone else's group they can sometimes and often do make a suggestion hey you
know what we're doing over here I think could affect what you want to do over there the the the way people are paid
everyone gets a a piece of the profits and uh but they're judged it's not what did you accomplish this year you know I'd have every year
people come in would come into to me and say you know I made so much money for the company my work made so much money for the company last year I I deserve a big rise I said oh yeah well that was
that was good work didn't it derive from so and so's work he says yeah yeah but we we I I really made it better and I said well and didn't you work with Joe
and Susan on this yes yes I I agree I I did I did that so I said you know if I added up all the money that everyone who
comes in here tells me they made for the company this year it would be five times as much as as the company made so uh you
know uh but we look back on three years four years five years how have they've done and they'll get raises accordingly um
and um and that's the way it works and people are well no one's perfectly happy with everything and I can't say there's no one who thinks he should be paid more
which is human nature but uh everyone's pretty happy it's a it's a very happy place yeah it's a very happy place so this this leads me to the the final point that I wanted to make about The
Medallion fund and what what you built over the years so you must know that that you and your colleagues at Renaissance have been an inspiration to many many Quant ative investors many
students here many faculty myself included and the favorite topic among quants getting together for beer or or
stronger um is how do you do it and why is it the case that even to this day there's nobody close to Renaissance and so I have my own conjecture that I'd
like to run by you and and get you to react to it and my conjecture is a little different it's not about the systems it's not about any particular
magic formula or or uh algorithm but rather being at a management School uh I guess I'm biased I actually think it's about the management
specifically I think it's the combination of the fact that you actually ended up being a very good prop Trader uh first before you even thought
about the mathematics you actually became a good Trader and then with that intuition of what it means to make money and lose money you ended up being a good
people picker and you ended up building around you an extraordinary team and that team has grown based upon the culture that you created you just mentioned that at the end of every year
you have these awkward conversations with people who can adjudicate among these very big egos except somebody that commands the respect of anybody so do you agree or disagree with that
character ation more or less I mean it was it was certainly good to have done fundamental
trading to you know just understand the mechanics of markets and so on uh of course we don't do that people don't do
that and I have to say I left Renaissance U when I was 72 so that was almost 9 years
ago and the management there uh just carried on we had some great
leaders and uh we haven't Mr a beat uh they've done just as well maybe better than they would have if I had stuck
around but I felt uh it was time for the younger people to take over I was had started spending more of my time with
our foundation which is a top IC of next week's uh
encounter and uh so I thought okay what it was two people who were co- uh executive I don't know I don't remember
what that title was but they had a very high title and gradually I had given them more and more uh responsibility so when I left
uh it was it was just fine and uh and I always keep pushing them to hire very smart young people and that's
I think my biggest contribution I'm the chair and we meet every every month and so on but just hiring great young people
into the U into the into the business is is the best thing you can do and your tenure as chair of Stony Brooks math department prepared you for that in some
ways yeah sure so I want to turn to a few miscellaneous topics now and again feel free to tell me that uh not interested in them as
early as 2003 Renaissance Technologies raised concerns about the birdie made off Ponzi
scheme um H how did you get uh wind of that and what motivated you to to even say anything to the SEC
we had had money invested with ma off for a long time not not the firm but uh relatives of
mine uh our foundation had an investment uh with uh with moff uh and I knew him a little
bit and he was really amazing he he kept coming up with with these very very steady returns very steady Returns come rain or
so at a certain point I said this guy has to know something that we don't know in fact he he certainly knew something that we didn't
know I had all the uh the uh tickets the the what do you call it the confirmations for going back years so I asked one of the guys in the at
Renaissance well in the company I was Renaissance that to look analyze these trades that he was doing and uh tell me
what you learn what what's a secret so this guy went to work and here was his
conclusion well when they put on a position they if they're buying something they generally get a very good price maybe the low of the day if
they're buying maybe the high of the day of they're selling but most of the time they're not putting on positions they stick with the position that account he
said for maybe 10% of their profits they claim they have t- bills sometimes and so was interest but 80% of the profits was a complete mystery it
was a complete mystery now what they did was let's
see they would put on a big position according to the tickets uh W with uh stocks which would the
collection of which would be approximately the S&P and then they would buy a a uh a put
or a call to protect themselves against uh uh outside moves well from what we understood they
had a huge amount of money under management so you would think when they put on these puts or calls or whatever it was it would it would move the market
actually in in those things but we could see no no evidence of that they said they were putting on these puts and
calls but you look at the put and call Market there was no evidence of any such activity
so uh I I thought well let's let's get out of this thing uh even Medallion had a little bit invested in it Medallion
had extra cash at that time and we had put it with so we sold it and uh and then nothing
happened and uh several years went by one of my relatives called me and said you know do you still like made off and I said
well I can't tell you to take your money out of it because he's been going for a long time and he he keeps on going and he's he must know something I I don't I
said I took my money out but I I couldn't advise someone to take their money out it never dawned on me that it was a Ponzi scheme I didn't know
what the heck he was doing doing but I just didn't like the looks of it so uh we couldn't understand what he was doing so that's why we got out 5 years
later uh the crap hit the fan and uh he was he was outed and uh and it was well
everyone knows what happened next so uh and a actually they look back six years for any profits that you may have made
so we our foundation had to had to give back some money to the uh to people who
had lost it uh but uh it was it was just uh the craziest thing the craziest thing in the world made off so the irony is
that the fake track record that made off posted was actually not as good as the real track record The Medallion fund that's true that's true so well it was Prett PR steady I have to say that it
was a it was a pretty pretty it was pretty steady but it was uh and then the the uh I don't know SEC
started investigating us because some people had said look these Renaissance people we don't know what they do either because of course no one knew exactly what what maida did and and of course we didn't tell people what
we were doing they couldn't see our portfolio they couldn't see anything uh by that time I think we had already
given all the money back to the investors so I could say well look we we can't be doing anything wrong because it's all our own money so so we we we're
not we giving back all the money to the investors but uh they did uh study us and work us over for a while and uh of
course they couldn't find anything bad um and then they went home right but but uh it was as a result of of made up that we were so examined by the SEC right so right around that time of course was the
financial crisis and that probably precipitated maid off's unraveling um what do you make of the financial crisis in the
aftermath you talk about 2008 yeah well it should never have happened it should never have
happened the uh there were these uh mortgage back Securities had been created they' always existed mortgage back Securities but
very fancy ones were getting created and uh they had all kinds of this and that and and so on and so forth
and in the old days the rating agencies their customers were the buyer of bonds the bond rating
agencies so they wanted to do right by their customers but at a certain point and then you'd get a report every week or a newsletter or something like that
but with the internet coming along people were sharing this who didn't subscribe so the rating agencies decided okay we're not going to charge the
buyers of the bonds we're going to charge the sellers of the bonds now if you think about it that's a conflict ICT of interest because they really want to get the bond have the bonds sold so
maybe they won't be so tough in in rating them and that's what happened the stuff was sold which you'd have to
be a uh and and stamped AAA and you know people were getting mortgages no docks you'd walk in you'd get a
mortgage uh how much money do you have oh I have $100,000 and how much money do you make oh I make $200,000 okay fine we'll give you this
much of a mortgage well they didn't even ask for Doc for do for documents in many cases or or your income tax forms or and
why were the banks being so lenient because they could sell them to people who would package up these these
mortgages and put them they would B ultimately end up as a morage back security stamped double a
AAA so everything had just become very LAX and uh and bare Sterns for example which was
a firm that we had always had great confidence in they were very conservative uh
outfit they almost went down the drain because of this uh fortunately they didn't we had money with them and as soon as it looked like they were going
to be in trouble uh we bailed out and got out 3 days before they folded then we were working with um Leman
Brothers we had a lot of money with Leman Brothers but this this is Medallion and so on we had a lot of money with lean brothers and some of our outside funds also
did but it was beginning to look not so good for them and uh I I called up the head of Leman
brothers and said you know dick we're going to have to take some of our money out I'm going to have to take half of it out uh I'm I'm uncomfortable with that
much being with you and he said okay fine so we did that and then things were looking worse
and worse and we had some insight into his into their balance sheet and we knew it was stuffed with these a lot of the assets with these mortgage back
Securities and I called him and I remember I was driving and I said dick we're going to have to take out the rest of the money and he said oh he said I thought
you called me to buy these new bonds that were issuing they're over subscribed but for you I'll you know I'll give give you a a piece and I said
um well I I I don't want to buy your bonds but I'll wait a few days and see how they sell before I take the rest of
the money out and uh a few days went by then the list of buyers of these bonds came out and it was the most
unsophisticated group of of you know an obscure teachers retirement fund no no reputable
big outfit was buying these bonds and said I call them said okay we're taking the rest of the money out and that was
three months I think before uh lemman lemman collapsed so but if the rating agencies had done their job this would not have
happened and but no one wanted wanted to blame the rating agencies because who's ever heard of rating a I mean the news papers want to blame the banks right
right they want to blame the big players uh but it was it was you know maybe not quite as simple as I'm saying
but it was a mortgage back collapse and these Bonds were rated improperly that that's what happened so um let me now since we're getting uh short on time I want to make sure
there's plenty of time for audience questions um so maybe we can open it up and um and while we're looking for our questions raise your hand and then U Kelly and Italy will pass a a mic to you
um while we're getting our first question um maybe that guy was the first one with the white shirt to hold up his hand [Laughter] so
yeah hi I'm miles I'm a junior at Harvard um I was wanting to ask so over the years obviously the the general markets have changed with the Advent of more computer technology has that
shifted your view on fundamental versus quantitative investing I mean earlier you seem to kind of point to the fact that at the end of the day fundamental investing is very Wishy waffy and based on intuition do you think that that is always true or do you think there are
people that truly have an advantage in in fundamental investing that people have uh in doing fun is it possible to do yes I mean obviously Renaissance is
is quantitative but are you always proquant over fundamental or do you think there's room for fundamental invest I think there look look at Warren Buffett he's had a great career and I
don't think he has a computer on the premises ex except maybe to count his
money uh but uh no uh very it's a perfectly legitimate way to invest then I guess what are the skill sets that differentiates a good fundamental
investor from a good quantitative investor say it again what what are the different skill sets that separate a good fundamental from a good quantitative investor oh I think it's a it's a world of difference
uh I think a good uh fundamental investor let's say in a company he wants to evaluate the management have a have a sense of the human beings that are
running this thing he wants to have a sense of uh where the market might be going uh and uh it
it's you know it's a set of skills and some people are are very good at it uh quantitative stuff is a is a different
set of skills and uh which suited me and uh so does that answer your question close
close enough yeah um Mr Simons um as quants with increasingly powerful tools seek out inefficiencies in the markets to exploit
and we keep exploiting them until there's nothing left to exploit that'll overcome transaction cost are we destined to slowly Drive ourselves out of business and if so how
long do we have who is we we quants oh we qu as we keep seeking the inefficiencies to exploit and thereby diminishing them well that's a good
question uh yes inefficiencies do eventually get traded out if they're discovered uh but the market is not
static it's Dynamic things change and therefore there's room I think for new inefficiencies to
materialize and uh so uh I I think it's never going to be you know uh all inefficiencies are out of it there's
nothing to discover on the other hand you know so far we we've managed to you know our our returns have been
more or less stable for a long time so but we we keep finding new things and throwing out things that that are no longer
working do new things emerge as quants are looking for new things so that quants are exploiting other quants I have no
idea okay well she's giving out the phone hi um what's your favorite
algorithm what's my favorite algorithm I'll tell you my favorite algorithm my favorite algorithm is something that I uh worked out when I
was at the institute for defense analysis and it has to do with uh it has to do with solving a certain classical problem in
the field and I solved it but it's class pafi it is I solved this problem and
they made a special purpose machine at NSA and I heard that 30 years later it was still they was still using this special purpose machine to implement
this this algorithm so that's that's my favorite algorithm and it's classified so U there's a guy right there
well hi you you'll get your turn hi uh right here um I was wondering what I was wondering um what you did
over time to kind of protect your intellectual Capital you had a lot of people working for you how did you keep everybody uh rowing in the same direction um and how did you protect
kind of this the special yeah it's a good question it's a good question well everyone uh signs a forever non-compete uh a uh no not a forever
non-computer for forever non-disclosure and uh after you've been there a couple years uh there's a non-compete agreement that you're
invited to sign and pretty much everyone does because there's a lot of money that's uh out of your bonus a certain amount is held
back uh for a while and then uh invested in Medallion actually and then you get it over time but uh so there's always you always have a lot of money on the
table which you've not yet gotten received which keeps people from running off we've only had one incident
a couple of Russian guys uh left and uh stole some of our secrets and uh well we had a lawsuit
against them and so on and so forth and um and well they're not in business anymore and the system that they had
made off with is now pretty Antiquated so we're not worried about that but uh it's a very good question but the main reason people don't want to leave it's
it's a very nice atmosphere it's it's fun to work there people get paid a lot of money uh there's no doubt about that
and uh it's fun so we we've had people retire and but they with the exception of those two Russians they've never gone into any investment
business they've just retired and I don't know done this and that one guy went up to the broad Institute and
became uh a terrific uh scientist genetic scientist working for broad so um I I think if if turnover is very
important important in any company and if a company has a a great deal of turnover there's something there's something wrong and uh and you noce
something right uh if turnover is very low of course one thing that could be right is you're paying too much but uh but uh but
it's good to have low turnover and and that's what Renaissance has hi at the beginning of your talk you mentioned that you wanted to understand
how the system that was presented to you you want to understand how it works and at another point you also mentioned that once you have the system it's all about like making it better and better so my
question is the balance between those two because as you try to make your system better and better there is the risk of H making it more complex to a point that you don't understand it
anymore how do you balance improving your model and keeping it simple enough to understand it actually
well uh that's a good question it's completely understandable because uh you can
uh understand it if if you wanted to spend a week uh doing nothing but understanding the system it's all written down and and so it it's
perfectly understandable there are a lot of you know predictive signals there's there's a lot of stuff going on it is
very complicated but it's not not understandable so we understand it hi mat I I work with Andre Stan can
you stand up I'm sorry yes so you mentioned continuous improvements of the systems um I wonder is medall enough to
day the core of it at least similar to what it was 10 or 20 years ago or has Medallion sort of reinvented itself over that time to be completely different things you know I didn't my ears aren't
so good could you understand what he asked yeah so is The Medallion of today uh pretty much the same as it was 10 or 20 years ago or has it reinvented itself
oh it's continuously Reinventing itself I think there are some parts of it that would probably have been there for 10 years or maybe even 20 years uh but
that's less and less as as new as new uh things come along so uh uh like like I said you you just have to
keep you just have to keep running people will discover some of the things that you've discovered then they'll get traded out uh so you have to keep coming up
with with with more and more things and uh we have a a great computer system and
and and you know and great scientists are out very good ones so that's the answer hi
Jim so you mentioned during the beginning phases of The Medallion there was a short period of time when you guys weren't doing so well I'd like to ask
did any point in time did you doubt yourself and if so how did you will s to continue and eventually succeed well in that period Well we we
shut it down uh I wasn't certain but I did feel uh that we could improve it to the point
where uh we were happy to continue trading so uh and i' I've
never doubted that things would keep working uh reasonably well um I think you know we've been lucky to
a certain ex you know luck has plays quite a role in life and uh a lot of people don't you know if a
guy's uh business fails he says oh it was bad luck if a guy's business succeeds he says oh I'm you know I'm a hard worker and naturally it succeeded
but uh there luck everyone so so far we've been pretty lucky but um I haven't been I haven't been very
worried you know there are times when when a month goes by we don't make money one month there it's very rare we don't make money in a month but once in a
while that happens and then I well it's what but it's it's all it's always come back okay
would there there's a woman right there I'm looking at you who didn't you didn't you raise your hand all right well we'll see if we can
get you uh what I find interesting is Dr low I know that you're big on behavioral finance and uh Dr Simmons it seems like when you talk about your past you talk
about your gut instincts and you kind of just pass it off as you know I I felt this way but I was wondering if you had more I don't know if your internal
Compass is a little bit better than most in guiding you through tough decisions like the last person asked again I couldn't understand too well I'm sorry the Acoustics in this room are not great
um I think that the uh she was asking about um the role of human behavior uh in quantitative investing that the fact fact is that you do have some kind of a gut instinct about when a system is
working or underperforming what role does that play this intuition and judgment uh in thinking about these strategies well I mean if you see
something that's that's steadily losing you don't that does not take intuition to determine that something is
wrong and you ought to stop doing that uh but uh well intuition you know
scientists uh some scientists have pretty good intuition scientific intuition um how how does that happen in
math you might say hey this this operation worked over there maybe it'll work over here uh I'll give it a
try uh so as people come into the firm they learn what has worked uh and sometimes say oh well if we perturb that a little bit it could
work even better or stuff like that some people you know have better scientific intuition but I think it's scientific intuition it's not Market intuition that
the the uh guys who who work there uh uh are are using so we're just about out of time uh so I want to have it one last question
and then we're going to wrap up with a couple comments uh would you say that fundamental approach in your investment modeling is primarily inductive
reasoning based or deductive by nature in other words data driven to come up with your models or more logic driven to come up with your models well we
certainly are logical uh it's hard to work without logic uh there's a lot of data um
sometimes one might come up with a number of things and just try them all out and see if one of them if
one of them works now the danger of that is uh if you're trying enough things something's going to work but you have to be sure that uh the statistics are
still in your favor you know uh if there was so much data that even though we tried a million things uh and one of them worked the
probability of that was very very slim and therefore you probably okay so uh you know we do try try a bunch of stuff
and uh I I don't know if that answers your question but okay so so Jim um in wrapping up I'm going to ask you two quick questions related one is that you
um moved from Stony Brook to doing trading because you were working on a problem that you were struggling with and to this day it's still unsolved you went back to working on it it's a tough
problem I imagine did you encounter any unsolved Finance problems that uh that you uh think about and struggle with unsolved Finance
problems well doesn't seem like there are't any given the track record of Medallion well I think there's a lot of people who will worry about how they're going to pay their rent uh which is
perhaps an unsolved problem as far as their concerned yeah um I don't know what an unsolved financial
problem really means but um okay have you had any financial problems a whole a whole bunch I would love to get access to the
Renaissance uh research staff to have them working with us on it but the the last question is for all of the uh future quants in the audience any advice
about uh how they ought to approach this field and and career I think any potential Quant should just not get into the business we don't need to have a a whole lot of people in this business but
okay well on behalf of uh MIT Finance what what advice could I give you it's just you know uh work hard hire
good people and uh it's not easy to to get into the business because you need big databases and a lot of computers and
stuff like that to uh to even start up but you know uh if if you have an idea and you can test it out and think it's
good uh you know more power to you that's all I can say well Jim on behalf of all of us here at MIT we want to thank you so much for sharing your
wisdom with us and I think that um your career in finance is just extraordinary and it's been uh an incredible inspiration to many many people and will continue to be inspiration but what I
want to tell everybody is what might be even more inspiring is what you're going to talk about next week because not only have you made tens of billions of dollars for investors and billions for
yourself but you've also given away a tremendous amount of money for philanthropic purposes and we're going to hear about that next Wednesday so I urge all of you to come back and here
the the the third and the 3m's uh of money uh um uh sorry mathematics money and making a difference so thank you very much great
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