Jim Simons: The mathematician who cracked Wall Street
Jim Simons - Philanthropist, mathematician
After astonishing success as a mathematician, code breaker and billionaire hedge fund manager, Jim Simons is mastering yet another field: philanthropy. Full bio
of a mathematical phenom.
and MIT at a young age.
that's the National Security Agency --
where they hired mathematicians
and stuff like that.
at your own mathematics,
working on their stuff.
well, the Vietnam War was on,
was a big fan of the war
a magazine section cover story,
I thought it was stupid.
which they published,
who works for Maxwell Taylor,
agrees with his views.
from General Taylor's.
and some kid came around
from Newsweek magazine
and ask what I was doing about my views.
mostly mathematics now,
then I'll do mostly their stuff."
intelligent thing I'd done that day --
that I gave that interview.
"I've got to call Taylor."
because you went on to Stony Brook
mathematicians of the century.
I was a graduate student at Berkeley.
and he liked them.
which you can easily see up there.
a famous paper together.
explain it to somebody.
it had something to do with spheres,
but I'll say about that work --
but before we get to that --
that's now flourishing.
it happened to apply to physics,
at least I knew nothing about physics,
knew a heck of a lot.
after the paper came out,
started applying it to string theory
to what's called "condensed matter."
called Chern-Simons invariants
that it would be applied to physics.
you never know where it's going to go.
how evolution shapes human minds
with a mathematical theory,
that it's being applied
the actual physical world.
named [Eugene] Wigner,
effectiveness of mathematics.
which is rooted in the real world
measure, everyone would do that --
back to save the day.
and Einstein realized,
in which I can cast general relativity."
piece of ingenuity.
and it has a lattice around it --
originally observed by [Leonhard] Euler,
a very important field in mathematics:
12 edges, six faces.
vertices minus edges plus faces --
these are triangles covering --
plus faces still equals two.
any which way --
of polygons and triangles
plus faces -- you'll get two.
of a doughnut: 16 vertices
32 edges, 16 faces.
with squares or triangles
you're going to get zero.
the Euler characteristic.
a topological invariant.
you're always get the same answer.
from the mid-1700s,
took an idea like this and moved it
and found new invariances?
actually, there were Chern classes.
of these types of invariants.
and we uncovered some new things.
while he was writing --
perhaps be these invariants.
a flavor of that amazing mind in there.
and having been a code-cracker at the NSA,
in the financial industry.
efficient market theory.
astonishing returns over two decades.
wasn't just the size of the returns,
with surprisingly low volatility and risk,
a wonderful group of people.
gotten a little tired of mathematics.
I had a little money.
with pure luck.
after a while I realized:
and we started making some models --
at IDA [Institute for Defense Analyses].
you test it out on a computer.
of some commodity.
"That's just a random, up-and-down walk --
over that whole period of time."
looking at that,
kind of a graph from the old days,
had a tendency to trend.
you see here, but trending in periods.
I'm going to predict today,
and I'd make some money.
such a system would work --
money, you'd make money.
during that period.
a bunch of lengths of trends in time
was predictive of what happened next.
and see what worked best.
have been great in the '60s,
by finding other approaches --
a tremendous amount of data --
in the early days.
and copied interest rate histories
because it didn't exist on computers.
people to do fundamental trading.
some didn't make money.
in that department.
got better and better,
something remarkable at Renaissance,
this group of people,
who could be lured away by money.
exciting mathematics and science.
because of the money.
came because of the money.
because it would be fun.
play in all this?
what we did was machine learning.
to simulate different predictive schemes,
the way we did things.
can be really quite wild and unexpected.
length of dresses, political opinion.
except hem lengths.
volumes, you name it.
and get it ready for analysis.
hypothesis is not correct.
might be just a random thing.
at multiple strange anomalies,
might be a random thing;
you can tell that it's not.
for a sufficiently long time --
random is not high.
anomalies can get washed out.
of the business.
at the hedge fund industry now
about that industry,
industry in general?
helping increase inequality?
in the hedge fund industry?
three or four years,
has not done so wonderfully.
going up as everybody knows,
that's been created in the last --
has not been created by hedge funds.
"What's a hedge fund?"
and 20 percent of profits.
different kinds of creatures.
slightly higher fees than that.
in the world at one time.
44 percent of upside.
spectacular amounts of money.
"How can you charge such high fees?"
was what people were --
as I think I told you,
because there's a capacity to the fund.
about the hedge fund industry
great mathematical and other talent
to the many other problems in the world?
and things like that.
about it too much.
into the investing world
It's increased liquidity.
people are trading that kind of stuff.
going off and starting a hedge fund.
where you're actually investing, though,
mathematics across America.
philanthropic issues together.
my beautiful wife --
about 20 years ago.
just as a convenient way to give charity.
but gradually a vision emerged --
to focus on basic research.
and went to work at the foundation.
is basically investing
giving them support and coaching.
to make that more effective
to which teachers can aspire.
the bad teachers,
all through the educational community,
and giving them status.
15,000 dollars a year.
in New York City in public schools today,
and that'll be 10 percent
in New York [City] public schools.
that you've supported philanthropically:
what you're looking at.
from geology to biology --
what did we start with?
did we have to work with on this route?
very interesting questions.
from geology up to RNA
how did that all work?
what do we have to work with?
is a star in formation.
which has 100 billion stars,
years to settle out.
in formation at any time.
along this settling-down period.
sort of circling around it,
or whatever it forms.
significant organic molecules.
but formaldehyde and cyanide --
the seeds, if you will -- of life.
that planets around the universe
basic building blocks.
there's going to be life all around?
of how tortuous this path is
those seeds, all the way to life.
will fall on fallow planets.
of where we came from,
that is something you would love to see.
and so improbable,
we could be a singularity.
that's floating around,
I got the chance to speak with Elon Musk,
physics seriously was it.
is taking math seriously,
and now it's allowing you to invest
of kids across America and elsewhere.
Math certainly works.
has been very enjoyable.
it's an inspirational thought to me,
so much more can come from it.
and for coming here to TED.
About the speaker:Jim Simons - Philanthropist, mathematician
After astonishing success as a mathematician, code breaker and billionaire hedge fund manager, Jim Simons is mastering yet another field: philanthropy.
Why you should listen
As a mathematician who cracked codes for the National Security Agency on the side, Jim Simons had already revolutionized geometry -- and incidentally laid the foundation for string theory -- when he began to get restless. Along with a few hand-picked colleagues he started the investment firm that went on to become Renaissance, a hedge fund working with hitherto untapped algorithms, and became a billionaire in the process.
Now retired as Renaissance’s CEO, Simons devotes his time to mathematics and philanthropy. The Simons Foundation has committed more than a billion dollars to math and science education and to autism research.
Jim Simons | Speaker | TED.com