Jim Simmons is a mathematician and a hedge fund manager (founded Renaissance Technologies in 1982). He is considered by many to have the best investment track record in the whole industry.
In this interview Jim explained how he got started in trading in his late thirties when he got tired of mathematics (who can blame him?):
"When I started
doing trading, I had gotten a little
tired of mathematics. I was in my late
30s I had a little money I started
trading and it went very well
I made quite a lot of money how it with
pure luck I mean I think it was pure
luck. simply wasn't mathematical modeling."
And how starting that venture ended up in forming one of the world's biggest hedge funds:
"But in looking at the data after a while
I realized hey this looks like there's
some structure here and I hired a few
mathematicians and we started trying to
make some models just the kind of thing
we did back at eye-dea
you design an algorithm you test it out
on a computer does it work doesn't it
work
and so on.
"
Simmons also stated how commodities and currencies used to show trending characteristics back in the day but that is. not the case any longer:
"(in) the old days commodities or
currencies had a tendency to trend."
"The
trend-following would have been great in
the 60s and it was sort of okay in the
70s by the 80s it wasn't such."
Jim stressed the importance of staying ahead of the competition by looking for shorter term approaches to trading and hiring very smart individuals:
"We stayed ahead of the
pack by finding by finding other other
approaches and shorter term approaches
to some extent. But the the real thing
was to gather a tremendous amount of
data and and we had to get it by hand in
the early days. We went down to the
Federal Reserve and copied interest rate
histories and stuff like that because it
didn't exist on computers. We got a lot
of data, very smart people and that
was the that was the key."
"In a certain sense what we
did was machine learning you you you
look at a lot of data and you try to
simulate different predictive schemes
until you get better and better at it it
doesn't doesn't necessarily feed back on
itself the way we did things but it
worked."
