I've written a suite of perl programs whose logic could be streamlined and improved. The perl programs are my attempt at testing the Efficient Market Hypothesis. I can no longer wrap my mind around the logic of the system, even though I wrote it.
So while I am having fun learning python, I have in mind a complete rewrite of the perl programs.
R and numpy both look like they could be useful, though the math I'm using is not very high-powered.
Two pieces of perl that I'll need to replace with python modules are Math::Brent (
http://search.cpan.org/dist/Math-Brent/Brent.pm)
for nonlinear function minimization (for the calculation of rates of return, solving of high-order polynomial equations) and a statistical linear fit package
(
http://search.cpan.org/~randerson/St...ics/LineFit.pm)
A python package (or R?) than can do multivariable statistical regression would be of great interest to me too.
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