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There's not anything there that is specific to quant work, it's just a reading list for C++. As an ex-quant, I very much agree with the comment made by Karan (
by Nick_C 16y ago
There's not anything there that is specific to quant work, it's just a reading list for C++.
As an ex-quant, I very much agree with the comment made by Karan (on the site). Our modelling was developed on statistical software such as SAS and SPS. The actual production code was simply Powerbuilder or C++.
- shogunmike 16y agoIt is a similar situation to legacy Fortran code in the academic physics community. Fortran is used because some guy wrote the core algorithm 30 years ago in Fortran 77 and never wrote any docs about it. "If it ain't broke don't fix it." I don't agree with this mentality at all. In fact, I make use of Python almost exclusively for the work I do (in a small fund). My NumPy/SciPy is not good enough though to choose it over C++ when I need to perform some hefty number crunching. How did you find using SAS/SPS? Is R not a good candidate for what you're doing?
- Nick_C 16y agoIt was over ten years ago and I just don't remember. The development modelling was done by a couple of other guys. I recall seeing R around, but I don't remember it being used for my markets, which were bonds and currencies. The data sets were very large and took hours to process (pre-Pentium 4); would that have anything to do with it?
- shogunmike 16y agoR has certainly gained some traction in recent years, as people have added more packages. It is interpreted so I'm not sure how this will affect speed. I haven't had a chance to use it personally so wouldn't be able to comment. I know a guy who has a dual processor Xeon machine, each with 4 cores, running MatLab. Once the code was parallelised it zipped along.