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I've used both R and Python with Pandas in a professional quantitative financial work to do both large and small scale projects. I would strongly recommend Python with Pandas over R for most new projects in the field especially in time series analysis. While I don't dispute vonjd in that you will find more libraries in R with algorithms on the bleeding ...


6

For data analysis, particularly for large data analysis project, pretty much most of the top quant hedge funds and a lot of the banks are using Python (over R) for a couple of reasons, although many still have bits and pieces of R for specific packages or functions (I work at a bank and interface with quite a few quant hedge funds on data analysis): ...


3

MF is linked with physics mostly because it solves the same PDEs (Black-Scholes equation is a certain type of Schrödinger equation for instance). As for the specific links you mentioned : Lie Algebra : Magnus expansion (to build fast approximation of time dependent ODEs like those arising in credit risk) Differential geometry : link with Varadhan ...


2

For the tasks listed, both Python and R preform very well. There are some packages in Python not in R and visa-versa, my solution for this is to simply call R from Python. This allows for the best of both worlds. It is also important to note I do not write any R code other than calling an R library from Python. Calling Python from R does not work equally ...



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