Let's now take a look at the three major operating systems that are likely to be used within quant trading research. I would like to argue that for the majority of more complex Python-oriented scientific/quantitative research that learning Ubuntu/Linux and the CLI will pay immense dividends over your quant career. Given that your likely goal is to spend as much time as possible researching and developing quantitative trading strategies, rather than reading through stacks of programming books, is it worth your while to learn a brand new operating system and associated command line interface (CLI)?Ĭlearly this will depend upon your circumstances, preferred method of trading research, coding language of choice and complexity of your models. However, Ubuntu/Linux is likely to be unfamiliar to many of you since Windows is still the de facto choice of operating system both at home and in the modern office environment. It is the most straightforward way to avoid problems with the bleeding-edge libraries that are required to carry out this form of research. The short answer, as of the writing date of this article, is if you want to carry out any serious/mathematical quant trading research (machine learning/deep learning) you should make use of Ubuntu 16.04 LTS Linux, with a desktop version on a local research machine and the server version on a live trading VPS or equivalent. Labs supporting Ukrainian Scientists is an expansive list of labs and PIs offering support at this time.One question that I am asked frequently is which operating system to use for quantitative trading research and implementation.
Personally, I have found the messages of support from scientists everywhere to be truly heartfelt, and I would like to highlight some of the community initiatives I’ve seen here:
We also want to use our platform to highlight the response from the scientific community.
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