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• Some programmers might say using 1 indexing is why R and Matlab do not work (it's the same argument for Julia).

• Neither LSEG (Refinitiv) nor Bloomberg offer direct usage of R or Matlab in their APIs. Provided almost all institutions use either LSEG, Bloomberg, or both, you have a massive problem trying to promote R or Matlab at work.

• R is licensed with GPL, as are most packages. As docs.python states,

• Some programmers might say using 1 indexing is why R and Matlab do not work (it's the same argument for Julia).

• Neither LSEG (Refinitiv) nor Bloomberg offer direct usage of R or Matlab in their APIs. Provided almost all institutions use either LSEG, Bloomberg, or both, you have a massive problem trying to promote R or Matlab at work.

• Efinancialcareers provides an interesting views from well known people in the industry. For example, Graham Giller, former head of data science research at JPMorgan and Deutsche Bank, thinks that

banks have settled on Python over R because banks' IT departments are predominantly run by computer scientists rather than people who care a lot about data.

• R is licensed with GPL, as are most packages. As docs.python states,

• the API is written in C++

• The derivatives pricing engine DLIB is written in DLIB, which is OCMAL based.

• The GUI is written in Javascript

• Some stuff is apparently written in Perl

• Python seems to have increased in the last decade, but I do think the statement above says it all. Also, even the Python API only works when bundled with the required C++ API.

• strong believer in OCAML

• the API is written in C++

• The derivatives pricing engine DLIB is written in DLIB, which is OCaml based.

• The GUI is written in JavaScript

• Some stuff is apparently written in Perl

• Python seems to have increased in the last decade, but I do think the statement above says it all. Also, even the Python API only works when bundled with the required C++ API.

• strong believer in OCaml

Low-Level Performance is crucial in real world infrastructure. That's why C/C++ reigns supreme for core functionalities in firms due to its raw speed. Julia may be quick, but its still yound and a niche language. Its a lot faster to deploy and easier to write, but if you need a larger pool of experienced programmers, C++ is has a lot more choices.

• is written in Java, and any custom function you write needs to be in Java.

That said, what your boss tells you to use is similar to actual languages (e.g. all questions must be written in English on Stack Overflow, or social media and the like. A languages success is driven by direct positive externalities, meaning a languages value improves as more users engage and participate with one another. That's why everyone uses WhatsApp. The community behind Python is honestly second to none. I frequently find myself just blindly typing a question into Google before thinking (e.g. how to define the font in Matplotlib) because SO almost always has the solution readily available anyways. If you look at places like Quora, Reddit and the like you will always find people promoting Python.

I only used Matlab / Octave before I started my career in finance (which is a long time ago). My sister uses it in the automative industry, because the simulink offerings are apparently great. I never actually came across someone using Matlab in finance.

• Some programmers might say using 1 indexing is why R and Matlab do not work (it's the same argument for Julia).

• Neither LSEG (Refinitiv) nor Bloomberg offer direct usage of R or Matlab in their APIs. Provided almost all institutions use either LSEG, Bloomberg or both, you have a massive problem trying to promote R or Matlab at work.

• R is licensed with GPL, as are most packages. As docs.python states,

Low-Level Performance is crucial in real world infrastructure. That's why C/C++ reigns supreme for core functionalities in firms due to its raw speed. Julia may be quick, but its still young and a niche language. It's a lot faster to deploy and easier to write, but if you need a larger pool of experienced programmers, C++ offers a lot more choices.

• is written in Java, and any custom function you write needs to be in Java.

Quantlib:

• written in C++

That said, what your boss tells you to use is similar to actual languages (e.g. all questions must be written in English on Stack Overflow), or social media and the like. A languages success is driven by direct positive externalities, meaning a languages value improves as more users engage and participate with one another. That's why everyone uses WhatsApp. 

The community behind Python is honestly second to none. I frequently find myself just blindly typing a question into Google before thinking (e.g. how to define the font in Matplotlib) because SO almost always has the solution readily available anyways. If you look at places like Quora, Reddit and the like you will always find people promoting Python.

I only used Matlab / Octave before I started my career in finance (which is a long time ago). My sister uses it in the automative industry, because the simulink offerings are apparently great in this context. It's mostly network effects again though, with people using it because others use it. I personally never came across someone using Matlab in finance.

• Some programmers might say using 1 indexing is why R and Matlab do not work (it's the same argument for Julia).

• Neither LSEG (Refinitiv) nor Bloomberg offer direct usage of R or Matlab in their APIs. Provided almost all institutions use either LSEG, Bloomberg, or both, you have a massive problem trying to promote R or Matlab at work.

• R is licensed with GPL, as are most packages. As docs.python states,