Just as you haven't experienced Fortran, there are several areas in science that have not experienced C++/Python, and rely on Fortran.
Care to elaborate on why this wouldn't be the case?
As far as I can see, half of my desk is ex CNRS/CERN/CEA/... , the other half is the top brightest PhDs and engineers. When I look at weather forecast models, or biological DNA white papers, I don't see much difference in terms of scientific process or category of problem than what we see in quantitative finance.
It may be sad, but the truth is finance phagocytates an immense chunk of the scientific community,abd it provides. There are interesting and hard problems to solve, virtually unlimited compute resources, etc.
Most top quant HF have yearly double digit million dollar infrastructure bills, compute and storage clusters rivaling or surpassing academic ones, dedicated hardware manufacturers, etc.
It's just not what people consider as "science" :-)
My point is that branch of HPC developed somewhat independently of most of other science disciplines. It's also relatively newer, so it doesn't rely heavily on legacy code from the 70's/80's. Generally, newer disciplines (computational biology, modern ML, etc) don't use Fortran. Older stuff (physics, electromagnetics, most engineering, etc) are full of Fortran, and continue to be.
Did you work in HFT? I would be very surprised if they used Python for that, and almost equally surprised if they all dismissed Fortran as an option.
Besides the things you named, quants also use Excell (of course) but probably less known is K, which is an APL type language
Even that is disappearing. It was common practice even 10 years ago to use MKL as backend.
> Did you work in HFT?
Yes, I've done (and still do) HFT and mid freq since around 15 years.
> I would be very surprised if they used Python for that
Surprise!
Nobody would dare do any heavy computation in e.g. C++ or Fortran or Cobol. It's just too unpractical, and slow to develop.
You calibrate your models in Python/pandas/... , offline on historical data, and just use the prebuilt model to make the real-time prediction in C++, which doesn't involve much more than simple linear algebra.
I would estimate conservatively that 80% of quants use Python, in both HFT and mid freq. There should be some niche where they use matlab, R, kdb or stata, but that's definitely a small fraction.
Sorry I just saw this. And what do you think MKL does?
Python is very widely used for prototyping and there's nothing anyone can do about it. In production the algos would be implemented in Cpp though. I'm merely stating a fact, not here to argue about anything. Raw K is almost never used but there's a lot of Q, depending on the shop.
I never saw any Fortran in my time at Bloomberg in the 2010s but allegedly there was still a lot of it running in the nether regions.