Value of learning Python and C++ for MM fundamental investing?

Hi, I have an internship lined up next summer at a large multi-manager hedge fund. I will be with the fundamental equities team. I have the option to take classes at my college this summer with full financial aid. I'm thinking of learning Python and C++ if these languages will help me as a fundamental investor (I know the trend is towards quantamental these days). Would this be a good idea? How helpful is coding on the job?

15 Comments
 

Plenty of value for python (not really C++)

Reason is whether fundamental or not it allows you 1) to view data differently 2) get access to alternative data and be able to crunch it and so 3) be a little different from all the monkeys from IB that just know how to plug numbers in excel and modify logos

Especially at a MM this will be super valuable

Moreover, there’s are plenty of utilities not related to investing such as simplifying tasks.

 

Python > C++ for the purpose of fundamental/quantamental analysis. They key advantages of C++, performance/speed and compiled/runtime error detection, are not big issues for analysis in this space. Python has an easier learning curve, higher popularity (meaning that someone has probably solve the issue you are stuck on at stackoverflow) and lower maintenance.

I would say the more funds have Python in their tech stack vs C++. Even in the quant space I think most modelling is done in Python while trading/execution might use lower latency codebases.

 

Most production-quality Python is accelerated by C/C++ under the hood anyway. One of the things that makes Python great is the prevalence of heavily optimized libraries (e.g. numpy) that let you write code at a high level and run it at speeds approaching native C/C++. Of course pure C/C++ will give you the edge when latency is a big issue, but it shouldn't matter for even highly compute-intensive fundamental analysis.

 

Although this is 1000% true, I think learning to code yourself is an immensely useful skill. Learning spark and other distributed computing methods has a steep skill curve, but I truly believe that the world is moving towards fundamental analysts with both skill sets.

Maybe I’m a little biased since I’m a fundamental equity analyst at large MM shop with a statistical machine learning background.

 

I work on a MM team that consumes a TON of data. There are a number of providers we use that have APIs that allow you to much more easily carve and utilize the datasets vs the web apps. We don’t employ a data scientist at this point because the manipulations we’re doing are relatively rudimentary and it’s another mouth to feed.

That said, we very much value the skillset and view it as a differentiating factor for analyst candidates. I don’t think you’d be wasting your time by learning basic Python/SQL skills

 

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