Benefits of learning R language


I have my heart set on a career in portfolio management.
Is it worth it investing the time in learning the R language?

Working in finance you deal with data and analysis all the time so my assumption is that it wouldn't hurt.


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Comments (27)

Apr 8, 2018 - 5:11pm

Hi Betseat-Getachew, the silence is deafening, sorry about that.... Any of the threads below helpful?

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Apr 17, 2018 - 12:39am

R is still on the come-up as far as being adopted in the finance world. It's still worth knowing though. The issue is that if you don't make some serious effort to apply your knowledge of R after you've learned it, it's very easy to forget. In other words, if your current job doesn't use R, it may be hard to maintain the skill. You should also consider either Python or SQL as those are also really popular languages.

Apr 17, 2018 - 12:50am

Above poster has the gist, but I'd point out that SQL is way different than R and Python. R and Python are a lot more multi-purpose. SQL does like, one thing and one thing well - handling DBs.

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Apr 17, 2018 - 1:27am

To break it down: SQL is great for extracting data from databases; Python/R is great for everything apart from that, including data manipulation and extraction from external sources. If this is your first programing language I would strongly recommend Python as it's easier to understand, more versatile and the online resources/community is superior to R

Apr 17, 2018 - 9:43am


I have my heart set on a career in portfolio management.
Is it worth it investing the time in learning the R language?

Working in finance you deal with data and analysis all the time so my assumption is that it wouldn't hurt.


I think it is worth it. Investing your time in R language will prove to be beneficial when there is any coding related task to be completed.

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Apr 17, 2018 - 7:50pm

Couple of thoughts here:

1) R is cool for stats research and visualization. TBH, the latter is where you'll be spending your time outshining excel. (Besides regressions, how much heavy stats do you think you'll do?)

2) The above is different if you are a quant. Numerical accuracy matters a lot and R is a analysis language. I bet quants are going to use C++ for the heavy lifting by writing high grade code to solve problems

3) The division of labor is real. JPM's quants and engineers developer and maintain the tools so you can focus on comparative advantage. IB analysts have build in custom functions build by PHD's in excel they can press a button for instead of writing code and waiting for it to run. I've had bosses burn me for focusing too much on the code when it's not my main job.

4) Depending on asset class, backtesting and coming up with ways to manipulate data is probably where you'll write R.

5) Depends on manager's preference and how much freedom you have to go outside excel.

Best Response
Apr 17, 2018 - 9:08pm

Python is probably better since with pandas you can do everything you can do with r plus it's closer to a normal programming language which will be useful if you end up in a job where you can add value by just automating simple tasks (which is a lot of them). The reason to use r is that a lot of academic research comes out in r first (so you can just download their packages instead of replicating it yourself) but at your level that probably won't be an issue. Also with python after you learn the basic syntax you can just start playing around with quantopian and focus more on learning the stuff you actually care about. SQL is good to know but also really easy to pick up so unless you can credibly claim to have experience writing optimized queries for big datasets it probably has little to no signalling value on top of either r or python (though if your resume feels sparse it still might be worth spending an hour or 2 going through an sql tutorial so you can claim you know it).

Apr 17, 2018 - 9:25pm

I doubt anyone above truly used R or Python on their job. For portfolio management purposes, R is way more efficient than Python because of its unique advantages in data cleaning and data manipulation. You can consider Python as the "dummy version" of C++, which would be a little too fancy for a job in portfolio management unless you are a quant.

I work in asset management, focusing on alternative credit investments. I almost exclusively use R on my job. I'm adept with R, Python and VBA, and I found out that R is best for my job. Python would be a powerful tool, yes, but I just don't think that's something necessary for asset management.

Apr 17, 2018 - 9:40pm

I worked at a large bulge bracket on their internal investments desk. We were translating all of our code from R to Python (in fact, my internship project was re-doing a bunch of their VaR Models) due to performance issues. Pandas was far quicker for implementing our LPs. To this day my old desk uses a combination of Python and C++, and all the R code has been deprecated.

Considering BAML and JPM both use Python forks for most of their development, I'm going to have to disagree with you.

Apr 17, 2018 - 10:33pm

I think we are talking about two different jobs. For quant/developers, Python is efficient, I have no about about that. But I don't think for investment analyst/portfolio managers, whose most quantitative work would be data manipulations and regressions for some occasions, R would a more user friendly tool box.

Apr 17, 2018 - 9:38pm

SQL will take you 2-3 weeks
Python will take you 3-6 months
R will take you 6+ months

Learn SQL + Python

just google're welcome
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Apr 18, 2018 - 8:42am

I have moved all of my infrastructure AND models from R to Python a few years ago. There are still things that R does better, but Python in Jupiter is such a great tool that it makes up for these deficiencies.

I have to say that the choice of the programming language will depend on PM preference, asset class and existing infrastructure. You should assume that you will end up learning and forgetting multiple languages through your career and there is nothing bad about that.

PS. I just wish there was a "table editor" that could be plugged into python

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