Programming Skills for Entry-Level Quantitative Finance
Summary
The document collects contrasting views on which programming skills may help someone entering quantitative finance. One response recommends depth in a low-level language such as C++, alongside practical familiarity with higher-level tools such as Python or R and with SQL and databases. Another describes using MATLAB and Stata for analysis, EViews for packaged econometrics, C++ for custom computation, and Excel with VBA for daily work.
These are personal opinions and examples rather than a formal hiring guide or tested comparison. The answers disagree about the lasting value of tools such as Excel, SAS, and Stata, and the discussion does not distinguish roles in research, trading, risk, or infrastructure in detail. Its useful takeaway is that programming needs depend on the finance specialty, while the examples span general scripting, statistical analysis, data management, and performance-sensitive or unusual numerical work.
Key ideas
- Programming requirements vary across quantitative finance roles.
- C++ is presented as useful for low-level or custom computational work.
- Python, R, SQL, and database skills are suggested as complementary capabilities.
- MATLAB and Stata are cited for numerical and econometric analysis.
- The recommendations are individual opinions, not a consensus or a detailed career roadmap.
Tags
Full text
# What programming skills are needed in quantitative finance? # What programming skills are needed in quantitative finance? I’m considering a career in finance when I complete my PhD in Mathematics in 2016. My only major programming experience was a C++ course during my MPhys in the 2007-8 academic year, although since then I’ve used LaTeX a lot, which has some similarities to proper programming. What should I be able to do as a programmer if I seek an entry-level job such as a quant? I’ve tried googling this, but what I find discussed instead is which languages are worth learning. I appreciate there may be too many exercises worth doing to list here, but I’d welcome any reference material that goes into this in appropriate detail. ## Answer by user9403 (score 2) https://quant.stackexchange.com/a/21431 It depends on what part of finance you want to go into. Basic scripting in SAS is often enough for some commercial banks. In my opinion (and others will disagree I'm sure) to be a "world class" quant you need to have in-depth knowledge of a low level programming language (eg C++), working knowledge in a few high level languages (R and Python, for example), and strong working knowledge of SQL and databases. Stay away from Excel, SAS, and STATA if you want long term (15+ years) of employability: those "languages" are obsolete and are being phased out. ## Answer by iNarek94 (score 1) https://quant.stackexchange.com/a/21430 Well, i mostly use $MatLab$, it has pre-constructed tools, user-friendly interface. Also $Stata$ for econometric analysis For econometrics you can also use $Eviews$, it can't be considered as programming though, everything is packed for easy use. In contrast, $Stata$ is better for some complex models. I have learnt $C++$, in fact, if you dig under most (if not all) applications, you'll find that $C$ is their "dad". $C++$ is great for "freestyle" and crazy ideas. For example, Matlab (and most computational prorgams) have limited bytes for their data. Due to some circumstances i had to solve a set of equations, which involved numbers going beyond 308 (MatLab's limit) digits. C++ turned out to be handy there (made a new class of floating numbers). Just saying. For daily basis $Excel$ should be good. Knowing how to use $VBA$ with it would give you a huge performance boost too. Good luck!
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