The best coding languages ​​for trading algorithms: Python, C++, Javascript?

If you want to get a systematic trading job, two coding languages ​​have long been key: Python and C++, but a new unscientific study of the languages ​​used to write open-source trading algorithms suggests there’s another possibility. : JavaScript.

Richard Hickling, a former software engineer at Bank of America, BNP Paribas, Barclays and elsewhere who now runs crypto analytics firm ProfitView, reviewed the most popular algorithmic trading projects. on Github. JavaScript is the second most popular language in Hickling’s sample.

Hickling claims no scientific rigor, but he had a method for selecting Github repositories from his sample of 35 repositories: he first looked at repositories popular with algo traders and quants; then he used stars to determine which other rests were popular; then he ranked them by popularity.

JavaScript can be really fast when run server-side as node.js, Hickling says. It’s not as fast as C++ but it’s still passably fast for mid-frequency trading algorithm applications. “He rose through the ranks quickly in recent years,” he recalls.

However, Python still dominates and C++ is still considered the gold standard when it comes to trading programs. “With Python, if you have an idea, you can just sit down and test it in a matter of minutes,” says Hickling. “But for very large projects, Python doesn’t have much of an advantage because on a large scale, you have to put a lot of controls on your architecture that get cumbersome with Python.”

The problem with C++ is always that it’s very hard to write, says Hickling. “It takes a lot more effort than Python. The value of C++ is that it is both expressive and high performance_. There are few languages ​​that rival it in this way.” For this reason, Hickling says you don’t approach a C++ project without a lot of thought and sufficient resources.

Could JavaScript provide an alternative? Vaccum Labs, a software company providing services to fintech industry says Node.js is faster than many people think and is “definitely much faster” than Python, making it ideal for exchanging prototypes in areas such as crypto market building.

A senior banking technologist says it won’t spill over into traditional finance. “I’ve heard of people using Node.js for the whole back-end trading platform as smaller places, but it’s just not good enough for front-office applications” , he said. “I would be amazed if anyone uses it for latency-sensitive algorithms.”

Click here to create an eFinancialCareers profile. Make yourself visible to recruiters who are hiring for the best jobs in technology and finance.

Have a confidential story, tip or comment you’d like to share? Contact: [email protected] first. WhatsApp/Signal/Telegram also available (Telegram: @SarahButcher)

Be patient if you leave a comment at the bottom of this article: all our comments are moderated by human beings. Sometimes these humans may be asleep or away from their desks, so your comment may take a while to appear. Eventually, it will – unless it’s offensive or defamatory (in which case it won’t.)

picture by Braden Collum on Unsplash

Sharon D. Cole