Why hedge funds now love Python as a programming language

Nat Kilsby was right. The former head of operations engineering at Goldman Sachs turned COO of Quadrature Capital told us in March that hedge funds are everywhere in Python coders, and that Python has become the language to learn for hedge fund jobs because it is a bridge between research and technology.
Eight months later, technologists say hedge fund demand for Python expertise is higher than ever.
“As the use of machine learning techniques and statistical analysis becomes more and more influential in the process of investing funds, Python and associated libraries (Pandas, etc.) are replacing R, Java and C ++” says Dean Looney, a quantitative headhunter at London-based research firm Referment. . Python simply offers the quantitative technologist, “much more flexibility and functionality, ”adds Looney.
Hedge funds don’t use Python for everything, but they do use Python a lot. Balyasny Asset Management, for example, is looking for data analysts who are proficient in Python to work on fundamental research, data collection and processing, as well as back-testing for the generation of data-driven ideas. However, he is also looking for people who can code in C # to work on front office trading systems that work with latency less than a second.
Python is too slow to replace C ++, C # or Fortran on high frequency systems, but for a lot of hedge funds and for a lot of functions where hedge funds require it, that is not the point. – “Python isn’t the fastest language in the world, but it’s fast enough for what hedge funds need most of the time,” says Sean Hunter, former vice president of technology and technical consultant at Goldman Sachs. “A lot of hedge funds will have a Python notebook that they run once a day that retrieves all of their positions and does all of the risk calculations.”
Python also has the advantage of being easy to learn and use compared to C ++ and Fortran, and it can be easily integrated with platforms like AWS as hedge funds move to the cloud.
The result is what recruiters describe as a substantial increase in the demand for hedge funds for Python developers compared to anyone else.
This is reflected in the job postings on eFinancialCareers. As the graph below shows, Python is cited in 39% of hedge fund technology job postings, compared to only 25% for C ++.
Hedge funds like Man Group have long been representatives of Python, but until a few years ago many were still using R or Matlab. The popularity of Python packages like Pandas and Numpy which enhance Python functionality has encouraged change. The same goes for things like Cython, which can make Python up to 30 times faster.
“Five years ago it was C ++ and Java, but Python is now the king of hedge funds,” says another tech headhunter in space. “As a language, it has come an incredibly long way in recent years. – Python is an object-oriented language in its own right, but it is very easy to learn and use. High frequency funds will always use C ++, but if you’re a mid-frequency fund, then Python is more than good enough.
Looney says the ideal hedge fund hire is now a quantitative Python developer who quickly translates the ideas of quantitative traders into actionable code. Good applicants can earn between £ 120,000 and £ 150,000 ($ 161,000 to $ 202,000) in base salary in London, plus bonuses of 150% on top.
Photo by Nick Fewings on Unsplash
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