Nat Kilsby was right. The former head of operations engineering for Goldman Sachs turned COO of Quadrature Capital told us in March that hedge funds were all over Python coders, and that Python hasbecome the language to learn forhedge fund jobs because it's a bridge between research and technology.
Eight months later, technologists say hedge funds' demand for Python expertise is higher than ever.
"As the use of machine learning techniques and statistical analysis becomes more influential in the investment process for funds, Python and associated libraries (Pandas etc) are replacing R, Java and C++," says Dean Looney, a quant headhunter at London search firm Referment. Python simplyoffers quantitative technologist, "a lot more flexibility and functionality," Looneyadds.
Hedge funds don't use Python for everything, but they use Python for a lot. Balyasny Asset Management, for example, is looking for data analysts conversant in Python to work on fundamental research, data gathering and processing,along withback-testing data-driven idea generation. However, it's looking also looking for people who can code inC# to work on front office trading systems operating withsub-second latency.
Python is too slow to replace C++,C# or Fortran on high-frequency systems, but for a lot of hedge funds and fora lot of the functions hedge funds require it for, this isn't the point.- "Python isn't the fastest language on the world – but it’s fast enough for what hedge fundsneed it to do a lot of the time," says Sean Hunter, a former Goldman Sachs technology VP and tech consultant. "Alot of hedge funds will have a Python notebook that theyrun once a day and that pulls in all their positionsand performs all 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 ashedge funds move to the cloud.
The upshot is what recruiters describe as a substantialincrease in hedge funds' demand for Python developers compared to anyoneelse.
This is reflected in the job advertisem*nts on eFinancialCareers. As the chart below shows, Python is cited in 39% of hedge fund technology job ads, compared to just 25% for C++.
Hedge funds like Man Group have long been exponents 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 improve Python functionality have encouraged the shift. So, too, have things like Cython, which can make Python up to 30X faster.
“Five years ago, it was C++ and Java, but Python is now king at hedge funds," says another technology headhunter in the space."As a language, it’s come an incredibly long way in recent years. – Python is a fully fledged object-oriented language, but is very easy to learn and to use. High-frequency funds will still use C++, but if you’re a mid-frequency fund, then Python is more than adequate.”
Looney says the ideal hedge fund hire now is a Python quant developerwho rapidly translate quant traders' ideas into actionable code. Good candidates can make£120k-£150k ($161k-$202k) in base salary in London, plus bonuses of 150% on top.
Photo by Nick Fewings on Unsplash
Have a confidential story, tip, or comment you’d like to share? Contact:sbutcher@efinancialcareers.comin the first instance. Whatsapp/Signal/Telegram also available. Bear with us if you leave a comment at the bottom of this article: all our comments are moderated by human beings. Sometimes these humans might be asleep, or away from their desks, so it may take a while for your comment to appear. Eventually it will – unless it’s offensive or libelous (in which case it won’t.)
FAQs
– Python is a fully fledged object-oriented language, but is very easy to learn and to use. High-frequency funds will still use C++, but if you're a mid-frequency fund, then Python is more than adequate.”
How do hedge funds use Python? ›
Python for Hedge Funds: Roles and Applications
They rely on coding skills to sort through vast amounts of data and design prototype strategies aimed at testing ideas. Python, with its rich data analysis libraries like pandas and SciPy, is preferred for developing these strategies.
Why has Python become more popular as a programming language? ›
Python is a popular language for web and software development because you can create complex, multi-protocol applications while maintaining concise, readable syntax. In fact, some of the most popular applications were built with Python.
What is the best programming language for hedge funds? ›
Python, MATLAB and R
All three are mainly used for prototyping quant models, especially in hedge funds and quant trading groups within banks. Quant traders/researchers write their prototype code in these languages. These prototypes are then coded up in a (perceived) faster language such as C++, by a quant developer.
Why is Python so popular in finance? ›
Python is the most popular programming language in finance. Because it is an object-oriented and open-source language, it is used by many large corporations, including Google, for a variety of projects. Python can be used to import financial data such as stock quotes using the Pandas framework.
Is Python useful for private equity? ›
Private Equity is in the developing stage of adopting Data Science. It is becoming more common for investment analyst roles to have a preference for candidates with programming skills, such as Python.
Why choose Python over other programming languages? ›
Python's syntax is clean, readable, and emphasizes code readability, making it an ideal language for both beginners and experienced developers. Its straightforward and easy-to-understand code structure allows for faster development and maintenance of applications.
Why is Python so powerful? ›
That's because the language emphasizes readability and makes coding very easy. Python is also the fastest-growing programming language in the world. Its high-level, interpreted, and object-oriented architecture makes it ideal for all types of software solutions.
Is Python in demand in 2024? ›
Python SQL developers are in high demand in 2024, with attractive salary ranges based on experience and qualifications.
How much does a hedge fund programmer earn? ›
Hedge Fund Software Developer Salary. $90,000 is the 25th percentile. Salaries below this are outliers. $130,000 is the 75th percentile.
Top leaders in the category for Hedge Fund software are DocSend, Backstop, StyleADVISOR. Here, you can view a full list of Hedge Fund tools in the market. How many companies use Hedge Fund software these days? Around the world in 2024, over 4,173 companies are currently using one or more Hedge Fund software.
What data do hedge funds use? ›
Hedge funds use two types of data to generate outsized returns: traditional data and alternative data. Traditional data comprises standard sources like SEC filings and government economic data, known for their accuracy and reliability.
Why Python is booming now? ›
Why is it so popular among programming languages? Python is the most accessible open-source coding language as it has a simple syntax to code. Because of its simplicity of learning and utilization, python codes can be handily composed and executed much more quickly than other programming dialects.
Why are Python programmers in high demand? ›
The increasing complexity of web applications and websites, combined with the growing reliance on machine learning and AI, are two factors contributing to the steady demand for Python developers.
Is Python the future of finance? ›
In the financial industry, the sophistication of economic models determines the accuracy of forecasts and the quality of investment strategies. Python has emerged as a pivotal force in enhancing these financial models, offering precision and adaptability in complex economic analyses.
How is Python used in investment banking? ›
Many financial firms use Python to automate the process of generating financial reports, such as balance sheets and income statements. Python's libraries for data manipulation and visualization can be used to extract data from financial systems and generate reports in a variety of formats, such as PDF or Excel.
How do hedge funds use NLP? ›
Natural Language Processing (NLP)
NLP models analyze news articles, earnings reports, and social media sentiment, providing a gauge of market sentiment and shifts. This information is invaluable in empowering hedge funds to make informed trading decisions while responding swiftly to market dynamics.
How do hedge funds use algorithms? ›
This can help hedge funds assess the risks and potential returns of different investment strategies and make more informed decisions. Algorithmic Trading: Hedge funds often use algorithms to automate the trading process and execute trades more quickly and efficiently.
How do hedge funds use data? ›
Hedge funds use two types of data to generate outsized returns: traditional data and alternative data. Traditional data comprises standard sources like SEC filings and government economic data, known for their accuracy and reliability.
