Programming Languages that are in demand in the Financial Sector
Published on 15 July 15
James1
To start my blog post, I would like to state that Programming knowledge and skills do have a say in the bustling world of finance. And with the way the finance industry shifts to becoming more automated and technologically inclined these days, programmers and developers in the finance sector are certainly of high demand.
For example, top financial institutions like Morgan Stanley and Credit Suisse have adopted Scala programming language for many of its features including currying, type inference, immutability, lazy evaluation, and pattern matching. Also, top global banks such as Deutsche Bank have adopted F#, a multi-paradigm programming language that encompasses functional, imperative, and object-oriented programming techniques. Banks certainly love to use F# as it is used as a cross-platform CLI language, but can also be used to generate JavaScript and GPU code
With the given examples, I would like to provide you a list of commonly used programming languages that are vital in the finance sector.
Java
Java is undeniably one of the more important languages to know because the vast majority of investment banking technology projects from low latency trading systems to market data pricing systems and order booking management platforms requires Java.
Here are some career opportunities for you in Java: Java Jobs
C#
Investment firms like SocGen and Morgan Stanley are certainly hiring C# WPF developers to grant them investment banking tech jobs and needing to work on cross-asset class trading platforms.
It seems the banks are also looking for C# developers to customise development of GUI components.
Continuing with C# and Java
Virtual Machine languages such as C# and Java have a favored place in investment banks. Financial institutions use a lot of these languages for their entire trading infrastructure, including data feeds and front-end trading interfaces.
C# and Java are also mostly used in the sell-side of finance, where you will be less likely to be working on quantitative work and more likely on infrastructure.
C++
If you do know C++, an object-oriented programming language where your design patterns are to a high standard, then you can probably be a quant developer or a traditional developer in the financial industry.
The older financial infrastructure is based on C++ code and that is where C++ developers are needed to maintain and extend it. This might be quantitative libraries running derivatives pricing models or simply trading infrastructure to process feeds and store the data.
And C++ is widely used for quant pricing models across structured products and derivatives.
Furthermore, if you have C++ expertise and want to work in an investment bank, there would certainly be a demand for C++ developers and programmers to create real time applications like risk engines, data feeds as well as connectivity for etrading, eMM and algo execution.
Another extra benefit of being an expert C++ programmer is that it will put you in demand from the high frequency trading funds.
HTML 5
Financial institutions and banks are not only looking for latency and performance of their technology platform, they want it to look polished and smooth-running as after all it is about engineering customer friendly applications in today�s digital age.
As many would know web applications support research and trading applications, making HTML 5 an indispensible knowledge that is not to be trifled. Also, handling HTML 5 is normally used with CSS or Java.
Python
Under investment banking technology, python has been the platform that is widely used for the past few years. Furthermore, investment banks are training up C++ and Java developers in-house on Python to address the new demands at the IT front.
Based on my take, Python skills are highly sought after for research based roles, as it�s faster to write code in this than C++. Furthermore, Cross-market risk management and trading systems are using Python and occasionally used together with C++ to build front-to-bank cross asset risk systems.
Moreover, Python is the arguably the most flexible programming language today and because of its flexibility, it can be easily written for financial modeling where you won�t be limited by how much data you can see on your screen and you can run more scenarios efficiently with a few lines of code.
For Backtesting trades, you are simply able to code an algorithm in Python and run it on data to see how it is being executed.
Lastly, Python is incredible for analyzing data where not only it retrieves data and arranges it; it allows you to directly import SQL queries well.
Conclusion
Ultimately, the choice of programming language really depends on which field of finance you are in and the ideal programming language for finance is certainly not straightforward and requires heavy consideration.
The career progression paths may differ for IT professionals depending on the industry they are working. To check out the ideal career progression paths click here.
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That is because more financial apps are web based. Java is suited well for web development. Apart from this, you have Java APIs and connectors to most backend systems, for eg. SWIFT.