The finance industry has always been one that is saturated with data and statistics. Those working in the financial industry need to be able to read the information they receive quickly and accurately in order to deliver the best results. IT solutions have come a long way in aiding financial professionals. It is important you choose the right language to suit your business needs.
This multi-purpose object-orientated programming language is ideal for creating desktop applications like Java FX, and design websites such as Spring MVC. It’s used for low latency execution, simulation, and data modeling.
It has a long history within the finance industry and one of the most in-demand languages on Wall Street. Its popularity is likely due to its security. Unfortunately, it is rather difficult for beginners to learn.
Python provides a large range of libraries, assisting with statistics and mathematical models. The similarity in with its syntax and mathematical formats often used with financial algorithms puts Python above the rest.
That being said, it isn’t a programming language known for its speed. Simulation algorithms may backfire when using Python.
If you require high performance and speed, C++ is a good choice for your financial solutions. It also has an extensive number of libraries, and as a low-level programming language, it can access the hardware better than some alternatives.
You will need a C++ developer to maintain legacy financial systems. It will also benefit you if you are a quant developer.
If you are in the habit of trading funds with high frequency, it is also worth hiring a C++ developer who is knowledgeable in the operating system internals, compiler restrictions, and optimizations.
R is highly popular for statistics and data manipulation. It can discover relationships between multiple variables within certain data. Financial professionals like it as it helps to forecast market behavior. R will assist anyone who handles a lot of numbers.
Structured Query Language is the sole intermediary between your database and other tools. Other languages like the three previously mentioned, all require an intermediary to communicate with data.
SQL can help design complex and large scale financial models, aiding in discovering connections between stock prices and what makes them change.
C# was an idea of Microsoft and belongs to the .NET framework. It is a high-level language that can be compared to Java. C# supports multiple paradigms. It uses the object-orientated approach, and within the financial industry, its uses are similar to those of Java.
C# if backed by a large community, perhaps this has helped the programming language gain some popularity.
The matrix laboratory is a qualitative programming language in top demand among financial developers.
Users can implement financial algorithms, matrix manipulation, data function plotting, as well as the development of UI.
Fortran and Julia
It is more than possible that you haven’t heard of these two programs. This is not to say that they haven’t made a dent in the financial sector.
Julia is a baby in terms of programming languages and is just recently started to be used by developers. It tries to make the line between assembly and high-level code less distinct. Codes can be incorporated as quickly as when using C, and you can work with the LLVM representation of functions.
Fortran is not new to the game. It is popular for its application in scientific and mathematical computations. Fortran performs equally as well as C, and even better at number crunching than some of the new programming languages.