If there’s one thing you can say about the world of finance, it’s that updated technology is something they depend on to do their jobs right. Whether you’re a banker, financial analyst, or an investment specialist, your job usually involves tons of data, not to mention tons of confidential information that needs to stay secure and away from the wrong ears and eyes. This is why there are so many programs developed just for these and other similar industries, and finding the best programming language to learn for finance of any type is not that difficult if you know where to look.
Some Programs Are Just Obvious
If you are familiar with some of the programming languages available right now, some are just more obviously useful than others. These languages are needed to develop certain apps and AI trading algorithms for financial modelling, running simulations, and data science, among other tasks. If you have a computer science degree that is 20 years old, you might not be familiar with some of the more advanced programs used today, which is why this article is being written.
One of the reasons the finance industry has always been receptive to new technologies is because they deal with so many numbers and confidential data, and it takes the most updated technology, which is continuously improving, to accommodate that data. If you look at the list of any IT company’s biggest clients, many of them are banks and other financial institutions, as well as investment firms and other entities that deal in lots of data and numbers. If you’re new to programming, you might as well get used to the fact that you’ll constantly be learning because there are not only new programs coming out all the time, but a lot of updates and changes are being made to those programs as well.
There are a lot of reasons why these programming languages are such good ones. If you’re not familiar with the languages that are used in today’s finance and investment sectors, below are some of them you may want to research.
Lots of people have heard of the C# programming language, but not everyone knows what it is or how significant it is to the financial industry. C# is a high-level language that was developed by Microsoft and which belongs to the .NET framework. It is a lot like Java, and it supports numerous paradigms, even using an object-oriented approach to do its job. Slowly but surely, C# is gaining in popularity in the finance industry, and just like Java, C# is mainly used for data modelling and data simulation.
C++ is a great solution in financial fields because it is high-performance and offers a lot of speed for all of your financial solutions. C++ has a lot of different libraries, much like Python does, and it is also known as a low-level language, meaning that it can access the hardware better compared to other languages. It is also able to communicate better with all of the internal components of the system.
If you are in the financial sector, C++ helps in many ways and can make a lot of your job a lot easier. Legacy financial systems, which are known to comprise a large portion of the financial applications in the entire world, are still being run on the C++ program. This is why, if you are in the financial sector, you truly need to have a C++ developer on your staff so that these systems can be maintained. If you are a C++ developer, trading funds with high frequency will benefit you. Still, of course, you have to be familiar with compiler restrictions, operating system internals, and optimisations if you want to do well in finance.
FORTRAN and JULIA
These are both programming languages that have done surprisingly well in the finance sector, even though they are not necessarily the most popular programming languages right now. Let’s take a brief look at each of them.
Fortran has been around a while, and in the past, it has been used in both mathematical and scientific computations. Because of this, Fortran is doing extremely well in the finance industry, and it is easy to understand why. As far as its performance goes, Fortran is pretty much on par with C. Also, in some instances, Fortran performs better than newer programming languages when it’s crunching numbers.
Julia is relatively new and is slowly gaining in popularity with developers. Julia essentially makes the line blurry between the assembly and the high-level code. It can help you incorporate code that is fast like C, and it can help you work with the LLVM representation of functions alongside their assembler codes.
Java is a multipurpose programming language that you can use to create desktop applications (JavaFX) or design great websites (Spring MVC, JavaEE). It is used in particular on the enterprise scale, and it is a very object-oriented programming language. If you take a look back at the history of Java, you’ll find it has been used extensively in both the banking and finance sectors and in-fact, Wall Street considers this programming language to be a must. As opposed to other languages, Java offers tremendous security, which could be the reason for its popularity on Wall Street and in the corporate world, where very sensitive data is the law of the land.
The one thing you should always keep in mind about Java, however, is that it tends to be more challenging to learn than many other languages, especially for beginners. In other words, there is a learning curve for Java. Some of the areas that Java is used for these days include data modelling, low-latency execution, and simulation, among others.
Short for matrix laboratory, MATLAB is very much in demand these days in the world of finance, in part because of its qualitative programming language features. Listed as a proprietary programming language, MATLAB helps users implement financial algorithms, data function plotting, matrix manipulation, and even the development of UI, as well as integrating it with software and various tools designed in other programming languages – often called a cross-platform.
Known for its legendary plotting tools, MATLAB is useful for floating-point linear algebra, and generator plots and other interactive finance tasks, and these days, it is attractive for traders or structures with the need to test things out in fast-moving markets. This is in part because it is such a fast language when it comes to coding time. MATLAB has a lot of fans in the applied mathematics sector, which is how it found its way into the world of finance.
Python has only been around since 1991, but it has grown by leaps and bounds since then. It is associated mostly with artificial intelligence (AI), data science, and machine learning. Why? Because it contains large numbers of libraries that help with all types of mathematical models and statistics. Furthermore, whether you want the desktop version or a mobile app of the program, it will be straightforward to develop. The main thing to keep in mind about Python is that it tends to be a rather slow programming language. Because of this, it is generally not recommended when you need to run something like a simulation algorithm.
Python is also very unique because its syntax is very similar to the mathematical format often used with all types of financial algorithms. Because of this, developers who are familiar with mathematics and economics consider it an excellent programming language for their needs.
When it comes to areas such as data manipulation and even statistics, this is a handy and popular programming language indeed. R can analyse and process data to discover the relationship between multiple variables. Because of this, R does great in the financial industry and can even help analysts forecast the market’s behaviour. It can predict which actions should be taken by investors after an asset’s value suddenly goes up. Indeed, any time your business involves working with a lot of numbers regularly, you need this programming language because it will simply make your life easier and less complicated.
R can be difficult to learn, but when it comes to data, it is second to none because it can accommodate everything from data visualisations to statistical computing, and everything in between.
Structured Query Language, or SQL, is considered not to be a true programming language by many people. Nevertheless, it is an essential language for many different reasons. When you use programs such as R, Python, Java, or any others for all of your financial solutions, you need an intermediary that essentially helps you communicate with your data. This is where SQL comes in. SQL is essentially an intermediary between the database and the other tools in your ecosystem.
Today’s financial experts tend to design very complicated and huge financial models by utilising SQL. SQL helps them discover what the link is between the stock prices and also to identify the factors that are necessary and responsible for changing those prices.
These are the main languages used in the financial industry, so having a familiarity, even if you don’t use them frequently, with at least two or three of them can help your career.