Python is widely used in the world of finance. But why? And how? Here, we look at why those looking to get into finance will either need to be able to use Python or at least understand the basics of why the applications they are using are often written with the Python language.
Unlike the relationship between Python and data science, where many data scientists work directly with the code of their applications, many finance industry professionals are likely to be using Python-based applications without actually knowing it.
Python and Finance
Professionals in the financial industry need to carry out complex and difficult computations on a consistent and frequent basis. Manually doing those calculations is simply not a workable solution, so technology and software are required to help support business decisions, investments, and future financial transactions.
Python is used to help run the procedures and processes that make those calculations within seconds—often through applications. As a result, users can use the final calculations to enable them to make informed judgments on any future deals or positions.
Python’s programming language can, once an application or procedure has been written, make light work of market data analysis. That analysis will likely involve huge amounts of data that a human could never possibly input into a spreadsheet, let alone a calculator, to make real-time calculations.
Speed is always of the essence when it comes to finance, as having a better knowledge of what is going on in the markets can help identify lucrative stock trade positions or arbitrage opportunities.
Below we look at why Python is so suitable for creating applications that make swift calculations of enormous amounts of financial data.
Pros of Python in Finance
First and foremost, Python is one of the simplest programming languages out there. That is a massive advantage as it means that it is far more accessible than its competitors.
When it comes to being used in finance, the fact that it is simple to write is crucial when the resulting application has to be capable of complex ideas. When complex coding is required to create a procedure or application, there is an increased danger that the final product will contain bugs or errors that will need to be dealt with.
Additionally, when something is simple to use, it is also far quicker. Developers will often arrive at the end product in a shorter amount of time than using other programming languages. This is because Python is more intuitive, thanks to being based on the structure of the English language.
Time-saving often results in cost-saving, too. If a Python developer is able to produce a product in a week (for illustrative purposes), that a Java developer would take three weeks to create, that will culminate in big savings that can then be invested into the business to help it grow.
Plus, Python is open source which means that any of its code that is downloaded and then modified can actually be distributed for free. While financial institutions are not usually lacking in funds, saving cash is always of the utmost importance to any firm. Especially since software and technology can be one of a company’s biggest expenditures, so any means of keeping costs down is always warmly received.
Another key feature of Python is that it is compatible with a large number of platforms and operating systems. Given how the applications that are developed in any programming language are often rolled out to a large number of people, using all manner of devices and platforms, that is crucial. Applications that materially improve a company’s ability to help its employees perform better must be able to work on whatever piece of technology those employees are using.
Cons of Python in Finance
Some, however, do find that there are a few sizable drawbacks to using Python to create applications and support procedures within the finance industry. Though many of those, a Python developer would argue, can easily be worked through.
For example, some claim that Python is slower than its competitors. The reason for the lack of speed is that it is dynamically typed, and so it takes longer to go through execution.
Many also complain that, in addition to being slow, Python requires a huge amount of memory space. That can be a big setback if a mobile application is required, but, for apps that run through a company server or desktop computer, Python is of a size that is manageable for everyday use.
How Python Helps in Finance
Python helps developers in the financial sector create applications and programs that allow for quick distribution to people all over the world, working on different platforms and operating systems. While Python may have it’s issues, almost every coding language does, and an experienced Python dev knows how to create work around for the issues or test them before the application is deployed to ensure they don’t impact the users experience.
