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Python's Application in Finance and Fintech

Updated: Dec 31, 2022


Python Programming

Gone are the days when you had to spend your whole day staring at a computer screen, waiting for the numbers to line up exactly right so you could make your stock trade and maximize your profits. Longer, more time-consuming, and demanding processes are being phased out in favour of programmed techniques that are executed automatically using Python, a popular programming language.


Python was one of the top three most popular languages in financial services, according to the HackerRank 2018 Developer Skills Report. Python appears to be one of the most in-demand languages in the banking business in 2020.


According to eFinancialCareers, the number of finance-related jobs mentioning Python has nearly tripled in the previous two years, rising from 270 to over 800. Citigroup, for example, now offers Python coding lessons as part of its continuing education program for financial analysts and traders.


In an interview with Lee Waite, the CEO of Citigroup Holdings, remarked, "We're going more quickly into this environment." “At the very least, knowing how to code appears to be beneficial.”


Python is still one of the most popular programming languages in the banking business, according to eFinancialCareers.



What makes Python such an excellent platform for fintech and finance projects?


Python is a dynamically high-level programming language that may be used to create a variety of applications in a variety of industries. To put it simply, Python is a highly adaptable programming language that can be tweaked to find the best fit for specific applications. It's also a general-purpose programming language that can be used to create web apps, websites, and even complicated programs. The most essential aspect of Python is its syntax, which is claimed to be the most closely related to the original mathematical syntax, making it highly adept at manipulating numbers. Python is deceptively simple to learn, despite its incredible versatility. To learn Python from the ground up, it should take roughly six months for a newbie with no prior programming experience.


However, don't be mislead by the name "simple programming language," since it is still extremely complex and has a variety of real-world applications.


Several features of Python make it a great pick for finance and fintech. Here are the most significant ones:


It's straightforward and adaptable

Python is simple to build and deploy, making it an ideal contender for dealing with financial industry applications, which are frequently extremely complicated.


Python's syntax is straightforward and speeds up development, allowing businesses to swiftly construct the software they require or launch new products. Simultaneously, it lowers the risk of error, which is crucial when building products for a highly regulated business such as finance.


Python is one of the most accessible programming languages

It allows building an MVP quickly

The financial services industry must become more agile and responsive to customer expectations, providing tailored experiences and value-added services. That's why financial institutions and fintechs require a system that's both versatile and scalable, which Python provides. Developers can swiftly get a concept off the ground and produce a good MVP using Python and frameworks like Django, allowing them to quickly identify a product/market fit.


Businesses can quickly update sections of the code or add new ones after evaluating the MVP to build a faultless product.


The Clearminds platform, which was developed using Python and Django, is an example of a successful MVP strategy. They now provide financial guidance as well as investment instruments.


It bridges the gap between economics and data science

Economists, on the other hand, are less likely to use languages like Matlab or R in their computations, preferring instead to use Python. That's why Python is so popular in finance because of its ease of use and practicality in constructing algorithms and formulas — it's much easier to integrate economists' work into Python-based systems.


Scipy, NumPy, and matplotlib are examples of tools that may be used to do complex financial computations and show the results in a user-friendly manner.


It has a diverse library and tool ecosystem

Python allows developers to create tools without having to start from scratch, saving time and money on development initiatives.

Furthermore, finance solutions sometimes necessitate third-party integrations, which Python frameworks facilitate. Python's development speed, combined with its array of tools and libraries, gives businesses a competitive edge when it comes to meeting changing consumer demands by providing products swiftly.


It's well-known

Python is surrounded by a thriving community of dedicated developers that contribute to open-source projects, create useful tools, and host endless events to exchange knowledge about Python development best practices.


Python is a computer language that is growing in popularity year after year. All of this makes it easier to find and hire skilled Python coders for fintech and finance projects. Organizations that invest in Python-based solutions can rest assured that their technology will not become obsolete very soon.



Python in the Financial Sector


Python is useful in a wide number of applications. The most common usage of the phrase in the financial services business is listed below.


Analytics Tools

Python is commonly used in quantitative finance to process and analyze massive datasets, such as financial data. Pandas is a library that simplifies the process of data visualization and allows for complex statistical analyses.

Python-based solutions are equipped with powerful machine learning algorithms that enable predictive analytics, which is extremely important to all financial services providers, thanks to libraries like Scikit or PyBrain.


Banking Software

Python, being Python, can be utilized to create tremendously scalable and secure banking software solutions. Python is utilised in the banking industry to power both online and offline applications. Python has been used to create and maintain a large number of payment gateways. In the offline world, ATM software is also written in Python since it allows for near-instantaneous seamless integration of algorithms, resulting in speedier transaction processing.


Example:

  • J.P. Morgan's personal pet project, Athena, is built on Python. JP Morgan's proprietary trading software, Athena, is written in Python.

  • Quartz is a joint trading, risk management, and position management platform developed by Bank of America and Merrill Lynch. Python was used to create it from the ground up.


Cryptocurrency Trading

Cryptocurrencies have infiltrated our financial world in a way that no other concept has. Despite the fact that the majority of the biggest cryptocurrencies are over five years old, they just became popular a few years ago. Python is already being used by bitcoin traders to run automated buy and sell scripts due to its versatility.


Python may be used to analyze historical and current cryptocurrency pricing data in order to forecast pricing patterns. Special Python programs, such as Anaconda, are well-suited to data analytics and have simplified and improved the lives of traders. Python is now being used by a number of cryptocurrency trading services to acquire historical pricing data, analyze it thoroughly, and make future forecasts.


Building a stock trading strategy with Python

Trading stocks is a tough job that involves daily analysis of thousands of figures and other data points in order to extract any useful information. The importance of numbers and other numerical data points in improving your trades cannot be overstated. Python can assist you in developing highly customized plans as well as tools that enable you to execute such strategies efficiently. Python not only allows you to plot data precisely, but it also allows you to use that data to make the most of each deal.


Let's look at an Arbitrage deal as an example. Arbitrage is the practice of benefitting from the price differential between two marketplaces for the same stock, commodity, or instrument. It entails purchasing at a lower price in one market and selling at a slightly higher price in the other. The difference in price between the two markets is the profit in an arbitrage trade.


A Python application could be used to compare the pricing of the same commodity/instrument/stock in multiple markets. This frees you up to focus on other essential things rather than staring at a screen all day comparing costs. Your Python application may return the highest and lowest prices across markets in different parts of the world, allowing you to make your trades more easily and profitably.



Why Should You Start Learning Python Right Away?


Python provides a number of advantages, particularly in the financial sector. Python has a lot of potential in the banking sector, from data analysis to cryptocurrencies to automated trading. Here are a few more reasons why you should start learning Python right away:


Ease & Readability

Python is, without a doubt, the most readable programming language available. It has a basic, well-defined grammar that allows you to learn it faster than other languages. Python also includes forced indentation, which makes life easier by making the program appear less complicated.


A Sense Of Accomplishment And Progress

Python is a relatively easy language to pick up and use. The majority of Python learning entails creating Python programs. This allows you to keep track of your progress and provides you with a sense of accomplishment.


Versatility

Do we really need to say anything further about Python now that we've covered everything there is to know about it? It isn't an exaggeration to argue that Python is the most versatile programming language available today. Python has a wide range of uses, and it's impossible to imagine a world without it.


Resources & Community

Since Python is so widely used, you'll be able to locate a plethora of resources if you run into trouble. The Python user and developer community is enormous, and, may we say, extremely friendly. One of the only reasons you could be learning Python is for this reason.



Conclusion


Python is a very versatile programming language with a simple syntax and excellent readability. It's utilized to create highly scalable platforms and web-based applications, and it's very helpful in a high-volume business like finance. It allows you to automate a number of tedious chores, such as gathering data from numerous sources, evaluating it, and making valuable conclusions.


With the correct amount of effort, this gorgeous, very powerful programming language is also relatively easy to master. It's enough to spend an hour a day on Python to become an expert in its use. We strongly advise you to get started right now!


It's easy to get frustrated trying to figure out how and where to begin studying Python. To save yourself the trouble, join one of these Python developer programs to get started and do check out our blog post on 8 Suggestions to Learn Python Fast.


Already know basic Python? We also have advanced courses to help you kick-start your journey with Python in the finance industry. Just send us an email at enquiry@gemrain.net and we will get back to you.



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