Should I Learn Python? (For Finance Professionals)
Gone are the days when you had to stare at a computer screen all day, waiting for the numbers to be just right so that you can make your stock trade to optimize your gains. The longer, more time-consuming and exhausting process is on the way out, giving way to programmable strategies that are auto-executed using the popular programming language, Python.
Wondering how? Read on to know more!
What is Python?
Python is a high-level programming language with dynamic semantics which can be used to build a number of applications in various fields. In simple terms, Python is a highly versatile programming language which can be altered to find the perfect fit for said applications.It is also a general programming language which can be used to build web applications, websites or even complex applications. The most important part of Python is its syntax — it is said to be closest to the original mathematics syntax, which makes it quite proficient in playing around with numbers. Though incredibly versatile, Python is ridiculously easy to learn. As an estimate, it should take a beginner with no knowledge of programming about six months to learn Python from scratch.
However, don’t let the terms “basic programming language” take you for a ride for it is still incredibly complex but has a number of real-world applications.
Real World Applications of Python
1. Web Applications & Frameworks
A lot of web applications that you use today are powered by Python. Google App’s search engine is powered partly by Python. The more complex frameworks such as ERP5, which is an enterprise resource planning system used in major industries such as aerospace, banking, etc., are also based completely on Python.2. Business Enterprises: A lot of businesses use Python to support their product. The biggest application of Python used by billions of users worldwide is YouTube. A number of functionalities on YouTube’s video sharing platform have been made possible only by the use of Python. Another huge platform, Reddit, shifted to a more versatile code by moving its framework to Python in the year 2005.
3. Experimentation/Building Prototypes
Since Python is a free programming language, it is only natural that it is also used for experimentation. Python is widely used to build prototypes and rough applications. The beauty of Python is that it can be used to highly customize these prototypes to provide a desirable user experience.
Applications of Python in Finance
Since Python is such a number-oriented and versatile programming language, it is used widely in the financial sector as well. Surprising? Shouldn’t be!
Specifically, it is used in the FinTech sector to build websites and web applications. However, since you would already know that, let’s talk about a few other applications of Python in the finance industry.
1. Banking Software
Python being, well Python, can be used to build highly scalable and incredibly secure banking software applications. Python is used in both online and offline applications which power the banking world. A lot of payment gateways were built and are maintained using Python. In the offline world, ATM software is also developed in Python, since it allows an almost-instant seamless integration of algorithms allowing for faster processing of transactions. Examples: i. Athena, J.P.Morgan’s own pet project is based on Python. Athena is JP Morgan’s own trading software built on Python. ii. Quartz is Bank of America and Merrill Lynch’s joint trading, risk management and position management platform. It was built from scratch using Python.
2. Cryptocurrency Trading
Cryptocurrencies have permeated our financial world like no other concept ever before. Even though most of the major cryptocurrencies are over five years old, they became popular only a couple of years back. Python, being so versatile, is already being used by cryptocurrency traders to execute automatic buy and sell programs.
You can program Python to analyse the past and present pricing data of cryptocurrencies to closely estimate pricing trends. Special Python packages, such as Anaconda are highly suitable for data analytics and have made traders’ lives much simpler and better. A lot of cryptocurrency trading websites currently use Python as an effective tool for gathering historical pricing data, analysing it thoroughly and making future predictions.
3. Automate Stock Trading
Trading stocks is a highly demanding job — it requires analysing thousands of numbers and other data points per day to retrieve any valuable information. Numbers and other number-based data points are incredibly important in optimizing your trades. Python can help you build highly customised strategies and tools that let you execute those strategies just as effectively. Not only does Python help you plot data accurately, but it also lets you use that data to get the most out of each trade.
Let’s take the example of an Arbitrage trade here. Arbitrage is basically profiting off of the difference of prices of one stock/commodity/instrument in two separate markets. It involves buying from one market at a lower price and selling in the other market for a slightly higher price. The profit in an arbitrage trade is the price difference between the two markets in question.
You could use a Python program to analyze the prices of the same commodity/instrument/stock in different markets. This allows you to concentrate on other important things, rather than having to stare at a screen all day, trying to analyze different prices. Your Python program can return the highest and lowest prices across markets in various parts of the world, allowing you to seamlessly make your trade, helping you to pocket the most profit you can.
Why Should You Learn Python ASAP?
Python has numerous advantages, especially in the finance industry. From data analysis to cryptocurrency to automatic trading, Python can be lucrative to the finance sector lot. Here are a few more reasons why you shouldn’t delay starting to learn Python:
1. Ease & Readability:
Python is arguably the most readable programming language. It has clear, well-defined syntax, which makes it simpler for you to learn it sooner than other languages. Python also has forced indentation which makes your life simpler by making the program appear less complex.
2. A Sense of Fulfillment and Progress:
Python is a fairly simple language to learn and use. In Python, most of the learning involves building applications using Python. This helps you track your progress and also gives you a sense of fulfillment.
After all that we’ve spoken about Python, do we really need to say more? It wouldn’t be an overstatement to say that Python is probably the most versatile programming language today. Its applications are varied and imagining the world without Python would be rather difficult.
4. Resources & Community:
Since Python is so widely used, you can find an umpteen number of resources should you encounter a problem. The community of Python users and developers is astronomical and may we add, just as friendly. This is one of the sole reasons you could be learning Python.
The Bottom Line
Python is an incredibly versatile language with a very simple syntax and great readability. It is used for building highly scalable platforms and web-based applications, and is extremely useful in a burdened industry such as finance. It helps you automate quite a few mundane tasks such as collection of data from various points, analyzing them, and drawing useful conclusions.
This beautiful, incredibly versatile programming language is also very easy to learn with the right amount of hard work. Spending an hour a day on Python is more than enough to become proficient in its use. We recommend you start right away!
Knowing how and where to start learning Python can get on your nerves pretty quickly. To save yourself the trouble, join one of Xccelerate’s beginners course on Python to get started. Already know basic Python? Xccelerate also has advanced courses to help you kick-start your journey with Python in the finance industry.
So get started today!
Originally published at xccelerate.co on December 18, 2018.