Python has been a useful tool ever since its inception back in the 80s. Over the years it has seen a growth in popularity, no more so than the past few years. Nowadays, it is undoubtedly one of the most used programming languages. We will look at what Python is and what it does, especially in regard to the finance industry.

 

Contents:

Choosing the Right Program for Trading

Reason Why Python Is a Great Choice for Algorithmic Trading

Python Applications

Pros & Cons of Python

Pros

Cons

Final Thoughts

 

Choosing the Right Program for Trading 

Python can be implemented in a broad range of industries. Before we can delve deeper in this, let's try to understand why you would need it in the first place. The modern world is controlled by technology. As a result, having knowledge about a leading programming language will obviously put your trading operations at an advantage. And because there are various languages out there, it is one of the best to bet on.

 

Financial traders should keep in mind that there is no such thing as the perfect programming language. As a serious trader, you have to consider various factors before proceeding to pick one. Some of the common influencers include:

• The nature of your trading strategy
• Your budget
• The efficiency of the programming language
• Versatility
• Durability

 

By selecting a few programming languages, you can analyze each one based on the above features. In doing so, you create a pros and cons list for each which will make choosing one easier.

 

Reason Why Python Is a Great Choice for Algorithmic Trading

We previously mentioned that python is one of the most popular programming languages today. In fact, it is the third most used as of 2021 just behind HTML/SS and JavaScript. One of the main reasons for the recent popularity surge is its nature as an open-source programming language that can be freely used by anyone.

 

Thanks to its multiple libraries, Python has enabled traders to create complex scientific models with relative ease. Pandas is one of the popular libraries connected to Python, the rest include:

• Zipline
• Scikit-Learn
• NumPy
• SciPy
• Pyglet

 

Another interesting feature about Python is the large communities of its users. These groups offer support to Python users by providing any useful, up-to-date tips to the libraries.  One of the largest Python communities is Python meetups which comprise more than 800, 000 members.

 

Python has solidified its practicality. Today some of the biggest companies have adopted its use as well. Here’s a list f the most prominent ones:

• Google
• Instagram
• Netflix
• Facebook
• Reddit

 

Python Applications

Python is versatile in its applications. It can be used for anything within the sphere of software design and website development. Popularly, Python has extended its application in the field of machine learning which has undeniable potential in the financial sector, especially with marketing and trading.

 

Because we live in a world that is constantly changing, many professionals recommend that learning Python be included in the training programs associated with finance. Doing so will finally bridge the gap between traders and software programmers. Other common applications not related to finance include:

• Video game development
• Medicine
• Education
• Network Programming 
• Desktop applications

 

Pros & Cons of Python

Python is not a perfect programming language. Although it is useful, it does have its own share of drawbacks as well. Let’s look at some of the advantages and disadvantages you’ll encounter while using Python.

Pros

• Python can be used at any scale which can vary depending on your trading goals;
• Python has the capability of supporting a multitude of data science libraries;
• It can be used for free and any additional features are affordable;
• Compared to other common programming languages, Python is easier to learn and get accustomed to;
• Another reason why Python is easy to learn and code is its readability, which is akin the reading the English Language;
• You can collect historical stock prices into Excel with Python;
• Python is compatible with any device regardless of what operating system it runs on.

Cons

• Due to the type of coding used in Python, the speed of interpretation of data is slowed down;
• Although it is compatible with a wide range of ORs, Python  does not have a high efficiency on mobile devices;
• Python is easy to learn and use, although this is a good feature to have it make this programming language one-dimensional. The choice of personalization is taken away from the developer;
• Many individuals might question the credibility of python due to its simplicity.

 

Final Thoughts

Python has been widely accepted in the field of algorithmic trading. Its current course shows that it will continue to be innovative as more indications in the financial industry are discovered.

 

It is an easy tool to use and is designed to be used by any trader regardless of income and level of expertise. Although it has its own fair share of problems, it is still by far one of the best programming languages out there.

 

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