Python is one of the most popular programming languages among traders because of its numerous benefits. One benefit of this open-source programming language is the availability of free commercial-use packages. The finance community uses Python to create statistical models and a sample trading strategy that allows them to easily predict market outcomes.
It is an ideal choice for traders, helping them build execution mechanisms, data connectors, and optimizing testing modules. Python can be used for backtesting, walk forward analysis, order management, and risk management. This guide will provide a detailed overview of the best learning resources, libraries, and steps for learning Python for trading.
What Is Python?
Python is a well-known general-purpose programming language used in many tech fields like software development, data analytics, and machine learning. This programming language is modular and can easily be integrated with third-party solutions and technologies. Python is also open source, with a community that readily contributes to the advancement of the programming language.
The Python Software Foundation is responsible for overseeing the direction and quality of the programming language. It is referred to as an interpreted language because it is translated to machine code. This is why it can be used to facilitate the writing of universal and portable programs that work well on different operating systems.
What Is Python Used for in Trading?
Python is an essential tool for technical analysis and quantitative finance. This open-source programming language offers exclusive library functions for facilitating the coding of algorithmic trading strategies. It eases the entire process which is why it is preferred over languages like C. It evaluates mathematical models quickly, making it useful for online trading platforms.
Python has a large built-in library of functions that allow traders to compute statistical methods in a few minutes. In high-frequency trading, time is important, and when trading is paired with algorithmic trading strategies, it can be a sure way to accumulate wealth. Furthermore, Python code runs mathematical models in trading strategy faster than other programming languages.
How Long Will It Take to Learn Python for Trading?
It can take around 13 weeks to learn Python for trading with the help of a coding bootcamp. If you apply yourself, this is enough time to learn the syntax as well as some important functions, such as converting a string to integer. Your learning method, time dedicated to learning, and how quickly you assimilate knowledge are key factors in learning Python for trading.
However, learning is an ongoing process. This means that mastery of the programming language may take months or even years. Knowledge of other programming languages can also help you master Python more quickly. Knowledge of programming languages such as Java, C, C#, and C++ can give you a competitive advantage.
Why Should You Learn Python for Trading?
You should learn Python for trading because it has numerous benefits. It will make it easier to work with large datasets using libraries like Dask. It may be overwhelming to work with large datasets that you need to analyze to gain insights into the stock market and improve your returns. Python helps ease this process even though you have to work with text.
Python Is Easy to Use
This programming language is popular because of its ease of use. Professionals use it for desktop applications, robotics, web applications, server automation, science, and machine learning to manage large financial datasets.
Since Python is also a scripting language, it makes it easier to analyze large amounts of financial data and trading signals without waiting for compilation. You can also use the programming language to extend the code with C or C++ code and perform various other tasks. As a result, it is an ideal language for algorithmic traders.
Shortcuts Already Exist
Python is bolstered by extensive libraries created by other professionals. Third-party open source libraries are available for use in specific situations such as financial trading. Some top extensive libraries for trading include Pybrain and Scikit. They are currently used by professional traders in the finance world.
These libraries are considered shortcuts because they eliminate the need for you to write code from scratch. Other popular trading add-ons include matplotlib, SciPy, and NumPy, which simplify the process of performing and visualizing financial algorithms and calculations. You can use them to communicate the results to decision-makers rather than just analyze data.
You have a lot of options with Python. There are textbooks, libraries, tutorials, and a large online community of Python enthusiasts to help you get started. In addition to general Python communities, you can find a trader-focused community to get more specific answers to your questions.
How Can I Learn Python for Trading?
If you have no coding experience, learning Python for trading may be more difficult. However, your learning method may ease the process for you. For instance, you can choose to enroll in a coding bootcamp, read a book, or take an online course. Each of these options has its benefits and some are recommended to help you master Python for trading.
Coding bootcamps have gained popularity in recent times because of their effective and unique learning methods. You can learn Python for trading at a coding bootcamp. The program often has a structured curriculum that takes students from the basics to more advanced aspects of Python for trading, such as using libraries for financial analysis.
The best coding bootcamps are flexible and offer hands-on training to help students develop a portfolio and replicate what they are learning on the job. If you prefer to learn in an interactive environment, this option may be the best for you.
Another flexible option for learning Python is through online courses. These courses are primarily self-paced and include hands-on exercises. Although they are not as interactive as coding bootcamps, some provide forums for students to collaborate and connect.
You have the option of enrolling in free programs and paying for a certificate of completion at the end. Udemy, Udacity, Coursera, and edX are some of the most popular online course providers. Some of the courses are taught by experienced professionals and are offered by universities.
Another useful option for learning Python is to read books. Experts have written guides to help you master Python for trading. The books come in both ebook and hard copy formats, so you can choose the one that suits your preferences. These books may also offer a structured curriculum and exercises that you can complete independently.
The major drawback of this learning method is the possibility of the material becoming outdated. Since it is printed, it may be difficult to get an update automatically. You will need to purchase another book to get an update. Ultimately, the choice is yours to make, and you should consider your learning preferences before doing so.
Top Python for Trading Libraries
Python offers some useful libraries for trading. A library is basically a chunk of precombined codes used to reduce the amount of time required to code. They come in handy for accessing pre-written codes that are used frequently. This helps prevent the need to write every single code from scratch.
It functions similarly to a physical library because it contains reusable resources that can be used in automated trading, such as creating a trading bot and trading algorithm. Listed below are some of the best Python libraries for trading.
- PyAlgoTrade. This is an event-driven backtesting library. This tool supports algorithmic traders by allowing them to evaluate trading ideas based on historical data. This library also provides data from Google Finance, Yahoo Finance, and NinjaTrader CSVs. It also supports TA-Lib integration and outperforms other libraries in terms of flexibility and speed.
- Pybacktest. This library is a backtesting framework in Pandas that is built to make backtesting faster. Users can specify their trading strategies with pandas and hide manual calculations for equity, trades, creating visualizations and performance statistics. The library supports multi-security testing and single security backtesting.
- Keras. This is a library for deep learning. Its main use is to develop neural networks as well as other deep learning models. It is extensible and modular and consists of elements for building neural networks like objectives, layers, and optimizers. Traders use it to predict stock prices using artificial neural networks.
- Scikit-learn. This machine learning library is built on the SciPy library. It consists of different algorithms such as clustering, classification, and regression. It is used with Numpy and SciPy alongside other Python libraries for numerical and scientific computations.
- Pandas. This vast library is used for data analysis and data manipulation. It works well with data frames, numerical tables, and time series. This is why it is preferred in a project involving algorithmic trading. It can also be used to perform arithmetic operations sequentially and Boolean indexing, import CSV files, and collect data on data frames.
There are numerous other libraries and tools that you must learn in order to master Python for trading. For example, you can work with trigonometric functions in Numpy or Numerical Python in its entirety. It is also a powerful library with implementations of massive multidimensional matrices and arrays. It applies to both hyperbolic and logarithmic functions.
How to Learn Python for Trading: A Step-by-Step Guide
Learning Python for trading can take a short or long period of time, it all depends on how you approach the subject. Ensure that you get the right motivation and that you choose a suitable learning method for your preferred education style. This eases the entire process and allows you to learn more quickly. Here are a few more pointers to help you learn Python for trading.
Start With the Fundamentals
Irrespective of the reason for learning Python, you need to start with the basics. When you start from the basics, you will be able to handle complex issues in Python. So ensure that you have a strong background to fall back to. You will learn about data types, syntax, loops, conditional statements, and various Python tools at this stage.
The fundamentals are quite straightforward and the syntax is easy, so you can learn it within a few weeks. If you are learning on your own, take time to study the basics in the right sequence because it will come in handy later. If you are learning in a course or bootcamp, there is a high chance it will be a part of the curriculum.
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Practice is important when it comes to learning Python for trading. You need to practice every day. Just like any spoken language, you need to continue practicing to become fluent. Set a goal for yourself and dedicate a few hours a day to practice what you are learning. You can easily find quizzes and exercises for beginners on the Internet.
Work on Projects
Working on projects is another effective way to learn. It doesn’t matter what learning method you choose, you can start to build projects after learning the basics. You don’t need to start with a complex project. If you’re working with conditional loops, you can create a project around that. Successful projects can be added to a professional portfolio that will showcase your skills to potential employers.
Learn Domain-Specific Libraries
When you have learned the basics of Python, you need to focus on domain-specific libraries. While it is important to know most of the concepts in Python, it may be difficult to learn them all within a short period. It’s a good idea to concentrate on the Python libraries you’ll need to predict financial market outcomes and make better decisions.
Join a Python Community
It is more interesting to learn when you belong to a community of other learners and professionals. If you get stuck practicing, you can always ask for help or get information from forums. This will allow you to teach others like you and provide them with advice on what to avoid.
A good place to find these communities is Reddit. You can also find them on Quora, Slack, Telegram, and LinkedIn. Joining these communities also makes networking with experts in your field easier. Such connections could be useful in the future.
Start Learning Python for Trading Today
Python is a simple programming language for beginners to learn. However, it can be more complicated when you want to learn more advanced aspects of trading. It is ideal to pick a suitable learning method such as a coding bootcamp because it can help you master the principles faster. This training includes hands-on practice and interactive learning as well.
With the right guidance, you can learn Python for trading and use it to make better decisions in the financial market.
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