Stock trading is a very lucrative business. Many people do this for a living, which can be a very profitable venture. However, it is difficult to do this work unless you have the right tools and resources. One such tool you need to invest in if you want to trade stocks is Python programming language. It provides access to various libraries which can help you build your trading strategies or back-test them against actual data sets using machine learning algorithms (MLA). Here we are going to discuss a guide to stock trading with Python.
Python coding and back-testing: How do you do it?
Python is a general-purpose programming language for scientific computing, data analysis, and machine learning. It’s also one of the most popular languages for data science.
The best part about Python is that it’s easy to learn and use. You can start programming in this language with no prior experience or background knowledge of computer science, mathematics, or math concepts like calculus. This makes it suitable for writing software applications where you don’t need too much knowledge about them but need more focus on solving problems using your brain power!
Use Anaconda’s Spyder as the IDE for writing code.
Spyder is a Python IDE that can be used for developing and debugging code. It’s free, open-source, and cross-platform (Windows, Linux & MacOS). Spyder has been developed by the NumPy community to make scientific Python programming easier.
Spyder offers many features that are missing from other IDEs, such as
data visualization tools
code completion suggestions
built-in unit tests
First, install Quantiacs toolbox from their official site or GitHub repo.
First, you must install the Quantiacs toolbox from their official site or GitHub repo.
Note that the installation instructions for each platform may differ slightly, so we’ll cover them separately below:
Install Quantiacs Toolbox in Python
If you’re using a Mac, then executing:
Bash pip installs quantiacs should do the trick. If not, try this command instead: bash pip3 install quantiacs. You can check where your library is by typing pip -l.
Second, Examples folder
Now go to the Examples folder in quantiacs python toolbox and copy and paste the files in that folder to your local directory.
The files are examples of trading strategies. A good way to learn how to code and back-test trading strategies using Python!
Finally, start doing stock trading with Python.
You can start doing stock trading with Python by importing the quantiacs module.
Import the panda’s module to import data into Pandas, a library that allows you to work with data in different formats.
The Matplotlib module offers beautiful graphs and graphics for your analysis of financial markets. You can use this to create graphs or even perform some basic statistical calculations on them.
The NumPy module allows you to deal with large numeric values (like stock prices). It’s useful when dealing with large datasets, especially with Pandas-based analyzes like machine learning models or neural networks!
Hopefully, this post has helped you start stock trading with Python. Contact us now to learn more about this tool and its features. More and more people are turning to Python for stock trading. So join the life-changing journey now.