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How to use backtesting to create a trading test strategy?

Updated: Apr 17


Author of the article

Author: Leonel Silima

Date of Publication: 08/03/2023




This post may contain affiliate links, which means I may receive a small commission, at no cost to you, if you make a purchase through a link


You might have read a lot about some data processing techniques in other articles of ours. However, in this article we are getting to work to create our own tool for testing trading strategies.



What are the tools needed for this project?


Firstly, you need basic notions of python and programming logic. Next I will present step by step how to create the project. You just need to follow all the points mentioned.


1. Python Installation


You can install python easily and free and to both Windows and Linux systems. Click here to access the installer according to your operating system and follow the instructions.


Don't worry about the pip package because version 3 of python already has it built in. In fact, you just need to go to its command line and view the version of python installed as shown in the following example.


smart trading, backtesting, finance data

Ready to install python with its incorporated pip? Let's proceed with the installation and import of the necessary libraries for the project.


2. Installation of necessary tools for the project


The first step is to install the text editor (the place where you will write your code). My advice is to install anaconda because it brings all the necessary tools for python including editors like PyCharm, Jupyter and others. In this project we will work with Jupyter. Find here anaconda installer and enjoy its amazing tools.


3. Installation of libraries


As we mentioned above, python has a package called pip that is used to install, update, and uninstall libraries. So, we are going to use this tool in our text editor to install the libraries that we are going to use in this project. See the following example.


  • Pandas installation

Pandas is a library used for data analysis and manipulation, it is open source and easy to use, it was built on the Python language. For its installation you just need to type in your text editor the following command:


pip install pandas


  • TA-Lib installation

TA-Lib is a library used by trading software developers required to perform technical analysis of financial market data. Type following command to install:


pip install TA-Lib


  • Yfinance installation

Yfinance is a open source library developed by Ran Aroussi as a means to access the financial data available on Yahoo Finance. Therefore, install it with the following command:


pip install yfinance


  • Backtesting installation

It’s a python framework that uses historical data to infer the viability of trading strategies. Install it with following command:


pip install Backtesting


4. Library import


With all the libraries installed, we proceed with their import for this purpose, we will apply the following procedures.

smart trading, backtesting, finance data

Then we define two input variables where we will ask the end user to define his trading range with start and end date. As we can see the example below:

smart trading, backtesting, finance data

Now let's instantiate an object with our yfinance library to call our input variables and download the data, based on our input stock also defined by the user.

smart trading, backtesting, finance data

At this point we create a class that asks us to strategize to test.

smart trading, backtesting, finance data

Next we run backtesting to visualize the results of the strategy.

smart trading, backtesting, finance data

Moreover, to improve the visualization, let's call the plot function. In particular, thi is incorporated in the backtesting library, to print a graph based on the parameters we defined.

smart trading, backtesting, finance data

Finally, we will run stats to view the details of the results.

smart trading, backtesting, finance data

FULL CODE

smart trading, backtesting, finance data

RESULTS

smart trading, backtesting, finance data

smart trading, backtesting, finance data

As noted in the result above, we had input data from May 2022 to today's date and AMZN (amazon) is our stock. In your case, you can try any stock available on yfinance.



Last thoughts


This tutorial presented an overview of the capabilities of the backtesting library. Our next step in the future is to develop an installable tool for these purposes. Stay tuned for our updates!





Reference list






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