All You Need To Get Started With Backtesting In Python

Learn how to backtest any technical indicator-based strategy using Python

This guide is a set of notebooks that teaches you a framework I have been using for the past 4+ years to backtest any of your technical strategies in Python.

I have condensed my learnings while building strategies for myself and implementing them in real market scenarios and you will learn it by implementing 5 of my high-accuracy strategies.

What will you learn?

• Using the Yahoo Finance database to access stock market data
• Understanding the most widely used technical indicators and how they are calculated
• Building a strategy using the indicators and implementing it on data from the last 10 years
• Calculating Backtesting results using various metrics for comparison with other strategies
• Optimizing your strategy further by implementing money market rules and getting more precise backtesting results
• Detailed observation of strategy results to see further scope for optimization.

All of this using the power of Python! It gives you the complete framework to do all of it in a plug-and-play format.

What do you mean by plug-and-play?

You can use these notebooks to backtest any stock listed on any major stock exchange in the world. All you need to do is alter your choice's time frame and stock and run the notebooks.

Can you use this to backtest using other strategies of your choice?

All you need to do is replace indicators of your choice with the existing ones and replace the strategy conditions for Buy and Sell based on your logic and you are good to go.

Moreover, these strategies and most importantly the backtesting framework I discuss here don't just apply to stocks but also to a wide variety of traded assets.

Some snippets from the guide :

Visualize the movement of technical indicators that are used in your strategy along with the daily price (OHLC Candlestick chart)

Learn to visualize when your strategy gave a buy/sell call at what price level over your entire backtesting period.

Why Python?

Python is one of the most versatile programming languages out there. It is powerful, simpler to understand, and has a large and diverse pool of developers who write and maintain code.

When it comes to Trading and Finance, python is the first choice among Algo traders and Quantitative Developers. Given that the Python community in finance is so huge, it makes it much easier to build and maintain your systems in Python.

This guide is for you if :

• You have a basic understanding of Python programming or programming in general
• You use technical indicators to make buy/sell decisions in financial markets
• You are a programmer and just getting started with trading in financial markets
• You are an experienced trader using technicals and just getting started with programming

Are there any prerequisites?

• Python computing stack installed on your local machine. You can download and install Anaconda or even use Google Colab.
• Basic understanding of programming in general or Python programming language
• Basic understanding of financial markets