texasraj/backtest_tutorial

Backtesting Tutorial for Algorithmic Trading

Welcome to the GitHub repository for our Udemy course on backtesting for algorithmic traders. This course is designed to teach you the fundamental concepts and practical applications of backtesting trading strategies, using Python and various financial analysis libraries.

About the Course

This course offers a comprehensive introduction to backtesting trading strategies. We focus on creating a robust framework to test your trading ideas and hypotheses with historical market data. The course covers:

• Building your own backtester in python.
• Before you backtest - use this protocol!
• Best Practices in Research for Quantitative Equity Strategies
• What Not to Do!
• The Importance of Causality in your Experiment Design
• Detecting False Investment Strategies
• Bonus Lectures

Repository Contents

This repository includes the Jupyter Notebooks used in the course:

• YFinance_Tutorial: An introduction to pulling free data from Yahoo Finance, using the yfinance library.
• Vectorized_Backtest_Tutorial.ipynb: The main tutorial notebook with Python code and detailed explanations.
• Intro_Transaction_Costs.ipynb: A tutorial to show how transaction costs can be added to your backtests.

Getting Started

To get started with the tutorial:

1. Clone the Repository: Clone this repository to your local machine using:

   git clone https://github.com/hudson-and-thames/backtest_tutorial.git

2. Set Up Your Environment:

   • It is recommended to use a virtual environment.
   • Open the getting_started.md file to follow the setup instructions.

3. Run the Jupyter Notebooks: Open the notebooks in Jupyter and follow along with the course.

Prerequisites

Before starting this course, you should have:

• Basic knowledge of Python programming.
• Understanding of financial markets and trading principles.
• Familiarity with Jupyter Notebooks.
• This is taught at a graduate level.

Contributing

We welcome contributions to this tutorial! If you have suggestions for improvements, please feel free to make a pull request or open an issue.

License

This tutorial is provided under the MIT License.

Contact

For any queries or feedback related to this course, please contact system[at]hudsonthames.org.