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Python for Algorithmic Trading

This project was developed while reading the book Python for Algorithmic Trading by Yves Hilpisch. It was created to give a presentation to students from Hult International Business School who are new to the topic of algorithmic trading. Therefore, it covers the first steps and basic strategies of this topic. The presentation includes the most important steps for algorithmic trading:

  1. Downloading the data from Yahoo Finance and Nasdaq Link
  2. Create a strategy and optimize parameters
  3. Backtest the strategy and plot findings.

The strategies covered are:

  • Simple Moving Averages

  • Momentum
  • Mean Reversion
  • Machine Learning (Linear and Logistic Regression)

This presentation should only be seen as an introduction and further development and optimization of the strategies should be considered.

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This code gives a broad introduction to 4 different Algorithmic Trading Strategies: Momentum, Mean Reversion, Moving Averages and Machine Learning.

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