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Algorithmic Trading with Python

Source code for Algorithmic Trading with Python (2020) by Chris Conlan.

Paperback available for purchase on Amazon.


Useful resources

These stand-alone resources can be useful to researchers with or without the accompanying book. The rest of the material in this repository depends on explanation and context given in the book.

  • Performance metrics used to evaluate trading strategies: metrics.py
  • Common technical indicators in pure Pandas: indicators.py
  • Converting common technical indicators into ternary signals: signals.py
  • Generic grid search wrapper for numeric optimization: optimization.py
  • Object-oriented building blocks for portfolio simulation: portfolio.py
  • Generic wrapper for multi-core repeated K fold cross-validation: model.py
  • Free-to-use simulated EOD stock data and alternative data streams: data

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Source code for Algorithmic Trading with Python (2020) by Chris Conlan

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