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

Paperback available for purchase on Amazon.

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