https://github.com/joacosnchz/spy-randomforest-trading

This trading strategy uses Random Forest Classifier in order to create buy or sell orders for the $SPY ETF outperforming buy & hold strategy
https://github.com/joacosnchz/spy-randomforest-trading

Last synced: 17 days ago
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This trading strategy uses Random Forest Classifier in order to create buy or sell orders for the $SPY ETF outperforming buy & hold strategy

• Host: GitHub
• URL: https://github.com/joacosnchz/spy-randomforest-trading
• Owner: joacosnchz
• License: mit
• Created: 2020-07-10T18:49:32.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2020-07-10T19:03:43.000Z (over 4 years ago)
• Last Synced: 2024-11-05T19:55:33.552Z (2 months ago)
• Language: Jupyter Notebook
• Size: 101 KB
• Stars: 0
• Watchers: 0
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# Abstract

This trading strategy uses Random Forest Classifier in order to create buy or sell orders for the $SPY ETF outperforming buy & hold strategy

# Description

The model is trained using previous 30 days as features and classified using the upcoming 5 days. The accuracy could be better and the confussion matrix shows some big false-positives, but as the equity curve shows it can still be profitable.

![Equity Curve](https://github.com/joacosnchz/spy-randomforest-trading/blob/master/equity_curve.png "Equity Curve")

Looking forward to improve the model performance

# Sources

https://www.quantstart.com/advanced-algorithmic-trading-ebook/