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Python implementations of commonly used trading algorithms

Project description


Python Implementations of popular Algorithmic Trading Strategies, along with genetic algorithms for tuning parameters based on historical data.

Algorithms -

  1. CCI Correction (Done)
  2. Stochastic Pop and Drop (Done)
  3. Percent Above 50-day SMA (Done)
  4. Moving Momentum (Done)
  5. Exponential Moving Averages (Done)
  6. Double Exponential Moving Averages (Done)
  7. Triple Exponential Moving Averages (Done)
  8. Six-Month Cycle MACD (Done)
  9. Gap Trading Strategies
  10. Harmonic Patterns
  11. The Last Stochastic Technique
  12. Percent B Money Flow
  13. Pre-Holiday Effect
  14. RSI2
  15. Faber’s Sector rotation Trading Strategy
  16. CVR3 VIX Market Timing
  17. Slope Performance Trend
  18. Swing Charting
  19. Ichimoku Cloud
  20. Trend Quantification and Asset Allocation

Project details

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Files for algotrader, version 0.1.dev0
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Filename, size algotrader-0.1.dev0.macosx-10.7-x86_64.tar.gz (22.3 kB) File type Source Python version None Upload date Hashes View
Filename, size algotrader-0.1.dev0-py3-none-any.whl (19.3 kB) File type Wheel Python version py3 Upload date Hashes View

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