TheSkallywag/Technical_Analysis_and_Feature_Engineering

Feature Engineering and Feature Importance of Machine Learning in Financial Market.

Feature Engineering and Feature importance in Financial markets.

Background knowledge for Feature Analysis in Finance click this.

Technical Indicators

• I studied over 80 technical indicators in five notebooks.

  • 1. Technical Indicators - Volume.ipynb
  • 2. Technical Indicators - Volatility.ipynb
  • 3. Technical Indicators - Trend.ipynb
  • 4. Technical Indicators - Momentum.ipynb
  • 5. Using technical indicators in Meta-labeling.ipynb

• Technical Indicators Binary Matrix

  • This is for an embedding experiment.

Old ones

• With some Tech. indicators (old version)
  • TI Analysis
• Is it better than simple market data?
  • TI vs. Simple

Feature Importance

• Which one is important? with MDI
  • Correlation with the PC (principle component) of highest MDI

Feature Engineering

• Deep Autoencoder
  • working on this
• CNN architecture
• Embedding like words

Data

• High Frequency Cryptos
• Daily Stocks

Other example

• Usage in my trading rule
• Strategies using technical indicators

References

• AFML (De Prado)
  • Chapter 8 Feature Importance
• MLF-FTTP (Dixon et al.)
  • Chapter 5. Interpretability
  • Chapter 8. 6. Autoencoders
• ML4AT (S. Jansen)
  • Chapter 4: Financial Feature Engineering
• ta (https://github.com/bukosabino/ta)