Feature engineering > model hacking

Summary

• The post discusses using fractionally differenced features (from Marcos Lopez de Prado) to transform non-stationary price data into stationary data while preserving memory, improving ML model generalization in microstructure strategies.
• The author’s thesis is that careful feature engineering (fractional differentiation) is more valuable than aggressively tuning models ("model hacking") for trading strategies.
• Quality assessment: Well-researched DD – references academic work, explains a specific technical method, and shares a personal positive experience in a microstructure strategy.