Research Topics:

This chapter explains why labeling is a critical step in supervised machine learning for finance.

This chapter addresses a fundamental flaw in modern portfolio theory: instability.

This chapter provides a comprehensive overview of the statistics required to evaluate a backtest, regardless of the backtesting paradigm used (historical, cross-validation, or synthetic).

This chapter argues that backtesting is one of the most misunderstood and misused techniques in finance.

This chapter argues that standard backtesting (historical simulation) is a flawed method for calibrating trading rules (like stop-losses and profit-taking barriers).