Complexity, or Simplicity?

Should investors, particularly those employing machine learning, prefer complex or simple prediction models? In the May 2025 revision of his paper entitled “Simplified: A Closer Look at the Virtue of Complexity in Return Prediction”, Daniel Buncic challenges prior research finding that portfolio performance (Sharpe ratio) increases with machine learning model complexity when the number of inputs (potential predictors) greatly exceeds the number of training observations. Using the same dataset, prediction models and portfolio evaluation methods as the prior research, he finds that: (more…)