The Cost of Overfitting: Lessons Traders Can Learn From Data Science

Overfitting happens when trading strategies are optimized too closely to historical data, mistaking noise for signal. While backtests may look impressive, overfit systems often collapse in live markets. By applying data science principles like in-sample/out-of-sample testing, cross-validation, simpler rule design, and probabilistic thinking, traders can build more resilient, adaptable strategies.