Why Your ML Trading Model Passes 442 Tests But Still Can't Beat a Coin Flip
Why Your ML Trading Model Passes 442 Tests But Still Can’t Beat a Coin Flip TL;DR A developer built a complete Lopez de Prado–style machine learning pipeline in Rust — 442 tests passing, zero bugs — and still ended up with an out-of-sample AUC of 0.50, which is mathematically equivalent to random guessing. The post sparked 43 community replies on r/algotrading, suggesting this is a painfully familiar experience for quant developers. If you’ve ever wondered why a technically flawless ML pipeline produces useless trading signals, this one’s for you. The short answer: correctness and predictiveness are two completely different problems. ...