darwintIQ has extended the evaluation window for live models to 40 hours and carved off the most recent 8 hours as a true out-of-sample holdout. The genetic algorithm optimises fitness on the training portion only, and a separate selection gate rejects any model that fails to stay profitable on the unseen tail. This article explains how the holdout works, why train-only fitness matters, and how to read the new holdout card in the Trader Detail View.
Correlation determines whether running multiple trading models spreads your risk or quietly concentrates it. This article explains correlation in trading, why apparent diversification across symbols can be an illusion, how correlation shifts in a crisis, and what darwintIQ’s multi-symbol view helps you see.
A short run of wins tells you almost nothing about whether a strategy has an edge. This article explains statistical significance in trading — why sample size determines how much you can trust a result, how randomness mimics skill over small samples, and how darwintIQ’s rolling evaluation builds confidence over time.