Every trading model in darwintIQ is built from three distinct layers: an entry logic type, a position manager, and a regime filter. This article breaks down what each component does, why each operates independently, and how their interaction shapes overall model performance.
Return stability measures how evenly distributed a trading model's profits are across the evaluation period rather than whether those profits are high in absolute terms. A model with high return stability generates its returns consistently across many trades and conditions. A model with low return stability may show similar total returns but achieves them through a small number of outsized outcomes that are unlikely to repeat reliably.