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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.

USDJPY currently reads fragile bearish, with regime and model leadership broadly aligned. Main risk: Market structure looks unstable.

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.

SP500 currently reads bullish, with regime and model leadership broadly aligned. Main risk: Current expectancy looks weak.

Mutual information is a statistical measure of the degree to which two variables are genuinely dependent — how much knowing one reduces uncertainty about the other. In trading model evaluation, it is used to assess whether a model's entry signals contain real predictive information about trade outcomes, rather than a pattern that appears meaningful but lacks structural dependence.