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Mean reversion and trend following are the two dominant systematic trading approaches. They succeed in almost opposite market conditions, which means neither has a permanent advantage. Understanding how market regimes create and destroy edge for each approach is the foundation of building models that remain functional across changing conditions.

The Stability Score in darwintIQ assesses how evenly distributed a trading model's returns are across the evaluation period, rather than whether returns exist in aggregate. A high Stability Score indicates consistent contribution throughout the window; a low score reveals that performance may be concentrated in a narrow portion of the period — a form of fragility that headline metrics can conceal.

The SupRes Position Manager is one of the position management components available in darwintIQ trading models. Rather than applying fixed pip distances or volatility-scaled rules, it uses identified support and resistance levels to determine where trades should exit — aligning trade management with the structural logic of the market itself.

Risk/reward ratio compares the potential profit of a trade to the potential loss. It is one of the most commonly cited metrics in trading — and one of the most frequently misunderstood. In darwintIQ, risk/reward is one of several metrics evaluated in context with win rate, Expected Value, and drawdown rather than in isolation.

Curve fitting occurs when a trading strategy is optimised so thoroughly on historical data that it captures noise rather than genuine patterns. The result looks compelling in backtesting and fails in live trading. Understanding how curve fitting happens — and why it is so easy to do by accident — is essential for anyone building or evaluating systematic trading models.