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Average True Range (ATR) is a volatility measure that scales with current market conditions rather than using a fixed value. In darwintIQ, the ATR Position Manager uses ATR multiples to calibrate stop and target distances dynamically — reducing noise-triggered exits and maintaining proportional risk across different symbols and market conditions.

Charlie is the new AI Market Analyst inside darwintIQ. It turns live model context into readable market interpretation through structured analytical workflows.

A common assumption in algorithmic trading is that more trades generate more profit. In practice, trading too frequently can dilute an edge, inflate drawdown, and increase exposure to adverse market conditions. In darwintIQ, trade frequency is evaluated alongside quality metrics like Expected Value and Profit Factor to distinguish genuinely productive activity from noise.

Win rate is one of the most intuitive metrics in trading — and one of the most misleading when used in isolation. A model can have a high win rate and still lose money. Understanding why requires looking at Expected Value, Risk/Reward, and how darwintIQ evaluates structural quality across multiple dimensions.

A regime filter is the component of a trading model that controls whether the model is allowed to trade based on the current market environment. In darwintIQ, regime filters are one of the three building blocks of every trading model, working alongside Entry Logic and Position Management to improve consistency across changing market conditions.