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SQX has many signals; what if we use genetic evolution just for exits? We could fix entry rules and let the algorithm optimize exits, focusing on trailing stops, profit targets, and break-even adjustments. We’ll set boundaries like trailing stops of 10-100 pips and profit targets of 20-100 pips. Fitness criteria will maximize profit factor and trade frequency while maintaining risk management with a 0.01 lots per $100 balance rule. We’ll monitor performance and pause if there are no improvements after 10 generations. Back tests will ensure strategies adapt to market conditions. With SQX exploring and us fine-tuning, this could be a gold-standard approach. Let’s get started!
