#AIImpactOnForex Curve fitting, in the context of strategy optimization, refers to the process of excessively tailoring a trading strategy's parameters to perform exceptionally well on a specific set of historical data. While the backtested results might appear impressive, the optimized parameters often become so specific to the past data that they lose their predictive power on new, unseen data. This results in a strategy that is "over-optimized" and likely to underperform, or even fail, in live trading conditions. The danger of curve fitting lies in mistaking random noise and market anomalies in the historical data for genuine patterns. Optimization algorithms, if not carefully controlled, can latch onto these spurious correlations, leading to parameter values that are not robust or adaptable to future market dynamics. Recognizing the signs of curve fitting, such as an excessive number of parameters relative to the amount of data, or unusually high sensitivity of performance to small changes in parameter values, is crucial for developing strategies with real-world applicability.