#AITradingAffectsForex Walk-forward optimization (WFO) is a powerful technique for evaluating AI model performance in trading. WFO involves training and testing an AI model on historical data, then evaluating its performance on out-of-sample data. This process is repeated iteratively, with the model being retrained and retested on new data. WFO provides a realistic evaluation of AI model performance, as it simulates the challenges of real-time trading. Key benefits of WFO include: Improved model selection: WFO helps traders select the best-performing AI model. Enhanced risk management: WFO evaluates model performance under various market conditions, enabling traders to assess risk. Increased confidence: WFO provides a more accurate assessment of AI model performance, giving traders greater confidence in their trading decisions. By using WFO, traders can optimize their AI models and achieve better trading results.