hlavni vysvetleni WF ma samostatnou sekci, tady hlavne linky na WF

Walk-Forward Optimization (WFO) is an advanced validation technique that simulates real-world trading by continuously re-optimizing strategy parameters over historical data and testing them on subsequent out-of-sample data segments. This process reveals the strategy’s ability to adapt to changing market conditions and helps identify overfitting.

Optimisation de la marche en avant extends traditional optimization by dividing historical data into multiple time segments. Each segment includes:

• Un Optimization Period (In-Sample)
• A Run Period (Out-of-Sample)

The strategy is optimized on the In-Sample data, and the resulting parameters are applied to the next segment (Out-of-Sample) to evaluate performance. This cycle is repeated across the dataset.

(link to Funtions -> Optimization -> Walk Forward)