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.

Walk-Forward Optimization extends traditional optimization by dividing historical data into multiple time segments. Each segment includes:

• An 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)