Walk-forward validation evaluates a time-dependent model or strategy through a sequence of chronological windows. Each step uses only earlier data for development and then tests on the next period, after which the window moves forward.
This design better resembles repeated real deployment than a random train-test split. It can reveal whether performance survives changing conditions, although results still depend on window choices, data quality, realistic execution assumptions and disciplined parameter selection.
