Example Concept: One common pitfall in hyperparameter tuning for time series models is not using time-aware cross-validation methods. Unlike random cross-validation, time series cross-validation respects the temporal order of data by using a rolling or expanding window approach. This ensures that the model is validated on future data, preventing data leakage and providing a more realistic evaluation of model performance.