Example Concept: One common pitfall is using inappropriate cross-validation techniques. Unlike typical cross-validation, time series data requires methods like time series split or walk-forward validation to maintain temporal order. Another issue is overfitting by selecting hyperparameters that perform well on a specific time window but fail to generalize to future data. Additionally, ignoring seasonality and trend components can lead to suboptimal hyperparameter settings that don't capture the underlying data structure.