Several metrics can be used to measure forecasting accuracy:
Mean Absolute Error (MAE): Measures the average magnitude of errors in a set of forecasts, without considering their direction. Mean Squared Error (MSE): Similar to MAE but gives more weight to larger errors, making it useful for identifying significant deviations. Mean Absolute Percentage Error (MAPE): Expresses accuracy as a percentage, making it easier to interpret across different scales.