In forecasting, what does a higher mean absolute percentage error (MAPE) indicate?

In forecasting, what does a higher mean absolute percentage error (MAPE) indicate?

• A. Better forecasting accuracy
• B. Higher forecasting reliability
• C. Greater deviation from actual values
• D. Lower average errors

Answer: (C)

A higher mean absolute percentage error (MAPE) signifies a greater deviation from actual values in forecasting. MAPE measures the accuracy of a forecasting method by calculating the average absolute percentage error between forecasted and actual values. When MAPE is high, it indicates that the forecasts are, on average, significantly off from the actual observed values. This metric provides insight into the performance of the forecasting model: a high MAPE more clearly highlights issues with the forecasts' reliability and precision, leading to concerns about the effectiveness of the forecasting method employed. Therefore, a higher MAPE indicates poor accuracy rather than reliability, which reinforces that the model is not performing well in predicting outcomes closely related to actual results.

A higher mean absolute percentage error (MAPE) signifies a greater deviation from actual values in forecasting. MAPE measures the accuracy of a forecasting method by calculating the average absolute percentage error between forecasted and actual values. When MAPE is high, it indicates that the forecasts are, on average, significantly off from the actual observed values.

This metric provides insight into the performance of the forecasting model: a high MAPE more clearly highlights issues with the forecasts' reliability and precision, leading to concerns about the effectiveness of the forecasting method employed. Therefore, a higher MAPE indicates poor accuracy rather than reliability, which reinforces that the model is not performing well in predicting outcomes closely related to actual results.