How is forecast error calculated?

The calculation of forecast error is a critical aspect of evaluating the accuracy of predictions made by a forecasting model. The correct formula for determining the forecast error is derived by subtracting the forecasted value from the actual value. This approach allows analysts to understand how far off the forecast was from what actually occurred, providing a clear indication of the model's performance.

Using the formula of actual value minus forecast value gives the net difference, which can be positive or negative. A positive error indicates that the forecast was lower than the actual outcome, while a negative error means the forecast was higher. This distinction is important for making adjustments to forecasting methods in the future, as it highlights specific areas of bias or consistent inaccuracies.

In contrast, the other choices do not accurately represent the conventional approach to calculating forecast error. For instance, the first option subtracts actual values from forecasts but does not align with the established convention. The third option provides a relative error but complicates the direct relationship between the forecast and actual values. Lastly, the fourth option incorrectly suggests a ratio rather than a difference, which does not convey the direction or magnitude of the error effectively. Thus, the choice of actual value minus forecast value captures the essence of forecast error accurately.