Point Forecast Evaluation: State of the Art.

This article provides an overview of the importance of evaluating forecasts and the current state of evaluating point forecasts. The main goal of evaluation is to monitor and improve the forecasting process. The article highlights the need to select the appropriate error measure, such as root mean squared error (RMSE), when evaluating forecasts. It also discusses the importance of scaling error measures when evaluating forecasts across different aggregations. The article suggests alternative approaches to the commonly used mean absolute percentage error (MAPE) and introduces concepts like root mean squared scaled error (RMSSE) and relative RMSE (rRMSE) for scaling error measures. Additionally, the article introduces the concept of forecast value added (FVA) as a way to compare different forecasting approaches. The author emphasizes the importance of accurately measuring and interpreting error measures in forecast evaluation. [Extracted from the article]