Some Empirical Findings on Short‐Term Forecasting: Technique Complexity and Combinations
研究了在需求数据波动大的短期预测环境中，简单预测技术和组合是否仍然更优，使用22个真实商业日度数据序列进行一期预测测试。
ABSTRACT The purpose of this research is to determine if prior findings that favor simple forecasting techniques and technique combinations hold true in a short‐term forecasting environment, where demand data can be quite volatile. Twenty‐two time series of daily data from a real business setting are used to test one‐period ahead forecasts, the epitome of short‐term forecasting. The time series vary systematically as to data volatility and forecast difficulty. Forecast accuracy is measured in terms of both mean absolute percentage error (MAPE) and mean percentage error (MPE).