Does updating judgmental forecasts improve forecast accuracy?

被引:14
作者
O'Connor, M
Remus, W
Griggs, K
机构
[1] Univ Hawaii, Honolulu, HI 96822 USA
[2] Univ New S Wales, Sydney, NSW, Australia
[3] Calif Polytech, San Luis Obispo, CA USA
关键词
judgment; time series; rolling forecasts;
D O I
10.1016/S0169-2070(99)00039-4
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study investigates whether updating judgmental forecasts of time series leads to more accurate forecasts. The literature is clear that accurate contextual information will improve forecast accuracy. However, forecasts are sometimes updated when pure temporal information like the most recent time series value becomes available. The key assumption in the latter case is that forecast accuracy improves as one gets closer in time to the event to be forecasted; that is, accuracy improves as new times series values become available. There is evidence both to support and to question this assumption. To examine the impact of temporal information on forecast accuracy, an experiment was conducted. The experiment found improved forecast accuracy from updating time series forecasts when new temporal information arrived if the time series was trended. However, there appeared to be no value in updating time series forecasts when the time series were relatively stable. (C) 2000 Elsevier Science BN. All rights reserved.
引用
收藏
页码:101 / 109
页数:9
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