Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Is there a golden rule?
AU - Fildes, Robert
AU - Petropoulos, Fotios
PY - 2015/8
Y1 - 2015/8
N2 - Armstrong, Green, and Graefe (this issue) propose the Golden Rule in forecasting: “be conservative”. According to the authors, the successful application of the Golden Rule comes through a checklist of 28 guidelines. Even if the authors of this commentary embrace the main ideas around the Golden Rule, which targets to address the “average” situation, they believe that this rule should not be applied automatically. There is no universal extrapolationmethod that can tackle every forecasting problem; nor are there simple rules that automatically apply without reference to the data. Similarly, it is demonstrated that for a specific causal regression model the recommendedconservative rule leads to unnecessary inaccuracy. In this commentary the authors demonstrate, using the power of counter examples, two cases where the Golden Rule fails. Forecasting performance is context dependentand, as such, forecasters (researchers and practitioners) should take into account the specific features of the situation faced.
AB - Armstrong, Green, and Graefe (this issue) propose the Golden Rule in forecasting: “be conservative”. According to the authors, the successful application of the Golden Rule comes through a checklist of 28 guidelines. Even if the authors of this commentary embrace the main ideas around the Golden Rule, which targets to address the “average” situation, they believe that this rule should not be applied automatically. There is no universal extrapolationmethod that can tackle every forecasting problem; nor are there simple rules that automatically apply without reference to the data. Similarly, it is demonstrated that for a specific causal regression model the recommendedconservative rule leads to unnecessary inaccuracy. In this commentary the authors demonstrate, using the power of counter examples, two cases where the Golden Rule fails. Forecasting performance is context dependentand, as such, forecasters (researchers and practitioners) should take into account the specific features of the situation faced.
KW - forecasting
KW - Time series
KW - ARIMA
KW - Regression modelling
KW - Forecasting accuracy
KW - model specification
KW - complexity
U2 - 10.1016/j.jbusres.2015.01.059
DO - 10.1016/j.jbusres.2015.01.059
M3 - Journal article
VL - 68
SP - 1742
EP - 1745
JO - Journal of Business Research
JF - Journal of Business Research
SN - 0148-2963
IS - 8
ER -