Assessing point forecast accuracy by stochastic error distance
提出基于预测误差累积分布函数与单位阶跃函数距离的点预测精度度量（随机误差距离），并证明所有标准损失函数均可表示为加权随机误差距离，从而建议关注条件中位数预测而非条件均值预测。
We propose point forecast accuracy measures based directly on distance of the forecast-error c.d.f. from the unit step function at 0 (“stochastic error distance,” or SED). We provide a precise characterization of the relationship between SED and standard predictive loss functions, and we show that all such loss functions can be written as weighted SEDs. The leading case is absolute error loss. Among other things, this suggests shifting attention away from conditional-mean forecasts and toward conditional-median forecasts.