Approximating Fixed‐Horizon Forecasts Using Fixed‐Event Forecasts
针对调查中固定事件预测的季节性，提出一种通过最小化均方近似误差来优化加权平均的方法，以更准确地近似固定期限预测，实证显示优于传统方法。
ABSTRACT Many forecast surveys ask their participants for fixed‐event forecasts. As fixed‐event forecasts have seasonal properties, users often employ an ad hoc approach to approximate fixed‐horizon forecasts based on these fixed‐event forecasts. We derive an optimal approximation for fixed‐horizon forecasts by minimizing the mean‐squared approximation error. Like the ad hoc approach, our approximation employs a weighted average of the fixed‐event forecasts. The optimal weights tend to differ substantially from those of the ad hoc approach. In empirical applications, the gains from using optimal instead of ad hoc weights turn out to be sizeable. The approximation approach proposed can also be useful in other applications.