How to Dominate the Historical Average
提出一种新的样本外预测股票溢价的方法，其斜率系数为保守常数，偏差低于历史均值但方差相同，理论和实证均显示预测表现优于历史均值。
Abstract We present a novel methodology for the out-of-sample forecast of the equity premium. Our predictive slope coefficient is a conservative constant that has a lower bias than the zero slope employed by the historical average, but has the same variance. We demonstrate that, theoretically and empirically, our method dominates the historical average in forecast performance. Our methodology establishes a simple yet powerful paradigm for exploiting the real-time equity premium predictability derived from a predictor. Applications of our method reveal that many predictors can forecast the equity premium, and that parameter estimates in previous studies add value to out-of-sample forecasts.