The Accuracy, Bias and Efficiency of Analysts’ Long Run Earnings Growth Forecasts
评估了分析师对美国公司长期盈利增长预测的准确性、偏差和效率，发现预测准确性极低，甚至不如简单预测零增长的模型，且存在偏差和低效，但主要误差来自随机因素。
This paper evaluates the accuracy, bias and efficiency of analysts’ long run earnings growth forecasts for US companies. It is shown that forecast accuracy is extremely low. Analysts’ long run earnings growth forecasts are less accurate than the forecasts of a naive model in which earnings growth is forecast to be zero. Consistent with their short run and interim forecasts, analysts’ long run forecasts are shown to be both biased and inefficient. Furthermore, there is evidence that analysts do not fully incorporate information about future earnings that is contained in current share prices. However, the bias and inefficiency of analysts’ forecasts contributes very little to their inaccuracy, which is shown to be primarily the result of random error. It is also shown that the performance of analysts’ long run earnings growth forecasts varies substantially both with the characteristics of the company whose earnings are being forecast and of the forecast itself. The most reliable earnings growth forecasts are low forecasts issued for large companies with low price‐earnings ratios and high market‐to‐book ratios.