Predicting Individual Analyst Earnings Forecasts
提出并检验了一个模型，利用其他分析师共识预测的变化、当前预测与共识的偏差以及累计股票回报，来预测分析师对每股收益的个人预测，发现这三个变量能解释约38%的预测修订变化。
In this study I propose and test a model that predicts individual analyst forecasts of corporate earnings per share (EPS) using the change in the mean consensus forecast of other analysts since the date of the analyst's current outstanding forecast; the deviation of the analyst's current forecast from the consensus forecast; and cumulative stock returns since the date of the analyst's current forecast. I find that these three variables explain about 38% of the variability in analyst forecast revisions. While there is evidence of a relation between changes in earnings expectations and price changes, virtually all of the explanatory power of my model arises from other analyst forecasts. Section 2 describes the data bases used and the sample selection process. Section 3 presents the model and method for predicting individual analyst forecasts. Section 4 reports the bias and accuracy of the predicted forecasts. Conclusions are in section 5.