Forecast Aggregation and Predictive Value
研究了通过平均分析师个人盈余预测形成共识预测如何提升预测价值，发现均值共识预测比个人预测具有更高的公司特定盈余反应系数，这归因于更丰富的信息集和个体误差的减少。
Investors find predictive value in analysts’ individual and consensus earnings forecasts. Although aggregating individual forecasts into consensus forecasts is an established practice, it is not self-evident why the practice of forecast aggregation exists. Theoretically, forecast aggregation is beneficial because it provides richer information and reduces idiosyncratic errors. This article examines how forecast aggregation through averaging analysts’ individual earnings forecasts increases the predictive value of these forecasts. On average, mean consensus forecasts result in higher firm-specific earnings response coefficients than individual analysts’ earnings forecasts. The aggregation of richer information sets and the reduction in idiosyncratic errors account for the increased forecast predictive value. These results rationalize the practice of forecast aggregation and highlight the roles of analysts’ earnings forecast quantity and quality in the way that forecast aggregation can effectively boost the predictive value of forecast information.