The Value of Crowdsourced Earnings Forecasts
研究了众包平台Estimize提供的盈利预测的价值，发现其有助于预测盈利和衡量市场预期，且众包规模越大效果越强，修正后的共识预测能带来显著回报。
ABSTRACT Crowdsourcing—when a task normally performed by employees is outsourced to a large network of people via an open call—is making inroads into the investment research industry. We shed light on this new phenomenon by examining the value of crowdsourced earnings forecasts. Our sample includes 51,012 forecasts provided by Estimize, an open platform that solicits and reports forecasts from over 3,000 contributors. We find that Estimize forecasts are incrementally useful in forecasting earnings and measuring the market's expectations of earnings. Our results are stronger when the number of Estimize contributors is larger, consistent with the benefits of crowdsourcing increasing with the size of the crowd. Finally, Estimize consensus revisions generate significant two‐day size‐adjusted returns. The combined evidence suggests that crowdsourced forecasts are a useful supplementary source of information in capital markets.