Generating Abnormal Returns Using Crowdsourced Earnings Forecasts from Estimize

In our paper, "Generating Abnormal Returns Using Crowdsourced Earnings Forecasts From Estimize" we examine consensus EPS and Revenue forecasts derived from the crowdsourced community Estimize, and find that they are more accurate than traditional Wall Street equity analysts' consensus forecasts. We then design a profitable strategy which trades on earnings surprises as benchmarked against Estimize. Finally, we demonstrate that a strategy which exploits the differences between the Wall Street and Estimize expectations prior to earnings dates earns excess returns, particularly among large cap stocks