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...

We describe the challenges of forecasting earnings in a globally interconnected marketplace, and we document inefficient use of information regarding foreign country exposures and expected country GDP growth at the consensus and individual forecast levels. A country's proximity to the US,...

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...

We theorize that accounting systems affect analysts' forecast accuracy through changes in earnings variability. We argue that the matching and historical cost principles reduce earnings variability, and hence, reduce analysts' earnings forecast errors. We also argue that restricting the choice...

An examination of analysts' accuracy in predicting annual earnings for firms reporting losses and firms reporting profits finds that analysts are ten times more accurate in predicting the earnings of profit firms. They have also improved their predictive ability for profit firms since the...

We argue that accounting conservatism makes earnings forecasting difficult by introducing transitory components in reported earnings. These transitory components are likely to be disproportionately represented in firms reporting losses. We show that analysts' mean forecast errors and absolute...