Analysts earnings forecasts: An alternative data source for failure prediction

Abstract

This study investigates four properties of earnings forecasts made by financial analysts to determine if systematic differences in these properties exists failing and healthy firms. The four properties are: The level of forecasts, forecast error, forecast bias, and forecast dispersion. Measures reflecting the four properties are used in models to distinguish failing and healthy firms and predict future bankruptcy. Results indicate that measures developed from analysts forecasts of future earnings can be exploited to distinguish failing from healthy firms