This article presents information on a study to examine the reliability of published predictions of future earnings. Reliability was examined by comparing predicted earnings with actual earnings for the same period. Reliability in this study was based on the degree of agreement between predicted earnings and actual earnings. Therefore, "reliability" was not used in the sense of declaring predicted earnings reliable or unreliable, but was used in the sense of the degree of closeness to being right. The study was restricted to examining the reliability of earnings predictions that could be included in the annual financial statements. Therefore, the first data requirement was that the earnings predictions be published in the Wall Street Journal within such a time period that the predictions could also be in the annual financial statements for the previous year. The Securities and Exchange Commission requires that annual reports of listed companies be issued no later than 120 days after the end of a firm's fiscal year.

This article reports the results of an empirical study which has bearing upon issues of the accuracy of management forecasts of income in particular and the time series properties of earnings data. From the standpoint of whether corporate forecasts of earnings should be disclosed, the question of accuracy is relevant. This article utilizes the Box-Jenkins methodology in the determination of the most appropriate time series model for each firm in the sample. The proposition that management forecasts of income should prove fairly accurate is not supported by the results of this study. In cases in which management forecasts proved reasonably accurate, overall they were not more so than those generated from the time series models. It remains possible that the management forecasts may contain additional information regarding risk or return. For example, market participants may use management forecasts and time series analysis. With respect to the time series properties of quarterly earnings, the results clearly demonstrate the significance of seasonality in quarterly earnings.