This dissertation addresses the prediction of corporate earnings. The thesis aims to examine whether the degree of precision in earnings forecasts can be increased by basing them on historical financial ratios. Furthermore, the intent of the dissertation is to analyze whether accounting standards affect the accuracy of analysts’ earnings forecasts. Finally, the objective of the dissertation is to investigate how the stock market is affected by the accuracy of corporate earnings projections. The dissertation contributes to a deeper understanding of these issues. First, it is shown how earnings forecasts can be generated based on historical timeseries patterns of financial ratios. This is done by modeling the return on equity and the growth-rate in equity as two separate but correlated timeseries processes which converge to a long-term, constant level. Empirical results suggest that these earnings forecasts are not more accurate than the simpler forecasts based on a historical timeseries of earnings. Secondly, the dissertation shows how accounting standards affect analysts’ earnings predictions. Accounting conservatism contributes to a more volatile earnings process, which lowers the accuracy of analysts’ earnings forecasts. Furthermore, the dissertation shows how the stock market’s reaction to the disclosure of information about corporate earnings depends on how well corporate earnings can be predicted. The dissertation indicates that the stock market’s reaction to the disclosure of earnings information is stronger for firms whose earnings can be predicted with higher accuracy than it is for firms whose earnings can not be predicted with the same degree of accuracy.