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The Prediction of Earnings Movements Using Accounting Data: Using XBRL

Amos Baranes and Rimona Palas

The usefulness of accounting information as a basis for a profitable investment strategy is an important issue. The objective of this study is to repeat the original Ou et al. study using the XBRL database, standardized financial reporting system required by the SEC. The study analyzes XBRL quarterly data, from the first quarter of 2011 to the fourth quarter of 2015, using a two-step Logit regression model to determine the variables to be included in the prediction model. The prediction model was then used to arrive at the probability of the directional movement of earnings between the current quarter and the subsequent quarter. The results of the final models' indicated a significant ability to predict subsequent earnings changes. The predictions appear to be correct on average about 72.4% of the time. However, these forecasts were not able to provide a basis for a profitable investment strategy.