The Prediction of Earnings Movements Using Accounting Data: Using XBRLAmos Baranes1* and Rimona Palas2
- *Corresponding Author:
- Baranes A
Peres Academic Center
8 HaNeviim St, POB 328
Rehovot, Israel 76120
E-mail: [email protected]
Received Date: November 10, 2016; Accepted Date: November 28, 2016; Published Date: December 08, 2016
Citation: Baranes A, Palas R (2016) The Prediction of Earnings Movements Using Accounting Data: Using XBRL. Int J Account Res 5:143. doi:10.4172/2472- 114X.1000143
Copyright: © 2016 Baranes A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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.