| Author(s) | Mohamad Taiseer AI-Ragby |
| Affiliation | Assic~tant Professor, Department (if Accountancy, Amman Private University, Jordan |
| Title | Predicting Net Income, Earnings Per Share and Dividends: An Empirical Study |
| Source | Journal of King Saud University. Administrative Sciences. Volume 12, No 2. (2000/1420) |
| Abstract | This study investigates the predictive ability of three naive models in predicting earnings for 68 Jor-danian public c-ompanies listed in Amman financial market. These models are: Random walk (RW), random walk plus constant (RWC), and random walk plus identical change (RWIC). The main results are: (i) The RW and RWC models seem to be superior predictors of net income before taxes sample wide, while the RWC per-forms better in predicting dividends and net income after taxes. Finally, the RWIC came out first in predicting eall1ings per share. (ii) With respect to economic sectors, the RW is ranked first in 10 out of 16 cases represent-ing four economic sectors and four variables. (iii) RW is the better predictor at the firm level. |
