Analysts' forecasts as earnings expectations |
| |
| Institution: | 1. University of California, Irvine, Irvine, CA, 92697, USA;2. University of Southern California, Los Angeles, CA, 90089, USA;1. Nanyang Business School, Nanyang Technological University, Singapore 639798, Singapore;2. College of Economics, Shenzhen University, China;3. Center for Finance and Accounting Research, Shenzhen University, China;4. Department of Finance and Insurance, Lingnan University, Hong Kong;5. Advisory Services, Ernst & Young LLP, USA;1. Carroll School of Management, Boston College, USA;2. J. M. Tull School of Accounting, Terry College of Business, University of Georgia, USA;3. Graduate School of Business, Stanford University, USA |
| |
| Abstract: | I examine three composite analyst forecast of earnings per share as proxies for expected earnings. The most current forecast weakly dominates the mean and median forecasts in accuracy. This is evidence that forecast dates are more relevant for determining accuracy than individual error. Consistent with previous research, I find analysts more accurate than time-series models. However prior knowledge of forecast errors from a quarterly autoregressive model predicts excess stock returns better than prior knowledge of analysts' errors. This is inconsistent with previous research, and is anomalous given analysts' greater accuracy. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
