Bathke, Allen W. and Lorek, Kenneth S. and Willinger, G. Lee (2005) Modeling of Nonseasonal Quarterly Earnings Data: Working Paper Series--05-17. Working Paper. NAU W.A. Franke College of Business.
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Abstract
We present new empirical evidence on the predictive power of statistically-based quarterly earnings expectation models for firms which exhibit nonseasonal quarterly earnings patterns. In marked contrast to extant work we find: 1) a considerably greater frequency of nonseasonal firms (36%) when compared to Lorek and Bathke (1984) (12%) and Brown and Han (2000) (17%), 2) the random walk model (RW) provides significantly more accurate pooled, one-step ahead quarterly earnings predictions across 40 quarters in the 1994-2003 holdout period than the first-order autoregressive model (AR1) popularized by Lorek and Bathke and Brown and Han, and 3) the RW model provides significantly more accurate quarterly earnings predictions for large nonseasonal firms than smaller nonseasonal firms. The latter finding documents a size-effect with respect to predictive ability for nonseasonal firms similar to that evidenced for seasonal firms. These findings are particularly salient to researchers in search of efficient statistically-based quarterly earnings expectation models since 129 of 296 (43.6%) sample firms are not covered by security analysts.
| Item Type: | Monograph (Working Paper) |
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| Publisher’s Statement: | Copyright, where appropriate, is held by the author. |
| ID number or DOI: | 05-17 |
| Keywords: | Working paper, nonseasonal quarterly earnings, predictive ability, ARIMA modeling |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HF Commerce |
| NAU Depositing Author Academic Status: | Faculty/Staff |
| Department/Unit: | The W.A. Franke College of Business |
| Date Deposited: | 19 Oct 2015 20:53 |
| URI: | http://openknowledge.nau.edu/id/eprint/1560 |
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