caa a22 4500 463187563 CHVBK 20180406164858.0 cr unu---uuuuu 170326e20070101xx s 000 0 eng 10.1007/s11156-006-0001-z doi (NATIONALLICENCE)springer-10.1007/s11156-006-0001-z The contextual nature of the predictive power of statistically-based quarterly earnings models [Elektronische Daten] [Kenneth Lorek, G. Willinger] We present new empirical evidence on the contextual nature of the predictive power of five statistically-based quarterly earnings expectation models evaluated on a holdout period spanning the twelve quarters from 2000-2002. In marked contrast to extant time-series work, the random walk with drift (RWD) model provides significantly more accurate pooled, one-step-ahead quarterly earnings predictions for a sample of high-technology firms (n = 202). In similar predictive comparisons, the Griffin-Watts (GW) ARIMA model provides significantly more accurate quarterly earnings predictions for a sample of regulated firms (n = 218). Finally, the RWD and GW ARIMA models jointly dominate the other expectation models (i.e., seasonal random walk with drift, the Brown-Rozeff (BR) and Foster (F) ARIMA models) for a default sample of firms (n = 796). We provide supplementary analyses that document the: (1) increased frequency of the number of loss quarters experienced by our sample firms in the holdout period (2000-2002) vis-à-vis the identification period (1990-1999); (2) reduced levels of earnings persistence for our sample firms relative to earnings persistence factors computed by Baginski etal. (2003) during earlier time periods (1970s-1980s); (3) relative impact on the predictive ability of the five expectation models conditioned upon the extent of analyst coverage of sample firms (i.e., no coverage, moderate coverage, and extensive coverage); and (4) sensitivity of predictive performance across subsets of regulated firms with the BR ARIMA model providing the most accurate predictions for utilities (n = 87) while the RWD model is superior for financial institutions (n = 131). Springer Science+Business Media, LLC, 2006 Lorek Kenneth College of Business Administration, Northern Arizona University, P.O. Box 15066, 86011-5066, Flagstaff, AZ, USA aut Willinger G. Price College of Business, University of Oklahoma, 73019, Norman, OK, USA aut Review of Quantitative Finance and Accounting Kluwer Academic Publishers-Plenum Publishers; http://www.springer-ny.com 28/1(2007-01-01), 1-22 0924-865X 28:1<1 2007 28 11156 https://doi.org/10.1007/s11156-006-0001-z text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11156-006-0001-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Lorek Kenneth College of Business Administration, Northern Arizona University, P.O. Box 15066, 86011-5066, Flagstaff, AZ, USA aut NATIONALLICENCE 700 1- Willinger G. Price College of Business, University of Oklahoma, 73019, Norman, OK, USA aut NATIONALLICENCE 773 0- Review of Quantitative Finance and Accounting Kluwer Academic Publishers-Plenum Publishers; http://www.springer-ny.com 28/1(2007-01-01), 1-22 0924-865X 28:1<1 2007 28 11156 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer