The Contextual Nature of the Predicitve Power of Statistically-Based Quarterly Earnings Model: Working Paper Series--05-18

Lorek, Kenneth S. and Willinger, G. Lee (2005) The Contextual Nature of the Predicitve Power of Statistically-Based Quarterly Earnings Model: Working Paper Series--05-18. Working Paper. NAU W.A. Franke College of Business.

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Abstract

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 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-a-vis the identification period (1990-1999); 2) reduced levels of earnings persistence for our sample firms relative to earnings persistence factors computed by Baginski et al. (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).

Item Type:	Monograph (Working Paper)
Publisher’s Statement:	Copyright, where appropriate, is held by the author.
ID number or DOI:	05-18
Keywords:	Working paper, quarterly earnings models, comparing predictive power
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 20:52
URI:	http://openknowledge.nau.edu/id/eprint/1559

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