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Analysts versus time-series forecasts of quarterly earnings: A maintained hypothesis revisited
Institution:1. University of Houston, Clear Lake, United States;2. University of New Mexico, United States;1. University of Alabama at Birmingham, Collat School of Business, 307B Business and Engineering Complex, Birmingham, AL 35294, United States;2. University of Alabama at Birmingham, Collat School of Business, 3011A Business and Engineering Complex, Birmingham, AL 35294, United States;3. Department of Accounting & MIS, University of Delaware, 219 Purnell Hall, Newark, DE 19716, United States;1. Goddard School of Business and Economics, Weber State University, Ogden, UT, United States of America;2. W. P. Carey School of Business, Arizona State University, Tempe, AZ, United States of America;3. Mike Ilitch School of Business, Wayne State University, Detroit, MI, United States of America
Abstract:We re-examine the maintained hypothesis of analysts' quarterly earnings per share (EPS) superiority versus ARIMA time-series forecasts. While our empirical results are consistent with overall analysts' dominance, they suggest a more contextual interpretation of this important relationship. Specifically, we find that for a relatively large number of cases (approximately 40%) ARIMA time-series forecasts of quarterly EPS are equal to or more accurate than consensus analysts' forecasts. Moreover, the percentage of time-series superiority increases: (1) for longer forecast horizons, (2) as firm size decreases, and (3) for high-technology firms. Due to the data demands that ARIMA forecasting requires we also examine using a seasonal random walk (SRW) model that requires only one year of data to create quarterly forecasts. Although the ARIMA time-series model results in a significant reduction in sample size it dominates the SRW model. Our findings support the analyst dominance over time series models but suggest that ARIMA time-series models may provide useful input to researchers seeking quarterly EPS expectation models for certain types of firms.
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