Analysts versus time-series forecasts of quarterly earnings: A maintained hypothesis revisited

Donald P. Pagach and Richard S. Warr

Advances in accounting, 2020, vol. 51, issue C

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.

Keywords: Analysts' quarterly EPS forecasts; ARIMA models; Maintained hypothesis; Expectation models (search for similar items in EconPapers)
JEL-codes: G17 M40 M41 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0882611020300675
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:advacc:v:51:y:2020:i:c:s0882611020300675

DOI: 10.1016/j.adiac.2020.100497

Access Statistics for this article

Advances in accounting is currently edited by Dennis Caplan

More articles in Advances in accounting from Elsevier
Bibliographic data for series maintained by Catherine Liu ().