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Analysts’ forecasts timeliness and accuracy post-XBRL

Sherwood Lane Lambert (Department of Accounting and Finance, University of West Florida, Pensacola, Florida, USA)
Kevin Krieger (Department of Accounting and Finance, University of West Florida, Pensacola, Florida, USA)
Nathan Mauck (University of Missouri-Kansas City, Kansas City, Missouri, USA)

International Journal of Accounting & Information Management

ISSN: 1834-7649

Article publication date: 4 March 2019

500

Abstract

Purpose

To the authors’ knowledge, this paper is the first to use Detail I/B/E/S to study directly the timeliness of security analysts’ next-year earnings-per-share (EPS) estimates relative to the SEC filings of annual (10-K) and quarterly (10-Q) financial statements. Although the authors do not prove a causal relationship, they provide evidence that the average time from firms’ filings of 10-Ks and 10-Qs to the release of analysts’ annual EPS forecasts during short timeframes (for example, 15-day timeframe from a 10-K’s SEC file date) subsequent to the 10-K and 10-Q filing dates significantly shortened with XBRL implementation and then remained relatively constant following implementation.

Design/methodology/approach

Using filing dates hand-collected from the SEC website for 10-Ks during 2009-2011 and filing dates for 10-Ks and 10-Qs during 2003-2014 input from Compustat along with analysts’ estimated values for next year EPS, actual estimated next year EPS realized and estimate announcement dates in Detail I/B/E/S, the authors study the days from 10-K and 10-Q file dates to announcement dates and the per cent errors for individual estimates during per- and post-XBRL eras.

Findings

The authors find that analysts are announcing next-year EPS forecasts significantly more frequently and in significantly shorter time in zero to 15 days immediately following 10-K and 10-Q file dates post-XBRL as compared to pre-XBRL. However, the authors do not find a significant change in forecast accuracy post-XBRL as compared to pre-XBRL.

Research limitations/implications

Because this study uses short timeframes immediately following the events (filings of 10-Ks and 10-Qs), the relationship between 10-Ks and 10-Qs with and without XBRL and improved forecast timeliness is strengthened. However, even this strengthened difference-in-difference methodology does not establish causality. Future research may determine whether XBRL or other factors cause the improved forecast timeliness the authors’ evidence.

Practical implications

This improved efficiency may become critical if financial statement reporting expands as a result of new innovations such as Big Data and continuous reporting. In the future, users may be able to electronically connect to financial statement data that firms are maintaining on a perpetual basis on the SEC website and continuously monitor and analyze the financial statement data dynamically in real time. If so, then unquestionably, XBRL will have played a critical role in bringing about this future innovation.

Originality/value

Whereas previous studies have utilized Summary IBES data to assess the impact of XBRL on analyst forecasts, the authors use Detail IBES to study the effects of XBRL adoption directly by measuring days from 10-K and 10-Q file dates in Compustat to each estimate’s announcement date recorded in IBES and by computing the per cent error using each estimate’s VALUE and ACTUAL recorded in Detail IBES. The authors are the first to evidence a significant shortening in average days and an increase in per cent of 30-day counts in the zero- to 15-day timeframe immediately following the fillings of 10-K s and 10-Qs.

Keywords

Acknowledgements

A draft version of this paper won the “Best Paper of the Conference” award at the 2016 American Accounting Association (AAA) Southeast Regional Conference.

Citation

Lambert, S.L., Krieger, K. and Mauck, N. (2019), "Analysts’ forecasts timeliness and accuracy post-XBRL", International Journal of Accounting & Information Management, Vol. 27 No. 1, pp. 151-188. https://doi.org/10.1108/IJAIM-05-2017-0061

Publisher

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Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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