Analysts' forecasts between last consensus and earning announcement date. Issue 4 (16th November 2020)

• Record Type: Journal Article
• Authors: Zhang, Weiqi; Ha, Huong; Gay, Hui Ting Evelyn
• Is Part Of: Journal of financial reporting & accounting. Volume 18:Issue 4(2020)
• Page Start: 779
• Page End: 793
• Publication Date: 2020-11-16
• Subjects: Forecast -- Last consensus calculation date -- Earnings announcement date -- Thomson financial database -- Consensus calculation date -- Earnings announcement date; Finance -- Research -- Periodicals; Accounting -- Research -- Periodicals; 657.3
• DOI: 10.1108/JFRA-04-2020-0102
• Languages: English
• ISSNs: 1985-2517

Abstract

Abstract : Purpose: Thomson financial database reports a monthly consensus measure of analysts' forecasts in the third week of every month, and firms' earnings announcement dates are usually different from the last consensus calculation date. Thus, there is a gap between the last consensus calculation date and the earnings announcement date of firms. This study aims to address the question: "Do analysts issue forecasts that are slightly higher than the consensus number to increase the accuracy of their forecasts?" Design/methodology/approach: This study is based on a sample of 91, 172 quarterly earnings forecasts of various firms from 1990 to 2007 made between the last consensus calculation date and quarterly earnings announcement date. Descriptive statistics and statistical tests were used to analyze the data. Findings: The findings propose that contrary to expectation, analysts' forecasts between the last consensus calculation date and earnings announcement date are smaller than the consensus number. Also, the forecasts made between the last consensus and earnings announcement date is not as informative as forecasts made at other times as they could merely reflect the analysts' herding behavior resulting from their career concerns. Originality/value: This study provides a link between the literature that studies firms' meet or beat analysts' earnings phenomenon and analysts' forecast decision-making context. This study also provides useful implications for the literature on the information content of analysts' forecasts.