A new measure of earnings forecast uncertainty

• 成果类型: Article
• 署名作者: Sheng, Xuguang; Thevenot, Maya
• 署名单位: State University System of Florida; Florida Atlantic University; American University
• 刊物名称: JOURNAL OF ACCOUNTING & ECONOMICS
• ISSN/ISSBN: 0165-4101
• DOI: 10.1016/j.jacceco.2011.11.001
• 发表日期: 2012
• 关键词: ANALYSTS FORECASTS; cross-section; management; dispersion; opinion

摘要

Relying on the well-established theoretical result that uncertainty has a common and an idiosyncratic component, we propose a new measure of earnings forecast uncertainty as the sum of dispersion among analysts and the variance of mean forecast errors estimated by a GARCH model. The new measure is based on both common and private information available to analysts at the time they make their forecasts. Hence, it alleviates some of the limitations of other commonly used proxies for forecast uncertainty in the literature. Using analysts' earnings forecasts, we find direct evidence of the new measure's superior performance. (C) 2011 Elsevier B.V. All rights reserved.