Analyst Information Acquisition via EDGAR

Brian Gibbons, P. Iliev, J. Kalodimos
{"title":"Analyst Information Acquisition via EDGAR","authors":"Brian Gibbons, P. Iliev, J. Kalodimos","doi":"10.2139/ssrn.3112761","DOIUrl":null,"url":null,"abstract":"We identify analysts’ information acquisition patterns by linking EDGAR (Electronic Data Gathering, Analysis, and Retrieval) server activity to analysts’ brokerage houses. Analysts rely on EDGAR in 24% of their estimate updates with an average of eight filings viewed. We document that analysts’ attention to public information is driven by the demand for information and the analysts’ incentives and career concerns. We find that information acquisition via EDGAR is associated with a significant reduction in analysts’ forecasting error relative to their peers. This relationship is likewise present when we focus on the intensity of analyst research. Attention to public information further enables analysts to provide forecasts for more time periods and more financial metrics. Informed recommendation updates are associated with substantial and persistent abnormal returns, even when the analyst accesses historical filings. Analysts’ use of EDGAR is associated with longer and more informative analysis within recommendation reports. This paper was accepted by Shiva Rajgopal, accounting.","PeriodicalId":8737,"journal":{"name":"Behavioral & Experimental Accounting eJournal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"60","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Behavioral & Experimental Accounting eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3112761","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 60

Abstract

We identify analysts’ information acquisition patterns by linking EDGAR (Electronic Data Gathering, Analysis, and Retrieval) server activity to analysts’ brokerage houses. Analysts rely on EDGAR in 24% of their estimate updates with an average of eight filings viewed. We document that analysts’ attention to public information is driven by the demand for information and the analysts’ incentives and career concerns. We find that information acquisition via EDGAR is associated with a significant reduction in analysts’ forecasting error relative to their peers. This relationship is likewise present when we focus on the intensity of analyst research. Attention to public information further enables analysts to provide forecasts for more time periods and more financial metrics. Informed recommendation updates are associated with substantial and persistent abnormal returns, even when the analyst accesses historical filings. Analysts’ use of EDGAR is associated with longer and more informative analysis within recommendation reports. This paper was accepted by Shiva Rajgopal, accounting.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过EDGAR获取分析师信息
我们通过将EDGAR(电子数据收集、分析和检索)服务器活动链接到分析师的经纪公司来识别分析师的信息获取模式。分析师在24%的预测更新中依赖于EDGAR,平均查看8份文件。我们发现,分析师对公共信息的关注是由信息需求、分析师的激励和职业关注驱动的。我们发现,通过EDGAR获取信息与分析师预测误差相对于同行的显著减少有关。当我们关注分析师研究的强度时,这种关系也同样存在。对公共信息的关注进一步使分析师能够提供更多时间段和更多财务指标的预测。明智的建议更新与大量和持续的异常回报相关联,即使分析师访问历史文件也是如此。分析师使用EDGAR与推荐报告中更长的、信息更丰富的分析相关。这篇论文被会计Shiva Rajgopal接受。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Don’t shoot yourself in the foot! A (real-effort task) experiment on income redistribution and voting. Causal Attribution, Benefits Sharing, and Earnings Management Sleep Debt and Information Processing in Financial Markets Game Changer: Can Modifications to Audit Firm Communication Improve Auditors’ Actions in Response to Heightened Fraud Risk? Retail Bond Investors and Credit Ratings
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1