地方信息优势与股票回报:来自社交媒体的证据†

IF 3.2 3区 管理学 Q1 BUSINESS, FINANCE Contemporary Accounting Research Pub Date : 2024-01-30 DOI:10.1111/1911-3846.12935
Yuqin Huang, Feng Li, Tong Li, Tse-Chun Lin
{"title":"地方信息优势与股票回报:来自社交媒体的证据†","authors":"Yuqin Huang,&nbsp;Feng Li,&nbsp;Tong Li,&nbsp;Tse-Chun Lin","doi":"10.1111/1911-3846.12935","DOIUrl":null,"url":null,"abstract":"<p>We examine the information asymmetry between local and nonlocal investors with a large dataset of stock message board postings. We document that abnormal relative postings of a firm, that is, unusual changes in the volume of postings from local versus nonlocal investors, capture locals' information advantage. This measure positively predicts firms' short-term stock returns as well as those of peer firms in the same city. Sentiment analysis shows that posting activities primarily reflect good news, potentially due to social transmission bias and short-sales constraints. We identify the information driving return predictability through content-based analysis. Abnormal relative postings also lead analysts' forecast revisions. Overall, investors' interactions on social media contain valuable geography-based private information.</p>","PeriodicalId":10595,"journal":{"name":"Contemporary Accounting Research","volume":"41 2","pages":"1089-1119"},"PeriodicalIF":3.2000,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Local information advantage and stock returns: Evidence from social media\",\"authors\":\"Yuqin Huang,&nbsp;Feng Li,&nbsp;Tong Li,&nbsp;Tse-Chun Lin\",\"doi\":\"10.1111/1911-3846.12935\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>We examine the information asymmetry between local and nonlocal investors with a large dataset of stock message board postings. We document that abnormal relative postings of a firm, that is, unusual changes in the volume of postings from local versus nonlocal investors, capture locals' information advantage. This measure positively predicts firms' short-term stock returns as well as those of peer firms in the same city. Sentiment analysis shows that posting activities primarily reflect good news, potentially due to social transmission bias and short-sales constraints. We identify the information driving return predictability through content-based analysis. Abnormal relative postings also lead analysts' forecast revisions. Overall, investors' interactions on social media contain valuable geography-based private information.</p>\",\"PeriodicalId\":10595,\"journal\":{\"name\":\"Contemporary Accounting Research\",\"volume\":\"41 2\",\"pages\":\"1089-1119\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-01-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Contemporary Accounting Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/1911-3846.12935\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contemporary Accounting Research","FirstCategoryId":"91","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1911-3846.12935","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0

摘要

我们利用股票留言板发帖的大型数据集研究了本地和非本地投资者之间的信息不对称问题。我们发现,公司的异常相对发帖量(即本地投资者与非本地投资者发帖量的异常变化)能反映本地投资者的信息优势。这一指标可以积极预测公司的短期股票回报以及同城同行公司的股票回报。情绪分析表明,发帖活动主要反映的是好消息,这可能是由于社会传播偏差和卖空限制造成的。我们通过基于内容的分析确定了驱动回报可预测性的信息。异常的相对发帖也会导致分析师的预测修正。总体而言,投资者在社交媒体上的互动包含有价值的基于地理位置的私人信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Local information advantage and stock returns: Evidence from social media

We examine the information asymmetry between local and nonlocal investors with a large dataset of stock message board postings. We document that abnormal relative postings of a firm, that is, unusual changes in the volume of postings from local versus nonlocal investors, capture locals' information advantage. This measure positively predicts firms' short-term stock returns as well as those of peer firms in the same city. Sentiment analysis shows that posting activities primarily reflect good news, potentially due to social transmission bias and short-sales constraints. We identify the information driving return predictability through content-based analysis. Abnormal relative postings also lead analysts' forecast revisions. Overall, investors' interactions on social media contain valuable geography-based private information.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
6.20
自引率
11.10%
发文量
97
期刊介绍: Contemporary Accounting Research (CAR) is the premiere research journal of the Canadian Academic Accounting Association, which publishes leading- edge research that contributes to our understanding of all aspects of accounting"s role within organizations, markets or society. Canadian based, increasingly global in scope, CAR seeks to reflect the geographical and intellectual diversity in accounting research. To accomplish this, CAR will continue to publish in its traditional areas of excellence, while seeking to more fully represent other research streams in its pages, so as to continue and expand its tradition of excellence.
期刊最新文献
Performance effects of insulating and non-insulating cost allocations in stable and unstable production environments Leader versus lagger: How the timing of financial reports affects audit quality and investment efficiency Bank audit committee financial expertise and timely loan loss recognition CAR 2024 Reviewer Recognition Program / Programme de reconnaissance des réviseurs 2024 de RCC Control issues: How providing input affects auditors' reliance on artificial intelligence
×
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