讲座题目：How do individual investors’ talks online move the market? Evidence on sentiment-induced correlated trading of different traders

讲座时间：2022年10月27日（星期四）下午15:00-16:30

讲座方式：腾讯会议ID：174-149-015

密码：221027

讲座链接：https://meeting.tencent.com/dm/Gv4pHWNjmOhr

主讲人：部慧，博士，北京航空航天大学经济管理学院金融系，副教授，博士生导师。2004年7月于中国科学技术大学获得经济学学士学位，2009年7月于中国科学院研究生院管理学院获得管理科学与工程博士学位。研究领域涉及实证资产定价、金融市场、风险管理、金融科技和监管科技等。已主持了国家自然科学基金项目4项，主持或参与多项省部级和横向课题。已发表学术论文近40篇，包括《International Journal of Forecasting》、《Economic Modelling》、《管理科学学报》、《系统工程理论与实践》、《中国管理科学》、《管理评论》等；已出版1本教材和2本专著。曾作为主要成员参与撰写了多篇政策研究报告上报中央两办和部委等，多份报告获得领导批示或被中办采纳，支撑了相关金融监管政策的推出。主持研发了4套金融监管系统；并曾参与业界风险管理系统的研发。已获授权技术发明专利4项，并有多项专利在审。曾参与研发和创新多个金融产品，包括大宗商品指数及其指数类衍生品和投资基金等。曾获得北京航空航天大学优秀教学成果奖一等奖1项，国际会议优秀论文奖5项，教学案例获奖1项。兼任中国系统工程学会金融系统工程专业委员会的理事、中国工业与应用数学学会金融数学、金融工程与精算专业委员会的青年专业委员会的金融工程方向的委员；兼任国内外20余本期刊的审稿人。

讲座简介：How institutional investors respond to individual investor sentiment and whether investor sentiment is priced are important research questions in asset pricing and behavior finance. This study explores the trading responses of different traders to firm-level investor sentiment and the effects of investor sentiment on cross-sectional stock returns from the perspective of return comovement and correlated trading. We extract the investors’ expectations about future returns directly from the online messages posted on the internet stock message boards of Eastmoney.com in China and construct the firm-level monthly investor sentiment indicators for the CSI300 Index constituent stocks from June 2009 to September 2016. We find that this investor sentiment indicator is a good proxy for noise trader risk and it has predictive power for stock returns. We propose a proxy for noise trader risk. We uncover several important empirical findings about the effects of investor sentiment. First, we confirm the existence of sentiment-induced return comovement. Second, we reveal that sentiment-induced correlated trading exists not only for small trades but also for large trades by using tick-by-tick quotation and transaction data. Third, we also find evidence of different trading responses of mutual funds to individual investors’ sentiments. Our study proposes that the differences in institutional investors’ trading responses may be related to their different views on whether investor sentiment has informative content and the condition of noise trader risk.