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投资者“听话听音”能获得超额收益吗?——从中国上市公司投资者电话交流会中高管声音情绪视角出发
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TitleCan Investor listen to the voice and get excess return?  
作者刘莉亚 陈瑞华 闵敏 朱小能  
AuthorLiu Liya, Chen Ruihua , Min Min and Zhu Xiaoneng  
作者单位上海财经大学金融学院 
Organization School of Finance, Shanghai University of Finance and Economics; Shanghai Key Laboratory of Financial Information Technology 
作者Emailliuliya@mail.shufe.edu.cn;liuliya0112@163.com;rex@163.sufe.edu.cn; mmin@mail.shufe.edu.cn; zhu.xiaoneng@mail.shufe.edu.cn 
中文关键词自愿信息披露 大数据 电话会议 声音 情绪 
Key WordsVoluntary Disclosure; Big Data; Conference Call; Voice, Sentiment 
内容提要心理学研究认为,声音、面部表情和姿势是人们交流时信息传递的重要渠道。那么在资本市场中,投资者能否捕捉到声音这一传递渠道中所蕴含的重要信息呢?基于此,本文收集了2013-2016年中国上市公司召开投资者电话交流会的相关音频文件,首次识别出高管的声音情绪,并对声音在资本市场信息传导中的作用进行了实证研究。研究发现:(1)业绩越好、规模越大、公司治理水平越高的公司越倾向于召开并披露投资者电话交流会。(2)高管的声音情绪在电话交流会的问答环节具有更高的信息含量,并且资本市场对高管的负面声音情绪更为敏感。(3)当公司高管处于高压力状态时,其负面声音情绪蕴含更多信息。本文研究表明电话交流会中高管的声音情绪具有独特的信息含量,投资者“听话听音”能够获得超额收益。本文是对自愿性信息披露研究的丰富和补充,并且为如何在大数据背景下利用声音数据进行研究提供了有益的参考。 
AbstractPsychology literature believed that human voice, facial expressions and the body language play important roles in the information delivery process. If so, can investors in the stock market capture this kinds of information from the voice channel? We collected the investors communication conference call held by China A-share listed companies during 2013-2016, and first recognized the sentiment in the manager’s voice. We examine the incremental informativeness of the manager’s voice sentiment and the corresponding market reaction, we find that (1) firms with higher profitability, larger size and better corporate governance are more likely to hold and publish the investor communication conference call. (2) the manager’s voice sentiments have more information in the Q&A part than presentation part during the conference call. And investors are more sensitive to manager’s negative voice sentiment. (3) manager’s voice sentiment will leak more information when they are under larger pressure. Our find shows that voice channel is non-negligible for the information communication in China’s stock market and manager’s voice sentiment have unique information, investors can use the information contained in the negative voice sentiment to get significant abnormal return. We contribute to the literature of voluntary disclosure and the way how academic study use the multi-dimensional of Big Data—the voice data. 
文章编号WP1345 
登载时间2019-03-11 
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