Investor sentiment from internet message postings and the predictability of stock returns

Soon-Ho Kim and Dongcheol Kim

Journal of Economic Behavior & Organization, 2014, vol. 107, issue PB, 708-729

Abstract: By using an extensive dataset of more than 32 million messages on 91 firms posted on the Yahoo! Finance message board over the period January 2005 to December 2010, we examine whether investor sentiment as expressed in posted messages has predictive power for stock returns, volatility, and trading volume. In intertemporal and cross-sectional regression analyses, we find no evidence that investor sentiment forecasts future stock returns either at the aggregate or at the individual firm level. Rather, we find evidence that investor sentiment is positively affected by prior stock price performance. We also find no significant evidence that investor sentiment from Internet postings has predictive power for volatility and trading volume. A distinctive feature of our study is the use of sentiment information explicitly revealed by retail investors as well as classified by a machine learning classification algorithm and a much longer sample period relative to prior studies.

Keywords: Investor sentiment; Return predictability; Internet posting messages; Text classification; Volatility; Trading volume (search for similar items in EconPapers)
JEL-codes: G10 G14 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (99)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jeborg:v:107:y:2014:i:pb:p:708-729

DOI: 10.1016/j.jebo.2014.04.015

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