Investor Sentiment from Internet Message Postings and Predictability of Stock Returns

52 Pages Posted: 12 Apr 2014 Last revised: 10 Dec 2014

See all articles by Soon-Ho Kim

Soon-Ho Kim

Korea University Business School (KUBS)

Dongcheol Kim

Korea University Business School

Date Written: April 11, 2014

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

JEL Classification: G10, G14

Suggested Citation

Kim, Soon-Ho and Kim, Dongcheol, Investor Sentiment from Internet Message Postings and Predictability of Stock Returns (April 11, 2014). Available at SSRN: https://ssrn.com/abstract=2423752 or http://dx.doi.org/10.2139/ssrn.2423752

Soon-Ho Kim

Korea University Business School (KUBS) ( email )

Anam-Dong, Seongbuk-Gu
Seoul 136-701, 136701
Korea

Dongcheol Kim (Contact Author)

Korea University Business School ( email )

Anam-Dong, Seongbuk-Gu
Seoul 136-701, 136701
Korea
+82-2-3290-2606 (Phone)

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