Tweets and Trades: The Information Content of Stock Microblogs

89 Pages Posted: 6 Nov 2010 Last revised: 10 Aug 2014

Timm O. Sprenger

Technische Universität München (TUM) - School of Management

Isabell M. Welpe

Technische Universität München (TUM) - School of Management

Multiple version iconThere are 2 versions of this paper

Date Written: November 1, 2010

Abstract

Microblogging forums have become a vibrant online platform to exchange trading ideas and other stock-related information. Using methods from computational linguistics, we analyze roughly 250,000 stock-related microblogging messages, so-called tweets, on a daily basis. We find the sentiment (i.e., bullishness) of tweets to be associated with abnormal stock returns and message volume to predict next-day trading volume. In addition, we analyze the mechanism leading to efficient aggregation of information in microblogging forums. Our results demonstrate that users providing above average investment advice are retweeted (i.e., quoted) more often and have more followers, which amplifies their share of voice in microblogging forums.

Keywords: Twitter, Microblogging, Stock Market, Investor Sentiment, Text Classification, Computational Linguistics

JEL Classification: G12, G14

Suggested Citation

Sprenger, Timm O. and Welpe, Isabell M., Tweets and Trades: The Information Content of Stock Microblogs (November 1, 2010). Available at SSRN: https://ssrn.com/abstract=1702854 or http://dx.doi.org/10.2139/ssrn.1702854

Timm O. Sprenger (Contact Author)

Technische Universität München (TUM) - School of Management ( email )

Arcisstrasse 21
Munich, 80333
Germany
+49-(0)89-289-24800 (Phone)
+49-(0)89-289-24805 (Fax)

HOME PAGE: http://www.strategie.wi.tum.de

Isabell M. Welpe

Technische Universität München (TUM) - School of Management ( email )

Leopoldstrasse 139
Munich, 80804
Germany
++49/89/289-24800 (Phone)
++49/89/289-24805 (Fax)

HOME PAGE: http://www.strategie.wi.tum.de

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