News or Noise? Internet Postings and Stock Prices

By Robert Tumarkin, Robert F. Whitelaw. 2001

437 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/6515952c416599a00966e9150405a5d22b89e86e

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Citations in the corpus

eInformation: A Clinical Study of Investor Discussion and Sentiment (2005, result): “Our results are consistent with those found by Tumarkin and Whitelaw (2001) and by Antweiler and Frank (2004).”
Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards (2004, background): “Consistent with our results Tumarkin and Whitelaw (2001) find that at daily frequency market activity does help predict message posting levels, and that message posting does not help predict stock returns.”
Widespread Worry and the Stock Market (2010, methodology): “Previous authors have drawn comparisons between internet message boards and individual stock prices, with mixed results (De Choudhury, et al. 2008; Tumarkin and Whitelaw 2001).”
Open source information, investor attention, and asset pricing (2013, result): “In contrast to this anecdotal evidence, Tumarkin and Whitelaw (2001) find that message board activity does not predict the industry-adjusted returns or the abnormal trading volume.”
Tweets and Trades: The Information Content of Stock Microblogs (2010, neutral): “For a limited sample of internet service sector stocks, Tumarkin and Whitelaw (2001) have explored the information embedded in voluntary user ratings (from strong buy to strong sell), but were unable to confirm that these recommendations contain relevant information related to stock returns.”
Empirical evaluation of an automated intraday stock recommendation system incorporating both market data and textual news (2014, background): “Other papers from the ﬁ - nancial literature [1,9,51,52,55] have examined the informativeness of different data sources such as news and message boards which appear in textual format.”
The predictive power of online chatter (2005, background): “Tumarkin and Whitelaw [22] showed that days of high discussion activity on the Raging Bull discussion forum correlated with abnormal market returns ; however, they showed that this abnormal activity did not predict market returns.”
How Does Social Media Impact Bitcoin Value? A Test of the Silent Majority Hypothesis (2018, result): “In contrast, in their study of Internet stocks, Tumarkin and Whitelaw [57] find that message board activity cannot predict stock prices, but instead, the causality appears to run from the market to the forums.”
Topic Modeling based Sentiment Analysis on Social Media for Stock Market Prediction (2015, background): “Some researchers report that the sentiments from social media have no predictive capabilities (Antweiler and Frank, 2004; Tumarkin and Whitelaw, 2001), while other researchers have re-ported either weak or strong predictive capabilities (Bollen et al., 2011).”
Deep learning for financial sentiment analysis on finance news providers (2016, neutral): “[9] 2 .”
Social signals and algorithmic trading of Bitcoin (2015, background): “05 and does not pass the KPSS test, giving a p-value above 0 .”
Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content (2013, positive): “This also applies to many other types of UGC in past studies, such as financial forums (Tumarkin and Whitelaw 2001) and e-commerce websites (Pavlou and Dimoka 2006).”