DisclaimerThe University of Gloucestershire has obtained warranties from all depositors as to their title in the material deposited and as to their right to deposit such material.The University of Gloucestershire makes no representation or warranties of commercial utility, title, or fitness for a particular purpose or any other warranty, express or implied in respect of any material deposited.The University of Gloucestershire makes no representation that the use of the materials will not infringe any patent, copyright, trademark or other property or proprietary rights.The University of Gloucestershire accepts no liability for any infringement of intellectual property rights in any material deposited but will remove such material from public view pending investigation in the event of an allegation of any such infringement. PLEASE SCROLL DOWN FOR TEXT.The Hasty Wisdom of the Mob: How Market Sentiment Predicts Stock Market Behavior M. S. Checkleya, D. Añón Higónb, H. Allesc ABSTRACT We explore the ability of sentiment metrics, extracted from micro-blogging sites, to predict stock markets. We also add ess se ti e ts' p edi ti e ti e-horizons. The data o e logge s' feeli gs about five major stocks. Taking independent bullish and bearish sentiment metrics, granular to two minute intervals, we model their ability to forecast stock price direction, volatility, and traded volume. We find evidence of a causal link from sentiments to stock price returns, volatility and volume. The predictive time-horizon is minutes, rather than hours or days. We argue that diverse and high volume sentiment is more predictive of price volatility and traded volume than nearconsensus is predictive of price direction. Causality is ephemeral. In this sense, the crowd is more a hasty mob than a source of wisdom.

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