Abstract
In this article, the authors provide new evidence on the usefulness of investor sentiment extracted from social media by taking advantage of a new data source covering a more comprehensive social media sphere. They use a unique dataset of social anomaly scores (SAS) to assess the volatility wisdom of crowds and develop trading strategies constructed using social-media-based market volatility sentiment. Using market prices of the VIX-related (CBOE Volatility Index) exchange-traded products, the authors find that these strategies economically outperform a benchmark, while taking into account commissions and management fees.
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