Abstract
We classify the sentiment of a large sample of StockTwits messages as bullish, bearish or neutral, and create a stock-aggregate daily sentiment polarity measure. Polarity is positively associated with contemporaneous stock returns. On average, polarity is not able to predict next-day stock returns. But when we condition on specific events, defined as sudden peaks of message volume, polarity has predictive power on abnormal returns. Polarity-sorted portfolios illustrate the economic relevance of our sentiment measure.
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Divernois, M. A., & Filipović, D. (2024). StockTwits classified sentiment and stock returns. Digital Finance, 6(2), 249–281. https://doi.org/10.1007/s42521-023-00102-z
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