Download This PaperStockTwits Classified Sentiment and Stock Returns
Swiss Finance Institute Research Paper No. 21-33
Digital Finance, Forthcoming
42 Pages Posted: 27 Aug 2020 Last revised: 29 Nov 2023
Date Written: September 3, 2020
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.
Keywords: investor sentiment; event study; social media; micro-blogs; natural language processing
JEL Classification: C55; G14; G17
Suggested Citation: Suggested Citation
Swiss Finance Institute ( email )
c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland
Swiss Finance Institute
c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland