Event Studies on Investor Sentiment

37 Pages Posted: 27 Aug 2020 Last revised: 23 Apr 2021

See all articles by Marc-Aurèle Divernois

Marc-Aurèle Divernois

EPFL; Swiss Finance Institute

Damir Filipović

Ecole Polytechnique Fédérale de Lausanne; Swiss Finance Institute

Date Written: September 3, 2020


60 million tweets are scraped from Stocktwits.com over 10 years and classified into bullish, bearish or neutral classes to create firm-individual polarity time-series. Changes in polarity are associated with changes of the same sign in contemporaneous stock returns. On average, polarity is not able to predict next day stock returns but when we focus on specific events (defined as sudden peak of tweet activity), polarity has predictive powers on abnormal returns. Finally, we show that bad events act more as surprises than good events.

Keywords: Investor sentiment, Event study, Polarity, Social Media, Microblogging, Natural Language Processing, Crowd Wisdom

JEL Classification: G11, G14, C32

Suggested Citation

Divernois, Marc-Aurèle and Filipovic, Damir, Event Studies on Investor Sentiment (September 3, 2020). Swiss Finance Institute Research Paper No. 21-33, Available at SSRN: https://ssrn.com/abstract=3657034 or http://dx.doi.org/10.2139/ssrn.3657034

Marc-Aurèle Divernois (Contact Author)

EPFL ( email )

Quartier UNIL-Dorigny, Bâtiment Extranef, # 211
40, Bd du Pont-d'Arve
CH-1015 Lausanne, CH-6900

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4

Damir Filipovic

Ecole Polytechnique Fédérale de Lausanne ( email )

Station 5
Lausanne, 1015

HOME PAGE: http://people.epfl.ch/damir.filipovic

Swiss Finance Institute

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4

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