Does Divergence of Opinion make better minds? Evidence from Social Media

Event Date: 2 November 2022

Speaker: Junhong Yang   (Sheffield University Management School)

Venue: CW404B

Time: 2pm

Abstract:

We investigate whether disagreement on StockTwits provides firm-specific information. Using supervised machine learning approaches and a novel dataset, we predict investors' recommendations and measure disagreement among investors on StockTwits. Our findings suggest that an increase in investors' disagreement results in a drop in return synchronicity. The negative impact of investors' disagreement on return synchronicity suggests higher inflows of firm-specific information. In line with this view, we find that disagreement improves price informativeness by increasing the price leads of earnings. Further empirical evidence suggests that the negative impact of disagreement on return synchronicity is more pronounced for firms with less transparent information environments and higher salience on StockTwits.

Published: 1 November 2022