Does Divergence of Opinions Make Better Minds? Evidence from Social Media

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Speaker bio

Junhong Yang is an associate professor in Finance at Sheffield University Management School. Prior to that, he held positions as an associate professor at SOAS University of London. Junhong has published widely in international academic journals, focusing on the area of the Economics of Transition in China, Corporate Finance, Financial Technology and Social Media. Junhong is also a Fellow of the Centre for Research into Accounting and Finance in Context (CRAFiC) and the Centre for Global Finance (CGF) at SOAS and an External Consultant at the Asian Development Bank Institute (ADBI). Earlier, he was also a Research Fellow at the Institute of Public Finance in Croatia. He has been involved in different research proposals and projects, including the ESRC/UKRI/AHRC/BA grants.

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.

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