Social media, political uncertainty, and stock markets

Rui Fan (), Oleksandr Talavera () and Vu Tran
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Rui Fan: Swansea University
Vu Tran: University of Reading

Review of Quantitative Finance and Accounting, 2020, vol. 55, issue 3, No 11, 1137-1153

Abstract: Abstract This study proposes a new measure of firm-level uncertainty exposure around important political events. More specifically, we construct a degree of (dis)agreement among social media users who jointly mention firms and politicians. We study a sample of over 23 million tweets mentioning both a firm from the S&P 500 composite and ‘Trump’ from October 2016 to May 2017. We then analyze the relationship between the (dis)agreement measure and individual stock features. The results suggest that increased disagreement among such tweets is associated with heightened stock price volatility and trading volume. This link is observed before the US Presidential Inauguration in January 2017 but not afterwards. The finding is confirmed by further robustness checks based on filtered tweets with policy keywords and policy-sensitive industries.

Keywords: Twitter; US election; Stock market; Investor sentiment; Text classification; Computational linguistics (search for similar items in EconPapers)
JEL-codes: D72 G12 G14 L86 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (10)

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DOI: 10.1007/s11156-020-00870-4

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