Social media, political uncertainty, and stock markets

被引:14
|
作者
Fan, Rui [1 ]
Talavera, Oleksandr [2 ]
Vu Tran [3 ]
机构
[1] Swansea Univ, Sch Management, Fabian Way, Swansea SA1 8EN, W Glam, Wales
[2] Univ Birmingham, Birmingham Business Sch, Edgbaston Pk Rd, Birmingham B15 2TY, W Midlands, England
[3] Univ Reading, ICMA Ctr, Henley Business Sch, Reading RG6 6BA, Berks, England
关键词
Twitter; US election; Stock market; Investor sentiment; Text classification; Computational linguistics; INFORMATION-CONTENT; INVESTOR SENTIMENT; CROSS-SECTION; VOLUME; VOLATILITY; DISPERSION; OPINIONS; RETURNS; NOISE; PRICE;
D O I
10.1007/s11156-020-00870-4
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
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.
引用
收藏
页码:1137 / 1153
页数:17
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