Social media and price discovery: the case of cross-listed firms

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

Discussion Papers from Department of Economics, University of Birmingham

Abstract: This paper examines whether social media information affects the price discovery process for cross-listed companies. Using over 29 million overnight tweets mentioning cross-listed companies, we investigate the role of social media for the linkage between the last periods of trading in the US markets and the first periods in the UK market. Our estimates suggest that the size and content of information flows in social networks support the price discovery process. The interactions between lagged US stock features and overnight tweets significantly affect stock returns and volatility of cross-listed stocks when the UK market opens. These effects weaken and disappear after one to three hours after the UK market opening. We also develop a profitable trading strategy based on overnight social media, and the profits remain economically significant after considering transaction costs.

Keywords: Twitter; investor sentiment; cross-listed stocks; text classification; computational linguistics (search for similar items in EconPapers)
JEL-codes: G12 G14 L86 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2020-03
New Economics Papers: this item is included in nep-cmp, nep-fmk, nep-ict and nep-mst
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https://repec.cal.bham.ac.uk/pdf/20-05.pdf

Related works:
Journal Article: Social media and price discovery: The case of cross‐listed firms (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:bir:birmec:20-05

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