Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Please note that all times are shown in the time zone of the conference. The current conference time is: 22nd Dec 2024, 11:32:52am CET
Matteo Benetton1, William Mullins2, Marina Niessner3, Jan Toczynski4
1UC Berkeley; 2UC San Diego; 3Indiana University; 4EPFL
Discussant: Charles Martineau (University of Toronto)
Younger adults increasingly look to social media for news and investment guidance about cryptocurrencies. In this paper we combine survey responses and transaction- level data to study how individuals respond to mainstream celebrity endorsements of cryptocurrencies on Twitter. We find that individuals appear to treat these celebrity tweets as financial advice: tweets are associated with a 16% higher probability that an individual invests in cryptocurrencies, with stronger effects for men, wealthier, and older investors. We also find that aggregate market trading volume in a given coin increases by 10% on the day of the celebrity tweet and stays elevated for the following two days, while returns exhibit a 3% spike with no reversal over the following week. We conclude by showing that investors would have been better off buying Bitcoin or Ethereum than the coin mentioned in the celebrity tweet.
X Bots and Earnings Announcements
Jan Hanousek1, Jan Hanousek2, Konstantin Sokolov1
1University of Memphis; 2Mendel University in Brno
Discussant: Olivier Dessaint (INSEAD)
This paper studies the rationale and effects of buying bots on X (former Twitter). We observe that large amount of attention to corporate X accounts around earnings announcements is driven by bots. Bot activity is a significant predictor of investor disagreement, which is persistent long-term. Moreover, bot activity increases analyst dispersion for the following quarterly earnings announcement. Consistent with managerial short-termism, bot activity often accompanies intense earnings management. Our results are robust to various specifications, including a matching approach indicating causal interpretation.
