Title | Biased information transmission in investor social networks: Evidence from professional traders |
Publication Type | Journal Article |
Year of Publication | 2020 |
Authors | Ng J, Lim S, Uzzi B |
Journal | Management Science |
Date Published | 07/2020 |
Abstract | This research examines how the positive or negative valence of proprietary information affects both the likelihood that people diffuse this information through their social networks and the likelihood that recipients’ access to this information provides them with a source of comparative advantage. Using a unique dataset of over 2 million stock trades and associated profits and losses, and 1 million instant messages exchanged between professional day traders at a U.S. hedge fund, we show that day traders are more likely to talk about their gains than their losses with their close contacts, suggesting that positive information is more likely to be shared among one’s close network of strong ties. However, by examining the subsequent behaviors of message recipients, we find that recipients tend to discount the value of positive, gains related information, being both more likely to pass on and profit from negative information related to trading losses, particularly from their strong ties. Our results suggest that although individuals are more likely to share positive information with their contacts, message recipients appear to account for the asymmetry in their subsequent communications and decision-making." |
URL | (https://www.aeaweb.org/conference/) |
DOI | 10.5465/AMBPP.2020.18198abstract |
Refereed Designation | Refereed |