"Study: Investors Exploit Social Connections in Stock Trading via Joint Board Memberships"

Researchers from Tampere University, along with an international team, have conducted a study on the impact of professional connections among directors, based on their joint board memberships, on their stock trading behavior. The study suggests that some investors in the insider network may utilize non-public information obtained through these relationships for stock trading purposes. The researchers developed a tool using machine learning methods to help market regulators identify investors who may be using inside information spread through social connections. The study utilized pseudonymized data, making it globally unique, and was funded by the OP Group Research Foundation. The findings have been published in the journal Expert Systems with Applications.

A new tool has been developed to help control the use of insider information that is spread through relationships. The tool utilizes graph neural networks to predict the trading behavior of investors in the insider network, enabling market regulators to identify individuals who may be using inside information in their stock trading. The system can be particularly useful for market regulators and stock exchanges in identifying suspicious investors. The research will continue to explore how insiders share information related to stock exchange releases within their social networks, aiming to uncover the spread and utilization of private information. The application of such systems can benefit all investors by reducing market abuse.