HSG research project examines the influence of social media on financial markets

The events surrounding the shares of US computer game retailer Gamestop in early 2021 were a financial earthquake that briefly turned the balance of power on Wall Street upside down and made headlines around the world. An army of small investors, coordinated via social media, drove up the value of Gamestop shares and successfully took on some of the largest hedge funds, which had bet on a falling share price.

The Gamestop example shows that prices on the financial markets can fluctuate sharply not only because of economic indicators or political events. Private investors increasingly share news, rumours and opinions about shares or cryptocurrencies via social platforms and continuously adjust their expectations based on this information. This collective communication influences how information spreads and ultimately how it is reflected in market prices.

Research project funded by the SNSF

‘Unfortunately, the influence of such social interactions on market dynamics has not yet been analysed in detail in the literature,’ says Prof. Dr. Francesco Audrino from the Department of Statistics and Mathematics at the University of St.Gallen (HSG). Under his leadership, a new research project funded by the Swiss National Science Foundation (SNSF) with CHF 601,810 will therefore measure and analyse these ‘financial social networks’. The aim is to capture the structure of these networks and their temporal dynamics.

Early warning system for financial crises?

With the help of this data, the researchers want to develop new methods for predicting fluctuations in financial markets – and the interactions between individual assets. This will enable more accurate forecasts of risk developments and can help both professional risk managers and private investors to make their portfolios more stable. In addition, the researchers want to investigate whether and how these financial networks affect economic stability. If patterns emerge, they could serve as early warning signals for market stress or impending financial crises. In the long term, the findings should then be incorporated into a web-based analysis tool designed to help financial institutions and supervisory authorities identify systemic risks at an earlier stage.