This video is part of the Deep Learning in Finance Summit, London 2017 Event. If you would like to access all of the videos please click here.

Signal Processing on Social Media: Theory and Evidence from Financial Markets

We analyze the processing of information from social media and news media, using a unique dataset on financial markets. We find patterns consistent with a theory of social media as an “echo chamber”: Social networks repeat information, but boundedly rational investors interpret repeated signals as new information. This is based on the empirical finding that stocks with high social media coverage experience high subsequent volatility and trading activity, while high news media coverage predicts low volatility and trading activity. Alternative mechanisms based on private information, investor disagreement, uncertainty shocks, and other behavioral biases are not consistent with the data.

Peiran Jiao, Research Fellow at University of Oxford

Peiran Jiao is a research fellow at Nuffield College and the Department of Economics, University of Oxford. He holds a PhD in Economics from Claremont Graduate University, CA, USA. His main research interests are behavioural and experimental economics and finance. His current projects focus on (1) experience-based learning in financial decision-making and game theoretic interactions, (2) information processing from the news and social media with implications in asset-pricing, macroeconomic outcomes and politics; (3) individual investors’ ability to solve complicated problems in financial markets. He also worked on neurofinance, studying the effects of hormone on trading behaviour and market dynamics.