Fundamentals or Noise? The Informative Value of Twitter Sentiment for REIT Returns

Twitter is established as a major platform for sharing information and opinions online. Previous research has demonstrated a connection between Twitter-expressed market sentiment and financial markets, including the U.S. REIT market. This study builds on existing literature by investigating the economic and real estate-related factors that shape Twitter sentiment and examining how its rational and irrational components differentially affect market dynamics. Given the nature of Twitter messages, comprehensive natural language processing is applied to clean and identify relevant posts and to provide the foundation for extracting the sentiment. The complex linguistic features of the given informal language are handled using a large language model. Preliminary results suggest that the rational component of social media sentiment holds increased predictive value for market trends in periods where a higher share of professional investors is active on social media, like the recent COVID-19 pandemic. On the contrary, the findings indicate that irrationality, which cannot be explained by the market itself, holds more explanatory power when mostly private investors are active on Twitter.