Information Processing and Stock Market Volatility - Evidence from Real Estate Investment Trusts

This study proposes novel measurements of investor psychology utilizing Big Data and reveals the impact of different measures on asset price volatility. We construct a news sentiment measure based on news articles reflecting information supply. News content is transformed into quantitative data utilizing sentiment analysis. We further investigate a metric for investor attention based on search queries from the web representing information demand. Consequently, we investigate how asset price volatility is attributable to information processing by investors. The main contribution of this paper is the analysis of novel insights into information processing by investors in the presence of Big Data. In particular, we find that the impact of news content (information supply) generally is much stronger than the effect of Big Data search behavior (information demand). While our results confirm the negativity-bias of investors, we find that measures additionally incorporating positive content outperform measures solely based on negative connotations.