Intraday Online Information Demand and its Relationship to REIT Prices

Katrin Kandlbinder and Marian Alexander Dietzel

Journal of Real Estate Portfolio Management, 2020, vol. 25, issue 2, 113-127

Abstract: In this study we develop a fictional trading strategy based on Google search volumes on an hourly basis for the MSCI U.S. REIT Index to show whether there is a relationship between intraday online search interest and REIT market movements. Furthermore, we investigate in which market circumstances this trading strategy has the best predicting abilities and examine the controversial questions of correlation and causality between search volumes and prices. The results indicate that search volumes have the ability to predict intraday REIT market movements, as the Google trading strategy achieves an outperformance of 7.37 percentage points on average compared to a buy-and-hold strategy of the underlying REIT. In falling market phases the performance results of the Google trading strategy are substantially better than in rising market phases. On average, there is a statistically significant negative correlation of -0.11 and a causality flow from prices to search volumes. The findings yield new insights into the information-gathering behavior and are therefore useful for understanding and anticipating the relationship between market information demand and REIT price movements.

Date: 2020
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DOI: 10.1080/10835547.2020.1791643

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