This dissertation explores the effect of investor attention, as measured by Google Search Volume Index, on security prices. It seeks to answer the following research questions: 1) what is the effect of investor attention on the expected returns of EREITs? And 2) what is the impact of investor attention on the open market repurchases post announcement returns?
Classic theory suggests that information is immediately incorporated into stock prices. However, existing empirical evidence shows that investors are limited in terms of the amount of information they can process. Kahneman (1973) advances that attention is a scarce cognitive resource. Individuals suffer from bounded rationality. When faced with large amounts of information, they are limited in terms of how much they can process. This implies that prices may not reflect all available information due to limited investor attention.
Essay 1 investigates the effect of investor attention on the expected returns of EREITs. The attention hypothesis of Barber and Odean (2008) suggests that increased attention leads to increased buying, which pushes prices and returns higher temporarily, but is followed by a reversal. We test the attention hypothesis on EREITs from 2004 to 2012 using Search Volume Index (SVI) data in Google Trends. We find that EREITs that generate high investor attention, as measured by SVI, earn higher returns compared to EREITs that generate no investor attention. The results are driven by small stocks and stocks with high book to market ratio. We report that the SVI effect is not due to impediments to trade and conjecture that SVI increases investor recognition among EREITs that are characterized by information incompleteness, leading to higher returns. Over time, this increase in returns is followed by a reversal.
Essay 2 uses the attention hypothesis to generate insights into stock repurchases price drift. Using a sample of 318 firms that made repurchase announcements between 2004 and 2008 and which have weekly search volume data in Google Tr [...]
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