This dissertation consists of two essays investigating the trading by institutions and its impact on the stock market. In the first essay, I investigate why changes in institutional breadth predict return. I first show that changes in breadth are positively associated with abnormal returns over the following four quarters. I then demonstrate that this return predictability can be attributed to the information about the firms' future operating performance. When I examine different types of institutions independently, I find that the predictive power varies across the population of institutions. More specifically, institutions that follow active management style are better able to predict future returns than the passive institutions, and their predictive power appears to be associated with information about future earnings growth. These findings are consistent with the information hypothesis that changes in breadth of institutional ownership can predict return because they contain information about the fundamental value of firms. In the second essay, I examine institutional herding behavior and its impact on stock prices. I document that herds by institutions usually last for more than one quarter and that herds occur more frequently for small and medium size stocks. I find that after herds end, there are reversals in stocks returns for up to four quarters. The magnitude of reversals is positively related to the duration of herding, and negatively related to the price impact of current herding activity. This pattern in returns prevails for all sub-periods examined and is concentrated in small and medium size stocks. My findings suggest that institutional herding may destabilize stock prices.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-4280 |
Date | 01 January 2007 |
Creators | Nguyen, Hoang |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations |
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