Doctor of Philosophy

dissertationThis dissertation studies how heterogeneous opinions affect financial market outcomes, including price informativeness and trading volume. The dissertation contains two chapters. In both chapters, theoretical models are developed and then supportive empirical evidence is provided. In the chapter ""Index Trading and Its Effects on the Underlying Assets'' (Chapter 2), I present a rational expectation model of index trading. The key finding is that the efficiency of each of the underlying stocks decreases as the proportion of index traders increases, while the efficiency of the index itself is unchanged. This result is achieved despite the fact that no arbitrage opportunities exist, i.e., the price of the basket (index) is the sum of its components. Using S&P 500 ETFs data, I show that the index contributes to price discovery in its underlying stocks. In addition, the regression analysis is consistent with the model predictions: index trading impairs efficiency of the component securities but does not have effects on the index itself. In the chapter ""News, Influence, and Evolution of Prices in Financial Markets'' (Chapter 2), we study the influence of published views on the evolution of prices by constructing a theoretical model and using empirical work to test the model. Our sequential trade model demonstrates how the influence of published views creates patterns in prices and volume. Still, a ""wisdom of the crowds'' effect emerges endogenously in our framework and helps expunge such shared errors from the price, thus setting the paper apart from the information cascades literature. We use the timing of earnings announcements to test our model, and find evidence consistent with the theoretical predictions. The magnitude of the empirical effects is then used to calibrate the model, and our calibration exercise suggests that patterns in the evolution of prices are affected more strongly by the extent of the influence of the published view than by its accuracy