My dissertation contains three chapters. Chapter one proposes a nonparametric method to evaluate the performance of a conditional factor model in explaining the cross section of stock returns. There are two tests: one is based on the individual pricing error of a conditional model and the other is based on the average pricing error. Empirical results show that for valueweighted portfolios, the conditional CAPM explains none of the asset-pricing anomalies, while the conditional Fama-French three-factor model is able to account for the size effect, and it also helps to explain the value effect and the momentum effect. From a statistical point of view, a conditional model always beats a conditional one because it is closer to the true data-generating process. Chapter two proposes a general equilibrium model to study the implications of prospect theory for individual trading, security prices and trading volume. Its main finding is that different components of prospect theory make different predictions. The concavity/convexity of the value function drives a disposition effect, which in turn leads to momentum in the cross-section of stock returns and a positive correlation between returns and volumes. On the other hand, loss aversion predicts exactly the opposite, namely a reversed disposition effect and reversal in the cross-section of stock returns, as well as a negative correlation between returns and volumes. In a calibrated economy, when prospect theory preference parameters are set at the values estimated by the previous studies, our model can generate price momentum of up to 7% on an annual basis. Chapter three studies the role of aggregate dividend volatility in asset prices. In the model, narrow-framing investors are loss averse over fluctuations in the value of their financial wealth. Persistent dividend volatility indicates persistent fluctuation in their financial wealth and makes stocks undesirable. It helps to explain the salient feature of the stock market including the high mean, excess volatility, and predictability of stock returns while maintaining a low and stable risk-free rate. Consistent with the data, stock returns have a low correlation with consumption growth, and Sharpe ratios are time-varying.