Chapter 1 investigates a link between capital market imperfections and asset pricing in a dynamic general equilibrium framework, and shows how the severity of the frictions in capital markets may increase the volatility of the return on equity. Investment frictions in this model constrain the firm's ability to change its investment plan for intertemporal capital accumulation, which leads to lower variability in investment and higher variability in the price of capital. Consequently, the more severe the frictions, the more volatile is the return on capital, implying that holding equity of the firm is riskier and that the risk-free asset is relatively more valuable, and thereby generating a higher equity premium.
Chapter 2 takes an empirical asset pricing approach in which changes in the default and term spreads are used as proxies for state variable risks associated with time variation in investment opportunities. The primary finding is that higher average returns on small and value stocks are systematically related to higher covariances with these macroeconomic variables. Furthermore, time-series regression and the Generalized Method of Moments cross-sectional estimation results show that these macroeconomic variables contain most of the pricing implications of Fama and French's (1993) size and book-to-market factors, implying that the size and value premiums are compensation for higher exposure to the risks related to variation of business conditions over the business cycle.
Chapter 3 investigates whether the extent to which firms are financially constrained is an important determinant of the cross-section of stock returns. The main findings are as follows. CAPM pricing errors are significantly positive for firms that are more likely financially constrained. In addition, the higher the firm's exposure to variation in credit market conditions, the more sensitive is the firm's return to a financial constraint factor. Furthermore, the estimated price of risk for the financial constraint factor is both economically and statistically significant. Taken together, the findings suggest that the degree of financial constraints is a dimension of systematic risk important for asset pricing.