My dissertation provides an empirical examination of a conditional asset pricing model that includes an investigation of the importance of a set of factors that are identified in research as adding to the explanatory power of cross-sectional expected returns. I examine the importance of a market beta, size, book-to-market value of equity, an earnings-price ratio, and earnings-price dummy variable for negative earnings firms, and betas from four economic variables in explaining the cross-section of expected returns. My asset pricing model is different from some models previously examined in that I allow risk to vary over time. By relating risk changes to specific market and economic conditions, I examine whether patterns occur in the way in which betas shift over time. By determining the importance of allowing changing risk in empirical models, I am able, in some situations, to more completely describe the cross-section of expected returns in an environment that most closely describes how investors value risky cash flows of a firm. Further, my empirical methodology also allows risk premiums to change over time. Relationships with returns are found to differ in bull and bear markets, economic expansions and recessions, and January and non-January months. This evidence indicates that investors use different firm and economic characteristics to value risky cash flows depending on what they expect to happen in the market or in the economy. Seasonal changes in expectations also occur.