I seek increasing our understanding of the origin of asset price booms and bust cycles and propose constructing structural dynamic equilibrium models that allow formalizing their interaction with the dynamics of consumption, hours worked, the current account, stock market trading activity, and monetary policy. For this purpose I propose developing macroeconomic models that relax the assumption of common knowledge of beliefs and preferences, incorporating instead subjective beliefs and learning about market behavior. These features allow for sustained deviations of asset prices from fundamentals in a setting where all agents behave individually rational.The first research project derives the derivative price implications of asset price models with learning agents and determines the limits to arbitrage required so that learning models are consistent with the existence of only weak incentives for improving forecasts and beliefs. The second project introduces housing, collateral constraints and open economy features into existing asset pricing models under learning to explain a range of cross-sectional facts about the behavior of the current account that have been observed in the recent housing boom and bust cycle. The third project constructs quantitatively plausible macro asset pricing models that can explain the dynamics of consumption and hours worked jointly with the occurrence of asset price boom and busts cycles. The forth project develops a set of monetary policy models allowing to study the interaction between monetary policies, the real economy and asset prices, and determines how monetary policy should optimally react to asset price movements. The last project explains the aggregate trading patterns on stock exchanges over boom and bust cycles and improves our understanding of the forces supporting the large cross-sectional heterogeneity in return expectations revealed in survey data.