"We propose a dynamic competitive equilibrium model of limit order trading, based on the premise that investors cannot monitor markets continuously. We study how limit order markets absorb transient liquidity shocks, which occur when a significant fraction of investors lose their willingness and...

Algorithms enable investors to locate trading opportunities, which raises gains from trade. Algorithmic traders can also process information on stock values before slow traders, which generates adverse selection. We model trading in this context and show that, for a given level of algorithmic...

We propose a dynamic competitive equilibrium model of limit order trading, based on the premise that investors cannot monitor markets continuously. We study how limit order markets absorb transient liquidity shocks, which occur when a significant fraction of investors lose their willingness and...

Incentive problems make securities' payoffs imperfectly pledgeable, limiting agents' ability to issue liabilities. We analyze the equilibrium consequences of such endogenous incompleteness in a dynamic exchange economy. Because markets are endogenously incomplete, agents have different...