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An Information-Based Theory of Time-Varying Liquidity




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    • Brendan Daley is at the Fuqua School of Business at Duke University. Brett Green is at the Haas School of Business at University of California–Berkeley. The authors are grateful to Bruno Biais, an anonymous Associate Editor, and two anonymous referees for their valuable feedback and suggestions. We are also are grateful to Jim Anton, Snehal Banerjee, Peter DeMarzo, Mike Fishman, Nicolae Gârleanu, Ravi Jagannathan, Arvind Krishnamurthy, Tyler Muir, Dimitris Papanikolaou, Yuliy Sannikov, Andy Skrzypacz, Chester Spatt, Dimitri Vayanos, and Bob Wilson. In addition, we thank seminar participants at Princeton, Harvard/MIT, Berkeley, UCLA, Caltech, Chicago Booth, Penn State, and the University of Illinois as well as conference participants at FRA, WFA, FIRS, FTG, Csef-Igier, and the Multinational Finance Conference for useful comments. The authors declare that they have no relevent or material financial inerests related to the research in this paper.


We propose an information-based theory to explain time variation in liquidity and link it to a variety of patterns in asset markets. In “normal times,” the market is fully liquid and gains from trade are realized immediately. However, the equilibrium also involves periods during which liquidity “dries up,” which leads to endogenous liquidation costs. Traders correctly anticipate such costs, which reduces their willingness to pay. This foresight leads to a novel feedback effect between prices and market liquidity, which are jointly determined in equilibrium. The model also predicts that contagious sell-offs can occur after sufficiently bad news.