Liquidity Black Holes

Stephen Morris () and Hyun Song Shin ()
Additional contact information
Hyun Song Shin: University of London, London School of Economics & Political Science (LSE), Department of Accounting and Finance

Yale School of Management Working Papers from Yale School of Management

Abstract: Traders with short horizons and privately known trading limits interact in a market for a risky asset. Risk-averse, long horizon traders supply a downward sloping residual demand curve that face the short-horizon traders. When the price falls close to the trading limits of the short horizon traders, selling of the risky asset by any trader increases the incentives for others to sell. Sales become mutually reinforcing among the short term traders, and payoffs analogous to a bank run are generated. A "liquidity black hole" is the analogue of the run outcome in a bank run model. Short horizon traders sell because others sell. Using global game techniques, this paper solves for the unique trigger point at which the liquidity black hole comes into existence. Empirical implications include the sharp V-shaped pattern in prices around the time of the liquidity black hole.

Keywords: Liquidity; asset pricing; global games (search for similar items in EconPapers)
JEL-codes: G12 C7 (search for similar items in EconPapers)
Date: 2004-07-28
View citations in EconPapers

Downloads: (external link)
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=446600 (application/pdf)

Related works:
Working Paper: Liquidity Black Holes (2004)
Working Paper: Liquidity Black Holes (2003)
Working Paper: Liquidity Black Holes (2004)
Journal Article: Liquidity Black Holes (2004)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:ysm:somwrk:ysm425

Access Statistics for this paper

More papers in Yale School of Management Working Papers from Yale School of Management
Contact information at EDIRC.
Series data maintained by ().