Market Microstructure.

PositionProgram and Working Group Meetings

The NBER's Working Group on Market Microstructure met on October 24 in Cambridge. Group Director Bruce Lehmann of University of California, San Diego, Eugene Kandel, Hebrew University, Jerusalem, and Avanidhar Subrahmanyam, University of California, Los Angeles, jointly organized the meeting. These papers were discussed:

Ioanid Rosu, University of Chicago, "Liquidity and Information in Order Driven Markets"

Discussant: Uday Rajan, University of Michigan

Paolo Pasquariello, University of Michigan, and Clara Vega, Federal Reserve Board, "Strategic Cross-Trading in the U.S. Stock Market"

Discussant: Bruce Mizrach, Rutgers University

Chiraphol Chiyachantana, Singapore Management University, and Pankaj Jain, University of Memphis, "The Opportunity Cost of Inaction in Financial Markets: An Analysis of Institutional Decisions and Trades"

Discussant: Sunil Wahals, Arizona State University

Azi Ben-Rephael and Avi Wolff, Tel Aviv University, and Ohad Kadan, Washington University in St. Louis, "The Diminishing Liquidity Premium"

Discussant: Ronnie Sadka, Boston College

Anna Obizhaeva, University of Maryland, "Price Impact and Spread: Application of Bias-Free Estimation Methodology to Portfolio Transitions" Discussant: Charles Jones, Columbia University

Alex Boulatov and Thomas George, University of Houston, "Securities Trading when Liquidity Providers are Informed"

Discussant: Ronald Goettler, University of Chicago

Using a dynamic model of an order-driven market, Rosu analyzes the interaction between liquidity traders and informed traders. Agents choose freely between limit and market orders by trading off execution price and waiting costs. In equilibrium, informed and patient traders generally submit limit orders, except when the fundamental value of the asset that they privately observe is far from the current market-inferred value, in which case they become impatient and submit a market order. As a result, a market buy order can be seen as an unambiguously positive signal; by contrast, a limit buy order is typically a weaker positive, and in some cases even a negative, signal. Rosu's model generates a rich set of relationships among prices, spreads, trading activity, and volatility. In particular, the order flow is autocorrelated if and only if there are informed traders in the market, and the autocorrelation increases with the percentage of informed traders. Higher volatility and lower trading activity generate larger spreads while, after...

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