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Trades and Quotes: A Bivariate Point Process

Posted: 29 Feb 2008  

Asger Lunde

University of Aarhus - School of Economics and Management; CREATES

Robert F. Engle

New York University - Leonard N. Stern School of Business - Department of Economics; New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER)

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Abstract

This article formulates a bivariate point process to jointly analyze trade and quote arrivals. In microstructure models, trades may reveal private information that is then incorporated into new price quotes. This article examines the speed of this information flow and the circumstances that govern it. A joint likelihood function for trade and quote arrivals is specified in a way that recognizes that an intervening trade sometimes censors the time between a trade and the subsequent quote. Models of trades and quotes are estimated for eight stocks using Trade and Quote database (TAQ) data. The essential finding for the arrival of price quotes is that information flow variables, such as high trade arrival rates, large volume per trade, and wide bid-ask spreads, all predict more rapid price revisions. This means prices respond more quickly to trades when information is flowing so that the price impacts of trades and ultimately the volatility of prices are high in such circumstances.

Keywords: duration analysis, market microstructure, transaction data

Suggested Citation

Lunde, Asger and Engle, Robert F., Trades and Quotes: A Bivariate Point Process. Journal of Financial Econometrics, Vol. 1, No. 2, pp. 159-188, 2003. Available at SSRN: https://ssrn.com/abstract=821702

Asger Lunde

University of Aarhus - School of Economics and Management ( email )

Aarhus
Denmark

CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Robert F. Engle (Contact Author)

New York University - Leonard N. Stern School of Business - Department of Economics ( email )

269 Mercer Street
New York, NY 10003
United States

New York University (NYU) - Department of Finance

Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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