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Liquidity in the Futures Pits: Inferring Market Dynamics from Incomplete Data

Published online by Cambridge University Press:  06 April 2009

Joel Hasbrouck
Joel Hasbrouck
Affiliation:
jhasbrou@stern.nyu.edu, Stern School of Business, New York University, Suite 9–190, Mail Code 0268, 44 West Fourth Street, New York, NY 10012.
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Abstract

Motivated by economic models of sequential trade, empirical analyses of market dynamics frequently estimate liquidity as the coefficient of signed order flow in a price change regression. This paper implements such an analysis for futures transaction data from pit trading. To deal with the absence of timely bid and ask quotes (which are used to sign trades in most equity market studies), this paper proposes new techniques based on Markov chain Monte Carlo estimation. The model is estimated for four representative Chicago Mercantile Exchange contracts. The highest liquidity (lowest order flow coefficient) is found for the S&P 500 index. Liquidity for the Euro and U.K. £ contracts is somewhat lower. The pork belly contract exhibits the least liquidity.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 39 , Issue 2 , June 2004 , pp. 305 - 326
Copyright
Copyright © School of Business Administration, University of Washington 2004

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