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

38 Pages Posted: 7 Nov 2008  

Joel Hasbrouck

New York University (NYU) - Department of Finance

Multiple version iconThere are 2 versions of this paper

Date Written: March 2003

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 index. Liquidity for the Euro and UK £ contracts is somewhat lower. The pork belly contract exhibits the least liquidity.

Keywords: Futures Markets, Liquidity, Gibbs Sampler, MCMC, Markov chain Monte Carlo, Foreign Exchange, Stock Index Futures

Suggested Citation

Hasbrouck, Joel, Liquidity in the Futures Pits: Inferring Market Dynamics from Incomplete Data (March 2003). NYU Working Paper No. S-DRP-03-15. Available at SSRN: https://ssrn.com/abstract=1296364

Joel Hasbrouck (Contact Author)

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