Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-15T04:37:46.722Z Has data issue: false hasContentIssue false
  • English
  • Français

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.
Get access Rights & Permissions [Opens in a new window]

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

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ball, C. A., and Chordia, T.. “True Spreads and Equilibrium Prices.” Journal of Finance, 56 (2001), 1801–1835.CrossRefGoogle Scholar
Carlin, B. P., and Louis, T. A.. Bayes and Empirical Bayes Methods for Data Analysis. London, England: Chapman and Hall (1996).Google Scholar
Casella, G., and George, E. I.. “Explaining the Gibbs Sampler.” The American Statistician, 46 (1992), 167–190.Google Scholar
Chan, J., and Lakonishok, J.. “Institutional Trades and Intraday Trade Price Behavior.” Journal of Financial Economics, 33 (1993), 173–199.CrossRefGoogle Scholar
Chan, J., and Lakonishok, J.. “The Behavior of Stock Prices around Institutional Trades.” Journal of Finance, 50 (1995), 1147–1174.CrossRefGoogle Scholar
Chib, S., and Greenberg, E.. “Markov Chain Monte Carlo Simulation Methods in Econometrics.” Econometric Theory, 12 (1996), 409–431.CrossRefGoogle Scholar
Christie, W. G.Harris, J. H. and Schultz, P. H.. “Why Did NASDAQ Market Makers Stop Avoiding Odd-Eighth Quotes?” Journal of Finance, 49 (1994), 1841–1860.Google Scholar
Dutta, P. K., and Madhavan, A. M.. “Competition and Collusion in Dealer Markets.” Journal of Finance, 52 (1997), 245–276.CrossRefGoogle Scholar
Easley, D., and O'Hara, M.. “Price, Trade Size, and Information in Securities Markets.” Journal of Financial Economics, 19 (1987), 69–90.CrossRefGoogle Scholar
Easley, D., and O'Hara, M.. “Order Form and Information in Securities Markets.” Journal of Finance, 46 (1991), 905–927.CrossRefGoogle Scholar
Easley, D., and O'Hara, M... “Adverse Selection and Large Trade Volume: The Implications for Market Efficiency.” Journal of Financial and Quantitative Analysis, 27 (1992a), 185–208.CrossRefGoogle Scholar
Easley, D., and O'Hara, M.. “Time and the Process of Security Price Adjustment.” Journal of Finance, 47 (1992b), 576–605.CrossRefGoogle Scholar
Engle, R. F. “Bayesian Analysis of Stochastic Volatility Models: Comment.” Journal of Business and Economic Statistics, 12 (1994), 395–396.Google Scholar
Evans, M. D. D. “FX Trading and Exchange Rate Dynamics.” Journal of Finance, 57 (2002), 2405–2447.CrossRefGoogle Scholar
Ferguson, M. F.Mann, S. C. and Schneck, L. J.. “Concentrated Trading in the Foreign Exchange Futures Markets: Discretionary Liquidity Trading or Market Closure.” Journal of Futures Markets, 18 (1998), 343–362.3.0.CO;2-8>CrossRefGoogle Scholar
Gamerman, D.Markov Chain Monte Carlo. New York, NY: Chapman and Hall (1997).Google Scholar
George, T. J.Kaul, G. and Nimalendran, M.. “Estimation of the Bid-Ask Spread and Its Components: a New Approach.” Review of Financial Studies, 4(1991), 623–656.CrossRefGoogle Scholar
Gilks, W. R.Richardson, S. and Spiegelhalter, D. J.. “Introducing Markov Chain Monte Carlo.” In Markov Chain Monte Carlo in Practice, Gilks, W. R., Richardson, S., and Spiegelhalter, D.J., eds. London, England: Chapman and Hall (1996).Google Scholar
Glosten, L. R., and Harris, L. E.. “Estimating the Components of the Bid/Ask Spread.” Journal of Financial Economics, 21 (1988), 123–142.CrossRefGoogle Scholar
Glosten, L. R., and Milgrom, P. R.. “Bid, Ask, and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders.” Journal of Financial Economics, 14 (1985), 71–100.CrossRefGoogle Scholar
Goodhart, C.Ito, T. and Payne, R.. “One Day in June 1993: A Study of the Working of the Reuters 2000–2 Electronic Foreign Exchange Trading System.” In The Microstructure of Foreign Exchange Markets, Frankel, J. A., Galli, G., and Giovannini, A., eds. Chicago, IL: Univ. of Chicago Press (1996).Google Scholar
Hamilton, J. D.Time Series Analysis. Princeton, NJ: Princeton Univ. Press (1994).CrossRefGoogle Scholar
Harris, L. E. “Estimation of Stock Price Variances and Serial Covariances from Discrete Observations.” Journal of Financial and Quantitative Analysis, 25 (1990a), 291–306.CrossRefGoogle Scholar
Harris, L. E.. “Statistical Properties of the Roll Serial Covariance Bid/Ask Spread Estimator.” Journal of Finance, 45 (1990b), 579–590.CrossRefGoogle Scholar
Harris, L. E.. “Stock Price Clustering and Discreteness.” Review of Financial Studies, 4 (1991), 389–415.CrossRefGoogle Scholar
Harris, L. E.. “Minimum Price Variations, Discrete Bid-Ask Spreads, and Quotation Sizes.” Review of Financial Studies, 7 (1994), 149–178.CrossRefGoogle Scholar
Harris, L. E.. “Decimalization: A Review of the Arguments and Evidence.” Univ. of Southern California (1997a).Google Scholar
Harris, L. E.. “Does a Large Minimum Price Variation Encourage Order Exposure?” School of Business Administration, Univ. of Southern California (1997b).Google Scholar
Hasbrouck, J. “Trades, Quotes, Inventories, and Information.” Journal of Financial Economics, 22 (1988), 229–252.CrossRefGoogle Scholar
Hasbrouck, J.. “Measuring the Information Content of Stock Trades.” Journal of Finance, 46 (1991a), 179–207.CrossRefGoogle Scholar
Hasbrouck, J.. “The Summary Informativeness of Stock Trades: An Econometric Analysis.” Review of Financial Studies, 4 (1991b), 571–595.CrossRefGoogle Scholar
Hasbrouck, J.. “Using the TORQ Database.” New York Stock Exchange (1992).Google Scholar
Hasbrouck, J.. “Modeling Microstructure Time Series.” In Handbook of Statistics 14: Statistical Methods in Finance, Maddala, G. S. and Rao, C. R., eds. Amsterdam: Elsevier North Holland (1996a).Google Scholar
Hasbrouck, J.. “Order Characteristics and Stock Price Evolution: an Application to Program Trading.” Journal of Financial Economics, 41 (1996b), 129–149.CrossRefGoogle Scholar
Hasbrouck, J.. “The Dynamics of Discrete Bid and Ask Quotes.” Journal of Finance, 54 (1999a), 2109–2142.CrossRefGoogle Scholar
Hasbrouck, J.. “Security Bid/Ask Dynamics with Discreteness and Clustering: Simple Strategies for Modeling and Estimation.” Journal of Financial Markets, 2 (1999b), 1–28.CrossRefGoogle Scholar
Hasbrouck, J.. “Trading Costs and Returns for U.S. Equities: The Evidence from Daily Data.” Stern School of Business, New York Univ. (2003).Google Scholar
Hasbrouck, J., and Ho, T. S. Y.. “Order Arrival, Quote Behavior, and the Return-Generating Process.” Journal of Finance, 42 (1987), 1035–1048.Google Scholar
Holthausen, R. W.Leftwich, R. W. and Mayers, D.. “The Effect of Large Block Transactions on Security Prices.” Journal of Financial Economics, 19 (1987), 237–267.CrossRefGoogle Scholar
Holthausen, R. W.Leftwich, R. W. and Mayers, D.. “Large Block Transactions, the Speed of Response, and Temporary and Permanent Stock Price Effects.” Journal of Financial Economics, 26 (1990), 71–95.CrossRefGoogle Scholar
Huang, R. D., and Stoll, H. R.. “Market Microstructure and Stock Return Predictions.” Review of Financial Studies, 7 (1994), 179–213.CrossRefGoogle Scholar
Huang, R. D., and Stoll, H. R.. “The Components of the Bid-Ask Spread: A General Approach.” Review of Financial Studies, 10 (1997), 995–1034.CrossRefGoogle Scholar
Jacquier, E.Polson, N. G. and Rossi, P. E.. “Bayesian Analysis of Stochastic Volatility Models.” Journal of Business and Economic Statistics, 12 (1994), 371–389.Google Scholar
Jones, C. S. “The Dynamics of Stochastic Volatility: Evidence from Underlying and Options Markets.” Simon School of Business, Rochester Univ. (2002).Google Scholar
Kandel, E., and Marx, L. M.. “NASDAQ Market Structure and Spread Patterns.” Journal of Financial Economics, 45 (1997), 61–89.CrossRefGoogle Scholar
Kim, C.-J., and Nelson, C. R.. State-Space Models with Regime Switching. Cambridge, MA: MIT Press (2000).Google Scholar
Kim, S.Shephard, N. and Chib, S.. “Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models.” Review of Economic Studies, 65 (1998), 361–393.CrossRefGoogle Scholar
Laux, P. A., and Senchack, A. J. Jr, “Bid-Ask Spreads in Financial Futures.” Journal of Futures Markets, 12 (1992), 621–634.CrossRefGoogle Scholar
Lee, C. M. C., and Ready, M. J.. “Inferring Trade Direction from Intraday Data.” Journal of Finance, 46 (1991), 733–746.CrossRefGoogle Scholar
Locke, P. R., and Venkatesh, P. C.. “Futures Market Transactions Costs.” Journal of Futures Markets, 17 (1997), 229–245.3.0.CO;2-L>CrossRefGoogle Scholar
Lyons, R. K. “Tests of Microstructural Hypotheses in the Foreign Exchange Market.” Journal of Financial Economics, 39 (1995), 321–351.CrossRefGoogle Scholar
Lyons, R. K.. “A Simultaneous Trade Model of the Foreign Exchange Hot Potato.” Journal of International Economics, 42 (1997), 275–298.CrossRefGoogle Scholar
Lyons, R. K.. The Microstructure Approach to Foreign Exchange Rates. Cambridge, MA: MIT Press (2001).CrossRefGoogle Scholar
Ma, C. K.Peterson, R. L. and Sears, R. S.. “Trading Noise, Adverse Selection and Intraday Bid-Ask Spreads in Futures Markets.” Journal of Futures Markets, 12 (1992), 519–538.CrossRefGoogle Scholar
Madhavan, A. and Roomans, M.. “Why Do Security Prices Change?“ Review of Financial Studies, 10 (1997), 1035–1064.CrossRefGoogle Scholar
Manaster, S., and Mann, S. C.. “Life in the Pits: Competitive Market Making and Inventory Control.” Review of Financial Studies, 9 (1996), 953–975.CrossRefGoogle Scholar
Odders-White, E. R. “On the Occurrence and Consequences of Inaccurate Trade Classification.” Journal of Financial Markets, 3 (2000), 259–286.CrossRefGoogle Scholar
O'Hara, M.Market Microstructure Theory. Cambridge, MA: Blackwell Publishers (1995).Google Scholar
Roll, R. “A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market.” Journal of Finance, 39 (1984), 1127–1139.Google Scholar
Schwert, G. W. “Symposium on Market Microstructure: Focus on NASDAQ.” Journal of Financial Economics, 45 (1997), 1–8.CrossRefGoogle Scholar
Shephard, N. “Fitting Nonlinear Time-Series Models with Applications to Stochastic Variance Models.” Journal of Applied Econometrics, 8 (1993), S135–S152.CrossRefGoogle Scholar
Smith, T., and Whaley, R. E.. “Estimating the Effective Bid/Ask Spread from Time and Sales Data.” Journal of Futures Markets, 14 (1994), 437–455.CrossRefGoogle Scholar
Subrahmanyam, A. “A Theory of Trading in Stock Index Futures.” Review of Financial Studies, 4 (1991), 17–51.CrossRefGoogle Scholar
U.S. Securities and Exchange Commission. Final Rule: Disclosure of Order Routing and Execution Practices. (2001).Google Scholar