Order Flow and the Bid-Ask Spread: An Empirical Probability Model of Screen-Based Trading

Posted: 3 Nov 2000

See all articles by Tim Bollerslev

Tim Bollerslev

Duke University - Finance; Duke University - Department of Economics; National Bureau of Economic Research (NBER)

Ian Domowitz

ITG, Inc.; National Bureau of Economic Research (NBER)

Jainxin Wang

affiliation not provided to SSRN

Date Written: February 1994

Abstract

A probabilistic framework for the analysis of screen-based trading activity in financial markets is presented. Conditional probability functions are derived for the stationary distributions of the best bid and offer in the market, given the order flows and the acceptance rates of bids and offers. These flows are conditioned on observable screen information. A two-step method is developed for the estimation of the conditional probability functions. The estimation allows for the separate identification of the unobservable order and acceptance flows, which in turn may be used to predict the stationary distributions of the bid- ask spreads, transaction prices, and other market statistics. A formal comparison of the predicted and the sample bid-ask spread distribution provides a stringent test of the model. The necessary econometric methods for conducting such a test, taking into account the parameter estimation error uncertainty, is developed. The methodology is applied to the screen-based interbank foreign exchange market, using a newly available dataset that consists of continuously recorded bid and ask quotes on the Deutschemark/U.S. Dollar exchange rate. The model is found to provide a good description of the salient probabilistic features of the market structure, even though the formal prediction based test for the spread distribution, with more than 29,000 out-of-sample quotations, rejects the exact parametric formulation of the order flows.

JEL Classification: G10

Suggested Citation

Bollerslev, Tim and Domowitz, Ian H. and Wang, Jainxin, Order Flow and the Bid-Ask Spread: An Empirical Probability Model of Screen-Based Trading (February 1994). Available at SSRN: https://ssrn.com/abstract=5849

Tim Bollerslev (Contact Author)

Duke University - Finance ( email )

Durham, NC 27708-0120
United States
919-660-1846 (Phone)
919-684-8974 (Fax)

Duke University - Department of Economics

213 Social Sciences Building
Box 90097
Durham, NC 27708-0204
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
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Ian H. Domowitz

ITG, Inc. ( email )

380 Madison Avenue, 4th Floor
Electronic Market Initiatives
New York, NY 10017
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Jainxin Wang

affiliation not provided to SSRN

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