Order Dynamics: Recent Evidence from the NYSE

40 Pages Posted: 7 Aug 2003 Last revised: 2 Sep 2017

See all articles by Andrew Ellul

Andrew Ellul

Indiana University - Kelley School of Business - Department of Finance; Centre for Economic Policy Research (CEPR); European Corporate Governance Institute (ECGI); CSEF - University of Naples Federico II - Centre for Studies in Economics and Finance (CSEF)

Pankaj K. Jain

University of Memphis - Fogelman College of Business and Economics

Craig W. Holden

Indiana University - Kelley School of Business - Department of Finance

Robert H. Jennings

Indiana University - Kelley School of Business - Department of Finance

Date Written: January 1, 2007

Abstract

Abstract: We examine investor order choices using evidence from a recent period when the NYSE trades in decimals and allows automatic executions. We analyze the decision to submit or cancel an order or to take no action. For submitted orders, we distinguish order type (market vs. limit), order side (buy vs. sell), execution method (auction vs. automatic), and pricing aggressiveness. We find that the NYSE exhibits positive serial correlation in order type on an order-by-order basis, which suggests that follow-on order strategies dominate adverse selection or liquidity considerations at a moment in time. Aggregated levels of order flow also exhibit positive serial correlation in order type, but appear to be non-stationary processes. Overall, changes in aggregated order flow have an order-type serial correlation that is close to zero at short aggregation intervals, but becomes increasingly negative at longer intervals. This implies a liquidity exhaustion-replenishment cycle. We find that small orders routed to the NYSE's floor auction process are sensitive to the quoted spread, but that small orders routed to the automatic execution system are not. Thus, in addition to foregoing price improvement, traders selecting the speed of automatic executions on the NYSE do so with little regard for the quoted cost of immediacy. As quoted depth increases, traders respond by competing on price via limit orders that undercut existing bid and ask prices. Limit orders are more likely and market sells are less likely late in the trading day. These results are helpful in understanding the order arrival process at the NYSE and have potential applications in academics and industry for optimizing order submission strategies.

Keywords: Order choice, limit order, market order, automatic execution

JEL Classification: G10

Suggested Citation

Ellul, Andrew and Jain, Pankaj K. and Holden, Craig W. and Jennings, Robert H., Order Dynamics: Recent Evidence from the NYSE (January 1, 2007). Journal of Empirical Finance, Vol. 14, No. 636-661, 2007, Available at SSRN: https://ssrn.com/abstract=424985 or http://dx.doi.org/10.2139/ssrn.424985

Andrew Ellul

Indiana University - Kelley School of Business - Department of Finance ( email )

1309 E. 10th St.
Bloomington, IN 47405
United States

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

European Corporate Governance Institute (ECGI) ( email )

c/o the Royal Academies of Belgium
Rue Ducale 1 Hertogsstraat
1000 Brussels
Belgium

CSEF - University of Naples Federico II - Centre for Studies in Economics and Finance (CSEF) ( email )

Via Cintia
Complesso Monte S. Angelo
Naples, Naples 80126
Italy

Pankaj K. Jain

University of Memphis - Fogelman College of Business and Economics ( email )

Memphis, TN 38152
United States

Craig W. Holden (Contact Author)

Indiana University - Kelley School of Business - Department of Finance ( email )

Kelley School of Business
1309 E. 10th St.
Bloomington, IN 47405
United States
812-855-3383 (Phone)
812-855-5875 (Fax)

HOME PAGE: http://www.kelley.iu.edu/cholden

Robert H. Jennings

Indiana University - Kelley School of Business - Department of Finance ( email )

1309 E. 10th St.
Bloomington, IN 47405
United States
812-855-2696 (Phone)
812-855-5875 (Fax)

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
763
Abstract Views
4,793
Rank
60,658
PlumX Metrics