Limit order placement across multiple exchanges

• Published in: 2012 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr) pp. 1 - 8
• Main Authors: Yim, R., Brzezinski, A.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2012
• Subjects: Data mining; Data models; Delay; Pricing; Resource management; Schedules; Stock markets
• ISBN: 1467318027; 9781467318020
• ISSN: 2380-8454
• DOI: 10.1109/CIFEr.2012.6327772

The US equity exchange market is organized as a National Market System, enforcing price priority across exchanges, but otherwise allowing competition for order flow among exchanges. This flexibility has naturally evolved to a market where exchanges have varying quality and cost of execution. To meet the obligation for best execution, a broker must employ a strategy for selecting the exchange to which limit orders are placed. We consider a market consisting of exchanges with different pricing and priority schemes, and derive a theoretical model to estimate the delay until execution of limit orders. We estimate model parameters from quote and trade data of stocks in the Russell 1000 index, and use them to evaluate expected delay per exchange. We show that inverted cost exchanges and price-size priority exchanges offer improved performance over short time intervals, while traditional and price-time priority exchanges offer improved performance over longer time intervals. We observe that while exchanges with large market share may have high market order liquidity, they may in fact have low limit order liquidity. Low limit order liquidity in turn leads to low execution quality of algorithmic orders. For time-sensitive algorithmic orders, we show a trade-off between execution quality and cost, and show exchanges on an efficient frontier for each stock that achieves good trade-off performance given current exchange pricing.