A Study of Dark Pool Trading Using an Agent-Based Model

A dark pool is a securities trading venue with no published market depth feed. Such markets have traditionally been utilized by large institutions as an alternative to public exchanges to execute large block orders which might otherwise impact settlement price. It is estimated that the trading volume of dark pool markets was 9% to 12% of the total U.S. equity market share volume in 2010 [1]. This phenomenon raises questions regarding the fundamental value of securities traded through dark pool markets and their impact on the price discovery process in traditional “visible” markets. In this paper, we establish a modeling framework for dark pool markets through agent-based modeling. It presents and validates the costs and benefits of trading small orders in dark pool markets. Simulated trading of 78 selected stocks demonstrates that dark pool market traders can obtain better execution rate when the dark pool market has more uninformed traders relative to informed traders. In addition, trading stocks with larger market capitalization yields better price improvement in dark pool markets.

[1]  Joel Hasbrouck,et al.  Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Securities Trading , 2007 .

[2]  A. Kyle.  Continuous Auctions and Insider Trading , 1985 .

[3]  Peter A. Beling,et al.  Agent based model of the E-Mini Future: Application for policy making , 2012, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC).

[4]  Mao Ye,et al.  A Glimpse into the Dark: Price Formation, Transaction Cost and Market Share of the Crossing Network , 2011 .

[5]  Szabolcs Mike,et al.  An Empirical Behavioral Model of Liquidity and Volatility , 2007, 0709.0159.

[6]  Steve Y. Yang,et al.  Agent Based Model of the E-Mini S&P 500 Future: Application for Policy Making , 2012 .

[7]  S. Ray.  A Match in the Dark: Understanding Crossing Network Liquidity , 2010 .

[8]  M. Nimalendran,et al.  Informational Linkages Between Dark and Lit Trading Venues , 2011 .

[9]  S. Maslov.  Simple model of a limit order-driven market , 1999, cond-mat/9910502.

[10]  Anat R. Admati,et al.  A Theory of Intraday Patterns: Volume and Price Variability , 1988 .

[11]  David C. Brown,et al.  Dark Pool Exclusivity Matters , 2013 .

[12]  Steven F. Railsback,et al.  Agent-Based and Individual-Based Modeling: A Practical Introduction , 2011 .

[13]  Maureen O'Hara,et al.  PRICE, TRADE SIZE, AND INFORMATION IN SECURITIES MARKETS* , 1987 .

[14]  Michael J. North,et al.  Toward teaching agent-based simulation , 2010, Proceedings of the 2010 Winter Simulation Conference.

[15]  Y. Amihud,et al.  Illiquidity and Stock Returns: Cross-Section and Time-Series Effects , 2000 .

[16]  Peter A. Beling,et al.  An Agent Based Model of the E-Mini S&P 500 and the Flash Crash , 2011 .

[17]  Alexander Schied,et al.  Price manipulation in a market impact model with dark pool , 2011, 1205.4008.

[18]  Haoxiang Zhu.  Do Dark Pools Harm Price Discovery? , 2013 .