A study of dark pool trading using an agent-based model

Sheung Yin Kevin Mo, Mark Paddrik, Steve Y. Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 2013 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
Pages19-26
Number of pages8
DOIs
StatePublished - 2013
Event2013 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013 - Singapore, Singapore
Duration: 16 Apr 201319 Apr 2013

Publication series

NameProceedings of the 2013 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013

Conference

Conference2013 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
Country/TerritorySingapore
CitySingapore
Period16/04/1319/04/13

Keywords

  • Dark pool
  • agent-based model
  • algorithmic trading
  • informed vs. uninformed trader

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