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An Empirical Analysis of Market Segmentation on U.S. Equity Markets

Published online by Cambridge University Press:  23 November 2017

Frank Hatheway ,
Amy Kwan  and
Hui Zheng
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Abstract

We examine the impact of trading on markets partially exempt from National Market System requirements (“dark venues”) on equity-market quality. We find evidence consistent with the notion that dark venues rely on their special features to segregate order flow based on asymmetric information risk, which results in their transactions being less informed and contributing less to price discovery on the consolidated market. Except for the execution of large transactions and trading in small stocks, the effects of dark-venue order segmentation are damaging to overall market quality. Our results have important implications for the regulation of international equity markets.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 52 , Issue 6 , December 2017 , pp. 2399 - 2427
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2017 

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Footnotes

1

We thank Hendrik Bessembinder (the editor), Tarun Chordia, Robert Faff, Douglas Foster, David Johnstone, Ronald Masulis, Andrew Patton, Talis Putniņš, Jeff Smith, Tom Smith, Peter Swan, Susan Thorpe, Ingrid Tierens (discussant), Monika Trapp (discussant), Vincent van Kervel (discussant), Terry Walter, Mao Ye (the referee), and participants at the 2013 Annual Central Bank Workshop on the Microstructure of Financial Markets, the 2014 European Finance Association Annual Meeting, the 2014 University of Maryland/Financial Industry Regulatory Authority Conference on Market Fragmentation, Fragility and Fees, and seminars held at Australian National University, Florida International University, the University of New South Wales, the University of Queensland, the University of Technology, Sydney, Australian Securities and Investments Commission, Goldman Sachs, Hong Kong Securities and Futures Commission, Nasdaq, Inc., and the U.S. Securities and Exchange Commission for helpful comments. We thank Nasdaq, Inc., for providing the data for this research. The data employed in this research are equivalent to the trade and quote data publicly available through such databases as Wharton Research Data Services. We note that Nasdaq, Inc., is a listing venue with lit trading in the U.S. equities markets. However, the views expressed herein are not intended to represent the views of Nasdaq, Inc., its employees, or directors. The authors are solely responsible for the content, which is provided for informational and educational purposes only. Nothing contained herein should be construed as investment advice, either on behalf of a particular security or an overall investment strategy.

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