Informed Trading and Market Structure

Date01 January 2015
Published date01 January 2015
European Financial Management, Vol. 21, No. 1, 2015, 148–177
doi: 10.1111/eufm.12003
Informed Trading and Market
Charlie X. Cai
Bradford University Schoolof Management, UK
Jeffrey H. Harris
Syracuse University, USA
Robert S. Hudson
University of Newcastle, UK
Kevin Keasey
International Institute of Banking and Financial Services, University of Leeds, UK
We examine London Stock Exchange trading around information releases and link
market quality dimensions with market structure during periods with heightened
interaction between informed and uninformed traders. We find support for both
the hypothesis that automated electronic markets minimise trading costs for
liquid stocks and the hypothesis that adverse selection costs are minimised with
intermediated trading. We examine how news affects both dealer and electronic
systems and find that electronic markets are prone to greater stealth trading and
post-trade volatility, both consistent with the proliferation of algorithmic trading
and short-term volatility events such as the May 6, 2010 ‘flash crash.’
Keywords: market structure,informed trading,trading systems,London stock
JEL classification: G10, G15
Wewould like to thank Kirsten Anderson and seminar participants at the University of Leeds
and the University of Brunel for their helpful comments. We thank John Doukas, the editor
of this journal, and the anonymous referee for their constructive and helpful comments. All
errors are our responsibility. Correspondence: Charlie X. Cai.
© 2013 John Wiley & Sons Ltd
Informed Trading and Market Structure 149
© 2013 John Wiley & Sons Ltd
1. Introduction
Technological advances have created unprecedented opportunities for developing a
variety of market structures for trading stock. In the USA, both Nasdaq and the
New York Stock Exchange (NYSE) have adopted electronic communications network
(ECN) technology as their primary trading platforms.1Indeed, technology has improved
market quality along many dimensions and, by facilitating automated executions, has
ushered in an explosion of trading volume. However, as the 6 May 2010 ‘flash crash’
demonstrates, technological changes also present challenges to financial markets. While
electronic systems facilitate algorithmic trading and high frequency trading strategies,
the diminished role of human interaction raises questions about the stability of these
electronic systems.2
A number of research papers examine various features of trading systems to assess the
efficiency and effectiveness of different market structures.3Generally, this work finds
that automation may providedirect cost advantages, but Venkataraman (2001) showsthat
electronic, disintermediated markets may suffer from large adverseselection costs which
may outweighpotential direct cost savings. In this paper, we use London Stock Exchange
(LSE) data to further examine the interaction between market quality characteristics and
the structure of the trading system itself. Our tests recognise the fact that traders face
both direct costs and adverse selection costs when executing orders. We first examine
the direct cost minimisation hypothesis that lowercost automated electronic markets are
most effective for liquid stocks with an abundance of public information available for
making trading decisions. Under this hypothesis, intermediation adds needless costs to
the trading process and, the trading system may affect the strategies that traders employ
in the search for the most cost effective execution.
Wethen examine the second (not mutually exclusive) hypothesis that adverse selection
costs are minimised with intermediated trading so that intermediated trading benefits
less liquid stocks where market makers can mitigate more substantial adverse selection
costs. Indeed, whenrelatively little information is available about smaller stocks, concern
about adverse selection costs may outweigh the prospects of higher direct costs. Under
this hypothesis, market makers add liquidity to the market, lowering the cost of informed
trading and accommodating larger trade sizes overall.
In order to test these hypotheses about how market structure affects market quality
characteristics, we would ideally like to measure market quality for stocks trading in
both dealer and electronic markets, ceteris paribus. In the absence of this opportunity,
one approach examines stocks which switch trading venues.4While this approach holds
1Using INET and ArcaEx platforms, respectively. The BATS Exchange grew from an ECN
to execute over 10% of US matched volume in just four years.
2Hendershott and Menkveld (2010), Brogaard (2010) and Jovanovic and Menkveld (2010)
each address the costs and benefits of high frequency traders and their use of trading
3Thiessen (2002), Handa et al. (2004) and Jain (2005) examine floor- and screen-based
systems. Berkman and Hayes (2000), Madhavan and Panchapagesan (2000), Sof ianos and
Werner (2000), and Battalio, et al. (2007) highlight the importance of floor participants,
while Benveniste et al. (1992), Madhavan and Sofianos (1998), Anand and Weaver (2004)
and Anand et al. (2010) characterise the value of a specialist.
4See, for example, Sanger and McConnell (1986), Christie and Huang (1995), Barclay
(1997), Clyde et al. (1997) and Kalay and Portniaguina (2001).

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