Algorithmic Trading, Liquidity, and Price Discovery: An Intraday Analysis of the SPI 200 Futures

Published date01 May 2014
Date01 May 2014
The Financial Review 49 (2014) 245–270
Algorithmic Trading, Liquidity, and Price
Discovery: An Intraday Analysis of the SPI
200 Futures
Tina Viljoen
The University of Sydney
P. Joakim Westerholm
The University of Sydney
Hui Zheng
The University of Sydney
We study the intraday price impact of algorithmic trading (AT) on futures markets. We
find that AT exhibits a strong reverse U-shape intraday pattern, and greater AT activity is
related to lower effective spreads, higher realized spreads and lower adverse selection risk,
which suggests that algorithmic traders strategically enter the market when transaction costs
and information asymmetry are lower. AT is associated with an increase in transaction costs
in the subsequent intraday period mainly through an increase in the adverse selection risk, and
is positively related to both public and private information. Our results strongly suggest that
algorithmic traders are informed and contribute to liquidity and price discovery on the futures
Corresponding author: Discipline of Finance, Business School, The University of Sydney, NSW 2006,
Australia; Phone: (61) 2 9351 3915; Fax: (61) 2 9351 6461; E-mail:
We would like to thank seminar participants at the Universityof Sydney and The Capital Markets Coop-
erative Research Centre for helpful comments. We specially thank Michael Goldstein (the guest editor)
and two anonymous referees for their constructive advice, which has significantly improved this paper.
All errors are the sole responsibility of the authors.
C2014 The Eastern Finance Association 245
246 T. Viljoen et al./The Financial Review 49 (2014) 245–270
Keywords: algorithmic trading, futures markets, market liquidity, price discovery
JEL Classifications: G10, G13, G14
1. Introduction
This study examines the impact of algorithmic trading (AT) on market liquid-
ity and price discovery in the futures markets. With technological innovation and
the transition to electronic trading platforms, the use of computer algorithms has
increased markedly in the past decade, coinciding with increased trading activity
and lower trade size (see Chordia, Roll and Subrahmanyam, 2011). It has been
well documented that price discovery in futures leads spot markets (see, e.g., Har-
ris, 1989; Stoll and Whaley, 1990; Chan, 1992; Huang and Stoll, 1994).1Hence,
it is particularly important to examine the impact of AT on futures markets as
the results will have a direct implication on the efficiency of underlying equities
The literature generally supports that AT contributes to the market efficiency
of equities markets by increasing liquidity and speeding up price discovery. For
example, Hendershott and Riordan (2013) find that AT is sensitive to the price
of liquidity, demanding liquidity when it is inexpensive, and supplying liquidity
when costs increase. Brogaard, Hendershott and Riordan (2013) examine the role
of high-frequency traders (HFTs) in price discovery and importantly find that HFTs
overall trade in the direction of reducing transitory pricing errors. Hendershott, Jones
and Menkveld (2011, p. 1) conclude that “AT improves liquidity and enhances the
informativenessof quotes.” Kirilenko, Kyle, Samadi and Tuzun (2011) show that HFT
participation on the futures markets has a significant impact on liquidity.Furthermore,
the importance of futures markets for price discovery is well documented in an
extensive body of literature (e.g., Stoll and Whaley, 1990; Tang, Mak and Choi,
1992; Tse, 1995).
This paper contributes to the literature in the following four ways. First, if AT
contributes to price discovery and pricing occurs first in the futures markets, then it
is important to understand the impact of AT on the futures markets. In this paper,
we connect the literature on AT with the literature on price discovery in the futures
markets. Second, we provide direct empirical evidence as to how AT affects liquidity
and price discovery in the Share Price Index (SPI) 200 Futures contracts traded on the
Australian Securities Exchange (ASX). The SPI contract is particularly interesting for
1For the Australian equities index future that we study, the lead–lag association between future and spot
has also been confirmed by Frino, Walter and West (2000). We verify the association between the future
and the spot index for our sample period (these results are available on request).

To continue reading

Request your trial

VLEX uses login cookies to provide you with a better browsing experience. If you click on 'Accept' or continue browsing this site we consider that you accept our cookie policy. ACCEPT