Order Aggressiveness, Trading Patience, and Trader Types in a Limit Order Market
Date | 01 November 2017 |
Published date | 01 November 2017 |
DOI | http://doi.org/10.1002/fut.21832 |
Order Aggressiveness, Trading Patience,
and Trader Types in a Limit Order Market
Junmao Chiu,* Huimin Chung, and George H. K. Wang
This study examines the order aggressiveness and trading patience of foreign institutional
traders, futures proprietary firm traders, individual day and non-day traders in the Taiwan index
futures market. We consider order choice given a completely transparent limit order book. Our
empirical results show that individual (foreign institutional) traders use a more aggressive
(patient) order submission strategy than the other trader types. We find significant differences
among trader types in the timing of order aggressiveness and trading patience over the intraday
time period. Both top and rest-of-the-order-book activities affect traders’order submission
decisions. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:1094–1123, 2017
1. INTRODUCTION
The electronic limit order market is a major mechanism for trading on equity, futures, and
option exchanges around the world. In this type of market, traders post bids and offers that
are transparent to other market participants. At the time of order submission, traders must
decide whether to submit either a market order, which is a bid or offer to transact at the
prevailing market price, or a limit order, which is a bid or offer to transact at a price at or better
than the specified limit price. With a market order, traders achieve execution certainty, but
may pay an unfavorable price for such immediacy. With a limit order, traders have the
probability of improving their execution price by setting a favorable limit price, but run the
risk of non-execution. Unlike a quote-driven market, there are no designated market makers.
In general, limit orders supply liquidity, whereas market orders consume liquidity. Market
liquidity is endogenous, determined by different order flow composition of limit versus
market orders in this market. Therefore, understanding the major factors that affect how
traders make an order choice given a completely transparent (i.e., full) limit order book at the
order submitting time interval is critically important for the analysis of the liquidity
performance of a limit order book market.
Junmao Chiu is an Assistant Professor of Finance, College of Management, Yuan Ze University, Taiwan.
Huimin Chung is a Professor of Finance, Graduate Institute of Finance, National Chiao Tung University;
Taiwan. George H. K. Wang is the Research Professor of Finance, School of Business, George Mason
University, Fairfax, Virginia. The authors wish to thanks the anonymous referee and Robert Webb (the editor)
for their valuable comments that significantly enrich the content of the paper. Junmao Chiu gratefully
acknowledges the financial support from the Ministry of Science and Technology of Taiwan (grant number:
MOST 103-2410-H-155-003). An earlier version of this study was presented at the 2015 Financial
Management Association Annual Meetings, in Orlando, Florida, the Third International Conference on
Futures and Derivative Markets, Shanghai, China, and the 2014 TFA International Conference, Hsinchu,
Taiwan.
*Correspondence author, College of Management, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li, Taoyuan
32003, Taiwan. Tel: þ886-3-4638800 ext. 6371, Fax: þ886-3-4557040, e-mail: jchiu@saturn.yzu.edu.tw
Received January 2016; Accepted October 2016
The Journal of Futures Markets, Vol. 37, No. 11, 1094–1123 (2017)
© 2016 Wiley Periodicals, Inc.
Published online 21 December 2016 in Wiley Online Library (wileyonlinelibrary.com).
DOI: 10.1002/fut.21832
The main purpose of this paper is to perform statistical tests on the hypotheses that
different types of traders (i.e., individual day traders, individual non-day traders, foreign
institutional traders, and futures proprietary traders in Taiwan index futures) who access
different sources of information and have different motives for trading in the index futures
market would lead them to have different order aggression submission behavior. To the best
of our knowledge, there is very limited literature focusing on the differences among foreign
institutional investors and other types of traders in their order aggressiveness strategies at the
order submission level based on complete limit order book information.
Prior theoretical papers (Glosten, 1994; Kumar & Seppi, 1993; Seppi, 1997) assume
limit orders and market orders are exogenously determined in their static models. These
models do not allow traders to choose between a market order and a limit order. Thus, these
models cannot derive implications concerning the proportion of limit and market orders in
the composition of order flow. More recent theoretical papers have analyzed traders’optimal
order placement strategies and market liquidity in the dynamic setting of a limit order book
market (Foucault, 1999; Foucault, Kadan, & Kandel, 2005; Parlour, 1998; Rosu, 2009).
Previous empirical papers provide evidence for the effect of spread, volatility, and
market depth on traders’order placement strategies (order aggression) in different markets
and over different sample periods (e.g., Chiu, Chung, & Wang, 2014; Chou and Wang, 2009;
Griffiths et al., 2000; Menkhoff, Osler, & Schmeling, 2010; Ranaldo, 2004). These papers
examine order submission decisions only between market orders, marketable limit orders
(orders between the best bid ask quotes) and limit orders at the top of the limit order book.
1
However, traders often submit their orders behind the best quote, leading to more depth away
from the best quote (Aitken et al., 2007; Hollifield et al., 2004). Another set of empirical
papers examine order submission strategies and characteristics of order books based on
market order and complete depth of order book (e.g., Biais, Hillion, & Spatt, 1995; Cao,
Hansch, & Wang, 2008; Xu, 2014), but these papers do not examine differences in order
placement strategies between institutional versus individual traders.
Recent literature shows that different trader types differ in their possession of
information, pricing kernel, investors’beliefs, and investor sophistication (Barber & Odean,
2008; Chakravarty, 2001; Goettler, Parlour, & Ranjan, 2005; Locke & Mann, 2005;
Polkovnichenko & Zhao, 2013). These differences can lead them to respond differently to
information shocks across trader types in their liquidity needs and trading and order
submission behaviors. For example, Aitken et al., (2007) find a major difference in the supply
of liquidity by several types of institutional investors. Kuo and Lin (2013) posit that individual
investors who trade more actively are not only overconfident of their information but also
biased in their interpretation of their information.
Based on previous empirical evidence mentioned above and a unique dataset available
to us, we perform empirical tests to explore whether these four types of traders have different
order aggression submission strategies in Taiwan’s index futures market due to the reason
that they have different sources of information, trading motives and trading strategies. We
include the market order and different limit order price quotes to examine how both top and
rest-of-the-order-book activities affect the investor order choice decision at order submission
level under various market conditions.
2
We divide traders into four groups (individual day
1
Duong et al. (2009) did include a category (labeled number 6 in their study) that includes buy (sell) orders at a price
less (greater) than the best bid (ask) quote. These orders are submitted behind the best quote, but Duong et al.
(2009) did not further classify the order aggressiveness categories in the rest of the order book.
2
Our order submission choices exclude cancellation activity since investors face order submission decisions
according to the market order and limit order in different limit order price quotes. If the limit order is not initially
executed, then investors could choose to cancel or revise their submission limit order (Cao et al., 2008; Fong & Liu,
2010).
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