Intraday Liquidity Provision by Trader Types in a Limit Order Market: Evidence from Taiwan Index Futures

• Author: Huimin Chung,George H. K. Wang,Junmao Chiu
• Published date: 01 February 2014
• Date: 01 February 2014
• DOI: http://doi.org/10.1002/fut.21586

INTRADAY LIQUIDITY PROVISION BY TRADER

TYPES IN A LIMIT ORDER MARKET:EVIDENCE

FROM TAIWAN INDEX FUTURES

JUNMAO CHIU, HUIMIN CHUNG and GEORGE H. K. WANG*

This study examines the dynamic liquidity provision process by institutional and individual

traders in the Taiwan index futures market, which is a pure limit order market. The empirical

analysis obtains several interesting empirical results. We find that trader type affects liquidity

provision in a number of interesting ways. First, although institutional traders use more limit

orders than market orders, foreign institution (individual) traders use a relatively higher

percentage of market (limit) orders in the early trading session and then switch to more limit

(market) orders for the remainder of the day until close to the end of the trading day. Second, net

limit order submissions by both institutional and individual traders are positively related to

one‐period lagged transitory volatility and negatively related to informational volatility. Third,

net limit order submissions by institutional traders are positively related to one‐period lagged

spread. Finally, both the state of limit order book and order size significantly influence all types

of traders’strategy on submission of limit order versus market order during the intraday trading

session. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 34:145–172, 2014

1. INTRODUCTION

Electronic limit order market is one of major trading venues in equity, futures, and option

exchanges around the world. Because no designated market makers exist in these markets,

limit orders supply liquidity and market orders consume liquidity. Thus, liquidity arises

endogenously from the orders submitted by market participants in the exchanges. Because

liquidity is a major performance measurement for exchanges, understanding the factors

affecting the limit order submission rate by different types of traders under different market

conditions is of interest to researchers, exchange officials, and investors.

Junmao Chiu is a Ph.D. Associate at the Graduate Institute of Finance, National Chiao Tung University,

Taiwan. Huimin Chung is a Professor of Finance at the Graduate Institute of Finance, National Chiao Tung

University, Taiwan. George H. K. Wang is the Research Professor of Finance at the School of Management,

George Mason University, Fairfax, Virginia. The authors would like to thank the anonymous referee and Robert

Webb (the editor) for their constructive comments and suggestions that significantly improved the quality of the study.

An earlier version of this study was presented at the 2011 Financial Management Association Annual Meetings, in

Denver, Colorado. The 4th NCTU International Finance Conference, in Hsinchu, Taiwan, and The AsianFA and

TFA 2012 Joint International Conference, in Taipei, Taiwan.

A part of this work was done when Junmao Chiu was a visiting scholar in the Finance area, School of Management,

George Mason University, Fairfax, VA 22030.

*Correspondence author, Schoolof Management, George Mason University, 4400 University Drive, Fairfax, Virginia

22030. Tel: 703‐993‐3415, Fax: 703‐993‐1870, e‐mail: gwang2@gmu.edu

Received September 2011; Accepted August 2012

The Journal of Futures Markets, Vol. 34, No. 2, 145–172 (2014)

© 2012 Wiley Periodicals, Inc.

Published online 28 November 2012 in Wiley Online Library (wileyonlinelibrary.com).

DOI: 10.1002/fut.21586

Previous literature has approached limit order trading strategy through both theoretical

models and empirical analysis. Earlier theoretical models assume that informed traders who

trade on short‐lived, private information are impatient and thus place market orders, whereas

uninformed traders who use limit orders must await execution (Glosten, 1994; Seppi, 1997).

Later theoretical models (e.g., Chakravarty & Holden, 1995; Harris, 1998; Kaniel &

Liu, 2006) relax this restrictive assumption. They suggest that informed traders use both

limited orders and market orders. In general, they show that the time horizon of private

information is positively related to the probability of using limit orders by informed traders.

Using an experimental asset market, Bloomfield, O’Hara, and Saar (2005) investigate

empirically the evolution of the liquidity provision by trader type in a pure limit order market

under an experimental market setting. They find that informed and liquidity traders use

reverse strategies: Although informed traders consume liquidity earlier in the trading day,

gradually becoming liquidity providers as they increasingly place more limit orders as the

trading day progresses, liquidity traders provide liquidity early in the trading day, gradually

shifting to consume liquidity as the day progresses. They also report that informed traders use

relatively more limit orders. These experimental results challenge the assumptions of the

theoretical models on the order choice of informed traders in a limit order market.

Goettler, Parlour, and Rajan (2005) study the dynamics of order choices in a limit order

market under asymmetric information. They suggest that the volatility of changes in the

fundamental value of an asset affects agents acquiring information about the asset, which in

turn affects the choice of order type of informed traders and market outcomes.

1

Keim and

Madhavan (1995) present empirical evidence on the order choices of institutional traders.

They find that informed traders with short‐lived information tend to use market orders

whereas informed traders with long horizon information (e.g., value traders) are more likely to

use limit orders.

On the empirical literature, Biais, Hillion, and Spatt (1995) examine the relation

between the limit order book and the order flow in the Paris Bourse. They find that the

conditional probability of submitting limit (market) orders by investors is higher when the

spread is wide (tight). Chung, Van Ness, and Van Ness (1999) also show that traders place

more limit orders when the intraday spread is wide in New York Stock Exchange (NYSE). Ahn,

Bae, and Chan (2001) examine the role of limit orders in providing liquidity in the Stock

Exchange of Hong Kong (SEHK), a pure limit order market. They find that one lagged period

transitory volatility is the major determinant of market depth (due to the submission of limit

orders) and that a rise in market depth is followed by a decrease in volatility.

2

Volatility also

determines the changing mix of market and limit orders.

Bae, Jang, and Park (2003) examine the trader’s choice between limit and market orders

using a sample from the NYSE SuperDot. They find that the order size, spread, and expected

transitory volatility are positively related with trader’s limit order choice. Using data from the

Moscow Interbank Currency Exchange, Menkhoff, Osler, and Schmeling (2010) investigate

the use of aggressive price limit orders by informed and uninformed traders in an ordered logit

regression framework. They show that informed traders are more sensitive to changes in the

spread, volatility, and market depth than uninformed traders in a pure limit market. We extend

this line of research by investigating the difference in market impact on order submission

1

Goettler et al. (2009, p. 68) obtain their results numerically from a theoretical model because they cannot obtain a

closed form solution when the relevant frictions of a limit order market are incorporated in the model. The relevant

frictions of a limit order market are discrete price staggered trader arrivals and asymmetric information. For other

theoretical models on the dynamics of order choice in limit order markets, see Rosu (2009) and Parlour and Seppi

(2008).

2

Ahn et al. (2001) do not accurately estimate transitory volatility; they use realized volatility to approximate transitory

volatility.

146 Chiu, Chung, and Wang