Mann, Venkataraman And Waisburd-Stock Liquidity And The Value Of A Designated Liquidity Provider Evidence From Paris Euronext.pdf

Stock Liquidity and the Value of a Designated Liquidity Provider: Evidence

from Euronext Paris ∞

Steve Mann *

Kumar Venkataraman **

Andy Waisburd *

Current Draft: October 2002

* Neeley School of Business, Texas Christian University, Box 298530, Fort Worth, Texas 76129

** Cox School of Business, Southern Methodist University, PO Box 750333, Dallas, Texas 75275

Contact information: e-mail address of Steve Mann is smann@tcu.edu , Kumar Venkataraman is

kumar@mailcox.smu.edu , and Andy Waisburd is a.waisburd@tcu.edu

∞ We thank Venkatesh Panchapagesan, Christopher Barry, and Rex Thompson for valuable comments

and discussion. We are grateful to Loic Choquet, Socheat Chhay and Lourent Fournier of Euronext Paris

for information on market structure in Paris, and to Pascal Samaran for providing us with the data. Mann

and Waisburd thank the Charles Tandy American Enterprise Center, and the Luther King Center for

Research in Financial Economics.

Stock Liquidity and the Value of a Designated Liquidity Provider: Evidence

from Euronext Paris

Abstract

This paper studies the value of a designated liquidity provider (DLP) in an electronic limit order

book. We conduct a natural controlled experiment by examining a sample of Euronext Paris

securities that trades both with and without the assistance of a market maker. We find that less

liquid stocks experience a statistically significant cumulative abnormal return of four percent

around the introduction of the DLP. For this sample, the DLP enhances market quality by

reducing the frequency of market failure, providing strong empirical support for Glosten (1989).

Liquid stocks are generally unaffected. Overall, these findings support the joint hypothesis that

liquidity is priced and that the services of the designated liquidity provider are an important

factor in this premium. We thus present compelling evidence of a link between market

microstructure and asset pricing.

Key Words: Liquidity provider; Market maker; Trading cost; Electronic limit order book

1. Introduction

The worldwide proliferation of automated trading systems has spurred a debate over the

role of financial intermediaries in the trading process. Although recent advances in technology

have significantly reduced the intermediation needs for mundane tasks such as order submission

or information dissemination, the role of a designated liquidity provider (DLP), such as the

NYSE specialist, as the central pillar of an order-driven market remains contentious. The

liquidity provider is most easily understood as a provider of immediacy. However, it is argued

that public limit orders can be stored in an electronic limit order book and can supply

immediacy. Glosten (1989) emphasizes an alternate rationale that the DLP may prevent market

failures by supplying liquidity during periods when the limit order book is thin. 1 This paper

measures the value of introducing a designated liquidity provider for a sample of stocks in the

Paris Bourse, an automated order driven market, and adds to our understanding on this debate.

Several empirical papers have documented the beneficial role of a DLP. 2 For example,

studies of the NYSE show that the specialist helps maintain narrow spreads and plays a

beneficial role in price formation by anticipating future order imbalances and reducing transitory

volatility. However, extant literature has mainly focused on traditional floor-based order driven

markets, such as the NYSE. This paper provides insight regarding the previously unstudied

value of a DLP in an automated order driven market.

The trading protocols in floor-based and automated markets differ considerably. More

specifically, the specialist at the NYSE has a privileged position vis-à-vis the market, due to

1 Theoretical expositions on the relative merits of order driven markets are also provided in Benveniste et al. (1992),

Glosten (1994), and Seppi (1997), besides others.

2 See, for example, Hasbrouck and Sofianos (1993), Madhavan and Smidt (1993), Madhavan and Sofianos (1998),

Kavajecz (1999), and Madhavan and Panchapegesan (2000) for evidence at the NYSE, Kehr et al. (2001) at the

Frankfurt Stock Exchange, and Mayhew (2002) and Anand and Weaver (2002) at the CBOE.

monopolistic access to order flow information. Given informational advantages, the specialist

may discern better than most traders time-variations in the composition of order flow and use

this information to enhance price discovery. NYSE regulations, in turn, require the specialist to

maintain a fair and orderly market and stabilize prices more often that he would on his own. In

contrast, the privileges and obligations of the DLP are more modest in automated trading

systems. The DLP has no informational advantage over other traders and passively provides

liquidity by posting limit orders in the book. 3 In turn, he has no obligation to stabilize the market,

though he is required to maintain market presence by quoting prices. Given these differences and

the global trend towards automated order driven markets, an important question is whether a

DLP adds value in such a market structure?

To address this question, we study a sample of 19 firms of medium-to-high liquidity

(“Liquid”) and 37 firms of low liquidity (“Illiquid”) for which a DLP was introduced by the Paris

Bourse between 1995 and 1998. First, we conduct an event study to analyze cumulative

abnormal returns around the introduction of the DLP. The liquidity premium hypothesis (see

Amihud and Mendelson (1986)) predicts that improvements in market liquidity lower the risk-

adjusted return required by investors. 4 Therefore, if the DLP enhances market quality, then we

expect an increase in stock price around the event. Further, theoretical models (e.g., Grossman

and Miller (1988), Glosten (1989)) predict that the DLP’s role assumes greater prominence for

less liquid stocks. As less liquid stocks suffer from higher information asymmetry (see Easley et

3 Madhavan and Sofianos (1997) say “Besides occasionally acting as a dealer, the (NYSE) specialists also supervise

the trading process, match buyers and sellers, act as agents for other brokers, and exercise crowd control to ensure

price and time priority and efficient order representation.” In automated trading systems, all the above functions are

either unnecessary or have been assigned to the central computer.

4 Brennan and Subrahmanyam (1996), Eleswarapu (1997), and Brennan et al. (1998), among others, present

evidence of cross-sectional relationship between expected returns and firm liquidity. Amihud et al. (1997),

Muscarella and Piwowar (2001), and Kalay et al. (2002)) examine stocks that transferred from call to continuous

markets and also find empirical support for the liquidity hypothesis.

al (1996)), the ability of the DLP to average profits across trades, consistently provide liquidity,

and prevent market failure becomes more valuable. In support of these predictions, we find that

the introduction of the DLP has created positive value, on average, for our sample of Illiquid

firms but not for our sample of Liquid firms. We estimate cumulative abnormal returns (CAR)

over an event window that begins five days before the DLP announcement date and ends 10 days

after the stocks started trading with a DLP. For the Illiquid sample, we find a statistically

significant CAR of 4.4% during the event window; however, for the liquid sample, the CAR is

not different from zero.

Next, in order to identify those attributes that are enhanced by DLP participation, our

investigation examines changes in various measures of market quality. The DLP does not

enhance traditional market quality measures such as trading volume, market depth or executions

cost. However, DLP introduction is associated with significant reductions in the likelihood of

market failure for the Illiquid sample, providing strong empirical support for Glosten (1989).

Finally, in support of the liquidity premium hypothesis, our cross-sectional analysis finds that

firms that experienced a larger improvement in market quality after DLP introduction also

experienced larger CARs.

This study is also particularly well suited to test theoretical predictions on the differential

value of a DLP in electronic call and continuous markets. The Liquid sample in our study trade

in a continuous, electronic limit order market (ELOB), while the Illiquid sample trade in a twice-

daily electronic call market. Glosten (1994) predicts that a continuous ELOB inherently has the

ability to handle extreme adverse selection and prevent market failures – the benefit of a DLP,

therefore, is likely to be modest. Furthermore, Economides and Schwartz (1995) propose that an

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