Chordia, Roll And Subrahmanyam -Commonality In Liquidity.pdf

Journal of Financial Economics 56 (2000) 3}28

Commonality in liquidity q

Tarun Chordia

, Richard Roll

* ,

Avanidhar Subrahmanyam

! Owen School of Management, Vanderbilt University, Nashville, TN 37203, USA

" The Anderson School, University of California Los Angeles, Los Angeles, CA 90095-1481, USA

Received 8 August 1998; received in revised form 27 May 1999

Abstract

Traditionally and understandably, the microscope of market microstructure has

focused on attributes of single assets. Little theoretical attention and virtually no

empirical work has been devoted to common determinants of liquidity nor to their

empirical manifestation, correlated movements in liquidity. But a wider-angle lens

exposes an imposing image of commonality. Quoted spreads, quoted depth, and e!ective

spreads co-move with market- and industry-wide liquidity. After controlling for well-

known individual liquidity determinants, such as volatility, volume, and price, common

in#uences remain signi"cant and material. Recognizing the existence of commonality is

a key to uncovering some suggestive evidence that inventory risks and asymmetric

information both a!ect intertemporal changes in liquidity.

(

2000 Elsevier Science S.A.

JEL classi x cation: G23; D82

Keywords: Liquidity; Trading costs; Co-movement; Microstructure

q For comments, suggestions and encouragement, we are indebted to Viral Acharya, Cli!ord Ball,

Michael Brennan, Will Goetzmann, Roger Huang, Craig Lewis, Mike Long, Ron Masulis, Patrick

Panther, Geert Rouwenhorst, Lakshmanan Shivakumar, Hans Stoll, and seminar participants at

Arizona, Bocconi, INSEAD, Rice, and Yale. An anonymous referee and the editor (Bill Schwert)

provided constructive suggestions that greatly improved the paper. Christoph Schenzler provided

expert programming advice. The "rst author was supported by the Dean's Fund for Research and

the Financial Markets Research Center at Vanderbilt University.

* Corresponding author. Tel.: #1-310-825-6118; fax: #1-310-206-8404.

E-mail address: rroll@anderson.ucla.edu (R. Roll)

PII: S 0 3 0 4 - 4 0 5 X ( 9 9 ) 0 0 0 5 7 - 4

T. Chordia et al. / Journal of Financial Economics 56 (2000) 3 } 28

1. Introduction

The individual security is the traditional domain of market microstructure

research. Topics such as transactions costs and liquidity naturally pertain to the

repeated trading of a single homogeneous asset. Typically, we do not think of

such topics in a market-wide context, except perhaps as averages of individual

attributes.

From the earliest papers (Demsetz, 1968; Garman, 1976), the bid}ask spread

and other microstructure phenomena have been modeled with an isolated

market maker in the pivotal role, providing immediacy at a cost determined by

either inventory risks from a lack of diversi"cation (Stoll, 1978a; Amihud and

Mendelson, 1980; Grossman and Miller, 1988), or by the specter of asymmetric

information (Copeland and Galai, 1983; Glosten and Milgrom, 1985). Privileged

information has pertained to an individual stock, the insider serving as proto-

type privilegee (Kyle, 1985; Admati and P#eiderer, 1988).

Empirical work also deals solely with the trading patterns of individual assets,

most often equities sampled at high frequencies (Wood et al., 1985; Harris, 1991),

or examines micro questions such as the price impact of large trades (Kraus and

Stoll, 1972; Keim and Madhavan, 1996; Chan and Lakonishok, 1997). The

single-asset focus is exempli"ed by a prominent recent paper (Easley et al., 1997),

whose empirical work is devoted to a single common stock, Ashland Oil, on

thirty trading days.

Even articles devoted to market design (Garbade and Silber, 1979; Mad-

havan, 1992) examine the in#uence of various trading mechanisms solely on the

costs of individual transactions. Studies of topics such as intermarket competi-

tion, or the contrast between dealer and auction markets, yield predictions

about individual liquidity and transaction costs.

We do not imply even the slightest criticism. The microstructure literature has

indeed become a very impressive body of knowledge. But in this paper we aspire

to direct attention toward unexplored territory, the prospect that liquidity,

trading costs, and other individual microstructure phenomena have common

underlying determinants. A priori reasoning and, as it turns out, sound empiri-

cal evidence suggest that some portion of individual transaction costs covary

through time.

Since completing the "rst draft of this paper, two other working papers with

similar results have appeared; see Hasbrouck and Seppi (1998) and Huberman

and Halka (1999). Given the virtual absence of documented commonality in the

existing literature, this sudden #urry seems to portend a shift of emphasis from

individual assets to broader market determinants of liquidity.

1.1. Plausible reasons for the existence of commonality in liquidity

Commonality in liquidity could arise from several sources. Trading activity

generally displays market-wide intertemporal response to general price swings.

T. Chordia et al. / Journal of Financial Economics 56 (2000) 3 } 28

Since trading volume is a principal determinant of dealer inventory, its variation

seems likely to induce co-movements in optimal inventory levels which lead in

turn to co-movements in individual bid}ask spreads, quoted depth, and other

measures of liquidity. Across assets, inventory carrying costs must also co-move

because these costs depend on market interest rates.

The risk of maintaining inventory depends also on volatility, which could

have a market component. Program trading of simultaneous large orders might

exert common pressure on dealer inventories. Institutional funds with similar

investing styles might exhibit correlated trading patterns, thereby inducing

changes in inventory pressure across broad market sectors. Whatever the

source, if inventory #uctuations were correlated across individual assets, liquid-

ity could be expected to exhibit similar co-movement.

One might think that little covariation in liquidity would be induced by

asymmetric information because few traders possess privileged information

about broad market movements. In the prototypical case of a corporate insider,

privileged information is usually thought to pertain only to that speci"c cor-

poration. Indeed, this presumption would be valid for certain types of informa-

tion, such as fraudulent accounting statements. However, there might be other

types of secret information, such as a revolutionary new technology, that could

in#uence many "rms, not necessarily all in the same direction. Within an

industry, occasional occurrences of asymmetric information could a!ect many

"rms in that sector.

1.2. Implications of commonality

Covariation in liquidity and the associated co-movements in trading costs

have interesting rami"cations and pose immediate questions. A key research

issue is the relative importance of inventory and asymmetric information. Of

equal interest would be other potential sources of commonality, as yet unim-

agined. How are these causes themselves related to market incidents such as

crashes? Does their in#uence depend on market structure or design?

There are practical implications of the commonality issue for traders, inves-

tors, and regulators. For example, sudden pervasive changes in liquidity might

have played a key role in otherwise puzzling market episodes. During the

summer of 1998, the credit-sensitive bond market seemed to undergo a global

liquidity crisis. This event precipitated "nancial distress in certain highly

leveraged trading "rms which found themselves unable to liquidate some posi-

tions to pay lenders secured by other, seemingly unrelated positions.

1 See the Wall Street Journal (1998) &Illiquidity means it has become more di$cult to buy or sell

a given amount of any bond 2 The spread between prices at which investors will buy and sell has

widened, and the amounts [being traded] have shrunk across the board 2 ' (emphasis added).

Similarly,

the international stock market crash of October 1987 was associated with no

T. Chordia et al. / Journal of Financial Economics 56 (2000) 3 } 28

identi"able noteworthy event (Roll, 1988), yet was characterized by a ubiquitous

temporary reduction in liquidity.

Trading costs should be cross-sectionally related to expected returns before

costs simply because after-cost returns should be equilibrated in properly

functioning markets (Amihud and Mendelson, 1986; Brennan and Subrah-

manyam, 1996). But commonality in liquidity raises the additional issue of

whether shocks in trading costs constitute a source of non-diversi"able priced

risk. If covariation in trading costs is cannot be completely anticipated and has

a varying impact across individual securities, the more sensitive an asset is to

such shocks, the greater must be its expected return. Hence, there are potentially

two di!erent channels by which trading costs in#uence asset pricing, one static

and one dynamic: a static channel in#uencing average trading costs and a

dynamic channel in#uencing risk. In future work, it would be of interest

to determine whether the second channel is material and, if so, its relative

importance.

This paper is devoted mainly to documenting the commonality in liquidity,

measuring its extent, and providing some suggestive evidence about its sources.

However, the precise identi"cation of these sources remains for future research.

Section 2 describes the data. Section 3 reports a progression of empirical

"ndings about commonality in liquidity. Section 4 provides some interpreta-

tions, makes suggestions for additional empirical research, calls on theorists for

help, and concludes.

2. Data

and the

number of shares the specialist had guaranteed to trade at the bid and ask

quotes.

The data do not reveal the identities of buyer and seller, so one cannot tell for

sure when the specialist is involved nor on which side. However, since the

quoted spread is given, it seems reasonable to deduce that an outsider is usually

the buyer (seller) when the transaction price is nearer the ask (bid)

Some stocks are rarely traded and would not provide reliable observations.

To be included here, we require that a stock be continually listed throughout

2 Transactions are matched to best bid and o!er quotes that existed at least "ve seconds prior to

the transaction time because Lee and Ready (1991) "nd that quote reporting has about a 5 second

delay.

Transactions data for New York Exchange (NYSE) stocks were obtained

from the Institute for the Study of Securities Markets (ISSM) during the most

recently available calendar year, 1992. The ISSM data include every transaction,

time-stamped, along with the transaction price, the shares exchanged, the

nearest preceding bid and ask prices quoted by the NYSE specialist,

T. Chordia et al. / Journal of Financial Economics 56 (2000) 3 } 28

The number of transactions is, of course, extremely

right-skewed; the largest stocks have thousands of daily trades.

Corresponding to every transaction, "ve di!erent liquidity measures are

computed: the quoted and e!ective bid}ask spreads, the proportional quoted

and e!ective spreads, and quoted depth. Their acronyms and de"nitions are

given in the "rst panel of Table 1.

The quoted spread and the depth are announced by the specialist and become

known to other traders prior to each transaction, though the lead time may be

only seconds. The e!ective spread is devised to measure actual trading costs,

recognizing that (a) many trades occur within the quoted spread and (b) if the

proposed transaction exceeds the quoted depth, NYSE specialists are allowed,

though not obliged, to execute that portion of the order in excess of the quoted

depth at an altered price.

To smooth out intraday peculiarities and thus to promote greater synchrone-

ity, and to reduce our data to more manageable levels, each liquidity measure is

averaged across all daily trades for each stock. Thus, for each of the 1169 stocks,

the working sample consists of at most 254 observations, one for each trading

day during the year. Table 1 presents summary statistics for the "ve liquidity

measures.

As would be anticipated, there is some right skewness in the cross-section of

daily average spreads; sample means exceed medians. The e!ective spread is

3 Since the available data cover only a single calendar year, there is always the possibility that our

results are not representative. We have no reason to suspect that 1992 data are peculiar but an

extended time period would be reassuring.

1992 on the NYSE, trading at least once on at least ten trading days that year.

To circumvent any possible problems with trading units, stocks are excluded if

they split or paid a stock dividend during the year. Because their trading

characteristics might di!er from ordinary equities, we also expunge assets in the

following categories: certi"cates, American depository receipts, shares of bene"-

cial interest, units, companies incorporated outside the U.S., Americus Trust

components, closed-end funds, and real estate investment trusts; 1169 individual

unalloyed equities remain.

There are 29,655,629 transactions in the 1169 stocks on the 254 trading days

during 1992. Not all stocks traded every day. To avoid any contaminating

in#uence of the minimum tick size, we delete a stock on a day its average price

falls below $2. Opening batch trades and transactions with special settlement

conditions are excluded because they di!er from normal trades and might be

subject to distinct liquidity considerations. For obvious reasons, transactions

reported out of sequence or after closing are not used. After all this "ltering,

289,612(296,926"1169(254) total stock-days remain, an average of 102.4

transactions per stock-day or about 99.9 transactions averaged over the 1169

stocks and 254 trading days. All but 13 of the 1169 stocks have transactions on

more than 100 days.

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