INTERNATIONAL STOCK MARKET LIQUIDITY
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree Doctor of Philosophy in the
Graduate School of The Ohio State University
By
Christof W. Stahel, M.A.
* * * * *
The Ohio State University
2004
Dissertation Committee:
Ren´e M. Stulz, Adviser
Kewei Hou
Ingrid M. Werner
Approved by
Adviser
Graduate Program in
Business Administration

ABSTRACT
This dissertation contributes to the international asset pricing literature. The
research it presents in its two essays is related to papers that investigate commonalities
in individual stock liquidity in the domestic US setting, to research that estimates
risk premia related to liquidity risk in the US, and to articles that explore properties
and determinants of market-wide liquidity in the US, while expanding the scope to
an international setting.
The first essay shows that individual liquidity exhibits commonalities in monthly
measures of individual stock liquidity within and across countries for a sample from
Japan, the UK, and the US from 1980 to 2001. An asset pricing analysis suggests
that expected stock returns are cross-sectionally related to the sensitivity of returns
to shocks in global liquidity in this sample and that global liquidity is a priced state

variable in an international framework at the portfolio as well as at the individual
stock level.
The second essay analyzes cross-regional and time-series properties of weekly
market-wide liquidity measures from 1990 to 2002 for five regional aggregates: de-
veloped Asia, North America, Europe, emerging Asia, and emerging America. The
aggregates are calculated from a sample that contains 39 developed and emerging
countries. The results suggest that liquidity shocks are contemporaneously corre-
lated and dynamically spread across regions. However, there is only week evidence
ii
that liquidity affects returns in this sample. An investigation of determinants of liq-
uidity indicates that market-wide returns, market-wide averages of individual stock
volatilities, and world net bond flows are fundamental drivers of market-wide liquid-
ity. There is little evidence that equity fund flows and interest rates consistently affect
liquidity in the sample.
Even though changes in liquidity can to some extent be explained by returns and
other determinants, shocks to liquidity continue to be contemporaneously correlated
across markets. But the empirical results from an application of extreme value theory
offers evidence that extreme shocks to liquidity are asymmetrically correlated in the
tail of the distribution. In particular, it is mostly negative extreme liquidity shocks
that are correlated between North America, Europe, and emerging America.
The overall conclusions from this dissertation are twofold. First, changes in global
liquidity constitutes an international risk factor, and financial assets with returns
that are more sensitive to this factor reward investors with higher expected returns.
However, the contribution of liquidity risk to expected returns seems to be more rele-
vant for developed markets. Second, market-wide liquidity is contemporaneously and
dynamically related across regions. Furthermore, these relationships do not simply
reflect other variables that are related across markets but constitute a phenomenon
by themselves.
iii
This dissertation is dedicated to the ones I miss and love.

iv
ACKNOWLEDGMENTS
I would like to thank my advisor Ren´e Stulz and my committee members Kewei
Hou and Ingrid Werner for their guidance, insightful feedback, and encouragement
that helped make this dissertation possible.
I also thank Tom Bates, Terry Campbell, Jeff Harris, Jean Helwege, David Hir-
shleifer, Roberto Ragozzino, and seminar participants at the University of Delaware,
Drexel University, George Mason University, HEC Montreal, The Ohio State Univer-
sity, Queen’s University, and Texas Tech University for helpful comments and sugges-
tions, and Laurie Pomerson for her help with too many versions of the manuscript.
v
VITA
June 25, 1964 . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Born – Z¨urich, Switzerland
1995 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .lic.oec.publ. – University of Z¨urich,
Switzerland
1997 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .M.A. Economics – The Ohio State Uni-
versity, USA
PUBLICATIONS
Research Publications
Michel Peytrignet and Christof W. Stahel, Stability of money demand in Switzerland:
A comparison of the M2 and M3 cases, Empirical Economics, 23:437–454, 1998.
FIELDS OF STUDY
Major Field: Business Administration
Concentration: Finance
vi
TABLE OF CONTENTS
Page
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Dedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Vita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
Chapters:
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 International Asset Pricing Models . . . . . . . . . . . . . . . . . . 2
1.2 Market Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 Capital Flows, Spillovers and Contagion . . . . . . . . . . . . . . . 5
1.4 Essay Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2. Is there a Global Liquidity Factor? . . . . . . . . . . . . . . . . . . . . . 11
2.1 Sample and Liquidity Measures . . . . . . . . . . . . . . . . . . . . 19
2.2 Commonalities in Liquidity . . . . . . . . . . . . . . . . . . . . . . 24
2.2.1 Contemporaneous Variation . . . . . . . . . . . . . . . . . . 24
2.2.2 Sources of Commonalities . . . . . . . . . . . . . . . . . . . 27
2.3 Asset Pricing Implications . . . . . . . . . . . . . . . . . . . . . . . 32
2.3.1 Liquidity Risk . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.3.2 Expected Returns and Trading Cost . . . . . . . . . . . . . 38
2.3.3 Stock Level Fama-MacBeth Regressions . . . . . . . . . . . 39
vii
2.4 Alternative Sample . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
2.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3. Are liquidity Shocks correlated across Equity Markets? . . . . . . . . . . 43
3.1 Sample and Liquidity Measure . . . . . . . . . . . . . . . . . . . . 48
3.1.1 Sample Properties . . . . . . . . . . . . . . . . . . . . . . . 51
3.2 Dynamic Transmission of Liquidity Shocks . . . . . . . . . . . . . . 52
3.3 Liquidity and Returns . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.4 Correlation of Extreme Liquidity Shocks . . . . . . . . . . . . . . . 61
3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
4. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

Appendices:
A. Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
B. Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
viii
LIST OF TABLES
Table Page
A.1 Liquidity Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
A.2 Commonality in Liquidity . . . . . . . . . . . . . . . . . . . . . . . . 80
A.3 Decomposition of Commonality . . . . . . . . . . . . . . . . . . . . . 81
A.4 Variance Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . 82
A.5 Liquidity Risk Premium - country and industry portfolios . . . . . . . 84
A.6 Liquidity Level and Return . . . . . . . . . . . . . . . . . . . . . . . . 85
A.7 Liquidity Risk Premium - size portfolios . . . . . . . . . . . . . . . . 86
A.8 Liquidity Risk Premium - country, industry, and size portfolios . . . . 87
A.9 Test of constant Risk Premiums . . . . . . . . . . . . . . . . . . . . . 88
A.10 Risk Premium and Liquidity as an Asset Characteristic . . . . . . . . 89
A.11 Fama-MacBeth Risk Premiums . . . . . . . . . . . . . . . . . . . . . 90
A.12 Commonalities and Decompositions - IPO . . . . . . . . . . . . . . . 91
A.13 Variance Decomposition - IPO . . . . . . . . . . . . . . . . . . . . . . 92
A.14 Liquidity Risk Premium - IPO . . . . . . . . . . . . . . . . . . . . . . 93
A.15 Sample Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
ix
A.16 Dynamic Transmission of Liquidity Shocks . . . . . . . . . . . . . . . 96
A.17 Granger-Causality Tests . . . . . . . . . . . . . . . . . . . . . . . . . 97
A.18 Correlation of Liquidity Shocks . . . . . . . . . . . . . . . . . . . . . 98
A.19 Liquidity Spillovers . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
A.20 Liquidity and Returns . . . . . . . . . . . . . . . . . . . . . . . . . . 101
A.21 Correlation of Liquidity Shocks and Return Shocks . . . . . . . . . . 106
A.22 Bivariate Peak Over Threshold Tail Correlations . . . . . . . . . . . . 107
x

LIST OF FIGURES
Figure Page
B.1 Changes in Market-wide Liquidity . . . . . . . . . . . . . . . . . . . . 109
B.2 Bivariate Peak Over Threshold Tail Correlations . . . . . . . . . . . . 110
xi
CHAPTER 1
INTRODUCTION
International capital flows steadily increased over the last couple of decades as
many financial markets opened their borders to foreign investors. For example, inter-
national portfolio investments have gradually grown from cumulative net flows into
Japan, the UK, and the US of about one billion US dollars in the 1980s to about two
billion US dollars in the 1990s. While most European and G-7 countries liberalized
their stock markets in the early 1970s, many emerging countries opened their markets
to foreign investors in the late 1980s and early 1990s.
1
This liberalization process allowed investors to extend their investment opportu-
nity set to include multiple markets. Markets are said to be integrated if assets are
traded at the same price regardless of where they are traded, and markets are said
to be segmented if an asset’s price depends on where it is traded. If markets are
integrated, all investors face the same investment opportunity set with no barriers to
international investment. In such world of integrated markets, expected returns on
risky assets are related to risk factors that are common to all markets.
1
See, for example, Kaminsky and Schmukler (2001).
1
The following sections survey the field of international asset pricing and offer a
bird’s-eye view of where this dissertation is embedded.
2
The survey is followed by a
brief outline and overview of the results of the two essays presented in chapter 2 and

chapter 3, and the final chapter offers some conclusions.
1.1 International Asset Pricing Models
The modeling of asset prices in a world of integrated financial markets depends
on the assumption of whether or not consumption opportunity sets of investors can
differ across countries. If consumption opportunity sets are the same for each investor,
markets are called perfect and the specific location of an investor does not matter when
maximizing life-time utility via an optimal investment portfolio choice. The law of
one price applied to international finance states that the domestic and foreign price of
a consumption good is proportional with the proportionality factor being the price of
foreign currency. If the law of one price holds across goods and countries, consumption
opportunity sets are equal across countries up to this common proportionality factor,
and the purchasing power parity of international finance holds. In such a world,
the location of an investor does not matter when he is translating future wealth
into consumption as the exchange rate adjusts accordingly to equate prices across
countries. Moreover, the returns on assets are related to risk factors which affect all
markets, and these factors can be viewed as common, global counterparts to factors in
domestic asset pricing models. In such a setting, the numerous models of asset pricing,
which have implicitly been developed for single markets, can simply be translated
into an international setting by viewing the extended investment opportunity set to
2
See the survey of the field of international finance by Karolyi and Stulz (2003b) and the compi-
lation of the most important work in the field by Karolyi and Stulz (2003a).
2
represent one global market. For example, in the simplest case of only one common
global risk factor, financial assets could be priced using a world version of the capital
asset pricing model (CAPM), where expected excess returns are proportional to the
expected excess return of the world market portfolio. The number and nature of the
risk factors is ultimately an empirical question, since theory does offer little guidance
in this respect.
There is a vast empirical literature investigating the performance of the world

CAPM and its multifactor extensions in unconditional and conditional forms for port-
folios and individual stocks. For example, tests of unconditional versions of the models
have been performed by Stehle (1977), Mark (1988), Harvey (1991), Chan, Karolyi,
and Stulz (1992), Fama and French (1998); and tests of conditional versions have
been carried out by Ferson and Harvey (1993, 1994, 1995, 1997) and Harvey (1995).
Overall, the evidence shows that portfolio risk premia can be explained by the covari-
ance of returns with the world market portfolio and that individual stock risk premia
can be explained by multifactor models with, for example, additional global size and
value-growth factors which resemble the domestic US factors proposed by Fama and
French (1993).
3
All of the above discussed models depend on purchasing power parity, but there is a
vast literature in international economics that casts strong doubts on the purchasing
power parity’s validity. This in turn implies that an investor’s evaluation of the
riskiness of an asset must depend on the specific location of the investor.
3
See also Griffin (2002), who decomposes the global factors into domestic and international
components and shows that the domestic component of the global value-growth factor is most
relevant.
3
Consider, for example, a riskless asset with a return denominated in a particular
currency. This asset is riskless for a domestic investor, but not for a foreign investor.
In such a world where consumption opportunity sets differ across countries, whenever
a domestic investor holds a foreign asset, the return in domestic currency depends on
the exchange rate and the investor faces exchange rate risk.
Solnik (1974), Sercu (1980), Stulz (1981a), Adler and Dumas (1983), and Solnik
(1983) derive asset pricing models in which foreign exchange rate risk is priced. The
research which empirically tests these pricing models, such as Jorion (1991), Dumas
and Solnik (1995), Santis and G´erard (1998), Dahlquist and Sallstrom (2002) finds
that foreign exchange rate risk is priced in international portfolios.

1.2 Market Integration
The integration of financial markets implies that investors who think that one
market offers higher expected returns over another market can move their funds to
that market. The enormous growth in cross-border net capital flow over the past three
decades offers testimony to the liberalization and integration of capital markets.
4
All of the international asset pricing models discussed so far rely on the assumption
that stock markets are integrated and investors can freely move their funds from
one country to another. However, there might exist a large number of direct and
indirect costs and barriers, such as foreign investment restrictions, legal constraints,
discriminatory taxes and higher investment cost, as well as psychological, cultural,
and behavioral aspects, that could segment markets and impede investors to take
4
For information on capital flows, see, for example, the Treasury International Capital Reporting
System from the US Treasury, and the World Economic and Financial Surveys from the International
Monetary Fund.
4
full advantage of international investment opportunities.
5
For example, Black (1974),
Stulz (1981b), Errunza and Losq (1985), and Eun and Janakiramanan (1986) directly
model the portfolio choice under the assumption of different levels of investment
barriers and restrictions on foreign ownership.
Most studies that investigate market integration work in an asset pricing frame-
work. They generally assume under the null hypothesis that expected returns are
generated by an international asset pricing model and under the alternative hypoth-
esis that expected returns are explained by pricing models related to segmented mar-
kets. These studies regularly cannot reject the assumption of market integration for
developed markets for the 1980s and 1990s. Even though explicit barriers mostly have
been removed for emerging markets, the extent to which the markets are integrated

into the world market depends ultimately on whether foreign investors actually in-
vest in these markets. There exists some empirical evidence in Bekaert and Harvey
(1995) and Foerster and Karolyi (1999), for example, which suggests that markets
are implicitly integrated, but with a degree that varies over time.
1.3 Capital Flows, Spillovers and Contagion
Given the evidence that most markets are integrated and risk premia are deter-
mined globally, it is natural to observe that stock prices around the world tend to
exhibit some comovement. There are a number of studies investigating the contem-
poraneous correlation among equity markets and lead and lag patterns in returns
and volatilities. While Longin and Solnik (1995) and Bekaert and Harvey (2000)
5
See Kaminsky and Schmukler (2001) for a comprehensive list of liberalization dates.
5
document general patterns and time-variation in international stock market correla-
tions, Eun and Shim (1989), Engle, Ito, and Lin (1990), and Hamao, Masulis, and Ng
(1990) document lead and lag effects across markets in returns as well as spillovers
in volatilities. However, linking the correlation patterns and spillovers to market and
economics factors has so far resulted in little significant evidence.
There is a growing literature in international finance that investigates the joint
dynamics of capital flows and asset returns. The basic question here is whether
flows reflect additional information of foreigners about changes in expected returns,
or whether flows impact returns themselves. As in Bohn and Tesar (1996), Seasholes
(2000), and Froot, O’Connell, and Seasholes (2001), for example, most of the results
suggest that foreign investors are feed-back traders – buying following positive re-
turns and selling following negative returns – and are worse informed than domestic
investors. However, Choe, Kho, and Stulz (1999) offer some evidence that this be-
havior of feedback trading weakened during the Korean crisis in the late 1990s, and,
hence, foreign investors are not to blame for enforcing the destabilization of markets
during crises periods.
One concern about comovements in returns and volatility spillovers is that such

cross-market relationships might at times be unwarranted by fundamentals in each
market. For example, Kaminsky, Lyons, and Schmukler (2000) demonstrate that
mutual funds engage in what they call contagion trading, that is selling in one mar-
ket when returns in another market are poor, and Edison and Warnock (2001) show
that portfolio flows to emerging markets depend little on the fundamentals of these
markets, but are related to US interest rates. The literature defines so called con-
tagion to be an increase in correlations among asset returns during periods of crises
6
beyond what fundamentals would suggest.
6
For example, Calvo and Reinhart (1996),
Frankel and Schmukler (1998), and Bailey, Chan, and Chung (2000) present evidence
that the correlation increased beyond fundamental determinants in the aftermath of
the Mexican crisis in 1994. Yet, Forbes and Rigobon (2002) caution that increased
volatilities around crises periods could falsely lead investigators to conclude that the
correlation increased as it might simply be the consequence of strong transmission
mechanisms that exist during more stable periods.
1.4 Essay Summary
Given the integration of financial markets and the large scale international port-
folio flows, it is a natural question to investigate the existence, nature, and impact
of market-wide liquidity in an international framework. The dissertation provides
empirical evidence in two related essays.
The market microstructure literature has extensively investigated how trading
activity, inventory costs, and market conditions affect liquidity – roughly speaking
the price concession an investor has to make to trade now versus tomorrow – and the
price formation process of individual securities. One central argument, originally put
forth by Amihud and Mendelson (1986), states that empirically observed asset prices
reflect liquidity costs, and assets that are less liquid are traded at a discount.
More recently, a number of studies have investigated whether liquidity consti-
tutes a risk factor in the pricing of financial assets (see, among others, Pastor and

Stambaugh 2003). They found for the US that unexpected market-wide changes in
liquidity constitutes a domestically priced risk factor.
6
See Claessens and Forbes (2002) and Karolyi (2003).
7
The first dissertation essay is presented in chapter 2. It is related to the above
discussed articles by employing three different international asset pricing models. In
particular, after identifying country, industry, and global commonalities in liquidity
of individual stocks, it analyzes the implication of such a global liquidity factor for the
pricing of financial assets in an international framework for a sample from the United
States, the United Kingdom, and Japan covering the period from 1980 to 2001.
The results for three different monthly liquidity measures — based on daily return
and trading volume data — suggest that individual stock liquidity exhibits commonal-
ities within countries and industries and co-moves globally. Furthermore, global and
country-specific commonalities dominate industry effects as the source of common
variation in liquidity.
The asset pricing analysis suggests that expected stock returns are cross-sectionally
related to the sensitivity of returns to shocks in global liquidity and that global liq-
uidity is a priced risk factor on the portfolio and the individual stock level. The
hypotheses that the liquidity risk premiums are equal across countries and industries
cannot be rejected. Moreover, the results are neither driven by time-varying levels
of asset-specific liquidity, nor by observations from recently listed firms, for which
liquidity and return processes are likely different.
The second dissertation essay is presented in chapter 3. It investigates the prop-
erties of changes in market-wide stock liquidity for a sample of weekly information
from 1990 to 2002 for five regional aggregates: Asia, Europe, North America, emerg-
ing Asia, and emerging America. The analysis is based on a measure that does not
rely on trading volume information, but only on return data. This is an important
8
difference with the measures used in chapter 2, since thin trading activities, which

might occur especially in emerging markets, biases the measures used in chapter 2.
The analysis of market-wide aggregates is important to better understand liquid-
ity. For example, to what extent can the same cross-market patterns discovered in
returns also be found in liquidity? Even though it is clear that changes in liquidity
affect the return of financial assets in developed markets, it is unclear how liquidity
is related across markets and returns, and what drives market-wide liquidity. Is the
cross-market relationship of liquidity simply reflecting a common underlying variable
or is it a phenomenon by itself?
The analysis offers evidence of significant cross-market relationships: liquidity
shocks are contemporaneously correlated; shocks from Asia dynamically spread into
North America and vice versa; shocks from Europe spread into Asia and vice versa;
shocks from North America spread into all regions; and shocks from emerging markets
are only transmitted between themselves. The investigation of volatility spillovers in
liquidity reveals that liquidity shocks in any market increase volatility of liquidity in
all other markets.
An analysis of the joint dynamic relationship of liquidity and market-wide returns
offers, however, only weak evidence that liquidity determines returns. But the results
suggest that changes in market valuations do affect liquidity, and market-wide aver-
ages of individual stock volatilities and world net bond flows are further fundamental
drivers of market-wide liquidity. Beyond these results, there is little evidence that
equity flows and interest rates affect liquidity consistently across markets.
Even though changes in liquidity can to some extent be explained by returns and
other determinants, shocks to liquidity continue to be contemporaneously correlated
9
across markets. However, the empirical results from an application of extreme value
theory offers evidence that extreme shocks to liquidity are asymmetrically correlated
in the tail of the distribution. In particular, mostly negative extreme liquidity shocks
are correlated between North America, Europe, and emerging America.
10
CHAPTER 2

IS THERE A GLOBAL LIQUIDITY FACTOR?
In this chapter, I address the question whether there exist commonalities in liq-
uidity in an international context, and whether they are country- or industry-specific
or of a global nature. Moreover, I analyze whether global liquidity is a priced risk
factor in an international framework. The analyses are based on a sample containing
daily observations from 1980 to 2001 for all stocks from the US, UK, and Japan.
The results from the investigation of commonalities suggest that individual stock
liquidity co-moves within countries and industries, as well as with global liquidity.
Furthermore, two separate analyses that are based on decompositions of the aggre-
gate measures show that a global and independent country factors dominate industry
effects as the source of common variation in liquidity. The asset pricing analysis
suggests that average stock returns are cross-sectionally related to the sensitivity of
returns to shocks in global liquidity, and that global liquidity risk is priced inter-
nationally at the portfolio and the individual stock level. Moreover, the hypothesis
that the liquidity risk premiums are equal across countries and industries cannot be
rejected. Additional results suggest that the cross-sectional relationship between av-
erage returns and shocks to liquidity is not driven by time-varying expected liquidity,
11
and the traditional view where assets with lower expected liquidity level command
higher expected returns finds some support.
The integration of capital markets over the last quarter of a century allowed in-
vestors to substantially improve the trade-off between risk and return. However, the
possibility to diversify beyond the domestic investment opportunity set also gave rise
to new and additional factors that determine the cross-sectional distribution of re-
turns. In integrated markets, assets are no longer priced in a domestic context but
rather relative to international risk factors. Cross-border capital flows and coordi-
nated monetary policies, both determinants of liquidity from a market microstructure
perspective, raise the question whether global liquidity constitutes such a risk factor.
To the extent that individual stock liquidity is driven by a common underlying factor,
shocks to this factor generate market-wide effects, and if asset returns and market-

wide liquidity are correlated, the source of common liquidity effects could constitute
a non-diversifiable risk factor for which investors might demand a risk premium for
bearing this risk.
International commonalities in liquidity could arise from several sources. Gross-
man and Miller (1988) point out that market liquidity of an individual asset is the
result of the interaction of a market making sector that balances the expected net
return from offering immediacy for an asset and the demand of investors to trade now
versus tomorrow. The market microstructure literature has extensively investigated
how order flow and trading volume affect liquidity and the price formation process
of individual securities focusing on two paradigms: the level of inventory cost for
immediacy suppliers; and the degree of asymmetric information among market par-
ticipants. Therefore, common factors that determine inventory cost and level across
12
many assets may induce international commonalities in liquidity through correlations
in the supply of immediacy. For example, a dealer’s inventory level is directly related
to trading volume which in turn is, at least partially, determined by international
portfolio flows. Moreover, global factors that influence price volatilities and interest
rates determine the cost of maintaining a market. Demand for immediacy, on the
other hand, is related to portfolio decisions. If, for example, investors reallocate port-
folios after a common shock to asset prices or interest rates, international liquidity
effects could arise. Or, if asset values in one market experienced a negative shock
and investors are required to satisfy margin calls they might rather liquidate assets
with non-depressed values in another markets and hence create cross-border liquidity
effects. However, there are not only rational explanations for time-varying liquidity.
For example, Baker and Stein (2002) argue that irrational investors underreacting to
information contained in order flow, induce a lower price impact and thereby boost
liquidity in general. This implies, under short-sales constraints, that higher levels of
liquidity can be associated with positive investor sentiments on the individual stock,
or on the aggregate level.
Whatever the underlying sources are, if individual stock liquidity is correlated

across assets, commonalities may constitute a non-diversifiable and priced risk factor.
The traditional view of liquidity as an asset specific issue, put forth by Amihud and
Mendelson (1986), is that the risk adjusted expected return is related to the expected
level of liquidity. For example, in order to induce an investor to hold an asset that
is on average more difficult to resell, the seller has to offer a price concession, and
such expected transaction costs are factored into the prices when assets are traded.
Thus, the observed relative price changes are simply gross returns. But what about
13