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Stock Market Liquidity and
Country Fundamentals
Ser-Huang Poon
Michael Rockinger
Konstantinos Stathopoulos
1
Risk Management Consideration
n
Liquidity adj-VaR  VaR    i  12 si 
i 1
n is the number of positions
 i is the dollar investment in ith position
si is the percentage bid-ask spread
n is not the problem but  i 1 i is
n
si is potentially a function of  i
Instead of spread, one could use price impact also.
2
Amihud (2002)
Illiquid if price impact is high:
ILi ,t 
ILm ,t
Ri ,t
$volumei ,t
1

Mt
Mt
 IL
i 1
i ,t
ln  PI i ,t  Voli ,t       trend   i ,t
 i ,t
$volumei ,t  exp 

 



3
What drives liquidity (in different countries)?
• Country fundamentals
• Computer technology, automated trading
• Liquidity funding management and territory of
operation
• Risk regulations and territorial divide
4
Liquidity Black Hole
• Liquidity dries up during sell-off and asset can
be sold only at a fire-sale price (price decline
scenario).
• Computer models used by different traders
are similar.
• Financial institutions are regulated in the
same way and respond the same way to
changes in volatility and correlation.
• Herding
• Liquidity funding management
5
“Amihud’s email”
• Volatility of economic variables
• Legal variables
• Country economic variables
6
Legal Variables
• Legal origin
• Financial regulation
- Insider trading and other laws
• Enforcement variables
7
Volatility of Economic Variables
• Volatility of industrial production or other
index of economic activity
• Volatility of monetary variables
- Various definition of money
- Interest rate
8
Country Economic Variables
• Per capita income, growth, new investment,
new firms
• Investment by individuals (India, China)
• Institution’s activity (% managed by funds)
• Market cap compared to economy
• Measure of float(???), in some countries, the
market float is large but the float is small.
9
Capital Market Governance
Daouk, Lee and Ng (2006, JCF)
• CMG index
• Earnings opacity
• Enforcement of insider laws,
• Removal of short selling restrictions
• Performance
• Low cost of equity
• High liquidity
• Efficient pricing
10
11
12
Capital Market Governance
Daouk, Lee and Ng (2006, JCF)
• 32 countries; Not focus on “crisis”
• Good governance
=> good performance
=> liquidity
• Not focus on “crisis”
13
Sample: 37 Stock Markets 1996-2007
Europe
Austria
Belgium
France
Germany
Italy
Portugal
Switzerland
UK
SE. Asia
HK
Indonesia
Japan
Korea
Malaysia
Philippine
Singapore
Taiwan
Thailand
Latin
Argentina
Chile
Colombia
Mexico
Peru
Venezuela
E.Europe
Czech
Poland
Russia?
Turkey?
Scandinavian
Denmark
Finland
Norway
Sweden
Others
Australia
China
India
Israel
South Africa
14
Illiquidity Measure 1
Indonesia
Philippines
India
HK
Germany
SouthAfrica
Mexico
Singapore
Thailand
Korea
Israel
Malaysia
Poland
Australia
Argentina
USA
Japan
Sweden
Turkey
Norway
Portugal
Finland
UK
Denmark
Peru
France
Taiwan
Czech
Switzerland
Chile
Belgium
China
Italy
Austria
Russia
Colombia
Venezuela
0
5
10
15
20
25
30
35
40
15
Illiquidity Measure 2
Philippines
Indonesia
India
Germany
USA
Israel
HK
Japan
SouthAfrica
Argentina
Korea
Australia
Singapore
Thailand
Turkey
Malaysia
Sweden
Mexico
Finland
Portugal
Switzerland
France
Denmark
Norway
Peru
Belgium
Taiwan
UK
China
Poland
Italy
Austria
Czech
Chile
Russia
Colombia
Venezuela
0
1
2
3
4
5
6
7
8
16
Illiquidity Measure 3
Colombia
UK
Chile
Mexico
Peru
Venezuela
Russia
Czech
Philippines
Argentina
Germany
SouthAfrica
Portugal
Norway
Austria
Denmark
Belgium
Indonesia
Sweden
Thailand
USA
France
Switzerland
Finland
Australia
Israel
India
Italy
HK
Singapore
Malaysia
Poland
Japan
Korea
Turkey
Taiwan
China
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
17
Regional Illiquidity Measures (Mean)
14
12
IL1
IL2
IL3
10
8
6
4
2
0
Latin
Europe
Scandinavian
Asia
USA
18
Illiquidity Measures (Mean) by Legal Origin
9
8
IL1
IL2
IL3
7
6
5
4
3
2
1
0
Scandinavian
German
French
English
19
Rank correlation
Volatility of economic variables
M2
Real IR
IR spread
FDI
Unemploy
GDP
GDPgrowth
M2/GDP
CPI
LT Unemploy
StockTO
StockValTraded
IL3
IL2
IL1
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
20
Rank correlation
Market Characteristics & Economic variables
StockTO
Listed
StockValTraded
Listed
GDP growth
CPI
NewBuss
M2/GDP
FDI
LT Unemploy
GDP
Corruption
Real IR
IR spread
GINI
Unemployed
M2
IL3
IL2
IL1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
21
Rank correlation
Legal variables
Top10 TO
Top10 Cap
Own Conc
Pub Enforce
Anti Dir
Prospect Liab
Tax Evas
ListedCo/pop
MktCap/GDP
Anti SelfDeal
Disclosure
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
22
Rank correlation
Deouk et. al. variables for capital market governance
Volatility
Syncronicity
IPO return
Expected Ret
IL3
IL2
IL1
EarnOpac
Vol/Cap
US/MktCap
CMG Index
Cost of Equity
MktDepth
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
23
Regional Illiquidity Measures
24
Liquidity & the 1987 Crash
Amihud (1990, JPM)
Period I: Oct5-Oct9,
Period II: Oct19,
Period III: Oct30
Pt
Pt m
$spreadt
ln
  ln m   0  1
 2
Pt 1
Pt 1
$spreadt 1
$spread  I 

i
$spread  I 

Period II (t) vs. Period I (t-1)
Period III (t) vs. Period II (t-1)
25
Liquidity & the 1987 Crash
Amihud (1990, JPM)
• Stocks that experienced a greater increase in
bid-ask spread suffer a greater price decline
during the crash => liquidity is a price factor
• Alpha2 is insignificant during the crash (II vs.
I) but significantly negative afterwards (III vs.
II) => flight to quality
• By the end of 1987, spread had narrowed but
remained higher than before Oct =>
persistence
26
To Do List:
• Compare CRSP-NYSE vs. NASDAC
• Study spread on e.g. Korea, Malaysia vs. US
• Riskmetrics’s individual company governance
scores
• More robust econometrics
• Managing liquidity-VaR
28