Download Study on Financial Market Segmentation in China: Evidence from Stock Market

EASTERN ACADEMIC FORUM
Study on Financial Market Segmentation in China: Evidence from
Stock Market
WANG Xiaoyan1, HU Debao2
1. School of Business, Renmin University of China, Beijing, China, 100872
2. International College, Renmin University of China, Beijing, China, 100872
[email protected]
Abstract: Under the background of transitional Economy, as the incompleteness of Chinese market
system, there are market segmentation problems in financial market. We make use of information
asymmetry hypothesis, liquidity diversity hypothesis to build a model to analyze the main factors
causing segmentation. Sample data from 2004 to 2009 was used to make an empirical analysis, and the
result shows that the segmentation is complex, mainly affected by risk preferences, liquidity diversity,
information asymmetry, while the differences of demand and supply do not have a significant effect on
it.
Keywords: Market segmentation, Financial market, Risk preference, Information asymmetry
1 Introduction
The premises of traditional classical economics are complete competition and complete information.
However, incomplete competition and asymmetric information is the ordinary state in economy. Under
the background of transitional economy, China is transferring form planned economy to market economy,
and the competition is insufficient because of path dependence, so it causes market failure. Market
segmentation is a specific reflection of incomplete competition and market failure. Market segmentation
means the price discrimination of the same resource or price gap between factors in different markets,
which caused by the market's direct or indirect barriers, and despite the cross-market arbitrage
opportunities exists, but can not be fulfilled.
Since China's stock market was established in early 1990s, Chinese government had a strict foreign
exchange regulation system. Domestic investors can not invest in foreign capital markets, while foreign
investors can not invest in the domestic capital markets either. Although there were domestic opening of
B shares, implementation of the QFII and QDII system, however the volume of trade is too small to
eliminate the split between domestic and foreign markets fundamentally. Therefore, price differentials
between A share market and H share market can not be alleviated or eliminated by arbitrage activities.
In China's capital market segmentation, the price of the Hong Kong-listed H-shares for foreign investors
is lower than the price of A-shares in the main market for domestic investors, which is different from the
rest of the world, which have similar arrangements for market segmentation. The special case of China's
financial market segmentation has drawn attention of many economists’ interest over these years. Now
we use the latest stock market data from 2004 to 2011 to build econometric models, to make an empirical
analysis of the factors affecting the gap between A shares’ and H shares' partition.
2 Theoretical Analysis of Market Segmentation
In market segmentation, there are four explanatory theories on premium (discount) of different shares:
2.1 Risk preferences
Investor risk aversion can be measured with the Beta value, according to CAPM theory, the higher Beta
value is, the higher the cost of capital is, and the higher the expected rate of return by investors is, but the
stock prices is lower.
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In the theoretical analysis, the risk is usually measured by the standard deviation of returns. Here, we'll
use the ratio of the standard deviation of stock returns, as the proxy variable of differences in risk
A
H
preferences, namely,  /  .
2.2 Liquidity diversity
Because of the market segmentation between A shares and H shares, the capital can't flow free between
the two markets, this will certainly result in differences in the two markets liquidity. The transaction cost
is lower in the market with better liquidity, so investors will have a relatively lower expected rate of
return. We can see from the dividend discount model, the lower the expected rate of return is, the higher
the stock prices are.
In the theoretical analysis, there are two kinds of proxy variables of liquidity diversity: relative trading
A
H
volume and relative turnover. Here, we chose the ratio of relative trading volume V / V as one of the
explanatory variables of discount rate.
2.3 The differences of market demand and supply
If the two markets are separated, there are inevitable differences of their investors' demand elasticity
(Chen, Lee and Rui, 2001). In China, the financial market in Hongkong is much more developed than in
the mainland, the financial products for H-shares investors is much more, so the demand elasticity of
H-shares investors is necessarily greater than A-shares investors'. So, A-shares investors in the mainland
are forced to accept a smaller risk premium, and A-shares prices are pushed up, leads to a discount
between A-shares and H-shares.
In fact, in the stock market, the differences driven by the supply or demand are not obvious in equilibrium.
The numbers of circulating capital in the markets are often determined by the supplies of the listed
companies rather than the needs of investors. Therefore, the impact to the discount by the differences of
market demand is investigated. In the theoretical analysis, the circulating capital is usually used, but
unfortunately not all samples of the circulating equity are collected, so, the ratio of total equity of A
shares and H shares are used to be proxy variables of the differences of market supply, namely,
TE A / TE H .
2.4 Information asymmetry
Information asymmetry reflects that some participants have but other participants don't have the
information. Because the influence factors of factor prices are complex, generally the buyer has less
information and is impossible to understand the complexity of the formation of the stock price, while the
seller can use the advantage information to interrupt the judgment standard of the buyer in order to
achieve more revenue. In the panel regression analysis, we can use the capitalization degree of listed
companies as a proxy variable of the information asymmetry. The higher the capitalization degree is, and
the bigger the company is, the company's governance structure, internal control system and information
disclosure system will be better, and the degree of information asymmetry is lower. Thus, the total equity
is one of the explanatory variables in the analysis.
3 Empirical Analysis
By the end of 2011, a total of 61 companies at the same time had listed on A-shares and H-shares market.
In the procedure of data processing, 5 companies were eliminated because of relatively too small data
sample volumes, the remaining 56 companies were left as samples of this research.
This paper selected the sample companies' A and H shares data of six years from January 1, 2004 to
December 31, 2011. Where, A-shares data is from Wind Info., H-shares data is from BLOOMBERG, the
exchange rate about HK dollars into RMB is from the GTA financial database CSMAR. As the amount of
data is too numerous, they won't be listed here. The data obtained, including capital of A-shares and
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H-shares, the stock price, trading volume, market capitalization, etc. in each trading day, and through
calculation, we can get the discount rate, the rate of return and its standard deviation, etc.
The discount rate is defined as:
PA  PH E
DISRit  it A it t
P it
The rate of return is defined as:
 P Ait  Dit   1 H  PHit  Dit E t 
R A it 
R it 
1
P A i(t 1)
P H i(t 1)
,
, i=1,2,3,...56
Which,
P A it
and
P H it
denote respectively the last settlement prices of A-shares and H-shares of
D
company i, at the time of t, it is the dividend at the time of t, RMB-denominated, and Et is the
exchange rate of HK dollars into RMB at the time of t.
When calculating the rate of return, considering the impact of stock splits and dividends paid on the stock
price, the stock right price with the forward answer authority pattern was used. And the H-shares price
was exchanged into the price RMB-denominated.
When analyzing the impact factors of the discount caused by market segmentation in A shares and H
shares, as sectional data and time series data were both involved, therefore, we chose the panel data
analysis method. The panel data analysis method is combination of cross-sectional data analysis methods
and time series analysis method, relative to a single cross-sectional data analysis methods and time series
analysis, panel data analysis can more accurately capture the complex behavior of the object, and the
panel data calculations and statistical inference are easier.
Then use the panel data analysis, with the PLS (Pooled Least Square) econometric method used the
models used are as follows:
A
A
 Ait
V it
TE it
DISRit  c 0  c1 * DISRi (t  1)  c 2 * H  c3 * H  c 4 * H  c5 * SIZEit   it
 it
V it
TE it
Where:
P A it  P H it E t
P A it
1.
denotes the discount rate of H-shares to A-shares, using D as a simplified
representation in the panel data analysis;
P A i(t-1)  P H i(t-1) E (t-1)
DISRi (t  1) 
P A i(t-1)
2.
denotes the discount rate lag 1 period, to measure the first-order
autocorrelation of itself, using T as a simplified representation in the panel data analysis;
DISRit 
3.  it /  it denotes the ratio of the standard deviation monthly of daily rate of return of as the proxy
variable of differences in risk preferences, using T as a simplified representation in the data processing;
A
H
4. V it / V it denotes the ratio of daily average trading volume of A shares and H shares in each month,
A
H
as the proxy variable of liquidity diversity, using V as a simplified representation;
A
H
TE it / TE it
5.
denotes the ratio of total equity of A shares and H shares, as the proxy variable of the
differences of market supply, using Q as a simplified representation;
6. SIZEit denotes the total equity of the company i at the end of each month, as the proxy variable of the
information symmetry, as its magnitude is much bigger than previous parameters, calculate them with
logarithm, and the results are simplified represented as S;
7.  it is the random disturbance term.
Then, the formula above could be simplified into:
D  c0  c1T  c2W  c3V  c4Q  c5S  
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4 The Results of Empirical Analysis
Compile the cross-sectional data into Eviews5.0, the obtained results by PLS estimation are as follows:
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
2.903246
0.418245
6.941496
0.0000
T
0.867892
0.010574
82.07793
0.0000
W
-0.009132
0.003395
-2.68984
0.0054
V
0.001189
0.000492
2.416667
0.0063
Q
0.009813
0.006395
1.53448
0.1358
S
-0.128431
0.019721
-6.5124
0.0000
Effects Specification
Cross-section fixed (dummy variables)
R-squared
0.920189
Mean dependent var
0.383219
Adjusted R-squared
0.918957
S.D. dependent var
0.296543
S.E. of regression
0.084397
Akaike info criterion
-2.042514
Sum squared resid
20.35976
Schwarz criterion
-1.925316
Log likelihood
2899.329
F-statistic
464.6876
Durbin-Watson stat
2.149532
Prob(F-statistic)
0.000000
From the table above, we can see, the adjusted R2 equals to 0.9101, it shows a very high goodness of fit,
the weighted equation fit very well. All variables have passed the significance test except Q.
Eliminate Q, adjust the model as follows:
D  c 0  c1T  c 2W  c3V  c 4 S  
Use PLS estimation again, and the results are as follows:
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
2.435671
0.332158
7.332869
0.0000
T
0.846719
0.011046
76.6539
0.0000
W
-0.009479
0.003177
-2.98363
0.0043
V
0.001569
0.000407
3.855037
0.0052
S
-0.113974
0.015452
-7.376
0.0000
Effects Specification
Cross-section fixed (dummy variables)
R-squared
0.924016
Mean dependent var
0.383709
Adjusted R-squared
0.910178
S.D. dependent var
0.289479
S.E. of regression
0.087489
Akaike info criterion
-2.083295
Sum squared resid
20.28437
Schwarz criterion
-1.964614
Log likelihood
2898.173
F-statistic
469.9892
Durbin-Watson stat
2.164312
Prob(F-statistic)
0.000000
In the adjusted model, adjusted R2 equals to 0.9101, it still shows a very high goodness of fit. All
variables have passed the significance test. The p value of significance of F test equals 0.0000. The
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equation marked the establishment at a very high level of confidence, can be used for economic
interpretation.
We can get the new estimation model:
D  2.4357  0.8467T  0.0095W  0.0016V  0.1140S Namely:
DISRit  2.4357  0.8467 DISRi ( t  1)  0.0095
0.0016
V
V
 Ait
 H it
A
it
H
 0.1140 SIZEit
it
5 Conclusion
The results show that:
1. The first-order lag of the discount rate is significantly positive, indicating the discount rate has a strong
first-order autocorrelation.
2. The regression coefficient of proxy variable which describes the differences of risk preferences is
significantly negative. It means that the greater the standard deviation of stock A's rate of return is, the
smaller the standard deviation of stock H's rate of returns is, and the smaller discount rate is.
This means the investors in the mainland are more risk preference, their behavior of speculation is heavier.
For the investors' speculation in the mainland stock market pushed up prices of A shares, A-share prices
is higher than H-shares to the same listed company.
On the other hand, it shows financial market in the Mainland of China is unmature, where are so few the
investment products for investors to choose, which forcing the mainland investors to accept a lower risk
premium. And which also lead to the system risk of the mainland stock market increased, makes it easy to
boom and crash. Previously, stock market crashed from the non-rational historical high of 6124 points to
less than 2000 points, which is a case to prove. Whereas in Hong Kong stock market, after years of
development and historical lessons, have cultivated much more rational investors, which cause the price
difference between A-shares and H-shares.
3. The coefficient of proxy variable which represents the market liquidity diversity is significantly
positive.
Liquidity is a key property of portfolio, which greatly affects the pricing of assets. Usually, stock with a
worse liquidity must have higher expected profit to compensate investors for the increased transaction
costs, therefore, the lower the transaction costs are, the higher the price of the stock with better liquidity is.
Consider the liquidity of A-shares and H-shares, because fewer opportunities for domestic investment to
choose, A-shares is the main investment product to domestic investors, its liquidity is strong; while
H-shares is only one of the many choices for international investors, and the holders of H-shares will face
a certain degree of inventory risk and adverse selection risk, its liquidity is weak. So the investors holding
H-shares will require an additional compensation earnings for the weak liquidity, and the price of
H-shares is lower.
4. The coefficient of proxy variable of information asymmetry is negative, which proves the affection of
information asymmetry to the discount of H-shares.
As we know, the housing market has its own operation principle, if the developers will fully open
commercial secret information of the quality and cost to the public, meanwhile, they accordingly limit
price, then it won't work, which will increase the difficulty of the actual operation of the market.
Therefore, for housing price failure problems of information asymmetry, I think that the feasible method
is to encourage economic regulation, but not directly limit the house price, severely punish illegal
enterprise on prices fraud in the asymmetric information in the regulations.
It indicates that the bigger company's corporate governance mechanisms, information disclosure system
are better, the difference between A shares and H shares is smaller, and the smaller company acts worse
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in this regard. We can conclude that asymmetric information may make the stock market coincidence in a
failure state. At the same time, arbitrage cannot ease it fully, so the government should firmly put
economic regulation to reduce problems by trading information asymmetry. Of course, the purpose of
government economy market regulation is to protect the market environment, to maintain the normal
market economy order. At present, which way the government should take to have market regulation to
reduce information asymmetry is still in dispute, especially the regulation tool of price limits. Soon Huat
Chan and Kenneth A. Kim (2005) stated price limits tool will reduce market uncertainty and irrational
through the price barriers, when irrational prices reached the limit point from the perspective of
performance. They found that price limit does not reduce market information asymmetry, can't improve
market efficiency, but increases the cost, so they suggest the government should reduce the economic
regulation by price limit in the information asymmetry market.
The effects of information asymmetry are mainly reflected in the following two aspects: (1) As
enterprises' registered and operating places are in the Mainland generally, Mainland investors have more
sources of information, through various informal channels to obtain a variety of information about listed
companies, and even get information prior to the public disclosure, enabling stock price manipulation and
insider trading rampant in A stock market. (2) As closer to information sources, Mainland investors can
usually get the information earlier, it's a disadvantage for H-shares investors. On the whole, domestic
investors' ability to access the information is much stronger than foreign investors, to access the
information of the same listed company, H-shares investors are at a disadvantaged position, and they are
only willing to pay a lower price to get a higher rate of return, resulting in a relatively A shares and H
shares discount, and the greater the degree of information asymmetry, the greater the discount.
Whereas the previous relevant studies suggest that foreign investors have more information superiority.
As Chui and Kwok (1998) considered that because of the Government's control to the mass media, the
foreign investors have more advanced information access and information analysis technology, and listed
companies are required to have more stringent information disclosure to foreign investors. And for other
reasons, foreign investors have more information superiority than the domestic investors. In the empirical
results, this view is not supported.
5. The ratio of total equity of A shares and H shares is as proxy variable of the supply differences, its
coefficient is positive, but not significant. So we can't say that the supply differences between A shares
and H shares can affect the discount.
According to panel data analysis, the factors that may affect the discount of H-shares are studied. The
complete 6 years market data of A shares and H shares from January 1, 2004 to December 31, 2011,
including a variety of conditions of stock market in both mainland and Hongkong, such as flat growth,
booms and crashes, slowly recovering. Thus, the empirical result model has a very strong economic
significance explaining the reality, it won’t be affected by noise of a particular market period.
The empirical analysis result proved that, the discount of H-shares is mainly affected by three factors: risk
preferences, liquidity diversity, information symmetry. And the differences of the market demand (supply)
don't have a significant impact on the discount. Of course, the ideal proxy variable of the difference
between demand and supply is the circulating equity, due to not collected data in this regard. Our research
adopts the total share capital of the corresponding periods as its proxy variables. There may be some error
due to restricted shares. And whether after eliminating the impact of restricted shares, we can get the
results that the differences of the market demand (supply) can significantly impact the discount, it
remains to be further studied.
Author Information:
Wang Xiaoyan: School of Business, Renmin University of China; Research interests: consumer
behavior Cell phone: +86 18618486942; Address: Room 901, Mingde Business Building, Renmin
University of China, Haidian District, Beijing, PRC; Zip code: 100872.
Email: [email protected]
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Hu Debao: lecturer, International College, Renmin University of China; Research interests: industrial
organization, consumer economics; Cell phone: +86 15120006853; Address: Room 536, Pinyuan No.3
Building, Renmin University of China, Haidian District, Beijing, PRC; Zip code: 100872.
Email: [email protected]
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